This paper investigates the underlying mechanism of endogenous formation of networks while building on firm-to-firm linkages. It also provides how firm-level input-output linkages across firms provide an amplification mechanism of shocks. After finding strong evidence that supports the asymmetry of the firm-level production networks, I build a model that lays a theoretical foundation between productivity and the formation of production networks. Empirical evidence reveals the close relationship between the expansion of a firm’s production network and its productivity. The productivity changes in each firm studied through the sophistication of a network while proposing a learning-by-networking hypothesis with other firms in their production network.
We analyze the transmission of producer price inflation shocks across the U.S. manufacturing industries from 1947 to 2018 using the Diebold-Yilmaz Connectedness Index framework, which fully utilizes the information in generalized variance decompositions from vector autoregressions. The results show that the system-wide connectedness of the input-output network Granger-causes the producer price inflation connectedness across industries. The input-output network and the inflation connectedness nexus is stronger during periods of major supply-side shocks, such as the global oil and metal price hikes, and weaker during periods of aggregate demand shocks, such as the Volcker disinflation of 1981-84 and the Great Recession of 2008. These findings are consistent with Acemoglu et al. (2016)’s conjecture that supply shocks are transmitted downstream, whereas demand shocks are transmitted upstream. Finally, preliminary results show that Trump tariffs caused an increase in the system-wide inflation connectedness in the first half of 2018, due to shocks mostly transmitted from tariff-targeted industries, namely, basic metals, fabricated metals and machinery.
This paper investigates the relationship between input-output networks and the transmission of inflation shocks across manufacturing industries in South Korea, an economy that is open to external shocks. Using the dynamic inflation connectedness measures for 1971-2020, we show that production networks are responsible for the amplification of inflation shocks during times of supply shocks, such as the oil price shocks of 1973-74 and 1979-80. On the contrary, production networks are weakly associated with inflation transmission across sectors if the shocks originate from the demand-side such as the East Asian Financial Crisis of 1997.
This paper provides insights for policymakers to evaluate the impact of staying at home and lockdown policies by investigating possible links between individual mobility and the spread of the COVID-19 virus in Italy. By relying on the daily data, the empirical evidence suggests that an increase in the number of visits to public spaces such as workspaces, parks, retail areas, and the use of public transportation is associated with an increase in the positive COVID-19 cases in a subsequent week. On the contrary, the increased intensity of staying in residential spaces is related to a decrease in the confirmed cases of COVID-19 significantly. Results are robust after controlling for the lockdown period. Empirical evidence underlines the importance of the lockdown decision. Further, there is substantial regional variation among the twenty regions of Italy. Individual presence in public vs. residential spaces has a more significant effect on the number of COVID-19 cases in the Lombardy region.