Virtually all theories of economic growth predict a positive relationship between population size and productivity. In this paper, I study a particular historical episode to provide direct evidence for the empirical relevance of such scale effects. In the af- termath of the Second World War, 8 million ethnic Germans were expelled from their domiciles in Eastern Europe and transferred to West Germany. This inflow increased the German population by almost 20%. Using variation across counties, I show that the settlement of refugees had large and persistent effects on the size of the local popula- tion, manufacturing employment, and income per capita. These findings are quantita- tively consistent with an idea-based model of spatial growth if population mobility is subject to frictions and productivity spillovers occur locally. The estimated model im- plies that the refugee settlement increased aggregate income per capita by about 12% after 25 years and triggered a process of industrialization in rural areas.
To counteract the adverse effects of shocks, such as the global pandemic, on the economy, governments have discussed policies to improve the resilience of supply chains by reducing dependence on foreign suppliers. In this paper, we develop and quantify an adaptive production network model to study network resilience and the consequences of reshoring of supply chains. In our model, firms exit due to exogenous shocks or the propagation of shocks through the network, while firms can replace suppliers they have lost due to exit subject to switching costs and search frictions. Applying our model to a large international firm-level production network dataset, we find that restricting buyer–supplier links via reshoring policies reduces output and increases volatility and that volatility can be amplified through network adaptivity.
We construct an endogenous growth model with random interactions where firms are subject to distortions. The TFP distribution evolves endogenously as firms seek to upgrade their technology over time either by innovating or by imitating other firms. We use the model to quantify the effects of misallocation on TFP growth in emerging economies. We structurally estimate the stationary state of the dynamic model targeting moments of the empirical distribution of R&D and TFP growth in China during the period 2007–2012. The estimated model fits the Chinese data well. We compare the estimates with those obtained using data for Taiwan and perform counterfactuals to study the effect of alternative policies. R&D misallocation has a large effect on TFP growth.
The integration of markets may improve efficiency by lowering costs or reducing local market power. India, seeking to reduce electricity shortages, set up a new power market, in which transmission constraints sharply limit trade between regions. During congested hours, measures of market competitiveness fall and firms raise bid prices. I use confidential bidding data to estimate the costs of power supply and simulate market outcomes with more transmission capacity. Counterfactual simulations show that transmission expansion increases market surplus by 22 percent, enough to justify the investment. One-third of this gain is due to sellers' response to a more integrated grid.
African agricultural markets are characterized by low farmer revenues and high consumer food prices. Many have worried that this wedge is partially driven by imperfect competition among intermediaries. This paper provides experimental evidence from Kenya on intermediary market structure. Randomized cost shocks and demand subsidies are used to identify a structural model of market competition. Estimates reveal that traders act consistently with joint profit maximization and earn median markups of 39 percent. Exogenously induced firm entry has negligible effects on prices, and low take-up of subsidized entry offers implies large fixed costs. We estimate that traders capture 82 percent of total surplus.
We find that three factors – cryptocurrency market, size, and momentum – capture the cross-sectional expected cryptocurrency returns. We consider a comprehensive list of price- and market-related return predictors in the stock market, and construct their cryptocurrency counterparts. Ten cryptocurrency characteristics form successful long-short strategies that generate sizable and statistically significant excess returns, and we show that all of these strategies are accounted for by the cryptocurrency three-factor model. Lastly, we examine potential underlying mechanisms of the cryptocurrency size and momentum effects.