for their valuable feedback and suggestions. We owe special thanks to V.V. Chari, Ian Dew-Becker, Chad Jones, Marco Ortiz, and Alberto Trejos for their insightful conference discussions of our paper. Finally, this paper benefitted greatly from the constructive comments of colleagues and seminar participants at Columbia, the Federal Reserve Bank of Richmond, UCSD, USC, the Paris School of Economics, Ente Einaudi, and Cambridge University, as well as the helpful feedback of organizers and participants of the following conferences: the Chicago Booth Junior Finance Symposium, the Central Bank of Peru 30th Research Meeting of Economists, the 7th Annual NBER Conference on Macroeconomics Across Time and Space hosted by the Federal Reserve Bank of Philadelphia, the 2013 SED meetings, the 2013 NBER Summer Institute EFG Meeting, the 2014 AEA meetings, the Wisconsin School of Business 5th Annual Conference on Money, Banking and Asset Markets, the 2015 Tepper-LAEF Macro Finance Conference, and the 2016 LAEF Pecuniary Externalities Conference. We declare that we have no relevant financial nor material interests related to the research described in this paper. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.© 2016 by Saki Bigio and Jennifer La'O. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. ABSTRACTWe study how an economy's production structure determines the response of aggregate output and employment to sectoral financial shocks. In our framework, economic production is organized in an input-output network in which firms face financial constraints on their working capital. We show how sectoral financial shocks propagate through the network and manifest at the aggregate level through two channels: a fall in total factor productivity and an aggregate labor wedge distortion. The strength of each channel depends on the overall network architecture and the location of shocks. Finally, we calibrate our model to the U.S. input-output tables and use it to quantitatively assess the role of the network multiplier within the context of the recent Financial Crisis and the Great Recession.

Zha, and participants at various seminars and conferences for many useful comments. Jorge Mondragon provided excellent research assistance. We are grateful for financial support by the Fondation Banque de France, and the Smith Richardson Foundation. Bianchi acknowledges the support of the National Science Foundation under Award 1324395. Bigio thanks the Federal Reserve Bank of San Francisco for its hospitality. The views expressed herein are those of the authors and not necessarily those of the Federal Reserve Bank of Minneapolis, the Federal Reserve System, or the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

I present a model in which asymmetric information in the quality of capital endogenously determines the degree of liquidity in an economy. Liquidity is used to relax financial constraints that affect investment and employment decisions. I explain how liquidity is determined by the wedges induced by financial frictions and, in turn, how these wedges depend on liquidity.Unlike real business cycle theory, aggregate fluctuations can be attributed to both mean preserving spreads in the quality of capital and real shocks. Quantitatively, the model generates sizeable recessions similar in magnitude to the financial crisis of

Abstract How does an economy’s production structure determine its macroeconomic response to sectoral distortions? We study a static, multisector framework in which production is organized in an input-output network and production decisions are distorted. Sectoral distortions manifest at the aggregate level via two channels: total factor productivity (TFP) and the labor wedge. We show that near efficiency, distortions have zero first-order effects on TFP and nonzero first-order effects on the labor wedge, and that a sufficient statistic for the latter are the Domar weights. We thereby provide a Hulten-like theorem for the aggregate effects of sectoral distortions. A quantitative application of the model to the 2008–09 financial crisis suggests that the U.S. input-output structure amplified financial distortions by roughly a factor of two during the crisis.

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