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2012-13 Mitra FAMILY GRANT Recipient The Side Effects of Progress: Skill-Biased Technological Change, Inequality, and Harms from 1970-2000 Warren Zhang, Class of 2013

The Side Effects of Progress: Skill-Biased Technological Change, Inequality, and Harms from 1970-2000

Warren Zhang

Mitra Scholar Program Mr. Lepler, Mentor 12 April 2013

Zhang 2 Modern technology breeds inequality and inhibits sustainable, broad-based growth. This paper has two sections. First, it analyzes the causes of the rapid growth of income inequality since the 1980s, finding that despite an important role for institutional changes such as tax policy and labor unions, the main driver of burgeoning inequality has been technological change. Beginning towards the end of the 1970s, the invention and widespread adoption of electronics and computer technology has led to dramatic increases in the demand for technically-skilled workers. Unlike in past technological revolutions, where many innovations tended to be biased in favor of unskilled workers (e.g. the factory system let unskilled laborers replace skilled artisans), modern technological innovations strongly complement skilled workers and substitute for unskilled workers, creating wage premium differentials and inequality. The second section of this paper analyzes some of the harms of inequality. While high levels of income disparity are not dangerous per se— without the promise of reward, there would be no incentives to innovate or invest—they have side effects that undermine long-term economic growth and promote financial crises. Ultimately, the technological advances that began in the late 1970s may have been a curse disguised as a blessing. By causing a massive surge in income inequality, technological progress actually helped weaken the conditions for stable, viable economic growth over the last four decades.

Trends in Inequality and their Causes, 1940-2000 The surge in income inequality in the United States in the last four decades, since the 1970s, is both a troubling social issue and a complex economic question. Formulating appropriate policy responses requires a clear view of not just the superficial trends in earnings data, but also in the deep fundamental factors that cause income dispersion to begin with. Thus, the first question we must answer is whether recent trends in income inequality are due to

Zhang 3 changes in wages or due to the reemergence of a Gilded Age-esque elite, living off of capital income. Evidence suggests that wages, not capital gains, are the main driver of inequality over the past half-century. An exhaustive analysis of IRS data from 1913 to 1998 by Thomas Piketty at the Paris School of Economics and Emmanuel Saez at the University of California-Berkeley concludes that “the increase in top income shares [from 1970-2000] is a direct consequence of the surge in top wages. As a result, the composition of income in the top income groups has shifted dramatically over the century: the working rich have now replaced the coupon-clipping rentiers.�1 Since shifts in wages have driven inequality, the logical next step is to examine trends in the labor market. Since the 1970s, top (90th percentile) wages have grown substantially, while median and bottom (50th and 10th percentile) wages have stagnated, or even declined in real terms.2 What’s more, over that exact same time period, the college wage premium has also risen dramatically.3 By themselves, these data points are not conclusive, but they strongly suggest that the most appropriate way to analyze changes in inequality over the last half-century is to examine shifts in the college wage premium through what Harvard economists Claudia Goldin and Lawrence F. Katz call a supply-demand-institutions (SDI) framework. In other words, wage (and income) inequality trends can be explained by the interplay between technological change, the relative supply and demand for skilled (i.e. college-educated) and unskilled labor, and the influence of various institutional factors such as unionization and government intervention in the economy4.

However, to fully utilize the SDI framework, and to understand the explosion in inequality that begins in the late 1970s, we must first understand how the low-inequality era of the mid-20th century emerged, and how it ended. Four key time periods play a pivotal role. The

Zhang 4 first is the Great Compression of income dispersion that occurred from 1940 to 1944, where the institutional factors that govern the next few decades first appeared. Next is the “Golden Age” of the American worker from 1945 to 1970, where inequality stayed low and real incomes at all levels see rapid growth. The third period of importance is the tumultuous 1970s, where a combination of shifting social, institutional, and economic conditions started to unravel. Finally, from 1980 to the present is the Age of Inequality, marked by rapid income growth at the top and stagnation everywhere else.

The Great Compression: 1940-1944 During the Second World War, the United States witnessed an unprecedented, swift reduction in income inequality. In 1940 the top ten percent of earners took home about 45% of all income, yet by 1944, that share had fallen to just 33%.5 Such a rapid decline in income dispersions cannot be explained through slow long-run shifts, such as the changes in the supply and demand of skilled labor. Instead, we must look to the government policies of the New Deal era and wartime wage and price controls for an answer. In the first of the four periods, the most important factor is institutional.

In the midst of the turmoil of the Great Depression, Franklin Delano Roosevelt took office with a mandate to heal the struggling economy. Since a theory of aggregate demand did not yet exist (John Maynard Keynes’s General Theory would not be published until 1936), Roosevelt and his advisers could not apply today’s basic macroeconomic stabilization tools, such as stimulus spending and other countercyclical policies. Instead, as MIT economists Frank Levy and Peter Temin document, FDR believed that the economy would naturally return to health if government policy restored wages and prices to higher, prewar levels.6 His New Deal policies reflect that belief. In the National Industrial Recovery Act of 1933, the government helped labor

Zhang 5 unions secure higher wages and shorter workdays by taking control of the contract negotiation process, raising prices substantially. The Act also set the nation’s first minimum wage at 25 cents per hour, which was equivalent to 27% of the average output per worker at the time. For comparison, the minimum wage is worth roughly half that today. While the Supreme Court struck down the National Industrial Recovery Act as unconstitutional, Congress preserved the minimum wage and expanded protections for unions in the National Labor Relations Act of 1935.7 Meanwhile, top tax rates rose from 25% in the early Hoover years to 79% by 1936.

Combined with other deficit-cutting measures, this inadvertently threw the economy back into recession, but the tax increase still furthered one of Roosevelt’s main goals: compressing the income distribution by raising low wages (through unions and the minimum wage) while reducing top incomes through progressive taxation of earnings and estates.8 Once the war broke out, the income distribution compressed even faster, as the Revenue Act of 1942 raised taxes on high earners further and the National Defense Mediation Board (and its successor, the National War Labor Board) homogenized wages across America.9 As a result, the share of wealth and income accruing to the top ten percent diminished dramatically. Those New Deal institutions would continue to play a role in the decades that followed.

The “Golden Age” of the American Worker: 1945-1969 The era from 1945 to 1970 was one of general stability coupled with substantial middleclass economic growth. Throughout the entire period inequality actually decreased slightly.

While the top 10% received 35% of all income in 1945, they took home about 34% of all income in 1970. The income share of the 90 to 99th percentiles of earners grew slowly, from 22.5% to 25%, while the income share of the top 1% dropped from about 12.5% immediately after the war

Zhang 6 to just 9% in 1970.10 The growth in the 90-99th percentiles reflects cumulative growth in capital gains, while the fall in the top 1% occurs primarily in incomes. Moreover, the “Golden Age� enjoyed extremely broad-based growth. Real incomes at the 20th, 50th, and 95th percentiles grew in concert, and in fact incomes at the 95th percentile actually grew slightly slower than median and low incomes.11 Both the supply and demand for skilled workers and the institutional framework of the postwar era played substantial roles in ensuring this outcome.

Education and the Supply-Demand Framework In this era, the primary driver of changes to the college wage premium was shifts in the supply of skilled workers, as growth in demand stayed relatively stable. Because technological progress was not strongly skill-biased, innovations tended to make both highly skilled workers and less skilled workers equally more productive. For instance, the mass adoption of cars let everyone from the old money elite to blue collar workers travel faster. Plus, the most widespread new technologies of the 1950s and 1960s were consumer goods, not capital goods. Products like the microwave, the refrigerator, and the air conditioner dramatically improved standards of living, but did not really affect worker productivity. Hence, changes in median family income closely tracked productivity growth over the entire period—since all workers became more effective, earnings growth was shared broadly over the entire economy. Meanwhile, between 1945 and 1970, the supply of skilled, college-educated workers increased substantially. Measures such as the GI bill and the creation of many public universities meant more and more students could attend college. A college degree replaced a high school diploma as the mark of an educated person, and high school graduates and high school dropouts increasingly became substitutes in the labor market.12 Goldin and Katz (2008) estimate that from 1940 to 1960, growth in the relative supply of college graduates outpaced growth in demand by about 1% annually, while

Zhang 7 growth in supply and demand kept pace with each other throughout the 1960s.13 In fact, holding demand constant, a 10% increase in the supply of skilled workers would be expected to reduce the college wage premium by about 6.1%.14 Over that same period, the college wage premium fell in the 1940s before rebounding somewhat in the 1950s, which seems to at least somewhat contradict the supply-demand framework. However, Goldin and Katz contend that the decline in the college wage premium in the 1940s overshot the equilibrium due to institutional factors, such as a sudden rise in unskilled pay due to mass unionization.15 Hence, the 1950s rebound merely brought the college wage premium back to its fundamental equilibrium value. Ultimately, the relative stability of the college wage premium in the 40s, 50s, and 60s acted as a powerful force in favor of a more equal dispersion of incomes.

Institutional Shifts: The Treaty of Detroit Era By itself, the stability in the college wage premium largely explains why inequality between top earners and median earners did not increase. Without skill-favoring technological shifts or a shrinking pool of college graduates, the college-educated workers at the top of the income distribution would not see larger paychecks. However, the supply-demand framework doesn’t explain two other key trends: why the income share of the top 1% of earners fell and why wages at the bottom of the income distribution stayed roughly in line with wages at the median.

In other words, why did the super-rich get relatively poorer, and why did even the least-skilled workers see their wages grow enough to keep up with everyone else? Those shifts reflect contemporary societal norms and labor market institutions. Labor-industry relations from 19451970, a period that Levy and Temin call the Treaty of Detroit era, are characterized by heavy government involvement, substantial union power, and social pressures against extravagant

Zhang 8 wealth. These forces, acting in concert, form the second cause of relative income equality in this time period.

In November 1945, out of concern that the end of strike controls during peacetime would lead to labor market disruption and perhaps even a second Great Depression, President Harry Truman convened a National Labor-Management Conference. The thirty-six industry, government, and union officials that attended agreed to two main principles. First, labor unions deserved respect as an integral part of the American economy, a significant concession by corporate leaders. Second, even after the war ended, the government would continue to intervene in labor-business disputes to protect union rights and avoid mass disruption of the economy.16 A few years later, the Treaty of Detroit, the famous 1949 agreement between General Motors and the United Auto Workers, consolidated union power. While labor acknowledged that management would control production and investment decisions, workers would see substantial real wage growth through the introduction of the cost-of-living adjustment, which tied wages to the Consumer Price Index, and the introduction of the annual improvement factor, which increased wages by an additional 2% per year to share productivity gains with workers.17 This system, combined with the introduction of worker pensions, soon spread to almost all major industries, including rubber and steel. The Treaty of Detroit inaugurated decades of stable labor-business relations. Collective bargaining spread throughout industries, and even nonunion firms began to approximate labor conditions at union firms. Under the watchful eyes of the National Labor Relations Board, contracts and wages in most manufacturing industries homogenized, both within industries and between them, leading to an era of sustained real wage growth for unskilled workers.18

Zhang 9 Meanwhile, top incomes continued to be squeezed by the effects of high marginal tax rates. Steeply progressive income, capital gains, and estate tax rates have dynamic effects: by reducing returns from wealth, they slow the rate at which wealth accumulates and at which the rich get richer.19 Combined, these tax policies made accumulating Gilded Age-style fortunes nearly impossible. Even more important, however, were prevailing social norms. High top tax rates persisted throughout the 1970s. In fact, a 1964 tax cut under President Lyndon Johnson did not lead to greater compensation of CEOs or higher incomes because companies feared government and media criticism.20 Things Fall Apart: 1970-1980 Over the course of the 1970s the top decile continued to earn about 34% of all income, virtually unchanged from the prior era.21 Yet this surface placidity masks the beginning of trends that triggered the surge in inequality during the following decade. The rate of real income growth for earners at the 95th percentile, which had trended slightly below the rates for median and 20th percentile earners, started to overtake the others.

The College Enrollment Boom & Skill-Biased Technical Change Partly due to draft avoidance during the Vietnam War, college enrollment rates surged towards the end of the 1960s and throughout the 1970s.22 Over the entire period from 1960 to 1980, the supply of college graduates grew at an unprecedented 3.77% per year.23 By 1976 about 40% of the U.S. population had attained some sort of post-high school education, from about 17% in 1960.24 Concurrently, the college wage premium fell by about 11% for women and about 5% for men between 1973 and 1979.25 However, by itself the surge in supply does not explain the fall in the college wage premium, as relative demand also increased by a similar amount. In fact, growth in supply and demand kept pace with each other during all of the 1970s.26

Zhang 10 This introduced a conundrum: while changes in the supply of skilled labor are simple to understand, what drove changes in demand for that labor? Why would growth in demand accelerate? One answer is that the marginal productivity of skilled workers must have increased.

Starting in the 1970s, skilled workers suddenly became more valuable. This suggests the existence of skill-biased technical change: shifts in technology that increase the value of skills.

This shift also appeared in the productivity vs. income data. While median family income and productivity tracked each other in the two and a half decades after World War II, median family income began to stagnate in the 1970s while productivity continued to increase. In other words, a minority of workers had become more productive and better compensated, but the rest had not.

MIT economist Daron Acemoglu notes that skill-biased technical change could have occurred due to an exogenous technology shock: advances in science that trigger increased demand for skills.27 But does the evidence support this claim? Intuitively, at least, it seems unlikely. If a technology boom had occurred, it should have started in the 1990s, with the development of the personal computer and the Internet. However, as Northwestern professor of economics Robert J. Gordon explains, the Third Industrial Revolution,28 based on computer and networking technology, actually traced its origins to the early 1960s. Many of the labor-saving benefits of the computer revolution were introduced in the 1960s and 1970s, such as the credit card (1950s), industrial robot (1961), automated telephone (1960s), computer-printed bill (1960), the memory typewriter (1970s), and the electronic calculator (1970). 29 And let us not forget that the transistor, which forms the fundamental building block of all modern electronic devices, was invented in 1947 and first mass manufactured in 1960. The implementation and further

Zhang 11 development of those technologies would have required far more skilled workers. Skilled workers were able to capitalize on the productivity improvements from computers and IT. Hence, the beginnings of the modern information revolution spurred a surge in demand for the college-educated. However, there does seem to be one major problem: After 1973, growth in total factor productivity, a measure of productivity after compensating for increases in labor and capital, collapses. As a Solow residual, total factor productivity should at least in theory measure productivity growth due to technological change. However, while the average annualized growth rate in TFP was 1.9% between 1947-1969, it fell to just 0.8% from 19702012, not exactly commensurate with a technological revolution.30 Fortunately, Valisher Ibragimov and Julian Sims, economists at the University of Bath School of Management, provide an explanation that preserves the exogenous technology shock theory. They note that aggregate measurements of productivity, such as TFP, suffer from two crucial flaws. First, measuring productivity in the service sector, where computer technology tends to concentrate, is substantially more difficult than doing so in the manufacturing sector. National statistics bureaus fail to properly quantify inputs and assess the qualitative productivity enhancements of information technology.31 Second, they note that while IT improvements offer competitive advantages and productivity enhancements to firms that properly utilize the new technologies, they undermine productivity growth in firms that fail to apply IT correctly. Since these changes cancel out, improved productivity would be invisible in the aggregate data. Microeconomic firmlevel studies, on the other hand, have found positive returns to investment in IT.32 Ibragimov and Sims (2008) also find that IT investments are strongly associated with increased RGDP per capita, suggesting that the benefits of a technological revolution do exist—they are simply being masked by poor data.33

Zhang 12 Institutional Drivers The analysis of changes in the supply and demand for skills still leaves one question unanswered, however: if the surge in supply of college graduates did not explain the falling college premium, what did? The unique economic conditions of the 1970s play a major role.

Excess stimulus from Vietnam War spending led to increased inflationary expectations and stagflation, which were compounded by supply shocks in food (1972-1973) and oil (1973-1974).

Meanwhile, as the total factor productivity data from the previous section indicates, productivity growth in the manufacturing sector, which was still unaffected by IT, ground to a halt. Since most union workers had contracts that added 2% wage growth per year on top of COLA adjustments, in anticipation of about 2% growth in productivity per year, the sudden slowdown of productivity growth from a 1.9% per year trend to a 0.8% per year trend meant that real wages of union workers, who were disproportionately non-college educated, rose substantially.34 This had the effect of reducing the college premium substantially. However, as the next section will explain, the deregulation and supply-side movements of the 1980s put an end to that.

The Age of Inequality: 1980-2000 Since the last stretch of the Cold War, the United States has seen rapid, persistent growth in inequality. The top 10%, who earned about 34% of all income in 1980, took home about 47% of all income in 2000. This enormous surge in inequality has been concentrated at the very top.

While the 90-99th percentiles earned 3% more of the nation’s total pool of income in 2011 than in 1980, the share of the top 1% of earners doubled, from about 10% to about 20%.35 This outsized surge in the inequality of income shares parallels changes in real incomes. Real incomes at the 95th percentile grew by about 40% from 1980 to 2000, while incomes at the median and at the 20th percentile stagnated after 1980.36

Zhang 13 Unexpectedly, however, this inequality is not caused by a surge of capital income or capital gains, which only play a significant role at the very end of the 20th century, during the dot-com bubble. Instead, as mentioned earlier, the growth in income inequality from 1980-2000 is driven by changes in wage inequality, of which there are two distinct trends. Over the entire period, upper-tail inequality, or wage inequality between the 90th percentile of earners and the median, grew dramatically. However, inequality between the median and the 10th percentile of wage earners only expanded from 1979-1987. Afterwards, inequality between low-wage workers and median workers actually contracted slightly.37 Institutional Shifts: Supply Side Economics and the Reagan Revolution The proximate cause of the sudden surge in inequality that occurred in the early 1980s can be attributed to a radical shift in tax policy, business-labor relations, and the side effects of the Volcker recession. Beginning under President Jimmy Carter, more American policymakers saw union-imposed work rules, regulations on corporations, and high top tax rates as obstacles to growth. During the Carter years, the government deregulated major industries, such as the airlines, and started pushing for more competition. However, change happened much more quickly once President Ronald Reagan took office. First, the Kemp-Roth tax cuts in 1981 helped accelerate wealth accumulation by high earners by cutting the top tax rate from 70% to 50% and by increasing the estate tax exemption from about $176,000 to $600,000. Then, the Tax Reform Act of 1986 further reduced top tax rates to 28%. This triggered a sudden, one-time surge in inequality, as the income share of the top decile (excluding capital gains) jumped from 35% in 1986 to 38% in 1988.38 More important than just the decrease in tax rates, however, was the newfound acceptance of high salaries. This shift of social norms very quickly made extremely

Zhang 14 high salaries for CEOs and other executives the norm. Hence, the Clinton and Bush I tax raises, which pushed the top tax rate back to 39.6%, are virtually invisible in the income share data.

Reagan’s decision to fire the striking air-traffic controllers also inaugurated a new era of labor-business relations. Reagan’s action indicated that the government would no longer intercede in labor-management disputes as it had throughout the post-WWII era.39 Instead, employers were free to start engaging in concession bargaining, reversing the generous wage growth policies of the 1960s and 1970s. New Federal Reserve Chairman Paul Volcker’s tightmoney policies wounded the unions even more. By forcing the economy into recession, the Fed successfully broke the inflationary expectations of the 1970s. However, financial markets, fearful of the government’s large deficits, kept real interest rates high. This boosted global demand for dollar-denominated U.S. assets, so between 1979 and 1984 the value of the dollar rose by 55%.40 The combination of lower domestic demand due to the recession and weakening exports due to the strong dollar crippled American durable goods manufacturing, a mainstay of private sector unionization. The transformation of America’s manufacturing core into the Rust Belt accelerated the decline of private sector unions. While 23% of private sector workers were unionized in 1979, a mere 16% were in 1985, and rates only diminished further over the next decade. Over that same period, total unionization rates among all male high school graduates fell from 44% to 32%. Outside of the public sector, unions quickly faded into irrelevance. 41 The decline of union power, the loss of manufacturing jobs, and the Volcker recession explain the increase in lower-tail inequality (between the 10th percentile and the median).

However, these forces do not explain why upper-tail inequality has continued to increase steadily, or why lower-tail inequality has actually slightly shrunk since 1990. For those reasons, we must return to the idea of skill-biased technological change.

Zhang 15 Skill-biased Technological Change From 1979 to 2000 the college wage premium rose by about 22% for men and women.

The makeup of employment in the United States has also shifted. The share of employment of workers without a college degree has fallen from 57.5% of all jobs in 1980 to just 42.7% in 2000. The empirical evidence showed substantial shifts in both the supply and demand for skilled workers. The rate of growth of the supply of skilled college graduates slowed from 3.77% per year (1960-1980 trend) to just 2% per year after 1980.42 As a result, Goldin and Katz (2008) concluded that in the period after 1980, demand for skilled workers outstripped supply.

However, by itself, the slowdown in the growth of the supply of skilled workers is not enough to explain growing wage inequality, nor does it tell us anything about why the income distribution has polarized since 1987, with inequality between the median and 10th percentile decreasing and inequality between the median and 90th percentile increasing. To fully account for those shifts, we must also examine trends in demand. In the 1980s, demand for college-educated workers accelerated; the exogenous technology shock described above was inducing skill-biased technical change. This matches the pattern of rising college premiums and inequality. However, starting in about 1990, the growth in relative demand for skilled workers slowed, though not to the extent of the supply.43 On its face, this seems to contradict the entire skill-biased technical change hypothesis.

Fortunately, this problem also has a resolution. Examining the data in detail reveals that earnings of workers with advanced degrees (anything after a bachelor’s degree) have increased rapidly and continuously since 1979, while earnings of bachelor’s-only workers rose until 1987, then slowly plateaued.44 As the college-educated group became a larger share of the workforce, it also became more heterogeneous. Demand for graduates from selective institutions and for the

Zhang 16 highest-skilled (with advanced degrees) has continued to rise, and these individuals have done well, while less skilled individuals have not done as well.45 Simply having a bachelor’s degree is no longer a guarantee of being at the top of the earnings distribution. While a four-year degree increases one’s median lifetime earnings by 74% compared to simply having a high school diploma, one can double one’s earnings by earning a doctorate (149% more) or a professional (180% more) degree.

What’s more, one’s choice of major and occupation have also become more important over time. Since the 1990s, the share of employment in low and high skill occupations has expanded, while the share of employment in mid-skill occupations has contracted. For skilled workers such as managers and other professionals, who perform nonroutine, abstract cognitive and interpersonal tasks, information technology acts as a complement, making these individuals even more productive. On the other hand, for workers performing routine analytical or mechanical tasks, such as middle white collar jobs and manufacturing, IT acts as a substitute, replacing people with computers and robots. It follows that workers in technologically intensive occupations, such as management, health care, and the STEM (science, technology, engineering, and math) fields earn several times more over their lifetimes than workers who are replaced by technology. In fact, a Georgetown University study found that the median STEM worker who only had a high school diploma would still earn more over the course of a lifetime than even the best-educated personal services or blue collar workers.46 Health care, management, and STEM professionals also gained the most from going to college, increasing their lifetime earnings by between 50-100% with the completion of any sort of advanced (post-bachelor’s) degree. Workers in other occupations usually gained less than 20% from adding a college degree (with the

Zhang 17 exception of education workers, as becoming a teacher without a college degree is almost impossible).

This demonstrates that what increases a worker’s marginal product (and thus his or her paycheck) the most is not simply having a degree, but rather possessing one of two types of skills: interpersonal/management ability or strong technical ability. Both of those are enhanced by technology and cannot be done by machines. The latter ability, too, also requires that one major in a technical, STEM field in college., The Center on Education and the Workforce at Georgetown discovered that nine of the ten majors with the highest median earnings per year in were in engineering or computer science, the subjects complemented best by increases in technology.47 On the other hand, the ten majors with the lowest median incomes are in subjects that have not benefited from technological innovations in the last thirty years such as counseling/psychology, theology, early childhood education, social work, and the arts.

Finally, low-skilled workers in service jobs, such as orderlies, cleaners, and food service workers, are virtually unaffected by IT, since their jobs cannot (yet) be replaced by technology.48 Jobs between the 20th and 60th percentiles of wages are the most likely by far to involve routine tasks, so the median worker is most affected by technological change. This explains why bottomtail inequality has stabilized while upper-tail inequality has increased: the median worker has been harmed the most by technological change, while bottom-percentile workers have been relatively unaffected and top-earners have benefited. This technology-driven dynamic of better wages for the skilled, declining wages for the middle, and stagnant wages for the bottom fueled the massive growth of inequality over this period.

Zhang 18 Harms of Inequality Since 1975, when the late Yale and Brookings Institution economist Arthur Okun published his book Equality and Efficiency: The Big Tradeoff, he posited that nations must choose between having an equitable income distribution and rapid economic efficiency and growth. Okun’s reassessment of the empirical and theoretical literature reveals substantial and manifold costs to inequality. These pernicious effects occur in several ways. First, income inequality reduces consumption and thus aggregate demand because the rich have a higher marginal propensity to save. Second, income inequality actually reduces the rate of growth by distorting the political system’s ability to create sustainable institutions and policies. Third, inequality promotes a growth in leverage that feeds financial crises. Fourth, inequality reduces social mobility.

Inequality & Consumption Wealthier individuals have a lower marginal propensity to consume. With their higher incomes, they are capable of saving more, and since the marginal utility of each additional dollar is lower, they have less incentive to spend. Hence, greater inequality reduces aggregate consumption and thus reduces economic growth. Princeton professor and chair of the President’s Council of Economic Advisers Alan Krueger provides evidence to back up this theory. He notes that the share of income received by the top one percent of earners grew by about fourteen percentage points between 1979 and 2007, or about $1.1 trillion per year (2007 dollars).49 The top 1% have a marginal propensity to save of about 0.5, while the average household has a savings rate of about 10%. Hence, if that $1.1 trillion per year had gone to the bottom 99% instead, annual consumption would have been about 5%, or $440 billion, higher.50 The rich simply do not consume enough to grow the economy as well as a broad middle class. However,

Zhang 19 the reverse is not true—aggregate demand did not decrease by $440 billion per year because of rising inequality. Instead, many households borrowed to fuel their consumption despite poor income growth. This presents its own set of problems, as analyzed in section II-C below.

Inequality, Growth, & Political Institutions Unexpectedly, high levels of income inequality do not incentivize economic growth— they suppress it. Analyzing data from the U.S. and eight developed European nations from 1830 to 1985, economists Torsten Persson and Guido Tabellini at the Stockholm University and the Università di Brescia, respectively, concluded that periods of high income inequality have a strong negative association with rates of later economic growth.51 In other words, highly unequal societies grow slower, not faster. However, this is not because Okun’s incentive theory is wrong.

Instead, suppressed growth occurs because high levels of inequality adversely affect the political institutions responsible for crafting economic policy, leading to counterproductive laws that strangle economic growth. Political, social, and economic institutions have powerful effects on a nation’s economy. As a previous section noted, the breakdown of social norms against high salaries for executives helped fuel wage inequality between the top 1% and the rest of society.

But what precisely are institutions? In line with the established literature, this paper will define institutions to be the “humanly derived constraints that shape human interaction,” or less formally, a society’s “rules of the game”.52 Human incentives are shaped by these institutions, and in return, those institutions are affected by changing preferences. Economists Daron Acemoglu, Simon Johnson, and James Robinson lay out a broad theory of how economic incentives emerge. First, the authors note that the distribution of resources in a society is naturally a source of conflict, and is thus a political question as well as an economic one.53 Since different economic institutions lead to different

Zhang 20 distributions of resources, disparate groups and individuals will compete for the political power needed to alter those institutions in their own favor. This puts two opposing forces to work. Due to their additional resources, the wealthy usually have more political power, which they use to push for policies that favor the rich54. The interests of the wealthy rarely align with those of society as a whole, so this sort of rent-seeking tends to promote persistent inequality, at the general public’s expense. However, pro-equality backlashes, which lead to the creation of redistributive tax and transfer policies, often only make matters worse.55 Such policies undermine incentives to work and invest, further weakening economic growth. Ultimately, the most sustainable institutions emerge when political and economic power is held by a relatively large group, since its self-interested policies are more likely to benefit all of society.

Inequality & Financial Crises Since the financial crisis of 2007, media and public attention have zeroed in on ballooning public debts, both in the U.S. and in the European Union. Yet the crisis surrounding government debt masked a far greater accumulation of debt: that of ordinary Americans.

Between 1981 and 2007, the private debt-to-GDP ratio grew from 90% to 210%.56 To meet the growing demand for financial services, the U.S. financial sector also doubled in size, from about 4% of the economy to an unprecedented 8%. That growing debt resulted from a massive surge in borrowing in the bottom 95% of the income distribution. While debt-to-income ratios hovered around 70% for the top 5% of earners over the entire period, the bottom 95% saw theirs double to 140%, mostly because of home mortgages.57 Such unsustainable debt levels helped fuel the financial crisis of 2007 and are slowing the recovery today, as households deleverage and repair their balance sheets.

Zhang 21 This surge in debt and the resulting crisis occurred in large part due to growing income inequality. As wage growth for most Americans stagnated while top earners pulled ahead, a “trickle-down consumption” effect occurred. According to the University of Chicago’s Marianne Bertrand and Adair Morse, a 10% increase in consumption by the top 20% of earners causes a 2.5% increase in consumption by the bottom 80%.58 Ordinary Americans started spending more even as their incomes stopped growing. In other words, they took on debt. In fact, had incomes for the top quintile grown at the same rate as incomes for the median over the past three decades, the average savings rate would have been about 1.5% higher, which translates to $500 more savings per household per year.59 However, workers did not just leverage up by themselves. As University of Chicago professor Raghuram Rajan concludes in his 2010 book “Fault Lines,” by reducing capital requirements at Fannie Mae and Freddie Mac, expanding loan guarantees at the Federal Housing Administration, and promoting widespread homeownership, government policies made it easier for workers to accumulate far too much debt.60 Moreover, these policy changes were spurred by rising inequality. Bertrand and Morse also found that congresspeople who represented the most unequal districts were more likely to vote for deregulation and more affordable credit in order to sustain broad-based consumption.61 Ultimately, while borrowing and spending propped up American consumers for a few decades, inequality-driven overleveraging eventually sowed the seeds of disaster.

Inequality & Social Mobility All too often, inequality is self-sustaining. As proven in the previous sections, American income inequality in the past few decades has largely occurred due to skill-biased technical change, which favors college-educated workers who are assisted by new technology. Yet one of

Zhang 22 the biggest determinants of whether a child attends college is his or her parents’ incomes—and this effect has become more powerful over time. For children born between 1961 and 1964, being in the top quartile increased your chances of entering college by 39% compared to the bottom quartile and raised your chances of graduating by 31%.62 But for children born between 1979-1982, being born into the top quartile raised your chances of enrollment by 51% and your chances of completion by 45% relative to those in the lowest quartile. College-educated parents have both the resources and the motivation to send their own children to college, while the less educated tend to stay that way. The intergenerational persistence of inequality is predicted to rise as a result. Currently, the best estimates of intergenerational income elasticity (IGE) put its value at around 0.4. In other words, if one’s parents earned 50% more than average, their children can be expected to earn 20% more than average in their generation. As Professor Krueger argues, the IGE in the U.S. is predicted to rise to about .56 over the next generation. Because income is now so dependent on skills, the rise in inequality in the past 30 years will make it even more difficult for the children of the poor to overcome their inherent disadvantages.

A detailed investigation of the causes of income inequality since the end of the 1970s reveals two distinct driving factors. First, during the 1980s, high incomes disappeared and labor unions weakened, removing the institutional factors that promoted broad-based growth during the 1950s and 1960s. Second, an exogenous technology shock from the emergence of computers and eventually the Internet increased the value of college-educated, high-skill workers, raising their incomes, while creating substitutes for most routine workers, squeezing the middle class. As healthy economies must have some level of inequality in order to incentivize growth, it is increasingly clear that rapid growth in inequality as driven by technological progress has pernicious effects that also undermine economic progress. Because of trickle-down consumption

Zhang 23 and easy credit policies designed to prop up growth through increased consumer debt, inequality spurs households to overleverage, setting the stage for an inevitable financial crisis and catastrophic consequences. Since inequality (outside the top 0.1%) has been caused by changes in productivity because of the complementary effects of IT, redistributive government policies would only distort incentives and further reduce growth. Instead, policy responses should focus on equipping the median worker with the skills needed to benefit from technological advances.

That means improving education and college graduation rates (with a focus on STEM fields), especially among lower-income families. The best way to promote long-run equality may be building a better education system today.

Technological progress is unquestionably important. Without the transfer of scientific advances to the commercial world, our lives would be far poorer and more tedious. But we should question the conventional wisdom that technological growth is an absolute, universal good. Because modern innovations only make a small subset of skilled workers more productive, they induce damaging, even crisis-provoking inequality.

Zhang 24 Notes

1

Thomas Piketty and Emmanuel Saez, "Income Inequality in the United States, 1913-1998," The Quarterly Journal of Economics 118, no. 1 (February 2003): 3, accessed March 23, 2013, http://elsa.berkeley.edu/~saez/pikettyqje.pdf.

2 David H. Autor, Lawrence F. Katz, and Melissa S. Kearney, "Trends in U.S. Wage Inequality: Revising the Revisionists," The Review of Economics and Statistics 90, no. 2 (May 2008): 301, accessed March 23, 2013, http://economics.mit.edu/files/586.

3 College Wage Premium, by Gender, 1973-2011," chart, in The State of Working America, by Lawrence Mishel, et al., 12th ed. (Ithaca, NY: Cornell University Press, 2012), 211, accessed April 4, 2013, http://stateofworkingamerica.org/files/book/Chapter4-Wages.pdf.

4 Claudia Goldin and Lawrence F. Katz, The Race between Education and Technology: The Evolution of U.S. Educational Wage Differentials, 1890 to 2005, research report no. 12984 (Cambridge, MA: National Bureau of Economic Research, 2007), 6, accessed March 23, 2013, http://www.nber.org/papers/w12984.

5 Piketty and Saez, “Income Inequality in the U.S.,” 12.

6 Frank Levy and Peter Temin, "Inequality and Institutions in 20th Century America" (working paper, Department of Economics, MIT, Cambridge, MA, June 27, 2007), 16, accessed April 3, 2013, http://ssrn.com/abstract=984330.

7 Levy and Temin, “Inequality and Institutions,” 16.

8 Ibid., 18.

9 Ibid., 20.

10 Piketty and Saez, "Income Inequality in the U.S.," 12.

11 Economic Policy Institute, "Low-, Middle-, and High-Income Growth, 1947-2011," chart, The State of Working America, October 5, 2012, accessed April 3, 2013, http://stateofworkingamerica.org/charts/real-income-growth-fordifferent-income-percentiles-diverged-in-the-1970s-with-real-incomes-flattening-in-the-20th-percentile-and-themedian-and-increasing-in-the-95th-percentile/.

12 Goldin and Katz, The Race between Education and Technology, 15.

13 Ibid., 12.

14 Ibid., 9.

15 Ibid., 12.

16 Levy and Temin, “Inequality and Institutions,” 20.

17 Ibid., 23.

18 Ibid., 24-26.

19 Piketty and Saez, "Income Inequality in the U.S.," 23.

20 Levy and Temin, “Inequality and Institutions,” 27.

21 Piketty and Saez, "Income Inequality in the U.S.," 12.

22 Autor, Katz, and Kearney, “Trends in U.S. Wage Inequality,” 307.

23 Goldin and Katz, The Race between Education and Technology, 13.

24 Organisation for Economic Co-operation and Development, "Percentage of Population That Has Attained Tertiary Education, by Age Group," infographic, OECD iLibrary, June 13, 2012, accessed April 4, 2013, http://www.oecdilibrary.org/economics/oecd-economic-surveys-canada-2012/population-with-tertiary-education-2009_eco_surveyscan-2012-graph32-en.

25 Lawrence Mishel et al., "Wages," in The State of Working America, 12th ed. (Ithaca, NY: Cornell University Press, 2012), 211, accessed April 4, 2013, http://stateofworkingamerica.org/files/book/Chapter4-Wages.pdf.

26 Goldin and Katz, The Race between Education and Technology, 12.

27 Daron Acemoglu, "Technical Change, Inequality, and the Labor Market," Journal of Economic Literature 40, no.

3 (March 2002): 11.

28 The First Industrial Revolution, as identified by Gordon (2012), occurred between 1750 and 1830 and was driven by the technologies of the steam engine, the textile loom, and the railroad. The Second Industrial Revolution introduced the technologies of electricity, the internal combustion engine, and indoor plumbing/running water between 1870-1900. In both cases, about 100 years passed before the effects of those inventions fully percolated throughout the economy; for example, IR2-based benefits, such as air conditioning and home appliances, did not become widespread until the 1950s-1970s.

29 Robert J. Gordon, Is US Economic Growth Over? Faltering Innovation Confronts the Six Headwinds, research report no. 18315 (Cambridge, MA: National Bureau of Economic Research, 2012), 11, accessed March 23, 2013, http://www.nber.org/papers/w18315.

Zhang 25

30

Center for the Study of Income and Productivity, Federal Reserve Bank of San Fransisco and The Economist, "U.S. Total Factor Business Productivity," chart, The Economist, September 8, 2012, accessed April 3, 2013, http://www.economist.com/blogs/freeexchange/2012/09/productivity-and-growth.

31 Valisher Ibragimov and Julian Sims, "An Updated View of the Productivity Paradox in the Early 21st Century" (paper presented at European Conference on Information Systems, Galway, Ireland, June 2008), 4, PDF. 32 Ibid., 5.

33 Ibid., 7.

34 Goldin and Katz, The Race between Education and Technology, 11.

35 Emmanuel Saez, Striking It Richer: The Evolution of Top Incomes in the United States (Berkeley, CA: University of California, 2013), 8, PDF. 36 Economic Policy Institute, "Low-, Middle-, and High-Income Growth, 1947-2011," chart, The State of Working America, October 5, 2012, accessed April 3, 2013, http://stateofworkingamerica.org/charts/real-income-growth-fordifferent-income-percentiles-diverged-in-the-1970s-with-real-incomes-flattening-in-the-20th-percentile-and-themedian-and-increasing-in-the-95th-percentile/.

37 Autor, Katz, and Kearney, “Trends in U.S. Wage Inequality,” 301.

38 Piketty and Saez, "Income Inequality in the U.S.," 12.

39 Levy and Temin, “Inequality and Institutions,” 34.

40 Ibid., 5.

41 Ibid.

42 Goldin and Katz, The Race between Education and Technology, 13.

43 Ibid.; Acemoglu, “Technical Change, Inequality, and the Labor Market,” 11.

44 Autor, Katz, and Kearney, “Trends in U.S. Wage Inequality,” 301.

45 Goldin and Katz, The Race between Education and Technology, 12.

46 Anthony P. Carnevale, Stephen J. Rose, and Ban Cheah, The College Payoff: Education, Occupations, Lifetime Earnings (Washington, D.C.: Georgetown University Center on Education and the Workforce, 2011), 9, accessed April 8, 2013, http://www9.georgetown.edu/grad/gppi/hpi/cew/pdfs/collegepayoff-complete.pdf.

47 Mary Beth Marklein, "College Major Analysis: Engineers Get Highest Salaries," USA Today, last modified May 23, 2011, accessed April 9, 2013, http://usatoday30.usatoday.com/news/education/2011-05-23-College-majorsengineering-higher-education_n.htm.

48 Autor, Katz, and Kearney, “Trends in U.S. Wage Inequality,” 318.

49 Alan B. Krueger, "The Rise and Consequences of Inequality in the United States," speech presented at Center for American Progress, Washington, D.C., January 12, 2012, Council of Economic Advisers, last modified January 12, 2012, accessed April 8, 2013, http://www.whitehouse.gov/sites/default/files/krueger_cap_speech_final_remarks.pdf.

50 Ibid.

51 Torsten Persson and Guido Tabellini, "Is Inequality Harmful for Growth?," American Economic Review 84, no. 3 (June 1994): 2, accessed April 8, 2013, http://didattica.unibocconi.it/mypage/upload/48805_20081009_055128_IS_INEQUALITY_HARMFUL_FOR_GR OWTH.PDF. 52 Daron Acemoglu, Simon Johnson, and James A. Robinson, "Institutions as a Fundamental Cause of Long-Run Growth," in Handbook of Economic Growth, ed. Philippe Aghion and Steven N. Durlauf, Handbooks in Economics (Amsterdam: North Holland, 2006), 1A:388, accessed April 8, 2013, http://economics.mit.edu/files/4469.

53 Ibid., 394, 390.

54 Ibid, 392.

55 Persson and Tabellini, 1.

56 Michael Kumhof and Romain Rancière, Inequality, Leverage and Crises, technical report no. 10-286 (Washington, D.C.: International Monetary Fund, 2010), 8, accessed April 8, 2013, https://www.imf.org/external/pubs/ft/wp/2010/wp10268.pdf.

57 Ibid., 7.

58 Marianne Bertrand and Adair Morse, "Trickle-Down Consumption" (working paper, Booth School of Business, University of Chicago, February 2012), 1, accessed April 8, 2013, http://isites.harvard.edu/fs/docs/icb.topic964076.files/BertrandMorseTrickleDown_textandtables.pdf.

59 Ibid, 19.

60 "Body of Evidence: Is a Concentration of Wealth at the Top to Blame for Financial Crises?," Free Exchange, The Economist, March 17, 2012, accessed April 8, 2013, http://www.economist.com/node/21550246.

61 Bertrand and Morse, “Trickle-Down Consumption,” 3.

Zhang 26

62

David Autor and Melanie Wasserman, Wayward Sons: The Emerging Gender Gap in Labor Markets and Education, publication no. 662 (Washington, D.C.: Third Way, 2013), 41, accessed April 3, 2013, http://www.thirdway.org/publications/662.

Zhang 27

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