Research

Abstract: Industrial policies combine multiple instruments, yet existing research typically studies individual components or treats the bundle as a monolithic intervention. I examine complementarity in policy components of an agro-processing industrial policy, Operation Flood, the world’s largest dairy-development program implemented across Indian districts from 1970 to 1996. Digitizing the implementing agency’s annual reports, I construct a district-by-year map of farmer cooperatives and dairy-processing plants. The components’ staggered rollout generated some districts with one component and some with the bundle. Using matched stacked difference-in-differences, I find that village milk prices in bundle districts increase by 33% during the flush season. Neither arm alone shows any significant effect, and I reject additivity for prices at the 10% level. A stylized model explains this complementarity.  Cooperatives alone can saturate local markets, while plants alone cannot transmit the value of an additional outlet upstream. The bundle routes surplus milk to processing and passes value back to farmers. Turning to structural change, the industrial employment share increases by 1.7 percentage points in bundle districts, with no significant standalone effects. This increase comes mainly from non-food manufacturing, with suggestive evidence of input-output linkages. The results show that industrial policy design must account for how market failures interact and how gains are shared along the supply chain.

Abstract: Can temporary wartime mobilization change the long-run development trajectory of an economy? We study how mobilization for World War II in colonial India influenced its subsequent long-run economic development. From 1939 to 1945, the British colonial government purchased massive amounts of war materiel within India. We study long-run impacts on Indian structural transformation – the transition of employment from agriculture to the modern sectors (industry and services) – in Indian districts. Causal identification takes a shift-share approach, exploiting variation across industries in war-related government orders, and variation across districts in their pre-war industrial structure. Our analysis covers nine decades (1921-2011), and makes use of a wide array of newly digitized data. We find that World War II economic mobilization (procurement of war materiel) had a positive and significant impact on long-run structural transformation in Indian districts. More than six decades later, Indian districts that experienced higher demand for war materiel during the war experienced higher structural transformation from agriculture towards industry and services. We find substantial spillovers across economic sectors, particularly towards services sectors that were not directly subject to the initial World-War-II-related demand.

Abstract: How does being connected to a local elected leader affect property tax compliance? Using a close election difference-in-discontinuities design with novel administrative data from an Indian district, we examine whether citizens who share their surname with winning candidates face different tax liability and compliance outcomes. We find that surname-sharing citizens face 804 INR higher annual property tax assessments and pay 832 INR more. These effects are concentrated among wealthier property owners. Complementary household survey data reveal that citizens who report social connections with leaders receive more visits and enforcement from the Gram Panchayat office. They also believe they will receive help finding jobs, assistance with Gram Panchayat-related work, and better public goods maintenance when their connected leader is in office, suggesting reciprocal expectations play a role in increasing compliance.

Abstract: Can place-based policies generate spillovers beyond the places they target? We study this question in the context of India's 2005 Special Economic Zones Act. Using large language models, we reconstruct each zone's regulatory history over the last two decades. We assemble a dataset of exact zone boundaries and link it to India's 600,000 villages and geocoded addresses for 2.9 million firms. We compare locations near zones that become operational with those near zones that have not yet become operational. We find that operational zones generate substantial local activity. Sales rise by 35 percent for firms inside the zone and 6 percent for nearby firms, and these gains persist even after the tax holiday expires. In host villages, non-farm employment rises by 28 percent and the non-farm employment share by 4.3 percentage points over a ten-year period. Employment growth in host villages is concentrated in upstream industries supplying goods and services to firms inside the zones. Consistent with these demand linkages, new-firm entry near the zone shifts toward industries more exposed to demand from SEZ firms.

Abstract: This chapter surveys the implications of some studies in network economics research for economic development. We focus on information flow and risk-sharing—two topics where work in theory, empirics, and policy analysis have been especially intensive and complementary. In analysing information, we distinguish models of information diffusion and aggregation, highlight how different models imply very different guidance regarding the right way to seed information. In discussing risk-sharing, we look at the key frictions that impede efficient informal insurance, and some potential unintended consequences when policymakers intervene to help. Throughout, we stress practical insights that can be used with limited measurement of the details of networks

Abstract: This paper documents, using a newly-constructed data set, the evolution of the characteristics of employer-sponsored DC schemes. The features we focus on are their match schedules, vesting schedules, and the extent of ‘auto-features’ (i.e. presence of auto-enrollment, the level of any default contribution, and presence and details of auto-escalation). The data we construct is formed by hand-coding the details in narrative plan descriptions attached to plan filings. Our data covers approximately 5,000 plans, covering up to 37 million participants annually, for the period 2003-2017. We document that matching schedules, when they are offered, have become more generous over time. However, the proportion of firms offering a match fell sharply during the Great Recession and the proportion offering one did not recover to its pre-financial crisis level for almost a decade. Vesting schedules for DC plans have remained essentially unchanged since 2003, while the proportion of plans with auto-enrollment has increased dramatically over the same period. We find that the vast majority of plans that offer auto-enrollment have a default rate that is substantially lower than the level that would fully exploit the match offered by the employers.