Econometrica最新文献

Most empirical work in economics has considered only a narrow set of measures as meaningful and useful to characterize individual behavior, a restriction justified by the difficulties in collecting a wider set. However, this approach often forces the use of strong assumptions to estimate the parameters that inform individual behavior and identify causal links. In this paper, we argue that a more flexible and broader approach to measurement could be extremely useful and allow the estimation of richer and more realistic models that rest on weaker identifying assumptions. We argue that the design of measurement tools should interact with, and depend on, the models economists use. Measurement is not a substitute for rigorous theory, it is an important complement to it, and should be developed in parallel to it. We illustrate these arguments with a model of parental behavior estimated on pilot data that combines conventional measures with novel ones.

Annually, work-related mortality is responsible for 5–7% of all global deaths, and at least 1-in-9 workers experience nonfatal occupational accidents (ILO (2019a,b)). Occupational Safety and Health (OSH) committees are considered the key worker voice institution through which to improve workplace safety and health (ILO (1981)). I present evidence of OSH committees' causal effects on workers and on factories. To do so, I collaborated with 29 multinational apparel buyers that committed to enforce a local mandate for OSH committees on their suppliers in Bangladesh. With the buyers, I implemented a nearly year-long field experiment with 84 supplier factories, randomly enforcing the mandate on half. The buyers' intervention increased compliance with the OSH committee law. Exploiting the experimental variation in OSH committees' strength, I find that stronger OSH committees had small, positive effects on objective measures of safety. These improvements did not come at a cost to workers in terms of wages or employment or to factories in terms of labor productivity. The effects on compliance, safety, and voice were largest for factories with better managerial practices. Factories with worse practices did not improve, and workers in these factories reported lower job satisfaction; this finding suggests complementarity between external enforcement and internal capacity in determining the efficacy of regulation.

The expectation is an example of a descriptive statistic that is monotone with respect to stochastic dominance, and additive for sums of independent random variables. We provide a complete characterization of such statistics, and explore a number of applications to models of individual and group decision-making. These include a representation of stationary monotone time preferences, extending the work of Fishburn and Rubinstein (1982) to time lotteries. This extension offers a new perspective on risk attitudes toward time, as well as on the aggregation of multiple discount factors. We also offer a novel class of non-expected utility preferences over gambles which satisfy invariance to background risk as well as betweenness, but are versatile enough to capture mixed risk attitudes.

Developing country megacities suffer from severe road traffic congestion, yet the level of congestion is not a direct measure of equilibrium inefficiency. I study the peak-hour traffic congestion equilibrium in Bangalore. To measure travel preferences, I use a model of departure time choice to design a field experiment with congestion pricing policies and implement it using precise GPS data. Commuter responses in the experiment reveal moderate schedule inflexibility and a high value of time. I then show that in Bangalore, traffic density has a moderate and linear impact on travel delay. My policy simulations with endogenous congestion indicate that optimal congestion charges would lead to a small reduction in travel times, and small commuter welfare gains. This result is driven primarily by the shape of the congestion externality. Overall, these results suggest limited commuter welfare benefits from peak-spreading traffic policies in cities like Bangalore.

We investigate optimal project management in a setting plagued by an indefinite number of setbacks that are discovered en route to project completion. The contractor can cover up delays in progress due to shirking either by making false claims of setbacks or by postponing the reports of real ones. The sponsor optimally induces work and honest reporting via a soft deadline and a reward for completion that specifies a bonus for early delivery. Late-stage setbacks trigger randomization between minimally feasible project extension and (inefficient) cancellation. Because extensions may be granted repeatedly, arbitrarily large overruns in schedule and budget are possible after which the project may still be canceled.

In markets with complicated products, individuals may choose how much time and effort to spend understanding and comparing alternatives. Focusing on insurance choice, we find evidence consistent with individuals acquiring more information when there are larger consequences from making an uninformed choice. Building on the rational inattention literature, we develop and estimate a parsimonious demand model in which individuals choose how much to research difficult-to-observe characteristics. We use our estimates to evaluate policies that simplify choice. Reducing the number of plans can raise welfare through improved choice as well as savings in information costs. Capping out-of-pocket costs generates larger welfare gains than standard models. The empirical model can be applied to other settings to examine the regulation of complex products.