We develop a quantitative spatial equilibrium model with endogenous migration and remittance decisions within households to examine the joint effect of migration and remittances on economic development. We apply the model to internal migration in China. Counterfactual analysis of the calibrated model shows that the presence of remittances increases migration and welfare, reduces regional inequality and facilitates structural change. Compared to a conventional single-person migration model, our household model suggests a larger reduction in regional inequality and stronger reallocation of employment from agriculture to manufacturing and services in response to the decline in migration costs over the period of 2000 to 2010.

This paper investigates the economic costs of the recent United Nations sanctions on North Korea. Exploiting a novel data set on North Korean firms, we construct measures of regional exposure to export and intermediate input sanctions and show that trade sanctions cause sharp declines in local nighttime luminosity. Additional analysis of newly available product-level price data reveals that import sanctions led to significant increases in market prices. We then estimate a quantitative spatial equilibrium model using cross-region variations. The model implies that the sanctions reduced the country's manufacturing output by 12.9% and real income by 15.3%. We further quantify the potential impact of alternative sanction scenarios.

Using a long panel data set on Japanese firms, we find that firms make more precise forecasts and less autocorrelated forecast errors as they gain more experience. Then, we build a firm dynamics model where firms gradually learn about their demand by using a noisy signal. Using expectations data over time, we cleanly isolate the learning mechanism from other mechanisms and find that it accounts for 20% - 40% of the overall decline in forecast errors over the life cycle. Productivity gains from removing information frictions range from 3% to 12%, with firm entry and exit playing prominent roles.

Firms face substantial uncertainty when doing business in new markets. We propose that multinational firms use "cross-market learning" to resolve such uncertainties. We develop a model of firm-level expectations formation with noisy signals from multiple markets and derive predictions on market entries and expectations formation over the firm's life cycle. Using a novel dataset of Japanese multinational corporations that includes sales expectations of each affiliate, we provide supportive evidence for the model's predictions. We find that firms rely on their performance in nearby markets to predict their profitability in a new market and make entry decisions. Such "cross-market" learning is less important after the firm has accumulated experience in the new market, but becomes more important if the uncertainty of the focal market is high or the firm has received more signals from the nearby markets.

This paper develops a quantitative model of multinational production (MP) with non-neutral technologies incorporating two stylized facts observed in a global firm-level data: first, larger firms on average use more capital-intensive technologies; second, among firms producing in the same industry and country, those from more capital-abundant home countries use more capital-intensive technologies. I quantify the model using both firm-level and aggregate moments for 37 countries. I found that the reduction in MP costs accounts for 56% of the average decline in labor shares from 1996 to 2011, and the model also replicates a negative relationship between the change in a country's labor share and the change in the foreign affiliates' output share as observed in the data.

We build a general equilibrium model of endogenous communication, quality control and trade. We derive a structural gravity equation from the model and show that exogenous communication costs increase the probability of product failure and have a more negative impact on trade flows of products with a lower elasticity of substitution. In our empirical application, we focus on direct flight connectedness as a key determinant of communication costs and estimate its causal impact using the derived gravity equation. We overcome the identification challenge using an instrumental variable constructed based on the discontinuity of direct flights at around 6,000-mile distance due to air travel regulations. Moreover, we obtain novel data on international business lawsuits and provide direct evidence that air connectedness reduces the probability of product failure. We combine the empirical estimates and our equilibrium model to quantify the aggregate impact of air connectedness.

Many industries are dominated by large and very profitable firms. We develop a theory of firm dynamics, where competing firms operate a fixed-cost technology but due to customer inertia can only slowly build up a customer base. We show how the interaction between scale economies and customer inertia creates dynamic entry barriers and persistent performance differences. Our model also resolves the `paradox of entry barriers': markets with higher fixed operating costs have higher long-run profits, but are unambiguously less attractive to enter, except when firms can also invest in product quality. In the latter case, early entrants can create persistent performance differences through upgrading and may want to enter high-cost markets.

Using data on both buyer-supplier and owner-subsidiary links between Japanese firms, we characterize the interconnection between production and ownership networks. In the cross- section, we find that the majority of the owner-subsidiary links are also buyer-supplier links, highlighting the role of goods or services transactions in vertical relationships. In addition, we find that firms are more likely to use buyers/suppliers that are already adopted by related parties, suggesting an indirect benefit of integration.

We study an international business cycle model with a global input-output network that encompasses a large class of international business cycle models to quantify the "aggregation bias" in cross-country shock spillover resulting from using an aggregated one-sector model. We show analytically that international shock spillover in a multi-sector model and an aggregated one-sector counterpart are generally different, and only the same under special parameterizations such as when sectoral shocks are identical. Quantitatively, using data for 20 countries between 1990 and 2009, we find that aggregation bias varies over time and, on average, results in about 25\% lower international shock spillover, suggesting that an aggregate model tends to underestimate the role of foreign shocks in domestic economy.

We provide a statistical framework to study the impact of counterfactual retaliatory tariffs on the 2020 U.S. presidential election. Using reduced-form estimates similar to Lake and Nie (2023) and the institutional features of the U.S. election, we predict the national election outcome as a weighted average of the state-level outcomes. We formulate an "optimal tariff" problem in which a government chooses tariffs to achieve targeted electoral outcomes abroad while minimizing the trade-weighted tariff burden. We provide an analytical characterization of the solution to the problem and implement it using trade statistics before the trade war and the reduced-form estimates. We find that the optimal tariffs focus on different industries from the actual retaliatory tariffs. These tariffs can flip key swing states with significantly lower average tariff rates.