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The Social Consequences of Poverty: An Empirical Test on Longitudinal Data

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• Published: 17 May 2015
• Volume 127 , pages 633–652, ( 2016 )

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• Carina Mood 1 , 2 &
• Jan O. Jonsson 1 , 2 , 3  

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An Erratum to this article was published on 22 July 2015

Poverty is commonly defined as a lack of economic resources that has negative social consequences, but surprisingly little is known about the importance of economic hardship for social outcomes. This article offers an empirical investigation into this issue. We apply panel data methods on longitudinal data from the Swedish Level-of-Living Survey 2000 and 2010 (n = 3089) to study whether poverty affects four social outcomes—close social relations (social support), other social relations (friends and relatives), political participation, and activity in organizations. We also compare these effects across five different poverty indicators. Our main conclusion is that poverty in general has negative effects on social life. It has more harmful effects for relations with friends and relatives than for social support; and more for political participation than organizational activity. The poverty indicator that shows the greatest impact is material deprivation (lack of cash margin), while the most prevalent poverty indicators—absolute income poverty, and especially relative income poverty—appear to have the least effect on social outcomes.

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1 Introduction

According to the most influential definitions, poverty is seen as a lack of economic resources that have negative social consequences—this is in fact a view that dominates current theories of poverty (Townsend 1979 ; Sen 1983 ; UN 1995 ), and also has a long heritage (Smith 1776 /1976). The idea is that even when people have food, clothes, and shelter, economic problems lead to a deterioration of social relations and participation. Being poor is about not being able to partake in society on equal terms with others, and therefore in the long run being excluded by fellow citizens or withdrawing from social and civic life because of a lack of economic resources, typically in combination with the concomitant shame of not being able to live a life like them (e.g., Sen 1983 ). Economic hardship affects the standard of life, consumption patterns, and leisure time activities, and this is directly or indirectly related to the possibility of making or maintaining friends or acquaintances: poverty is revealed by not having appropriate clothes, or a car; by not being able to afford vacation trips, visits to the restaurant, or hosting dinner parties (e.g., Mack and Lansley 1985 ; Callan et al. 1993 )—in short, low incomes prevent the poor from living a life in “decency” (Galbraith 1958 ).

The relational nature of poverty is also central to the social exclusion literature, which puts poverty in a larger perspective of multiple disadvantages and their interrelationships (Hills et al. 2002 , Rodgers et al. 1995 ; Room 1995 ). While there are different definitions of the social exclusion concept, the literature is characterized by a move from distributional to relational concerns (Gore 1995 ) and by an emphasis on the importance of social integration and active participation in public life. The inability of living a decent or “ordinary” social life may in this perspective erode social networks, social relations, and social participation, potentially setting off a downward spiral of misfortune (Paugam 1995 ) reinforcing disadvantages in several domains of life. This perspective on poverty and social exclusion is essentially sociological: the playing field of the private economy is social. It is ultimately about individuals’ relations with other people—not only primary social relations, with kin and friends, but extending to secondary relations reflected by participation in the wider community, such as in organizations and in political life (UN 1995 ).

Despite the fact that the social consequences of limited economic resources are central to modern perspectives on poverty and marginalization, this relation is surprisingly seldom studied empirically. Qualitative research on the poor give interesting examples on how the negative effects of poverty works, and portray the way that economic problems are transformed into social ones (Ridge and Millar 2011 ; Attree 2006 ). Such studies, however, have too small sample sizes to generalize to the population, and they cannot tell us much about the range of the problem. The (relatively few) studies that have addressed the association between poverty and social outcomes on larger scale tend to verify that the poor have worse social relations (Böhnke 2008 ; Jonsson and Östberg 2004 ; Levitas 2006 ), but Barnes et al. ( 2002 ) did not find any noteworthy association between poverty (measured as relative income poverty, using the 60 %-limit) and social relations or social isolation. Dahl et al. ( 2008 ) found no relation between poverty and friendships, but report less participation in civic organizations among the poor. All these studies have however been limited to cross-sectional data or hampered by methodological shortcomings, and therefore have not been able to address the separation of selection effects from potentially causal ones.

Our aim in this study is to make good these omissions. We use longitudinal data from the Swedish Level of Living Surveys (LNU) 2000 and 2010 to study how falling into poverty, or rising from it, is associated with outcomes in terms of primary and secondary social relations, including participation in civil society. These panel data make it possible to generalize the results to the Swedish adult population (19–65 in 2000; 29–75 in 2010), to address the issue of causality, and to estimate how strong the relation between economic vulnerability and social outcomes is. Because the data provide us with the possibility of measuring poverty in several ways, we are also able to address the question using different—alternative or complementary—indicators. Poverty is measured as economic deprivation (lack of cash margin, self-reported economic problems), income poverty (absolute and relative), and long-term poverty, respectively. The primary, or core, social outcomes are indicated by having social support if needed, and by social relations with friends and relatives. We expand our analysis to secondary, or fringe, social outcomes in terms of participation in social life at large, such as in civil society: our indicators here include the participation in organizations and in political life.

2 Different Dimensions/Definitions of Poverty

In modern welfare states, the normal take on the issue of poverty is to regard it as the relative lack of economic resources, that is, to define the poor in relation to their fellow citizens in the same country at the same time. Three approaches dominate the scholarly literature today. The first takes as a point of departure the income deemed necessary for living a life on par with others, or that makes possible an “acceptable” living standard—defined as the goods and services judged necessary, often on the basis of consumer or household budget studies. This usage of a poverty threshold is often (somewhat confusingly) called absolute income poverty , and is most common in North America (cf. Corak 2006 for a review), although most countries have poverty lines defined for different kinds of social benefits. In Europe and in the OECD, the convention is instead to use versions of relative income poverty , defining as poor those whose incomes fall well behind the median income in the country in question (European Union using 60 % and OECD 50 % of the median as the threshold). As an alternative to using purchasing power (as in the “absolute” measure), this relative measure defines poverty by income inequality in the bottom half of the income distribution (Atkinson et al. 2002 ; OECD 2008 ).

The third approach argues that income measures are too indirect; poverty should instead be indicated directly by the lack of consumer products and services that are necessary for an acceptable living standard (Mack and Lansley 1985 ; Ringen 1988 ; Townsend 1979 ). This approach often involves listing a number of possessions and conditions, such as having a car, washing machine, modern kitchen; and being able to dine out sometimes, to have the home adequately heated and mended, to have sufficient insurances, and so on. An elaborate version includes information on what people in general see as necessities, what is often termed “consensual” poverty (e.g., Mack and Lansley 1985 ; Gordon et al. 2000 ; Halleröd 1995 ; van den Bosch 2001 ). Other direct indicators include the ability to cover unforeseen costs (cash margin) and subjective definitions of poverty (e.g., van den Bosch 2001 ). The direct approach to poverty has gained in popularity and measures of economic/material deprivation and consensual poverty are used in several recent and contemporary comparative surveys such as ECHP (Whelan et al. 2003 ) and EU-SILC (e.g., UNICEF 2012 ; Nolan and Whelan 2011 ).

It is often pointed out that, due to the often quite volatile income careers of households, the majority of poverty episodes are short term and the group that is identified as poor in the cross-section therefore tends to be rather diluted (Bane and Ellwood 1986 ; Duncan et al. 1993 ). Those who suffer most from the downsides of poverty are, it could be argued, instead the long-term, persistent, or chronically poor, and there is empirical evidence that those who experience more years in poverty also are more deprived of a “common lifestyle” (Whelan et al. 2003 ). Poverty persistence has been defined in several ways, such as having spent a given number of years below a poverty threshold, or having an average income over a number of years that falls under the poverty line (e.g., Duncan and Rodgers 1991 ; Rodgers and Rodgers 1993 ). The persistently poor can only be detected with any precision in longitudinal studies, and typically on the basis of low incomes, as data covering repeated measures of material deprivation are uncommon.

For the purposes of this study, it is not essential to nominate the best or most appropriate poverty measure. The measures outlined above, while each having some disadvantage, all provide plausible theoretical grounds for predicting negative social outcomes. Low incomes, either in “absolute” or relative terms, may inhibit social activities and participation because these are costly (e.g., having decent housing, needing a car, paying membership fees, entrance tickets, or new clothes). Economic deprivation, often indicated by items or habits that are directly relevant to social life, is also a valid representation of a lack of resources. Lastly, to be in long-term poverty is no doubt a worse condition than being in shorter-term poverty.

It is worth underlining that we see different measures of poverty as relevant indicators despite the fact that the overlap between them often is surprisingly small (Bradshaw and Finch 2003 ). The lack of overlap is not necessarily a problem, as different people may have different configurations of economic problems but share in common many of the experiences of poverty—experiences, we argue, that are (in theory at least) all likely to lead to adverse social outcomes. Whether this is the case or not is one of the questions that we address, but if previous studies on child poverty are of any guidance, different definitions of poverty may show surprisingly similar associations with a number of outcomes (Jonsson and Östberg 2004 ).

3 What are the Likely Social Consequences of Poverty?

We have concluded that poverty is, according to most influential poverty definitions, manifested in the social sphere. This connects with the idea of Veblen ( 1899 ) of the relation between consumption and social status. What you buy and consume—clothes, furniture, vacation trips—in part define who you are, which group you aspire to belong to, and what view others will have of you. Inclusion into and exclusion from status groups and social circles are, in this view, dependent on economic resources as reflected in consumption patterns. While Veblen was mostly concerned about the rich and their conspicuous consumption, it is not difficult to transfer these ideas to the less fortunate: the poor are under risk of exclusion, of losing their social status and identity, and perhaps also, therefore, their friends. It is however likely that this is a process that differs according to outcome, with an unknown time-lag.

If, as outlined above, we can speak of primary and secondary social consequences, the former should include socializing with friends, but also more intimate relations. Our conjecture is that the closer the relation, the less affected is it by poverty, simply because intimate social bonds are characterized by more unconditional personal relations, typically not requiring costs to uphold.

When it comes to the secondary social consequences, we move outside the realm of closer interpersonal relations to acquaintances and the wider social network, and to the (sometimes relatively anonymous) participation in civil or political life. This dimension of poverty lies at the heart of the social exclusion perspective, which strongly emphasizes the broader issues of societal participation and civic engagement, vital to democratic societies. It is also reflected in the United Nation’s definition, following the Copenhagen summit in 1995, where “overall poverty” in addition to lack of economic resources is said to be “…characterized by lack of participation in decision-making and in civil, social, and cultural life” (UN 1995 , p. 57). Poverty may bring about secondary social consequences because such participation is costly—as in the examples of travel, need for special equipment, or membership fees—but also because of psychological mechanisms, such as lowered self-esteem triggering disbelief in civic and political activities, and a general passivity leading to decreased organizational and social activities overall. If processes like these exist there is a risk of a “downward spiral of social exclusion” where unemployment leads to poverty and social isolation, which in turn reduce the chances of re-gaining a footing in the labour market (Paugam 1995 ).

What theories of poverty and social exclusion postulate is, in conclusion, that both what we have called primary and secondary social relations will be negatively affected by economic hardship—the latter supposedly more than the former. Our strategy in the following is to test this basic hypothesis by applying multivariate panel-data analyses on longitudinal data. In this way, we believe that we can come further than previous studies towards estimating causal effects, although, as is the case in social sciences, the causal relation must remain preliminary due to the nature of observational data.

4 Data and Definitions

We use the two most recent waves of the Swedish Level-of-living Survey, conducted in 2000 and 2010 on random (1/1000) samples of adult Swedes, aged 18–75. Footnote 1 The attrition rate is low, with 84 % of panel respondents remaining from 2000 to 2010. This is one of the few data sets from which we can get over-time measures of both poverty and social outcomes for a panel that is representative of the adult population (at the first time point, t 0 )—in addition, there is annual income information from register data between the waves. The panel feature obviously restricts the age-groups slightly (ages 19–65 in 2000; 29–75 in 2010), the final number of analyzed cases being between 2995 and 3144, depending on the number of missing cases on the respective poverty measure and social outcome variable. For ease of interpretation and comparison of effect sizes, we have constructed all social outcome variables and poverty variables to be dichotomous (0/1). Footnote 2

In constructing poverty variables, we must balance theoretical validity with the need to have group sizes large enough for statistical analysis. For example, we expand the absolute poverty measure to include those who received social assistance any time during the year. As social assistance recipients receive this benefit based on having an income below a poverty line that is similar to the one we use, this seems justifiable. In other cases, however, group sizes are small but we find no theoretically reasonable way of making the variables more inclusive, meaning that some analyses cannot be carried out in full detail.

Our income poverty measures are based on register data and are thus free from recall error or misreporting, but—as the proponents of deprivation measures point out—income poverty measures are indirect measures of hardship. The deprivation measure is more direct, but self-reporting always carries a risk of subjectivity in the assessment. To the extent that changes in one’s judgment of the economic situation depend on changes in non-economic factors that are also related to social relations, the deprivation measure will give upwardly biased estimates. Footnote 3 As there is no general agreement about whether income or deprivation definitions are superior, our use of several definitions is a strength because the results will give an overall picture that is not sensitive to potential limitations in any one measure. In addition, we are able to see whether results vary systematically across commonly used definitions.

4.1 Poverty Measures

Economic deprivation combines information from two survey questions:

Cash margin whether the respondent can raise a given sum of money in a week, if necessary (in 2000, the sum was 12,000 SEK; in 2010, 14,000 SEK, the latter sum corresponding to approximately 1600 Euro, 2200 USD, or 1400 GBP in 2013 currency rates). For those who answer in the affirmative, there is a follow-up question of how this can be done: by (a) own/household resources, (b) borrowing.

Economic crisis Those who claim that they have had problems meeting costs for rent, food, bills, etc. during the last 12 months (responded “yes” to a yes/no alternative).

As economically deprived we classify those who (1) have no cash margin, or (2) can raise money only by borrowing in combination with having reported economic crisis.

Absolute poverty is defined as either (a) having a disposable family income below a poverty threshold or (b) receiving social assistance, both assessed in 1999 (for the survey 2000) or 2009 (for the survey 2010). The poverty line varies by family type/composition according to a commonly used calculation of household necessities (Jansson 2000 ). This “basket” of goods and services is intended to define an acceptable living standard, and was originally constructed for calculating an income threshold for social assistance, with addition of estimated costs for housing and transport. The threshold is adjusted for changes in the Consumer Price Index, using 2010 as the base year. In order to get analyzable group sizes, we classify anyone with an income below 1.25 times this threshold as poor. Self-employed are excluded because their nominal incomes are often a poor indicator of their economic standard.

Deprived and income poor A combination of the indicator of economic deprivation and the indicator of absolute poverty. The poor are defined as those who are economically deprived and in addition are either absolute income-poor or have had social assistance some time during the last calendar year.

Long - term poor are defined as those interviewed in 2010 (2000) who had an equivalized disposable income that fell below the 1.25 absolute poverty threshold (excluding self-employed) or who received social assistance in 2009 (1999), and who were in this situation for at least two of the years 2000–2008 (1990–1998). The long-term poor (coded 1) are contrasted to the non-poor (coded 0), excluding the short-term poor (coded missing) in order to distinguish whether long-term poverty is particularly detrimental (as compared to absolute poverty in general).

Relative poverty is defined, according to the EU standard, as having a disposable equivalized income that is lower than 60 % of the median income in Sweden the year in question (EU 2005). Footnote 4 As for absolute poverty, this variable is based on incomes the year prior to the survey year. Self-employed are excluded.

4.2 Social and Participation Outcomes

4.2.1 primary (core) social relations.

Social support The value 1 (has support) is given to those who have answered in the positive to three questions about whether one has a close friend who can help if one (a) gets sick, (b) needs someone to talk to about troubles, or (c) needs company. Those who lack support in at least one of these respects are coded 0 (lack of support).

Frequent social relations This variable is based on four questions about how often one meets (a) relatives and (b) friends, either (i) at ones’ home or (ii) at the home of those one meets, with the response set being “yes, often”, “sometimes”, and “no, never”. Respondents are defined as having frequent relations (1) if they have at least one “often” of the four possible and no “never”, Footnote 5 and 0 otherwise.

4.2.2 Secondary (fringe) Social Relations/Participation

Political participation : Coded 1 (yes) if one during the last 12 months actively participated (held an elected position or was at a meeting) in a trade union or a political party, and 0 (no) otherwise. Footnote 6

Organizational activity : Coded 1 (yes) if one is a member of an organization and actively participate in its activities at least once in a year, and 0 (no) otherwise.

4.3 Control Variables

Age (in years)

Educational qualifications in 2010 (five levels according to a standard schema used by Statistics Sweden (1985), entered as dummy variables)

Civil status distinguishes between single and cohabiting/married persons, and is used as a time-varying covariate (TVC) where we register any changes from couple to single and vice versa.

Immigrant origin is coded 1 if both parents were born in any country outside Sweden, 0 otherwise.

Labour market status is also used as a TVC, with four values indicating labour market participation (yes/no) in 2000 and 2010, respectively.

Global self - rated health in 2000, with three response alternatives: Good, bad, or in between. Footnote 7

Table  1 shows descriptive statistics for the 2 years we study, 2000 and 2010 (percentages in the upper panel; averages, standard deviations, max and min values in the lower panel). Recall that the sample is longitudinal with the same respondents appearing in both years. This means, naturally, that the sample ages 10 years between the waves, the upper age limit being pushed up from 65 to 75. Both the change over years and the ageing of the sample have repercussions for their conditions: somewhat more have poor health, for example, fewer lack social support but more lack frequent social relations, and more are single in 2010 (where widows are a growing category). The group has however improved their economic conditions, with a sizeable reduction in poverty rates. Most of the changes are in fact period effects, and it is particularly obvious for the change in poverty—in 2000 people still suffered from the deep recession in Sweden that begun in 1991 and started to turn in 1996/97 (Jonsson et al. 2010 ), while the most recent international recession (starting in 2008/09) did not affect Sweden that much.

The overall decrease in poverty masks changes that our respondents experienced between 2000 and 2010: Table  2 reveals these for the measure of economic deprivation, showing the outflow (row) percentages and the total percentages (and the number of respondents in parentheses). It is evident that there was quite a lot of mobility out of poverty between the years (61 % left), but also a very strong relative risk of being found in poverty in 2010 among those who were poor in 2000 (39 vs. 5 % of those who were non-poor in 2000). Of all our respondents, the most common situation was to be non-poor both years (81 %), while few were poor on both occasions (6 %). Table  2 also demonstrates some small cell numbers: 13.3 % of the panel (9.4 % + 3.9 %), or a good 400 cases, changed poverty status, and these cases are crucial for identifying our models. As in many panel studies based on survey data, this will inevitably lead to some problems with large standard errors and difficulties in arriving at statistically significant and precise estimates; but to preview the findings, our results are surprisingly consistent all the same.

We begin with showing descriptive results of how poverty is associated with our outcome variables, using the economic deprivation measure of poverty. Footnote 8 Figure  1 confirms that those who are poor have worse social relationships and participate less in political life and in organizations. Poverty is thus connected with both primary and secondary social relations.

The relation between poverty (measured as economic deprivation) and social relations/participation in Sweden, LNU 2010. N = 5271

The descriptive picture in Fig.  1 does not tell us anything about the causal nature of the relation between poverty and social outcomes, only that such a relation exists, and that it is in the predicted direction: poor people have weaker social relations, less support, and lower levels of political and civic participation. Our task now is to apply more stringent statistical models to test whether the relation we have uncovered is likely to be of a causal nature. This means that we must try to rid the association of both the risk for reverse causality—that, for example, a weaker social network leads to poverty—and the risk that there is a common underlying cause of both poverty and social outcomes, such as poor health or singlehood.

5.1 The Change Model

First, as we have panel data, we can study the difference in change across two time-points T (called t 0 and t 1 , respectively) in an outcome variable (e.g., social relations), between groups (i.e. those who changed poverty status versus those who did not). The respondents are assigned to either of these groups on the grounds of entering or leaving poverty; in the first case, one group is non-poor at t 0 but experiences poverty at t 1 , and the change in this group is compared to the group consisting of those who are non-poor both at t 0 and t 1 . The question in focus then is: Do social relations in the group entering poverty worsen in relation to the corresponding change in social relations in the group who remains non-poor? Because we have symmetric hypotheses of the effect of poverty on social outcomes—assuming leaving poverty has positive consequences similar to the negative consequences of entering poverty—we also study whether those who exit poverty improve their social outcomes as compared to those remaining poor. We ask, that is, not only what damage falling into poverty might have for social outcomes, but also what “social gains” could be expected for someone who climbs out of poverty.

Thus, in our analyses we use two different “change groups”, poverty leavers and poverty entrants , and two “comparison groups”, constantly poor and never poor , respectively. Footnote 9 The setup comparing the change in social outcomes for those who change poverty status and those who do not is analogous to a so-called difference-in-difference design, but as the allocation of respondents to comparison groups and change groups in our data cannot be assumed to be random (as with control groups and treatment groups in experimental designs), we take further measures to approach causal interpretations.

5.2 Accounting for the Starting Value of the Dependent Variable

An important indication of the non-randomness of the allocation to the change and comparison groups is that their average values of the social outcomes (i.e. the dependent variable) at t 0 differ systematically: Those who become poor between 2000 and 2010 have on average worse social outcomes already in 2000 than those who stay out of poverty. Similarly, those who stay in poverty both years have on average worse social outcomes than those who have exited poverty in 2010. In order to further reduce the impact of unobserved variables, we therefore make all comparisons of changes in social outcomes between t 0 and t 1 for fixed t 0 values of both social outcome and poverty status.

As we use dichotomous outcome variables, we get eight combinations of poverty and outcome states (2 × 2 × 2 = 8), and four direct strategic comparisons:

Poverty leavers versus constantly poor, positive social outcome in 2000 , showing if those who exit poverty have a higher chance of maintaining the positive social outcome than those who stay in poverty

Poverty leavers versus constantly poor, negative social outcome in 2000 , showing if those who exit poverty have a higher chance of improvement in the social outcome than those who stay in poverty

Poverty entrants versus never poor, positive social outcome in 2000 , showing if those who enter poverty have a higher risk of deterioration in the social outcome than those who stay out of poverty, and

Poverty entrants versus never poor, negative social outcome in 2000 , showing if those who enter poverty have a lower chance of improvement in the social outcome.

Thus, we hold the initial social situation and poverty status fixed, letting only the poverty in 2010 vary. Footnote 10 The analytical strategy is set out in Table  3 , showing estimates of the probability to have frequent social relations in 2010, for poverty defined (as in Table  2 and Fig.  1 above) as economic deprivation.

The figures in Table  3 should be read like this: 0.59 in the upper left cell means that among those who were poor neither in 2000 nor in 2010 (“never poor”, or 0–0), and who had non-frequent social relations to begin with, 59 % had frequent social relations in 2010. Among those never poor who instead started out with more frequent social relations, 90 per cent had frequent social relations in 2010. This difference (59 vs. 90) tells us either that the initial conditions were important (weak social relations can be inherently difficult to improve) or that there is heterogeneity within the group of never poor people, such as some having (to us perhaps unobserved) characteristics that support relation building while others have not.

Because our strategy is to condition on the initial situation in order to minimize the impact of initial conditions and unobserved heterogeneity, we focus on the comparisons across columns. If we follow each column downwards, that is, for a given initial social outcome (weak or not weak social relations, respectively) it is apparent that the outcome is worse for the “poverty entrants” in comparison with the “never poor” (upper three lines). Comparing the change group [those who became poor (0–1)] with the comparison group [never poor (0–0)] for those who started out with weak social relations (left column), the estimated probability of frequent social relations in 2010 is 7 % points lower for those who became poor. Among those who started out with frequent relations, those who became poor have a 17 % points lower probability of frequent relations in 2010 than those who stayed out of poverty.

If we move down Table  3 , to the three bottom lines, the change and comparison groups are now different. The comparison group is the “constantly poor” (1–1), and the change group are “poverty leavers” (1–0). Again following the columns downwards, we can see that the change group improved their social relations in comparison with the constantly poor; and this is true whether they started out with weak social relations or not. In fact, the chance of improvement for those who started off with non-frequent social relations is the most noteworthy, being 33 % units higher for those who escaped poverty than for those who did not. In sum, Table  3 suggests that becoming poor appears to be bad for social relations whereas escaping poverty is beneficial.

5.3 Expanding the Model

The model exemplified in Table  3 is a panel model that studies change across time within the same individuals, conditioning on their initial state. It does away with time-constant effects of observed and unobserved respondent characteristics, and although this is far superior to a cross-sectional model (such as the one underlying Fig.  1 ) there are still threats to causal interpretations. It is possible (if probably unusual) that permanent characteristics may trigger a change over time in both the dependent and independent variables; or, put in another way, whether a person stays in or exits poverty may be partly caused by a variable that also predicts change in the outcome (what is sometimes referred to as a violation of the “common trend assumption”). In our case, we can for example imagine that health problems in 2000 can affect who becomes poor in 2010, at t 1 , and that the same health problems can lead to a deterioration of social relations between 2000 and 2010, so even conditioning on the social relations at t 0 will not be enough. This we handle by adding control variables, attempting to condition the comparison of poor and non-poor also on sex, age, highest level of education (in 2010), immigrant status, and health (in 2000). Footnote 11

Given the set-up of our data—with 10 years between the two data-points and with no information on the precise time ordering of poverty and social outcomes at t 1 , the model can be further improved by including change in some of the control variables. It is possible, for example, that a non-poor and married respondent in 2000 divorced before 2010, triggering both poverty and reduced social relations at the time of the interview in 2010. Footnote 12 There are two major events that in this way may bias our results, divorce/separation and unemployment (because each can lead to poverty, and possibly also affect social outcomes). We handle this by controlling for variables combining civil status and unemployment in 2000 as well as in 2010. To the extent that these factors are a consequence of becoming poor, there is a risk of biasing our estimates downwards (e.g., if becoming poor increases the risk of divorce). However, as there is no way to distinguish empirically whether control variables (divorce, unemployment) or poverty changed first we prefer to report conservative estimates. Footnote 13

Throughout, we use logistic regression to estimate our models (one model for each social outcome and poverty definition). We create a dummy variable for each of the combinations of poverty in 2000, poverty in 2010 and the social outcome in 2000, and alternate the reference category in order to get the four strategic comparisons described above. Coefficients do thus express the distance between the relevant change and comparison groups. The coefficients reported are average marginal effects (AME) for a one-unit change in the respective poverty variable (i.e. going from non-poor to poor and vice versa), which are straightforwardly interpretable as percentage unit differences and (unlike odds ratios or log odds ratios) comparable across models and outcomes (Mood 2010 ).

5.4 Regression Results

As detailed above, we use changes over time in poverty and social outcomes to estimate the effects of interest. The effect of poverty is allowed to be heterogeneous, and is assessed through four comparisons of the social outcome in 2010 (Y 1 ):

Those entering poverty relative to those in constant non-poverty (P 01  = 0,1 vs. P 01  = 0,0) when both have favourable social outcomes at t 0 (Y 0  = 1)

Those exiting poverty relative to those in constant poverty (P 01  = 1,0 vs. P 01  = 1,1) when both have favourable social outcomes at t 0 (Y 0  = 1)

Those entering poverty relative to those in constant non-poverty (P 01  = 0,1 vs. P 01  = 0,0) when both have non-favourable social outcomes at t 0 (Y 0  = 0)

Those exiting poverty relative to those in constant poverty (P 01  = 1,0 vs. P 01  = 1,1) when both have non-favourable social outcomes at t 0 (Y 0  = 0)

Poverty is a rare outcome, and as noted above it is particularly uncommon to enter poverty between 2000 and 2010 because of the improving macro-economic situation. Some of the social outcomes were also rare in 2000. This unfortunately means that in some comparisons we have cell frequencies that are prohibitively small, and we have chosen to exclude all comparisons involving cells where N < 20.

The regression results are displayed in Table  4 . To understand how the estimates come to be, consider the four in the upper left part of the Table (0.330, 0.138, −0.175 and −0.065), reflecting the effect of poverty, measured as economic deprivation, on the probability of having frequent social relations. Because these estimates are all derived from a regression without any controls, they are identical (apart from using three decimal places) to the percentage comparisons in Table  3 (0.33, 0.14, −0.17, −0.07), and can be straightforwardly interpreted as average differences in the probability of the outcome in question. From Table  4 it is clear that the three first differences are all statistically significant, whereas the estimate −0.07 is not (primarily because those who entered poverty in 2010 and had infrequent social relations in 2000 is a small group, N = 25).

In the column to the right, we can see what difference the controls make: the estimates are reduced, but not substantially so, and the three first differences are still statistically significant.

The estimates for each social outcome, reflecting the four comparisons described above, support the hypothesis of poverty affecting social relations negatively (note that the signs of the estimates should differ in order to do so, the upper two being positive as they reflect an effect of the exit from poverty, and the lower two being negative as they reflect an effect of entering poverty). We have indicated support for the hypothesis in Table  4 by shading the estimates and standard errors for estimates that go in the predicted direction.

Following the first two columns down, we can see that there is mostly support for the hypothesis of a negative effect of poverty, but when controlling for other variables, the effects on social support are not impressive. In fact, if we concentrate on each social outcome (i.e., row-wise), one conclusion is that, when controlling for confounders, there are rather small effects of poverty on the probability of having access to social support. The opposite is true for political participation, where the consistency in the estimated effects of poverty is striking.

If we instead follow the columns, we ask whether any of the definitions of poverty is a better predictor of social outcomes than the others. The measure of economic deprivation appears to be the most stable one, followed by absolute poverty and the combined deprivation/absolute poverty variable. Footnote 14 The relative poverty measure is less able to predict social outcomes: in many instances it even has the non-expected sign. Interestingly, long-term poverty (as measured here) does not appear to have more severe negative consequences than absolute poverty in general.

Because some of our comparison groups are small, it is difficult to get high precision in the estimates, efficiency being a concern particularly in view of the set of control variables in Table  4 . Only 14 out of 62 estimates in models with controls are significant and in the right direction. Nonetheless, with 52 out of 62 estimates in these models having the expected sign, we believe that the hypothesis of a negative effect of poverty on social outcomes receives quite strong support.

Although control variables are not shown in the table, one thing should be noted about them: The reduction of coefficients when including control variables is almost exclusively driven by changes in civil status. Footnote 15 The time constant characteristics that are included are cross-sectionally related to both poverty and social outcomes, but they have only minor impacts on the estimated effects of poverty. This suggests that the conditioning on prior values of the dependent and independent variables eliminates much time invariant heterogeneity, which increases the credibility of estimates.

6 Conclusions

We set out to test a fundamental, but rarely questioned assumption in dominating definitions of poverty: whether shortage of economic resources has negative consequences for social relations and participation. By using longitudinal data from the Swedish Level-of-living Surveys 2000 and 2010, including repeated measures of poverty (according to several commonly used definitions) and four social outcome variables, we are able to come further than previous studies in estimating the relation between poverty and social outcomes: Our main conclusion is that there appears to be a causal relation between them.

Panel models suggest that falling into poverty increases the risk of weakening social relations and decreasing (civic and political) participation. Climbing out of poverty tends to have the opposite effects, a result that strengthens the interpretation of causality. The sample is too small to estimate the effect sizes with any precision, yet they appear to be substantial, with statistically significant estimates ranging between 5 and 21 % units.

While these findings are disquieting insofar as poverty goes, our results also suggest two more positive results. First, the negative effects of poverty appear to be reversible: once the private economy recovers, social outcomes improve. Secondly, the negative consequences are less for the closest social relations, whether there is someone there in cases of need (sickness, personal problems, etc.). This is in line with an interpretation of such close relations being unconditional: our nearest and dearest tend to hang on to us also in times of financial troubles, which may bolster risks for social isolation and psychological ill-being,

Our finding of negative effects of poverty on civic and political participation relates to the fears of a “downward spiral of social exclusion”, as there is a risk that the loss of less intimate social relations shrinks social networks and decreases the available social capital in terms of contacts that can be important for outcomes such as finding a job (e.g., Lin 2001 ; Granovetter 1974 ). However, Gallie et al. ( 2003 ) found no evidence for any strong impact of social isolation on unemployment, suggesting that the negative effects on social outcomes that we observe are unlikely to lead to self-reinforcement of poverty. Nevertheless, social relations are of course important outcomes in their own right, so if they are negatively affected by poverty it matters regardless of whether social relations in turn are important for other outcomes. Effects on political and civic participation are also relevant in themselves beyond individuals’ wellbeing, as they suggest a potentially democratic problem where poor have less of a voice and less influence on society than others.

Our results show the merits of our approach, to study the relation between poverty and social outcomes longitudinally. The fact that the poor have worse social relations and lower participation is partly because of selection. This may be because the socially isolated, or those with a weaker social network, more easily fall into poverty; or it can be because of a common denominator, such as poor health or social problems. But once we have stripped the analysis of such selection effects, we also find what is likely to be a causal relation between poverty and social relations. However, this effect of poverty on social outcomes, in turn, varies between different definitions of poverty. Here it appears that economic deprivation, primarily indicated by the ability of raising money with short notice, is the strongest predictor of social outcomes. Income poverty, whether in absolute or (particularly) relative terms, are weaker predictors of social outcomes, which is interesting as they are the two most common indicators of poverty in existing research.

Even if we are fortunate to have panel data at our disposal, there are limitations in our analyses that render our conclusions tentative. One is that we do not have a random allocation to the comparison groups at t 0 ; another that there is a 10-year span between the waves that we analyze, and both poverty and social outcomes may vary across this time-span. We have been able to address these problems by conditioning on the outcome at t 0 and by controlling for confounders, but in order to perform more rigorous tests future research would benefit from data with a more detailed temporal structure, and preferably with an experimental or at least quasi-experimental design.

Finally, our analyses concern Sweden, and given the position as an active welfare state with a low degree of inequality and low poverty rates, one can ask whether the results are valid also for other comparable countries. While both the level of poverty and the pattern of social relations differ between countries (for policy or cultural reasons), we believe that the mechanisms linking poverty and social outcomes are of a quite general kind, especially as the “costs for social participation” can be expected to be relative to the general wealth of a country—however, until comparative longitudinal data become available, this must remain a hypothesis for future research.

http://www.sofi.su.se/english/2.17851/research/three-research-departments/lnu-level-of-living .

We have tested various alternative codings and the overall pattern of results in terms of e.g., direction of effects and differences across poverty definitions are similar, but more difficult to present in an accessible way.

Our deprivation questions are however designed to reduce the impact of subjectivity by asking, e.g., about getting a specified sum within a specified time (see below).

In the equivalence scale, the first adult gets a weight of one, the second of 0.6, and each child gets a weight of 0.5.

We have also tried using single indicators (either a/b or i/ii) without detecting any meaningful difference between them. One would perhaps have assumed that poverty would be more consequential for having others over to one’s own place, but the absence of support for this can perhaps be understood in light of the strong social norm of reciprocity in social relations.

We have refrained from using information on voting and membership in trade unions and political parties, because these indicators do not capture the active, social nature of civic engagement to the same extent as participation in meetings and the holding of positions.

We have also estimated models with a more extensive health variable, a s ymptom index , which sums responses to 47 questions about self-reported health symptoms. However, this variable has virtually zero effects once global self-rated health is controlled, and does not lead to any substantive differences in other estimates. Adding the global health measure and the symptom index as TVC had no effect either.

Using the other indicators of poverty yields very similar results, although for some of those the difference between poor and non-poor is smaller.

We call these comparison groups ”never poor” and ”constantly poor” for expository purposes, although their poverty status pertains only to the years 2000 and 2010, i.e., without information on the years in between.

With this design we allow different effects of poverty on improvement versus deterioration of the social outcome. We have also estimated models with a lagged dependent variable, which constrains the effects of poverty changes to be of the same size for deterioration as for improvement of the social outcome. Conclusions from that analysis are roughly a weighted average of the estimates for deterioration and improvement that we report. As our analyses suggest that effects of poverty differ in size depending on the value of the lagged dependent variable (the social outcome) our current specification gives a more adequate representation of the process.

We have also tested models with a wider range of controls for, e.g., economic and social background (i.e. characteristics of the respondent’s parents), geography, detailed family type and a more detailed health variable, but none of these had any impact on the estimated poverty effects.

It is also possible that we register reverse causality, namely if worsening social outcomes that occur after t 0 lead to poverty at t 1 . This situation is almost inevitable when using panel data with no clear temporal ordering of events occurring between waves. However, reverse causality strikes us, in this case, as theoretically implausible.

We have also estimated models controlling for changes in health, which did not change the results.

If respondents’ judgments of the deprivation questions (access to cash margin and ability to pay rent, food, bills etc.) change due to non-economic factors that are related to changes in social relations, the better predictive capacity of the deprivation measure may be caused by a larger bias in this measure than in the (register-based) income measures.

As mentioned above, this variable may to some extent be endogenous (i.e., a mediator of the poverty effect rather than a confounder), in which case we get a downward bias of estimates.

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Mood, C., Jonsson, J.O. The Social Consequences of Poverty: An Empirical Test on Longitudinal Data. Soc Indic Res 127 , 633–652 (2016). https://doi.org/10.1007/s11205-015-0983-9

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Accepted : 09 May 2015

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2 Understanding Prosperity and Poverty: Geography, Institutions, and the Reversal of Fortune

• Published: May 2006
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Geography and institutions are the two main contenders to explain the fundamental causes of cross-country differences in prosperity. The geography hypothesis — which has a large following both in the popular imagination and in academia — maintains that the geography, climate, and ecology of a society’s location shape both its technology and the incentives of its inhabitants. This essay argues that differences in institutions are more important than geography for understanding the divergent economic and social conditions of nations. While the geography hypothesis emphasizes forces of nature as a primary factor in the poverty of nations, the institutions hypothesis is about man-made influences. A case is developed for the importance of institutions which draws on the history of European colonization.

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2.3 Explaining Poverty

Learning objectives.

• Describe the assumptions of the functionalist and conflict views of stratification and of poverty.
• Explain the focus of symbolic interactionist work on poverty.
• Understand the difference between the individualist and structural explanations of poverty.

Why does poverty exist, and why and how do poor people end up being poor? The sociological perspectives introduced in Chapter 1 “Understanding Social Problems” provide some possible answers to these questions through their attempt to explain why American society is stratified —that is, why it has a range of wealth ranging from the extremely wealthy to the extremely poor. We review what these perspectives say generally about social stratification (rankings of people based on wealth and other resources a society values) before turning to explanations focusing specifically on poverty.

In general, the functionalist perspective and conflict perspective both try to explain why social stratification exists and endures, while the symbolic interactionist perspective discusses the differences that stratification produces for everyday interaction. Table 2.2 “Theory Snapshot” summarizes these three approaches.

Table 2.2 Theory Snapshot

The Functionalist View

As discussed in Chapter 1 “Understanding Social Problems” , functionalist theory assumes that society’s structures and processes exist because they serve important functions for society’s stability and continuity. In line with this view, functionalist theorists in sociology assume that stratification exists because it also serves important functions for society. This explanation was developed more than sixty years ago by Kingsley Davis and Wilbert Moore (Davis & Moore, 1945) in the form of several logical assumptions that imply stratification is both necessary and inevitable. When applied to American society, their assumptions would be as follows:

• Some jobs are more important than other jobs. For example, the job of a brain surgeon is more important than the job of shoe shining.
• Some jobs require more skills and knowledge than other jobs. To stay with our example, it takes more skills and knowledge to perform brain surgery than to shine shoes.
• Relatively few people have the ability to acquire the skills and knowledge that are needed to do these important, highly skilled jobs. Most of us would be able to do a decent job of shining shoes, but very few of us would be able to become brain surgeons.
• To encourage the people with the skills and knowledge to do the important, highly skilled jobs, society must promise them higher incomes or other rewards. If this is true, some people automatically end up higher in society’s ranking system than others, and stratification is thus necessary and inevitable.

To illustrate their assumptions, say we have a society where shining shoes and doing brain surgery both give us incomes of $150,000 per year. (This example is very hypothetical, but please keep reading.) If you decide to shine shoes, you can begin making this money at age 16, but if you decide to become a brain surgeon, you will not start making this same amount until about age 35, as you must first go to college and medical school and then acquire several more years of medical training. While you have spent nineteen additional years beyond age 16 getting this education and training and taking out tens of thousands of dollars in student loans, you could have spent those years shining shoes and making $150,000 a year, or $2.85 million overall. Which job would you choose?

Functional theory argues that the promise of very high incomes is necessary to encourage talented people to pursue important careers such as surgery. If physicians and shoe shiners made the same high income, would enough people decide to become physicians?

Public Domain Images – CC0 public domain.

As this example suggests, many people might not choose to become brain surgeons unless considerable financial and other rewards awaited them. By extension, we might not have enough people filling society’s important jobs unless they know they will be similarly rewarded. If this is true, we must have stratification. And if we must have stratification, then that means some people will have much less money than other people. If stratification is inevitable, then, poverty is also inevitable. The functionalist view further implies that if people are poor, it is because they do not have the ability to acquire the skills and knowledge necessary for the important, high-paying jobs.

The functionalist view sounds very logical, but a few years after Davis and Moore published their theory, other sociologists pointed out some serious problems in their argument (Tumin, 1953; Wrong, 1959).

First, it is difficult to compare the importance of many types of jobs. For example, which is more important, doing brain surgery or mining coal? Although you might be tempted to answer with brain surgery, if no coal were mined then much of our society could not function. In another example, which job is more important, attorney or professor? (Be careful how you answer this one!)

Second, the functionalist explanation implies that the most important jobs have the highest incomes and the least important jobs the lowest incomes, but many examples, including the ones just mentioned, counter this view. Coal miners make much less money than physicians, and professors, for better or worse, earn much less on the average than lawyers. A professional athlete making millions of dollars a year earns many times the income of the president of the United States, but who is more important to the nation? Elementary school teachers do a very important job in our society, but their salaries are much lower than those of sports agents, advertising executives, and many other people whose jobs are far less essential.

Third, the functionalist view assumes that people move up the economic ladder based on their abilities, skills, knowledge, and, more generally, their merit. This implies that if they do not move up the ladder, they lack the necessary merit. However, this view ignores the fact that much of our stratification stems from lack of equal opportunity. As later chapters in this book discuss, because of their race, ethnicity, gender, and class standing at birth, some people have less opportunity than others to acquire the skills and training they need to fill the types of jobs addressed by the functionalist approach.

Finally, the functionalist explanation might make sense up to a point, but it does not justify the extremes of wealth and poverty found in the United States and other nations. Even if we do have to promise higher incomes to get enough people to become physicians, does that mean we also need the amount of poverty we have? Do CEOs of corporations really need to make millions of dollars per year to get enough qualified people to become CEOs? Do people take on a position as CEO or other high-paying job at least partly because of the challenge, working conditions, and other positive aspects they offer? The functionalist view does not answer these questions adequately.

One other line of functionalist thinking focuses more directly on poverty than generally on stratification. This particular functionalist view provocatively argues that poverty exists because it serves certain positive functions for our society. These functions include the following: (1) poor people do the work that other people do not want to do; (2) the programs that help poor people provide a lot of jobs for the people employed by the programs; (3) the poor purchase goods, such as day-old bread and used clothing, that other people do not wish to purchase, and thus extend the economic value of these goods; and (4) the poor provide jobs for doctors, lawyers, teachers, and other professionals who may not be competent enough to be employed in positions catering to wealthier patients, clients, students, and so forth (Gans, 1972). Because poverty serves all these functions and more, according to this argument, the middle and upper classes have a vested interested in neglecting poverty to help ensure its continued existence.

The Conflict View

Because he was born in a log cabin and later became president, Abraham Lincoln’s life epitomizes the American Dream, which is the belief that people born into poverty can become successful through hard work. The popularity of this belief leads many Americans to blame poor people for their poverty.

US Library of Congress – public domain.

Conflict theory’s explanation of stratification draws on Karl Marx’s view of class societies and incorporates the critique of the functionalist view just discussed. Many different explanations grounded in conflict theory exist, but they all assume that stratification stems from a fundamental conflict between the needs and interests of the powerful, or “haves,” in society and those of the weak, or “have-nots” (Kerbo, 2012). The former take advantage of their position at the top of society to stay at the top, even if it means oppressing those at the bottom. At a minimum, they can heavily influence the law, the media, and other institutions in a way that maintains society’s class structure.

In general, conflict theory attributes stratification and thus poverty to lack of opportunity from discrimination and prejudice against the poor, women, and people of color. In this regard, it reflects one of the early critiques of the functionalist view that the previous section outlined. To reiterate an earlier point, several of the remaining chapters of this book discuss the various obstacles that make it difficult for the poor, women, and people of color in the United States to move up the socioeconomic ladder and to otherwise enjoy healthy and productive lives.

Symbolic Interactionism

Consistent with its micro orientation, symbolic interactionism tries to understand stratification and thus poverty by looking at people’s interaction and understandings in their daily lives. Unlike the functionalist and conflict views, it does not try to explain why we have stratification in the first place. Rather, it examines the differences that stratification makes for people’s lifestyles and their interaction with other people.

Many detailed, insightful sociological books on the lives of the urban and rural poor reflect the symbolic interactionist perspective (Anderson, 1999; C. M. Duncan, 2000; Liebow, 1993; Rank, 1994). These books focus on different people in different places, but they all make very clear that the poor often lead lives of quiet desperation and must find ways of coping with the fact of being poor. In these books, the consequences of poverty discussed later in this chapter acquire a human face, and readers learn in great detail what it is like to live in poverty on a daily basis.

Some classic journalistic accounts by authors not trained in the social sciences also present eloquent descriptions of poor people’s lives (Bagdikian, 1964; Harrington, 1962). Writing in this tradition, a newspaper columnist who grew up in poverty recently recalled, “I know the feel of thick calluses on the bottom of shoeless feet. I know the bite of the cold breeze that slithers through a drafty house. I know the weight of constant worry over not having enough to fill a belly or fight an illness…Poverty is brutal, consuming and unforgiving. It strikes at the soul” (Blow, 2011).

Sociological accounts of the poor provide a vivid portrait of what it is like to live in poverty on a daily basis.

Pixabay – CC0 public domain.

On a more lighthearted note, examples of the symbolic interactionist framework are also seen in the many literary works and films that portray the difficulties that the rich and poor have in interacting on the relatively few occasions when they do interact. For example, in the film Pretty Woman , Richard Gere plays a rich businessman who hires a prostitute, played by Julia Roberts, to accompany him to swank parties and other affairs. Roberts has to buy a new wardrobe and learn how to dine and behave in these social settings, and much of the film’s humor and poignancy come from her awkwardness in learning the lifestyle of the rich.

Specific Explanations of Poverty

The functionalist and conflict views focus broadly on social stratification but only indirectly on poverty. When poverty finally attracted national attention during the 1960s, scholars began to try specifically to understand why poor people become poor and remain poor. Two competing explanations developed, with the basic debate turning on whether poverty arises from problems either within the poor themselves or in the society in which they live (Rank, 2011). The first type of explanation follows logically from the functional theory of stratification and may be considered an individualistic explanation. The second type of explanation follows from conflict theory and is a structural explanation that focuses on problems in American society that produce poverty. Table 2.3 “Explanations of Poverty” summarizes these explanations.

Table 2.3 Explanations of Poverty

It is critical to determine which explanation makes more sense because, as sociologist Theresa C. Davidson (Davidson, 2009) observes, “beliefs about the causes of poverty shape attitudes toward the poor.” To be more precise, the particular explanation that people favor affects their view of government efforts to help the poor. Those who attribute poverty to problems in the larger society are much more likely than those who attribute it to deficiencies among the poor to believe that the government should do more to help the poor (Bradley & Cole, 2002). The explanation for poverty we favor presumably affects the amount of sympathy we have for the poor, and our sympathy, or lack of sympathy, in turn affects our views about the government’s role in helping the poor. With this backdrop in mind, what do the individualistic and structural explanations of poverty say?

Individualistic Explanation

According to the individualistic explanation , the poor have personal problems and deficiencies that are responsible for their poverty. In the past, the poor were thought to be biologically inferior, a view that has not entirely faded, but today the much more common belief is that they lack the ambition and motivation to work hard and to achieve success. According to survey evidence, the majority of Americans share this belief (Davidson, 2009). A more sophisticated version of this type of explanation is called the culture of poverty theory (Banfield, 1974; Lewis, 1966; Murray, 2012). According to this theory, the poor generally have beliefs and values that differ from those of the nonpoor and that doom them to continued poverty. For example, they are said to be impulsive and to live for the present rather than the future.

Regardless of which version one might hold, the individualistic explanation is a blaming-the-victim approach (see Chapter 1 “Understanding Social Problems” ). Critics say this explanation ignores discrimination and other problems in American society and exaggerates the degree to which the poor and nonpoor do in fact hold different values (Ehrenreich, 2012; Holland, 2011; Schmidt, 2012). Regarding the latter point, they note that poor employed adults work more hours per week than wealthier adults and that poor parents interviewed in surveys value education for their children at least as much as wealthier parents. These and other similarities in values and beliefs lead critics of the individualistic explanation to conclude that poor people’s poverty cannot reasonably be said to result from a culture of poverty.

Structural Explanation

According to the second, structural explanation , which is a blaming-the-system approach, US poverty stems from problems in American society that lead to a lack of equal opportunity and a lack of jobs. These problems include (a) racial, ethnic, gender, and age discrimination; (b) lack of good schooling and adequate health care; and (c) structural changes in the American economic system, such as the departure of manufacturing companies from American cities in the 1980s and 1990s that led to the loss of thousands of jobs. These problems help create a vicious cycle of poverty in which children of the poor are often fated to end up in poverty or near poverty themselves as adults.

As Rank (Rank, 2011) summarizes this view, “American poverty is largely the result of failings at the economic and political levels, rather than at the individual level…In contrast to [the individualistic] perspective, the basic problem lies in a shortage of viable opportunities for all Americans.” Rank points out that the US economy during the past few decades has created more low-paying and part-time jobs and jobs without benefits, meaning that Americans increasingly find themselves in jobs that barely lift them out of poverty, if at all. Sociologist Fred Block and colleagues share this critique of the individualistic perspective: “Most of our policies incorrectly assume that people can avoid or overcome poverty through hard work alone. Yet this assumption ignores the realities of our failing urban schools, increasing employment insecurities, and the lack of affordable housing, health care, and child care. It ignores the fact that the American Dream is rapidly becoming unattainable for an increasing number of Americans, whether employed or not” (Block, et. al., 2006).

Most sociologists favor the structural explanation. As later chapters in this book document, racial and ethnic discrimination, lack of adequate schooling and health care, and other problems make it difficult to rise out of poverty. On the other hand, some ethnographic research supports the individualistic explanation by showing that the poor do have certain values and follow certain practices that augment their plight (Small, et. al., 2010). For example, the poor have higher rates of cigarette smoking (34 percent of people with annual incomes between $6,000 and $11,999 smoke, compared to only 13 percent of those with incomes $90,000 or greater [Goszkowski, 2008]), which helps cause them to have more serious health problems.

Adopting an integrated perspective, some researchers say these values and practices are ultimately the result of poverty itself (Small et, al., 2010). These scholars concede a culture of poverty does exist, but they also say it exists because it helps the poor cope daily with the structural effects of being poor. If these effects lead to a culture of poverty, they add, poverty then becomes self-perpetuating. If poverty is both cultural and structural in origin, these scholars say, efforts to improve the lives of people in the “other America” must involve increased structural opportunities for the poor and changes in some of their values and practices.

Key Takeaways

• According to the functionalist view, stratification is a necessary and inevitable consequence of the need to use the promise of financial reward to encourage talented people to pursue important jobs and careers.
• According to conflict theory, stratification results from lack of opportunity and discrimination against the poor and people of color.
• According to symbolic interactionism, social class affects how people interact in everyday life and how they view certain aspects of the social world .
• The individualistic view attributes poverty to individual failings of poor people themselves, while the structural view attributes poverty to problems in the larger society.

For Your Review

• In explaining poverty in the United States, which view, individualist or structural, makes more sense to you? Why?
• Suppose you could wave a magic wand and invent a society where everyone had about the same income no matter which job he or she performed. Do you think it would be difficult to persuade enough people to become physicians or to pursue other important careers? Explain your answer.

Anderson, E. (1999). Code of the street: Decency, violence, and the moral life of the inner city . New York, NY: W. W. Norton.

Bagdikian, B. H. (1964). In the midst of plenty: The poor in America . Boston, MA: Beacon Press.

Banfield, E. C. (1974). The unheavenly city revisited . Boston, MA: Little, Brown.

Block, F., Korteweg, A. C., & Woodward, K. (2006). The compassion gap in American poverty policy. Contexts, 5 (2), 14–20.

Blow, C. M. (2011, June 25). Them that’s not shall lose. New York Times , p. A19.

Bradley, C., & Cole, D. J. (2002). Causal attributions and the significance of self-efficacy in predicting solutions to poverty. Sociological Focus, 35 , 381–396.

Davidson, T. C. (2009). Attributions for poverty among college students: The impact of service-learning and religiosity. College Student Journal, 43 , 136–144.

Davis, K., & Moore, W. (1945). Some principles of stratification. American Sociological Review, 10 , 242–249.

Duncan, C. M. (2000). Worlds apart: Why poverty persists in rural America . New Haven, CT: Yale University Press.

Ehrenreich, B. (2012, March 15). What “other America”? Salon.com . Retrieved from http://www.salon.com/2012/03/15/the_truth_about_the_poor/ .

Gans, H. J. (1972). The positive functions of poverty. American Journal of Sociology, 78 , 275–289.

Goszkowski, R. (2008). Among Americans, smoking decreases as income increases. Retrieved from http://www.gallup.com/poll/105550/among-americans-smoking-decreases-income-increases.aspx .

Harrington, M. (1962). The other America: Poverty in the United States . New York, NY: Macmillan.

Holland, J. (2011, July 29). Debunking the big lie right-wingers use to justify black poverty and unemployment. AlterNet . Retrieved from http://www.alternet.org/story/151830/debunking_the_big_lie_right-wingers_use_to_justify_black_poverty _and_unemployment_?page=entire .

Kerbo, H. R. (2012). Social stratification and inequality . New York, NY: McGraw-Hill.

Lewis, O. (1966). The culture of poverty. Scientific American, 113 , 19–25.

Liebow, E. (1993). Tell them who I am: The lives of homeless women . New York, NY: Free Press.

Murray, C. (2012). Coming apart: The state of white America, 1960–2010 . New York, NY: Crown Forum.

Rank, M. R. (1994). Living on the edge: The realities of welfare in America . New York, NY: Columbia University Press.

Rank, M. R. (2011). Rethinking American poverty. Contexts, 10 (Spring), 16–21.

Schmidt, P. (2012, February 12). Charles Murray, author of the “Bell Curve,” steps back into the ring. The Chronicle of Higher Education . Retrieved from http://chronicle.com/article/Charles-Murray-Author-of-The/130722/?sid=at&utm_source=at&utm_medium=en .

Small, M. L., Harding, D. J., & Lamont, M. (2010). Reconsidering culture and poverty. The Annals of the American Academy of Political and Social Science, 629 (May), 6–27.

Tumin, M. M. (1953). Some principles of stratification: A critical analysis. American Sociological Review, 18 , 387–393.

Wrong, D. H. (1959). The functional theory of stratification: Some neglected considerations. American Sociological Review, 24 , 772–782.

Social Problems Copyright © 2015 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

By Joe Hasell, Max Roser, Esteban Ortiz-Ospina and Pablo Arriagada

Global poverty is one of the most pressing problems that the world faces today. The poorest in the world are often undernourished , without access to basic services such as electricity and safe drinking water ; they have less access to education , and suffer from much poorer health .

In order to make progress against such poverty in the future, we need to understand poverty around the world today and how it has changed.

On this page you can find all our data, visualizations and writing relating to poverty. This work aims to help you understand the scale of the problem today; where progress has been achieved and where it has not; what can be done to make progress against poverty in the future; and the methods behind the data on which this knowledge is based.

Key Insights on Poverty

Measuring global poverty in an unequal world.

There is no single definition of poverty. Our understanding of the extent of poverty and how it is changing depends on which definition we have in mind.

In particular, richer and poorer countries set very different poverty lines in order to measure poverty in a way that is informative and relevant to the level of incomes of their citizens.

For instance, while in the United States a person is counted as being in poverty if they live on less than roughly $24.55 per day, in Ethiopia the poverty line is set more than 10 times lower – at $2.04 per day. You can read more about how these comparable national poverty lines are calculated in this footnote. 1

To measure poverty globally, however, we need to apply a poverty line that is consistent across countries.

This is the goal of the International Poverty Line of $2.15 per day – shown in red in the chart – which is set by the World Bank and used by the UN to monitor extreme poverty around the world.

We see that, in global terms, this is an extremely low threshold indeed – set to reflect the poverty lines adopted nationally in the world’s poorest countries. It marks an incredibly low standard of living – a level of income much lower than just the cost of a healthy diet .

From $1.90 to $2.15 a day: the updated International Poverty Line

What you should know about this data.

• Global poverty data relies on national household surveys that have differences affecting their comparability across countries or over time. Here the data for the US relates to incomes and the data for other countries relates to consumption expenditure. 2
• The poverty lines here are an approximation of national definitions of poverty, made in order to allow comparisons across the countries. 1
• Non-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account. 3
• Data is measured in 2017 international-$, which means that inflation and differences in the cost of living across countries are taken into account. 4

Global extreme poverty declined substantially over the last generation

Over the past generation extreme poverty declined hugely. This is one of the most important ways our world has changed over this time.

There are more than a billion fewer people living below the International Poverty Line of $2.15 per day today than in 1990. On average, the number declined by 47 million every year, or 130,000 people each day. 5

The scale of global poverty today, however, remains vast. The latest global estimates of extreme poverty are for 2019. In that year the World Bank estimates that around 650 million people – roughly one in twelve – were living on less than $2.15 a day.

Extreme poverty: how far have we come, how far do we still have to go?

• Extreme poverty here is defined according to the UN’s definition of living on less than $2.15 a day – an extremely low threshold needed to monitor and draw attention to the living conditions of the poorest around the world. Read more in our article, From $1.90 to $2.15 a day: the updated International Poverty Line .
• Global poverty data relies on national household surveys that have differences affecting their comparability across countries or over time. 2
• Surveys are less frequently available in poorer countries and for earlier decades. To produce regional and global poverty estimates, the World Bank collates the closest survey for each country and projects the data forward or backwards to the year being estimated. 6
• Data is measured in 2017 international-$, which means that inflation and differences in the cost of living across countries are taken into account . 4

The pandemic pushed millions into extreme poverty

Official estimates for global poverty over the course of the Coronavirus pandemic are not yet available.

But it is clear that the global recession it brought about has had a terrible impact on the world’s poorest.

Preliminary estimates produced by researchers at the World Bank suggest that the number of people in extreme poverty rose by around 70 million in 2020 – the first substantial rise in a generation – and remains around 70-90 million higher than would have been expected in the pandemic’s absence. On these preliminary estimates, the global extreme poverty rate rose to around 9% in 2020. 7

• Figures for 2020-2022 are preliminary estimates and projections by World Bank researchers, based on economic growth forecasts. The pre-pandemic projection is based on growth forecasts prior to the pandemic. You can read more about this data and the methods behind it in the World Bank’s Poverty and Shared Prosperity 2022 report. 8

Hundreds of millions will remain in extreme poverty on current trends

Extreme poverty declined during the last generation because the majority of the poorest people on the planet lived in countries with strong economic growth – primarily in Asia.

The majority of the poorest now live in Sub-Saharan Africa, where weaker economic growth and high population growth in many countries has led to a rising number of people living in extreme poverty.

The chart here shows projections of global extreme poverty produced by World Bank researchers based on economic growth forecasts. 9

A very bleak future is ahead of us should such weak economic growth in the world’s poorest countries continue – a future in which extreme poverty is the reality for hundreds of millions for many years to come.

• The extreme poverty estimates and projections shown here relate to a previous release of the World Bank’s poverty and inequality data in which incomes are expressed in 2011 international-$. The World Bank has since updated its methods, and now measures incomes in 2017 international-$. As part of this change, the International Poverty Line used to measure extreme poverty has also been updated: from $1.90 (in 2011 prices) to $2.15 (in 2017 prices). This has had little effect on our overall understanding of poverty and inequality around the world. You can read more about this change and how it affected the World Bank estimates of poverty in our article From $1.90 to $2.15 a day: the updated International Poverty Line .
• Figures for 2018 and beyond are preliminary estimates and projections by Lakner et al. (2022), based on economic growth forecasts. You can read more about this data and the methods behind it in the related blog post. 10
• Data is measured in 2011 international-$, which means that inflation and differences in the cost of living across countries are taken into account. 4

The rapid progress seen in many countries shows an end to poverty is possible

Each of the countries shown in the chart achieved large declines in extreme poverty over the last generation. 11

The fact that rapid progress against poverty has been achieved in many places is one of the most important lessons we can learn from the available data on extreme poverty.

For those who are not aware of such progress – which is the majority of people – it would be easy to make the mistake of believing that poverty is inevitable and that action to tackle poverty is hence doomed to fail.

The huge progress seen in so many places shows that this view is incorrect.

After 200 years of progress the fight against global poverty is just beginning

Over the past two centuries the world made good progress against extreme poverty. But only very recently has poverty fallen at higher poverty lines.

Global poverty rates at these higher lines remain very high:

• 25% of the world lives on less than $3.65 per day – a poverty line broadly reflective of the lines adopted in lower-middle income countries.
• 47% of the world lives on less than $6.85 per day – a poverty line broadly reflective of the lines adopted in upper-middle income countries.
• 84% live on less than $30 per day – a poverty line broadly reflective of the lines adopted in high income countries. 12

Economic growth over the past two centuries has allowed the majority of the world to leave extreme poverty behind. But by the standards of today’s rich countries, the world remains very poor. If this should change, the world needs to achieve very substantial economic growth further still.

The history of the end of poverty has just begun

How much economic growth is necessary to reduce global poverty substantially?

• The data from 1981 onwards is based on household surveys collated by the World Bank. Earlier figures are from Moatsos (2021), who extends the series backwards based on historical reconstructions of GDP per capita and inequality data. 13
• All data is measured in international-$ which means that inflation and differences in purchasing power across countries are taken into account. 4
• The World Bank data for the higher poverty lines is measured in 2017 international-$. Recently, the World Bank updated its methodology having previously used 2011 international-$ to measure incomes and set poverty lines. The Moatsos (2021) historical series is based on the previously-used World Bank definition of extreme poverty – living on less than $1.90 a day when measured in 2011 international-$. This is broadly equivalent to the current World Bank definition of extreme poverty – living on less than $2.15 a day when measured in 2017 international-$. You can read more about this update to the World Bank’s methodology and how it has affected its estimates of poverty in our article From $1.90 to $2.15 a day: the updated International Poverty Line .
• The global poverty data shown from 1981 onwards relies on national household surveys that have differences affecting their comparability across countries or over time. 2
• Such surveys are less frequently available in poorer countries and for earlier decades. To produce regional and global poverty estimates, the World Bank collates the closest survey for each country and projects the data forward or backwards to the year being estimated. 6
• Non-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account. This is also true of the historical data – in producing historical estimates of GDP per capita on which these long-run estimates are based, economic historians take into account such non-market sources of income, as we discuss further in our article How do we know the history of extreme poverty?

Explore Data on Poverty

About this data.

All the data included in this explorer is available to download in GitHub , alongside a range of other poverty and inequality metrics.

Where is this data sourced from?

This data explorer is collated and adapted from the World Bank’s Poverty and Inequality Platform (PIP).

The World Bank’s PIP data is a large collection of household surveys where steps have been taken by the World Bank to harmonize definitions and methods across countries and over time.

About the comparability of household surveys

There is no global survey of incomes. To understand how incomes across the world compare, researchers need to rely on available national surveys.

Such surveys are partly designed with cross-country comparability in mind, but because the surveys reflect the circumstances and priorities of individual countries at the time of the survey, there are some important differences.

Income vs expenditure surveys

One important issue is that the survey data included within the PIP database tends to measure people’s income in high-income countries, and people’s consumption expenditure in poorer countries.

The two concepts are closely related: the income of a household equals their consumption plus any saving, or minus any borrowing or spending out of savings.

One important difference is that, while zero consumption is not a feasible value – people with zero consumption would starve – a zero income is a feasible value. This means that, at the bottom end of the distribution, income and consumption can give quite different pictures about a person’s welfare. For instance, a person dissaving in retirement may have a very low, or even zero, income, but have a high level of consumption nevertheless.

The gap between income and consumption is higher at the top of this distribution too, richer households tend to save more, meaning that the gap between income and consumption is higher at the top of this distribution too. Taken together, one implication is that inequality measured in terms of consumption is generally somewhat lower than the inequality measured in terms of income.

In our Data Explorer of this data there is the option to view only income survey data or only consumption survey data, or instead to pool the data available from both types of survey – which yields greater coverage.

Other comparability issues

There are a number of other ways in which comparability across surveys can be limited. The PIP Methodology Handbook provides a good summary of the comparability and data quality issues affecting this data and how it tries to address them.

In collating this survey data the World Bank takes a range of steps to harmonize it where possible, but comparability issues remain. These affect comparisons both across countries and within individual countries over time.

To help communicate the latter, the World Bank produces a variable that groups surveys within each individual country into more comparable ‘spells’. Our Data Explorer provides the option of viewing the data with these breaks in comparability indicated, and these spells are also indicated in our data download .

Global and regional poverty estimates

Along with data for individual countries, the World Bank also provides global and regional poverty estimates which aggregate over the available country data.

Surveys are not conducted annually in every country however – coverage is generally poorer the further back in time you look, and remains particularly patchy within Sub-Saharan Africa. You can see that visualized in our chart of the number of surveys included in the World Bank data by decade.

In order to produce global and regional aggregate estimates for a given year, the World Bank takes the surveys falling closest to that year for each country and ‘lines-up’ the data to the year being estimated by projecting it forwards or backwards.

This lining-up is generally done on the assumption that household incomes or expenditure grow in line with the growth rates observed in national accounts data. You can read more about the interpolation methods used by the World Bank in Chapter 5 of the Poverty and Inequality Platform Methodology Handbook.

How does the data account for inflation and for differences in the cost of living across countries?

To account for inflation and price differences across countries, the World Bank’s data is measured in international dollars. This is a hypothetical currency that results from price adjustments across time and place. It is defined as having the same purchasing power as one US-$ would in the United States in a given base year. One int.-$ buys the same quantity of goods and services no matter where or when it is spent.

There are many challenges to making such adjustments and they are far from perfect. Angus Deaton ( Deaton, 2010 ) provides a good discussion of the difficulties involved in price adjustments and how this relates to global poverty measurement.

But in a world where price differences across countries and over time are large it is important to attempt to account for these differences as well as possible, and this is what these adjustments do.

In September 2022, the World Bank updated its methodology, and now uses international-$ expressed in 2017 prices – updated from 2011 prices. This has had little effect on our overall understanding of poverty and inequality around the world. But poverty estimates for particular countries vary somewhat between the old and updated methodology. You can read more about this update in our article From $1.90 to $2.15 a day: the updated International Poverty Line .

To allow for comparisons with the official data now expressed in 2017 international-$ data, the World Bank continues to release its poverty and inequality data expressed in 2011 international-$ as well. We have built a Data Explorer to allow you to compare these, and we make all figures available in terms of both sets of prices in our data download .

Absolute vs relative poverty lines

This dataset provides poverty estimates for a range of absolute and relative poverty lines.

An absolute poverty line represents a fixed standard of living; a threshold that is held constant across time. Within the World Bank’s poverty data, absolute poverty lines also aim to represent a standard of living that is fixed across countries (by converting local currencies to international-$). The International Poverty Line of $2.15 per day (in 2017 international-$) is the best known absolute poverty line and is used by the World Bank and the UN to measure extreme poverty around the world.

The value of relative poverty lines instead rises and falls as average incomes change within a given country. In most cases they are set at a certain fraction of the median income. Because of this, relative poverty can be considered a metric of inequality – it measures how spread out the bottom half of the income distribution is.

The idea behind measuring poverty in relative terms is that a person’s well-being depends not on their own absolute standard of living but on how that standard compares with some reference group, or whether it enables them to participate in the norms and customs of their society. For instance, joining a friend’s birthday celebration without shame might require more resources in a rich society if the norm is to go for an expensive meal out, or give costly presents.

Our dataset includes three commonly-used relative poverty lines: 40%, 50%, and 60% of the median.

Such lines are most commonly used in rich countries, and are the main way poverty is measured by the OECD and the European Union .More recently, relative poverty measures have come to be applied in a global context. The share of people living below 50 per cent of median income is, for instance, one of the UN’s Sustainable Development Goal indicators . And the World Bank now produces estimates of global poverty using a Societal Poverty Line that combines absolute and relative components.

When comparing relative poverty rates around the world, however, it is important to keep in mind that – since average incomes are so far apart – such relative poverty lines relate to very different standards of living in rich and poor countries.

Does the data account for non-market income, such as food grown by subsistence farmers?

Many poor people today, as in the past, rely on subsistence farming rather than a monetary income gained from selling goods or their labor on the market. To take this into account and make a fair comparison of their living standards, the statisticians that produce these figures estimate the monetary value of their home production and add it to their income/expenditure.

Research & Writing

Despite making immense progress against extreme poverty, it is still the reality for every tenth person in the world.

$2.15 a day: the updated International Poverty Line

What does the World Bank’s updated methods mean for our understanding of global poverty?

Global poverty over the long-run

How do we know the history of extreme poverty?

Joe Hasell and Max Roser

Breaking out of the Malthusian trap: How pandemics allow us to understand why our ancestors were stuck in poverty

The short history of global living conditions and why it matters that we know it

Poverty & economic growth.

The economies that are home to the poorest billions of people need to grow if we want global poverty to decline substantially

Global poverty in an unequal world: Who is considered poor in a rich country? And what does this mean for our understanding of global poverty?

What do poor people think about poverty?

More articles on poverty.

Three billion people cannot afford a healthy diet

Hannah Ritchie

Homelessness and poverty in rich countries

Esteban Ortiz-Ospina

Historical poverty reductions: more than a story about ‘free-market capitalism’

Interactive charts on poverty.

Official definitions of poverty in different countries are often not directly comparable due to the different ways poverty is measured. For example, countries account for the size of households in different ways in their poverty measures.

The poverty lines shown here are an approximation of national definitions, harmonized to allow for comparisons across countries. For all countries apart from the US, we take the harmonized poverty line calculated by Jolliffe et al. (2022). These lines are calculated as the international dollar figure which, in the World Bank’s Poverty and Inequality Platform (PIP) data, yields the same poverty rate as the officially reported rate using national definitions in a particular year (around 2017).

For the US, Jolliffe et al. (2022) use the OECD’s published poverty rate – which is measured against a relative poverty line of 50% of the median income. This yields a poverty line of $34.79 (measured using 2017 survey data). This however is not the official definition of poverty adopted in the US. We calculated an alternative harmonized figure for the US national poverty using the same method as Jolliffe et al. (2022), but based instead on the official 2019 poverty rate – as reported by the U.S. Census Bureau.

You can see in detail how we calculated this poverty line in this Google Colabs notebook .

Jolliffe, Dean Mitchell, Daniel Gerszon Mahler, Christoph Lakner, Aziz Atamanov, and Samuel Kofi Tetteh Baah. 2022. Assessing the Impact of the 2017 PPPs on the International Poverty Line and Global Poverty. The World Bank. Available to read at the World Bank here .

Because there is no global survey of incomes, researchers need to rely on available national surveys. Such surveys are designed with cross-country comparability in mind, but because the surveys reflect the circumstances and priorities of individual countries at the time of the survey, there are some important differences. In collating this survey data the World Bank takes steps to harmonize it where possible, but comparability issues remain.

One important issue is that, whilst in most high-income countries the surveys capture people’s incomes, in poorer countries these surveys tend to capture people’s consumption. The two concepts are closely related: the income of a household equals their consumption plus any saving, or minus any borrowing or spending out of savings.

To help communicate the latter, the World Bank produces a variable that groups surveys within each individual country into more comparable ‘spells’ (which we include in our data download ). Our Data Explorer provides the option of viewing the data with these breaks in comparability indicated.

The international-$ is a hypothetical currency that results from price adjustments across time and place. It is defined as having the same purchasing power as one US-$ in a given base year – in this case 2017. One int.-$ buys the same quantity of goods and services no matter where or when it is spent. There are many challenges to making such adjustments and they are far from perfect. But in a world where price differences across countries and over time are large it is important to attempt to account for these differences as well as possible, and this is what these adjustments do. Read more in our article From $1.90 to $2.15 a day: the updated International Poverty Line .

​​According to World Bank data, in 1990 there were 2.00 billion people living in poverty, and in 2019 that had fallen to 0.648 billion. The average fall over the 29 years in between is: (2.00 billion – 0.648 billion)/29 = 46.6 million. Dividing by the number of days (29 x 365) gives the average daily fall: (2.00 billion – 0.648 billion)/(29 x 365) = 128,000. (All figures rounded to 3 significant figures).

The projections are generally made on the assumption that incomes or expenditure grow in line with the growth rates observed in national accounts data. You can read more about the interpolation methods used by the World Bank in Chapter 5 of the Poverty and Inequality Platform Methodology Handbook.

We use the figures presented in the World Bank’s Poverty and Shared Prosperity 2022 report. Earlier estimates were also published in Lakner, C., Mahler, D.G., Negre, M. et al. How much does reducing inequality matter for global poverty?. J Econ Inequal (2022). https://doi.org/10.1007/s10888-021-09510-w . Available online here .

Earlier estimates were also published in Lakner, C., Mahler, D.G., Negre, M. et al. How much does reducing inequality matter for global poverty?. J Econ Inequal (2022). https://doi.org/10.1007/s10888-021-09510-w . Available online here .

The figures are taken from a World Bank blog post by Nishant Yonzan, Christoph Lakner and Daniel Gerszon Mahler. The post builds on and updates the estimates published by Lakner et al. (2022).In September 2022, the World Bank changed from using 2011 international-$ to 2017 international-$ in the measurement of global poverty. The International Poverty Line used by the World Bank and the UN to define extreme poverty was accordingly updated from $1.90 a day (in 2011 prices) to $2.15 (in 2017 prices).In order to match up to the projected figures, the extreme poverty estimates shown here relate to a previous release of the World Bank’s data using data expressed in 2011 prices, which vary slightly from the latest data in 2017 prices. You can read more about this change and how it affected the World Bank estimates of poverty in our article From $1.90 to $2.15 a day: the updated International Poverty Line .Lakner, C., Mahler, D.G., Negre, M. et al. How much does reducing inequality matter for global poverty?. J Econ Inequal (2022). https://doi.org/10.1007/s10888-021-09510-w . Available online here .

We use the figures provided in the blog post, which extend the methods presented in Lakner et al. (2022).Lakner, C., Mahler, D.G., Negre, M. et al. How much does reducing inequality matter for global poverty?. J Econ Inequal (2022). https://doi.org/10.1007/s10888-021-09510-w . Available online here .

Shown are those countries with a decline of more than 30 percentage points over a period of 15 years or more.There are a number of ways in which comparability across the different household surveys on which this data is based can be limited. These affect comparisons both across countries and within individual countries over time.The World Bank’s Poverty and Inequality Platform Methodology Handbook provides a good summary of the comparability and data quality issues affecting this data and how it tries to address them. In collating this survey data the World Bank takes a range of steps to harmonize it where possible, but comparability issues remain. To help communicate the latter, the World Bank produces a variable that groups surveys within each individual country into more comparable ‘spells’. Our Data Explorer provides the option of viewing the data with these breaks in comparability indicated.

You can read more about how the World Bank sets these higher poverty lines, as well as the International Poverty Line against which it measures extreme poverty, in our article From $1.90 to $2.15 a day: the updated International Poverty Line . To the three poverty lines adopted officially by the World Bank – $2.15, $3.65 and $6.85 – we add a higher line broadly consistent with definitions of poverty in high income countries. See our article Global poverty in an unequal world: Who is considered poor in a rich country? And what does this mean for our understanding of global poverty?

For details of the methods used to produce the long-run poverty data see, Moatsos, M. (2021). Global extreme poverty: Present and past since 1820. In van Zanden, Rijpma, Malinowski and Mira d’Ercole (eds.) How Was Life? Volume II: New Perspectives on Well-Being and Global Inequality since 1820. Available from the OECD here .

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• Published: 11 June 2019

Religion and poverty

• Gottfried Schweiger 1  

Palgrave Communications volume  5 , Article number:  59 ( 2019 ) Cite this article

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• Development studies
• Social policy

A Correction to this article was published on 29 August 2019

This article has been updated

Religion and poverty are two of the world’s most enduring social and cultural phenomena. They have a long and eventful history, and are not separate from one another, but closely interrelated: on the one hand, there is a long tradition of religiously motivated poverty; on the other hand, giving to the poor is often seen as a religious duty. In recent years, faith-based organisations have been recognised in research as an important factor in global poverty reduction. This comment surveys some of the key areas of enquiry and debate focused on exploring the connection between religion and poverty.

Introduction

Religion and poverty are two of the world’s most enduring social and cultural phenomena. They have a long and eventful history, and are closely interrelated: for instance, on the one hand, there is a long tradition of religiously motivated poverty; on the other hand, giving to the poor is often seen as a religious duty. At least three lines of research can be distinguished in order to understand the connection between religion and poverty:

What role does religion and religious affiliation play in the socio-economic status of populations, and what are the reasons for any influences?

What role do religion and faith play in the daily lives of people in overcoming their poverty and in how they view themselves and society?

What role do religious and faith-based organisations play in fighting poverty and engaging with the poor?

In recent years diverging trends in the relationship between religion and society have emerged. While in some parts of the world secular and post-secular thinking now shape and supplant the role and place of religion in the public sphere and in social life, in other areas, religious and faith-based norms and practices are still prominent. A case in point concerns religious-based conflicts over social status and access to resources and the differentiation of socio-economic inequalities along religious lines, an example being the experiences of Islamic minorities in some Western European countries, which are traditionally Christian.

Against such a background, religion is seen often both as the target of criticism for legitimising inequalities and injustices such as poverty, as well as a driver for potential change and empowerment.

Religion and the lives of the poor

A number of important questions are worth exploring Footnote 1 . First, to what extent are religion and poverty connected at the demographic level (Keister, 2011 ; Thorat, 2010 ; Hoverd et al., 2013 )? Are members of certain religions more affected by poverty than others? In which social and geographical areas is this the case and why? What historical developments, which combine religious affiliation and poverty, have become entrenched at the social level? Are there other socio-economic characteristics that connect religion and poverty (for instance, that certain religions are mainly lived by migrants)? Is the link between religion and poverty consequently due to other socio-economic factors, and is religious belonging a random characteristic? In exploring such questions it is important that lived religious practice be distinguished from the mere belonging to a religion, and in both cases local characteristics have to be taken into account in each case. After all, religions, especially the ‘great world religions’, are extremely diverse in themselves and the composition of their adherents is inevitably heterogeneous. A case in point concerns the relationship between religious affiliation and beliefs about the actual causes of poverty. A study conducted in the United States (Hunt, 2002 ) showed that “religious factors” have a significant influence on the assumed causes of poverty and whether this is explained as “individualistic”, “structuralist” or “fatalistic”.

Questions also arise about the role of religion in the lives of poor people (Sullivan, 2011 ; Yurdakul and Atik, 2016 ; Puffer et al., 2012 ; Dillen and Van Hoof, 2016 ; Rogers and Konieczny, 2018 ). First, it seems trivial to note that religions (which can be understood as complex cultural practices and belief systems) can sometimes play an important role in the lives of poor people to help them understand themselves and interpret the world around them, their social and economic position, and their immediate society. For example a recent study (Hoverd and Sibley, 2013 ) examining a representative sample in New Zealand showed that religious people living in deprived neighbourhoods have higher subjective well-being than their non-religious neighbours living in the same area. Under impoverished conditions, the difference in well-being between religious and non-religious people is evident, while in affluent neighbourhoods, subjective well-being was high regardless of religiousness.

All religions have something to say about poverty, and other issues related to social inequality, and offer implicit and explicit interpretative templates (Beyers, 2014 ). Religions can relieve and burden, they can stand against poverty and legitimise resistance, but they can also justify inequalities, poverty and exploitation. It is the case that religious belief systems can frequently be understood in different ways and that they can produce texts, discourses and practices that can be interpreted multifariously. For researchers, and especially for those people and institutions that are engaged in poverty alleviation, the potential impact of religions—whether positive or negative—is clearly of importance and interest.

Religion and the alleviation of poverty

In recent years extensive research has been undertaken to explore the extent to which religions can contribute to poverty reduction. At the micro level, this may be related to the role of religion in the everyday lives of those in poverty, and the formation of norms and practices—for example, when it turns out that religiosity, or even belonging to a particular religion, has the potential to alleviate poverty, such as by acting on it at the motivational level and encouraging people to try to break out of poverty rather than submit to it. However, the focus of most research tends to be on those who fight poverty— through philanthropic activities, in faith-based organisations (FBO) and via other outlets. Here, too, a distinction can be made between different levels (e.g., a local soup kitchen, versus, a global confederation of relief, development and social service, such as Caritas), practices and social and geographical areas of action.

Individuals’ motivations to work with poor communities—in whatever form, be it charitable, professional or political—can be founded on and inspired by religious beliefs. In many religions, helping poor and marginalised people has a long tradition as a form of lived faith. Giving alms to those in need, for example, often becomes part of a believing Muslim character and one of the five pillars of the Islamic way of life (Ali and Hatta, 2014 ; Raimi et al., 2014 ). Zakat is considered a compulsory almosis, which means that it is a duty for all who have received their belongings from God to help the needy members of the community. In Christianity, the support of the poor by wealthy individuals, monasteries and the church is widespread and can be traced back to the faith’s origins (Holman, 2009 ). The relationship between the help offered by an individual or at the level of ‘the church’, on the one hand, and the establishment of state support programmes and social rights, on the other hand, is interpreted inconsistently and differently in religious traditions. At the level of organisations and institutions, commitment to poverty alleviation can be bundled, channelled and institutionalised, thereby becoming more than the sum of any individual parts.

Religious and faith-based social organisations, as well as churches and congregations, are engaged in a variety of ways in poverty reduction and the provision of social and health services and assistance (Furness and Gilligan, 2012 ; Thornton et al. 2012 ; Tomalin, 2012 ; Göçmen, 2013 ). They do this both in the developed countries of the global North and in the developing countries of the global South, where different forms of organisation and degrees of institutionalisation and internationalisation can be found. For example, a study involving case studies in Indonesia, Fiji and Samoa (Thornton, Sakai, and Hassall, 2012 ) showed that the contribution of religious groups in providing disaster relief and welfare services to their members and advocacy for the poor is often present but not always comprehensive or positive. The influence of religious groups in the public sphere and as institutions can also exacerbate unresolved tensions between different ethnic and secular groups. However, given the impact of limited state capacity, natural disasters and climate change, there is a clear need for effective partnerships between governments and religious groups to ensure the efficient and sustainable delivery of social services and to bring about social change for the benefit of those in poverty. Among other things, FBOs differ greatly in their size and level of professionalisation. Some are well connected global players with highly professional structures and many resources, while others are local initiatives and smaller bodies (e.g., churches) with little infrastructure. In any case, FBOs have established themselves as important actors in the field of poverty alleviation on a global scale and became important partners for other NGOs and government institutions.

The role of religion in the fight against poverty is by no means uncontroversial and conflict-free (whether within organisations or among their religious sponsors) as well as in the theological discourses within these religions. To what extent religion should be socially active and how this can be justified within religion and theology continues to be a subject of vibrant debate (Clarke, 2011 ; Togarasei, 2011 ; Noble, 2014 ; Rajkumar, 2016 ).

Change history

29 august 2019.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

See the research collection related to this article on ‘Poverty and Religion’: https://www.nature.com/collections/dxkjhtslmk

Ali I, Hatta ZA (2014) Zakat as a poverty reduction mechanism among the Muslim community: case study of Bangladesh, Malaysia, and Indonesia. Asian Soc Work Policy Rev 8(1):59–70. https://doi.org/10.1111/aswp.12025

Article   Google Scholar  

Beyers J (2014) The effect of religion on poverty. HTS Theol Stud 70:01–10

Google Scholar  

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Thursday, September 9, 2010

A hypothesis on poverty.

Destitution is a process in political economy. It is not simply that the technical requirements for labor processes require some kinds of bodies to be denied access [...] It is not simply that revenue for social sector spending is simultaneously squeezed, and thus eligibility for social protection by the state will need to be restricted (Russell and Malhotra, 2001). It is also that the exclusion of people from exploitation is culturally legitimated; society actively allows oppressive practice and, it is argued here, the state is often complicit in this process.

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Main article content, the poverty hypothesis and intergenerational transmission of child labor: evidence from ghana, victoria nyarkoah sam.

This study seeks to find evidence to support the claim that Child labor in Ghana is  mainly a poverty phenomenon and follows an inter-generational pattern. The two  econometric approaches used show that poor households are more likely to send their  children out to work. Furthermore, parents are more likely to send their children out to  work if they were child laborers themselves. The study recommends that policy should  focus on the reduction of poverty since it is a major determinant of child labor, this will  automatically prevent the perpetuation of child labor into the next generation.

Keywords : Poverty Hypothesis, Intergenerational Transmission, Child Labor,  Univariate Logit Model, Bivariate Probit Model, Ghana

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Household financial literacy and relative poverty: An analysis of the psychology of poverty and market participation

Shanping wang.

1 Business School, Hunan Normal University, Changsha, China

2 School of Mathematics and Statistics, Hunan Normal University, Changsha, China

3 School of Electronic Information, Hunan First Normal University, Changsha, China

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The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Financial literacy is the significant human capital factor affecting people's ability to obtain financial services. Evaluating the relationship between financial literacy and relative poverty is of great significance to poverty reduction. This study investigated the impacts of financial literacy on relative poverty from the perspective of poverty psychology and market participation using data from the 2017, 2019 China Household Finance Survey (CHFS). The empirical findings showed that financial literacy can alleviate relative household poverty through household participation in entrepreneurial activities, commercial insurance participation and the choice of lending channels. Financial literacy has significant poverty reduction effect on households of continuous operation, reduces the likelihood of exiting operation. Further discussion showed that the poverty reduction effect of financial literacy is more pronounced among households with higher levels of financial literacy, under the age of sixty, low levels of indebtedness and in the eastern region. Our study provides empirical evidence for encouraging market participation and promoting financial literacy and provide valuable recommendations for the policymaker to improve poverty reduction effect in the developing country context.

Introduction

Poverty has been a top social issue in the world, and the 2030 Agenda for Sustainable Development was officially adopted at the United Nations Sustainable Development Summit, where “eradicating poverty in all its forms” is the first of many goals (Tollefson, 2015 ; Li et al., 2016 ). However, the issue of poverty is very complex. With the expansion of the concept and application of poverty academics have gradually shifted from a focus on absolute poverty to relative poverty. Absolute poverty generally refers to a household income is insufficient to maintain minimum subsistence conditions, falling into absolute material deprivation. Unlike absolute poverty, relative poverty refers to people living below the average level of other groups in society. The problem of relative poverty is somewhat complex and dynamic (Wan et al., 2021 ). First, relative poverty is related to the absolute poverty line set by countries and regions. If the poverty line of the World Bank is taken as the standard, China will still have large number of poor people. Second, the development trend of poverty is dynamic. Solving the problem of relative poverty not only focuses on the income of poor groups, but also pays attention to cultivating the endogenous development capacity of poor groups (Capacity Development Group, 2006 ). Therefore, how to continue to effectively promote poverty governance and cultivate the endogenous development motivation of poor households, so that households can sustainably increase their income and get rid of poverty is an important issue for the future governance of poverty.

Financial literacy, which is an important human capital factor, specifically refers to people's comprehensive ability to master the basic economic knowledge and financial concepts to manage and allocate funding resources to achieve household benefits through financial services (Atkinson and Messy, 2011 ). A new financial supply system has been developed through the close combination of Internet communication technologies and financial supply, which improves the breadth of financial coverage and the innovation of financial services goods (Reboul et al., 2021 ). Families with a certain level of financial literacy can obtain development opportunities under the background of digital finance and play a crucial role in the governance of relative poverty. However, according to the survey data, the financial literacy of residents in many countries and regions in the world is generally low. For example, Disney and Gathergood ( 2013 ) found in the UK household survey questionnaire database that the questionnaire contained three questions on simple interest, compound interest and minimum repayment, and the results showed that 11% of the respondents got all the answers wrong and only 30% got all the answers right. Klapper et al. ( 2013 ) found that Russia, as a country with rapid growth in consumer lending, only 41% of the respondents could understand the retaliatory interest, and 46% could answer the simple concept of inflation. Lusardi and Tufano ( 2015 ) used the sample of the United States to suggest that only 1/3 of the respondents have a certain understanding of the calculation of compound interest and the details of the use of credit cards. The Brief Report on Consumer Financial Literacy Survey (2021) published by The People's Bank of China shows that, 1 the financial demand and their financial literacy of Chinese consumers are improving. At the same time, the report points out that residents' expectations of financial investment are also irrational, which is prone to irrational investment behavior. If residents have high financial literacy, they can better understand bank lending policies, insurance services and other related financial services, reducing the cost of financial services (Van Rooij et al., 2011 ). When households have access to certain funds and insurance services, they can smooth consumption, participating in Entrepreneurship and lower poverty risk shocks, thereby alleviating poverty. Therefore, the level of financial literacy is directly related to whether households can grasp the income opportunities brought about, thus having an impact on their current livelihood status. This provides a new idea for solving the problem of relative poverty, which is important to improve the quality of poverty reduction and promote regional sustainable poverty alleviation.

Existing research have investigated and achieved various conclusions on ways to increase household income and alleviate relative poverty. From the macro perspective, existing scholars believe that the “Trickle-down effect” of economic development (Dollar and Kraay, 2002 ; Yang et al., 2021 ), inclusive financial development (Ho and Iyke, 2017 ; Kong and Loubere, 2021 ), labor mobility, land transfer (Carvalho et al., 2016 ; Li et al., 2020 ), infrastructure construction and urbanization (Chen et al., 2019 ; Medeiros et al., 2021 ) and other factors alleviate relative poverty. However, studies have also point that while economic growth can explain the decline in poverty rates, it has poor explanatory power and there is no evidence that such growth can spontaneously reduce incidence of poverty (Kakwani and Pernia, 2000 ). In addition, some studies have emphasized the relationship between financial development and poverty, but the findings have not been consistent (Bolarinwa and Akinbobola, 2021 ). It is worth noting that the above studies analyze the impact of external conditions such as policy implementation and macro environment on relative poverty, ignoring the subjective initiative of poor subjects and failing to consider the role of human capital inherent in poor subjects. Although studies have analyzed poverty alleviation of the poor from human capital factors such as education, health, and work experience (Zon and Muysken, 2001 ; Quinn, 2006 ; Bellemare and Bloem, 2018 ; Liu F. et al., 2021 ), little literature has examined household poverty reduction from the perspective of financial literacy.

Some studies have shown that financial literacy has a certain positive impact on the subjective willingness of actors. On the one hand, households with higher financial literacy can enhance the inclusiveness of inclusive finance (Grohmann et al., 2018 ). For instance, increasing access to banking business and microfinance information can improve the availability of financial services (Hasan et al., 2021 ). There are significant effects on household consumption level and consumption inequality (Dinkova et al., 2021 ; Koomson et al., 2021 ), family members' retirement plans (Lusardi and Olivia, 2007 ), and household entrepreneurial behavior (Zhao and Li, 2021 ). On the other hand, financial literacy has a positive effect on financial behavior, such as asset allocation choices (Lusardi et al., 2013 ), financial market participation (Van Rooij et al., 2011 ; Nguyen and Nguyen, 2020 ), financial decision-making (Guiso and Tullio, 2008 ), investment diversification (Guiso and Jappelli, 1998 ), reduction of over-indebtedness (Lusardi and Peter, 2009 ), and credit demand (Lusardi and Peter, 2009 ; Stango and Jonathan, 2009 ). Therefore, improving the financial literacy of family members in their daily participation in production and business processes can make rational and optimal economic decisions to obtain benefits and reduce the incidence of poverty (Lusardi et al., 2013 ; Emara and Mohieldin, 2020 ). Therefore, one aim of this study is to examine the effect of financial literacy on the relative poverty of households.

Improving household financial literacy and achieving poverty alleviation are the results of a combination of economic decisions. Existing literature has studied the improvement of household financial literacy and absolute poverty alleviation from the perspective of household rationality. It is found that financial literacy has a positive impact on alleviating income poverty and asset poverty in rural households (Xu et al., 2021 ). However, there are also literature showing that households with higher financial literacy have a greater likelihood of increasing leverage through financial instruments and overdraft consumption; if the prices of financial assets falls sharply and the overdraft is too large, they will fall into poverty for a long time (Sarthak and Ashish, 2012 ). Most believe that the poverty reduction effect is generated through the rational asset allocation choices of actors (Shan, 2019 ), but did not consider the cultural factors behind financial behavior, i.e., households living in poverty for a long time, after being influenced by some culture, will generate poverty dependence, conservative risk preferences, information barriers and other psychological perceptions of poverty thus triggering severe financial needs of households and self-inhibiting phenomenon of market participation, thus falling into the poverty trap. Therefore, the second purpose of this study is to analyze the internal mechanism of the influence of financial literacy on relative poverty from the perspective of poverty psychology and planned behavior, test the mediating effect and theoretically expand the understanding of the impact mechanism of relative poverty.

Although previous research had confirmed that financial literacy can contribute to poverty alleviation (Shan, 2019 ; Xu et al., 2021 ), this effect is heterogeneous in different household characteristics and regions. Different household characteristics can have an impact on households' financial market participation (Azeem et al., 2017 ; Decerf, 2017 ). Younger household members are more likely to learn basic financial knowledge, cross the consumption threshold of financial services, and be more receptive to financial services and better able to enjoy the benefits of financial development than older people (Calvin et al., 2018 ). Households with higher indebtedness tend to have higher financing constraints and may engage in more irrational economic behavior, making it difficult for households to get rid of poverty quickly (Sarthak and Ashish, 2012 ). Therefore, the third aim of this study is to explore the heterogeneous effects of financial literacy on relative poverty under different household characteristics and regional development levels.

Compared with the existing literature, three contributions to this analysis can be summarized here. First, taking financial literacy as the main human capital factor affecting households' relative poverty enriches the literature exploring the relationship between the two in empirical studies. Some literature believes that family members with certain financial literacy can rationally allocate assets and produce poverty reduction effect from a rational perspective. However, for households living in poverty for a long time, there is a certain degree of poverty psychological cognition. Whether the improvement of household financial literacy can inhibit the occurrence of relative poverty or not is lack of relevant research. From the perspective of poverty psychology theory, our study constructs a theoretical system of financial literacy poverty reduction, which helps to explain how to improve household financial literacy to alleviate the relative poverty. Second, to reveal the inner mechanism of household financial literacy to alleviate relative poverty. Based on the theories of poverty psychology and financial behavior, we verify the role of micro-mechanisms of household financial market participation in financial literacy poverty reduction, provide new ideas for guiding residents to participate in financial markets and thus alleviate relative poverty. Third, we analyze the heterogeneity of the financial literacy on relative poverty, in different household characteristics and regions, and clarify put the boundaries within which the results of our study are valid. In addition, we also hope that this study can help relevant departments to formulate management countermeasures for enhancing residents' financial literacy and stimulating household residents' financial market participation, achieving new breakthroughs in financial literacy poverty reduction.

The remaining sections of this paper are arranged as follows. Section Theoretical background and hypothesis development presents the theoretical link between financial literacy and relative poverty. Section Methodology discusses the methodology, which includes data sources, measurement of key variables and estimation techniques. Section Empirical results and analyses provides contains the findings and analyses, including baseline regression results, endogeneity treatment and robustness tests. Section Analyses of impact mechanisms presents the analyses of impact mechanism and the further analysis. Section Discussion provides discussion and Section Conclusion presents conclusion.

Theoretical background and hypothesis development

When the family has certain material conditions, there has been a shift in poverty governance from absolute poverty to relative poverty. Absolute poverty is usually defined as the difficulty in obtaining income or necessities to meet the basic survival of a household, and the failure to secure basic needs such as housing, utilities, transport, compulsory education and basic health care, relative poverty is identified by setting a poverty line, i.e., 50 or 60% of the median household income. On the other hand, according to Sen ( 1999 ), the main causes of poverty are The deprivation of the household's power and ability to access benefits. Relative poverty is connoted by the term “moderate poverty”, which refers specifically to the difficulty of the household to reach a socially acceptable level due to a lack of social resources and the ability to develop itself (Wu, 2021 ). In the process of alleviating relative poverty, poverty alleviation efforts should focus on building an anti-poverty path based on the capacity building and resource accumulation of households. Therefore, the governance of relative poverty should also start with improving the viable capacity of households to access economic and social development opportunities and thus escape poverty.

It has been shown that the emotional state, social pressure, and other psychological characteristics of poor groups can influence household economic behavior (Guiso and Paiella, 2008 ; Carvalho et al., 2016 ; Haq et al., 2021 ). The theory is generally explained from two perspectives: the behavioral economics and the poverty psychological. The theory of behavioral economics argues that liquidity constraints or background risks under imperfect formal financial markets are seen as an explanatory theoretical mechanism by which poverty affects economic behavior (Gennetian and Shafir, 2015 ; Key, 2022 ). While the poverty psychological theory argues that chronic poverty states may lead individuals to develop psychological characteristics such as negative affect and stress, resulting in poor groups exhibiting poverty dependence due to a lack of initiative, lack of social responsibility. Psychological trap of poverty is that this psychology of poverty will lead to insufficient household participation in financial markets and is not conducive to poverty alleviation (Haushofer and Fehr, 2014 ; Fu et al., 2020 ). Therefore, this paper argues that financially literate can alleviate relative poverty through household participation in entrepreneurial activities by reducing “Poverty dependence”, household commercial insurance participation by improving “Risk appetite”, and household credit access by breaking down “Information barrier” (see Figure 1 ). Therefore, this paper proposes hypothesis 1:

Mechanism of household financial literacy alleviating relative poverty.

• Hypothesis 1: Financial literacy can alleviate relative poverty.

The poorer groups are less resource endowed and less able to develop themselves, and in the long run tend to develop a negative dependency mentality. Families with high financial literacy will the ability to use their knowledge and skills to make reasonable and effective decisions in management of money and resources, have entrepreneurial skills to circumvent negative dependency (Evans and Jovanovic, 1989 ; Santos et al., 2018 ).

According to the Theory of Planned Behavior, behavioral intention is a direct determinant of behavioral implementation, and individual behavioral attitudes and perceptual behavioral control influence individual behavioral intention at different levels (Yang et al., 2020 ). Entrepreneurial intention is a visual representation of the subjective attitudes of potential entrepreneurs regarding entrepreneurial activities and can effectively predict the probability of entrepreneurial behavior. Therefore, entrepreneurial behavior is subject to entrepreneurial intentions, and subjective norms formed by attitudes about investment, financing and risk management behaviors, perceptual behavioral control and perceptions of support and pressure in the external environment combine to influence their entrepreneurial intentions.

Financial literacy can promote household entrepreneurial activity to alleviate relative poverty through the following pathways. First, financial literacy has an impact on household entrepreneurial activity according to the framework of the theory of planned behavior. Households choose entrepreneurial options based on a direct measure of the benefits, costs, and risks. At the same time, entrepreneurship as a form of risky investment can have a direct exclusionary effect on households with low endogenous developmental dynamics and weak human capital. Therefore, financial literacy has a direct impact on individual financial market participation and allocation decisions to different types of assets, as well as on the overall utility of entrepreneurship, and therefore has a direct impact on entrepreneurial choices and the future entrepreneurial intentions of non-entrepreneurial households. Second, financial literacy releases household demand for credit and alleviates credit constraints. Financial constraints on entrepreneurial activity are the primary constraint on residents' entrepreneurial activity (Karaivanov, 2012 ; Weng et al., 2022 ). Improving financial literacy can help households understand various sources of borrowing information, credit market lending policies, and loan processes, reducing their cognitive biases and increasing their chances of successful borrowing (Akudugu et al., 2009 ; Cude et al., 2020 ), thus increasing their willingness to start a business. Third, it is beneficial for households to have the basic skills and qualities needed to carry out entrepreneurial activities (Oggero et al., 2020 ). Higher financial literacy enables better use of financial instruments and improves the current lack of investment opportunities, thus promoting households' participation in market investments (Van Rooij et al., 2011 ; Yang et al., 2022 ) and willingness to start a business (Rugimbana and Oseifuah, 2010 ; Bilal et al., 2021 ). Thus, by improving financial literacy, households build up long-term human capital, reduce “Poverty dependency” and engage in entrepreneurship to generate sustainable income to alleviate relative poverty. Based on this, this paper proposes the following hypothesis:

• Hypothesis 2: Financial literacy alleviates relative poverty by reducing “Poverty dependency” and promoting household participation in entrepreneurial activities.

Financial literacy includes the ability to use financial information and then use financial literacy to plan financially, arrange for retirement and save and accumulate wealth, and is an important piece of human capital that allows individuals to manage their financial resources effectively. Individuals' financial literacy includes irrational financial behavior, such as “Risk appetite”, depending on their cultural background and work experience. In the processes of social finance, the socio-economic environment in which individuals live is changing, financial information channels are diversifying (Gudmunson and Danes, 2011 ; Liu et al., 2022 ), and risk attitudes are changing, and rational financial decisions and behaviors are being made accordingly (Jappelli and Padula, 2013 ; Yin and Yang, 2022 ). Therefore, financial literacy can improve households' subjective attitudes toward financial products that are “Risk appetite”, improve risk management, and protect against the risks of relative poverty.

Mitigating the occurrence of relative household poverty is not only about enhancing the household's ability to sustainably increase income, but also about defending against the risk of the household falling into poverty in the future (Koomson et al., 2020 ). In general, the larger the risk shock, the greater the likelihood that a household will fall into poverty, i.e., its vulnerability, and the more likely it is to fall into poverty when faced with a risk event. Risk attitude is seen to be an individual attribute that changes over time (Roszkowski and Davey, 2010 ; Baláz, 2021 ). On the one hand, financial literacy can change households' risk attitudes and prevent them from falling into poverty by choosing financial instruments such as insurance and credit for risk protection when facing external risks (Urrea and Maldonado, 2011 ; Kwon and Ban, 2021 ). On the other hand, through information analysis and screening of financial products, increasing social trust (Hansen, 2017 ) and risk-taking capacity (Hong et al., 2020 ), for example, by increasing households' willingness to purchase financial insurance, the insurance mechanism will work to help households diversify their risks when they are covered by insurance and other protection, thus reducing the probability of falling into poverty in the future. Based on this, this paper proposes the following hypothesis:

• Hypothesis 3: Financial literacy alleviates relative poverty by improving “Risk appetite” and promoting household commercial insurance participation.

If households lack understanding of the loan products and lending policies, it will lead to a misunderstanding that they cannot access credit and generate demand for credit (Petrick, 2004 ; Howard, 2015 ), and there is “Information barrier”. If household members are aware of credit policies, it will facilitate their formal credit demand and access to formal credit (Akudugu et al., 2009 ; Pak, 2018 ). With the development of financial markets, households can improve their financial literacy in the process of participating in socio-economic markets, breaking down “Information barrier” and optimizing financial decision-making. Therefore, the importance of financial literacy to household financial behavior is increasingly evident, and the lack of financial literacy can be an important factor in the lack of demand for credit and demand-based credit constraints among households (Sol Murta and Miguel Gama, 2022 ).

This paper argues that improved financial literacy can break down “Information barrier” and facilitate households' access to credit, alleviating the incidence of relative poverty. First, improved financial literacy can help households to increase their understanding of credit market policies and procedures and reduce their cognitive biases, thereby increasing their willingness to borrow from formal financial institutions and their demand for formal credit. Families' understanding of the loan information from various channels will improve their probability of loan success (Sol Murta and Miguel Gama, 2022 ). It allows households to have some funds to avoid falling into poverty in case of external risk shocks or when they undertake their own financial activities. Second, increased levels of financial literacy help households to make better use of financial instruments to improve the current lack of innovation and investment opportunities, for example, households become more active in financial market investments (Van Rooij et al., 2011 ; Yang et al., 2022 ) and households gain a share of income. Thirdly, financial literacy drives household financial accumulation (Lusardi et al., 2017 ; Sekita et al., 2022 ), maintains a good credit history, and thus the availability of formal credit is likely to be better, at the same time, it promotes households' “loan application efforts”, i.e., the more financially literate they are, the more likely they are to apply to formal financial institutions. The higher the financial literacy, the more likely the household is to apply for loans from formal financial institutions, which in turn can protect the household from the risk of poverty arising from investment failure and indebtedness (Jitsuchon, 2001 ; Gathergood, 2012 ), and alleviate relative poverty. Based on this, the following hypothesis is proposed:

• Hypothesis 4: Financial literacy alleviates relative poverty by breaking down “Information barrier” and promoting the availability of formal household credit.

Methodology

Sample and data collection.

This paper uses data from China Household Finance Survey (CHFS) in 2017 and 2019. This survey was developed by Southwestern University of Finance and Economics to create a database to investigate the financial behavior of Chinese households. The data were collected from 29 provinces, 345 cities/counties in 2019. The head of the household, as the respondent, answer the questionnaires including items related to demographic characteristics, assets and liabilities, insurance and social security, household expenditures and income, and views on family, marriage, and community governance. The head of the household is the owner of the property of the house and is the family member who knows the most about the household's financial situation. The database can provide panel data analysis for this article.

The original data was pre-processed as follows. As CHFS survey on “financial literacy” did not cover all households, the sample of households with missing indicators was excluded, deleted the family whose head of household is under the age of 16 and over the age of 80, and the outliers of the sample were subjected to an upper and lower 5% tailing process, resulting in a sample size of 8,735 households after pre-processing.

Variables and measures

Dependent variable: relative poverty.

Absolute poverty and relative poverty are the two most common types of poverty. Absolute poverty is defined as falling into absolute material deprivation because a poor household's total income is insufficient to cover basic survival expenses. It is primarily identified by establishing a minimum income or nutrition standard. However, absolute poverty theory cannot explain the persistence of poverty in developed countries (or regions), resulting in a change in the focus and difficulty of poverty governance from addressing absolute poverty to alleviating relative poverty. Relative poverty is a long-term poverty phenomenon that manifests itself primarily in a state of relative material and living conditions relative to others, and a society with abundant material resources does not eliminate the problem of relative poverty (Decerf, 2017 ).

The successful identification of relatively poor households in academics is still in its early stages and follows two basic paradigms, one from a welfare viewpoint, establishing a percentage of median or average income as the relative poverty level, and the other from a socioeconomic perspective (Ravallion and Chen, 2011 ; Chakravarty et al., 2016 ). The viability perspective of poverty is another relative poverty identification paradigm, which contends that relative poverty criteria should detect whether persons lack the potential to survive and socially integrate (Bourguignon and Atkinson, 2000 ). In Latin American nations such as Mexico and Brazil, relative poverty criteria combine income and multidimensional poverty, taking into consideration the level values of various variables such as income, education, and health. This form of identification is practical, but unlike absolute poverty eradication initiatives that focus on fundamental living stability, relative poverty governance focuses on household upward mobility and the opportunity to develop themselves so that they do not fall into poverty in the future. Based on theory of vulnerability as expected poverty (VEP), some scholars have formulated relative poverty standards from the perspective of poverty risk, which has attracted more and more attention in the field of poverty (Dang et al., 2014 ; Hohberg et al., 2018 ).

Therefore, this article measures relative poverty from two viewpoints. The first measure is to define the relative poverty level at US$3.2 per person per day consumption. In 2018, the World Bank established poverty line criteria for developing countries of $1.9 and 3.2 per person per day consumption, existing studies typically use $1.9 as the absolute poverty line, and this paper uses $3.2 as the relative poverty line for households, and after adjusting for purchasing power parity and CPI, which is RMB 4,260 per capita per year as the relative poverty line. If the surveyed household's per person per day consumption is < $3.2, the variable is set to 1, otherwise, it is set to 0. The second measure is to use the vulnerability to poverty to define the relative poverty. One popular approach considers vulnerability as expected poverty (VEP) proposed by Chaudhuri et al. ( 2002 ), i.e., the probability of a household falling into poverty in a future period. Vulnerability to poverty assesses the possibility that a household's income or level of wellbeing will fall below the poverty line if it experiences a risk shock. This indicator indicates changes in the dynamics of poverty and has significant policy consequences (Azeem et al., 2017 ).

It is worth noting that this paper sets a poverty line for household consumption when calculating poverty vulnerability using VEP 2 and vulnerability cutoff based on the incidence of poverty in the current year. Table 1 reports the statistical results of household poverty and the incidence of vulnerability 3 . As can be seen from the table, although absolute poverty has improved considerably in China, the relative poverty and vulnerability rates are still high.

Descriptive statistics of incidence of poverty and vulnerability to poverty.

Explanatory variable: Financial literacy

Financial literacy is the ability of people to acquire basic economic information and financial ideas, manage and allocate resources in order to attain household income through financial services (Atkinson and Messy, 2011 ). The variable “financial literacy” has primarily been quantified in the literature by using dummy variables for household replies to financial questions in questionnaires, i.e., risk diversification, inflation, interest rate and interest compounding (Klapper et al., 2015 ; Grohmann et al., 2018 ).

This paper uses four questions involving financial knowledge and financial behavior from the Chinese Household Finance Survey (CHFS) to examine respondents' financial literacy. Two dummy variables are constructed for each question. The dummy variable corresponding to the first question is 1 if the respondent is “Extremely concerned”, “Very concerned” or “Generally concerned”, otherwise it is 0. The second and third dummy variables indicate whether the question is answered correctly (if the question is answered correctly, set the variable to 1, otherwise it is 0). The dummy variable corresponding to the fourth question is 1 if the respondent is “Project with high-risk and high-return” or “Project with slightly high-risk and slightly high-return”, otherwise it is 0. We used the iterative principal factor method to conduct factor analysis on the four questions and eight variables to produce the financial literacy indicators used in this paper (Van Rooij et al., 2011 ). Table 2 shows the questions designed in the questionnaire among them.

The questions about financial knowledge and financial behavior to examine the financial literacy of the respondents.

The distribution of the financial literacy index and the correlation between the two sub-dimensions of financial literacy are presented in Figure 2 . It can be concluded that the overall financial literacy index is approximately normally distributed. Although there is some positive correlation between financial knowledge and financial behavior, the correlation coefficient between the former and the latter two is not high (correlation coefficient <0.3).

The distribution of the financial literacy index.

Control variables

Control variables are used in regression analysis to reduce the interference of other factors in estimating the primary causal effect. To analyze the influence of household financial literacy on relative poverty more effectively, the effect of other factors on relative poverty must be removed. We adjust for other factors affecting household relative poverty at three levels based on known research findings, individual characteristics, household characteristics and regional development.

Specifically, firstly, individual characteristics variables, including the gender of the household head (Gender, male = 1, female = 0), age of the household head (Age), years of education of the household head (Edu), and marital status of the household head (Marriage, married = 1, unmarried = 0). Secondly, household characteristics variables, including family scale (Family Scale), health status of household members (Health), dependency ratio (Dependency ratio), proportion of family engaged in agricultural labor (Agricultural), proportion of family engaged in non-agricultural labor (Non-agriculture), household income (Income), household net assets (Net asset), and relationship network (Network). Finally, the paper also controls for regional development variables, regional characteristics (Regional, eastern region = 1, central region = 2, and western region = 3) and regional economic development (Economic). Logarithm the following variables, household income, household net worth, and relationship network. Table 3 reports the results of the descriptive statistics of the variables.

Descriptive statistics of the data used in the estimates.

Estimation strategy

Panel regression models always had the following advantages, which could reduce endogeneity induced by unobservable individual heterogeneity and provide more information about individuals' dynamic behavior (Baloch et al., 2020 ; Gallardo, 2020 ). To analyze that how financial literacy affects the relative poverty of households, we primarily generate the following model in this paper.

First, the panel Probit model is established as follows:

Where, poverty i, t is the variable of relative poverty, if the surveyed household's per person per day consumption is < $3.2, the variable is poverty i, t = 1, otherwise, it is set to 0. finlit i indicating the household financial literacy index, Control i, t would be those who affect the relative poverty but are not related to financial literacy, μ i is individual fixed effects in household, λ t is a period fixed effect, ε i t ~ i i d ( 0 , σ 2 ) is random perturbation term, i is different household ( i = 1, 2,…., 10,846), and t is year ( t = 2017, 2019) and α 0 , α 1 and α 2 being the regression coefficients.

Second, the panel model is established as follows:

Where, vulnerability i, t is the variable of relative poverty, the vulnerability to poverty is measured by drawing on vulnerability as expected poverty (VEP) proposed by Chaudhuri et al. ( 2002 ). See the literature for specific calculation steps (Hohberg et al., 2018 ). finlit i indicating the household financial literacy index, Control i would be those who affect the relative poverty but are not related to financial literacy, μ i is individual fixed effects in household, λ t is a period fixed effect, ϵ i , t ~ i i d ( 0 , σ 2 ) is random perturbation term, i is different household ( i =1, 2,…., 10,846), and t is year ( t = 2017, 2019) and β 0 , β 1 , and β 2 being the regression coefficients.

Empirical results and analyses

Benchmark regression results.

Table 4 shows the results of the benchmark regression of household financial literacy on relative poverty. Considering that there is a certain correlation between financial literacy and variables such as household income, household net assets, and relationship network, columns (1) and (3) in Table 4 report the significant negative marginal effect of financial literacy on household relative poverty when the above control variables are not added, indicating that financial literacy helps to reduce the probability of households experiencing relative poverty. In addition, columns (2) and (4) present the complete estimates with the addition of the above control variables, the marginal effect of the financial literacy index decreases, but remains significantly negative at the 5% level and above. A comparison of the results in Table 4 shows that the significance of the coefficients of the key explanatory variables is relatively stable, and that the effect of financial literacy on relative household poverty remains significant even after controlling for other relevant variables, suggesting that household financial literacy alleviates relative poverty and Hypothesis 1 holds.

Benchmark regression: household financial literacy and relative poverty.

*, **, and *** denote significant at 10, 5, and 1% levels, respectively. The standard errors are reported in parentheses .

Poverty reduction effects of financial literacy in different dimensions

Considered that there may be differences in different dimensions of household financial literacy on relative poverty alleviation, this paper further investigates the impact of household financial literacy sub-dimension dimensions on relative poverty. Firstly, columns (1) and (4) in Table 5 show that the effect of household financial knowledge on relative poverty is significantly negative at the 1% level, in other words, increased financial knowledge helps to reduce the probability of relative poverty among households. Secondly, no significant effect of household financial behavior on alleviating relative poverty is obtained from columns (2) and (5). Finally, in columns (3) and (6) of Table 5 , the effects of household financial knowledge and financial behavior on relative poverty are examined simultaneously. The regression results at this point show that financial knowledge continues to have a significant negative effect, while financial behavior no longer has a significant effect. This suggests that there is some variation in the effect of the different dimensions of the household financial literacy index on relative poverty, with the effect of improving household financial knowledge on relative poverty being more significant than that of financial behavior.

Distinguishing different dimensions: the impact of household financial literacy on relative poverty.

*, **, and *** denote significant at 10, 5, and 1 levels, respectively. The standard errors are reported in parentheses .

Endogeneity issue

In the above analysis, benchmark regression may have endogeneity issue due to reverse causality and omitted variables. On the one hand, threshold effect of financial markets may constrain the participation of poor households in financial markets and affect the “Learning by doing” of financial literacy, while non-poor households have more opportunities to participate in financial services and improve their financial literacy, thus there is an inverse causal relationship. On the other hand, respondents' answers to questions related to financial literacy are subjective and may be biased when administering the questionnaire. To alleviate the endogeneity issue, based on Ellis et al. ( 2017 ) and Sol Murta and Miguel Gama ( 2022 ), this paper used the “average of other households' financial literacy indices in the same community” as an instrumental variable. This is justified because respondents can improve their financial literacy by interacting with other households in the same community, and the financial literacy index of other households in the same community does not directly affect the poverty status of the household. Thus, the instrumental variable satisfies the relevance and exogeneity condition.

Table 6 reports regression results of using the instrumental variable. Column (1) and (2) shows the results of estimation using Two-stage Probit model and instrumental variable. The financial literacy index is an endogenous variable, the one-stage regression F-value and KP rk LM-value confirm that the instrumental variables are appropriate. The marginal effect of the financial literacy index increases after accounting for endogeneity, indicating that not considering endogeneity issues would underestimate the impact of financial literacy. Further, columns (3) and (4) are estimated using 2SLS, and financial literacy significantly reduces relative household poverty, with a smaller regression coefficient than when endogeneity is not considered. To increase the exogeneity of the instrumental variables, column (5) and (6) add community variables, such as community disposable income per capita, share of business and industry households, we obtain largely consistent findings. In summary, instrumental variable estimate results show that household financial literacy still significantly reduces relative poverty, while ignoring the endogeneity issue underestimates the impact of financial literacy.

Estimation results of using the instrumental variable.

**, and *** denote significant at 5% and 1% levels, respectively. The standard errors are reported in parentheses .

Robustness tests

To test the robustness of the benchmark regression results, firstly, the measure of relative poverty was replaced. Robustness tests were conducted using alternative relative poverty lines and vulnerability cutoff. Based on Rippin ( 2016 ), 70% of net income per capita and net household assets are used as the new relative poverty line. At the same time, we use the 50% vulnerability line for the test, and columns (1), (2), and (3) in Table 7 show that the findings obtained remain consistent with the previous ones. Secondly, the measure of financial literacy was replaced. The regression results are estimated using equal weighting method to measure the financial literacy index and the results in columns (4) and (5) indicate that the findings are consistent with those previously obtained. The paper then replaces the sample set 4 . The results in columns (6) and (7) remain unchanged, as the four municipalities are removed from the original sample. Finally, the estimation model is replaced. Given that there is a correlation between poverty and vulnerability, and that vulnerability is usually higher for households in deep poverty, this paper used Bivariate Probit model to test the poverty-reducing effects of financial literacy, and the results in columns (8) and (9) show that the basic findings remain unchanged.

Robustness tests: substitution variables, sample size, and estimation model.

**, and *** denote significant at 5% and 1% levels, respectively .

Analyses of impact mechanisms

Promoting household participation in entrepreneurial activities.

According to Hypothesis 2, financial literacy alleviates relative poverty by eliminating the “Poverty dependency” effect and by promoting household participation in entrepreneurial activities. The mechanism of household participation in entrepreneurship involves two main issues: entrepreneurial activity reduces relative household poverty and financial literacy increases household willingness to start a business. This paper follows this line of thought and extends the analysis in two ways. Firstly, the sample is divided into two groups of poor and non-poor households to discuss the differential impact of financial literacy on entrepreneurship among different types of poor households. Second, dummy variables are set based on household entrepreneurship status to investigate the impact of entrepreneurial persistence on relative poverty and how financial literacy affects household entrepreneurial persistence 5 .

Using the instrumental variable from the previous section and measuring household participation in entrepreneurship based on the CHFS questionnaire “whether the household is involved in business or industry”, the variable is equal to 1 if the respondent answered “Yes” and 0 otherwise if the respondent answered “No”. In this paper, we focus on non-farm entrepreneurship. Table 8 reports the results of the estimation, where column (1) shows that household involvement in entrepreneurship helps to reduce the likelihood of poverty in the household. Columns (2), (3), and (4) show that financial literacy significantly contributes to household participation in entrepreneurship and has a greater positive effect on non-poor households. Further, columns (5) and (6) also yield that household continuation in business can significantly reduce relative poverty, with insignificant effects for initial business and exit from business, while financial literacy can significantly reduce the likelihood of household exit from business. The reason for this may be that the poverty alleviation effect of new business start-up households is insignificant compared to that of continuing households due to the short duration of the business. Exiting households also fail to improve household poverty when they exit the business due to capital, tax burden or poor business performance. In summary, financial literacy can play a positive role in alleviating relative household poverty by promoting household participation in entrepreneurship. On the one hand, financial literacy has a greater impact on promoting entrepreneurship among non-poor households, and on the other hand, financial literacy can significantly reduce the likelihood of households withdrawing from business. Therefore, Hypothesis 2 holds.

Test on the impact mechanism of financial literacy on relative poverty (2SLS estimation).

**, and *** denote significant at 5% and 1% levels, respectively. The standard error of clustering at the provincial level is in parentheses .

Commercial insurance participation

Financial literacy promotes participation in commercial insurance by improving the “Risk appetite”, which protects households from the risk of falling into poverty due to negative shocks. Financial literacy reduces the conservative and risk-averse psychological characteristics of the poor and leads to rational financial decisions, which in turn leads to increased risk tolerance through participation in commercial insurance. According to the CHFS questionnaire “whether the household buys commercial insurance”, the variable is equal to 1 if the respondent answered “Yes” and 0 otherwise if the respondent answered “No”. Using the instrumental variable from the previous section, the results are reported in Table 9 , where columns (1) and (2) indicate that financial literacy significantly contributes to households' willingness to participate in commercial insurance, and that participation in commercial insurance significantly reduces household vulnerability to poverty. Hypothesis 3 holds.

*** denote significant at 1% levels. The standard error of clustering at the provincial level is in parentheses .

The choice of lending channels

The choice of loan channel is also an important factor affecting household poverty. Poor households suffer from cognitive biases due to information barriers. Financial literacy promotes household financial accumulation, maintains good credit, promotes “Loan-seeking efforts”, thus enhances formal credit channel choice. According to the CHFS questionnaire “whether the household choose formal loan channels”, the variable is equal to 1 if the respondent answered “Yes” and 0 otherwise if the respondent answered “No”. Table 9 reports the results of regressions using instrumental variables. Column (3) and (4) shows that financial literacy has a significant positive effect on households' preference for formal loan channels, which in turn reduces household poverty vulnerability. In summary, financial literacy can mitigate household poverty vulnerability by increasing residents' risk resilience, mainly by influencing their choice to participate in formal loan channels. Hypothesis 4 holds.

Further analysis

Robustness tests have been used above to show that financial literacy is indeed an important factor influencing households' relative poverty, and that financial literacy affects relative poverty through the institutional pathways of household participation in entrepreneurship activities, commercial insurance participation and formal loan channels. However, the following questions need further analysis. Firstly, is there a difference in the effect of financial literacy on household poverty reduction by level of financial literacy? Secondly, what are the micro effects of financial literacy on poverty alleviation by factors such as household structure, debt level and regional location? These are all questions that require further analysis.

Grouping of different levels of financial literacy

In this paper, households are divided into low level financial literacy group, medium level financial literacy group, medium high level financial literacy group and high-level financial literacy group according to the financial literacy index to study the impact of different levels of financial literacy of households on vulnerability to poverty. Columns (1)–(4) of Table 10 present the regression results. It suggested that financial literacy in different household groups can significantly reduce household poverty vulnerability at levels above 5%, and that the poverty reduction effect is more pronounced for households with high levels of financial literacy.

Further analysis: different financial literacy groups.

Heterogeneity analysis: Different household characteristics and regional locations

This section presents a heterogeneous analysis of the microeconomic effects of financial literacy in alleviating relative household poverty in terms of household characteristics, debt level and regional location. The results of the heterogeneity analysis regressions are reported in Table 11 .

Heterogeneity analysis: different households characteristics and regional location.

Firstly, based on the grouping of household characteristics, the full sample was divided into two groups according to the criterion of “presence of persons aged 60 years old and over in the household”. The results of the sample regressions are presented in columns (1), (2), (7), and (8) of Table 11 . Except for the insignificant coefficient on financial literacy in column (2), the coefficient on financial literacy in all cases is significant at the 5% level or higher, with a negative sign, suggesting that increased financial literacy is more likely to alleviate the relative poverty of the “under the age of sixty” sample. The possible explanation for this is that the development of digital finance based on the Internet and smartphones has continued to raise the threshold of access to financial services, while older people, who mostly lack the ability to use computers and mobile phones, are more receptive to financial services than younger and middle-aged groups and are better able to enjoy the benefits of financial development.

Secondly, based on the grouping of household debt level, the entire sample was divided into two groups: including households of the low debt level and households of the high debt level, using “whether household debt level is higher than the average level of the community in which the sample is located” as the grouping criterion for measuring the level of household debt. Columns (3), (4), (9), and (10) of Table 11 show the results of the sub-sample regressions based on household indebtedness. The coefficients on financial literacy in columns (4) and (10) are not significant, while the coefficients on financial literacy in columns (3) and (9) are significant at the 1% level with a negative sign, indicating that financial literacy is more likely to reduce poverty among households with low levels of debt. Possible explanations are that groups with higher levels of indebtedness tend to have greater financing constraints, lower household income and a higher risk of households falling into poverty. At the same time, households with high levels of debt are likely to engage in more irrational economic behavior, making it difficult for them to move out of poverty quickly.

Finally, the paper uses “whether the sample household belongs to the eastern province” as the grouping criterion for regional locations, divides the full sample into “eastern region” and “central and western region”. Columns (5), (6), (11), and (12) of Table 11 show the results of the sub-samples regressions based on regional location, where the coefficients of financial literacy are all significantly negative at the 1% level, and the coefficients of the samples of “eastern region” are larger than those of the samples of “central and western region”. The regression analysis suggests that increased financial literacy is more likely to alleviate the relative poverty of households in the eastern region of China.

Financial literacy, an important human capital characteristic for households, is significant for alleviating relative poverty. Based on theories of poverty psychology, behavioral finance and vulnerability as expected poverty (VEP), we used panel model, an instrumental variables model, and the Probit model to investigate the impact of financial literacy on relative poverty. The empirical findings suggest that household financial literacy has the effect of alleviating poverty, which is consistent with previous findings (Xu et al., 2021 ), and the mechanism analysis further shows that financial literacy reduces relative poverty through promoting household participation in entrepreneurial activities, commercial insurance participation, and the choice of lending channels. The reduction poverty effect of financial literacy is more significant for “high levels of financial literacy”, “under the age of sixty”, “low levels of indebtedness”, and “households in the eastern”. Implementing multi-channel financial literacy enhancement programs to effectively improve the scope of household financial literacy, continuously improving the efficiency and quality of the household entrepreneurial environment, and actively promoting the diversification of financial products and innovation in service delivery are policy implications of our findings. The results of this paper have implications for other countries. Detailed analysis are as follows.

First, the results of benchmark regression indicate that household financial literacy can alleviate relative poverty. Unlike earlier studies, this paper seeks to explain the empirical findings using theories of poverty psychology and behavioral finance. Chronic poverty can lead to irrational social cognitive features such as negative emotions, stress, and cognitive biases, as well as the construction of self-reinforcing mechanisms of poverty, it can lead households into the poverty trap (Haushofer and Fehr, 2014 ). Financial literacy might have a positive impact on the subjective initiative of family members. On the one hand, it can encourage households to improve their understanding of basic financial services and work toward achieving benefits for themselves (Grohmann et al., 2018 ; Hasan et al., 2021 ). On the other hand, it can have a positive impact on family members' financial behaviors such as asset allocation decisions, financial decisions, and debt reduction (Lusardi and Peter, 2009 ; Lusardi and Tufano, 2015 ), breaking the psychological trap of poverty and increasing income and self-development capacity to alleviate relative poverty.

Second, focus on the control variables, as for household income, significant strong negative correlations appeared. The growth of the income can decrease the relative poverty, which are identical to the previous conclusions (Luo, 2022 ). Household income can meet the needs of family members for daily life goods, it effectively promotes the accumulation of human capital such as education and labor skills of family members, increases their own development ability, and reduces the incidence of poverty by obtaining a continuous income after participating in social labor (Shan, 2019 ). Household net worth and relationship networks can also alleviate relative poverty, and the building of physical and social capital in the household has a limited effect on preventing poverty but can help to reduce the probability of future poverty (Liu et al., 2019 ). The years of education of the household head, marital status of the household head, health status of household members, proportion of family engaged in non-agricultural labor, and regional economic development show the positive effect on household relative poverty with significance level (Zon and Muysken, 2001 ; Li et al., 2016 ; Azeem et al., 2017 ; Decerf, 2017 ). In compared to earlier research, the relative poverty rate of households is higher when the gender of the household head is male, possibly because men have a higher appetite for risk, increasing the likelihood of future household poverty, and the male do not have better saving habits than women and are weaker in resisting the risk of poverty (Almenberg and Dreber, 2015 ; Bannier and Neubert, 2016 ). Families with larger family size and higher dependency ratio can raise the economic burden on the household (Bellemare and Bloem, 2018 ). Households with a high proportion of agricultural labor may get less income and are more likely to fall into poverty.

Finally, the empirical findings showed that financial literacy can alleviate relative poverty through promoting household participation in entrepreneurial activities, commercial insurance participation, and the choice of lending channels. There are possible reasons for the above results. (1) According to the theory of planned behavior, households with higher financial literacy can actively participate in financial markets and various types of asset allocation and encourage household participation in entrepreneurial activities (Yang et al., 2020 ). Concurrently, improved financial literacy enables households to acquire the fundamental skills and literacy required to engage in entrepreneurial activities, resulting in long-term human capital accumulation (Liu M. et al., 2021 ), and household participation in entrepreneurship generates sustainable income to alleviate relative poverty. (2) According to theory of vulnerability as expected poverty (VEP), alleviating relative household poverty necessitates not just improving the households' ability to stabilize income, but also having the ability to resist future poverty risks. Families with higher financial literacy can change their risk attitudes and choose financial tools like insurance and loans to insulate themselves from external threats and keep their families out of poverty (Koomson et al., 2020 ). Simultaneously, households with higher financial literacy analyze information and evaluate financial products in boosting social trust and risk-taking abilities, as well as household willingness to purchase financial insurance (Kwon and Ban, 2021 ), and when these safeguards are obtained, they assist households in diversify risks and decrease the probability of future poverty. (3) According to Behrman's theoretical analysis of educational returns, financial literacy can influence the “Learning by doing” process of household participation in financial markets (Behrman et al., 2012 ; Lusardi et al., 2017 ), assisting households in understanding credit policies and lending processes in attempt to decrease cognitive biases. This may increase households' propensity to lend from formal financial institutions as well as their demand for formal credit (Rugimbana and Oseifuah, 2010 ; Bilal et al., 2021 ). Meanwhile, financial literacy drives household financial accumulation, maintains a good credit history, increases loan success chances, and with access to certain funds, households are strong enough to withstand the risk of poverty due to shocks from unknown risk factors such as investment failure and debt, alleviating relative poverty.

Financial literacy significantly reduced the relative poverty of households, while financial knowledge had a more significant effect on poverty reduction. Using 2017 and 2019 China Household Finance Survey (CHFS), we analyze some mechanism effects, including that financial literacy alleviates relative poverty.

In this study, we measure the relative poverty of household from both static and dynamic perspectives. Based on The World Bank in 2018 set the poverty line criteria for developing countries, we select $3.2 per person per day of consumption for the relative poverty line. In addition, the vulnerability to poverty is measured by drawing on based on vulnerability as expected poverty (VEP) proposed by Chaudhuri et al. ( 2002 ), which reflected the dynamics of relative poverty. We then used factor analysis method to construct a household financial literacy index (including financial knowledge and financial behavior) based on the CHFS questionnaire. The empirical results show that financial literacy alleviates relative poverty through promoting household participation in entrepreneurial activities, commercial insurance participation and the choice of lending channels.

Further analysis shows that the poverty reduction effect is more pronounced for households with high levels of financial literacy. Financial literacy promotes household participation in business and industry, and continuous operation significantly reduces household relative poverty, while the effects of new operation and exit operation are not significant. The effect of financial literacy on poverty reduction is more pronounced for the households of under the age of sixty, low levels of indebtedness and in the eastern region.

The conclusions of this paper have important policy implications: first, implement a multi-channel financial literacy enhancement program to effectively increase the scope of household financial literacy. Targeting financial education at the elderly and groups with lower educational knowledge, financial literacy can be given full play to poverty reduction by increasing financial literacy education in communities and villages and building comprehensive information service platforms on the internet; enhancing their ability to allocate funds, financial planning, etc. Second, the environment for household entrepreneurship should be continuously improved to enhance the efficiency and quality of entrepreneurship. Financial support should be provided to households with a certain level of financial literacy, combined with tax and fee reductions and other means to increase households' willingness to sustain their businesses and ensure that entrepreneurial activities have a poverty-reducing effect in the long term. Third, focus on the livelihoods of vulnerable households and strengthen their risk management capacity. Improve community and village infrastructure to prevent shocks that lead to widespread exposure of households to vulnerability risks, in addition, actively promote the diversification of financial products and innovation in service delivery methods to provide vulnerable households with basic protection that can withstand certain negative risk shocks.

There are some limitations in this study. First, this study does not use a cross-country sample for empirical analysis. Financial literacy is influenced by tradition culture and educational level, and the level of developing financial literacy differs among countries. Therefore, whether the financial literacy index in this paper is applicable to other countries remains to be studied. Further research using cross-country data for the analysis modifies the bias caused by culture and tradition. Second, we should further select more appropriate instrumental variable. The average financial literacy level and welfare indicators of families will be affected by the level of regional economic development. Especially in urban families, families with similar conditions will choose to live in a community, and the exogenous nature of instrumental variables need further discussion.

Data availability statement

Ethics statement.

Ethical review and approval were not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

Author contributions

SW: introduction, discussion, implications, and conclusion. PC: the concept, design, methods, result analysis, and paper writing. SH: editing, revising, proofreading, and language editing. All authors contributed to the article and approved the submitted version.

This research was funded by the National Social Science Fund of China, Grant Numbers: 20STA058 and 18AJY003.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

1 www.gov.cn/xinwen/2021-09/23/content_5638786.htm

2 In this paper, we used household consumption level to measure vulnerability to poverty. On the one hand, there are often large measurement errors in income data in micro data survey, and consumption data can more accurately reflect Family Welfare (Deaton, 1989 . On the other hand, using income level to calculate poverty vulnerability is difficult to find control variables, and not controlling income variables will lead to serious endogenous problems.

3 In this paper, we used the three-step feasible generalized least squares (FGLS) to estimate the vulnerability of family poverty, see the literature for specific steps (Chaudhuri et al., 2002 ; Hohberg et al., 2018 ).

4 Municipalities directly under the central government have strong particularity in many aspects, such as strategic positioning, spatial status and economic development. In terms of the theme of this study, previous studies have found that the economy of the four municipalities directly under the central government is relatively developed, employment opportunities are relatively sufficient, and residents' entrepreneurial motivation is inhibited (Huang and Qian, 2008 ). To eliminate the possible impact of the sample of municipalities directly under the central government, this study excludes the sample data of Beijing, Shanghai, Tianjin and Chongqing.

5 According to the contents of the questionnaire CHFS 2017 and 2019, families are divided into: continuous operation (the families surveyed twice in a row participated in industrial and commercial operation), new operation (only participated in operation in 2019) and exit operation (only participated in operation in 2014).

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Does capitalism cause poverty?

.chakra .wef-1c7l3mo{-webkit-transition:all 0.15s ease-out;transition:all 0.15s ease-out;cursor:pointer;-webkit-text-decoration:none;text-decoration:none;outline:none;color:inherit;}.chakra .wef-1c7l3mo:hover,.chakra .wef-1c7l3mo[data-hover]{-webkit-text-decoration:underline;text-decoration:underline;}.chakra .wef-1c7l3mo:focus,.chakra .wef-1c7l3mo[data-focus]{box-shadow:0 0 0 3px rgba(168,203,251,0.5);} Ricardo Hausmann

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Capitalism gets blamed for many things nowadays: poverty, inequality, unemployment, even global warming. As Pope Francis said in a recent speech in Bolivia: “This system is by now intolerable: farm workers find it intolerable, laborers find it intolerable, communities find it intolerable, peoples find it intolerable. The earth itself – our sister, Mother Earth, as Saint Francis would say – also finds it intolerable.”

But are the problems that upset Francis the consequence of what he called “unbridled capitalism”? Or are they instead caused by capitalism’s surprising failure to do what was expected of it? Should an agenda to advance social justice be based on bridling capitalism or on eliminating the barriers that thwart its expansion?

The answer in Latin America, Africa, the Middle East, and Asia is obviously the latter. To see this, it is useful to recall how Karl Marx imagined the future.

For Marx, the historic role of capitalism was to reorganize production. Gone would be the family farms, artisan yards, and the “nation of shopkeepers,” as Napoleon is alleged to have scornfully referred to Britain. All these petty bourgeois activities would be plowed over by the equivalent of today’s Zara, Toyota, Airbus, or Walmart.

As a result, the means of production would no longer be owned by those doing the work, as on the family farm or in the craftsman’s workshop, but by “capital.” Workers would possess only their own labor, which they would be forced to exchange for a miserable wage. Nonetheless, they would be more fortunate than the “reserve army of the unemployed” – a pool of idle labor large enough to make others fear losing their job, but small enough not to waste the surplus value that could be extracted by making them work.

With all previous social classes transformed into the working class, and all means of production in the hands of an ever-dwindling group of owners of “capital,” a proletarian revolution would lead humanity to a world of perfect justice: “From each according to his ability, to each according to his needs,” as Marx famously put it.

Clearly, the poet and philosopher Paul Valéry was right: “The future, like everything else, is no longer what it used to be.” But we should not make fun of Marx’s well-known prediction error. After all, as the physicist Niels Bohr wryly noted, “Prediction is difficult, especially about the future.”

We now know that as the ink was drying on the Communist Manifesto, wages in Europe and the United States were beginning a 160-year-long rise, making workers part of the middle class, with cars, mortgages, pensions, and petty bourgeois concerns. Politicians today promise to create jobs – or more opportunities to be exploited by capital – not to take over the means of production.

Capitalism could achieve this transformation because the reorganization of production allowed for an unprecedented increase in productivity. The division of labor within and across firms, which Adam Smith had already envisioned in 1776 as the engine of growth, allowed for a division of knowhow among individuals that permitted the whole to know more than the parts and form ever-growing networks of exchange and collaboration.

A modern corporation has experts in production, design, marketing, sales, finance, accounting, human resource management, logistics, taxes, contracts, and so on. Modern production is not just an accumulation of buildings and equipment owned by Das Kapital and operated mechanically by fungible workers. Instead, it is a coordinated network of people that possess different types of Das Human-Kapital. In the developed world, capitalism did transform almost everyone into a wage laborer, but it also lifted them out of poverty and made them more prosperous than Marx could have imagined.

That was not the only thing Marx got wrong. More surprisingly, the capitalist reorganization of production petered out in the developing world, leaving the vast majority of the labor force outside its control. The numbers are astounding. While only one in nine people in the United States are self-employed, the proportion in India is 19 out of 20. Fewer than one-fifth of workers in Peru are employed by the kind of private businesses that Marx had in mind. In Mexico, about one in three are.

Even within countries, measures of wellbeing are strongly related to the proportion of the labor force employed in capitalist production. In Mexico’s state of Nuevo León, two-thirds of workers are employed by private incorporated businesses, while in Chiapas only one in seven is. No wonder, then, that per capita income is more than nine times higher in Nuevo León than in Chiapas. In Colombia, per capita income in Bogota is four times higher than in Maicao. Unsurprisingly, the share of capitalist employment is six times higher in Bogota.

In poverty-stricken Bolivia, Francis criticized “the mentality of profit at any price, with no concern for social exclusion or the destruction of nature,” along with “a crude and naive trust in the goodness of those wielding economic power and in the sacralized workings of the prevailing economic system.”

But this explanation of capitalism’s failure is wide of the mark. The world’s most profitable companies are not exploiting Bolivia. They are simply not there, because they find the place unprofitable. The developing world’s fundamental problem is that capitalism has not reorganized production and employment in the poorest countries and regions, leaving the bulk of the labor force outside its scope of operation.

As Rafael Di Tella and Robert MacCulloch have shown, the world’s poorest countries are not characterized by naive trust in capitalism, but by utter distrust, which leads to heavy government intervention and regulation of business. Under such conditions, capitalism does not thrive and economies remain poor.

Francis is right to focus attention on the plight of the world’s poorest. Their misery, however, is not the consequence of unbridled capitalism, but of a capitalism that has been bridled in just the wrong way.

This article is published in collaboration with Project Syndicate . Publication does not imply endorsement of views by the World Economic Forum.

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Author: Ricardo Hausmann, a former minister of planning of Venezuela and former Chief Economist of the Inter-American Development Bank, is Professor of the Practice of Economic Development at Harvard University.

Image: A villager harvests rice crop in the field at the village of Karampur, 70 km (43 miles) from Sukkur in Pakistan’s Sindh province August 12, 2010. REUTERS/Akhtar Soomro.

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Louis Freedberg

September 23, 2019, 14 comments.

While racial and ethnic segregation in the nation’s schools is strongly correlated with gaps in academic achievement, the income level of students’ families in a school rather than its racial or ethnic composition account for those gaps, according to a new study.

The study, based on massive amounts of data from schools attended by nearly all of the nation’s black and Hispanic students, was conducted by Sean Reardon, a professor at Stanford University’s Graduate School of Education, and other researchers from Stanford, Pennsylvania State University and St. John’s University in New York City.

Sean Reardon of Stanford University’s Graduate School of Education

Achievement gaps among black, Hispanic and white students, the study found, is “completely accounted for” by the poverty level of students in a school, as measured by the percentage of students who qualify for free and reduced priced meals.

“While racial segregation is important, it’s not the race of one’s classmates that matters,” the researchers concluded in the study released today. “It’s the fact that in America today, racial segregation brings with it very unequal concentrations of students in high and low poverty schools.”

“Differences in exposure to poverty may be more important for the development of achievement gaps than differences in exposure to minority students,” they state. The study looked at student test performance in math and English language arts between the 3rd and 8th grade.

The study looked at what it called de facto segregation in schools, districts and metropolitan areas across the United States with high concentrations of black and Hispanic students, in contrast to the de jure  segregation that occurred in many parts of the United States, especially in the American South, as a result of official laws or ordinances barring access to schools based on race.  

While the study didn’t break down achievement gaps by state or district, it was accompanied by a tool kit that for the first time maps average test scores, how much students’ learning improves each year and trends in test score data for every school and district in the nation. Thus it is possible to drill down into hundreds of districts like Los Angeles Unified , Fresno Unified , West Contra Costa Unified  and thousands more around the country to look at how these districts are doing on a range of indicators related to test scores — and the extent to which performance is improving over time.

The study underscores the consequences of the nation having virtually abandoned efforts to desegregate its schools over the last several decades as courts have lifted desegregation orders, and desegregation has become harder to accomplish as school districts in many metropolitan areas have had a declining share of white students.

This is especially the case in California where the demographic makeup of the schools has changed dramatically in recent decades. In the just completed school year (2018-19), white students made up 24 percent of California’s total enrollment of 6.2 million students, compared to 38 percent 20 years ago. Black students declined from 8.8 percent in 1998-99 to 5.4 percent of the total student enrollment, while enrollment of Latinos increased from 41 percent to 54 percent over the same period, as did that of Asian students, from 8.1 percent to 9.3 percent.

A 2016 report by UCLA’s Civil Rights Project asserted that Latino and black students in California attended some of the most segregated schools in the United States, meaning that they were most likely to attend a school with the lowest proportion of white students.

The researchers point out that efforts to desegregate schools have virtually ceased and instead the focus among school reformers and lawmakers is now primarily on trying to improve the quality of schooling “within a system of schooling that is highly segregated by both race and class.”

Reardon and his colleagues found that the more segregated a school system, the larger the average achievement gap, and that the gaps grow faster during the K-8 grades than in less segregated ones.

The study focused on averages for the entire nation and as a result does not highlight where students and schools are “ beating the odds, ” as described for example in a recent paper by the Learning Policy Institute, or the fact that there are many black and Hispanic students who perform far above average and are outstanding students.

The test scores reflect what the researchers broadly refer to as “educational opportunities,” which include not only what they are taught in school, but learning opportunities in their homes and in neighborhoods, their access to child care, preschool, and after-school programs and a range of other resources typically available to higher income children.

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S Dwyer 3 years ago 3 years ago

Many thanks for research and articles like this one, which debunk the myths about race and academic achievement. Many other studies don’t separate causation from correlation and only perpetuate racist narratives. Keep up the honest work!

Mellanie 5 years ago 5 years ago

Having grown up in the ’60s and now working in an inner city school for 26 years, I guess I was mistaken in my belief that schools in large cities had taken care of the problems of inequality because of family economics. This article tells me that there are still inequalities in schools. I don’t understand why these problems have not been addressed in all this time??!!

Ellen Graham 5 years ago 5 years ago

Zeev Wurman is right and Dr. Conrad is wrong. Home culture and expectations about education are far more critical than any other factor. It's just not politically correct to talk about the massive number of boys in hispanic and black homes without fathers. This does impact students because they themselves have told me. Yes teaching matters and too often, lazy teachers are not held accountable. Part of it is the teach to the test mentality … Read More

Zeev Wurman is right and Dr. Conrad is wrong. Home culture and expectations about education are far more critical than any other factor. It’s just not politically correct to talk about the massive number of boys in hispanic and black homes without fathers. This does impact students because they themselves have told me. Yes teaching matters and too often, lazy teachers are not held accountable. Part of it is the teach to the test mentality that permeates low income schools. In upper class school districts, teachers have more academic freedom. For example, in my school fewer novels are read. I always use whole text but am discouraged from doing so, instead I am pointed in the direction of the horrific Pearson high school English text. I don’t use it and never will.

School has to be relevant but parents also have to set examples. I have had students whose own parents went back to school as adults and this greatly motivated them to do well in school. Parents matter, home culture matters, fathers matter but standardized tests don’t matter and should be done away with.

Bryan Reece 5 years ago 5 years ago

Good article. The relationship between income, race and ethnicity is complex. There are a few universities that continue to promote their diversity statistics but primarily recruit middle and upper income students if color. This needs to be addressed across all education.

Brigitt 5 years ago 5 years ago

I worked in the flatlands of West Contra Costa Unified from 1996-2000. All my students were poor. All my students had free/reduced lunch. When I moved to Southern California, I worked with mostly Hispanic, high poverty students as well. Family life and parent engagement is crucial. Poor children with engaged parents improved academically with me. Poor students who had parents or guardians who did not engage were almost always behind 1-3 grade levels. Research must … Read More

I worked in the flatlands of West Contra Costa Unified from 1996-2000. All my students were poor. All my students had free/reduced lunch. When I moved to Southern California, I worked with mostly Hispanic, high poverty students as well. Family life and parent engagement is crucial. Poor children with engaged parents improved academically with me. Poor students who had parents or guardians who did not engage were almost always behind 1-3 grade levels. Research must be done on not just how poor students of color (white, brown, black) perform in school, but how much time parents spend helping them every night. Discussions they have at the dinner table, family expectations. I’m tired of people “blaming” teachers in these districts or classrooms. Dr. Conrad’s comment about quality of teachers and how these students get new teachers who are not well qualified is a detail. Teachers like myself who work in these schools are and were MAINLY seasoned teachers. Not novices. We attended 101 workshops and meetings in our district, we went on to get master’s and Ph.D’s. Some of us (like myself) are National Board Certified Teachers which is a rigorous certification to receive. Why? Because we are dedicated to help poor WHITE, BLACK, HISPANIC, ASIAN, etc. students. We study data, modify our teaching to accommodate and reach children everyday. It can’t all be because of teachers when we look at the gap. Poverty is a major factor and so is Parent Involvement AND their education.

Tabitha Dell'Angelo 5 years ago 5 years ago

While poverty is a key variable, there is some evidence to suggest that how teachers approach their practice can mediate the effects of poverty. I think it is important to remember that we can make an impact in the spaces where we have access and some ability to create change. see https://blogs.lse.ac.uk/usappblog/2016/04/06/how-teachers-can-mediate-the-impact-of-poverty-in-low-income-schools/

Ariel 5 years ago 5 years ago

I still think it must be a combination of factors that all contribute to the same issue of resource allocation. There’s a reason for higher poverty rates among black and brown students, and it’s being culturally different from the white majority that controls curriculum, staffing, lawmaking, and all aspects of education at the leadership level.

Bill Leiter 5 years ago 5 years ago

Well said Zeev Wurman. The full 60 page report is peppered with complex appearing equations and symbols that few people would understand. And that’s its point I think: to obfuscate and impress. That’s all. Your 5 or 6 sentences posted here contain more actual insight than the whole report. Let’s hope that most people will be able to see it for what it is.

Paul Muench 5 years ago 5 years ago

How is this different than the Coleman Report?

Zeev Wurman 5 years ago 5 years ago

Well, when it was the color of skin that was the supposed determinant of achievement, East-Asian students showed this couldn’t have been the whole story. Now when the argument is that it is poverty, the relative success of "poor" East-Asian students—and there are quite a few of those—show that the new glib explanation is still just that — a glib explanation. Large achievement gaps exist within same schools, and frequently within the same classroom. That … Read More

Well, when it was the color of skin that was the supposed determinant of achievement, East-Asian students showed this couldn’t have been the whole story. Now when the argument is that it is poverty, the relative success of “poor” East-Asian students—and there are quite a few of those—show that the new glib explanation is still just that — a glib explanation.

Large achievement gaps exist within same schools, and frequently within the same classroom. That can’t be a matter of major differences in resources or teacher quality. In fact, often just the opposite—spending on disadvantaged students is typically higher than on non-disadvantaged students.

So inquiring minds would like to know when those distinguished researchers direct their attention to home cultures (and the resulting school discipline).

SpecialKinNJ 5 years ago 5 years ago

A reliable source https://object.cato.org/sites/cato.org/files/pubs/pdf/pa746.pdf provides evidence indicating that per pupil costs/expenditures have increased at a 45 degree angle since the 1970s, but average reading, writing and arithmetic scores have not increased at all (see especially Page. Data for states are provided.) The stability of average performance on tests of reading writing and arithmetic is due not so much to lack of effort to change that pattern as to resistance of such abilities to change — as … Read More

A reliable source https://object.cato.org/sites/cato.org/files/pubs/pdf/pa746.pdf provides evidence indicating that per pupil costs/expenditures have increased at a 45 degree angle since the 1970s, but average reading, writing and arithmetic scores have not increased at all (see especially Page. Data for states are provided.)

The stability of average performance on tests of reading writing and arithmetic is due not so much to lack of effort to change that pattern as to resistance of such abilities to change — as suggested by data for a recent (almost) 30-year period showing the average performance of all students as well as students classified by race/ethnicity, taking an internationally recognized test (the SAT). See table below, showing SAT Critical Reading averages for selected years. Note. Data for Asian-Americans indicate that they’re exceptions to that rule. Their average has improved steadily, and they’re now “leaders of the pack”.

Table 1. SAT Critical Reading average selected years 1987 ’97 2001 ’06 ’11 ’15 ’16 507 505 506 503 497 495 494 All students 524 526 529 527 528 529 528 White 479 496 501 510 517 525 529 Asian …………………………… .. …..436 Hispanic 457 451 451 454 451 448 Mex-Am 436 454 457 459 452 448 Puerto R 464 466 460 458 451 449 Oth Hisp 471 475 481 487 484 481 447 Amer Ind 428 434 433 434 428 431 430 Black SOURCE: U.S. Department of Education, National Center for Education Statistics.(2012). Digest of Education Statistics, 2011 (NCES 2012-001), Chapter 2. SAT averages for college-bound seniors, by race/ethnicity: Selected years,1986-87 through 2010–11 Data for 2015&2016 https://nces.ed.gov/fastfac… Note 2016 data were not provided for Hispanic subgroups. If SAT averages haven’t changed materially over almost 30 years, despite the effort, time and money expended to improve educational programs for all students, it seems reasonable to assume that we shouldn’t expect any meaningful change in average level of performance in this critically important ability in the foreseeable future. And what if the achievement gap is here to stay!! And it is important to remember that correlation does not imply causation.

Dr. Bill Conrad 5 years ago 5 years ago

The chief determinant of whether economically disadvantaged students will succeed in school is the quality of the teachers they get and the ability of those teachers to know their content well and to effectively implement high quality professional practices . Economically disadvantaged students are most likely to get the most novice or TFA teachers out of an overall teacher pool that is derived from color in the lines colleges of education unprepared in content … Read More

The chief determinant of whether economically disadvantaged students will succeed in school is the quality of the teachers they get and the ability of those teachers to know their content well and to effectively implement high quality professional practices .

Economically disadvantaged students are most likely to get the most novice or TFA teachers out of an overall teacher pool that is derived from color in the lines colleges of education unprepared in content knowledge and pedagogy. That is their fate and it is the root cause of the achievement gap. Economically disadvantaged parents do not have the economic wherewithal to pay for extra tutoring and after school support line White and Asian parents do! They are the most sensitive to the quality of the teachers.

Local school boards and milquetoast administrators hold the line on allocating their most qualified teachers from predominantly wealthy white schools to schools with predominantly Brown and economically disadvantaged students!

Correlation does not mean causation. Scratch the surface. Visit classrooms where the economically poor Brown children are “educated” and you will see for yourself!

Ann 5 years ago 5 years ago

Dr. Conrad, I'm afraid I disagree. I have never worked in a district that allowed teachers to choose sites. Teachers usually take the placement at whatever site they get hired, then rarely move. The problem is there are far to many who receive tenure have not shown themselves to be good teachers. Principles simply do not say no often enough. The larger problem and where it begins in the schools of education that 1) admit … Read More

Dr. Conrad, I’m afraid I disagree. I have never worked in a district that allowed teachers to choose sites. Teachers usually take the placement at whatever site they get hired, then rarely move. The problem is there are far to many who receive tenure have not shown themselves to be good teachers. Principles simply do not say no often enough. The larger problem and where it begins in the schools of education that 1) admit those with lesser academic qualifications and 2) do an abhorrent job teaching pedagogy instead spending too much time on ‘culture’ and ‘social justice’. This has been so for decades. Twenty years back in California we were getting pretty well trained teachers from Fresno State but that has deteriorated as well. BTW the same situation for admin credentials.

Bill Conrad 5 years ago 5 years ago

I don't think that we are in disagreement. The woeful colleges of education are the root cause of producing a pool of teachers in general who are not well prepared in either content or pedagogy. These are the teaches that students of color and economically disadvantaged students are destined to get. If we do a thought experiment advocated by Mutiu Fagbayi from Performance Fact, we might be better able to see the issue. If … Read More

I don’t think that we are in disagreement. The woeful colleges of education are the root cause of producing a pool of teachers in general who are not well prepared in either content or pedagogy. These are the teaches that students of color and economically disadvantaged students are destined to get.

If we do a thought experiment advocated by Mutiu Fagbayi from Performance Fact, we might be better able to see the issue. If we randomly selected 30 students of color or economically disadvantaged students and assigned them a teacher. Is it possible that this teacher could ensure that 50% of the students meet standards? If we assigned a different teacher. Is it possible that that teacher could ensure that 80% of the students meet standards? Is it possible to assign a teacher who only gets 25% of the students to meet standards. Of course, all of these scenarios are true. So it is not the children who are the issue, it is the adults and their level of preparedness. No?

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