Knowledge that Transforms

We study how career and wage incentives affect labor productivity through self-selection and incentive effect channels using a two-stage field experiment in Malawi. First, recent secondary school graduates were hired with either career or wage incentives. After employment, half of the workers with career incentives randomly received wage incentives, and half of the workers with wage incentives randomly received career incentives. Career incentives attract higher-performing workers than wage incentives do, but they do not increase productivity conditional on selection. Wage incentives increase productivity for those recruited through career incentives. Observable characteristics are limited in explaining selection effects of entry-level workers.

We show that academics with experience in government jobs generate spillovers for their early-career colleagues. Our template is the National Science Foundation rotation program in which the agency employs academics, called rotators, on loan from their university. Within two years after the rotator's return, fresh assistant professors in her department increase their research resources materially and are more likely to win small and medium-size grants compared to academics in three control groups. Consistent with evidence that the mechanism is mentoring from the rotator, the results suggest that access to individuals with insights gained outside academia propels scientific careers.

In the standard missing data model, data are either complete or completely missing. However, applied researchers face situations with an arbitrary number of strata of incompleteness. Examples include unbalanced panels and instrumental variables settings where some observations are missing some instruments. I propose a model for settings where observations may be incomplete, with an arbitrary number of strata of incompleteness. I derive a set of moment conditions that generalizes those in Graham's ( 2011 ) standard missing data setup. I derive the associated efficiency bound and propose efficient estimators. Identification can be achieved even if it fails in each stratum of incompleteness.

Portfolio sorting is ubiquitous in the empirical finance literature, where it has been widely used to identify pricing anomalies. Despite its popularity, little attention has been paid to the statistical properties of the procedure. We develop a general framework for portfolio sorting by casting it as a nonparametric estimator. We present valid asymptotic inference methods and a valid mean square error expansion of the estimator leading to an optimal choice for the number of portfolios. In practical settings, the optimal choice may be much larger than the standard choices of five or ten. To illustrate the relevance of our results, we revisit the size and momentum anomalies.

We examine residential relocation and opting out of the public school system in response to school choice lottery outcomes. We show that rising kindergartners and sixth graders who lose a school choice lottery are 6 percentage points more likely to exit the district or change neighborhood schools (20% to 30% increase) and make up 0.14 to 0.35 standard deviations in average school test scores between lottery assignment and attendance the following year. Using hedonic-based estimates of land prices, we estimate that lottery losers pay a 9% to 11% housing price premium for access to a school with a 1 standard deviation higher mean test score.

Becker's theory of home production suggests substitutability between consumption spending and home production. Using panel data with detailed information on spending and time use, we analyze house-holds' ability to replace consumption spending by home produced counterparts. Keeping wages fixed and changing lifetime resources by the shock to housing wealth during the Great Recession we estimate an elasticity of substitution that is consistent with a Life-Cycle Becker model. However, we estimate that only about 11% of total spending is replaceable by home production, which, in contrast to prior literature, makes it unlikely that home production fully mitigates the consequences of wealth shocks to well-being.

The most commonly employed paradigms for decision making under risk are expected utility, prospect theory, and regret theory. We examine the simple heuristic of maximizing the probability of being ahead, which in some natural economic situations may be in contradiction to all three of the above fundamental paradigms. We test whether this heuristic, which we call probability dominance (PD), affects decisions under risk. We set up head-to-head situations where all preferences of a given class (expected utility, original or cumulative prospect theory, or regret theory) favor one alternative yet PD favors the other. Our experiments reveal that 49% of subjects' choices are aligned with PD in contradiction to any form of expected utility or prospect theory maximization; 73% are aligned with PD as opposed to preferences under risk aversion and under original and cumulative prospect theory preferences; and 68% to 76% are aligned with PD contradicting preferences under regret theory. We conclude that probability dominance substantially affects choices and should therefore be incorporated into decision-making models. We show that PD has significant economic consequences. The PD heuristic may have evolved through situations of winner-take-all competition.

Medicare reimburses health care providers for the drugs they administer. Since 2005, it has reimbursed based on the past price of the drug. Reimbursement on past prices could motivate manufacturers to set higher launch prices because providers become less sensitive to price and because provider reimbursement is higher if past prices were higher. Using data on drug launch prices between 1999 and 2010, we estimate that reimbursement based on past prices caused launch prices to rise dramatically. The evidence is consistent with the 2018 claim from Medicare's administrator that it “creates a perverse incentive for manufacturers to set higher prices.”

We investigate the willingness of individuals to persist at exploration when confronted by prolonged periods of negative feedback. We design a two-dimensional maze game and run a series of randomized experiments with human subjects in the game. Our results suggest individuals explore more when they are reminded of the incremental cost of their actions, a result that extends prior research on loss aversion and prospect theory to environments characterized by model uncertainty. In addition, we run simulations based on a model of reinforcement learning that extend beyond two-period models of decision making to account for repeated behavior in longer-running, dynamic contexts.

After the fall of the Berlin Wall on November 9, 1989, and the collapse of the German Democratic Republic, a sudden, unexpected, and massive influx of East German migrants hit the entire West German labor market. The context is well suited for investigating whether immigration influences natives' wages and how the effects depend on product and labor market conditions. We propose direct measures of potential migration with exogenous variation, compare migrants to natives with similar capabilities, and segment the labor market along predetermined margins. We find that immigration can have negative effects on the wages of natives. These effects surface when product and labor markets are competitive but not under regulations that restrict the entry of firms and provide workers with a strong influence on firms' decision making.