For many problems in macroeconomics, development economics, labor economics, and international trade, whether technical change is biased towards particular factors is of central importance. This paper develops a simple framework to analyze the forces that shape these biases. There are two major forces affecting equilibrium bias: the price effect and the market size effect. While the former encourages innovations directed at scarce factors, the latter leads to technical change favoring abundant factors. The elasticity of substitution between different factors regulates how powerful these effects are, and this has implications about how technical change and factor prices respond to changes in relative supplies. If the elasticity of substitution is sufficiently large, the long-run relative demand for a factor can slope up. I apply this framework to discuss a range of issues including: Why technical change over the past 60 years was skill-biased, and why the skill bias may have accelerated over the past twenty-five years. Why new technologies introduced during the late eighteenth and early nineteenth centuries were unskill-biased. Why biased technical change may increase the income gap between rich and poor countries. Why international trade may induce skill-biased technical change. Why a large wage-push, as in continental Europe during the 1970s, may cause capital-biased technical change. Why technical change may be generally labor-augmenting rather than capital-augmenting.
A large literature documents a substantial rise in U.S. wage inequality and educational wage differentials over the past several decades and finds that these trends can be primarily accounted for by shifts in the supply of and demand for skills reinforced by the erosion of labor market institutions affecting the wages of low- and middle-wage workers. Drawing on an additional decade of data, a number of recent contributions reject this consensus to conclude that (1) the rise in wage inequality was an episodic event of the first-half of the 1980s rather than a secular phenomenon, (2) this rise was largely caused by a falling minimum wage rather than by supply and demand factors; and (3) rising residual wage inequality since the mid-1980s is explained by confounding effects of labor force composition rather than true increases in inequality within detailed demographic groups. We reexamine these claims using detailed data from the Current Population Survey and find only limited support. Although the growth of overall inequality in the U.S. slowed in the 1990s, upper tail inequality rose almost as rapidly during the 1990s as during the 1980s. A decomposition applied to the CPS data reveals large and persistent rise in within-group earnings inequality over the past several decades, controlling for changes in labor force composition. While changes in the minimum wage can potentially account for much of the movement in lower tail earnings inequality, strong time series correlations of the evolution of the real minimum wage and upper tail wage inequality raise questions concerning the causal interpretation of such relationships. We also find that changes in the college/high school wage premium appear to be well captured by standard models emphasizing rapid secular growth in the relative demand for skills and fluctuations in the rate of growth of the relative supply of college workers - though these models do not accurately predict the slowdown in the growth of the college/high-school gap during the 1990s. We conclude that these patterns are not adequately explained by either a 'unicausal' skill-biased technical change explanation or a revisionist hypothesis focused primarily on minimum wages and mechanical labor force compositional effects. We speculate that these puzzles can be partially reconciled by a modified version of the skill-biased technical change hypothesis that generates a polarization of skill demands.
We apply an understanding of what computers do to study how computerization alters job skill demands. We argue that computer capital (1) substitutes for workers in performing cognitive and manual tasks that can be accomplished by following explicit rules; and (2) complements workers in performing nonroutine problem-solving and complex communications tasks. Provided that these tasks are imperfect substitutes, our model implies measurable changes in the composition of job tasks, which we explore using representative data on task input for 1960 to 1998. We find that within industries, occupations, and education groups, computerization is associated with reduced labor input of routine manual and routine cognitive tasks and increased labor input of nonroutine cognitive tasks. Translating task shifts into education demand, the model can explain 60 percent of the estimated relative demand shift favoring college labor during 1970 to 1998. Task changes within nominally identical occupations account for almost half of this impact.
In this paper we consider the extent to which skill-biased technological changes are transferring across international borders, thereby altering the skill structure of labour markets. Evidence of increased relative demand for skilled workers is uncovered in the manufacturing sectors of 37 high-, middle-, and low-income countries. Skill-biased technology transfer is central to the increased demand for skilled workers in middle-income countries. In low-income countries there is less evidence of such a mechanism operating.
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Although the college-high school wage gap for younger U. S. men has doubled over the past 30 years, the gap for older men has remained nearly constant. In the United Kingdom and Canada the college-high school wage gap also increased for younger relative to older men. Using a model with imperfect substitution between similarly educated workers in different age groups, we argue that these shifts reflect changes in the relative supply of highly educated workers across age groups. The driving force behind these changes is the slowdown in the rate of growth of educational attainment that began with cohorts born in the early 1950s in all three countries.
Between 1986 and 1990, the Mexican government reduced tariffs and import license coverage by more than 50%. The author, using micro-level data, analyzes the impact of trade reform on Mexican wages and employment. Industries that had greater reductions in protection levels, she finds, had a larger percentage of low-skill workers. Wage dispersion increased in both the non-tradables sector and, to a much greater degree, the tradables sector. This pattern suggests that trade reform increased wage inequality. The decline in import license coverage appears to have reduced relative wages of workers in reformed industries by 2%, but did not affect relative employment. Reductions in tariffs had no statistically significant effect on relative wages or relative employment.
This paper argues that skill-biased technical change has some deficiencies as a hypothesis about the impact of technology on the labor market and that a more nuanced view recently proposed by Autor, Levy and Murnane (2003) is a more accurate description. The difference between the two hypotheses is in the prediction about what is happening to employment in low-wage jobs. This paper presents evidence that employment in the UK is polarizing into lovely and lousy jobs and that a plausible explanation for this is the Autor, Levy and Murnane hypothesis.
This paper uses microeconomic data from the U.K. Family Expenditure Surveys (FES) and the General Household Surveys (GHS) to describe and explain changes in the distribution of male wages. Since the late 1970s wage inequality has risen very fast in the U.K., and this rise is characterized both by increasing education and age differentials. We show that a large part of the changes in the U.K. can be summarized quite simply as increases in education differentials and a decline of growth of entry-level wages that persist subsequently. This fact we interpret as cohort effects. We also show that, like in the U.S., an important aspect of rising wage inequality is increased within-group wage dispersion. Finally we use the GHS to evaluate the role of alternative education measures.
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