I find it fascinating to study decentralized decision-making and its collective impact. When institutions, organizations, or individuals make decisions that affect the choices of others, the final results can often be complex and lead to unintended consequences. I use mathematical models of markets and games to predict outcomes in these situations and to develop principles to guide predicted outcomes. My research uses analytically rigorous arguments and quantitative methods to derive conclusions that are more likely to survive the test of time. A brief summary of my research classified into broad categories is included below. Published papers and their abstracts are available here.
Game Theory and Competitive Strategy
Over the past 10-15 years, my research has overturned this conventional wisdom, transformed the understanding of the fundamental forces underlying the new cases, developed new tools to analyze directly interdependent interactions involving strategic substitutes and heterogeneity, and expanded the understanding of related influential literatures like directional optimization, global games, and dynamic games. My papers on these topics include Roy and Sabarwal (2008, 2010, 2012), Monaco and Sabarwal (2016), Barthel and Sabarwal (2018), Hoffmann and Sabarwal (2015, 2019a, 2019b), Feng and Sabarwal (2020, 2021), Barthel, Hoffmann, and Sabarwal (2021), and Sabarwal and Vu (2020)). Based on the success of this research, I was awarded a contract to write a research monograph on monotone games which has just been published (see Sabarwal (2021)).
Competition, Markets, and Welfare
My research on financial markets sheds light on different aspects of the design, pricing, and performance of asset-backed securities, irreversible investments, and limited liability debt contracts in financial markets. Theoretical underpinnings of these ideas are formulated in the early study of chain reactions of personal bankruptcy as an equilibrium phenomenon in anonymous asset-backed securities markets with limited liability consumer debt contracts in the setting of multi-period, multi-asset, multi-good, multi-agent, incomplete and competitive markets in Sabarwal (2003). That paper also showed how allowing for bankruptcy can improve borrower welfare and lender welfare by endogenously creating new assets with better risk-sharing opportunities. These ideas paved the way for the first academic paper on the drivers of default and prepayment on subprime auto loans using hazard rate modeling and data from asset-backed securities in Heitfield and Sabarwal (2004). Common structures used in the design of asset-backed securities and their associated risks are discussed in Sabarwal (2006).
The equilibrium effect of limited liability debt contracts on the NPV investment threshold for irreversible investments in real options theory is studied in Sabarwal (2005). This presented the first derivation of the NPV threshold as an equilibrium phenomenon in models of irreversible investment with a competitive lending sector.
Studying antitrust aspects of investment banking, Kulkarni and Sabarwal (2007) show that the high and stable spreads charged to bring moderate-sized IPOs to market are hard to explain using the standard argument that investment banks provide differentiated services to firms in different industries.
I have been intrigued by efficiency-driven mergers and acquisitions and studied some properties of Upward Pricing Pressure (UPP), a new tool that is being used increasingly widely worldwide in the analysis of horizontal mergers. UPP is tractable, easy to implement, uses less information than other standard measures, and is derived from the existing theory of oligopoly. Dutra and Sabarwal (2020) show that the accuracy of UPP as a tool in merger analysis is enhanced greatly by inclusion of merger-specific cost efficiencies directly in the computation. Our formulation of UPP may be an excellent and cheaper alternative to full-merger simulations, which are considerably more expensive to implement. This has the potential to impact antitrust policy worldwide.
Computer Science & Networks
A new paper in this area is the following. Proliferation of misinformation in social networks is an increasingly central topic in society recently. The process of misinformation spread shares structural similarities with the way infectious disease spreads in a society of connected individuals. Using a general model that subsumes both these cases, Higgins and Sabarwal (2021) investigate the control and spread of contagion in networks with aggregative virality. This research solves long-standing theoretical problems in this area, develops new algorithms that are computationally tractable, and applies theoretical results to study contagion in scale-free networks using Monte Carlo methods.
A problem in personal bankruptcy research has been lack of publicly available data. Only a few hundred cases are found in publicly available datasets, as compared to more than 40 million bankruptcy filings since 1898. Lenders have some data but it is not representative and is unavailable for academic research. With external funding from the National Science Foundation (2014-17, $176,061) and the Alfred P. Sloan Foundation (2012-13, $48,160), I led research teams to collect bankruptcy data from historical court records at the Kansas City office of the National Archives of the United States. Altogether, the research team took about 525,000 photographs of documents from more than 25,000 cases filed in 24 federal district courts in 18 states over different periods spanning more than a century (1898-2002). These projects funded 4 graduate students and 17 undergraduate students at KU to gain first-hand research experience in original source data collection, a rare and increasingly sought skill in economics.