[ Online Appendix ], First Draft: October 2018, This Version: August 2020
This paper studies the role of endogenous trade-credit linkages for the propagation of shocks in a multisector model where firms finance production using bank and trade credit. I build a model in which the adjustment in the volume and cost of trade credit introduces interdependent distortions and captures two counteracting mechanisms: (1) Firms smooth shocks by substituting bank and trade credit. (2) An increase in the cost of trade credit amplifies financial shocks by tightening the financing condition of customers. In a quantitative application of the model to the US economy during the 2008-2009 crisis, I simulate the model using financial shocks only and show that: (1) Trade-credit linkages generate large spillovers relative to an economy with bank finance only; (2) The smoothing mechanism was operative, though small; (3) Sectors extending relatively more trade credit to customers than their volume of bank loans are systemically important and generate large spillovers.
Work in Progress
Financial Frictions and Regional Comovement in the US.
An extensive literature has documented the evolution of comovement of economic activity across countries over time. The importance of bilateral trade as a driver of business cycle synchronization has been highlighted repeatedly. However, the failure of quantitative models to capture the comovement observed in trade data has been dubbed the “trade-comovement puzzle”. Against the back-drop of the quantitative importance of trade credit – the BIS estimates that two thirds of world trade is supported by inter-firm credit – I investigate the ability of an international multisector general equilibrium model with both trade and financial linkages within and across regions to generate comovement patterns and magnitudes as observed in the data.
Networked Forecasts: Theory and Evidence (with Vasco Carvalho)
In this paper, we show that information on the structure of the production network of an economy can help to: (a) produce better forecasts of both sector-level and aggregate growth rates and, (b) quantify the influence of particular sectors on both disaggregate and aggregate forecasts. In the first part of this paper, we offer three theoretical contributions: We show that (1) a small number of key sectors drive the long-run forecasts of all production activities in the economy and (2) the short-run dynamics and persistence of disaggregate forecasts depend on a property of the network of links across production units. (3) We study how knowledge of the underlying network can lead to efficiency gains in aggregate forecasting. In the second part, we compare the aggregate predictive ability of multisector growth models to a set of econometric models and quantify the influence of particular sectors on both disaggregate and aggregate forecasts based on the theoretical results derived in this paper.