The Origins of Aggregate Fluctuations in a Credit Network Economy

Altinoglu, Engin Levent

doi:10.17016/feds.2018.031

Cited by 14 publications

(8 citation statements)

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“…In their models, intermediate good trade is financed by supplier trade credit. Thus, by adding direct credit linkages, Altinoglu (2016) and Luo (2016) generate further predictions regarding the correlation structure of sectoral output and the propagation of shocks.…”

Section: Resultsmentioning

confidence: 99%

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Distortions in Production Networks

Bigio¹,

La’O²

2016

129

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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 They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.© 2016 by Saki Bigio and Jennifer La'O. All rights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.

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Section: Resultsmentioning

confidence: 99%

“…That said, clearly considering more deeply the origins of credit constraints would yield further insight. Along these lines, very recent work by Altinoglu (2016) and Luo (2016) embed a credit network into a production network structure. In their models, intermediate good trade is financed by supplier trade credit.…”

Section: Resultsmentioning

confidence: 99%

Distortions in Production Networks

Bigio¹,

La’O²

2016

129

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“… Some recent papers have investigated aggregate volatility in production networks with inefficient equilibria (where Hulten's theorem does not hold). Some examples include Bigio and La'O (), Baqaee (), Altinoglu (), Grassi (), and Baqaee and Farhi (). See also Jones (, ), Bartelme and Gorodnichenko (), and Liu (). …”

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confidence: 99%

The Macroeconomic Impact of Microeconomic Shocks: Beyond Hulten's Theorem

Baqaee¹,

Farhi

2019

ECTA

326

234

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We provide a nonlinear characterization of the macroeconomic impact of microeconomic productivity shocks in terms of reduced‐form nonparametric elasticities for efficient economies. We also show how microeconomic parameters are mapped to these reduced‐form general equilibrium elasticities. In this sense, we extend the foundational theorem of Hulten (1978) beyond the first order to capture nonlinearities. Key features ignored by first‐order approximations that play a crucial role are: structural microeconomic elasticities of substitution, network linkages, structural microeconomic returns to scale, and the extent of factor reallocation. In a business‐cycle calibration with sectoral shocks, nonlinearities magnify negative shocks and attenuate positive shocks, resulting in an aggregate output distribution that is asymmetric (negative skewness), fat‐tailed (excess kurtosis), and has a negative mean, even when shocks are symmetric and thin‐tailed. Average output losses due to short‐run sectoral shocks are an order of magnitude larger than the welfare cost of business cycles calculated by Lucas (1987). Nonlinearities can also cause shocks to critical sectors to have disproportionate macroeconomic effects, almost tripling the estimated impact of the 1970s oil shocks on world aggregate output. Finally, in a long‐run growth context, nonlinearities, which underpin Baumol's cost disease via the increase over time in the sales shares of low‐growth bottleneck sectors, account for a 20 percentage point reduction in aggregate TFP growth over the period 1948–2014 in the United States.

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“…Long and Plosser (1983), Horvath (1998), Horvath (2000), Dupor (1999), Acemoglu et al (2012), Foerster et al (2011), and Atalay (2014)) by showing that the number of sectoral connections in an economy could amplify or mitigate the effect of sectoral shocks on aggregate volatility, depending on the degree of substitutability between inputs. This paper also contributes to the literature of financial frictions in multisector model started with Bigio and La'O (2016) and extended by Luo (2015), Altinoglu (2015), and MirandaPinto and Young (2016). Unlike Bigio and La'O (2016), Luo (2015), and Altinoglu (2015), the model in this paper delivers financial cascades.…”

Section: Introductionmentioning

confidence: 65%

“…This paper also contributes to the literature of financial frictions in multisector model started with Bigio and La'O (2016) and extended by Luo (2015), Altinoglu (2015), and MirandaPinto and Young (2016). Unlike Bigio and La'O (2016), Luo (2015), and Altinoglu (2015), the model in this paper delivers financial cascades. A sectoral productivity or financial shock that causes one sector to become constrained can generate a domino effect where many other sectors become financially constrained.…”

Section: Introductionmentioning

confidence: 65%

Production Networks and Aggregate Fluctuations: Evidence, Theory, and Policy

Miranda

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In this dissertation we study the sources of aggregate fluctuations with emphasis on the role of firms' linkages and non-linearities in production. In Chapters 1 and 2, we present a new set of empirical facts on i) the relationship between the structure of inter-sectoral linkages and aggregate fluctuations, and ii) the relationship between firms' elasticity of substitution in production and the spreads on corporate bonds during periods of high corporate debt and in recessions. We then construct a multisector model that is able to deliver the observed empirical patterns. In Chapter 3 we test the predictions of different dynamic multisector models regarding how well they predict the observed co-movement of sectoral output growth in the U.S. industrial sectors. Finally, in Chapter 4 we study the normative implications of combining the models in Chapters 1-3.In Chapter 1, we study what features of the countries' domestic structure of sectoral linkages can help account for the observed differences in cross-country volatility of growth and the size of macroeconomic downturns. The empirical cross-country evidence, crosssectional and panel data, suggests that unlike previous multisector models predict, the density of sectoral connections -number of sectoral connections in countries' input-output tables -is strongly correlated with aggregate volatility and the size of downturns. Therefore, we develop a multisector model that is able to deliver a role for the density of connections.The key implications of the model are that: i) the density of sectoral connections amplifies shocks -as observed for manufacturing oriented countries -if firms have low elasticity of substitution between labor and intermediates, while ii) density mitigates shocks -as observed for service oriented countries -if firms have high elasticity. In addition, iii) the density of connections amplifies the size of downturns -as observed for manufacturing oriented countries -if low elasticity firms face frictions in the use of intermediates, while iv) density mitigates downturns -as observed for service oriented countries -if high elasticity firms face frictions in the use of labor.In Chapter 2, we study what are the sectors of the economy that have more troubles in financing inputs during recessions in the U.S. Using firm level and sector level data, we find that during times of high corporate debt i) manufacturing sectors with lower estimated elasticities of substitution between labor and intermediates pay higher spread on corporate bonds, while service sectors with larger elasticities pay higher spreads on corporate bonds.We also find that during recessions firms with low elasticity between labor and interme- In Chapter 3, we contrast the predictions of different multisector DSGE models with the observed correlations of sectoral output growth in the U.S. industrial sectors. We study models that differ in the timing of the investment decision and in the technology used to build physical capital. To focus on the role of capital accumulation, we as...

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The Origins of Aggregate Fluctuations in a Credit Network Economy

Cited by 14 publications

References 46 publications

Distortions in Production Networks

Distortions in Production Networks

The Macroeconomic Impact of Microeconomic Shocks: Beyond Hulten's Theorem

Production Networks and Aggregate Fluctuations: Evidence, Theory, and Policy

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