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Record W2898325562 · doi:10.1111/infi.12148

Your fathers’ mistakes: Critiques of GDP and the search for an alternative

2018· article· en· W2898325562 on OpenAlex

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Bibliographic record

VenueInternational Finance · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsnot available
Fundersnot available
KeywordsIndex (typography)Agency (philosophy)PovertyGross domestic productHuman Development IndexDemocracyGovernment (linguistics)Standard of livingSociologyEconomicsPolitical sciencePoliticsEconomic growthLawSocial scienceHuman development (humanity)

Abstract

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THE GREAT INVENTION: THE STORY OF GDP AND THE MAKING AND UNMAKING OF THE MODERN WORLD Ehsan Masood New York and London: Pegasus Books, 2016 THE GROWTH DELUSION: WEALTH, POVERTY, AND THE WELL-BEING OF NATIONS David Pilling New York: Tim Duggan Books, 2018 GDP: A BRIEF BUT AFFECTIONATE HISTORY Diane Coyle Princeton and Oxford: Princeton University Press, 2014 I spent 19 years working for the Bureau of Economic Analysis—the US government agency responsible for measuring the nation's gross domestic product, or GDP. Like most medium to large organizations, the BEA used performance measures to track our agency's performance. After all, in the words of William Thompson (Lord Kelvin), “when you can measure what you are speaking about and express it in numbers you know something about it” (Crosby, 1997, p. 225). In 2008, for example, our agency of about 500 employees was using seven different performance indicators. How many indicators would we need to track the performance of a nation? Canada decided to ask its own citizens what needed to be included in an index of well-being. Their responses led to the development of the Canadian Index of Wellbeing, an index of 64 indicators centered on eight domains—community vitality, democratic engagement, education, environment, healthy populations, leisure and culture, living standards, and time use (Pilling, 2018, pp. 236–237). I think most of us would agree that all these domains are important to the well-being of a nation and its people. Yet, amazingly, when international comparisons of economic and social performance are made, they most often use just a single indicator—GDP. GDP, which measures the value of the goods and services produced by a national economy, is one of the most widely reported national numbers. In the United States, for example, each quarter private economists and Federal Reserve banks attempt to forecast the first estimate of US GDP, which is issued by the Bureau of Economic Analysis roughly 30 days after the end of the quarter. When the number is finally announced, major newspapers publicize it and analyze its implications on their front pages, and financial markets react to the news. A similar process is repeated in major countries throughout the world. And when economic data from different countries need to be compared, GDP is usually the basis for the comparisons. These three books all use the measurement of GDP as a framework for a broader discussion of economic and social policy. GDP measures economic activity, but it does not measure economic or social well-being, equality of opportunity, environmental protection, or happiness. The use of GDP as the main yardstick for judging policy success and failure says that nations value economic growth above all else. If nations wish to pursue goals other than growth, they need yardsticks other than GDP. In these books, the critique of GDP stands in for a critique of an obsession with growth, and the search for alternatives to GDP stands in for the search for other societal goals and objectives. Despite its centrality in evaluating the prosperity of nations, GDP is a surprisingly recent invention. The crisis of the Great Depression of the 1930s, followed by the need to mobilize resources for the Second World War led governments in the United Kingdom and the United States to engage the leading economists of the time in developing new systems for measuring the economy. After the war, the Marshall Plan relied on GDP to help rebuild the economies of Europe, and under the auspices of the United Nations, GDP became an international statistical standard. GDP is part of the national accounts, which is a system based on double-entry accounting principles that measures aggregates that economists are interested in. Every economic transaction involves at least two parties, a supplier and a user, and national accounts thus can measure these concepts in multiple ways. The most basic definition of GDP is the “production approach”, in which the value added of an enterprise or an industry is equal to its output minus the intermediate inputs that are used in production. For example, when I was with BEA, I worked with the territorial government of American Samoa to develop GDP estimates for the territory. The major industry of the territory (which has a population of about 60,000) is tuna canning. The output is canned tuna, and the main intermediate inputs are fish (mostly imported from non-resident fishing vessels) and metal plates for the cans. The value added, or GDP, of the tuna canning industry is the value of the output minus the value of the inputs. The GDP for the total economy is simply the sum of the value added for all industries. There are two other approaches for measuring GDP. The “expenditure approach” is based on how the products are used; it is the sum of consumption by households and by governments, investment (or capital formation), and exports, less imports. The “income approach” is based on the income earned from production; it is the sum of wage and non-wage compensation paid to employees, operating surplus and proprietors' income earned by owners of capital, and the taxes payable by producers. In principle, these three approaches to calculating GDP—production, expenditure, and income—should add up to the same value, though with real-world data there are likely to be statistical errors or discrepancies (Coyle, 2014, pp. 25–28). These three approaches refer to measuring GDP in “nominal” terms, that is measured in current prices as reflected in the value of the nation's monetary unit, such as dollars or euros. But money can be an unstable yardstick, as inflation erodes its purchasing power (or less commonly, deflation causes its purchasing power to rise). Economic analysis often requires that changes in nominal GDP be split into changes in prices and changes in the volume of goods and services produced, or “real” GDP. GDP, of course, includes thousands of goods and services, each with its own prices and volumes, so the split must be made using index numbers (Coyle, 2014, pp. 30–31). As soon as GDP was conceived, a debate commenced about whether it was the best way to assess an economy. Economist Simon Kuznets wrote: “It would be of great value to have national income estimates that would remove from the total the elements which, from the standpoint of a more enlightened social philosophy than that of an acquisitive society, represent disservice rather than service” (Pilling, 2018, pp. 29–30). Kuznets would have preferred a measure that excluded socially harmful or wasteful products, including spending on armaments and other government spending. He was looking to measure well-being rather than production. While GDP covers market production exhaustively, it is less exhaustive in its coverage of production that is not marketed. For example, services provided by volunteers are mostly not counted. Nor does GDP count most work that household members do for themselves—activities such a child care, meal preparation, and household cleaning and maintenance. If a household pays a service provider to do them, these activities are included in GDP, but not if the household members do them themselves (Coyle, 2014, pp. 37–39). The Internet and smart phones have transformed modern life, and many traditional products no longer appear in GDP. A generation ago, most people spent money on cameras, film, and developing photos; now they mostly rely on smart phones for their photography, post the photos online, and no longer need to buy or develop film. People communicate using free websites or apps, where the services are funded by advertising. These free services make people better off, but they may not be counted in GDP or the productivity statistics. More generally, official statistics have trouble taking account of the quality improvements associated with innovative technology (Pilling, 2018, pp. 73–79). Over the last three decades global economic inequality has fallen, as large, formerly poor countries like China and India have developed and raised hundreds of millions of people from poverty into the global middle class. But nations usually look at inequality within the nation, rather than globally, and several countries—especially the United States—have seen large increases in inequality. GDP is a measure of aggregate production and does not measure how equally the benefits of that production are shared. GDP can tell you that a nation's total production is growing, but it cannot tell you if incomes are rising for all segments of society (Pilling, 2018, pp. 96–99). In discussing the economic development of poor countries, Pilling (2018) writes: “Growth—and by that I mean even raw growth as measured imperfectly by GDP—has the power to transform poor people's lives” (p. 124). Growth in GDP per capita can lead to reduced child mortality, better education, and better health. But these positive outcomes are not inevitable. In Angola, for example, oil wealth flowed to a narrow elite connected to the government and failed to improve child mortality and life expectancy. Translating economic growth into improvements in welfare takes good policies and time (Pilling, 2018, pp. 132–133). Economic growth has often been accompanied by environmental degradation, which is omitted from GDP. A country that has tempered its growth to maintain clean air and water and biodiversity may rank lower in GDP than one that has not. In fact, sometimes an increase in GDP may reflect production that exists only to counteract the effects of environmental degradation, such as when patients require medical treatment for the effects of particulate emissions (Masood, 2016, p. 9). While GDP has been successful at holding the attention of economists and policy makers, it fails as a one-size-fits-all measure of national progress or of the welfare of the citizenry. To fill this gap, various alternative measures have been suggested. Nordhaus and Tobin (1972) proposed a “measure of economic welfare” that attempted to remove expenditures that do not directly contribute to welfare, such as defense expenditures and commuting costs, and to add imputations for leisure and non-market work that are omitted from GDP but do contribute to welfare. They addressed sustainability in the sense of measuring the capital requirements for maintaining per capita GDP. They also discussed natural resources but concluded that natural resource constraints would not act as a major drag on economic growth. However, while their measure of economic welfare generated academic interest, government statistical agencies have largely ignored it. Another measure that has achieved some success in official, governmental use is the Genuine Progress Index (GPI). Based on work by Herman Daly, an ecological economist, the measure was adopted by the State of Maryland in 2010. It also starts with GDP and adjusts for income inequality, non-market benefits from the environment, and activities like volunteer work that are not counted in GDP. It is based on 26 economic, environmental, and social indicators, all expressed in dollars to produce a single number. Maryland compiled GPI back to 1960, and it showed that economic growth as measured by GDP often had offsetting effects on the environment or on congestion. State policy makers use GPI to take account of effects of economic growth on the environment or on health. The GPI has now been calculated for several other states and localities within the United States, as well as for a few countries (Pilling, 2018, pp. 223–231). Perhaps the most widely used indicator of welfare was developed by Pakistani economist Mahbub ul Haq for the UN Development Programme. In 1990, they launched the Human Development Index, the highlight indicator in the Human Development Report. The index was based on three indicators, which were available for most developing countries—life expectancy, adult literacy, and per capita income. Each indicator is measured on a scale of 0–1, and the category scores are averaged (Masood, 2016, pp. 89–97). In 2015, the countries with the highest HDI—Norway, Australia, Switzerland, Denmark, and the Netherlands—all had high incomes, but they differed from the countries with the highest GDP per capita—Qatar, Luxembourg, Singapore, Brunei, and Kuwait. This is because HDI and GDP per capita are measuring different things. While HDI reflects differences in income, it also reflects factors such as literacy and health that matter for welfare. More recently, the UN has added a measure of inequality to the index (Coyle, 2014, pp. 72–75; Pilling, 2018, pp. 232–234). During the global financial crisis and great recession of 2008, French president Nicolas Sarkozy decided that the mismeasurement of living standards was one of the problems that urgently needed to be addressed. He assembled an all-star international commission to look at alternatives to GDP, led by Stiglitz, Sen, and Fitoussi (2010). Their report, Mismeasuring Our Lives, recommends that policy makers pay less attention to GDP and pay more attention to distribution, quality of life, and sustainability. They did not think that any single indicator should replace GDP; rather, they recommended that a dashboard of indicators should describe the nation's well-being, focusing especially on the household perspective, taking account of non-market activities, and looking at indicators of health, education, governance, social connections and relationships, the environment, and insecurity. In an article in Nature, Costanza et al. (1997) attempted to measure the “value of the world's ecosystem services and natural capital”. They measured these services in dollars so that they could be compared directly with GDP. Because most of these services are not transacted in markets, they largely relied on indirect methods to value them—especially, estimates of “willingness to pay”. Their estimate of the value of ecosystem and natural capital services was huge—$33 trillion in 1997, much larger than world GDP at the time. Their estimates also proved to be controversial. Economists criticized the methodology, which required substantial extrapolation from data and on the other the of a value on (Masood, 2016, pp. Despite the the United has work in this its global on of and or In and a from the produced a that addressed and global Their concluded that reflected a market failure and that by spending of GDP now to global the economies could an in global consumption to While the had some with the global attention largely to traditional growth (Masood, 2016, pp. If it is to indicators for well-being, should we simply pursue In the of on nation to do that when that national rather than GDP, would be the of national policy. of was not the same that would measure in their It was a of one to living in with and our and the and of our own Their of did not with was in (Pilling, 2018, pp. 1990, the of by economists has have people do people And they have used data to to various economic of this work is based on data that people to assess their own happiness. The on seven main of relationships, financial health, and For example, people with a especially are than are or also takes a on happiness. to have a positive on and are of These may some policies for such as or employees the to of (Pilling, 2018, the World has provided of the countries the The countries to be and the to be But income does not all the In the 2016 report, for example, in it in GDP per The of the most of the and countries to GDP per healthy life expectancy, social to count to make life and of (Pilling, 2018, pp. Ehsan Masood is a and and The Great at this the of invention. These in are not in or but rather are academic government or at international such as the United is largely by a of of developed new for measuring economies and about Mahbub ul the economist the Human Development Index, and the Canadian oil became the of the UN Programme. about the of as a the of and Herman Daly, one of the of the of ecological is and and of the three books, I think this is the one from which I the most in of new I also a of where I with He that because GDP is as a policy the only way to better policy is to the definition of GDP (Masood, 2016, pp. But what does not to is that the current definition of GDP is the measure for many of policy. For example, the monetary policy or the would not be and would be if the definition of GDP were to ecosystem services or indicators. does not mean that a broader indicator or of indicators would not also be for it just that different measures are for different policy The other two books that multiple indicators are but Masood the The other where I with is about the of the of gross national product, or was because it is more to the statistics on national income that had been was by the and World War The of was a and not the of any single I think all three books that But what I think they is in the of a few such as Simon Kuznets and of While did important in the How to for the was not the first work to a measure of including government For example, at the developed estimates that included government spending and I the first to use the national A of the of and GDP has not been but when it I think it more and be less by than the that is David Pilling is an and for the and has reported from several The Growth attention to the developing with about a of the focusing on the problems of economic He and people from many is and For have not this is the most of the three all three books are and to In this we for example, about the financial the American and how GDP is measured for in would like to GDP, Pilling for GDP as one in a dashboard of indicators, and of the indicators would of is about on measuring wealth (Pilling, 2018, pp. While I agree with that wealth can be as important as income (or I it that does not that some countries do produce estimates of at least some of the of The of or international for national for measuring and several economies do produce wealth statistics. these statistics are not available for the less developed countries, and even for developed countries they does not Pilling would like to For example, would like to estimates of capital, which are not in national wealth statistics some countries are to But more generally, I would like to have seen more attention to the data other than GDP that are Diane Coyle is an economist has worked in and reflects a of how GDP is used by economic and the in the is is also with the main to just The can be when writes: of GDP is also the of (Coyle, 2014, p. a of the is a economic of and the the of after World War the of the and the financial crisis and recession of the last with a that is a to More than the other books, critique of GDP the in which it is even as a measure of problems in for quality and new goods and the failure to household production. main of with Coyle is with of the national accounts treatment of financial can think about the financial services produced by a it services to its are and To these services, sometimes banks also rely on the make money from the the they and any they pay to The national accounts the as an indirect service and they part of the service to the and part to the the treatment in GDP that part of the paid by a is an indirect service and the is of of the treatment of financial services is that in to a service and interest, there should be a that covers the associated with on (Coyle, 2014, pp. The treatment recommended by the does not that which could GDP to the service this the US national accounts did the as and in their treatment to remove the But Coyle to and the treatment to to But the current is with economic for example, in William on monetary and some problems that the To the that problems in measuring financial services, I think they are associated more with rather than with the three books into the of measuring the performance of the economy, the environment, and well-being. They also use the framework of statistics to our about what goals our society should be of is that when people use they should think more about the concepts that are measured and take that the is measuring the in GDP is and in many other data such as national income, household income, or household consumption would better the should more with the available statistics and about them so that we can make more use of Economist and from US Bureau of Economic

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Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.313
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it