We estimate a model of importers in Hungarian micro data and conduct counterfactual analysis to investigate the effect of imported inputs on productivity. We find that importing all input varieties would increase a firm's revenue productivity by 22 percent, about half of which is due to imperfect substitution between foreign and domestic inputs. Foreign firms use imports more effectively and pay lower fixed import costs. We attribute a quarter of Hungarian productivity growth during 1993-2002 to imported inputs. Simulations show that the productivity gain from a tariff cut is larger when the economy has many importers and many foreign firms. JEL: F12,F14 Keywords: imports, intermediate inputs, firm productivityUnderstanding the link between international trade and aggregate productivity is one of the major challenges in international economics. To learn more about this link at the microeconomic level, a recent literature explores the effect of imported inputs-which constitute the majority of world trade-on firm productivity. Studies show that improved access to foreign inputs has increased firm productivity in several countries, including Indonesia (Mary Amiti Jozef Konings 2007), Chile (Hiroyuki Kasahara Joel Rodrigue 2008) and India (Petia Topalova Amit Khandelwal 2011). 1 A next step in this research agenda is to investigate the underlying mechanism through which imports increase productivity. As Juan Carlos Hallak James A Levinsohn (2008) emphasize, understanding which firms gain most, through what channel, and how the effect depends on the economic environment, are important for evaluating the welfare and redistributive implications of trade policies.To explore these questions, we estimate a structural model of importer firms

Why is GDP growth so much more volatile in poor countries than in rich ones? We identify four possible reasons: (i) poor countries specialize in more volatile sectors; (ii) poor countries specialize in fewer sectors; (iii) poor countries experience more frequent and more severe aggregate shocks (e.g. from macroeconomic policy); and (iv) poor countries' macroeconomic fluctuations are more highly correlated with the shocks of the sectors they specialize in. We show how to decompose volatility into these four sources, quantify their contribution to aggregate volatility, and study how they relate to the stage of development. We document the following regularities. First, as countries develop, their productive structure moves from more volatile to less volatile sectors. Second, the level of specialization declines with development at early stages, and slowly increases at later stages of development. Third, the volatility of country-specific macroeconomic shocks falls with development. Fourth, the covariance between sector-specific and country-specific shocks does not vary systematically with the level of development. We argue that many theories linking volatility and development are not consistent with these findings and suggest new directions for future theoretical work.

Social distancing interventions can be effective against epidemics but are potentially detrimental for the economy. Businesses that rely heavily on face-to-face communication or close physical proximity when producing a product or providing a service are particularly vulnerable. There is, however, no systematic evidence about the role of human interactions across different lines of business and about which will be the most limited by social distancing. Here we provide theory-based measures of the reliance of U.S. businesses on human interaction, detailed by industry and geographic location. We find that, before the pandemic hit, 43 million workers worked in occupations that rely heavily on face-to-face communication or require close physical proximity to other workers. Many of these workers lost their jobs since. Consistently with our model, employment losses have been largest in sectors that rely heavily on customer contact and where these contacts dropped the most: retail, hotels and restaurants, arts and entertainment and schools. Our results can help quantify the economic costs of social distancing.

Many of the facts about the extensive margin of trade—which firms export, and how many products are sent to how many destinations— are consistent with a surprisingly large class of trade models because of the sparse nature of trade data. We propose a statistical model to account for sparsity, formalizing the assignment of trade shipments to country, product, and firm categories as balls falling into bins. The balls-and-bins model quantitatively reproduces the pattern of zero product- and firm-level trade flows across export destinations, and the frequency of multiproduct, multidestination exporters. In contrast, balls-and-bins overpredicts the fraction of exporting firms. ( JEL F11, F14)