The Relative Efficiency of Skilled Labor across Countries: Measurement and Interpretation

I study how the relative efficiency of high- and low-skill labor varies across countries. Using microdata for countries at different stages of development, I document that differences in relative quantities and wages are consistent with high-skill workers being relatively more productive in rich countries. I exploit variation in the skill premia of foreign-educated migrants to discriminate between two possible drivers of this pattern: cross-country differences in the skill bias of technology and in the relative human capital of skilled labor. I find that the former is quantitatively more important, and discuss the implications of this result for development accounting. (JEL I26, J24, J31, J61, L16, O15)

Unpacking Skill Bias: Automation and New Tasks

We extend the canonical model of skill-biased technical change by modeling the allocation of tasks to factors and allowing for automation and the creation of new tasks. In our model, factor prices depend on the set of tasks they perform. Automation can reduce real wages and generate sizable changes in inequality associated with small productivity gains. New tasks can increase or reduce inequality depending on whether they are performed by skilled or unskilled workers. Industry-level data suggest that automation significantly contributed to the rising skill premium, while new tasks reduced inequality in the past but have contributed to inequality recently.

Worker Personality: Another Skill Bias beyond Education in the Digital Age

We present empirical evidence suggesting that technological progress in the digital age will be biased not only with respect to skills acquired through education but additionally with respect to non-cognitive skills (personality). We measure the direction of technological change by estimated future digitalization probabilities of occupations, and non-cognitive skills by the Big Five personality traits from four German worker surveys. Even though we control for education and work experience, we find that workers who are more open to experience, emotionally more stable and less agreeable will tend to be less susceptible to digitalization. We also find that future technological progress may not continue to hollow out the middle class as much as it did in the recent past. These results suggest that education and labor market policies should put more emphasis on children’s and workers’ personalities to strengthen their labor market resilience in the digital age.

Why Has Urban Inequality Increased?

This paper examines mechanisms driving the more rapid increases in wage inequality in larger cities between 1980 and 2007. Production function estimates indicate strong evidence of capital–skill complementarity and increases in the skill bias of agglomeration economies in the context of rapid skill-biased technical change. Immigration shocks are the source of identifying variation across cities in changes to the relative supply of skilled versus unskilled labor. Estimates indicate that changes in the factor biases of agglomeration economies rationalize at least 80 percent of the more rapid increases in wage inequality in larger cities. (JEL J24, J31, O33, R23)

Brain Drain from Israel and Skill-Biased Global Immigration Policy

A more generous welfare state (particularly with an aging population) has financing needs that immigrants could fill. With high-skilled immigrants more likely to pay in rather than draw on the welfare state, more generous welfare states are more inclined to try to attract high skilled. Israel ranks third in the world in the number of university graduates per capita, after the United States and the Netherlands. It possesses the highest per capita number of scientists in the world, with 135 for every 10,000 citizens (compared to 85 per 10,000 in the United States). Israelis took full advantage of the immigration skill bias. When examining the index for educated émigrés, i.e., those with a college degree, the average index is 12.41 and Israel's index is more than three times higher, 41.45. Using this index, Israel is higher than Portugal and the gap between Israel and Ireland (49.09) narrows considerably.