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American Inequality in Historical Perspective

American Inequality in Historical Perspective. Economics 2333 Class 10 Spring 2014 Professor Robert A. Margo. General Outline. Background Goldin and Katz: The “Race” Between Technology and Education Katz and Margo: A Unified View of the Relative Demand for Skills Across the C19 and C20

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American Inequality in Historical Perspective

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  1. American Inequality in Historical Perspective Economics 2333 Class 10 Spring 2014 Professor Robert A. Margo

  2. General Outline • Background • Goldin and Katz: The “Race” Between Technology and Education • Katz and Margo: A Unified View of the Relative Demand for Skills Across the C19 and C20 • Goldin and Margo: The Great Compression of the 1940s • If time: Frydman and Saks on executive pay

  3. Background: American Inequality in Historical Perspective • Approaches to inequality: functional versus individual (or household) distribution. • Functional: factor shares. For most of American history, little change in labor’s share (slight increase). Major change was in land vs. capital – land’s share decreased from C19 to C20, capital’s share increased. BUT recently capital’s share has increased – see new book by Thomas Piketty. • Individual (household) distribution: human capital (Goldin and Katz), gender/race/ethnic discrimination, institutional factors (unions, minimum wage). • Kuznets curve (AER 1955) – inequality vs. per capita income follows an inverted U. Model involves shift of labor out of agriculture. Inequality is much higher in non-farm economy because of diversity of skills and (initially) inelastic supplies of skills. As labor shifts out of agriculture, inequality increases. Supply of skills catches up and government may engage in redistribution, producing downward segment of the Kuznets inverted U. • Large literature in development on the Kuznets curve. Historical literature is mostly Williamson and various co-authors.

  4. Summary: Broad History of US Inequality • C19: Williamson and Lindert argue that inequality rises, starting around 1820. Evidence is drawn from available wage series by occupation and also wealth data. • According to WL, skill premium (artisan/common labor wage ratio) increased sharply from 1820 to 1860. However, errors in WL (see Margo 2000). Archival wage series by Margo (2000) finds decrease or no trend in artisan/unskilled wage ratio and slight increase in clerk/unskilled; see below. • Wealth inequality does appear to increase over the C19 but further work is needed. • VERY important: previous work on C19 ignores slaves and Native Americans before Civil War BUT post Civil War data will include former slaves (and Native Americans). New project by Williamson and Lindert attempts to correct for this but not ready for prime time, IMHO. • In C20, inequality declines in the first half of the century and then rises in the second half. Based on occupational wage data, Iowa state census of 1915, 1940-present IPUMS and CPS, IRS tax records, SSA master file, SEC filings (Frydman and Saks). • Moral: not a Kuznets curve, but possibly a cycle. Cycle appears more dramatic in the C20 than in the C19.

  5. The Race Between Technology and Education • New technology is frequently “embodied” in capital goods (e.g. computers). In 20th century capital and skilled (educated) labor are relative complements. Fall in price of capital → increase in relative demand for skilled labor. • If relative supply of skill keeps up, relative wage of skilled labor won’t change. But if supply lags behind demand, relative wage of skilled labor increases. • Important book by Goldin and Katz (2008) shows that, over the course of the 20th century in the US, relative supply of skilled labor grew more quickly than demand in the first half of the 20th century, but slower in the second half. So, relative wage of skilled labor fell during first half, but rose in second. Rise in second is part of the rise of the “one percent”. • Relative demand for skilled labor increased in every decade of the 20th century at about the same pace, except for the 1940s when it was slower. More on the 1940s later. • Goldin and Katz argue that capital-skill complements originates with diffusion of electrical power. Electricity permits many new skill intensive technologies and also eliminates many unskilled jobs on the shop floor.

  6. Main Points, Katz and Margo • Standard economic history/labor history view: Technology and “skill” are relative complements in C20/C21 but capital deepening is “de-skilling” in C19. • KM emphasize the continuity between the first (C19) and second “industrial revolution” (C20) in US economic development. • Link (informal): task-based framework of Acemoglu-Autor. In both IRs new technology embodied in capital goods alters the allocation of labor of different levels of education/skill to tasks. This alters the relative demand for different levels of education/skill.

  7. Deep Background • Williamson & Lindert (1980). Assumed capital-skill complementarity in C19 manufacturing. Claimed to find evidence of an American inverted-U: rising skilled blue collar-unskilled wage premium before 1860. • Upward ante-bellum trend in artisan/unskilled wage ratio disputed by Margo (2000) who finds upward trend in white collar/unskilled wage premium before Civil War. • James & Skinner (1983). Capital complementary to natural resources but not skill. • Goldin & Sokoloff (1982): relative use of women and children increases with establishment size, 1820-1850. • Standard labor history perspective: diffusion of factory system is “de-skilling”: percent artisan ↓. Atack, Bateman, and Margo (2004) show negative relationship between average establishment wage and size. • Goldin & Katz (1998): origins of technology-skill complementarity for production workers found in diffusion of electrical power. Wage-firm size relationship turns positive.

  8. Task-Based Perspective I • Dramatic capital-deepening in C19 century manufacturing. Takes the form of “special purpose, sequentially-implemented” machinery. • Translation: machine (partially) substitutes for skilled artisan in production. Today, the computer substitutes for mid-level white collar. • BUT skilled labor designs the machines and skilled labor installs and maintains the machines. Eg. Steam-powered plants hire “machinists” and/or “engineers”. Today, IT designs and implements software, maintains system. • In C19 firms become much larger. Why? Improved transportation (Adam Smith) plus mechanization (steam). Impact on white collar demand.

  9. Task-Based Perspective II • Prediction (from slightly modified Goldin and Katz 1998 framework): • As firms become bigger from access to cheaper motive power (steam power), % skilled artisan ↓ and % operative ↑. • BUT as firms get bigger, managerial tasks increase in number & complexity & % white collar (arguably) ↑. • Division of labor in manufacturing “hollows” out the middle (skilled blue collar) in favor of the low-skill (operative) and high-skill (white collar) jobs.

  10. Katz-Margo: Evidence for 19th Century Manufacturing • In manufacturing, labor shifts towards larger, more capital intensive establishments. Firm size increases, economies of scale. • Using 1850-80 censuses of manufacturing, KM show that capital intensive, steam-powered establishments used relatively more unskilled labor. Effect of steam/capital is mostly explained by larger firm size. Indirect implication is that capital deepening encouraged more division of labor in production.

  11. Was Technical Change “De-Skilling” in C19 America? Occupation Distributions • Evidence from manufacturing censuses suggests 19th century technical change was “de-skilling” but does not directly address white collar skills. • KM look at occupation by industry starting in 1850. Compute a very broad occupation distribution for manufacturing – white collar, skilled artisan, and operative/unskilled – and somewhat more detailed classification for overall economy.

  12. Results: Occupation Distributionsfor 1850 to 1910 • Manufacturing: clear evidence of “hollowing-out”. Share artisan decreases, while share white collar and share operative/unskilled increase. • Overall: (a) no long term trend in share artisan (or, modest U-shape) (b) share white collar increases (c) share operative/unskilled decreases. • Why the difference? (a) manufacturing sector grows, relatively intensive in artisan labor despite hollowing out (b) construction sector is an increasing share of GNP, intensive in artisan labor (c) share operative/unskilled rises in manufacturing but declines in overall economy because of shift of labor out of agriculture. • Bottom line #1: C19 manufacturing was “de-skilling” in the artisan sense but not white-collar sense. Makes sense in task framework. • Bottom line #2: NO de-skilling in the aggregate economy. Increase in relative demand for educated (white collar) labor extends backward in time from Goldin-Katz to at least 1850.

  13. Supply vs. Demand: Relative Wages • Relative wage of educated labor declines first half of C20, rises during second half (Goldin and Katz 2008). Pattern is due to supply shifts; relative demand for skilled/educated labor increases rapidly & steadily. • What about C19? Cannot say about returns to schooling directly because C19 censuses only collected data on literacy and nothing on earnings/income. • KM use archival data to construct new time series of wages for unskilled labor, artisans, and white collar workers. Evidence suggests that relative wage of white collar workers increases, flat for artisans.

  14. New Wage Series • We extend Margo (2000) by presenting national wage series for common labor, artisans and white collar for 1866-1880. • Same data source (Reports of Persons and Articles Hired) and similar methods of construction (hedonic wage regressions) • Caveat: series are first produced at region-occupation level and then aggregated using region-occupation weights. Some inconsistencies in weighting pre vs. post-bellum.

  15. White Collar (Clerk) Earnings Increase relative to Common Laborers and Artisans from 1820s to 1870s U-shaped earnings of Artisans relative to Common Laborer ends up at About same places in 1870s as in the 1820s

  16. Occupational Change: 1920 to 2010 • Monotonic secular skill upgrading from 1920 to 1980 in overall economy and manufacturing • Polarization of employment growth from 1990 to 2010 • Seen in declining share of “middle skill” jobs • Continued rise in prof/managerial share • Rise in in-person service employment and low-skill share for overall economy in 2000s

  17. Table 6A: Occupational Change from 1920 to 2010Aggregate Economy, Civilian Employment, 16+

  18. Table 6B: Occupational Change from 1920 to 2010Manufacturing, Civilian Employment, 16+

  19. Summary: Katz and Margo • Capital deepening relentless in US economic history. Alters task assignments in production process, which affects relative demand for different types of skills. • In C19 manufacturing capital deepening displaced tasks performed by skilled artisans for those performed by operatives + specialized machines, especially if powered by steam. Hollowing-out of occupation distribution in C19 manufacturing is conceptually similar to today (computers vs. mid-level white collar). • There is NO de-skilling in aggregate economy post-1850 and likely earlier (but not that much earlier). • In 19th century race was slightly won by technology like second half of 20th century, and unlike first half of 20th century.

  20. The Great Compression • Sharp reduction in inequality in the 1940s. “Great Compression” is an (obvious) play on “Great Depression”. • But GD does not appear to be the cause of the GC. Inequality rises in the early 1930s but by 1940 is back to where it was at the start of the decade. • GC reflects forces associated with WW2 and various post-war institutional changes (GI Bill, minimum wage, unions). Also some role for narrowing of geographic differences in school quality. Change in inequality is so large that it mostly remains in place until 1970. • Important side effect of GD: narrowing of black-white income differences in 1940s, rivals change during Civil Rights movement of the 1960s (Margo 1995). Flip side is rising wage inequality since 1970s has impeded black-white convergence.

  21. Trends in wage dispersion

  22. Frydman and Saks • Executive pay has risen sharply, absolutely and relative to the average worker in recent decades. Are the recent trends in the level and structure of executive pay unusual? • Are the determinants of the recent trends in compensation similar to the factors that shaped compensation in earlier periods? • A competitive labor market for executives (scale) • Rent extraction by CEOs (corporate governance) • Managerial incentives (pay-to-performance) • Changes in managerial skills

  23. New dataset on executive compensation Executive compensation: 1936 – 1992: annual data from historical proxy statements and 10-K reports - 50 largest firms in 1940, 1960 and 1990 (total of 101 firms) - 3 highest-paid executives in each firm 1992 – 2005: annual data from Compustat’s Executive Compensation Database - also based on proxy statements - 3-highest paid executives in the same 101 firms Other firm-level data: - Market value from CRSP - Other firm-level variables from Moody’s Manuals (1936-1950) and Compustat (1950-2005)

  24. Sample Summary Statistics

  25. Representativeness of the Sample Potential issue: - (Small) Unbalanced panel of firms that are successful at some point Compare to other samples: - Forbes surveys (800 firms since 1970) - Hall & Liebman (475 firms, 1980 to 1994) Use weighting schemes: - inversely proportional to probability of being selected among the 500 largest firms in each year - inversely proportional to firm’s market share or the firm’s share of aggregate sales among the 500 largest firms Other uses of our data: - firm in sample only since year of selection - use years close to 1940, 1960, and 1990 only Conclusion: - our sample is representative of the largest 300 public firms in the economy in each year - no significant bias for using the whole time span for each firm

  26. Median Real Value of Total Compensation, 1936-2005

  27. Median Real Value of Total Compensation, 1936-2005 Note: Based on the three highest-paid officers in the largest 50 firms in 1940, 1960 and 1990.

  28. Average and Median Total Compensation, 1936-2005

  29. Distribution of Total Compensation, 1936-2005 90th percentile 75th percentile 50th percentile 25th percentile 10th percentile

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