Knowledge that Transforms

This paper presents a methodology that uses matching comparisons to explain gender wage differences. The approach emphasizes gender differences in the supports of the distributions of observable characteristics and provides insights into the distribution of unexplained gender pay differences. This nonparametric alternative to the Blinder-Oaxaca (BO) decomposition does not require the estimation of earnings equations and divides the gap into four additive elements. Two of these are analogous to the elements of the BO decomposition (but computed only over the common support of the distributions of characteristics), while the other two account for differences in the supports.

We provide a systematic analysis of the bilateral factors driving portfolio equity holdings across countries. We find that bilateral equity holdings are strongly correlated with bilateral trade in goods and services. Larger bilateral positions are also associated with proxies for informational proximity.

We study the consequences of an exogenous upsurge in coca prices and cultivation in Colombia, where most coca leaf is now harvested. This shift generated only modest economic gains in rural areas, primarily in the form of increased self-employment earnings and increased labor supply by teenage boys. The rural areas that saw accelerated coca production subsequently became considerably more violent, while urban areas were affected little. These findings are consistent with the view that the Colombian civil conflict is fueled by the financial opportunities that coca provides and that rent-seeking by combatants limits the economic gains from coca.

The advent of the U.S. Interstate Highway System provides an interesting experiment, which I use to identify the labor market effects of reduced trade barriers. This highway network was designed to connect cities and border crossings and to serve national defense, and as an unintended consequence it crossed many rural counties. I find that these counties experienced an increase in trade-related activities, such as trucking and retail sales. By increasing trade, the highways raised the relative demand for skilled manufacturing workers in skill-abundant counties and reduced it elsewhere, consistent with the predictions of the Heckscher-Ohlin model.

We examine the empirical role of different explanations for the lack of capital flows from rich to poor countries—the “Lucas Paradox.” The theoretical explanations include cross-country differences in fundamentals affecting productivity, and capital market imperfections. We show that during 1970–2000, low institutional quality is the leading explanation. Improving Peru's institutional quality to Australia's level implies a quadrupling of foreign investment. Recent studies emphasize the role of institutions for achieving higher levels of income but remain silent on the specific mechanisms. Our results indicate that foreign investment might be a channel through which institutions affect long-run development.

We examine the effects of aid on growth in cross-sectional and panel data—after correcting for the possible bias that poorer (or stronger) growth may draw aid contributions to recipient countries. Even after this correction, we find little robust evidence of a positive (or negative) relationship between aid inflows into a country and its economic growth. We also find no evidence that aid works better in better policy or geographical environments, or that certain forms of aid work better than others. Our findings suggest that for aid to be effective in the future, the aid apparatus will have to be rethought.

A recent “revisionist” literature characterizes the pronounced rise in U.S. wage inequality since 1980 as an “episodic” event of the first half of the 1980s driven by nonmarket factors (particularly a falling real minimum wage) and concludes that continued increases in wage inequality since the late 1980s substantially reflect the mechanical confounding effects of changes in labor force composition. Analyzing data from the Current Population Survey for 1963 to 2005, we find limited support for these claims. The slowing of the growth of overall wage inequality in the 1990s hides a divergence in the paths of upper-tail (90/50) inequality—which has increased steadily since 1980, even adjusting for changes in labor force composition—and lower-tail (50/10) inequality, which rose sharply in the first half of the 1980s and plateaued or contracted thereafter. Fluctuations in the real minimum wage are not a plausible explanation for these trends since the bulk of inequality growth occurs above the median of the wage distribution. Models emphasizing rapid secular growth in the relative demand for skills—attributable to skill-biased technical change—and a sharp deceleration in the relative supply of college workers in the 1980s do an excellent job of capturing the evolution of the college/high school wage premium over four decades. But these models also imply a puzzling deceleration in relative demand growth for college workers in the early 1990s, also visible in a recent “polarization” of skill demands in which employment has expanded in high-wage and low-wage work at the expense of middle-wage jobs. These patterns are potentially reconciled by a modified version of the skill-biased technical change hypothesis that emphasizes the role of information technology in complementing abstract (high-education) tasks and substituting for routine (middle-education) tasks.

Researchers have increasingly realized the need to account for within-group dependence in estimating standard errors of regression parameter estimates. The usual solution is to calculate cluster-robust standard errors that permit heteroskedasticity and within-cluster error correlation, but presume that the number of clusters is large. Standard asymptotic tests can over-reject, however, with few (five to thirty) clusters. We investigate inference using cluster bootstrap-t procedures that provide asymptotic refinement. These procedures are evaluated using Monte Carlos, including the example of Bertrand, Duflo, and Mullainathan (2004). Rejection rates of 10% using standard methods can be reduced to the nominal size of 5% using our methods.