The Network Origins of Aggregate Fluctuations

Abstract

This paper argues that, in the presence of intersectoral input–output linkages, microeconomic idiosyncratic shocks may lead to aggregate fluctuations. We show that, as the economy becomes more disaggregated, the rate at which aggregate volatility decays is determined by the structure of the network capturing such linkages. Our main results provide a characterization of this relationship in terms of the importance of different sectors as suppliers to their immediate customers, as well as their role as indirect suppliers to chains of downstream sectors. Such higher‐order interconnections capture the possibility of “cascade effects” whereby productivity shocks to a sector propagate not only to its immediate downstream customers, but also to the rest of the economy. Our results highlight that sizable aggregate volatility is obtained from sectoral idiosyncratic shocks only if there exists significant asymmetry in the roles that sectors play as suppliers to others, and that the “sparseness” of the input–output matrix is unrelated to the nature of aggregate fluctuations.

May's instability in large economies

“…The argument is that the fat-tailed distribution of sizes of independent firms/sectors slows down the regression of fluctuations from the standard N −1/2 behaviour to N −α , with α ≤ 1/2 related to the tail exponent of the distribution. Although some empirical support for this scenario has been put forth [11, 14], other works suggest that network effects are in fact dominant [15][16][17], as idiosyncratic shocks can cascade along the input-output network and eventually become macroscopic 2 . One particular stigma of these network effects is the strong co-variation of fluctuations across different sectors [22] -but see also [23].While the cascade story is enticing, the baseline Cobb-Douglas network model proposed by Acemoglu, Carvalho et al [1,15] is, in our view, not convincing.…”

Modeling loss-propagation in the global supply network: The dynamic agent-based model acclimate

“…As in I-O and CGE models, its spatial and sectoral resolution is, in principle, only limited by data availability. Modeling the interplay of multiple heterogeneous agents and considering the network structure of their interlinkages allows to describe complex effects such as cascading losses and lock-in situations (Acemoglu et al, 2012(Acemoglu et al, , 2015. Yet, considering national sectors, this study still lacks a realistic representation of the firm size distribution.…”

“…Locally, disasters directly suppress economic activity such as commodity production. The associated losses, however, can spread to other sectors via back-and forward-linkages of the supply chains causing indirect losses (Rose, 2004;Acemoglu et al, 2012). Further, recent studies suggest that in the last decades the vulnerability of the economy with respect to climate extremes has increased (OECD, 2015;Wenz and Levermann, 2016).…”

“…For instance, they can allocate the scale-free topology of firm networks to the competition among the firms. Further, as in the static theory (Acemoglu et al, 2012), their model permits to ascribe aggregate volatility to the fat-tailed distribution of firm sizes.…”

Interdependencies and Causalities in Coupled Financial Networks

“…Previous studies related to financial systems [8,43,[45][46][47][48][49] have shed light not only on the topology of financial networks, i.e., the monetary and information flow within economic and governance networks, but have also examined systemic risk propagation. Acemoglu et al [50] argue that macroeconomic shocks that originate in one sector may not necessarily be contained close to the origin, but rather could spill over to other parts of the economy affecting other sectors' outputs generating significant aggregate effect. This study illuminates the often ignored cascading failure effect that could contribute to disastrous consequences in the entire economic system.…”