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• BOOK REVIEW
• 24 May 2024

The global economy’s 200-year growth spurt — and what comes next

• Rutger Hoekstra 0

Rutger Hoekstra is an ecological economist at the Institute of Environmental Sciences, Leiden University, the Netherlands. He is the author of Replacing GDP by 2030 and coordinator of WISE Horizons, a beyond-growth project funded by the European Union.

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Increasing demand for digital technologies drives work at the world’s largest transformer supplier, in Rugao, China. Credit: Costfoto/Future Publishing/Getty

Growth: A Reckoning Daniel Susskind Allen Lane/Belknap (2024)

For decades, the global economy has been growing by 2–5% per year. This growth is eating up ever more resources, destroying biodiversity and ushering in dangerous levels of global warming. Endless growth of this kind isn’t sustainable. What can be done? Should growth be maintained, but differently, to protect Earth while resolving inequalities and other social problems? Or should growth be curbed and the global economy stabilized or even shrunk? These are crucial questions with complex answers, about which people disagree fervently.

In Growth , economist Daniel Susskind delves into the roots of these problems and offers suggestions. His passages putting economic growth into historical context are engaging. Yet, in my view, his wider analyses and solutions are too limited to make this book a good starting point for the broad moral discussion that he advocates.

Growth, past and future

Susskind begins by pointing out how economic growth is a recent phenomenon. For around 300,000 years, while societies were mainly agricultural or capable only of subsistence, overall long-term prosperity remained more or less stagnant. Then, around the start of the nineteenth century, something unprecedented happened: the global economy began a 200-year growth spurt.

How rich is too rich?

Why? Economists have no definitive answer, Susskind rightly concludes. He provides an insightful overview of hypotheses, based on factors including capital investment, technological progress, skilled and educated workers, and cultural and institutional conditions. He highlights the importance of innovations such as medical science and breakthroughs in transportation and manufacturing. And he stresses that a society that is more receptive to science is also culturally better equipped to apply these innovations in the economy.

In the aftermath of the Second World War, economic growth was propelled to the top of the list of policy objectives in the West. It was seen as key to rebuilding shattered European economies, and crucial to prevailing in the cold war and in creating full employment — an important objective since the Great Depression in the 1930s. The idea spread and went on to become a global policy objective.

Gross domestic product (GDP) came to be seen as a measure of the success of a society — and an end in itself, rather than a means to an end, as most economists see it. But this posed a “growth dilemma”, Susskind notes. On the one hand, “GDP is correlated with almost every measure of human flourishing”. On the other, the fossil fuels and digital technologies underlying this economic growth are “climate-destroying, inequality-creating, work-threatening, politics-undermining, and community-disrupting”.

Illegal gold mining has led to deforestation in the Peruvian Amazon. Credit: Cris Bouroncle/AFP/Getty

Public discussions about how to resolve this dilemma are contentious, even factional. To oversimplify, there are two main camps. One, championing ‘green growth’, extols the benefits of economic expansion and stresses that it can be achieved sustainably. The second, focused on ‘degrowth’, argues that economic growth is not the solution to social and ecological problems, but the cause. It holds that these issues can be solved only by a democratically agreed reduction in growth in rich countries.

Susskind refers to his own position as “weak degrowth”, but spends much time analysing how to “unleash” growth by reforming intellectual-property laws, increasing research and development and getting more people to innovate. He makes a powerful argument that society must dictate the direction of innovation — towards green technologies, for example — to reduce the negative effects of growth.

Yet, Susskind admits, hard choices will inevitably be required. Choosing whether to pursue more or less economic growth will always affect “other goals”, such as a healthy climate, fair distribution of wealth, cohesive communities, well-paid and high-quality work and a functioning democracy. To navigate these decisions, he suggests, society will need to ask itself some deep “moral questions” through participatory democratic processes such as citizens’ assemblies.

A reckoning

What should a reader make of this? Just like Susskind, I am no expert on all the scientific domains needed to make such choices. No one is. I’m sympathetic to his remark that it is impossible to write on such a broad topic and provide a full and uncontroversial overview of all the literature. But, in many sections, such as the one on GDP, I was unconvinced.

I have worked in national accounts and on alternatives to GDP . Yet I was confused by Susskind’s argument that economists should follow “GDP minimalism”, such that GDP should be limited to measuring the “taxable income” of society. He lists many well-known problems with GDP and proposals to expand its scope, but does not say what exactly he would change.

Why the world cannot afford the rich

For example, Susskind argues that economists should not expand the scope of GDP by factoring in damages such as air pollution. He bases this on “moral modesty” — in his view, value-laden choices have no place in a quantitative metric. Yet he does not provide a comprehensive way of judging what is in and what is out. Many sectors that contribute to current GDP figures — such as tobacco, alcohol, fossil fuels, gambling, social media and businesses that take advantage of monopolies or price gouging — might also be considered immoral. Should those be removed?

Susskind also wants to restrict what GDP measures to emphasize “technical diligence”. It is unclear what that would mean. The quantity and quality of health services are hard to measure, for example; should these be excluded from economic growth figures? And the availability of data varies for each country. Should internationally comparable GDP figures be abandoned and each country have its own definitions? Or should economists revert to the lowest common denominator, considering only factors for which every country has adequate statistics? The book is inconclusive.

Susskind suggests using a dashboard of indicators rather than adjusting GDP. Yet, strangely, he doesn’t reference influential dashboards such as the United Nations Sustainable Development Goals or its predecessors, the Millennium Development Goals, which have existed for decades.

Deeper problems lurk in the theoretical foundation of Growth . Four things stand out.

First, the standard view in the literature is that economic growth is a means to an end, not the end itself. Yet, without justification, Susskind frames his arguments around achieving economic growth as a goal, alongside others.

To build a better world, stop chasing economic growth

Second, he argues that, because ideas are infinite, there is no limit to possible economic growth. This is quite a claim, and he does not provide convincing support. He simply points to the possible combinations of atoms and the number of recipes one could make from a given set of ingredients. Because the number of variations is huge, he thinks it likely that society will continue to generate enough useful ideas to go on expanding the economy.

Yet, some of the books Susskind refers to undermine that. For example, Robert Gordon’s Rise and Fall of American Growth (2016) argues that the generation of useful ideas (those that contribute to quality of life) has slowed since the 1970s, and that this is why we should not expect economic growth to continue.

In medicine, too, the rate of discovery has reduced in the past few decades. Life expectancy dropped in many countries during the COVID-19 pandemic. And many high-income nations are experiencing increased mortality owing to ‘bad’ ideas including drugs, alcohol, fast food and guns.

Degrowth can work — here’s how science can help

Third, Susskind argues that growth-driving ideas are unrestricted by the limits of a finite planet. Yet, scientists have shown that six out of nine ‘planetary boundaries’ — Earth systems, such as climate change, that will have a huge effect on current and future generations — are being crossed ( K. Richardson et al. Sci. Adv . 9 , eadh2458; 2023 ). Given this, Susskind’s unfounded optimism seems too large a risk.

Fourth, Susskind’s ‘moral discussion’ framing seems restrictive. He is willing to sacrifice a bit of growth for the sake of “other” societal goals. But, frankly, I was expecting a deeper discussion of what constitutes ‘a good life’ and how those lives could be led in a way that respects the limits of the planet and takes into account other people and future generations. I would also expect a discussion of the sacrifices that people might need to make, in terms of diet, transportation, consumption or taxation. I see no justification that ‘expanding economic activity by between 0 and x %’ is a valid boundary to such a fundamental moral debate.

In sum, Growth offers a readable and useful introduction to the green-growth perspective. There are insightful parts and I support a plea for a moral reckoning. But the book omits crucial environmental insights and lacks the robustness needed for such a foundational debate around the goals of society.

Nature 629 , 992-994 (2024)

doi: https://doi.org/10.1038/d41586-024-01520-8

Competing Interests

The author declares no competing interests.

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Inflation and Economic Growth

Data for around 100 countries from 1960 to 1990 are used to assess the effects of inflation on economic performance. If a number of country characteristics are held constant, then regression results indicate that the impact effects from an increase in average inflation by 10 percentage points per year are a reduction of the growth rate of real per capita GDP by 0.2-0.3 percentage points per year and a decrease in the ratio of investment to GDP by 0.4-0.6 percentage points. Since the statistical procedures use plausible instruments for inflation, there is some reason to believe that these relations reflect causal influences from inflation to growth and investment. However, statistically significant results emerge only when high- inflation experiences are included in the sample. Although the adverse influence of inflation on growth looks small, the long-term effects on standards of living are substantial. For example, a shift in monetary policy that raises the long-term average inflation rate by 10 percentage points per year is estimated to lower the level of real GDP after 30 years by 4-7%, more than enough to justify a strong interest in price stability.

• Acknowledgements and Disclosures

MARC RIS BibTeΧ

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From economic wealth to well-being: exploring the importance of happiness economy for sustainable development through systematic literature review

• Open access
• Published: 23 May 2024

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• Shruti Agrawal   ORCID: orcid.org/0000-0002-1620-9429 1 , 5 ,
• Nidhi Sharma 1 , 5 ,
• Karambir Singh Dhayal   ORCID: orcid.org/0000-0002-0000-4330 2 &
• Luca Esposito   ORCID: orcid.org/0000-0001-5983-6898 3 , 4  

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The pursuit of happiness has been an essential goal of individuals and countries throughout history. In the past few years, researchers and academicians have developed a huge interest in the notion of a ‘happiness economy’ that aims to prioritize subjective well-being and life satisfaction over traditional economic indicators such as Gross Domestic Product (GDP). Over the past few years, many countries have adopted a happiness and well-being-oriented framework to re-design the welfare policies and assess environmental, social, economic, and sustainable progress. Such a policy framework focuses on human and planetary well-being instead of material growth and income. The present study offers a comprehensive summary of the existing studies on the subject, exploring how a happiness economy framework can help achieve sustainable development. For this purpose, a systematic literature review (SLR) summarised 257 research publications from 1995 to 2023. The review yielded five major thematic clusters, namely- (i) Going beyond GDP: Transition towards happiness economy, (ii) Rethinking growth for sustainability and ecological regeneration, (iii) Beyond money and happiness policy, (iv) Health, human capital and wellbeing and (v) Policy push for happiness economy. Furthermore, the study proposes future research directions to help researchers and policymakers build a happiness economy framework.

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Beyond GDP: A Movement Toward Happiness Economy to Achieve Sustainability

National progress, sustainability and higher goals: the case of Bhutan’s Gross National Happiness

Economic Performance, Happiness, and Sustainable Development in OECD Countries

Avoid common mistakes on your manuscript.

1 Introduction

Happiness is considered the ultimate goal of human beings (Ikeda, 2010 ; Lama, 2012 ). All economic, social, environmental and political human activities are aligned towards achieving this goal. This fundamental pursuit of human life introduces a new scope of research, namely the ‘happiness economy’ (Agrawal and Sharma 2023 ). The happiness economy is an emerging economic domain wherein many countries are working to envision and implement a happiness-oriented framework by expanding how they measure economic success, which includes wellbeing and sustainability (Cook and Davíðsdóttir 2021 ; Forgeard et al., 2011 ). The investigation of happiness, life-satisfaction and subjective well-being has witnessed increasing research interest across the disciplines- from psychology, philosophy, psychiatry, and cognitive neuroscience to sociology, economics and management (Diener 1984 ; Hallberg and Kullenberg, 2019 ).

In the post-Covid era, the world seeks an enormous transformation shift in the public system (Costanza 2020 ). However, public authorities need more time to realize such needs. To experience the ‘policy transformation’ within the coming few years, we require a paradigm shift that helps warm peoples’ hearts and minds. The new economic paradigm can penetrate the policy processes in advanced economies and every part of the world affected by the epidemic with the support of intellectuals, researchers, entrepreneurs and professionals.

OECD ( 2016 ) proposed a well-being economy framework to measure living conditions and people’s well-being. In 2020, developed countries like Finland, New Zealand, Iceland, Scotland and Wales have become members of the Wellbeing Economy Government (WEGo) (Abrar 2021 ). Since then, the network of government and international authorities across the globe has gained a quick momentum concerning an increasing tendency about a growing tendency to concentrate governmental decisions around human well-being rather than wealth and economic growth (Coscieme et al. 2019 ; Costanza et al. 2020 ).

In light of these circumstances, the purpose of this article is to describe the concept of a “happiness economy” or one that seeks to give everyone fair possibilities for growth, a sense of social inclusion, and stability that can support human resilience (Coyne and Boettke 2006 ). It provides a promising route towards improved social well-being and environmental health and is oriented towards serving individuals and communities (Skul’skaya & Shirokova, 2010 ). Moreover, the happiness economy paradigm is a transition from material production and consumption of commodities and services as the only means to economic development towards embracing a considerable variety of economic, social, environmental and subjective well-being dynamics that are considered fundamental contributors to human happiness (Atkinson et al., 2012 ; King et al., 2014 ; Agrawal and Sharma 2023 ). In following so, it reflects the ‘beyond growth’ approach that empathizes with the revised concept of growth, which is not centred around an increase in income or material production; instead it is grounded in the philosophy of achieving greater happiness for more people (Fioramonti et al. 2019a ).

Whereas the other critiques of economic growth emphasize contraction, frugality and deprivation, the happiness economy relies on a cumulative approach of humanity, hope and well-being, with a perceptive to build a ‘forward-looking’ narrative of ways for humans to live a happy and motivated life by inspiring the cumulative actions and encouraging policy-reforms in the measuring growth of an economy (Stucke 2013 ). Agrawal et al. ( 2023a , b ) explore the domain of happiness economics through a review of the various trends coupled with the future directions and highlight why it needs to be supported for a well-managed economic system and a happy society.

In this paper, we define a “happiness economy as an economy that aims to achieve the well-being of individuals in a nation, promoting human happiness, environmental up-gradation, and sustainability. Alternatively, as an economy where the wellbeing of people counts more than the goals of production and income”. Moreover, we have examined the existing body of research on the happiness economy and analyzed the emerging research themes related to rethinking the conventional approach to economic growth. We conclude by discussing how the happiness economy concept has been accepted so far and realizing its importance by triggering policy reforms at the societal level, by outlining potential future directions that might be included into the current national post-growth policies.

Various researchers and experts in the field of happiness economy support the idea that there is a lack of thorough studies related to the concept, definitions, and themes of the happiness economy model in the nations. This gap has motivated us to conduct a SLR in order to identify the evolution in the domain of happiness economy and to identify the emerging themes in this context. Therefore, this present study seeks to offer a holistic outline of the emerging research area of the happiness economy and helps to understand how the happiness economy can accelerate sustainable development. With the following research questions, this study seeks to give an all-encompassing review of this subject.

What is the annual publication trend in this domain and the most contributing authors, journals, countries etc?

Which themes and upcoming research areas are present in this field?

What directions will the happiness economics study field go in the future?

The SCOPUS database was used to achieve the above research objectives. We have selected 257 articles for examination by hand-selecting the pertinent keywords and going over each one. In the methods section, a thorough explanation of the procedures for gathering, reviewing, and selecting documents is provided.

The remainder of this paper is structured as follows; A thorough survey of the literature on the happiness economy is provided in Sect.  2 . The research approach employed in the study is presented in Sect.  3 . A thorough data analysis of the research findings is given in Sect.  4 . After discussing the results in Sect.  5 , Sect.  6 suggests areas for further research in this field. The study is summarised with a conclusion in Sect.  7 . Section  8 outlines the study’s limitation.

2 Literature review

The supporters of conventional economic growth proclaim that the material production of goods and services and consumption is vital to enhancing one’s living standards. The statement is true to some degree, mainly in countries of enormous deprivation. Some studies have found significantly less correlation between growth and happiness after fulfilling minimum threshold needs (Easterlin 1995 ; Kahneman and Krueger, 2006 ; Inglehart et al., 2008 ). These studies recommend that rather than concentrating solely on economic growth, governmental policy should give priority to non-economic aspects of human existence above a particular income level. According to some researchers, it is challenging to distinguish between the use and emissions of natural resources and economic growth (absolute decoupling) because of the interdependence between socioeconomic conditions and their biophysical basis (Wiedenhofer et al. 2020 ; Wang and Su, 2019 ; Wu et al., 2018 ). However, a shred of increasing evidence shows that it could be possible for humans to maintain a quality of life and a decent standard of living inside the ecological frontier of the environment, given that a contemporary perspective on the production and use of materials are adopted in conjunction with more fair wealth distribution (Millward-Hopkins et al. 2020 ; Bengtsson et al., 2018 ; Ni et al., 2022 ).

The scholarly discourse and institutional framework on the relationship between happiness and economic progress are synthesised in the happiness economy (Frey and Gallus 2012 ; Sohn, 2010 ; Clark et al., 2016 ; Easterlin, 2015 ; Su et al., 2022 ). From a happiness economy perspective, extreme materialism is unsustainable as it significantly impacts natural resources and hinders social coherence and individuals psychological and physical well-being (Fioramonti et al. 2022a ). Additionally, inequalities within countries have grown, while psychological suffering has increased, especially during accelerated growth (Vicente 2020 ; Galbraith, 2009 ). The modern world is witnessing anxiety, depression, wars, reduction of empathy, climate change, pandemics, loss of social bonds and other psychological disorders (Brahmi et al., 2022 ; Santini et al., 2015 ).

It has been scientifically proven that cordial human relations, care-based activity, voluntary activities and the living environment immensely impact a person’s health and societal well-being (Bowler et al. 2010 ; Keniger et al., 2013 ). Ecological economists demonstrated that free ecosystem services have enhanced human well-being (Fang et al. 2022 ). Social epidemiologists have long argued that an increase in inequalities has a negative influence on society while providing equality tends to improve significant objective ways of well-being, from healthier communities to happier communities, declining hate and crime and enhancing social cohesion, productivity, unity and mutual trust (Aiyar and Ebeke 2020 ; Ferriss, 2010 ).

From moving beyond materialistic growth, the happiness economy promotes, appreciates, and protects the environmental, societal, and human capital contributions that lead to cummalative well-being. In a happiness economy framework, a multidimensional approach is needed to evaluate the level of development based on the environmental parameters, health outcomes, as well as public trust, hope, value-creating education and social bonds (Agrawal and Sharma 2023 ; Bayani et al. 2023 ; Lavrov, 2010 ). Such factors have consistently been excluded from any traditional concept or assessment of economic growth. As a result, countries have promoted more industrial activities that deteriorate the authentic ways of human well-being and, hence, the foundations of economic progress.

An excess of production can create a detrimental effect on climate and people’s health, thereby creating a negative externality for society (Fioramonti et al. 2022b ). Moderation of output may be more efficient and desirable than hyper/over-production, as the former can reduce negative environmental externalities (e.g. waste, climate change) and create positive externalities (e.g. employment of the local resources and community) (Kim et al. 2019 ; Kinman and Jones, 2008 ). Moreover, people can also be productive in other contexts outside of the workplace, such as as volunteers, business owners, artists, friends, or members of the community (Fioramonti et al. 2022a ).

Various scholars and scientific research have established that the essential contributions to happiness in one’s life are made by natural surroundings, green and blue spaces, eco-friendly environment, healthy social relations, spirituality, good health, responsible consumption and value-creating education (Helliwell et al. 2021 ; Francart et al., 2018 ; Armstrong et al., 2016 ; Gilead, 2016 ; Giannetti et al., 2015 ). Unfortunately, existing conventional growth theories have ignored all these significant contributions. For example, GDP considers natural ecosystems as economically helpful only up until they are mined and their products are traded (Carrero et al. 2020 ). The non-market benefits they generate, such as natural fertilization, soil regeneration, climate regulation, clean air and maintenance of biodiversity, are entirely ignored (Boyd 2007 ; Hirschauer et al., 2014). The quality time people spend with their families and communities for leisure, educating future generations and making a healthy communal harmony is regarded meaningless, even in the event that they are important to enhance people’s well-being and, hence, to assist any dimension of economic engagement (Griep et al. 2015 ; Agrawal et al., 2020 ). Similarly, if an economy is focusing on people’s healthy lifestyle (for example, by providing comfortable working hours, improving work-life balance, emphasizing mental health, focusing on healthy food, reducing pollution, and promoting sustainable consumption), it is not considered in sync with the growth paradigm (Roy 2021 ; Scrieciu et al., 2013; Shrivastava and Zsolnai 2022 ; Lauzon et al., 2023 ).

Among the latest reviews, Bayani et al. ( 2023 ) highlight that the economics of happiness helps reduce the country’s financial crime by providing a livelihood that reduces financial delinquency. Chen ( 2023 ) highlights that smart city performance enhances urban happiness by adopting green spaces, reusing and recycling products, and controlling pollution. The study by (Agrawal and Sharma 2023 ) proposed a conceptual framework for a happiness economy to achieve sustainability by going beyond GDP. Similarly, Fioramonti et al. ( 2019b ) explored going beyond GDP for a transition towards a happy and well-being economy. The article by Laurent et al. ( 2022 ) has intensively reviewed the well-being indicators in Rome and proposed a conceptual framework for it.

Table  1 provides a thorough summary of the prior review studies about the happiness economy and its contribution to public policy and sustainable development.

3 Research methodology

In the current study, we have adopted an integrative review approach of SLR and bibliometric analysis of the academic literature to get a detailed knowledge of the study, which could also help propose future research avenues. The existing scientific production’s qualitative and quantitative context must be incorporated for a conclusive decision. The study by Meredith ( 1993 ) defines that SLR enables an “integrating several different works on the same topic, summarising the common elements, contrasting the differences, and extending the work in some fashion”. In the present study, the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) is applied to perform the SLR to follow systematic and transparent steps for the research methodology, as shown in Fig.  1 . The PRISMA technique includes the identification, screening, eligibility, and exclusion criteria parts of the review process.

Additionally, examples of the data abstraction and analysis processes are provided (Mengist et al. 2020 ; Moher et al., 2015 ). The four main phases of the PRISMA process are eligibility, identification, screening, and data abstraction and analysis. Because the PRISMA technique employs sequential steps to accomplish the study’s purpose, it benefits SLR research. Moreover, the bibliometric analysis helps summarise the existing literature’s bibliographic data and determine the emerging condition of the intellectual structure and developing tendencies in the specified research domain (Dervis 2019 ).

3.1 Identification

The step to conduct the PRISMA is the identification of the relevant keywords to initiate the search for material. Next, search strings for the digital library’s search services are created using the selected keywords. The basic search query is for digital library article titles, keywords, and abstracts. Next, a Boolean AND or OR operator is used to generate the search string (Boolean combinations of the operators may also be used).

There are different search databases to conduct the review studies, such as Scopus, Sage, Web of Science, IEEE, and Google Scholar. Among all the available search databases, we have used the Scopus database to identify the articles; since 84% of the material on Web of Science (WoS) overlaps with Scopus, very few authors have addressed the benefits of adopting Scopus over WoS (Mongeon and Paul-Hus 2016 ). Scopus is widely used by academicians and researchers for quantitative analysis (Donthu et al. 2021 ). It is the biggest database of scientific research and contains citations and abstracts from peer-reviewed publications consisting of journal research articles, books and conference articles (Farooque et al., 2019 ; Dhayal et al., 2022 ; Brahmi et al., 2022 ). The following search term was used: (TITLE-ABS-KEY (“happiness economy” OR “economics of happiness” OR “happiness in economy” OR “economy of happiness” OR “economy of wellbeing” OR “wellbeing economy” OR “wellbeing in economy” OR “beyond growth”). This process yields 380 artciles in the initial phase.

3.2 Screening

The second phase is completed by all identified articles from the Scopus database obtained from the search string in the identification phase. The publications are either included or excluded throughout the screening process based on the standards established by the authors and with the aid of particular databases. Exclusion and inclusion criteria are shown during the screening phase to identify pertinent articles for the systematic review procedure. The timeline of this study’s selected articles is from 1995 to 2023. The first article related to the research domain was published in 1995. The second criterion for the inclusion includes the types of documents. In the present research, the authors have regarded only peer-reviewed journals and review articles. Other types of articles, such as books, book chapters, conference articles, notes, and editorials, are excluded to maintain the quality of the review. The third inclusion and exclusion criterion is based on language. All the non-English language documents are excluded to avoid translation confusion; hence, only the English language articles are considered for the final review. After the screening process, 297 articles are obtained.

3.3 Eligibility

Articles are manually selected or excluded depending on specific criteria specified by the authors during the eligibility process. During the elimination process, the authors excluded the articles that did not fit into the scope of review after manual screening of the articles. Two hundred fifty-seven articles were selected after the eligibility procedure. These selected articles are carefully reviewed for the study by reviewing the titles, abstracts, and standards from earlier screening processes.

3.4 Data abstraction and analysis

Analysis and abstraction of data are part of the fourth step. Finally, 257 papers were taken into account for final review. After that, the studies are culled to identify pertinent themes and subthemes for the current investigation by thoroughly reviewing each article’s text. An integrative review is a form of study that combines mixed, qualitative, and quantitative research procedures. It is carried out as shown in Fig.  1 . R-studio Bibliometrix and VOSviewer version 1.6.18 were used to evaluate the final study dataset corpus of 257 articles. Since the Bibliometrix software package is a free-source tool programmed in the R language. It is proficient of conducting comprehensive scientific mapping. It also contains several graphical and statistical features with flexible and frequent updates (Agrawal et al. 2023a , b ).

Extraction of articles and selection process

This section provides an answer to the first research question, RQ1, by indicating the main information of corpus data, research publication trends, influential prolific authors, journals, countries and most used keywords, etc. (Refer to Tables  2 , 3 and 4 ) and (Refer to Figs.  2 , 3 , 4 , 5 and 6 ).

4.1 Bibliometric analysis

Table  2 shows the relevant information gathered from the publication-related details. It presents the cognitive knowledge of the research area, for instance, details about authors, annual average publication, average citations and collaboration index. By observing the rate of document publishing, the study illustrates how much has already been done and how much remains to be investigated.

The annual publication trend is shown in Fig.  2 . It is reflected that the first article related to happiness in an economy was released in the year 1995 when (Bowling 1995 ) published the article “What things are important in people’s lives? A survey of the public’s judgements to inform scales of health related quality of life” where the article discussed “quality of life” and “happiness” as an essential component of a healthy life. Oswald ( 1997 ) brought the concept of happiness and economics together and raised questions such as “Does money buy happiness?” or “Do you think your children’s lives will be better than your own?”. Eventually, the gross national product of the past year and the coming year’s exchange rate was no longer the concern; instead, happiness as the sublime moment became more accurate (Schyns 1998 ; Easterlin, 2001; Frey and Stutzer, 2005 ). Post-2013, we can see exponential growth in the publication trend, and the reason behind the growth is the report published by the “ Stiglitz-Sen-Fitoussi” Commission, which has identified limitations of GDP and questioned the metric of wealth, economic and societal progress. The affirmed questions have gained the attention of researchers and organizations, and thus, they have explored the alternatives to GDP. As a result, the “Organization for Economic Co-operation and Development” (OECD) have proposed a wellbeing framework. Some research work has significantly impacted that time, contributing to the immense growth in this research area (Sangha et al. 2015 ; Spruk and Kešeljević, 2015 ; Nunes et al., 2016 ).

Publication trend

Table  3 shows the top prolific journals concerning the topmost publications in the domain of happiness economy for the corpus of 257 articles, namely “International Journal of Environmental Research and Public Health”, “Ecological Economics”, “Ecological Indicators”, “Sustainability” and “Journal of Cleaner Production” with 5, 4, 4,4 and 4 articles respectively (Refer to Table  4 ). Moreover, the most influential journals with maximum citations are “Nature Human Behavior”, “Quality of Life Research”, “Journal of Applied Behavior Analysis”, “Journal of Cleaner Production” and “Ecological Economics”, with 219, 205, 186, 154 and 142 citations, respectively. “Journal of Cleaner Production” and “Ecological Economics” are highly prolific and the most influential journals in the happiness economy research domain.

Table  4 shows the most influential authors. Baños, R.M. and Botella, C. are the two most contributing authors with maximum publications. For the maximum number of citations, Zheng G. and Coscieme L. are the topmost authors for their research work. The nations were sorted according to the quantity of publications, and Fig.  3 showed where the top ten countries with the highest number of publications are listed originated. It can be seen from the figure that the United Stated has contributed the maximum publications, 66, followed by the United Kingdom with 41 articles, followed by Germany with 32 articles. It is worth noting that emerging nation such as India and China have also made significant contributions.

Top ten contributing countries

Figure  4 shows semantic network analysis in which the relationships between words in individual texts are performed. In the present study, we have identified word frequency distributions and the co-occurrences of the authors’ keywords in this study. We employed co-word analysis to find repeated keywords or terms in the title, abstract, or body of a text. In Fig.  5 , the circle’s colour represents a particular cluster, and the circle’s radius indicates how frequently the words occur. The size of a keyword’s node indicates how frequently that keyword appears. The arcs connecting the nodes represent their co-occurrence in the same publication. The greater the distance between two nodes, the more often the two terms co-occur. It can be seen that “happiness” is linked with “growth” and “life satisfaction”. The nodes of “green economy”, “ecological economics”, and “climate change” are in a separate cluster that shows they are emerging areas, and future studies can explore the relationship between happiness economy with these keywords.

Co-ocurrance of author’s keyword (Author’s compilation)

4.2 Thematic map analysis through R studio

The thematic analysis map, as shown in Fig.  5 , displays, beneath the author’s keywords, the visualisation of four distinct topic typologies produced via a biblioshiny interface. The thematic map shows nine themes/clusters under four quadrants segregated in “Callon’s centrality” and “density value”. The degree of interconnectedness between networks is determined by Callon’s centrality, while Callon’s density determines the internal strength of networks. (Chen et al. 2019 ). The rectangular boxes in Fig.  5 represent the subthemes under each topic or cluster that are either directly or indirectly connected to the major themes, based on the available research. In the upper-right quadrant, four themes have appeared, namely “circular economy”, “well-being economy”, “depression”, and “sustainable development”, they fall under the category of motor themes since they are extremely pertinent to the research field, highly repetitious, and well-developed. When compared to other issues with internal linkages but few exterior relations, “urban population” in the upper-left quadrant is seen as a niche concern since it is not as significant. This cluster may have affected the urban population’s happiness (Knickel et al. 2021 ). “Social innovation” is categorised as an emerging or declining subject with low centrality and density, meaning it is peripheral and undeveloped. It is positioned in the lower-left quadrant. Last but not least, the transversal and fundamental themes “happiness economy”, “subjective well-being”, and “climate change” in the lower-right quadrant are seen to be crucial to the happiness economy study field but are still in the early stages of development. As a result, future research must place greater emphasis on the quantitative and qualitative growth of the study area in light of the key themes that have been identified.

Thematic map analysis

4.3 Science mapping through cluster analysis

In the study, science mapping was conducted to examine the interrelationship between the research domains that could be intellectual (Aria and Cuccurullo 2017 ; Donthu et al. 2021 ). It includes various techniques, such as co-authorship analysis, co-occurrence analysis, bibliographic coupling, etc. We have used R-Studio for the study’s temporal analysis by cluster analysis. To answer RQ2, the authors have performed a qualitative examination of the emerging cluster themes through the science mapping of the existing research corpus of 257 articles by performing bibliographic coupling of documents. Bibliographic coupling analysis helps identify clusters reflecting the most recent research themes in the happiness economy field to illuminate the field’s current areas of interest.

The visual presentation of science mapping relied on VoSviewer version 1.6.18 (refer to Fig.  6 ). Five significant clusters emerged in this research domain (refer to Table  5 ). Going beyond GDP: Transition towards happiness economy, rethinking growth for sustainability and ecological regeneration, beyond money and happiness policy, health, human capital and wellbeing and Policy-Push for happiness economy. A thorough examination identified cluster analyzes has also assists us in identifying potential future research proposals. (Franceschet 2009 )

4.4 Cluster 1: Going beyond GDP: transition towards happiness economy

It depicts from the green colour circles and nodes, where seven research articles were identified with a common theme of beyond GDP that can be seen in Fig.  6 . Cook and Davíðsdóttir ( 2021 ) investigated the linkages between the alternative measure of the beyond growth approach such as a well-being economy prespective and the SDGs. They proposed a conceptual model of a well-being economy consisting of four capital assets interrelated with SDGs that promote well-being goals and domains. To extend the concept of going beyond GDP, various economic well-being indicators are being aligned with the different economic, environmental, and social dimensions to target the set goals of SDG. It is found that the “Genuine Progress Indicator” (GPI) is consider as the most extensive method that covers the fourteen targets among the seventeen’s SDG’s. Cook et al. ( 2022 ) consider SDGs to represent the classical, neoclassical and growth-based economy model and as an emerging paradigm for a well-being economy. The significance of GDP is more recognized within the goals of sustainable development.

GPI is considered an alternative indicator of economic well-being. On this basis, excess consumption of high-quality energy will expand macro-economic activity, which GDP measures. For such, a conceptual exploration of the study is conducted on how pursuing “Sustainable Energy Development” (SED) that can increase the GPI results. As the study’s outcome, according to the GPI, SED will have a significant advantage in implementing energy and environment policy and will also contribute to the advancement of social and economic well-being. Coscieme et al. ( 2020a ) explored the connection between the unconditional growth of GDP and SDG. The author considered that policy coherence for sustainable development should lessen the damaging effects of cyclic manufacturing on the ecosystem. Thus, the services considered free of charge in the GDP model should be valued as a component of society. Generally, such services include ecosystem services and a myriad of “economic” functions like rainfall and carbon sequestration. To work for SDG 8, defined by the “United Nations Sustainable Development Goals” (UNSDGs), a higher GDP growth rate would eventually make it more difficult to achieve environmental targets and lessen inequality. Various guidelines were proposed to select alternative variables for SDG-8 to enhance coherence among all the SDG and other policies for sustainability.

Fioramonti et al. ( 2019a ) state their focus is to go beyond GDP toward a well-being economy rather than material output with the help of convergence reforms in policies and economic shifts. To achieve the SDG through protecting the environment, promoting equality, equitable development and sharing economy. The authors have developed the Sustainable Well-Being Index (SWBI) to consolidate the “Beyond GDP” streams as a metric of well-being matched with the objectives to achieve SDG. The indicators of well-being for an economy have enough possibility to connect current transformations in the economic policies and the economy that, generally, GDP is unable to capture.

Fioramonti et al. ( 2022a ) investigate the critical features of the Wellbeing Economy (WE), including its various parameters like work, technology, and productivity. Posting a WE framework that works for mainstream post-growth policy at the national and international levels was the study’s primary goal. The authors have focused on building a society that promotes well-being that should be empowering, adaptable, and integrative. A well-being economic model should develop new tools and indicators to monitor all ecological and human well-being contributors. A multidimensional approach including critical components for a well-being economy was proposed that creates value to re-focus on economic, societal, personal, and natural aspects. Rubio-Mozos et al. ( 2019 ) conducted in-depth interviews with Fourth Sector business leaders, entrepreneurs, and academicians to investigate the function of small and medium-sized businesses and the pressing need to update the economic model using a new measure in line with UN2030. They have proposed a network from “limits to growth” to a “sustainable well-being economy”.

4.5 Cluster 2: Rethinking growth for sustainability and ecological regeneration

Figure  6 depicts it from blue circles and nodes, wherein four papers were identified. Knickel et al. ( 2021 ) proposed an analytical approach by collecting the data from 11 European areas to examine the existing conditions, difficulties, and anticipated routes forward. The goal of the study is to define the many ideas of a sustainable well-being economy and territorial development plans that adhere to the fundamental characteristics of a well-being economy. A transition from a conventional economic viewpoint to a broader view of sustainable well-being is centred on regional development plans and shifting rural-urban interactions.

Pillay ( 2020 ) investigates the new theories of de-growth, ecosocialism, well-being and happiness economy to break the barriers of traditional economic debates by investigating ways to commercialise and subjugate the state to a society in line with non-human nature. The significant indicator of Gross National Happiness (GNH) is an alternative working indicator of development; thus, the Chinese wall between Buddha and Marx has been built. They questioned the perspective of Buddha and Marx, whether they were harmonized or became a counter-hegemonic movement. In order to determine if the happiness principle is grounded in spiritual values and aligns with the counter-hegemonic ecosocialist movement, the author examined the ecosocialist perspective. Shrivastava and Zsolnai ( 2022 ) have investigated the theoretical and practical ramifications of creative organisations for well-being rooted in the drive for a well-being economy. Wellbeing and happiness-focused economic frameworks are emerging primarily in developed countries. This new policy framework also abolishes GDP-based economic growth and prioritizes individual well-being and ecological regeneration. To understand its application and interpretation, Van Niekerk ( 2019 ) develops a conceptual framework and theoretical analysis of inclusive economics. It contributes to developing a new paradigm for economic growth, both theoretically and practically.

4.6 Cluster 3: ‘Beyond money’ and happiness policy

It depicts pink circles and nodes, wherein five articles were identified, as shown in Fig.  6 . According to Diener and Seligman ( 2004a ) economic indicators are critical in the early phases of economic growth when meeting basic requirements is the primary focus. However, as society becomes wealthier, an individual’s well-being becomes less dependent on money and more on social interactions and job satisfaction. Individuals reporting high well-being outperform those reporting low well-being in terms of income and performance. A national well-being index is required to evaluate well-being variables and shape policies systematically. Diener and Seligman ( 2018 ) propounded the ‘Beyond Money’ concept in 2004. In response to the shortcomings of GDP and economic measures, other quality-of-life indicators, such as health and education, have been created. The national account of well-being has been proposed as a common path to provide societies with an overall quality of life metric. While measuring the subjective well-being of people, the authors reasoned a societal indicator of the quality of life. In this article, the authors have proposed an economy of well-being model by combining subjective and objective measures to convince policymakers and academicians to enact policies that enhance human welfare. The well-being economy includes quality of life indicators and life satisfaction, subjective well-being and happiness.

Frey and Stutzer ( 2000 ) perceived the microeconomic well-being variables in countries. In the study, survey data was used from 6000 individuals in Switzerland and showed that the individuals are happier in developed democracies and institutions (government federalization). They analyzed the reported subjective well-being data to determine the function of federal and democratic institutions on an individual’s satisfaction with life. The study found a negative relationship between income and unemployment. Three criteria have been employed in the study to determine happiness: demographic and psychological traits, macro- and microeconomic factors, and constitutional circumstances. Thus, a new pair of determinants reflects happiness’s effect on individuals’ income, unemployment, inflation and income growth.

Happiness policy, according to Frey and Gallus ( 2013b ), is an intrinsic aspect of the democratic process in which various opinions are collected and examined. “Happiness policy” is far more critical than continuing a goal such as increasing national income and instead considered an official policy goal. The article focuses on how politicians behave differently when they believe that achieving happiness is the primary objective of policy. Frey et al. ( 2014 ) explored the three critical areas of happiness, which are positive and negative shocks on happiness, choice of comparison and its extent to derive the theoretical propositions that can be investigated in future research. It discussed the areas where a more novel and comprehensive theoretical framework is needed: comparison, adaptation, and happiness policy. Wolfgramm et al. ( 2020 ) derived a value-driven transformation framework in Māori economics of wellbeing. It contributes to a multilevel and comprehensive review of Māori economics and well-being. The framework is adopted to advance the policies and implement economies of well-being.

4.7 Cluster 4: Health, human capital and wellbeing

It is depicted as a red colour circle and nodes in Fig.  6 , and only three papers on empirical investigations were found. Laurent et al. ( 2022 ) investigated the Health-Environment Nexus report published by the “Wellbeing Economy Alliance”. In place of increased production and consumption, they suggested a comprehensive framework for human health and the environment that includes six essential paths. The six key pathways are well-being energy, sustainable food, health care, education, social cooperation and health-environment nexus. The proposed variables yield the co-benefits for the climate, health and sustainable economy. Steer clear of the false perception of trade-offs, such as balancing the economy against the environment or the need to save lives. McKinnon and Kennedy ( 2021 ) focuses on community economics of well-being that benefits entrepreneurs and employees. They investigated the interactions of four social enterprises that work for their employees inside and within the broader community. Cylus et al. ( 2020 ) proposed the opportunities and challenges in adopting the model of happiness or well-being in an economy as an alternative measure of GDP. Orekhov et al. ( 2020 ) proposed the derivation of happiness from the World Happiness Index (WHI) data to estimate the regression model for developed countries.

4.8 Cluster 5: Policy-push for happiness economy

It is depicted as an orange circle and nodes in Fig.  6 , and only five papers on empirical and review investigations were found. Oehler-Șincai et al. ( 2023 ) proposed the conceptual and practical perspective of household-income-labour dynamics for policy formulation. It discusses the measurement of well-being as a representation of various policies focusing on health, productivity, and longevity. It focuses on the role of policy in building the subjective and objective dimensions of well-being, defines the correlation between well-being, employment policies, and governance, is inclined to the well-being performance of various countries, and underscores present risks that jeopardize well-being. Musa et al. ( 2018 ) have developed a “community happiness index” by incorporating the four aspects of sustainability—economic, social, environmental, and urban governance—as well as the other sustainability domains, such as human well-being and eco-environmental well-being. From then onwards, community happiness and sustainable urban development emerged. Chernyahivska et al. ( 2020 ) developed strategies to raise the standard of living for people in countries undergoing economic transition by using the quality of life index. The methods uncovered are enhancing employment opportunities and uplifting the international labour market in urban and rural areas, prioritizing human capital, eliminating gender inequality, focusing on improving the individual’s health, and enhancing social protection. Zheng et al. ( 2019 ) investigated the livelihood and well-being index of the population that makes liveable conditions and city construction in society based on people’s happiness index. The structure of a liveable city should be emphasised on sustainable development. The growth strategy in urban areas is an essential aspect of building a liveable city. Frey and Gallus ( 2013a ) criticised the National Happiness Index as a policy goal in a country because it cannot be measured and thus fails to measure the true happiness of people. To measure real happiness, the government should establish living conditions that enable individuals to become happy. The rule of law and human rights must support the process.

The structure of a liveable city should be emphasized in sustainable development. The growth strategy in urban areas is an essential aspect of building a liveable city. Frey and Gallus ( 2013a ) criticized the National Happiness Index as a policy goal in a country because it cannot be measured and thus fails to identify the true individuals happiness. To measure real happiness, the government should establish living conditions that enable individuals to be happy. The process needs to be supported by human rights and the rule of law.

Visualization of cluster analysis

5 Discussion of findings

Concerns like the improved quality-of-life and a decent standard of living within the ecological frontier of the environment have various effects on individuals overall well-being and life satisfaction. The ‘beyond growth’ approach empathized with the revised concept of growth, which is based on the idea of maximising happiness for a larger number of people rather than being driven by a desire for financial wealth or production. In that aspect, the notion of happiness economy is designed that prioritizes serving both people and the environment over the other. This present article has focused on the beyond growth approach and towards a new economic paradigm by doing bibliometric and visual analysis on the dataset that was obtained from Scopus, helping to determine which nations, publications, and authors were most significant in this field of study.

In this field of study, developed nations have made significant contributions as compared to the developing nations. In total, 59 countries have made the substantial contribution to the beyond growth approach literature an some of them have proposed their respective national well-being economy framwework. Among 59 countries the United States and the United Kingdom have been crucial to the publishing. With the exception of five of the top 10 nations, Europe contributes the most to scientific research. The existing research shows the inclination of developed and developing countries to build a new economic paradigm that goes beyond growth by prioritizing the happiness level at individual as well as at collective level.

The most prolific journals in this research domain are the “International Journal of Environmental Research” and “Public Health” with the total publication of 5 and 4. The top two cited journals were the “ Nature Human Behavior” with 219 citations and the “Quality of Life Research” with 205 citations. Due to various economic and non-economic factors, these journals struggled to strike a balance between scientific accuracy and timeliness, and it became vital to spread accurate and logical knowledge. For, example, discussing the relationship between inequality and well-being, exploring the challenges and opportunites of happiness economy in different countries, assessing the role of health in all policies to support the transition to the well-being economy. Visualization of semantic network analysis of co-ocurrance of authors keywords from the VOSviewer showed the future research scope to explore the association between happiness economy along with green economy, climate change, spirituality and sustainability. However, in the thematic mapping, the motor themes denotes the themes that are well-developed and repetative in research, such as, well-being economy, depression, sustainable development and circular economy. The basic themes depicts the developing and transveral themes such as happiness economy, subjective well-being and climate condition. As a result, future research must place greater emphasis on the theoretical and practical expansion of the research field in view of the determined major subjects.

The present study have performed the cluster analysis to identify the emerging research themes in this domain through VOSviewer that helps to analyze the network of published documents. Based on published papers, the author can analyse the interconnected network structure with the use of cluster analysis. We have identified the top five clusters from the study. Each cluster denote the specific and defined theme of the research in this domain. In cluster 1, the majorly of the authors are working in the area of going beyond GDP and transition towards happiness economy, which consists of empirical and review studies. Cluster 2 represents that authors are exploring the relationship between rethinking growth for sustainability and ecological regeneration to evaluate the transition from a conventional economic thought to a broader view of sustainable well-being which is centred on regional development plans and shifting rural-urban interactions. In cluster 3, the authors are exploring the beyond money and happiness policy themes and identified the shortcomings of GDP and economic measures, other quality-of-life indicators, such as health and education. They have proposed the well-being index to evaluate the well-being variables and shape socio-economic policies systematically. The authors have proposed an economy of well-being model by combining subjective and objective measures to convince policymakers and academicians to enact policies that enhance human welfare. The well-being economy includes quality of life indicators and life satisfaction, subjective well-being and happiness. In cluster 4, the authors are working of related theme of Health, human capital and wellbeing, whereby they have put up a comprehensive framework for health and the environment that includes several important avenues for prioritising human and ecological well-being over increased production and consumption. In cluster 5, the authors have suggested the policy-push for happiness economy in which they have identified the conceptual and practical perspective of household-income-labour dynamics for policy formulation. Majorly of the authors in this clutster have focused on the role of policy in building the subjective and objective dimensions of well-being, defines the correlation between well-being, employment policies, and governance, is inclined to the well-being performance of various countries, and underscores present risks that jeopardize well-being. Hence, the present study will give academics, researchers, and policymakers a thorough understanding of the productivity, features, key factors, and research outcomes in this field of study.

6 Scope for future research avenues

The emergence of a happiness economy will transform society’s traditional welfare measure. Such changes will generate more reliable and practical means to measure the well-being or welfare of an economy. After a rigorous analysis of the existing literature, we have proposed the scope for future research in Table  6 .

7 Conclusion

In 2015, the United Nations proposed the pathbreaking and ambitious seventeen “Sustainable Development Goals” (SDGs) for countries to steer their policies toward achieving them by 2030. In reality, economic growth remains central to the agenda for SDGs, demonstrating the absence of a ground-breaking and inspirational vision that might genuinely place people and their happiness at the core of a new paradigm for development. As this research has reflect, there are various evidence that the happiness economy strategy is well-suited to permeate policies geared towards sustainable development. In this context, ‘happiness’ may be a strong concept that ensures the post-2030 growth will resonate with the socioeconomic and environmental traits of everyone around the world while motivating public policies for happiness.

The current research has emphasized the many dynamics of the happiness economy by using a bibliometric analytic study of 257 articles. We have concluded that the happiness economy is an emerging area that includes different dimensions of happiness, such as ecological regeneration, circular economy, sustainability, sustainable well-being, economic well-being, subjective well-being, and well-being economy. In addition to taking into consideration the advantages and disadvantages of human participation in the market, a happiness-based economic system would offer new metrics to assess all contributions to human and planetary well-being. In terms of theoretical ramifications, we suggest that future scholars concentrate on fusing the welfare and happiness theory with economic policy. As countries are predisposed to generate disharmony and imbalance, maximizing societal well-being now entails expanding sustainable development. Since the happiness economy is still a relatively novel field, it offers numerous potential research opportunities.

8 Limitations

Similar to every other research, this one has significant restrictions as well. We are primarily concerned that all our data were extracted from the Scopus database. Furthermore, future research can utilize other software like BibExcel and Gephi to expound novel variables and linkages. Given the research limitations, this article still provides insightful and relevant direction to policymakers, scholars, and those intrigued by the idea of happiness and well-being in mainstream economics.

The study offers scope for future research in connecting the happiness economy framework with different SDGs. Future studies can also carry empirical research towards creating a universally acceptable ‘happiness economy index’ with human and planetary well-being at its core.

Data availability

Data not used in this article.

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Agrawal, S., Sharma, N., Dhayal, K.S. et al. From economic wealth to well-being: exploring the importance of happiness economy for sustainable development through systematic literature review. Qual Quant (2024). https://doi.org/10.1007/s11135-024-01892-z

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AI is showing ‘very positive’ signs of eventually boosting GDP and productivity

Goldman Sachs Research predicted last year that generative AI could boost GDP and raise labor productivity growth over the coming decade. Since publishing that outlook, investment in generative AI has boomed, but it will take time for the technology to filter into the overall economy.

“Until we've seen more significant uptake in the actual application of AI, in the regular work production process, I don't think that we're going to see as big of an impact on productivity,” says Joseph Briggs, who co-leads the Global Economics team in Goldman Sachs Research. Briggs wrote last year’s AI report with Goldman Sachs economist Devesh Kodnani.

“That being said, the early signals of future productivity gains look very, very positive,” he adds.  

While adoption of generative AI is lagging investment in the technology , Goldman Sachs Research sees potential for AI to automate many work tasks. It’s expected to start having a measurable impact on US GDP in 2027 and begin affecting growth in other economies around the world in the years that follow.

We spoke with Briggs about how the team’s forecast has held up over the past year, which businesses are adopting generative AI, and the technology’s impact on the labor market.

Based on what you’re seeing from the data, how are we tracking against your productivity prediction?

We haven't seen much of an impact on productivity growth so far. But the reason being is, even though we still see a lot of potential for AI to automate a lot of the things that workers do on a day-to-day basis, thereby saving a lot of time and generating large productivity gains, the adoption rates are just fairly limited right now. The key step, of course, in automating tasks is that people have to start using it. And so until we've seen more significant uptake in the actual application of AI, in the regular work production process, I don't think that we're going to see as big of an impact on productivity.

That being said, the early signals of future productivity gains look very, very positive. Some of the academic literature and economic studies that have looked at the increase in productivity that we've seen following AI adoption, in a few specific cases, supports our view that large productivity gains are possible. The average increase in productivity is about 25%. Case studies of companies that have adopted AI imply similarly large efficiency gains. And so, you know, there's a lot of reasons to be optimistic. It will just take a little bit more time to see these productivity gains realized.

Did you change your forecast for the coming decade based on the actual data?

No, it really hasn't changed because our forecasts don’t assume any AI boost at all before 2027. And the very small increases in adoption that we've seen in the one year since we wrote our initial report, I think, are consistent with our view that over the next three years AI is probably not going to be a main driver of labor productivity and potential GDP growth. Even though we do still think that it's going to be a significant driver of productivity and GDP growth over a much longer horizon.

What explains the divergence between the strong investment in generative AI that you’re seeing compared with the slow rates of adoption?

For AI to be deployed on a widespread basis, there's a lot of things that need to happen. First you need to have models that are powerful enough and trained appropriately so they can actually be useful in everyday work product. Then you need to have the capability to facilitate and answer all the queries that people are going to be posing to AI models, when they do use them every day multiple times a day when they're engaged in regular work. Having both these things requires a big increase in investment in semiconductors which in turn requires a big increase in investment in network capacity.

And ultimately, that’s going to require an increase in electricity and collective power investment to support the increase in demand that facilitating queries will require.

We are seeing clear signs that investment is increasing. Revenues of semiconductor manufacturers are up about 50% since early 2023. If you look at forecast revisions for AI hardware providers, they imply about a $250 billion increase since a year ago. And so there's a lot of signs that the investment laying the groundwork for future use of AI is occurring.

The adoption and usage will occur when these pieces are in place, and companies actually start using AI on an everyday basis. For the most part that hasn't happened yet. We see about 5% of companies reporting that they do use generative AI today in regular production, but this is a fairly small share relative to the overall number of companies that we think will ultimately benefit.

How is that 5% putting generative AI to use?

There are a few specific use cases that are emerging if you look across the industries that are using generative AI. First and foremost, we see adoption rates higher in areas like information services, finance and insurance. The motion picture and sound recording industry, for instance, is another area where adoption is far above the economy wide average.

If we're talking about the things that people say that they're using it for, marketing, automation, chatbot, speech text, and data analysis are all areas that stand out as ways that companies are applying AI right now. This is kind of the low hanging fruit where AI is most applicable, at least in its current form. Ultimately, we think that a broader set of tasks are going to be automated by generative AI. But that probably requires a build out of an application layer to support the broader automation we see possible.

What about the other 95%? What’s holding them back?

There are a number of factors that are slowing down the pace of AI adoption. A lot of executives can see the economic potential of generative AI, but even those that see benefits report a lack of knowledge about AI, concerns about privacy and security, and concerns about overinvesting in an early version of the technology as barriers. I think that a lot these reasons broadly reflect that companies want to make sure that they get generative AI right, and companies are therefore taking deliberate approach to AI adoption.

These views generally align with what we've seen in some of the business surveys, where CEOs are asked about their intention to use generative AI. Very few say that they expect it's going to significantly impact their business over the next one to three years. Most say that they expect to see a significant impact over the three-to-10-year horizon.  

What’s been the net impact on jobs? How do you expect that to change over time?

Given that we've seen very little adoption, it's not surprising that we haven't seen much of an impact on the labor market. If we look at things like the unemployment rate between occupations that are highly exposed to AI automation, and those that are less, they basically tracked each other one-for-one for the last year or two. There have been some layoff announcements attributed to generative AI, but for the most part it seems like a very, very small share – less than 20,000 of all layoffs generated in the economy, which comes down to less than 0.1% of total job separations. So AI hasn't resulted in any significant job loss yet.

In fact, if we look at the labor demand that is generated it’s probably driven a net increase in employment. There has been a notable pickup in job postings mentioning AI as a desirable skill. This is especially true in the information technology sector. And so, it's very well possible, and probably even likely, that the net impact on the labor market has been positive thus far. This is kind of in line with our expectations over the long run, where we do expect that generative AI won't lead to a large amount of job loss. We generally think that it's going to create opportunities either in AI adjacent sectors or occupations or in sectors where labor has a comparative advantage. 

This article is being provided for educational purposes only. The information contained in this article does not constitute a recommendation from any Goldman Sachs entity to the recipient, and Goldman Sachs is not providing any financial, economic, legal, investment, accounting, or tax advice through this article or to its recipient. Neither Goldman Sachs nor any of its affiliates makes any representation or warranty, express or implied, as to the accuracy or completeness of the statements or any information contained in this article and any liability therefore (including in respect of direct, indirect, or consequential loss or damage) is expressly disclaimed.

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MIT professor hoses down predictions AI will put a rocket under the economy

It's easier to foresee growing inequality than surging growth.

Artificial intelligence (AI) may not do much to boost productivity – and could end up widening the income gap between owners of capital and workers.…

In a National Bureau of Economic Research paper titled "The Simple Macroeconomics of AI," Daron Acemoglu, professor of economics at Massachusetts Institute of Technology, argues that predictions AI will improve productivity and boost wages in a "blue-collar bonanza" are overly optimistic.

"AI will have implications for the macroeconomy, productivity, wages and inequality, but all of them are very hard to predict," Acemoglu argues. "This has not stopped a series of forecasts over the last year, often centering on the productivity gains that AI will trigger."

One rosy forecast predicts the advent of AI will see 100 percent GDP growth over the next decade, and a more modest forecast from Goldman Sachs of "seven percent (or almost $7 trillion) increase in global GDP and lift productivity growth by 1.5 percentage points over a ten-year period." Similar optimism was evident in last year's McKinsey Global Institute report, which suggested AI and other automation tech could increase annual average GDP growth by 0.5 to 3.4 percentage points in advanced economies over the next decade.

Acemoglu is skeptical, noting that prior introductions of automation through robotics benefited business owners and managers while workers experienced more negative outcomes.

Based on research last year that estimated about 20 percent of US workers could have half of their jobs done by an LLM, Acemoglu estimates that AI can save 27 percent in labor costs, or 14.4 percent in overall costs.

But those figures don't necessarily do much for productivity.

"This calculation implies that total factor productivity (TFP) effects within the next ten years should be no more than 0.66 percent in total – or approximately a 0.064 percent increase in TFP growth annually," Acemoglu reasons.

The professor therefore anticipates AI will boost GDP growth by only 0.93 percent to 1.16 percent over the next decade.

But even that figure may be too optimistic, he argues, because productivity estimates come from automating "easy tasks" – future tasks may be more complicated and less amenable to automation. He therefore contends there will be a more modest increase in TFP and GDP in the next ten years – on the order of 0.53 percent and 0.90 percent, respectively.

And some of that GDP growth may not improve overall economic welfare if the investment in AI brings with it extra costs, like higher energy consumption requirements.

Acemoglu goes on to argue that AI is unlikely to significantly improve wages and that even if the technology improves the productivity of low-end and middle-performing workers, it may not reduce inequality.

"I estimate that AI will not reduce inequality and is likely to have a negative effect on the real earnings of low-education women (especially white, native-born low-education women)," he asserts in his paper. His findings also suggest that "AI will further expand the gap between capital and labor income as a whole." ®