MIT Spring 2018: Lecture 1 An Overview of Topics and Questions

MIT 14.662 Spring 2018: Lecture 1 An Overview of Topics and Questions David Autor, MIT and NBER February 7, 2018

Agenda 1 Incomes: Levels, Growth, Inequality Household incomes Wage Inequality Intergenerational income mobility 2 Skills, Education, and Earnings Skills and educational attainment Wage differentials by skill Occupational change & employment polarization 3 Top Incomes and Superstars 4 Trade and Labor Markets 5 The Importance of Place 6 Minimum wages, Pay comparisons, Wage spillovers 7 Gender Differences in Education and Labor Markets

population rose by about 2 billion. Many factors have contributed to that decline, but the most important is the rise of China it alone Falling World Poverty, 1981-2008 accounted for around half a billion people moving out of extreme poverty. Data: Poverty rates in developing countries have fallen sharply since the early 1980s, although much of the decline reflects China s economic resurgence. % of population 60 Poverty rates for the developing world, 1981 2008 % below poverty line $1.25 per day 40 $1.25 per day (less China) 20 0 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 Source: OECD (2013), Perspectives on Global Development 2013, http://dx.doi.org/10.1787/888932812908.

mid-2000s, there were again striking variations between countries. Income Ginis To be sure, in OECD: it rose in most, Midnotably 1980s thethrough United States, Approximately New Zealand and perhaps surprisingly Finland and Sweden. But in some 2013 others, such as France, it barely budged. Data: Income inequality has increased in most OECD countries since the mid 1980s. Gini measure of income inequality, mid 1980s and 2013 1985 2013 or latest year available Gini points 50 45 Increase Little change Decrease 40 35 30 25 20 15 DNK CZE NOR FIN SWE HUN DEU LUX CAN AUS ITA NZL JPN GBR ISR USA MEX OECD22 Source: OECD (2015), In It Together: Why Less Inequality Benefits All, http://dx.doi.org/10.1787/888933207711. BEL NLD FRA GRC TUR

U.S. Real HH Incomes at Select Percentiles, 1967-2012 200 180 Income in thousands (2012 dollars) Recession $191,200 160 95th 140 120 $114,200 90th $146,000 100 80 $90,400 50th (median) 60 $42,900 $51,000 40 20 $9,800 10th $12,200 0 1967 1975 1980 1985 1990 1995 2000 2005 2012 U.S. Census Bureau 2013

Growth in U.S. Real Mean Family Income by Quintile, 1947 1973 and 1973 2013 Growth in Real Mean Family Income by Income Quintile, 1947-1973 and 1973-2013 Percent per year 0 1 2 3 Bottom Second Middle Fourth Top Top 5 Percent 1947-1973 1973-2013 Source: U.S. Census Bureau, Historical Income Table F3 and Goldin and Katz (2007, Figure 1) for 1947-73 U.S. Census Bureau 2013

Average Annual Income % Change in Family Size-Adjusted Mean Income by Quintile 4 Lowest Second Third Fourth Highest 3 2 1 0-1 -2-3 -4 1969-1979 1979-1989 1989-1999 1999-2007 2007-2012 U.S. Census Bureau 2013

Declining U.S. Middle Class 1971 2015 Share of adults living in middle-income households is falling % of adults in each income tier 2015 2011 2001 1991 1981 Lowest 20 20 18 18 17 Lower middle 9 9 9 9 9 Middle 50 51 54 56 59 Upper middle 12 12 Highest 11 12 9 8 7 5 12 3 Middle-income households: Incomes that are two-thirds to double that of U.S. median household income (after adjusting for household size) 1971 16 9 61 10 4 Pew Research Center 2015

Fraction Upper Class Fraction Lower Class 1971 2015 Ages 65 and older Married, no children at home Black Married, with children at home White Asian* Women All Men Ages 45-64 U.S. born** Bachelor's degree or more Foreign born** Ages 30-44 Unmarried Ages 18-29 Hispanic Some college/two-year degree Less than high school graduate High school graduate -0.1-1.3-5.4-7.9-16.1-18.1-21.9 14.9 11.2 10.1 6.8 4.1 3.5 3.2 2.7 2.1 2.1 1.3 0.0 26.7

Changes in the 90/10 Ratio of Full-Time Male Earnings Across Twelve OECD Countries, 1980-2011 Change in Ratio of 90th Percentile Male Earnings to 10th Percentile Male Earnings, 1980 2011 1.5 1.2 0.9 0.6 0.3 0.0 0.3 0.6 Numbers at the base of each bar correspond to the 90/10 earnings ratio in each country in 1980. 3.3 2.4 2.6 2.0 4.1 2.4 2.1 2.2 2.7 2.1 2.7 3.6 France Finland Japan Sweden Korea Germany Denmark Netherlands Australia New Zealand United Kingdom United States Autor 2014

U.S. Earnings Inequality in the Post-War Era, 1945-2005 Goldin and Katz 2008

U.S. Indexed Real Incomes at the 20th, 50th and 95th Percentiles, 1945 2005 Goldin and Katz 2008

U.S. Real Weekly Wages (PCE Deflator) 1962 2012: Men Men's Average Weekly Wages, Selected Percentiles of the Wage Distribution: 1962-2012 ($2012) Average Weekly Wage 0 500 1000 1500 2000 2500 3000 95th 90th 75th 50th 25th 10th 1960 1970 1980 1990 2000 2010 Murphy and Topel 2016

U.S. Real Weekly Wages (PCE Deflator) 1962 2012: Women Average Weekly Wage 0 500 1000 1500 2000 Women's Average Weekly Wages, Selected Percentiles of the Wage Distribution: 1962-2012, ($2012) 1960 1970 1980 1990 2000 2010 95th 90th 75th 50th 25th 10th Murphy and Topel 2016

Growth in Log Real Weekly Wages 1970/72 2010/12 Growth in Men's and Women's Log Weekly Wages by Percentiles of the Wage Distribution, 1970-72 through 2010-12 Change in Log Wage 0.2.4.6.8 1 Women Men 0 20 40 60 80 100 Percentile of Wage Distribution Murphy and Topel 2016

Average Hours Worked by Wage Percentile, 1970/2 and 2010/12: Men Murphy and Topel 2016

Average Hours Worked by Wage Percentile, 1970/2 and 2010/12: Women Figure 7B Murphy and Topel 2016

Evolution of Inequality in the UK, 1977-2006 Atkinson 2008

Rise in West German Male Wage Inequality, 1985-2009 15 Figure 1a: Trends in Percentiles of Real Log Daily Wage West German Men Relative to 1996 Base 10 Value of Wage Percentile Value in 1996 5 0 5 10 15 20 25 10th Percentile 20th Percentile 50th Percentile 80th Percentile 30 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 Year Note: figure shows percentiles of log real daily wage for full time male workers on their main job, deviated from value of same percentile in 1996 and multiplied by 100. Figure 1b: Trends in Percentiles of Real Log Card, Hourly Wages Heining, Kline 2013 U.S. Men Relative to 1979 base

Countries with High Cross-Sectional Inequality Have Low Relative Earnings Mobility Corak 2013

OECD Thinks so Too... Data: Charts like this similar to the Great Gatsby curve suggest that countries with higher levels of inequality have lower rates of social mobility. Inequality and mobility (intergenerational earnings elasticity) across OECD countries Intergenerational earnings elasticity 90 DNK 85 FIN 80 NOR KOR JPN CAN 75 SWE AUS NZL 70 DEU 65 60 CHE ESP 55 50 FRA GBR ITA USA 45 20 255 30 30 40 Source: OECD (2015), In It Together: Why Less Inequality Benefits All, http://dx.doi.org/10.1787/888933207806. Inequality (Gini points) How s life? Corak 2013

Comparing U.S. Parents and Children s Income Distributions by Birth Cohort B. Family Income Distributions: 1940 Birth Cohort C. Family Income Distributions: 1980 Birth Cohort 80th percentile of parents distribution 80th percentile of parents distribution Density Density 14th percentile of children's distribution 74th percentile of children's distribution Parents Children Parents Children 0 27k 50k 100k 150k Income (Measured in Real 2014$) 0 50k 80k 100k 150k Income (Measured in Real 2014$) Notes: These figures show how the copula affects estimates of absolute mobility cohort over all copulas satisfying first-order Chettystochastic al. dominance 2017of children s separately by cohort. The solid circles in Panel A replicate the baseline estimates line corresponding to the cohorts (1971-1984) for which Chetty et al. (2014b) distributions of children in the 1940 birth cohort and their parents, measured at app with zero income are excluded, but children with zero income are included when $200,000 are excluded. Panel C plots analogous income distributions for childre percentile that a child must reach in order to earn more than his or her parents for shown by the dashed vertical lines in Panels B and C. Panel D also shows a heat m

Absolute Mobility: Children Earning More than Their Parents Chetty et al. 2017

Absolute Mobility: Children Earning More than Their Parents A. Selected Cohorts by Parent Income Percentile Pct. of Children Earning more than their Parents 100 80 60 40 20 0 1940 1950 1960 1970 1980 0 20 40 60 80 100 Parent Income Percentile (conditional on positive income) Chetty et al. 2017

Counterfactuals for Absolute Mobility: Contributions of Slowing GDP growth vs. Rising Inequality Chetty et al. 2017

segregation, reinforcing reduced economic mobility, given evidence of neighborhood ef- The Trend fects on child in Absolute long-run economic Mobility outcomes isthe Extremely bottom half of workers Highly include Correlated increasing (17, 18). Declining U.S. geographic mobility the minimum wage, strengthening workers with Trend Intergenerational Income Growth contributes to reduced income mobility, as moves from declining to expanding regions have been a source of economic vibrancy (19). In our view, faster growth is necessary but not sufficient to restore higher intergengrams, such as sectoral programs (20). Policies with potential to raise wages for Mobility and child-parent income gap, linked over time (Top) From online table 1, column CY, of Chetty et al. (see www.equality-of-opportunity.org/data/); (bottom) from table S1 in Chetty et al. (1). Based on authors calculations (see SM). Absolute mobility Children-parents real median income ($) 1 0.9 0.8 0.7 0.6 0.5 0.4 40,000 30,000 20,000 10,000 0-10,000 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 bargaining power, enforcing antidiscrimination laws, and preventing anticompetitive employer practices. Katz Earnings and Krueger for low-income 2017 households would increase if labor force participation were to increase. Subsidized day their e researc interve standa REFERE 1. R. C 2. The with me ma pro fere 3. Res SM in m pre dec 4. The me the mo but 5. D. C 6. J. J. 7. C. G Tec Cam 8. Est Uni upd Pop 9. C. G (20 10. D. H 11. G. J (20 12. S. Z 13. D. H 14. D. H 15. D. W

Wage Returns to Measured Skills Are Substantial but Variable Across Countries Cross-national differences in wage returns to skills, 2011 2013 Percentage increase for a one standard deviation increase in skill Sweden Czech R. Norway Italy Denmark Cyprus Finland Belgium France Estonia Slovak R. Austria Earnings gain 95% confidence interval Netherlands Japan Poland Canada Korea U.K. Spain Germany Ireland U.S. 0 5 10 15 20 25 30 percent Hanushek et al. 2013

Measured Skills Highly Correlated with Education: Gaps in Literacy Proficiency by Education Group in OECD Countries Differences in literacy proficiency, by educational attainment Lower than upper secondary Upper secondary Tertiary Unadjusted Adjusted A. Mean literacy proficiency scores Mean score Cyprus 1 Estonia Japan Norway Czech Republic Denmark Italy Korea Slovak Republic Poland Finland Germany Australia Austria Average Spain Ireland England/N. Ireland (UK) Canada Netherlands Sweden Flanders (Belgium) France United States B. Mean literacy score differences between low- and high-educated adults Tertiary minus lower than upper secondary 200 225 250 275 300 325 0 20 40 60 80 Score Score-point difference OECD Skills Outlook 2013

Emp Rates Uniformly High among Top Tercile PIAAC Scorers in 2012 Proportion Employed 0 20 40 60 80 100 Korea Slovak Republic Poland Czech Republic Italy France Ireland Japan Spain Flanders (B) Finland PIAAC average Austria Estonia England/N. Ireland (UK) Australia Sweden Denmark Germany Canada Netherlands U.S. Norway Broecke, Quintini and Vandeweyer (2015)

Emp Rates Uniformly Low among Bottom Tercile PIAAC Scorers in 2012 Proportion Employed 0 20 40 60 80 100 Slovak Republic Spain Italy Ireland Poland Finland Czech Republic Flanders (B) Denmark France Sweden PIAAC average England/N. Ireland (UK) Netherlands Estonia Australia Germany U.S. Austria Norway Japan Canada Korea Broecke, Quintini and Vandeweyer (2015)

Major Employment Transitions: Agriculture to Industry to Services Johnston 2012

U.S. Educational Progression: Years of Completed Schooling by Birth Cohort, 1876-1975 Goldin and Katz, 2008

Years of Completed Schooling by Birth Cohort and Sex, 1876-1975 Goldin and Katz, 2008

U.S. High School Completion Rates by Birth Cohort 1930 1975 Acemoglu and Autor 2012

U.S. College Completion Rates by Birth Cohort 1930 1975 0.35 0.30 Fraction with college degree 0.25 0.20 0.15 0.10 All Males Females 0.05 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 Year of birth Figure 8. College Completion Rates by Birth Cohort: 1930 1975 Acemoglu and Autor 2012

Distribution of Educational Attainment of the U.S. Workforce, 1915 2005: So Low in 1915! Goldin and Katz 2008

College Share of U.S. Hours Worked, 1963-2012 College share of hours worked (%) 15 20 25 30 35 40 45 50 1964 1967 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012 Autor 2014

College Share of Hours Worked in the U.S. 1963-2012: Males and Females with <10 Years of Potential Experience College share of hours worked (%) 15 20 25 30 35 40 45 50 55 60 65 1964 1967 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012 Males: 0-9 Yrs Experience Females: 0-9 Yrs Experience Autor 2014

Tertiary Education Completion in OECD Countries as of 2012 by Age Groups, 25 34 and 55 65 Population with tertiary education Percentage, by age group % 70 60 50 40 30 20 10 0 25-34 year-olds 55-65 year-olds Korea Canada Japan Denmark England/N. Ireland (UK) Cyprus¹ Poland Ireland 1. See notes at the end of this chapter. Countries are ranked in descending order of the percentage of 25-34 year-olds with tertiary education. Source: Survey of Adult Skills (PIAAC) (2012), Table B2.2 in Annex B. Finland Flanders (Belgium) Estonia Norway Australia Average United States Netherlands France Sweden Spain Germany Czech Republic Slovak Republic Italy Austria OECD Skills Outlook 2013

Earnings Differentials between College and High School Young Adults 30-44 in OECD Countries, 2005 Country Differential Country Differential Denmark 22% Sweden 22% Spain 30% Australia 34% Belgium 34% Finland 38% Italy 43% Netherlands 47% Austria 48% France 48% Korea 48% Germany 50% Ireland 59% UK 61% OECD (2007): Education at a Glance

Indexed Real Full-Time Wages in U.S. by Sex and Education, 1963-2012: Rising Return Reflects (in part) Falling HS Level College versus High-School Wage Gap (Percent) 35 45 55 65 75 85 95 105 1964 1967 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012

The U.S. College/High-School Premium, 1963-2012 Changes in real wage levels of full-time U.S. workers by sex and education, 1963 2012 Real weekly earnings relative to 1963 (men) A Real weekly earnings relative to 1963 (women) B 2.0 2.0 Some college 1.8 1.6 > Bachelor's degree Bachelor's degree 1.8 1.6 High school dropout High school graduate 1.4 1.4 1.2 1.2 1.0 1.0 1964 1968 1972 1976 1980 1984 1988 1992 1996 200020042008 2012 1964 1968 1972 1976 1980 1984 1988 1992 1996 200020042008 2012 Autor, 2014

Average Change per Decade in US Occupational Employment Shares for Two Periods: 1940 1980 and 1980 2010 Katz & Margo, 2014 (in Autor 2015)

Occupational Polarization, 1979 2012Percent Growth in Employment by Occupational Category

Occupational Polarization in the U.S., 1982 2012: An Aggregate View Notes: Data from the Bureau of Labor Statistics, Current Population Survey. See Appendix A for details. Jaimovich and Siu 2014

Employment Polarization in the European Union, 1993-2010 18% 15% Low Paying Middle Paying High Paying 12% 9% 6% 3% 0% -3% -6% -9% -12% -15% -18% -14.9% -8.6% -8.5% -7.6% -6.7% -10.9% -10.8% -10.7% -10.6% -10.6% -10.4% -10.3% -9.6% -12.1% -12.0% -4.9% Goos, Manning and Salomons, 2014

Occupational Polarization, 1979 1989, 1990-2007 0.2 100 change in employment share 0.15 0.1 0.05 0 1979 1989 1990 2007 0.05 0 20 40 60 80 100 Skill percentile (ranked by occupational mean wage) Figure 5. Smoothed Changes in Employment by Occupational Skill Percentile, 1979 2007 Acemoglu and Autor 2011

Occupational Polarization, 1979 2007, Detailed View! Acemoglu and Autor 2011

Evolution of Employment in Occupational Groups by Skills Proficiency, 1998 2009 (24 OECD Countries) Evolution of employment in occupational groups defined by level of skills proficiency Percentage change in the share of employment relative to 1998, by occupational groups defined by workers average level of proficiency in literacy and numeracy % 25 20 Occupations with highest average scores 15 10 5 0-5 Occupations with lowest average scores Occupations with next to highest average scores -10-15 -20 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Occupations with next to lowest average scores OECD Skills Outlook 2013

Growth of High-Math/High-Social Occupations 1980-2012 Deming 2016

Occupational Skill and Wage Profiles of U.S. College Workers by Year of Labor Market Entry, 1990-2010 Declining Fortunes of Young College Workers Since 2000? Panel A. Cognitive employment profiles 0.7 Panel B. Wage profiles 2.8 Employment share 0.65 0.6 0.55 2.7 2.6 2.5 2.4 0.5 1990 1995 2000 2005 2010 Year 2.3 1990 1995 2000 2005 2010 Year Figure 1. Cognitive Employment and Wage Profiles for Exactly College Workers Beaudry, Green and Sand 2014

Occupational Skill and Wage Profiles of U.S. Post-College Workers by Year of Labor Market Entry, 1990-2010 Declining Fortunes of Young Post-College Workers Since 2000? Panel A. Cognitive employment profiles 0.9 Panel B. Wage profiles 3 Employment share 0.85 0.8 0.75 2.9 2.8 2.7 0.7 1990 1995 2000 2005 2010 Year 2.6 1990 1995 2000 2005 2010 Year Figure 3. Cognitive Employment and Wage Profiles for Post-College Workers Beaudry, Green and Sand 2014

has been particularly striking in the United States: In 1980, the top 1% of income recipients in the U.S. earned 8% of all pre-tax income; by 2012, their share had risen to over 19%. Other OECD countries also saw big rises, including the United Kingdom and Australia. OECD Top 1% Income Shares, 1981-2012 Data: Top earners have increased their share of total earnings in most OECD countries since the 1980s. Share of top 1% incomes in total pre tax income, 1981 2012 (or latest year available) % 2012 1981 20 15 10 5 0 United States United Kingdom Germany Canada Switzerland Ireland Portugal Japan Italy Australia Spain France Norway Finland New Zealand Sweden Denmark Netherlands Source: OECD (2014), Focus on Top Incomes and Taxation in OECD Countries: Was the crisis a game changer?, http://dx.doi.org/10.1787/888932965953.

3. WHY IS INCOME INEQUALITY RISING? OECD Income Taxes Becoming Less Progressive Data: Tax rates on top incomes fell substantially between the 1980s and the financial crisis. Maximum, minimum and average statutory tax rates on top incomes in OECD countries, 1981 2013 (or latest) % 100 90 80 70 60 50 40 30 20 10 0 1981 OECD maximum: 93% OECD average: 66% 51 1990 Source: OECD (2014), Focus on Top Incomes and Taxation in OECD Countries: Was the crisis a game changer?, http://dx.doi.org/10.1787/888932965953. 47 2000 43 2005 41 2008 43 OECD minimum: 15% 2013

Top Decile Income U.S. Income Share, 1917 2015 50% 45% Top 10% Income Share 40% 35% 30% Including capital gains Excluding capital gains 25% 1917 1922 1927 1932 1937 1942 1947 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007 2012 Piketty and Saez, 2003 (updated to 2015)

Top Decile Wage Share, 1917 2015 37.5% 35.0% 32.5% Share (in %) 30.0% 27.5% 25.0% 22.5% 20.0% 1927 1932 1937 1942 1947 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007 Piketty and Saez, 2003 (updated to 2015)

Top Decile U.S. Income Shares, 1917 2015: P1, P1-P5, P5-P10 Share of total income accruing to each group 25% 20% 15% 10% 5% Top 1% (incomes above $443,000 in 2015) Top 5-1% (incomes between $180,500 and $443,000) Top 10-5% (incomes between $124,800 and $180,500) 0% 1913 1918 1923 1928 1933 1938 1943 1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003 2008 2013 Piketty and Saez, 2003 (updated to 2015)

Top Decile U.S. Wage Income Shares, 1917 2015: P1, P1-P5, P5-P10 14% 13% P90-95 P95-99 P99-100 12% 11% Share (in %) 10% 9% 8% 7% 6% 5% 4% 1927 1932 1937 1942 1947 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007 Piketty and Saez, 2003 (updated to 2015)

Average Real Wage Incomes: Top 1% and Bottom 99% Average Bottom 99% Income (2015 dollars) $55,000 $50,000 $45,000 $40,000 $35,000 $30,000 $25,000 $20,000 $15,000 $10,000 $5,000 Bottom 99% average income Top 1% average income $1,100,000 $1,000,000 $900,000 $800,000 $700,000 $600,000 $500,000 $400,000 $300,000 $200,000 $100,000 Average Top 1% Income (2015 dollars) $0 $0 1913 1918 1923 1928 1933 1938 1943 1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003 2008 2013 Piketty and Saez, 2003 (updated to 2015)

Piketty and Saez, 2003 (updated to 2015) Top 0.1% Income Share, 1917 2015 Top 0.1% US Pre-Tax Income Share, 1913-2015 12% Top 0.1% Income Share 10% 8% 6% 4% 2% Top 0.1% income share (incomes above $2.0m in 2015) 0% 1913 1918 1923 1928 1933 1938 1943 1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003 2008 2013 Source: Piketty and Saez, 2003 updated to 2015. Series based on pre-tax cash market income including or excluding realized capital gains, and always excluding government transfers.

Top 0.1% Income Share, 1917 2015: Income Sources US Top 0.1% Pre-Tax Income Share and Composition 12% 10% 8% Capital Gains Capital Income Business Income Salaries 6% 4% 2% 0% 1916 1921 1926 1931 1936 1941 1946 1951 1956 Source: Piketty and Saez, 2003 updated to 2015. Series based on pre-tax cash market income including or excluding realized capital gains, and always excluding government transfers. 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011 Piketty and Saez, 2003 (updated to 2015)

Top 1% Income Share: Anglophone Countries 30 25 United States Canada Ireland United Kingdom Australia New Zealand 20 15 10 5 0 1910 1915 1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Top percentile share (in percent) Figure 8. Top 1 Percent Share: English Speaking Countries (U-shaped), 1910 2005 Atkinson, Piketty, Saez 2011

Top 1% Income Share: Middle Europe and Japan 30 25 France Netherlands Japan Germany Switzerland 20 15 10 5 0 1900 1905 1910 1915 1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 Top percentile share (in percent) 2000 2005 Figure 9. Top 1 Percent Share: Middle Europe and Japan (L-shaped), 1900 2005 Source: Atkinson and Picketty (2007, 2010). Atkinson, Piketty, Saez 2011

Top 1% Income Share: Nordic Countries and Southern Europe 30 25 Sweden Finland Norway Spain Portugal Italy Top percentile share (in percent) 20 15 10 5 0 1900 1905 1910 1915 1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Figure 10. Top 1 Percent Share: Nordic and Southern Europe (U/L-shaped), 1900 2006 Source: Atkinson and Picketty (2007, 2010). Atkinson, Piketty, Saez 2011

Top 1% Income Share: Developing Countries 30 25 China Argentina Singapore Indonesia India Top percentile share (in percent) 20 15 10 5 0 1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Figure 11. Top 1 Percent Share: Developing Countries, 1920 2005 Atkinson, Piketty, Saez 2011

Adding Capital Gains: US, Canada, Spain, Sweden and Finland 25 Share in total income of top percentile (in percent) 20 15 10 5 U.S. Canada Spain Sweden Finland 0 1949 1953 1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 U.S. with CGs Canada with CGs Spain with CGs Sweden with CGs Finland with CGs U.S. Sweden Figure 7. Effect of Capital Gains on Share of Top Percentile, 1949 2006 Atkinson, Piketty, Saez 2011

Occupations and National Income Shares of Top 1 Percent of Households, 1979 2005 Share of National Income Including Capital Gains Accruing to Top 1% of HH's 1979-2005 21.00 18.00 15.00 12.00 9.00 6.00 3.00 2.82 0.32 0.61 1.22 0.91 3.84 3.09 0.37 1.00 2.16 1.80 5.58 5.89 4.93 0.75 0.96 1.24 1.01 1.78 1.59 3.05 3.44 7.80 7.85 All other Computer, Math, Engineer, Technical Lawyers Medical Finance Executives/Managers Non-Finance 0.00 1979 1993 1999 2005 Bakija, Cole and Heim 2012

Occupations of the Top 1 Percent of U.S. Households, 1979 2005 100.0 Occupations of Those in Top 1% Including Capital Gains, 1979-2005 90.0 80.0 30.7 24.5 32.8 33.0 All Other 70.0 60.0 50.0 40.0 30.0 3.2 3.7 8.5 6.7 19.7 15.9 7.7 10.8 7.2 7.4 6.7 7.7 13.9 14.2 6.7 7.7 Computer, Math, Engineer, Technical Lawyers Medical Finance 20.0 10.0 35.3 33.3 32.7 30.0 Executives/Managers Non-Finance 0.0 1979 1993 1999 2005 Bakija, Cole and Heim 2012

Median Earnings Gap Between College & High School Grads Roughly Doubles between 1979 and 2012 College/high school median annual earnings gap, 1979 2012 In constant 2012 dollars 70,000 dollars Household gap $30,298 to $58,249 60,000 50,000 40,000 Male gap $17,411 to $34,969 30,000 20,000 10,000 Female gap $12,887 to $23,280 0 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012 Autor, 2014

Small Economies Trade More as Share of GDP International imports and exports in goods and services As percentage of GDP, 2010 or latest available year Imports Exports 100 176.7 141.5 90 80 70 60 50 40 30 20 10 0 USA AUS GRC TUR OECD FRA ESP ITA ZAF RUS CHN MEX NZL CAN GBR ISR FIN CHL EU27 PRT EA17 POL NOR DEU SWE DNK KOR CHE AUT ISL SVN EST NLD CZE SVK BEL HUN IRL LUX

Merchandise Trade to GDP 1960 2009: Rising 65% 60% 55% 50% 45% 40% 35% 30% Denmark, Norway, Sweden Germany, France, Italy US, UK, Canada China, India 25% 20% Australia 15% 10% Japan 05% 0% 1960 1970 1980 1990 2000 2010 Source: World Bank, 2011

44 Journal of Economic Perspectives Rise of Middle-Income Countries in World Trade Table 1 Exports and Imports Relative to GDP by Regional Trading Partner Exports to partner relative to regional GDP Imports from partner relative to regional GDP Region Trade partner 1994 2008 Percentage point change 1994 2008 Percentage point change Low-income Low-income countries 0.8% 3.2% 2.4 0.8% 3.2% 2.4 countries Middle-income countries 4.5% 11.6% 7.1 6.0% 17.1% 11.1 China, India 1.1% 8.3% 7.2 1.8% 10.7% 8.9 High-income countries 20.0% 31.8% 11.8 15.1% 23.0% 7.9 World 26.3% 55.0% 28.6 23.7% 54.0% 30.4 Mid-income Low-income countries 0.7% 2.1% 1.4 0.5% 1.4% 0.9 countries Middle-income countries 5.3% 15.6% 10.3 5.3% 15.6% 10.3 China, India 2.2% 7.5% 5.3 2.4% 7.4% 5.0 High-income countries 16.9% 29.6% 12.7 18.6% 26.0% 7.4 World 25.1% 54.8% 29.8 26.8% 50.4% 23.6 China and Low-income countries 0.8% 2.7% 1.9 0.5% 2.1% 1.6 India Middle-income countries 9.5% 15.2% 5.7 8.6% 15.4% 6.8 China, India 0.1% 1.2% 1.1 0.1% 1.2% 1.1 High-income countries 14.3% 25.3% 11.0 9.8% 14.1% 4.3 World 24.8% 44.4% 19.6 19.0% 32.7% 13.7 High-income Low-income countries 0.3% 0.7% 0.4 0.5% 1.0% 0.5 countries Middle-income countries 3.7% 6.6% 2.9 3.4% 7.5% 4.1 China, India 0.5% 1.7% 1.2 0.7% 3.1% 2.4 High-income countries 12.8% 16.9% 4.1 12.8% 16.9% 4.1 World 17.4% 26.0% 8.6 17.4% 28.6% 11.2 Source: UN Comtrade, http://comtrade.un.org/. Hanson 2012

China s Historic Rise as a World Manufacturing Power Shares of world manufacturing exports 20 15 10 percent 5 1985 1990 1995 2000 2005 2010 Year 0 China USA Other emerging economies Germany Autor, Dorn, Hanson 2016

The Share of U.S. Employment in Manufacturing, 1939 2014

U.S. Manufacturing Employment Fell by 20% During 1999-2007, and by 32% During 1999-2016 22,000 21,000 20,000 19,000 18,000 17,000 16,000 15,000 14,000 13,000 12,000 11,000 10,000 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0,00 1939 1942 1945 U.S. Manufacturing Employment, 1939-2016 (1,000s) 1943, 16.6 mil 1948 1951 1954 1958 1961 1964 1967 1970 1973 1977 1980 1983 1979, 19.7 mil 1999, 17.3 mil 1986 1989 2007, 13.8 mil 1992 1996 1999 2010, 11.9 mil 2002 2005 2008 2016, 12.4 mil 2011 2015

Unequal Gains: Parts of America Most Affected by China s Rising Manufacturing Prowess, 1990 2007 Autor, Dorn, Hanson & Wall Street Journal, 2016

national price changes, P i. Kovak (2013) studies a similar model in which Approach are fixed. Here we allow the amounts of labor and specific factors to vary Regional Tariff Changes in Brazil 1990-1995 ust described, definethis the regional tari or RT r, as our empirical alization. Wewesolve variation of change, the model incappendix B, yielding the e ect on local labor demand. This measure corresponds to the weightedfigure 3: Regional Tari Changes mtion s relationship governing the evolution of wages in a region r. e change in (1), where we utilize only the variation in prices that is driven by X X w r = RT Cr =ri P i i i ri X drln(1l +r ), i ble goods industries. To calculate the 1 ri ri, i! ri T ri, (3) (1) Belém we measure 1 ri Manaus as industry i s initial Fortaleza mal employment as one'iminus where and, the initial P share, of industry value ri 'ip r wagebill 9 i is the tari rate in 1 j rj 'j industry i, and d 1 rk 'long k the represents k di erence from Recife dsification of Brazilian trade liberalization. is a slightly aggregated version of the one in Kovak (2013), accounting for additional ng the locallonger laborsample di errelated substantially the local industry distribution of their markets i is industry i0papers s tariﬀin period. define markets based on commuting patterns Salvador )). definitionfigure performs well based on thisvariation standardinasindustry well - only 3.4 and ghtsourri local vary market across regions. 2 demonstrates how 0 s lived and worked inisdi erent markets in 2000 and 2010, respectively. ishows s share of tradedbrasília n in RT Cr. The ri figure the initial industry distribution of employment ion is shown in Figure 3. The analysis omits 11 microregions, -17%shown to -12% with a cross-hatched sector employment in r largestarea the most negative value, Colatina, city and in Espı rito Santo se include i) Manaus, which was partthe of second a Free Trade hence not subject to tari -12% to -10% Belo Horizonte n, ii) the value, microregions that constitute themato stategrosso of Tocantins, which was created positive Paranatinga, in central state. The industries on in 1988 and 'i is our onesample minus labor s to -9% dentifiable throughout period, and iii) a few other-10% municipalities that are omitted from the most negativeoftova the most positive tari change. -9% Colatina has more in i regions. The inclusion share or exclusion of these when possible has to no-6% substantive e ect on the São Paulo de of the particularly in theaggregate apparel and industries. ented the diagram, main analyses using a more localfood laborprocessing market definition, mesoregions -6% to +1.4% Curitiba esults are nearly identical. s agricultural goods and wood products almost exclusively, both of which faced xamples. hanges. Thus, although all regions faced the same set of tari changes across Porto Alegre employment shares using the 1991 Census, as it provides a more detailed industry classifican RAIS. We initially use formal shares because of our focus on formal sector outcomes and ly leave formal employment, but returning 10 appears to be quite difficult (Dix-Carneiro 2014). 3, results are very similar when using overall employment shares, including both formal and Dix-Carneiro andfor Kovak 2014 Local laboroutside marketsthe reflect microregions by IBGE, aggregated slightly to account border changes between We also use overall shares when studying outcomes formal sector indefined Section 7.

The Geography of Upward Mobility in America Chetty and Hendren, 2014

Children s Predicted Income Rank at Age 26 by Parents Income Percentile C. For Children with Parent at the 25 th Percentile (County) D. For Children with Parent at the 75 th Percentile (County) Notes: These figures illustrate the geographic variation in child income rank outcomes Chetty at ageand 26 from Hendren the 1985 cohort 2018amongst our sample of permanent residents across commuting zones (CZs) and counties in the U.S. Panel A reports the expected rank for children whose parental income is at the 25th percentile of the income distribution of parents, and Panel B reports the expected rank for children whose parental income is at the 75th percentile. Both figures use the baseline family income definitions for parents and children. The figure restricts to the subset of parents who stay in the commuting zone throughout

Causal Effects of Place on Children of 25 th Pctile HH s B. At the County Level; within CZs Chetty and Hendren 2018 These figures show the coe cients of regressions of the model components for below-median income families (p =

Minimum Wage Increases Between 1979 and 2016 Figure A.2: Minimum Wage Increases between 1979 and 2016 WY WY WY WY WY WY WY WY WY WV WV WV WV WV WV WV WV WV WV WV WI WI WI WI WI WI WI WI WI WI WA WA WA WA WA WA WA WA WA WA WA WA WA WA WA WA WA WA WA WA WA WA VT VT VT VT VT VT VT VT VT VT VTVTVT VT VT VT VT VT VT VT VT VT VT VT VT VT VA VA VA VA VA VA VA VA VA UT UT UT UT UT UT UT UT UT TX TX TX TX TX TX TX TX TX TN TN TN TN TN TN TN TN TN SD SD SD SD SD SD SD SD SD SD SD SC SC SC SC SC SC SC SC SC RI RI RI RI RI RI RI RI RI RI RI RI RI RI RI RI RI RI PA PA PA PA PA PA PA PA PA PA OR OR OROR OR OR OR OR OR OR OR OR OR OR OR OR OR OR OR OR OK OK OK OK OK OK OK OK OK OH OH OH OH OH OH OH OH OH OH OH OH OH OH NY NY NY NY NY NY NY NY NY NY NY NY NY NY NV NV NV NV NV NV NV NV NV NV NV NM NM NM NM NM NM NM NM NM NJ NJ NJ NJ NJ NJ NJ NJ NJ NJ NJ NH NH NH NH NH NHNH NHNH NH NH NH NH NE NE NE NE NE NE NE NE NE NE NE ND ND ND ND ND ND ND ND ND ND NC NC NC NC NC NC NC NC NC MT MT MT MT MT MT MT MTMTMTMT MT MT MT MT MT MS MS MS MS MS MS MS MS MS MO MO MO MO MO MO MO MO MO MO MO MO MO MN MN MN MN MN MN MN MN MN MN MN MN MN MN MI MI MI MI MI MI MI MI MI MI MI ME ME ME ME ME ME ME ME ME ME ME ME ME ME ME ME ME ME MD MD MD MD MD MD MD MD MD MD MD MD MA MA MA MA MA MA MA MA MA MA MA MA MA MA MA LA LA LA LA LA LA LA LA LA KY KY KY KY KY KY KY KY KY KS KS KS KS KS KS KS KS KS IN IN IN IN IN IN IN IN IN IL IL IL IL IL IL IL IL IL IL IL IL ID ID ID ID ID ID ID ID ID IA IA IA IA IA IA IA IA IA HI HI HI HI HI HI HI HI HI HI HI HI GA GA GA GA GA GA GA GA GA FL FL FL FL FL FL FL FL FL FL FL FL FL FL FL DE DE DE DE DEDEDEDE DE DE DE DE DE DE DE DC DC DC DC DC DC DC DC DC DC DC DC DC CT CT CT CT CT CT CT CT CT CT CT CT CT CT CT CT CT CT CT CT CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CA CA CA CA CA CA CA CA CA CA CA CA CA AZ AZ AZ AZ AZ AZ AZ AZ AZ AZ AZ AZ AZ AZ AR AR AR AR AR AR AR AR AR AR AR AL AL AL AL AL AL AL AL AL AK AK AK AK AK AK AK AKAK AK AK 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012 2015 2016 Notes: ThefigureshowsallMWincreasesbetween1979and2016.Thereareattotalof516minimumwageincreases.The blue circles show the primary minimum wage events used in estimating equation 4; thepartiallytransparentorangetriangles highlight small minimum wage changes where minimum wage increased less than $0.25 (the size of our wage bins) or where less than 2 percent of the workforce earned between the new and the old minimum wage. The green circles indicate federal changes, which we exclude from our primary sample of treatments because the change in missing number of jobs, Db, isonlyidentified from time-series variation for these events as there are no control states with wage floors lower than the new minimum wage (see the text for details).

Minimum Wage Has Gone from Highly Binding to Irrelevant to Binding 64 AMERICAN ECONOMIC JOURNAL: APPLIED ECONOMICS JANUARY 2016 0.14 Share at or below the minimum 0.12 0.1 0.08 0.06 0.04 0.02 Female Male/female pooled Male 0 1979 1985 1990 1995 2000 2005 2010 Figure 2. Share of Hours at or Below the Minimum Wage Notes: The figure plots estimates of the share of hours worked for reported wages equal to or less than the applicable state or federal minimum wage, corresponding with data from columns 4 and 8 of Tables 1A and 1B. out the possibility of true spillovers. But they underscore that spillovers estimated with conventional household survey data sources must Autor, be treated Manning with caution & Smith since 2017 they cannot necessarily be distinguished from measurement artifacts with available

Percentage of 25-34 Year-Olds Who Have Attained Tertiary Education, by Gender (2014) OECD Education and at a Glance 2014

Years of Completed Schooling by Birth Cohort and Sex, 1876-1975 Goldin and Katz, 2008

U.S. Women are Better Students than U.S. Men High School Grade Point Average 2.6 2.7 2.8 2.9 3 3.1 Grade Point Averages of Graduating High School Seniors 1990-2009 2.77 2.59 Females 2.90 2.68 3.00 2.79 3.05 2.83 Males 1990 1994 1998 2000 2005 2009 year 3.09 2.86 3.10 2.90 Murphy and Topel 2016

Educational Attainment by High School Graduates: Cohorts Completing High School 1916 2003 Educational Attainment of High School Cohorts, 1916-2003 Men and Women Aged 18 in the Indicated Year Share of Cohort with Indicated Education 0.1.2.3.4.5.6.7 Men, Some College Women, Some College Men, 4 Years College Women, 4 Years College 1920 1940 1960 1980 2000 High School Cohort Murphy and Topel 2016

U.S. Wen s College Attainment: Not Much Happening College Attainment (16 Years) by High School Cohort and Age Men, High School Cohorts 1960-2000 Percent College ( 16) at Age.1.15.2.25.3.35.4 '70 '65 2000 '95 '90 '65 '85 '70 '80 '75 '60 20 25 30 35 40 Age Murphy and Topel 2016

U.S. Women s College Attainment: Big Gains Percent College ( 16) at Age.1.2.3.4 College Attainment (16 Years) by High School Cohort and Age Women, High School Cohorts 1960-2000 2000 '95 '90 '85 '80 '70 '75 '65 '60 20 25 30 35 40 Age Murphy and Topel 2016

Failure to Launch: BA Attainment for Students Enrolling in a 4-Year College in 2003/04 by Family Income Quartile 90% 80% 76% 80% 70% 66% 60% 57% 50% 47% 40% 30% 20% 10% 0% Bottom quartile (<$32,000) 2nd quartile ($32,000-$59,999 3rd quartile ($60,000-$91,999) Highest quartile ($92,000 or more) Highest 6% ($!50,000 or more) National Center for Education Statistics, Beginning Postsecondary Students Longitudinal Study

14.662 requirements Requirements 1 Weekly readings/comments 2 Four p-sets 3 Two research proposals 4 Final/general 5 Class participation