Knowledge that Transforms

We present new identification resiilts for models of first-price, second-price, ascending (English), and descending (Dutch) auctions.We analyze a general specification of bidders' preferences and the underlying information structure, nesting as special cases the pure private values and pure common values models, and allowing both ex ante symmetric and asymmetric bidders.We address identification of a series of such models and propose strategies for discriminating between them on the basis of observed data.In the simplest case, the symmetric independent pri- vate values model is nonparametrically identified even if only the transaction price from each auction is observed.For more complex models, we provide conditions for identification and testing when additional information of one of the following types is available: (i) one or more bids in addition to the transaction price; (ii) exogenous variation in the number of bidders; (iii) bidder-specific covariates that shift the distribution of valuations; (iv) the ex post reahzation of the value of the object sold.Our results include new tests that distinguish between private and common values models.

We construct and estimate an equilibrium search model with on–the–job–search. Firms make take–it–or–leave–it wage offers to workers conditional on their characteristics and they can respond to the outside job offers received by their employees. Unobserved worker productive heterogeneity is introduced in the form of cross–worker differences in a “competence” parameter. On the other side of the market, firms also are heterogeneous with respect to their marginal productivity of labor. The model delivers a theory of steady–state wage dispersion driven by heterogenous worker abilities and firm productivities, as well as by matching frictions. The structural model is estimated using matched employer and employee French panel data. The exogenous distributions of worker and firm heterogeneity components are nonparametrically estimated. We use this structural estimation to provide a decomposition of cross–employee wage variance. We find that the share of the cross–sectional wage variance that is explained by person effects varies across skill groups. Specifically, this share lies close to 40% for high–skilled white collars, and quickly decreases to 0% as the observed skill level decreases. The contribution of market imperfections to wage dispersion is typically around 50%.

Self-selected migration presents one potential explanation for why observed returns to a college education in local labor markets vary widely even though U.S. workers are highly mobile.To assess the impact of self-selection on estimated returns, this paper first develops a Roy model of mobility and earnings where workers choose in which of the 50 states (plus the District of Columbia) to live and work.Available estimation methods are either infeasible for a selection model with so many alternatives or place potentially severe restrictions on earnings and the selection process.This paper develops an alternative econometric methodology which combines Lee's (1983) parametric maximum order statistic approach to reduce the dimensionality of the error terms with more recent work on semiparametric estimation of selection models (e.g., Ahn and Powell, 1993).The resulting semiparametric correction is easy to implement and can be adapted to a variety of other polychotomous choice problems.The empirical work, which uses 1990 U.S. Census data, confirms the role of comparative advantage in mobility decisions.The results suggest that self-selection of higher educated individuals to states with higher returns to education generally leads to upward biases in OLS estimates of the returns to education in state-specific labor markets.While the estimated returns to a college education are significantly biased, correcting for the bias does not narrow the range of returns across states.Consistent with the finding that the corrected return to a college education differs across the U.S., the relative state-to-state migration flows of college-versus high school-educated individuals respond strongly to differences in the return to education and amenities across states.

The flood of veterans enrolling in college at the end of World War II contributed to widespread rhetoric that the G.I. Bill brought about the "democratization" of American higher education. Whether military service, combined with educational benefits, led World War II veterans to increase their investments in college has received little research attention. Our estimation strategy focuses on between-cohort differences in military service, and we use census data to compare the collegiate attainment of veterans and nonveterans. The net effect of military service and G.I. benefits was substantial gains in the collegiate attainment of World War II veterans.

We study optimal incentives for a two‐stage production process. First, we identify conditions under which the optimal incentive structure for both workers is based on total volume and conditions for when the final stage worker’s incentives are based on relative performance. We show that a bottleneck‐free and balanced line is optimal only when both workers’ contracts are based on volume, while it becomes desirable to limit the final stage worker’s productivity when his compensation is based on relative performance. Thus, we demonstrate that the benefit of removing bottlenecks hinges critically on the structure of the optimal incentive arrangement.

We present a model in which unemployed workers simultaneously sample n potential employers. By varying n, we nest search and Walrasian‐type models of the labor market. We show that low values of n yield typical search equilibria: the wages are dispersed below the marginal productivity of labor. Interestingly, as n exceeds a relatively small threshold, the Walrasian‐type equilibrium emerges with the competitive wage quoted by all firms. For intermediate values of n, the equilibrium is a hybrid of the Walrasian and search equilibria. The model generates wage rigidity and yields novel predictions regarding the comovement of wages, firm turnover, and unemployment.

The negative effect of quits on the willingness of firms to provide on‐the‐job training is well documented in the theoretical literature. Here we explore the strength of this effect by solving a firm’s dynamic optimization problem where there is uncertainty about future productivity and nonzero firing costs. We find that the degree to which quit rates affect hiring depends on the ratio of firing to hiring costs. As this ratio rises, the negative effect of quits becomes less important, eventually reversing itself. We also describe how quit rates affect the firing decision. We highlight some testable implications of our analysis.