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<link>http://repository.iiitd.edu.in/xmlui/handle/123456789/1374</link>
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<pubDate>Mon, 13 Apr 2026 09:33:32 GMT</pubDate>
<dc:date>2026-04-13T09:33:32Z</dc:date>
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<title>Entanglements of infrastructure, resources, and community politics in northeast India : a study of the Patkai Hills, Arunachal Pradesh</title>
<link>http://repository.iiitd.edu.in/xmlui/handle/123456789/1867</link>
<description>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.
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<pubDate>Wed, 01 Apr 2026 00:00:00 GMT</pubDate>
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<dc:date>2026-04-01T00:00:00Z</dc:date>
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<title>Groundwater level dynamics and agricultural land-use change : econometric issues and strategies</title>
<link>http://repository.iiitd.edu.in/xmlui/handle/123456789/1376</link>
<description>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.
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<pubDate>Sun, 17 Dec 2023 00:00:00 GMT</pubDate>
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<dc:date>2023-12-17T00:00:00Z</dc:date>
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