Networks and the Macroeconomy: An Empirical Exploration

By Daron Acemoglu, Ufuk Akcigit, William R. Kerr. NBER macroeconomics annual, 2016

558 citations recorded by the source corpus.

The propagation of macroeconomic shocks through input-output and geographic networks can be a powerful driver of macroeconomic fluctuations. We first exposit that in the presence of Cobb-Douglas production functions and consumer preferences, there is a specific pattern of economic transmission whereby demand-side shocks propagate upstream (to input-supplying industries) and supply-side shocks propagate downstream (to customer industries) and that there is a tight relationship between the direct impact of a shock and the magnitudes of the downstream and the upstream indirect effects. We then investigate the short-run propagation of four different types of industry-level shocks: two demand-side ones (the exogenous component of the variation in industry imports from China and changes in federal spending) and two supply-side ones (TFP shocks and variation in knowledge/ideas coming from foreign patenting). In each case, we find substantial propagation of these shocks through the input-output network, with a pattern broadly consistent with theory. Quantitatively, the network-based propagation is larger than the direct effects of the shocks. We also show quantitatively large effects from the geographic network, capturing the fact that the local propagation of a shock to an industry will fall more heavily on other industries that tend to collocate with it across local markets. Our results suggest that the transmission of various different types of shocks through economic networks and industry interlinkages could have first-order implications for the macroeconomy.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/befab26cd8caa6110b5c72cca412c4ea75d0b585

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Citations in the corpus

Econometric analysis of production networks with dominant units (2020, unknown): “The (log) real-wage equation, (6), generalizes equation (3) in Acemoglu et al. (2012) by allowing for time variations in prices and technologies.”
Networks of Value Added Trade (2017, unknown): “The structure of the connections between firms (Gabaix, 2011) or sectors (Acemoglu et al., 2012) in a given country plays a fundamental role in the transmission of shocks from individual agents to the whole economy, notably through cascade effects. Networks offer a way to express how idiosyncratic s”
The Development Effects of the Extractive Colonial Economy: The Dutch Cultivation System in Java (2019, unknown): “See Acemoglu et al. (2016), Baqaee (2015), Acemoglu et al. (2012), Carvalho (2009) for the role of input– outputlinkagesintransmittingmacroeconomicshocksandLiu(2017),Lane(2017),Bartelme and Gorodnichenko(2015) higherdensityofintercityandlocalroads,aswellasrailroads,thanplacesjustafewkilometers…”
The propagation of monetary policy shocks in a heterogeneous production economy (2018, background): “Gabaix (2011) and Acemoglu et al. (2012) show theoretically the network structure and the firm-size distribution are potentially important propagation mechanisms for aggregate fluctuations originating from firm and industry shocks. Acemoglu, Akcigit, and Kerr (2015) and Barrot and Sauvagnat (2016) s”
Monetary Policy Through Production Networks: Evidence from the Stock Market (2017, unknown): “However, recent work by Gabaix (2011) and Acemoglu et al. (2012), building on Long and Plosser (1983) and Horvath (1998), shows that the law of large numbers does not readily apply when the firm-size distribution or the importance of sectors as suppliers of intermediate inputs to the rest of the eco”
Trade Network Centrality and Currency Risk Premia (2019, unknown): “I make these contributions theoretically by embedding the nontradables friction of Backus and Smith (1993) within a multi-country version of the network model of Acemoglu et al. (2012)2. The latter work shows how production networks can give rise to aggregate economic fluctuations. The model illustr”
The Relationship Between Global Value Chains and Productivity (2017, background): “Upstream industries further from the final consumers are more exposed to demand shocks (Acemoglu et al., 2015).”
Production Networks: A Primer (2019, methodology): “In this section, we follow Acemoglu et al. (2012) and use Theorems 1 and 2 to revisit Lucas’s argument and characterize the conditions under which input-output linkages in the economy can indeed generate sizable aggregate fluctuations from purely idiosyncratic shocks.”