This article investigates wage differentials for employees of different size firms utilizing an econometric methodology that allows the size of employer to be treated as endogenous in the context of discrete, ordered employer-size data. As a result we are able to estimate (i) employer-size wage gaps, which are corrected for selectivity bias, and (ii) the magnitude and direction of the selection bias. Decompositions of the resulting wage differentials are computed, with comparisons of the conditional (on sorting across employer size) and unconditional wage gaps.

This article formulates and estimates alternative equilibrium models of industrial wage determination and self-selection. In explaining industrial wage differentials, we find that it is important to account for heterogeneous sector-specific skills and self-selection decisions by agents concerning their sector of employment. The classical Roy model is rejected. So is an efficiency units model of the labor market. A revised Roy model that accounts for comparative advantage in the choice of industrial sectors and choice between market and nonmarket work is much more successful in explaining cross-section wage distributions and their evolution over time.

This paper examines real wage measures that include leisure and nonlabor income in consumption decisions with respect to the advantages and disadvantages of partial versus complete welfare orderings and of utility-based versus utility-free wage indices. In addition, we argue that the usefulness of a real wage measure beyond welfare comparison has been ignored. To test the robustness of utility-based indices, these real wage measures are calculated for two different utility-function specifications, the indirect addilog system and the linear expenditure system. Further comparisons are made against index bounds that are independent of the functional form for preferences.

There are two obvious possibilities that can account for the rise in productivity during recent recessions. The first is that the decline in the workforce was not random, and that the average worker was of higher quality during the recession than in the preceding period. The second is that each worker produced more while holding worker quality constant. We call the second effect, "making do with less," that is, getting more effort from fewer workers. Using data spanning June 2006 to May 2010 on individual worker productivity from a large firm, it is possible to measure the increase in productivity due to effort and sorting. For this firm, the second effect-that workers' effort increases-dominates the first effect-that the composition of the workforce differs over the business cycle.

There are persistent differences in self-reported subjective well-being across US metropolitan areas, and residents of declining cities appear less happy than others. Yet some people continue to move to these areas, and newer residents appear to be as unhappy as longer-term residents. While historical data on happiness are limited, the available facts suggest that cities that are now declining were also unhappy in their more prosperous past. These facts support the view that individuals do not maximize happiness alone but include it in the utility function along with other arguments. People may trade off happiness against other competing objectives.

Being hired into a job depends not only on one’s own skill but also on that of other applicants. When another able applicant applies, a well-suited worker may be forced into unemployment or into accepting an inferior job. A model of this process defines over- and underqualification and provides predictions on its prevalence and on the wages of mismatched workers. It also implies that unemployment is concentrated among the least skilled workers, while vacancies are concentrated among high-skilled jobs. Four data sets are used to confirm the implications and establish that the hiring probability is low when competing applicants are able.

Many believe that classroom interactions play an important role in students’ academic achievement, but there is little evidence on peer effects within subclassroom groups. We exploit random seat assignment in a Chinese middle school to estimate how the gender of neighboring students affects a student’s academic achievement. We find that being surrounded by five females rather than five males increases a female’s test scores by 0.2–0.3 standard deviations but has no significant effects on a male’s test scores. These results suggest a low-cost way to potentially improve performance within the world’s largest school system.

How and by how much do supervisors enhance worker productivity? Using a company-based data set on the productivity of technology-based services workers, we estimate supervisor effects and find them to be large. Replacing a boss who is in the lower 10% of boss quality with one who is in the upper 10% of boss quality increases a team’s total output by more than adding one worker to a nine-member team would. Workers assigned to better bosses are less likely to leave the firm. A separate normalization implies that the average boss is about 1.75 times as productive as the average worker.

This article tests whether the correlation between wages and concentration of employment can be explained by unobserved worker productivity. Residential location is used as a proxy for unobserved productivity, and average commute time to workplace is used to test whether location-based productivity differences are compensated away by longer commutes. Analyses using confidential data from the 2000 Decennial Census find that estimates of agglomeration wage premia within metropolitan areas are robust to comparisons within residential location and that estimates do not persist after controlling for commuting costs, suggesting that the productivity differences across locations are due to location, not individual unobservables.

We estimate peer effects in college achievement using a data set in which individuals are exogenously assigned to peer groups of about 30 students with whom they are required to spend the majority of their time interacting. This feature enables us to estimate peer effects that are more comparable to changing the entire cohort of peers. Using this broad peer group, we measure academic peer effects of much larger magnitude than found in previous studies. The effects persist at a diminished rate into follow-on years, and we find evidence of nonlinearities in the magnitude of the effects across student academic ability. (c) 2009 by The University of Chicago.