Final Report Summary - MACRONETS (Production Networks in Macroeconomics)
A modern economy is an intricately linked web of specialized production units, each relying on the flow of inputs from their suppliers to produce their own output which, in turn, is routed towards other downstream units. Recent work in economics stresses that the structure of this production network is key in determining whether and how microeconomic shocks – affecting only a particular firm or technology – can propagate throughout the economy and shape aggregate outcomes. If this is the case, understanding the structure of this production network can better inform both academics on the origins of aggregate fluctuations and policy-makers on how to prepare for and recover from adverse shocks that disrupt these production chains. Work carried under the MACRONETS project can be usefully split in three parts: (i) novel evidence on the micro origins of aggregate fluctuations in networked economies; (ii) novel theoretical results offering new testable implications concerning the impact of individual firms and sectors on comovement and aggregate fluctuations and (iii) novel theoretical and empirical results on the importance of existent production network linkages for the diffusion of new inputs and new technologies.
First, we have provided novel evidence which enables researchers and policy-makers to trace back the origins of business cycles fluctuations to individual superstar firms, sectors or technologies interconnected by input-supply relations. One way to achieve this is to exploit natural experiments - e.g. the exogenous and regional nature of the Great East Japan Earthquake of 2011 - and combine it with large scale information on firm-to-firm linkages in Japan to provide a systematic quantification of the role of input-output linkages as a mechanism for the propagation and amplification of shocks. Using this methodology, we were able to document that the disruption caused by the earthquake and its aftermaths propagated upstream and downstream supply chains, affecting the direct and indirect suppliers and customers of disaster-stricken firms. We then used our empirical findings to obtain an estimate for the overall macroeconomic impact of the shock by taking these propagation effects into account. We found that the propagation of the shock over firm-level input-output linkages can account for a 1.2 percentage point decline in Japan’s gross output in the year following the earthquake. A second way to assess the aggregate risk imposed by systemically important firms is through the development of quantitative models that are amenable to simulation and forecasting. Following this alternative methodology, work under MACRONETS showed how heterogenous firm growth over the business cycle - and in particular large firm dynamics - can impact aggregate fluctuations. In particular, we found that individual shocks to a small number of very large firms can account for 30% of aggregate fluctuations in the US economy. Taken together these findings highlight the importance of systemic firms - be it by their centrality in nation-wide supply chains or by their sheer size and consequent impact on final output and labor markets - as drivers of macroeconomic risk.
Second, the MACRONETS project has developed a new set of theoretical results to better understand the impact of individual firms and sectors on the macroeconomy. In particular, we have generalized exisiting models of production networks to shed light on: (i) empirical patterns of firm and sectoral comovement over time (ii) how firm and sectoral comovement are function of how far apart the different firms and sectors are in the production network (iii) how central firms and sectors in the production network comove more with aggregate GDP and how this can be usefully deployed when forecasting of aggregate GDP. In all, we have developed a suite of theoretical results, drawing on traditional tools of network analysis —such as distance across nodes or centrality of a given node— that, when combined with novel economic models, provide empirically testable hypothesis regarding comovement and aggregate fluctions.
Third, the MACRONETS project sought to understand the role of production networks in the adoption and diffusion of new inputs (e.g. semiconductors for example). This perpetual process of adoption and diffusion of new technologies is, in turn, at the heart of technological progress and long term growth. Guided by a novel endogenous production network framework, we document a novel stylized fact at both the sector and the firm level: producers are more likely to adopt inputs that are already used – directly or indirectly – by their current suppliers. In particular, using disaggregated input-output data, we show that initial network proximity to a given sector in 1967 significantly increases the likelihood of adoption throughout the subsequent four decades. A one-standard deviation decrease in network distance is associated with an increase in the adoption probability by one third to one half. Similarly, U.S. firms are significantly more likely to develop new input linkages among their suppliers’ network neighborhood. Our results imply that the existing production network plays a crucial role in the diffusion of inputs and the evolution of technology.
First, we have provided novel evidence which enables researchers and policy-makers to trace back the origins of business cycles fluctuations to individual superstar firms, sectors or technologies interconnected by input-supply relations. One way to achieve this is to exploit natural experiments - e.g. the exogenous and regional nature of the Great East Japan Earthquake of 2011 - and combine it with large scale information on firm-to-firm linkages in Japan to provide a systematic quantification of the role of input-output linkages as a mechanism for the propagation and amplification of shocks. Using this methodology, we were able to document that the disruption caused by the earthquake and its aftermaths propagated upstream and downstream supply chains, affecting the direct and indirect suppliers and customers of disaster-stricken firms. We then used our empirical findings to obtain an estimate for the overall macroeconomic impact of the shock by taking these propagation effects into account. We found that the propagation of the shock over firm-level input-output linkages can account for a 1.2 percentage point decline in Japan’s gross output in the year following the earthquake. A second way to assess the aggregate risk imposed by systemically important firms is through the development of quantitative models that are amenable to simulation and forecasting. Following this alternative methodology, work under MACRONETS showed how heterogenous firm growth over the business cycle - and in particular large firm dynamics - can impact aggregate fluctuations. In particular, we found that individual shocks to a small number of very large firms can account for 30% of aggregate fluctuations in the US economy. Taken together these findings highlight the importance of systemic firms - be it by their centrality in nation-wide supply chains or by their sheer size and consequent impact on final output and labor markets - as drivers of macroeconomic risk.
Second, the MACRONETS project has developed a new set of theoretical results to better understand the impact of individual firms and sectors on the macroeconomy. In particular, we have generalized exisiting models of production networks to shed light on: (i) empirical patterns of firm and sectoral comovement over time (ii) how firm and sectoral comovement are function of how far apart the different firms and sectors are in the production network (iii) how central firms and sectors in the production network comove more with aggregate GDP and how this can be usefully deployed when forecasting of aggregate GDP. In all, we have developed a suite of theoretical results, drawing on traditional tools of network analysis —such as distance across nodes or centrality of a given node— that, when combined with novel economic models, provide empirically testable hypothesis regarding comovement and aggregate fluctions.
Third, the MACRONETS project sought to understand the role of production networks in the adoption and diffusion of new inputs (e.g. semiconductors for example). This perpetual process of adoption and diffusion of new technologies is, in turn, at the heart of technological progress and long term growth. Guided by a novel endogenous production network framework, we document a novel stylized fact at both the sector and the firm level: producers are more likely to adopt inputs that are already used – directly or indirectly – by their current suppliers. In particular, using disaggregated input-output data, we show that initial network proximity to a given sector in 1967 significantly increases the likelihood of adoption throughout the subsequent four decades. A one-standard deviation decrease in network distance is associated with an increase in the adoption probability by one third to one half. Similarly, U.S. firms are significantly more likely to develop new input linkages among their suppliers’ network neighborhood. Our results imply that the existing production network plays a crucial role in the diffusion of inputs and the evolution of technology.