We argue that anomalies may experience prolonged decay after discovery and propose a Bayesian framework to study how that impacts portfolio decisions. Using the January effect and short-term index autocorrelations as examples of disappearing anomalies, we find that prolonged decay is empirically important, particularly for small-cap anomalies. Papers that document new anomalies without accounting for such decay may actually underestimate the original strength of the anomaly and imply an overstated level of the anomaly out of sample. We show that allowing for potential decay in the context of portfolio choice leads to out-of-sample outperformance relative to other approaches.

Using survey data, we analyze institutional investors’ expectations about the future performance of fund managers and the impact of those expectations on asset allocation decisions. We find that institutional investors allocate funds mainly on the basis of fund managers’ past performance and of investment consultants’ recommendations, but not because they extrapolate their expectations from these. This suggests that institutional investors base their investment decisions on the most defensible variables at their disposal and supports the existence of agency considerations in their decision making.

We examine how students of varying abilities sort (and are sorted) into colleges of varying qualities. Our data indicate substantial amounts of both academic undermatch (high-ability students at low-quality colleges) and academic overmatch (low-ability students at high-quality colleges). Student application and enrollment decisions, rather than college admission decisions, drive most deviations from academic assortative matching. Financial constraints, information, and the public college options facing students all affect this sorting, but mainly via college quality rather than the match between ability and quality. More informed students attend higher-quality colleges, even when doing so involves overmatching.

We test hypotheses regarding risk taking behavior of competitors in settings characterized by one-on-one, single elimination tournaments. We draw data from 579 professional golf matches and over 18,000 holes from 2003 to 2013 in tournaments where match-play scoring is used rather than stroke-play. Because of the uniqueness of the data, we are able to provide clean empirical tests of how risk taking is affected by horizon effects (holes remaining), peer effects arising from heterogeneity in player abilities, match status (whether behind or ahead), and the difficulty of the task/project (hole). The findings are applicable to corporate settings where only a few rivals compete for a prize, such as a winning bid, a promotion, market share dominance, and patents. Other applications include litigation contests and political elections.

Recent literature has documented failures of truthful preference reporting in the strategy-proof deferred acceptance algorithm. I consider the implications of these strategic mistakes for a common welfare consideration: the ability of the mechanism to sort the best students to the best schools. I find that these mistakes have the potential to significantly help or significantly hinder sorting. Through this channel, the presence of mistaken play may have widely varying welfare effects. I discuss related considerations in the welfare evaluation of mistaken play in the deferred acceptance algorithm and the implications for “nudges” that correct these mistakes.

Toward understanding assortative matching, this is a self-contained introduction to research on search and matching. We first explore the nontransferable and perfectly transferable utility matching paradigms, and then a unifying imperfectly transferable utility matching model. Motivated by some unrealistic predictions of frictionless matching, we flesh out the foundational economics of search theory. We then revisit the original matching paradigms with search frictions. We finally allow informational frictions that often arise, such as in college-student sorting.

This paper re-creates three of the samples from LaLonde’s famous 1986 paper that began the literature on “within-study designs” that uses experiments as benchmarks against which to assess the performance of nonexperimental identification strategies. In particular, we recreate the experimental data for the target group of women on welfare from the National Supported Work (NSW) Demonstration and two of the corresponding comparison groups drawn from the Panel Study of Income Dynamics (PSID). The loss of these data resulted in the (sizable) subsequent literature devoting its attention solely to the NSW men. In addition to repeating LaLonde’s analyses on our recreations of his files for the AFDC women, we apply (many of) the estimators from later papers by Dehejia and Wahba and by Smith and Todd to these data. Our findings support the general view in the literature that women on welfare pose a less difficult selection problem when evaluating employment and training programs. They also call into question the generalizability of some of the broad conclusions that Dehejia and Wahba and Smith and Todd draw from their analyses of the NSW men.