“Commercial Bank Heterogeneity and the Transmission of Monetary Policy Through Bank Lending” [Job Market Paper; Internal Award: Kleinsorge Research Award]
Abstract: The commercial banking sector in the United States comprises numerous small, local (community) banks primarily focused on small business lending, alongside a smaller group of large, geographically-diversified (non-community) banks that cater to larger borrowers. I study how heterogeneity in lending practices across these two types of banks influences the transmission of monetary policy to the real economy. Using the novel pass-through impulse response function (PT-IRF) introduced in Nikolaishvili (2023), I quantify the contributions of community versus noncommunity bank lending to the dynamic effect of a monetary policy shock on output. My findings show that noncommunity bank lending amplifies the contractionary effects of a monetary tightening in the short run, whereas community bank lending has a stronger amplificatory contribution in the medium run. These results suggest that a continued decline in the relative presence of community banks may lead to a subsequent decline in the persistence of monetary transmission. Furthermore, the adverse impact of a monetary tightening on spending must linger more heavily among small businesses and agricultural producers in remote rural areas, since these borrower segments tend to heavily rely on community bank lending as a source of funds. In short, I show that the composition of the commercial banking sector affects the timing and distributional impact of monetary policy transmission through heterogeneity in lending practices.
“Pass-Through Impulse Response Functions (PT-IRFs)” [New Draft Coming Soon]
Abstract: Impulse response functions (IRFs) offer little insight regarding the channels through which a shock propagates through a dynamical system. I formulate the concept of a pass-through impulse response function (PT-IRF), which measures the passage of a structural shock through specific sets of variables in a given system. I demonstrate the applicability of the PT-IRF by performing inference on the effect of a monetary policy shock on unemployment through various channels of the monetary transmission mechanism using a structural vector autoregression.
“Computing Temporary Equilibria using Exact Aggregation” (with David Evans) [Preparing for Submission]
Abstract: We suggest a new method of approximating temporary equilibria in heterogeneous agent models. Our approach offers a significant speedup without a notable drop in accuracy relative to established methods. We demonstrate the effectiveness of our procedure by applying it to a model with heterogeneous boundedly rational agents, and comparing its performance to that of alternative methods.
“The Evolution of Community Bank Interconnectedness” [Internal Award: Best Field Paper / PhD Research Paper]
Abstract: I find that the community banking sector in the United States has become more interconnected since the global financial crisis, which implies greater exposure to systemic risk and increased vulnerability in future financial crises. I estimate a hierarchical dynamic factor model using a Bayesian approach to extract posterior distributions of national, regional, and state-level latent drivers of quarterly fluctuations in state-average community bank return-on-equity for all 50 US states. The resulting estimates show evidence of both considerable national comovement and state-specific idiosyncrasy with no signs of significant regional comovement. Furthermore, the results show a decrease in the intensity of idiosyncratic dynamics of state-level community bank profitability since the crisis, along with an increase in national comovement across most states.
 “Measuring economic activity in the presence of superstar MNEs” (with Philip Economides) Economics Letters (2023)
Works in Progress
“Monetary Transmission via Expectations in DSGEs with Bounded Rationality” (with Edder Martínez Lazo)
“Inference on PT-IRFs: VARs and Local Projections”
“Estimating Large Bayesian Hierarchical Dynamic Factor Models”
Other Works & Publications
 “News Shocks under Financial Frictions: A Comment on Görtz et al. (2022)” (with Thomas Ash and Ethan Struby) I4R Discussion Paper Series (2023)
 “Using deep learning to examine the correlation between transportation planning and perceived safety of the built environment” (with Justin Hollander, Alphonsus Adu-Bredu, Minyu Situ, and Shabnam Bista) Environment and Planning B: Urban Analytics and City Science (2021)
Julia package for simulating and estimating multi-level/hierarchical dynamic factor models (HDFMs).