The research in Psychology and Economics (a.k.a. Behavioral Economics) suggests that individuals deviate from the standard model in three respects: (1) nonstandard preferences, (2) nonstandard beliefs, and (3) nonstandard decision making. In this paper, I survey the empirical evidence from the field on these three classes of deviations. The evidence covers a number of applications, from consumption to finance, from crime to voting, from charitable giving to labor supply. In the class of nonstandard preferences, I discuss time preferences (self-control problems), risk preferences (reference dependence), and social preferences. On nonstandard beliefs, I present evidence on overconfidence, on the law of small numbers, and on projection bias. Regarding nonstandard decision making, I cover framing, limited attention, menu effects, persuasion and social pressure, and emotions. I also present evidence on how rational actors—firms, employers, CEOs, investors, and politicians—respond to the nonstandard behavior described in the survey. Finally, I briefly discuss under what conditions experience and market interactions limit the impact of the nonstandard features.

How has publishing in top economics journals changed since 1970? Using a data set that combines information on all articles published in the top-five journals from 1970 to 2012 with their Google Scholar citations, we identify nine key trends. First, annual submissions to the top-five journals nearly doubled from 1990 to 2012. Second, the total number of articles published in these journals actually declined from 400 per year in the late 1970s to 300 per year most recently. As a result, the acceptance rate has fallen from 15 percent to 6 percent, with potential implications for the career progression of young scholars. Third, one journal, the American Economic Review, now accounts for 40 percent of top-five publications, up from 25 percent in the 1970s. Fourth, recently published papers are on average three times longer than they were in the 1970s, contributing to the relative shortage of journal space. Fifth, the number of authors per paper has increased from 1.3 in 1970 to 2.3 in 2012, partly offsetting the fall in the number of articles per year. Sixth, citations for top-five publications are high: among papers published in the late 1990s, the median number of Google Scholar citations is 200. Seventh, the ranking of journals by citations has remained relatively stable, with the notable exception of the Quarterly Journal of Economics, which climbed from fourth place to first place over the past three decades. Eighth, citation counts are significantly higher for longer papers and those written by more coauthors. Ninth, although the fraction of articles from different fields published in the top five has remained relatively stable, there are important cohort trends in the citations received by papers from different fields, with rising citations to more recent papers in Development and International, and declining citations to recent papers in Econometrics and Theory. (JEL A14)

Economists have studied the impact of numerous state laws, from welfare rules to voting ID requirements. Yet for all this policy evaluation, what do we know about policy diffusion—how these policies are introduced and spread from state to state? We present a series of facts based on a data set of 602 U.S. state policies spanning the past seven decades. First, proxies of state capacity do not predict a higher likelihood of innovating new policies, but the political leaning of the state does predict a higher likelihood of introducing partisan laws since 1990. Second, the diffusion of policies from 1950 to 2000 is best predicted by proximity—a state is more likely to adopt a policy if nearby states have already done so—as well as similarity in voter policy preferences. Third, since 2000, party alignment has become the strongest predictor of diffusion, and the speed of adoption has increased. Models of learning and correlated preferences can account for the earlier patterns, but the findings for the last two decades indicate a sharply increasing role of party control. We conclude that party polarization has emerged as a key factor recently for policy adoption, plausibly leading to a worse match between state policies and voter preferences.

How much do different monetary and non-monetary motivators induce costly effort? Does the effectiveness line up with the expectations of researchers and with results in the literature? We conduct a large-scale real-effort experiment with eighteen treatment arms. We examine the effect of (1) standard incentives; (2) behavioural factors like social preferences and reference dependence; and (3) non-monetary inducements from psychology. We find that (1) monetary incentives work largely as expected, including a very low piece rate treatment which does not crowd out effort; (2) the evidence is partly consistent with standard behavioural models, including warm glow, though we do not find evidence of probability weighting; (3) the psychological motivators are effective, but less so than incentives. We then compare the results to forecasts by 208 academic experts. On average, the experts anticipate several key features, like the effectiveness of psychological motivators. A sizeable share of experts, however, expects crowd-out, probability weighting, and pure altruism, counterfactually. As a further comparison, we present a meta-analysis of similar treatments in the literature. Overall, predictions based on the literature are correlated with, but underperform, the expert forecasts.

Media outlets are increasingly owned by conglomerates, inducing a conflict of interest: a media outlet can bias its coverage to benefit companies in the same group. We test for bias by examining movie reviews in media outlets owned by News Corp, such as the Wall Street Journal, and Time Warner, such as Time. We find higher ratings for 20th Century Fox movies in News Corp. outlets compared to movies by other studios. To disentangle bias from correlation of taste, we introduce and validate a novel matching procedure using individual movie ratings from online platforms. Using this procedure, we find no evidence of bias in News Corp. nor Time Warner outlets. We reject even small effects, such as bias of one extra star (out of four) every thirteen movies. We test for differential bias when the return to bias is plausibly higher, examine bias by media outlet and by journalist, as well as editorial bias. We also consider bias by omission—whether media outlets are more likely to review highly-rated movies by affiliated studios—and conflict of interest within a movie aggregator. In none of these dimensions do we find evidence of bias. We relate to previous work and discuss three explanations for the lack of bias in our setting: high values of media reputation, organizational features in a conglomerate, and low returns to bias.

We show that most U.S. food, drugstore, and mass-merchandise chains charge nearly uniform prices across stores, despite wide variation in consumer demographics and competition. Demand estimates reveal substantial within-chain variation in price elasticities and suggest that the median chain sacrifices $16 million of annual profit relative to a benchmark of optimal prices. In contrast, differences in average prices between chains are broadly consistent with the optimal benchmark. We discuss a range of explanations for nearly uniform pricing, highlighting managerial inertia and brand image concerns as mechanisms frequently mentioned by industry participants. Relative to our optimal benchmark, uniform pricing may significantly increase the prices paid by poorer households relative to the rich, dampen the response of prices to local economic shocks, alter the analysis of mergers in antitrust, and shift the incidence of intranational trade costs.

Laboratory experiments in psychology find that media violence increases aggression in the short run. We analyze whether media violence affects violent crime in the field. We exploit variation in the violence of blockbuster movies from 1995 to 2004, and study the effect on same-day assaults. We find that violent crime decreases on days with larger theater audiences for violent movies. The effect is partly due to voluntary incapacitation: between 6 p.m. and 12 a.m., a one million increase in the audience for violent movies reduces violent crime by 1.1% to 1.3%. After exposure to the movie, between 12 a.m. and 6 a.m., violent crime is reduced by an even larger percent. This finding is explained by the self-selection of violent individuals into violent movie attendance, leading to a substitution away from more volatile activities. In particular, movie attendance appears to reduce alcohol consumption. The results emphasize that media exposure affects behavior not only via content, but also because it changes time spent in alternative activities. The substitution away from more dangerous activities in the field can explain the differences with the laboratory findings. Our estimates suggest that in the short run, violent movies deter almost 1,000 assaults on an average weekend. Although our design does not allow us to estimate long-run effects, we find no evidence of medium-run effects up to three weeks after initial exposure.

We study editorial decisions using anonymized submissions matched to citations at four leading economics journals. We develop a benchmark model in which editors maximize the expected quality of accepted papers and citations are unbiased measures of quality. We then generalize the model to allow different quality thresholds, systematic gaps between citations and quality, and a direct impact of publication on citations. We find that referee recommendations are strong predictors of citations and that editors follow these recommendations closely. We document two deviations from the benchmark model. First, papers by highly published authors receive more citations, conditional on the referees' recommendations and publication status. Second, recommendations of highly published referees are equally predictive of future citations, yet editors give their views significantly more weight.

We analyze how academic experts and nonexperts forecast the results of 15 piece-rate and behavioral treatments in a real-effort task. The average forecast of experts closely predicts the experimental results, with a strong wisdom-of-crowds effect: the average forecast outperforms 96 percent of individual forecasts. Citations, academic rank, field, and contextual experience do not correlate with accuracy. Experts as a group do better than nonexperts, but not if accuracy is defined as rank-ordering treatments. Measures of effort, confidence, and revealed ability are predictive of forecast accuracy to some extent and allow us to identify “superforecasters” among the nonexperts.

How do investors respond to predictable shifts in profitability? We consider how demographic shifts affect profits and returns across industries. Cohort size fluctuations produce forecastable demand changes for age-sensitive sectors, such as toys, bicycles, beer, life insurance, and nursing homes. These demand changes are predictable once a specific cohort is born. We use lagged consumption and demographic data to forecast future consumption demand growth induced by changes in age structure. We find that demand forecasts predict profitability by industry. Moreover, forecast demand changes five to ten years in the future predict annual industry stock returns. One additional percentage point of annualized demand growth due to demographics predicts a 5 to 10 percentage point increase in annual abnormal industry stock returns. However, forecasted demand changes over shorter horizons do not predict stock returns. A trading strategy exploiting demographic information earns an annualized risk-adjusted return of approximately 6 percent. We present a model of inattention to information about the distant future that is consistent with the findings. We also discuss alternative explanations, including omitted risk-based factors. (JEL E21, G12, G32, J11, L11, L25)