Producer Price Inflation Connectedness and Input-Output Networks

Abstract

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.

A network analysis of electricity demand and the cryptocurrency markets

“…through return spillover and volatility spillover. This approach has been applied in other markets like cryptocurrency (Ji et al, 2019), financial and macroeconomic sectors (Cotter et al, 2017; Diebold & Yilmaz, 2015a), manufacturing and industrial sector (Bilgin & Yilmaz, 2018), financial and real sectors (Uluceviz & Yilmaz, 2018), global banking sector (Demirer et al, 2018), global credit risk sector (Bostanci & Yilmaz, 2015), global business cycle (Diebold & Yilmaz, 2015b), etc. Notwithstanding, the network models used to study the ECN system are discussed in detail.…”

“…Diebold and Yilmaz (2015a) and Cotter, Hallam, and Yalmaz (2017) used this approach to study the connectedness and information spillover between the financial and macroeconomic sectors. Bilgin and Yilmaz (2018) also used this approach to examine the connectedness and spillover of information between the manufacturing and industrial sector. Uluceviz and Yilmaz (2018) analysed the information spillover and connectedness between the financial and real sectors.…”

An assessment of the impact of various macro-economic variables on the manufacturing sector: The case of the Visegrád four

“…Depreciation in the local currency is associated with an increase in domestic prices and an increase in export prices. Bilgin and Yilmaz (2018) assessed the relationship between PPI and manufacturing input-output networks in the U.S. from 1947 to 2018. Results indicated that manufacturing input-output networks do Granger-cause the PPI across industries.…”