PhD Theses

Essays on production risk management in smallholder agriculture: an economic investigation with observational microdata

2026-08-22T22:00:39Z

Essays on production risk management in smallholder agriculture: an economic investigation with observational microdata Shukla, Sumedha; Arora, Gaurav (Advisor) This thesis presents applied microeconomic analyses pertaining to production risk management on small farms, with a focus on distributional aspects of farmer decision-making and farm productivity. In the first paper, I study the heterogeneous impact of agricultural credit on crop yield quantiles for households operating millet-based cropping systems. Equilibrium credit rationing under asymmetric information is the economic channel underlying heterogeneous credit-yield linkage. Therefore, I exploit within sample, quantile- based variation in credit-yield linkage to detect credit rationing incidence among sample households. Specifically, I propose a new metric for household-specific ex-ante odds of credit rationing, beyond identifying whether the average-household was rationed. I interpret these odds within a state contingent technology framework, which reveals how credit rationing influences farm-level adaptation under uncertainty. In the second paper, I employ a beta regression model in conjunction with a non linear instrumental variable approach, i.e., Beta- IV framework to estimate input-conditioned crop yield densities from plot-level observational data for wheat, rice, cotton and pigeonpea. The key inputs considered are nitrogen, phosphorus and irrigation levels. My work reveals novel evidence on how crop inputs influence production risk across major crops. I use these density estimates to evaluate the role of mixed-cropping to manage production risk among risk-averse, smallholder farmers in semi-arid India (Di Falco and Chavas 2006). My third paper is a data contribution to algorithmically reconcile identifier inconsistencies in land quality information in the Village Dynamics Studies in South Asia (VDSA)-plot-level panel dataset comprising 1,689 farm households across multiple survey waves during 1975-2014. My algorithm uses VDSA's plot nomenclature and phonetic/vernacular similarities to reduce data loss extent from 52% to <2%. In the fourth paper, I examine farmers’ subjective soil quality perceptions and assess how these perceptions diverge from data-based evidence. I construct and model a plot-level measure of soil quality misperception as the gap between survey-based soil quality metrics and corresponding data-based measures from high-resolution gridded maps. Further, I examine previously-unexplored two-way causal relations between soil misperceptions and input application decisions by using appropriate IVs for each directional relationship. Overall, my essays advance academic and policy research on smallholder agriculture in the global South.

Entanglements of infrastructure, resources, and community politics in Northeast India : a study of the Patkai Hills, Arunachal Pradesh

2026-06-15T12:15:03Z

Entanglements of infrastructure, resources, and community politics in Northeast India : a study of the Patkai Hills, Arunachal Pradesh Wangsu, Manta; Nair, Gayatri (Advisor) Based on the ethnography of the Tangsas conducted from July 2022 to September 2023, this study examines the operations of the informal coal industry in the Patkai Hills region of Arunachal Pradesh, involving multiple actors, including the community, the state, and non-state actors such as armed groups and external private players. It explores the interplay between the extractive process of the coal industry and road infrastructure, focusing on how the community is impacted by this and their perceptions of development. The study reveals the specific political, infrastructural, and economic conditions under which a formal coal industry transitioned to informal coal operations. In doing so, it interrogates what constitutes the region’s politics of regulations and deregulations within the larger political economy of development. The study also highlights the evolving socioeconomic dynamics within the Tangsa community, particularly in relation to changing landholding practices, ecological implications, livelihood crises, and widening intra-community inequality, among other issues that have been shaped by this shift. The findings of this study further indicate how participation in the region’s informal coal economy is primarily determined by distinct social locations within the community, political positions, and economic circumstances. Rather than viewing all the involved actors as homogeneously complicit, the study illuminates the ground realities where the larger sections of the Tangsa community remain excluded from equitable benefits despite their involvement in the extractive process, while influential local elites secure disproportionate profits. The study situates this phenomenon within the region's broader context of development interventions and resource politics, demonstrating how informal coal mining manifests as extractivism, driven by the penetration of external capital and changing internal social dynamics among the Tangsas. Ultimately, it explores the relationships between an emerging ecological crisis and widening intra-community inequalities among the Tangsas stemming from the informal coal operations in the Kharsang area of the Patkai Hills region.

Groundwater level dynamics and agricultural land-use change : econometric issues and strategies

2024-01-19T22:00:16Z

Groundwater level dynamics and agricultural land-use change : econometric issues and strategies Ali, Saif; Arora, Gaurav (Advisor) A significant body of literature has pointed to a causal relationship between agricultural irrigation and groundwater depletion in India. Despite these allusions, I know of no rig- orous estimation of the causal impact of cropland water demand on groundwater level change. This gap in research could be due to data availability/quality issues as well as the methodological challenge of identifying the underlying mechanisms that drive change in groundwater dynamics. In order to reconcile these challenges, I construct a unique dataset integrating satellite data products with administrative data including variables that account for climatic, hydrologic, geologic and socio-economic factors. I study three specific issues related to the identification of groundwater depletion mech- anisms. First, I detect systematic or non-random missingness in administrative ground- water data due to the occurrence of “dry wells”. Dry wells signify extensive depletion such that groundwater falls below the maximum depth of monitoring wells. Naive omission of dry wells can lead to severe false optimism about regional groundwater situations. I employ a set of ‘observable’ covariates of groundwater to predict the in- cidence of dry wells in an unlabelled dataset. I then utilize the prediction probabilities to quantify the statistical bias due to non-random missingness in conditional ground- water estimation models. Second, I consider the obstacles in statistical inference that arise from the fact that groundwater aquifers represent a non-exclusive common pool resource whereby the costs and benefits of resource use are shared by spatially proxi- mate users. I employ a statistical tool known as the semivariogram to estimate spatial autocorrelation in groundwater levels. Such estimation provides empirical evidence for delineating the spatial boundaries for resource sharing within a groundwater aquifer. I then assess the impact of the spatial aquifer structure for economic policy and ground- water management science. Finally, I develop a framework for assessing the causal impact of agricultural land-use intensification on groundwater depletion founded on a structural model that is derived from a groundwater balance equation. The identification strategy relies on a 2-stage least squares approach instrumented with spatially varying, crop-specific minimum support price (MSP) which lead to differential incentives for al- locating farm acres across multiple crops and hence groundwater extraction outcomes. This work advances the study of the causal relationship between groundwater irrigation and depletion by addressing three oft-ignored econometric issues that arise in such a study. Overall, my essays bear relevance for groundwater management and policy mak-ing as well as academic research where accurate and efficient estimation of statistical moments of groundwater levels is of paramount importance.