Can increasing the number of politicians in village councils affect access to justice? Re-election incentives make politicians facilitate access to justice as a form of 'constituency service'—a larger council size makes additional human resources of greater diversity and ability available to provide such services. I examine village councils (Gram Panchayats) in India and test whether adding additional elected members to councils facilitates their constituents' access to the formal legal system. I do so by leveraging population-based cutoffs and creating an original dataset on court cases filed by litigants from over 40,000 villages over 8 years in one of the largest Indian states. I find that citizens who live in village councils with additional members file a larger number of cases in courts, driven by an increase in registered crime. An important driver of the increased capacity is achieved through better political selection—larger councils increase the representation of marginalized groups, allowing for a more diverse group of constituents to approach council members for assistance. By highlighting the key role played by council members, I deepen our understanding of how citizens in developing countries access the formal legal system.

Do shorter terms worsens legislative performance of indirectly elected members? Shorter terms can cause elected members to shirk on their legislative responsibilities due to a realignment of priorities, and worsen legislative performance. In this paper, we argue that a higher quality of elected representatives can overcome negative incentives created by shorter terms. However, once members are no longer of a higher quality, negative incentives like shorter terms can worsen their performance. We leverage two historical natural experiments in the the indirectly elected Rajya Sabha of the Indian Parliament to test our theoretical propositions. Using detailed data from parliamentary records, we show that shorter terms do not worsen the legislative performance of positively selected members – those with higher intrinsic qualities – however, it worsens performance of members who are not positively selected. In doing so, we contribute to the literatures on term lengths, legislative performance and institutional design.

This paper evaluates the effect of unfunded legal reforms on judicial productivity. I use data and evidence from one of India’s largest state that prohibited the manufacture, consumption and sale of alcohol and charged violators with criminal penalties - having large effects on the criminal justice system. To evaluate the effect of the legal reform on the judicial system, I use micro-level data on court cases and measures of judicial productivity to provide evidence on how the unfunded mandate hampered judicial productivity. I leverage a difference-in-differences analysis using a neighboring state as a control group due to shared geography and historical institutions. I find that the alcohol ban increased the demands on the justice system, decreased its efficacy and had no effect on its efficiency. I evaluate and rule out alternate explanations pertaining to judicial capacity, scheduling and priority changes.

In many parts of the world, judges are transferred frequently and based on political considerations. Judge transfers reduce court productivity and impede the speedy resolution of court cases. We test these propositions using big data from the courts of first instance in Uttar Pradesh, India’s largest state, and credible research designs. The data confirm that judge transfersareindeedfrequentandpoliticized: theyoccurapproximatelyonceevery10months, both due to and to limit political interference. Transfers reduce court productivity, and make it less likely that cases are decided in a time-bound manner. These outcomes obtain because transfers cause temporary judge vacancies, and since portions of cases that experience judge transfers need to be reheard. This paper documents a major, unappreciated cause of judicial delays and demonstrates how seemingly mundane judge staffing decisions are politicized and can havemajor welfare implications.

Understanding treatment effect heterogeneity is important, but many standard approaches to estimate heterogeneous treatment effects rely on strong assumptions. We present a novel approach to estimate heterogeneous treatment effects in a variety of experimental and observational set-ups commonly used in economics and political science such as multi-arm RCTs and difference-in-differences designs. We set up the estimation and inference problem in the form of a linear varying coefficient model and use Bayesian Additive Regression Trees (BART) to estimate the coefficients. We demonstrate how the approach can be leveraged to understand heterogeneity in multi-arm experiments and difference-in-differences designs. Our approach makes no parametric assumptions about the treatment effect function and estimates it using a flexible regression tree ensemble. We illustrate the benefits of using the approach to estimate heterogeneous treatment effects for studies across various sub-fields of political science. In doing so, our study adds to the growing literature on using flexible machine-learning methods for causal inference.

Does declaration of the public health emergency matter for reporting of COVID-19 deaths, and does this vary by the death reporting system in place at the county level? While the COVID-19 public health emergency was active, deaths due to COVID-19 were required to be investigated in some states. However, the declaration ended this requirement. We combine county-level restricted data on COVID-19 mortality and jurisdictional information on medico-legal systems that determined whether deaths required to be investigated by the medico-legal investigating officers (typically, coroners or medical examiners). Our findings suggest that the declaration that ended the public health emergency reduced the number of deaths reported whose main cause of death was attributed to COVID-19. We also find that the decrease in death reporting is mainly in counties which have medical examiners, suggesting that the type and manner of death investigation carried out by different medico-legal officers influenced the COVID-19 mortality statistics.