Origins of the Unemployment Rate: The Lasting Legacy of Measurement without Theory

Card, David

doi:10.1257/aer.101.3.552

Cited by 42 publications

(30 citation statements)

References 17 publications

(12 reference statements)

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“…Everyone came away realising that no one had a clue what the actual unemployment rate was. And so the American Statistical Association set up the Committee on Governmental Labor Statistics to assist with wording questions about joblessness for the 1930 census 2 …”

Section: The Historical Contextmentioning

confidence: 99%

Measuring Society Who, What, When, Where, Why and How

Nagaraja

2019

Significance

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Section: The Historical Contextmentioning

confidence: 99%

Measuring Society Who, What, When, Where, Why and How

Nagaraja

2019

Significance

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“…Before the 1920s, the United States produced none of the aggregate economic statistics we now take for granted. Data -official or privately produced -on employment, inflation, income distribution, and growth were largely unavailable throughout the 1800s, and only became available at the state or local level in the 1890s to 1910s (Stapleford 2009, Card 2011). In the 1920s-1940s, the United States government began to produce consistent series of national data on inflation (the Consumer Price Index), unemployment (via the Current Population Survey), and economic growth (in the National Income and Product Accounts).…”

Section: Building Knowledge Infrastructuresmentioning

confidence: 99%

Rediscovering the 1%: Knowledge Infrastructures and the Stylized Facts of Inequality

Hirschman¹

2019

Preprint

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What is the relationship between theory and observation in the social sciences? This article advances a sociological reformulation of the “theory-ladenness” of data. Drawing on insights from the history and sociology of science, I argue that knowledge infrastructures, not just individual experts’ perceptions, are theory-laden. This conceptual framework helps to explain why scholars missed the rise of top incomes in the 1980s and 1990s. In the 2000s, newly-analyzed tax data revealed that top incomes had begun a dramatic upward climb in the early 1980s, summarized as the rise of “the 1%.” This article explains why it took two decades for this increase to become salient. I show how mid-20th century economic theory shaped the assembly of two knowledge infrastructures for identifying stylized facts about income inequality, both of which were incapable of tracking top incomes. Macroeconomists focused on labor’s share of national income, but ignored the distribution of income between individuals. Labor economists drew on newly- available survey data to explain wage disparities. By relying on surveys, these scholars filtered top incomes out of view: surveys top-coded high incomes and thus were incapable of detecting the rise of the 1%. Studies of top incomes that relied on income tax data fell by the wayside, creating the conditions under which experts, policymakers, and the public alike could be surprised by the rise of the 1%. Knowledge infrastructures are laden with past theories; in turn, these infrastructures shape the production of new theories and new ways of understanding contemporary social problems.

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“…Data -official or privately produced -on employment, inflation, income distribution, and growth were largely unavailable throughout the 1800s, and only became available at the state or local level in the 1890s to 1910s (Stapleford 2009, Card 2011). In the 1920s-1940s, the US began to produce consistent series of national data on inflation (the Consumer Price Index), unemployment (via the Current Population Survey), and economic growth (in the National Income and Product Accounts).…”

Section: Establishing the Regimesmentioning

confidence: 99%

Rediscovering the 1%: Economic Expertise and Inequality Knowledge

Hirschman¹

2016

Preprint

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In the 2000s, academics and policymakers began to discuss the growth of top incomes in the United States, especially "the 1%" Newly analyzed tax data revealed that top incomes had begun a dramatic upward climb in the early 1980s. This article investigates why it took two decades for this increase to become politically and academically salient. I show how experts assembled two "regimes of perceptibility" for producing knowledge about income inequality, and that neither was capable of tracking top incomes. Macroeconomists focused on labor's share of national income, but ignored the distribution of income between individuals. Labor economists drew on newly available survey data to explain wage disparities. By relying on surveys, these scholars unintentionally eliminated top incomes from view: surveys top-coded high incomes and thus were incapable of detecting the rise of the 1%. Studies of top incomes that relied on income tax data fell by the wayside, creating the conditions under which experts, policymakers, and the public alike could be surprised by the rise of the 1%. This historical study offers insights into the political power of economic expertise by clarifying the complex linkages between observations, stylized facts, causal theories, and policy attention.

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Origins of the Unemployment Rate: The Lasting Legacy of Measurement without Theory

Cited by 42 publications

References 17 publications

Measuring Society Who, What, When, Where, Why and How

Measuring Society Who, What, When, Where, Why and How

Rediscovering the 1%: Knowledge Infrastructures and the Stylized Facts of Inequality

Rediscovering the 1%: Economic Expertise and Inequality Knowledge

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