Input Specificity and the Propagation of Idiosyncratic Shocks in Production Networks
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Barrot, Jean Noël; Sauvagnat, Julien

doi:10.1093/qje/qjw018

Cited by 850 publications

(501 citation statements)

References 65 publications

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“…The lagged effect of a temperature shock on the economic variables does not come at a surprise as the shock does not affect all sectors homogeneously and, thus, propagates only gradually across the economy. This intuition is confirmed by Barrot and Sauvagnat (2016) who show that firm-specific shocks to suppliers, induced by natural disasters, have large short-term adverse effects on sales growth of their customers over the four consecutive quarters.…”

mentioning

confidence: 71%

Temperature Shocks and Welfare Costs

et al. 2017

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This paper examines the welfare implications of rising temperatures. Using a standard VAR, we empirically show that a temperature shock has a sizable, negative and statistically significant impact on TFP, output, and labor productivity. We rationalize these findings within a production economy featuring long-run temperature risk. In the model, macro-aggregates drop in response to a temperature shock, consistent with the novel evidence in the data. Such adverse effects are long-lasting. Over a 50-year horizon, a one-standard deviation temperature shock lowers both cumulative output and labor productivity growth by 1.4 percentage points. Based on the model, we also show that temperature risk is associated with non-negligible welfare costs which amount to 18.4% of the agent's lifetime utility and grow exponentially with the size of the impact of temperature on TFP. Finally, we show that faster adaptation to temperature shocks results in lower welfare costs. These welfare benefits become substantially higher in the presence of permanent improvements in the speed of adaptation.JEL classification: E30, G12, Q0

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confidence: 71%

Temperature Shocks and Welfare Costs

et al. 2017

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“…Changes in relationship-specific characteristics may arise from variation in restrictions on firms' use of alternative inputs, e.g. Barrot and Sauvagnat (2016). Variation in such restrictions may emerge from changes-driven by innovation or industry regulation-in production technologies, complementarities among firms' activities, or market competition.…”

Section: When Calibrated To Match Key Characteristics Of Customer-supmentioning

confidence: 99%

“…However, the propensity of the relationship between firm i and j at year t, p ijt , is unobservable. In the context of supply chains, nonetheless, evidence documented by Barrot and Sauvagnat (2016) suggest that p ijt is related with firms i and j's input specificities. As firms' input specificities are likely to depend on the percentage of sales that a customer represents for its supplier as well as firms' industry concentration, I proxy for p ijt as p ijt ≈ % of sales that j represents for i at t × Concentration score in j's industry at t. (13) Thus, the higher the percentage customer j represents for supplier i, the higher the likelihood that shocks affecting j also affect i.…”

Section: Calibrationmentioning

confidence: 99%

Inter-firm Relationships and Asset Prices

Ramírez

2017

FEDS

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This paper proposes a novel link between the propagation of shocks within production networks and asset prices. It develops a dynamic network model in which the propagation of firm cash-flow shocks via inter-firm relationships affects the economy's equilibrium asset prices. When calibrated to match key features of customer-supplier networks in the United States, the model generates long-run risks, high and volatile risk premia, and a low and stable risk-free rate. Consistent with data from firms in manufacturing and service industries, the model predicts that central firms in the network command lower risk premiums than peripheral firms, and that firm-level return volatilities exhibit a high degree of co-movement.

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“…Skidmore and Toya (2002) and Toya and Skidmore (2014) assess a country's exposure to disasters as the number of significant events occurred in a certain period. Barrot and Sauvagnat (2016), Hosono et al (2016) and Calo-Blanco et al…”

Section: Introductionmentioning

confidence: 95%

Natural Disasters and Demand for Redistribution: Lessons from an Earthquake

et al. 2018

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The literature shows that when a society believes that wealth is determined by random "luck" rather than by merit, it demands more redistribution. Adverse shocks, like earthquakes, strengthen the belief that random "bad luck" can frustrate the outcomes achieved with merit. We theoretically illustrate that individuals react to such shocks by raising support for redistribution. We then present evidence of this behavior by exploiting a natural experiment provided by one of the strongest seismic events that occurred in Italy in the last three decades, the L'Aquila earthquake in 2009. We assemble a novel dataset by matching information on the ground acceleration registered throughout the National Strong Motion Network during the earthquake with survey data about individual opinions on redistribution collected a few months later. The empirical analysis illustrates that the intensity of the shakes is associated with subsequent stronger beliefs that, for a society to be fair, income inequalities should be levelled by redistribution.

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Input Specificity and the Propagation of Idiosyncratic Shocks in Production Networks *

Cited by 850 publications

References 65 publications

Temperature Shocks and Welfare Costs

Temperature Shocks and Welfare Costs

Inter-firm Relationships and Asset Prices

Natural Disasters and Demand for Redistribution: Lessons from an Earthquake

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