Link to the paper (May 2022)

SSRN link

Abstract

This paper revisits financial networks in a model of mandatory bail-ins and complementary bailouts. Under mandatory bail-ins, network’s role is reshaped and beyond its previous contagion-related role, because counterparty obligations, in the first place, are used for bail-ins against idiosyncratic failures. Diversification faces a novel tradeoff: higher diversification increases aggregate bail-ins for avoiding initial failures; however, against large shocks, bail-ins are not effective and complementary bailouts are costly, and higher diversification leads to more unavoided failures. Nevertheless, dense networks have major advantages for non-contagion-related reasons that didn’t exist before and maximize welfare except in extreme cases of system-wide contagion risk

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Last updated version here (September 2021)

Slides, SSRN link

Abstract

This paper presents a coalitional rescue framework in financial networks, where banks’ potential losses from failures incentivize them to rescue each other and a welfare-losses-minimizing government contributes to rescues via bailout transfers. Endogenous rescues reverse fundamental insights into financial networks and provide general insights into how interconnected agents behave differently against each other’s fragility and how the government can reduce welfare-losses via a combination of ex-ante policies and ex-post transfers. Surprisingly, for any particular bank, the government’s bailout decision is independent of contagious effects (or the whole network structure) and depends only on the direct costs and benefits of its rescue (or local connectivity). Therefore, rescues occur selectively. Nevertheless, a network-neutrality result holds: In any financial network (under a mild condition), the government always prevents certain types of failures. Despite the network-neutrality in rescue decisions, banks’ contributions in rescues and the welfare losses vary dramatically depending on the network structure. I characterize welfare-losses-minimizing networks and introduce a new concept: “self-contained networks”, which applies to different settings beyond financial networks.

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Presentations: Federal Reserve Board, North American Summer Meeting of the Econometric Society (UC Davis), International Conference on Game Theory (Stony Brook University), Coalition Theory Network Workshop (Maastricht University), NET Institute Conference (NYU Stern, invited), Conference on Network Science and Economics (Washington University in St. Louis)

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Last updated version here (July 2020)

SSRN link, Video (NBER Economics of AI Conference 2019)

Abstract

We study how advances in labor-substituting (automation) technologies affect production networks. Labor-substituting advances lower the wages of substitutable workers relative to non-substitutable workers, affecting employment in the entire economy, well beyond the production chains adopting the new technologies. As automation progresses, the production network becomes denser, increasing the centralities of producers of automation and their (direct and indirect) suppliers. The growth effects of automation emerge gradually, and the changes in income inequality and overall productivity depend on (i) alternative uses of the replaced labor, and (ii) sectoral compositions of substitutable and non-substitutable workers. These provide explanations for why today’s automation is different from historical ones.

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Presentations: SED 2020 (invited), AEA 2020 Annual Meeting, NBER Economics of AI Conference 2019, Harvard Kennedy School, 2019 European Winter Meeting of the Econometric Society, CIRANO Workshops on Networks in Trade and Finance

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