Person:

Mullainathan, Sendhil

In this paper, we provide a new framework for analyzing corruption in public bureaucracies. The standard way to model corruption is as an example of moral hazard, which then leads to a focus on better monitoring and stricter penalties with the eradication of corruption as the final goal. We propose an alternative approach which emphasizes why corruption arises in the first place. Corruption is modeled as a consequence of the interaction between the underlying task being performed by bureaucrat, the bureaucrat's private incentives and what the principal can observe and control. This allows us to study not just corruption but also other distortions that arise simultaneously with corruption, such as red-tape and ultimately, the quality and efficiency of the public services provided, and how these outcomes vary depending on the specific features of this task. We then review the growing empirical literature on corruption through this perspective and provide guidance for future empirical research.

Labor market policies succeed or fail at least in part depending on how well they reflect or account for behavioral responses. Insights from behavioral economics, which allow for realistic deviations from standard economic assumptions about behavior, have consequences for the design and functioning of labor market policies. We review key implications of behavioral economics related to procrastination, difficulties in dealing with complexity, and potentially biased labor market expectations for the design of selected labor market policies including unemployment compensation, employment services and job search assistance, and job training.

Much of our understanding of corporations builds on the idea that managers, when they are not closely monitored, will pursue goals that are not in shareholders’ interests. But what goals would managers pursue? This paper uses variation in corporate governance generated by state adoption of antitakeover laws to empirically map out managerial preferences. We use plant‐level data and exploit a unique feature of corporate law that allows us to deal with possible biases associated with the timing of the laws. We find that when managers are insulated from takeovers, worker wages (especially those of white‐collar workers) rise. The destruction of old plants falls, but the creation of new plants also falls. Finally, overall productivity and profitability decline in response to these laws. Our results suggest that active empire building may not be the norm and that managers may instead prefer to enjoy the quiet life.

We present a model of uninformative persuasion in which individuals “think coarsely”: they group situations into categories and apply the same model of inference to all situations within a category. Coarse thinking exhibits two features that persuaders take advantage of: (i) transference, whereby individuals transfer the informational content of a given message from situations in a category where it is useful to those where it is not, and (ii) framing, whereby objectively useless information influences individuals' choice of category. The model sheds light on uninformative advertising and product branding, as well as on some otherwise anomalous evidence on mutual fund advertising.

This article considers several aspects of the economic decision making of the poor from the perspective of behavioral economics, and it focuses on potential contributions from marketing. Among other things, the authors consider some relevant facets of the social and institutional environments in which the poor interact, and they review some behavioral patterns that are likely to arise in these contexts. A behaviorally more informed perspective can help make sense of what might otherwise be considered “puzzles” in the economic comportment of the poor. A behavioral analysis suggests that substantial welfare changes could result from relatively minor policy interventions, and insightful marketing may provide much needed help in the design of such interventions.

We investigate the market for news under two assumptions: that readers hold beliefs which they like to see confirmed, and that newspapers can slant stories toward these beliefs. We show that, on the topics where readers share common beliefs, one should not expect accuracy even from competitive media: competition results in lower prices, but common slanting toward reader biases. On topics where reader beliefs diverge (such as politically divisive issues), however, newspapers segment the market and slant toward extreme positions. Yet in the aggregate, a reader with access to all news sources could get an unbiased perspective. Generally speaking, reader heterogeneity is more important for accuracy in media than competition per se.

Economists have become increasingly interested in studying the nature of production functions in social policy applications, with the goal of improving productivity. Traditionally models have assumed workers are homogenous inputs. However, in practice, substantial variability in productivity means the marginal productivity of labor depends substantially on which new workers are hired—which requires not an estimate of a causal effect, but rather a prediction. We demonstrate that there can be large social welfare gains from using machine learning tools to predict worker productivity, using data from two important applications—police hiring and teacher tenure decisions.

Economists have long been interested in the idea that there is a direct circular relation between poverty and low productivity, and not just one that is mediated by market failures, usually in asset markets. The nutrition-based efficiency wage model (Partha Dasgupta and Debraj Ray, 1987) is the canonical example of models where this happens: However it has been variously suggested (see for example T. N. Srinivasan, 1994) that the link from nutrition to productivity and especially the link from productivity to nutrition is too weak to be any more than a small part of the story. Partha Dasgupta himself acknowledges this when he writes "nutrition-productivity construct provides a metaphor,..., for ... an economic environment harboring poverty traps" (Partha Dasgupta, 1997, page 5). We propose an alternative approach to this question based on the idea that attention is a scarce resource that is important for productivity. Specifically, people may not be able to fully attend to their jobs if they are also worrying about problems at home and being distracted in this way reduces productivity. But not paying attention at home is also costly: early symptoms of a child's sickness may go unnoticed; water may run out at the end of the day; kerosene for lighting lamps at home might run out and make it hard to do homework; etc. Finally, the extent to which home life distracts depends on the nature of home life. Specifically, certain goods (e.g. a good baby sitter, a 24-hour piped water supply, a connection to a power supply grid) can reduce the extent of home life distraction. These three assumptions generate an interesting relation between income and productivity that is at the core of our model. The non-poor in this model, by virtue of owning distraction-saving goods and services at home, are able to focus more on their work. Hence they will be more productive at work and will be able to afford more distraction-saving goods. This simple two-way relationship between income and productivity produces a discontinuity in the relation between human capital and earnings which is certain cases can lead to a poverty trap, even in the absence of any market failures.