Published Papers
2024
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Beliefs and The Net Worth Trap (Accepted at the Journal of Economic Theory)Goutham Gopalakrishna, Seung Joo Lee, and Theofanis Papamichalis2024We develop a tractable framework to explore how beliefs about long-term economic growth shape macroeconomic and financial stability. By modeling belief distortions among productive capital users, we provide an analytical characterization of a novel phenomenon termed the “net worth trap”, where overly optimistic or pessimistic beliefs of productive agents prevent them from rebuilding wealth, causing permanent inefficiencies. A procyclical swing in beliefs reduces or exacerbates the instability, indicating that the type of belief when the economy is vulnerable has important con- sequences on financial stability and macroeconomic dynamics.
Working Papers
2024
- Asset Pricing, Participation Constraints, and InequalityGoutham Gopalakrishna, Zhouzhou Gu, and Jonathan Payne2024
How do asset returns interact with wealth inequality? Empirical evidence shows that portfolio choices and financial constraints lead to unequal risk exposure across households and financial intermediaries. To understand the dynamic general equilibrium implications, we build a macroeconomic model with heterogeneous households, a financial sector, asset market participation constraints, and endogenous asset price volatility. We develop a new deep learning methodology for characterizing global solutions to this class of macro-finance models. We show that wealth inequality, financial sector recovery, and asset price dynamics depends on which households are able to purchase assets during crisis. This means the government faces a trade-off between tighter leverage constraints and a more equal recovery. In our calibrated model, asset returns and participation constraints account for a large fraction of the change in wealth inequality over the past half-century.
- ALIENs for Continuous Time EconomiesGoutham Gopalakrishna, and Yuntao Wu2024
This paper extends the growing deep learning based literature on solving equilibrium economic models and introduces Active Learning Inspired Equilibrium Nets (ALIENs). The method is particularly tailored for continuous-time models involving high-dimensional state spaces, aggregate shocks, and nonlinear dynamics. ALIENs extend the deep learning methods to include time-stepping and active learning to transform non-linear problems into sequences of contraction mappings, ensuring stability and convergence. Active learning prioritizes computational efforts in economically significant regions of the state space, improving accuracy. The proposed methodology is validated across a few applications, from infinite-horizon heterogeneous agent models with free boundaries to high-dimensional asset pricing models. Additionally, the paper introduces Deep-Macrofin+, a numerical library that facilitates the implementation of these techniques for researchers.
2022
- A Macro-Finance model with Realistic Crisis DynamicsGoutham Gopalakrishna2022
Financial recessions are typically characterized by a large risk premium and a slow recovery. However, macro-finance models have trouble quantitatively explaining these empirical features, especially when they are calibrated to simultaneously match both the observed unconditional and conditional macroeconomic and asset pricing moments. In this paper, I build a macro-finance model that quantitatively explains the salient features of a financial crisis, such as a large drop in output, a spike in the risk premium, reduced financial intermediation, and a long duration of economic distress. The model has leveraged intermediaries with stochastic productivity and a state-dependent exit rate that governs the transition into and out of a crisis. A model without these two features suffers from a trade-off between the amplification and persistence of crisis. I show that my model resolves this tension and generates realistic crisis dynamics.
- Supply Chain Finance and Firm Capital StructureGoutham Gopalakrishna, Laura Bottazzi, and Claudio Tebaldi2022
We analyze a proprietary dataset of factoring transactions, where a financial intermediary, a factor, provides capital to support customers-supplier trade-credit transactions. At the empirical level, we characterize distinctive features that correlate customer and supplier capital structure determinants with the intensity of observed factoring transactions. Our key finding is that the characteristics of the production-related supply-chain network and downstream competition simultaneously shape the inter-firm trade- and bank-related debt chains and the firm-specific corporate financial policies. To match this evidence, we develop a structural model where the intensity of usage of factoring services is endogenously determined, jointly with the capital structures of the bank, the supplier, and the customer.