Published or Forthcoming Papers
We investigate the strict exogeneity assumption, a necessary condition for estimator consistency in many finance panel settings. We outline tests for strict exogeneity in both traditional (non-IV) and IV settings. When we apply these tests in common traditional finance panel regressions, we find that the strict exogeneity assumption is often rejected, suggesting large inference errors. We test for strict exogeneity in specific finance IV panel settings and illustrate the potential for these tests to help confirm, or rule out, the validity of common panel IV estimators. We offer a set of recommendations to address the strict exogeneity issue in finance research.
♦ Lead Article in JFQA
♦Presented at the 2015 London Business School Symposium on Causal Inference, the 2016 Financial Research Association conference in Las Vegas, Iowa University, and the University of Nebraska
Corporate Investment and Innovation in the Presence of Competitor Constraints, Review of Financial Studies (2019), with Zack Liu
We study the relation between investment behavior and competitor financial constraints. Using inter-firm patent citations and text-based product market similarities to identify intransitive competitor networks, we find that firms increase investment spending, patenting activity, and employee poaching when competitor constraints become more binding. In addition, firms shift their investment composition (product market and patent portfolios) towards competitors who experience a relative tightening in constraints. These effects are robust to controlling for selection and correlated effects across competitors. To mitigate endogeneity concerns, we exploit the 2004 AJCA tax holiday and the 1989 junk bond crisis as exogenous shocks to competitor constraints and find similar effects.
♦ Presented at the 2017 American Finance Association meetings in Chicago, Texas Christian University, the University of Texas at Austin, Michigan State University, and the 2015 Midwest Finance Association
A large literature explores whether asset returns comove in excess of what can be explained by fundamentals, therefore indicating the existence of frictions or behavioral biases. However, we show that comovement is a ubiquitous feature of asset returns that will arise in the presence of latent or mismeasured systematic factors. Thus, existing empirical tests cannot distinguish between alternate sources of comovement, and several documented interpretations of comovement in favor of particular explanations are premature and warrant reconsideration. We propose new statistical tests of excess comovement that account for latent factors and that exploit additional implications of market efficiency.
♦ Presented at the 2020 AFA meeting in San Diego, Emory University, Michigan State University, Rice University, Southern Methodist University, Texas Christian University, Tulane University, the University of Arizona, the University of Houston, the University of New Orleans, and the University of Texas at Dallas
Firm clustering is positively correlated with productivity, and it exhibits significant cross-sectional variation across industries. Thus, it is important to understand the industry characteristics that drive firms’ decisions to co-locate. We develop a model of knowledge sharing and derive the prediction that riskier and more complex industries experience the greatest gains from knowledge spillovers. Using tests that account for the nonrandomness of location decisions, we find a strong positive relationship between industry risk or complexity and the clustering of: 1) firms’ headquarters, 2) patent inventors, and 3) R&D expenses. Customer–supplier proximity is also significantly and positively related to industry risk and complexity.
♦Presented at the 2019 Urban Economics Association Conference in Philadelphia, the 2016 Regional Science Association International Conference, Michigan State University, and Tulane University
Does Economic Comparability Discipline Financial Reporting?, with Audra Boone, Rachel Li, and Parth Venkat
We exploit a pairwise measure of product market differentiation to study the relation between economic comparability and financial accounting fraud. We show that firms with greater economic comparability exhibit a significantly lower incidence of fraud. Importantly, this effect is economically larger than that of most predictors of fraud documented in the literature. To help establish identification, we exploit economic comparability with rivals issuing IPOs, as well as cross-sectional variation in accounting comparability, firm complexity, institutional ownership, and analyst coverage. Our analyses suggest that greater economic comparability enhances the external information environment, which improves external monitoring and disciplines manager reporting behavior.
♦Best Paper Award at the New Zealand Finance Meeting (2018). Also presented at Alabama, Clemson University, Drexel University, Michigan State University, the Sixth Annual Conference on Financial Market Regulation, Southern Methodist University, the University of Nevada Las Vegas, the 2018 Financial Management Association (best paper semi-finalist), the SEC, and the Australasian Finance and Banking Conference
Work in Progress
We adapt methods from spatial econometrics to explore the industrial scope of regional network effects in corporate decisions. These methods circumvent well-known challenges in estimating and interpreting empirical models of externalities. We find that cumulative regional network effects are roughly 4-5 times as important as own-firm effects for explaining corporate investment decisions, but only 1.2 and 1.5 times as important for financing decisions and firm performance, respectively. To explore whether these effects operate primarily within or across industry boundaries, we implement a novel structured network regression that allows for a (convex) combination of networks based on product market and supply chain relationships, in addition to regional proximity. We find that regional effects operate primarily within industry boundaries, and that outside of industry regional effects are only present (yet highly attenuated) for corporate investment decisions. These findings lend support to the urban specialization view of agglomeration economies proposed by Marshall (1920).
This paper uses the introduction of Transportation Networking Companies (TNC), such as Uber, to show that access to flexible sources of income facilitates entrepreneurship. TNCs give prospective entrepreneurs the ability to earn a substantive wage, which provides the financial assurance to start their new businesses. Because hours are set independently, entrepreneurs also maintain the temporal flexibility to work the unpredictable hours that characterize new ventures. We employ a difference-in-differences approach that exploits variation in the timing and location of TNC introductions and find evidence that the introduction of TNCs increases young firm employment and proprietorship. We also present survey-based evidence consistent with these findings; TNCs have provided artists, musicians, engineers and other entrepreneurs the financial and temporal flexibility to pursue their passions.