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Many governments in developing countries have pursued policies targeting specific geographic areas over the past several decades. However, only a few have rigorously evaluated the causal impact of these interventions. This paper examines the effectiveness of a prominent place-based policy in India: the centrally sponsored New Industrial Policy for the state of Uttarakhand. Using georeferenced economic census data, the analysis applies a boundary discontinuity research design and zones in on the unique border between Uttarakhand and Uttar Pradesh, two states that were officially one before the implementation of the New Industrial Policy. The findings show that there was a significant and abrupt increase in employment at the town and village level when crossing the state border from Uttar Pradesh to Uttarakhand after the full implementation of the New Industrial Policy. The conclusion even holds for firms within the same sector. The increase is mainly due to larger firm sizes and expansions into new industries. A main component of the New Industrial Policy was excise tax incentives for certain industries. The paper finds that the increase in cross-border employment is higher for sectors receiving excise tax incentives than others. Additionally, exploring spillovers between industries, the paper shows that, controlling for the direct effects, the sectors with labor requirements similar to those receiving excise tax incentives also experience an increase in employment. Finally, the growth in the number of firms in Uttar Pradesh close to the border remained stable before and after the New Industrial Policy, which suggests the results are not fully driven by firms relocating from Uttar Pradesh to Uttarakhand.

Agglomeration Economies --- Boundary Discontinuity --- Coagglomeration --- Competitiveness and Competition Policy --- Employment --- Excise Tax --- Export Competitiveness --- Foreign Trade Promotion and Regulation --- Industrial Policy --- International Economics and Trade --- Macroeconomics and Economic Growth --- Private Sector Development --- Social Disparity --- Spatial Economics --- Tax Incentive --- Taxation and Subsidies --- Trade Facilitation

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This paper uses data on nearly half a million actual shipments from a trucking portal in India to provide evidence on how trucking costs depend on route characteristics and affect the intensive and extensive margins of shipment flows. The empirical analysis using pre-pandemic data (before March 24, 2020) confirms the presence of thick market externalities along a route and spillovers across routes due to network externalities, both of which confer advantages to origins and destinations with larger market sizes. The paper utilizes exogenous variations in value-added tax on gasoline across states to provide causal estimates of the elasticity of shipment flows with respect to trucking costs. The empirical estimates suggest that a 1 percent increase in trucking unit costs reduces trade flows by 2.8?3.9 percent. On the extensive margin of trade, three eastern states and several smaller territories constitute isolated regions that were largely cut off from the trading networks during the pre-pandemic period. Trucking costs increased by 32 percent during the early post-lockdown period (June 2020 to February 2021). The increase was greater along longer routes. In the short run, the increase in freight rates led to a proportionate decrease in trade flows across states. It pushed a significant number of poorer and remoter states into the ranks of isolated regions.

Freight and freightage --- Rates.

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The last expenditure survey released by India's National Sample Survey organization dates back to 2011, which is when India last released official estimates of poverty and inequality. This paper sheds light on how poverty and inequality have evolved since 2011 using a new household panel survey, the Consumer Pyramids Household Survey conducted by a private data company. The results show that: (1) extreme poverty is 12.3 percentage points lower in 2019 than in 2011, with greater poverty reductions in rural areas; (2) urban poverty rose by 2 percentage points in 2016 (coinciding with the demonetization event) and rural poverty reduction stalled by 2019 (coinciding with a slowdown in the economy); (3) poverty is estimated to be considerably higher than earlier projections based on consumption growth observed in national accounts; and (4) consumption inequality in India has moderated since 2011.

Poverty --- Household surveys. --- Consumption (Economics) --- Rural development. --- Surveys.