We characterize how firms structure supply chains under climate risk. Using new data on the universe of firm-to-firm transactions from an Indian state, we show that firms diversify sourcing locations, and that suppliers exposed to climate risk charge lower prices. Our event-study analysis shows firms with suppliers in flood-affected districts experience a temporary decline in inputs, followed by a return to original levels. We develop a general equilibrium spatial model of firm input sourcing under climate risk. Firms diversify identical inputs from suppliers across space, trading off the probability of a climate disruption against higher input costs. We quantify the model using data on 271 Indian regions, showing real wages vary across space and are correlated with geography and productivity. Wages are inversely correlated with sourcing risk, giving rise to a cost minimization-resilience tradeoff. Supply chain diversification unambiguously reduces real wage volatility, but ambiguously affects their levels, as diversification may come with higher input costs. While diversification helps mitigate climate risk, it exacerbates the distributional effects of climate change by reducing wages in regions prone to more frequent shocks.

Neighborhoods are strong determinants of both economic opportunity and criminal activity. Does improving connectedness between segregated and unequal parts of a city predominantly import opportunity or export crime. We use a spatial general equilibrium framework to model individual decisions of where to work and whether to engage in criminal activity, with spillovers across the criminal and legitimate sectors. We match at the individual level various sources of administrative records from Medellin, Colombia, to construct a novel, granular dataset recording the origin and destination of both workers and criminals. We leverage the rollout of a cable car system to identify key parameters of the model, informing how changes in transportation costs causally affect the location and sector choices of workers and criminals. Our counterfactual exercises indicate that, when improving the connectedness of almost any neighborhood, overall criminal activity in the city is reduced, and total welfare is improved.

Neighborhoods are strong determinants of both economic opportunity and criminal activity. Does improving connectedness between segregated and unequal parts of a city predominantly import opportunity or export crime. We use a spatial general equilibrium framework to model individual decisions of where to work and whether to engage in criminal activity, with spillovers across the criminal and legitimate sectors. We match at the individual level various sources of administrative records from Medellin, Colombia, to construct a novel, granular dataset recording the origin and destination of both workers and criminals. We leverage the rollout of a cable car system to identify key parameters of the model, informing how changes in transportation costs causally affect the location and sector choices of workers and criminals. Our counterfactual exercises indicate that, when improving the connectedness of almost any neighborhood, overall criminal activity in the city is reduced, and total welfare is improved.

Emerging economies often feature low-quality institutions, generating micro-level trade frictions. In these settings, firms may rely on cultural-proximity-based informal institutions to overcome such frictions. We quantify the aggregate effects of cultural proximity in a production network. Using new microdata on firm-to-firm trade from India with information on prices, transactions, and caste and religious connections, we find that higher cultural proximity reduces prices and fosters trade at intensive and extensive margins. Our evidence suggests these results are driven by firms trying to overcome frictions imposed by low-quality institutions. Guided by these facts, we propose a quantitative firm-level production network model, where cultural proximity and institutional quality influence trade and matching costs. Our counterfactual exercises indicate that an economy composed of culturally closer firms features lower costs, lower prices, higher sales and higher welfare with respect to an economy with culturally distant firms.

We provide one of the first estimates of elasticities of substitution across suppliers within the same product. We estimate these elasticities by using new real-time administrative tax data on product-level prices and quantities with firm-to-firm transactions, and leveraging the geographic and temporal variation from the Covid-19 lockdowns in India. Suppliers are highly complementary even at this granular level, with an estimated elasticity of 0.55, thus amplifying negative shocks by transmitting them through the supply chain. We quantify this transmission and show that under our estimated elasticities, the overall fall in output is substantial and widespread. In policy counterfactuals, we quantify the importance of firm connectivity separately from firm size, and of targeting aid to connected firms. Protecting more connected firms mitigates output declines non-linearly with the size of the productivity shock.

We show that shared identity with elected leaders helps entrepreneurs form new and productive businesses. Following close Indian elections during 2006 −16, local firm entry by entrepreneurs belonging to the same cultural groups as winning candidates increases. Despite benefitting from preferential behavior, and in contrast to earlier work, such politically connected entrants are more productive than incumbent in-group firms. Simultaneously, business formation by out-group entrepreneurs does not decline. The high TFP of in-group entrants suggests barriers that previously precluded the entry of potentially high-performing firms. Administrative entry costs seem to be a key barrier that in-group politicians help ease.

This paper studies the role of customer and supplier acquisition in shaping firm dynamics and aggregate productivity. Using transaction-level data from a large Indian state, we document lifecycle patterns of customer and supplier networks. We find that younger firms have fewer customers and suppliers, lower sales and intermediate expenditures, and higher output prices and input costs. Motivated by these patterns, we develop a model of endogenous network formation where heterogenous firms undertake costly acquisition of customers and suppliers over the lifecycle. We study the normative properties of the model and find that the decentralized equilibrium is inefficient due to vertical and search externalities. Inefficient pricing and acquisition choices lead to quantitatively large aggregate productivity losses. We use the model to study how differences in acquisition technology map to productivity differences. We find that improvements in acquisition technology can generate sizable productivity gains, and that improvements in allocative efficiency are central for delivering these gains.