Knowledge that Transforms

Default effects are pervasive, but the reason they arise is often unclear. We study optimal policy when the planner does not know whether an observed default effect reflects a welfare-relevant preference or a mistake. Within a broad class of models, we find that determining optimal policy is impossible without resolving this ambiguity. Depending on the resolution, optimal policy tends in opposite directions: either minimizing the number of nondefault choices or inducing active choice. We show how these considerations depend on whether active choosers make mistakes when selecting among nondefault options. We illustrate our results using data on pension contribution defaults.

This paper introduces a structural model for the coevolution of networks and behavior. We characterize the equilibrium of the underlying game and adopt the Bayesian Double Metropolis-Hastings algorithm to estimate the model. We further extend the model to incorporate unobserved heterogeneity and show that ignoring this heterogeneity can lead to biased estimates in simulation experiments. We apply the model to study R&D investment and collaboration decisions in the chemical and pharmaceutical industry and find a positive knowledge spillover effect. Our model also provides a tractable framework for a long-run key player analysis.

We evaluate a program that recruited local entrepreneurs to open and operate new schools in 200 underserved villages in Sindh, Pakistan. School operators received a per student subsidy to provide tuition-free primary education, and half the villages received a higher subsidy for females. The program increased enrollment by 32 percentage points and test scores by 0.63 standard deviations, with no difference across the two subsidy schemes. Estimating a structural model of the demand and supply for school inputs, we find that program schools selected inputs similar to those of a social planner who internalizes all the education benefits to society.

We evaluate electronic monitoring as an alternative to prison for nonviolent offenses. Leveraging plausibly exogenous variation in sentencing outcomes generated by quasi-random assignment of judges, we find electronic monitoring reduces reoffending at both extensive and intensive margins. Compared with prison, electronic monitoring is estimated to reduce the probability of reoffending by 22 percentage points five years after sentencing and by 11 percentage points ten years after sentencing, with the cumulative number of offenses reduced by 40% ten years after sentencing. These results demonstrate that electronic monitoring has sustained crime-reducing effects.

We investigate the effects of early-life medical treatments on the treated children and their families. We use a regression discontinuity design that exploits changes in medical treatments across the very low birth weight (VLBW) cutoff. Using administrative data from Denmark, we establish that VLBW children have better health and higher test scores. We find that these benefits spill over to other family members: mothers enjoy better mental health, and siblings have higher test scores. Maternal mental health improvements seem to be driven by better focal child health and sibling spillovers by improved interactions within the family and parental compensating behavior.

We examine two Pakistani programs to see if the public disclosure of tax information and social recognition of top taxpayers promotes tax compliance. Pakistan began revealing income tax paid by all taxpayers in 2012. Simultaneously, another program began recognizing and rewarding the top 100 tax- paying corporations, partnerships, self-employed individuals, and wage earners. We find that the public disclosure caused an increase of 9 log points and the social recognition program 17 log points in the tax payments of agents exposed to the program. Our results suggest that such programs can be important policy levers to mobilize additional resources.

This paper introduces forward-looking measures of the network connectedness of fears in the financial system arising due to the good and bad beliefs of market participants about uncertainty that spreads unequally across a network of banks. We argue that this asymmetric network structure extracted from call and put traded option prices of the main U.S. banks contains valuable information for predicting macroeconomic conditions and economic uncertainty, and it can serve as a tool for forward-looking systemic risk monitoring.

I leverage the staggered rollout of VAT in Pakistan to document the role of withholding mechanism in the self-enforcement of a VAT. Focusing on firms already in the tax net, I see how their outcomes respond when the tax is extended upward to intermediates used by them. I find that the upward extension of VAT, which triggers the withholding mechanism, causes an immediate and large (more than 40 log points) surge in sales reported by firms. The evolution of bunching above the zero-liability point and of input costs reported by firms suggests that this large response is indeed driven by the withholding mechanism. I also explore the role of withholding in the extensive margin compliance choices of firms.

This paper studies the link between self-image and behavior among those who face stigma due to poverty and social exclusion. Using a randomized field experiment with sex workers in Kolkata (India), we examine whether a psychological intervention to mitigate adverse effects of internalized stigma can induce behavior change. We find significant improvements in participants' self-image, their savings choices, and health clinic visits. Administrative data confirm that these changes in savings and preventive health behavior persist 15 and 21 months later, respectively. Our findings highlight the potential of purely psychological interventions to improve the life choices and outcomes of marginalized groups.

We study productivity differences in vertically integrated steel facilities using equipment-level information on inputs and output for each of the main stages in the value chain. We obtain stage-level productivity estimates by estimating a multistage production system and then integrate them into estimates for integrated facilities. At this level, we do not find statistically significant differences in productivity by ownership. This conceals important differences upstream and downstream in the value chain: private firms outperform in pig iron and steelmaking but lag in sintering. Inferior access to higher-quality raw materials and use of less automated technology are likely sources of these differences.