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LABOR ECONOMICS Lecture 5: Earnings Inequality–Facts and Explanations Prof. Saul Hoffman Université de Paris 1 Panthéon-Sorbonne March, 2013

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Overview Focus on three very important & influential papers (sections only): Katz and Murphy (KM), "Changes in Relative Wages, 1963-87: Supply and Demand Factors," Quarterly Journal of Economics, 1992. Juhn, Murphy, and Pierce (JMP), Wage Inequality and the Rise in Returns to Skill, Journal of Political Economy, 1993. Autor, Katz, and Kearney (AKK), Trends in US Wage Inequality, Review of Economics and Statistics, 2008 2

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Overview – What Happened and When Earnings differences between different groups of workers, esp by education, increased, beginning 1980s. Interpret as changes in factor prices for different factors of production. (KM) Supply/Demand Analysis – Compare W with E by group. Do supply-only explanations make sense? If demand-side explanations are required, what is source? Skill-biased technological change (SBTC) v industry shifts Earnings differences among workers within groups also increased, beginning 1970s. How interpret? Rising returns to skill, measured and unmeasured? (JMP) Subtler analysis of how computerization affected wage distribution (AKK) 3

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Earnings by Education in US, 1963-2005 (AKK) 4

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Three Inequality Trends (AKK) 5

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Supply/Demand Approach (KM) 6 w E Requires D: College Ed, 1980s-2000s Requires S: College Ed, 1970s Requires S Requires D

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Demand Shifts-The SBTC Hypothesis (KM) Between-industry v within-industry demand shifts Between-industry Example: rise/fall of industries with different underlying skill intensity of demand. Within-industry: SBTC (skill-biased technological change) and change in MPs; change in demand at fixed input prices. Computerization Graphing of possible Effects Subtler analysis: what do computers do? See later slide 7

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Decomposition of Earnings ChangesSkills v Prices (JMP) Human Capital Earnings regression: Y it = X it β t + μ it Y= earnings; X= observable skill measures (education, experience) β = value of unit of X (return to education) μ = residual part of earnings unrelated to X or β. Decompose change in wage inequality over time into three sources: in individual characteristics (X) in prices (value of skill) (β)between-group inequality in distribution of unobservables (μ)within-group inequality 8

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Decomposition of Earnings Changes (cont.) Compute three hypothetical wage distributions; compare to actual change in inequality Pooled Regression with constant prices and distr of observables Y 1 it = X it β + μ - isolates impact of change in observables (X) Prices vary with year: Y 2 it = X it B t + μ – isolates impact of changing return to Xs All varying, including distribution of unobservables: Y 3 it = X it B t + μ it Estimate, then find 90/10 differential for each distribution to assess impact on actual change Findings: Figure 7 & Table 4 9

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Computers and Labor Demand by Task A Subtler View 10

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Polarization of Earnings- 90/50 v 50/10 trends Computerization has non-monotonic impacts on demand for skill throughout earnings distribution Increased demand for abstract tasks Decreased demand for routine tasks No effect on routine tasks that are not amenable to mechanization; Ex: Personal Services (restaurant, entertainment, travel, gyms/personal trainers). See Autor/Katz/Kearney for more (Fig 10 &11) 11

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Labor Market Inequality in the US Summary Income Inequality has been increasing in U.S. since early 1970s after long period of decline. Big increase in 1980s, weaker since Reflects increases in both between-group and within-group inequality Demand probably more important than supply in explaining increase in between-group inequality. Both within-in industry and between-industry changes are important. Non- neutral (skill-biased) technological change very important. Increase in return to observed skills (education) and unobserved skill (residual). Increase in within-group inequality more important than increase in between- group inequality --- and harder to explain! Computerization & its non-monotonic impacts 12

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