MEASURING AND INTERPRETING TRENDS IN ECONOMIC INEQUALITY†

The Polarization of the U.S. Labor Market

By DAVID H. AUTOR,LAWRENCE F. KATZ, AND MELISSA S. KEARNEY*

Much research (surveyed in Katz and Autor, We reconsider this revisionist view, focusing 1999) documents a substantial widening of the on a marked change in the evolution of the U.S. U.S. wage structure since the late 1970s, driven wage structure over the past 15 years and di- by increases in educational wage differentials vergent trends in upper- and lower-tail wage and residual wage inequality. The growth in inequality. We first document that wage in- wage inequality was most rapid during the equality in the top half of the distribution has 1980s, and involved a spreading out of the exhibited an unchecked secular rise for 25 entire wage distribution. Rapid secular growth years, but it has ceased growing since the late in the demand for skills, partly from skill-biased 1980s (and for some measures narrowed) in the technical change (SBTC), combined with a bottom half of the distribution. We next dem- slowdown in the growth of the relative supply onstrate that employment growth differed sharply of college workers helps explain these wage in the 1990s versus the 1980s, with more rapid changes. Eroding labor market institutions—the growth of employment in jobs at the bottom and minimum wage and unions—further contrib- top relative to the middle of the skill distribu- uted to rising wage inequality. tion. Borrowing terminology from Maarten Goos Recent work emphasizes a slowing of wage and Alan Manning (2003), we characterize this inequality growth over the last 15 years (David pattern as a “polarization” of the U.S. labor Card and John DiNardo, 2002; Thomas Le- market, with employment polarizing into high- mieux, forthcoming). This “revisionist” litera- wage and low-wage jobs at the expense of mid- ture views the 1980s surge in wage inequality as dle-skill jobs. We then show how a model of an “episodic” event caused by institutional computerization in which computers comple- forces and argues that “modest” inequality ment nonroutine cognitive tasks, substitute for growth in the 1990s is inconsistent with a key routine tasks, and have little impact on nonrou- role for SBTC. tine manual tasks, can rationalize this polariza- tion pattern.

† Discussants: Eli Berman, University of California-San Diego; Amitabh Chandra, Dartmouth University; Lawrence I. Divergent Upper- and Lower-Tail Wage Katz, Harvard University. Inequality * Autor: Department of Economics, Massachusetts Insti- tute of Technology, 50 Memorial Drive, E52-371, Cam- Figure 1 displays the evolution of the 90-50 bridge, MA 02142 and NBER (e-mail: [email protected]); and 50-10 log-hourly wage differentials for all Katz: Department of Economics, Harvard University, Lit- workers (males and females) from 1973 to 2004 tauer Center, Cambridge, MA, 02138 and NBER (e-mail: using (hours-weighted) wage data from the Cur- [email protected]); Kearney: The Brookings Institution, 1775 Massachusetts Avenue, N.W., Washington, DC, rent Population Survey (CPS) May samples (for 20036 and NBER (e-mail: [email protected]). We 1973–1978) and Merged Outgoing Rotation are grateful to Daron Acemoglu, Eli Berman, Frank Levy, Group samples (for 1979–2004).1 It shows sub- and Sendhil Mullainathan for superb suggestions, and to Michael Anderson and Tal Gross for excellent research assistance. Autor acknowledges support from the National Science Foundation (CAREER SES-0239538) and the 1 Our sample selection and data processing steps for CPS Sloan Foundation. Katz acknowledges support from the wage data are the same as those described in the Data Mellon Foundation and the Radcliffe Institute for Advanced Appendix of Autor et al. (2005b), extended to cover wage Study. data for 2004. 189 190 AEA PAPERS AND PROCEEDINGS MAY 2006

FIGURE 1. MALE AND FEMALE LOG HOURLY 90/50 AND 50/10 EARNINGS RATIOS FIGURE 2. CHANGES IN MALE AND FEMALE LOG REAL HOURLY EARNINGS BY PERCENTILE, 1973–1988 Source: Current Population Survey May and Monthly AND 1988–2004 Files, 1973–2004. Source: See Figure 1. stantial increases in upper-half (90-50) and lower-half (50-10) wage inequality from 1979 2005a). Using tax-return data, Thomas Piketty to 1987, expanding the 90-10 wage differential and Emmanuel Saez (2003) further document by 21 log points. But the trends in upper-half the divergence of earnings in the very upper-end and lower-half inequality diverge after 1987, of distribution (the top 1 percent) relative to with upper-half wage inequality continuing to other workers since the 1970s. rise steadily while lower-half inequality growth We examine how a nuanced view of techno- ceased in the late 1980s (with a contraction in logical change may contribute to these trends. the 50-10 differential of four log points from Following Autor et al. (2003), our framework 1987 to 2004). Monotonic rising wage inequal- observes that the first-order impact of comput- ity in the 1980s and diverging upper- and lower- erization is to displace “middle skilled,” routine tail inequality since the late 1980s are observed cognitive and manual tasks, such as bookkeep- for males and females separately, for the weekly ing and repetitive production work. If routine wages of full-time workers, and for the CPS tasks are more complementary to high-skilled March samples (Autor et al., 2005a). abstract tasks than to “nonroutine manual” tasks Figure 2 illustrates where in the wage struc- (such as those of truck drivers), the computer- ture the divergence of upper- and lower-tail ization of routine work can generate labor mar- wage inequality trends have occurred. It plots ket polarization. The model predicts that wage cumulative log hourly real earnings growth (in- polarization should be accompanied by employ- dexed using the Personal Consumption Expen- ment polarization. ditures implicit price deflator) by wage percentile for 1973 to 1988 and for 1988 to II. Job Polarization Trends 2004. The figure shows an almost linear spread- ing out of the entire wage distribution for 1973 We examine trends in the “quality,” skill to 1988. In contrast, wage growth has polarized content, and task content of U.S. jobs since since 1988, with faster wage growth in the 1980. We follow Goos and Manning’s (2003) bottom quartile than in the middle two quartiles, analysis of the United Kingdom in exploring and with the most rapid rise and a continued how U.S. employment growth by occupation spreading out of the distribution in the top has been related to skill proxied by initial edu- quartile. cational levels or wages. The divergence of upper- and lower-tail wage We first sort (3-digit) occupations into per- inequality since the late 1980s holds for residual centiles by mean years of schooling in 1980, wage inequality and is robust to adjustments for using data from the 1980 Census Integrated labor force composition changes (Autor et al., Public Use Microsample (IPUMS). Figure 3 plots VOL. 96 NO. 2 MEASURING AND INTERPRETING TRENDS IN ECONOMIC INEQUALITY 191

We have tested the robustness of these pat- terns with an alternative skill definition—me- dian hourly wage in an occupation in 1980. This skill measure also indicates that employment growth was roughly monotonic in skill during the 1980s and then polarized in the 1990s. Da- ron Acemoglu (1999) reports similar U.S. job polarization from the mid-1980s to early 1990s using more aggregated industry-occupation cells, and Goos and Manning (2003) document job growth polarization for Britain, another country with a large increase in wage inequality. A third methodology for measuring employ- FIGURE 3. SMOOTHED CHANGES IN OCCUPATIONAL ment structure trends involves changes in em- EMPLOYMENT SHARES 1980–2000, WITH OCCUPATIONS ployment by job task content. Autor et al. RANKED BY THEIR 1980 AVERAGE YEARS OF SCHOOLING (2003) take this approach using data on task Source: Census Integrated Public Use Microsamples content from the Dictionary of Occupational 1980, 1990, and 2000. Titles aggregated to Census occupations. We extend their analysis of employment growth in industry-gender-education cells using CPS data employment growth, measured as the change in through 2002. We find that employment growth an occupation’s share of total hours worked, was most rapid in the 1990s for cells intensive from 1980 through 1990 and 1990 through in nonroutine cognitive tasks (those most com- 2000, against 1980 occupational skill (educa- plementary with computerization), was declin- tion) percentile using employment shares from ing at an increasing rate in the 1990s for cells the 1980 to 2000 IPUMS.2 For the 1980s, the intensive in routine cognitive and manual tasks figure shows declining employment at the bot- (those most substitutable for computers), and tom of the distribution, and near-monotonic (al- ceased declining in the 1990s for (typically low- most linear) increases in employment moving wage) jobs intensive in nonroutine manual tasks. up the education distribution. In contrast, em- These patterns of employment growth by ed- ployment growth in the 1990s polarized with ucation, wages, and task intensity suggest that the most rapid increases in high-skill jobs, slow- labor demand shifts have favored low- and est growth in middle-skill jobs, and modest high-wage workers relative to middle-wage growth in low-skill jobs. workers over the last 15 years. This contrasts This pattern of job growth (and possible labor with the labor demand shifts of the 1980s, demand shifts) corresponds well with the wage which appear to have been monotonically rising structure changes shown in Figure 2. In a com- in skill. parison of the 1980s to the 1990s, we find that employment growth is more rapid in the 1990s III. A Model and Interpretation below the fortieth and above the eightieth per- centiles of the occupational skill distribution Our framework, building on Autor et al. and declines in the middle. (2003), considers how a decline in the real price of computing power may lead to a polarization of work. The model is based on four observa- tions that are well supported by the existing 2 We employ a consistent set of occupation codes for census years 1980, 1990, and 2000 developed by Peter B. evidence. First, computer capital—denoted by Meyer and Anastasiya M. Osborne (2005). We use a locally K and measured in efficiency units—is a close weighted smoothing regression (bandwidth 0.8 with 100 substitute for human labor in routine cognitive observations) to fit the relationship between decadal growth and manual tasks, such as clerical work and in occupational employment share and occupations’ initial percentile in the 1980 skill distribution, measured by mean repetitive production tasks. Second, routine task years of schooling. Figure 3 plots the fitted values from input—embodied in either computer capital or these regressions. human labor—is a complement to workers 192 AEA PAPERS AND PROCEEDINGS MAY 2006

engaged in abstract reasoning tasks such as chooses to supply either one efficiency unit of ␩ Ͻ problem solving and coordination. Third, there labor to manual tasks if i wm/wr or supplies ␩ exists a panoply of nonroutine manual tasks for i efficiency units of labor to routine tasks oth- which computers currently neither directly sub- erwise. Thus labor supply to manual (routine) stitute nor strongly complement, such as the tasks is weakly upward (downward) sloping in tasks performed by truck drivers, waiters, and wm/wr. janitors. We refer to these categories of tasks as Equilibrium occurs when: (a) the economy abstract (A), routine (R), and manual (M); and operates on the demand curve of the aggregate we consider them to correspond roughly to production function; (b) each factor is paid its high-, intermediate-, and low-skilled occupa- marginal product; and (c) the labor market tions. Lastly, we observe that workers’ ability to clears so that no worker wishes to reallocate engage in specific tasks is contingent on their labor input among tasks. education. We assume that there are two types Because computer capital is a perfect substi- ϭ ␳ ␳ of workers: college workers, who can perform tute for routine labor, wr , a decline in abstract tasks; and high school workers who can reduces wr one for one. We are interested in the substitute between routine and manual tasks. effect of a decline in ␳ on: (a) the equilibrium The exogenous driving force in our model is quantity of routine task input; (b) the allocation the precipitous decline in the price of computing of labor between routine and manual tasks; (c) power in recent decades. Computerization—the the wage paid to each task; and (d) the observed falling real price of computers—lowers the wage in each job type—which, for routine tasks, price of routine task input and increases demand may differ from the wage paid per efficiency for routine tasks. We sketch the formal model unit of routine task input. here and refer the reader to an online Theory Since own-factor demand curves are down- Appendix available at www.e-aer.org/data/ ward sloping, a decline in ␳ raises demand for may06_app_p06006.pdf. routine tasks. This demand can be supplied by Output, priced at unity, is produced using the either additional computer capital or routine aggregate Cobb-Douglas production function labor input. Due to worker self-selection, the Y ϭ A␣R␤M␥ with ␣, ␤, ␥ ʦ (0, 1), ␣ ϩ ␤ ϩ additional demand will be supplied by computer ␥ ϭ 1, and where A, R, and M denote the three capital. The reason is that manual and routine tasks above. Abstract and manual tasks are per- tasks are q-complements—a rise in routine in- ␳ formed by workers who supply labor inputs, LA put (spurred by the fall in ) raises the marginal and LM. Routine tasks can be performed either productivity of manual task input. ␳ by workers who supply LR or by computer cap- When (and thereby wr) falls, some work- ital, K, measured in efficiency units, which is a ers—those with relatively low ␩—self-select perfect substitute for LR. Computer capital is from routine to manual tasks. This additional supplied perfectly elastically to routine tasks at labor supply works against the beneficial effects price ␳, which is falling at an exogenous rate. of computerization on the manual wage. It is ␳ There are many workers with educational possible for both wm and wr to fall when supplies assumed exogenous. Each college declines, but the wage of manual relative to worker is endowed with one efficiency unit of routine tasks (wm/wr) unambiguously rises. abstract skill, which she supplies inelastically to We distinguish between the wage of routine abstract tasks. Each high school worker, i,is tasks measured in efficiency units and the endowed with one efficiency unit of manual observed wages of workers in routine tasks, ␩ skill and i efficiency units of routine skill, which are affected by composition. As work- where ␩ is distributed continuously on the unit ers self-select out of routine tasks, the remain- interval with positive mass at all points ␩ ʦ [0, ing routine workers have above-average 1]. High school workers do not possess abstract routine skills, meaning the observed routine skills. wage can rise or fall (overall and relative to ␳ The supply of high school labor to routine wm)as declines. and manual tasks is determined by self-selection. As with manual workers, workers in abstract Let wm and wr equal the wages paid to manual tasks benefit from a rise in routine task input and routine tasks. Each high school worker, i, due to q-complementarity. For abstract tasks, VOL. 96 NO. 2 MEASURING AND INTERPRETING TRENDS IN ECONOMIC INEQUALITY 193 however, there is no countervailing labor supply IV. Conclusions response to buffer the positive impact of com- puterization on the abstract wage. Conse- The major new U.S. wage structure “facts” quently, computerization unambiguously raises evident in the last decade are the smooth, wa, absolutely and relative to wr and wm.A secular rise in upper-tail inequality over the more realistic production function would rein- last 25 years, coupled with an expansion and force this pattern through greater complementa- then compression of lower-tail inequality. rity of computerization with abstract tasks than These facts are not easily handled by standard manual tasks. institutional stories. The minimum wage ex- Does this framework generate a polarization planation fits only lower-tail inequality trends of work? The key observation of the model is well to 1987 (Autor et al., 2005b), and does that computers do not appear to substitute di- not explain why relative employment in low-wage rectly for the lowest-skilled workers; rather they jobs fell as the minimum wage dropped. A appear to displace a set of “middle-skilled” rou- “social-norms” explanation of the skewing of tine tasks. Displacing this “middle” generates the upper reaches of the wage distribution (as polarization through three mechanisms. First, it suggested by Piketty and Saez, 2003) has some directly lowers the wage of middle-skill tasks. plausibility but needs work to refine clear, test- Second, it raises the wage of high-skilled (ab- able predictions. stract) tasks through q-complementarity. Fi- Our analysis offers unambiguous evidence nally, it has ambiguous effects on the wages of that demand shifts are likely to be a key com- low-skilled (manual) tasks due to offsetting im- ponent of any cogent explanation for the chang- pacts of q-complementarity and additional labor ing U.S. wage structure. We find that quantity supply of workers displaced from routine tasks. and price changes covary positively throughout Thus, computerization always raises “upper-tail” the earnings distribution both in the 1980s, inequality in our model—the wage gap between when the wage structure was spreading mono- abstract and routine tasks. But it can either ex- tonically, and in the 1990s, when it was polar- pand or compress “lower-tail” inequality—the izing. We believe that the changing distribution wage gap between routine and manual tasks— of job task demands, spurred directly by ad- depending on whether the q-complementarity or vancing information technology and indirectly labor supply effect dominates. by its impact on outsourcing, goes some dis- We can think of the model as moving be- tance toward interpreting the recent polarization tween two equilibria as the price of computers of the wage structure. declines. Initially computerization displaces workers from routine and into manual tasks, depressing wages in the middle and (poten- REFERENCES tially) the bottom of the distribution, even as the abstract wage increases. When ␳ falls suffi- Acemoglu, Daron. “Changes in Unemployment ciently, the model exhibits a second equilibrium and Wage Inequality: An Alternative Theory in which routine tasks are performed exclu- and Some Evidence.” American Economic sively by K. In this equilibrium, only the q- Review, 1999, 89(5), pp. 1259–78. complementarity effect operates; further declines Antra`s, Pol; Garicano, Luis and Rossi-Hansberg, in ␳ raise wages in both manual and abstract Esteban. “Offshoring in a Knowledge Econ- tasks. Thus, the model is consistent with an omy.” Quarterly Journal of Economics initially monotone wage impact of computeriza- (forthcoming). tion followed by a polarization of the wage Autor, David H.; Katz, Lawrence F. and Kearney, distribution as jobs “hollow out” to encompass Melissa S. “Rising Wage Inequality: The Role only abstract and manual tasks. A similar im- of Composition and Prices.” National Bureau pact of international outsourcing could arise of Economic Research, Inc., NBER Working from declining international coordination costs Papers: No. 11628, 2005a. associated with information technology advances Autor, David H.; Katz, Lawrence F. and Kearney, (Frank Levy and Richard J. Murnane, 2004; Pol Melissa S. “Trends in U.S. Wage Inequality: Antra`s et al., forthcoming). Reassessing the Revisionists.” National 194 AEA PAPERS AND PROCEEDINGS MAY 2006

Bureau of Economic Research, Inc., NBER Handbook of labor economics. Vol. 3A. Am- Working Papers: No. 11627, 2005b. sterdam: Elsevier Science, North-Holland, Autor, David H.; Levy, Frank and Murnane, 1999, pp. 1463–1555. Richard J. “The Skill Content of Recent Lemieux, Thomas. “Increased Residual Wage Technological Change: An Empirical Explo- Inequality: Composition Effects, Noisy Data, ration.” Quarterly Journal of Economics, or Rising Demand for Skill?” American Eco- 2003, 118(4), pp. 1279–333. nomic Review (forthcoming). Card, David and DiNardo, John E. “Skill-Biased Levy, Frank and Murnane, Richard J. The new Technological Change and Rising Wage In- division of labor: How computers are creat- equality: Some Problems and Puzzles.” Jour- ing the next job market. New York: Princeton nal of Labor Economics, 2002, 20(4), pp. University Press and Russell Sage Founda- 733–83. tion, 2004. Goos, Maarten and Manning, Alan. “Lousy and Meyers, Peter B. and Osborne, Anastasiya M. “Pro- Lovely Jobs: The Rising Polarization of posed Category System for 1960–2000 Census Work in Britain.” London School of Eco- Occupations.” U.S. Bureau of Labor Statistics, nomics, Center for Economic Performance Working Paper Series: No. 383, 2005. Discussion Papers: No. DP0604, 2003. Piketty, Thomas and Saez, Emmanuel. “Income Katz, Lawrence F. and Autor, David H. “Changes Inequality in the United States, 1913–1998.” in the Wage Structure and Earnings Inequal- Quarterly Journal of Economics, 2003, ity,” in Orley Ashenfelter and David Card, 118(1), pp. 1–39. This article has been cited by:

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