RESEARCH

Selected Working Papers

Coauthored with Ioannis Floros and Shane Johnson 

Abstract:  We hypothesize that firms required by SFAS No. 131 to begin disclosing segment information attempt to counteract potential competitive harm by increasing information redaction. Using a difference-in-difference setting, we find that firms increasing the number of reported segments after the rule change exhibit a greater increase in information redaction than firms maintaining the same number of reported segments. Consistent with concerns about competitive harm driving the changes, the significant increases are concentrated in firms with greater divergence in profitability across segments, higher abnormal profitability, and negative abnormal stock returns in response to the SFAS No. 131 finalization. In addition, the firms that observables predict would increase information redaction, but did not, experience decreases in sales growth and profit margin. Our results highlight a way firms act to offset changes in mandatory disclosure. They have implications for understanding disclosure and shed light on firms’ motives for employing confidential treatment of information.

Employee Protection and Financial Reporting Quality 

Coauthored with Anwer Ahmed, Sarah Noor, and Nina Xu 

Abstract:  In this study, we exploit the staggered state adoptions of wrongful discharge laws (WDLs) to study the effect of employment protection on financial reporting quality. Using a generalized difference-in-differences model, we find that treatment firms improve financial reporting quality (measured by absolute discretionary accruals and incidences of small profits) after the adoption of WDLs. We further find that the effect is stronger for firms with greater incentives to reduce information processing costs and for firms that are more affected by employment protection, consistent with the idea that managers improve financial reporting quality to mitigate higher information processing costs resulting from employment protection. Our study offers novel insights into the causal effect of employment protection on financial reporting quality.

Measuring Expected Volatility Using Earnings Line Items as Risk Exposures

Coauthored with Jeremiah Green

Abstract:  We exploit the cross-section of income statement line items to create a measure, sigma, of a firm's ex-ante systematic risk. Sigma captures firm-year risk by combining income statement items with the variance-covariance matrix of line-item-related systematic risk factors. In addition to capturing systematic risk, sigma has an intuitive interpretation - the risk-driven standard deviation of expected changes in earnings. Sigma is positively associated with the volatility of earnings, CAPM beta, and earnings beta; however, it incrementally explains the cross-section of expected returns, with an annualized difference of three-factor equal(value)-weighted alpha of 6.1%(10.1%) between the highest and the lowest decile-ranked sigmas. Sigma explains returns when analysts' forecasts are not available and performs better for low profitability firms for which time varying risk exposure and multifaceted risk exposure are likely to be important. 

Do Inter-Industry Common Owners Facilitate Inter-Industry Information Sharing?

solo-authored

Abstract: I investigate whether common owners with industry expertise facilitate information sharing from a connected foreign industry (i.e., an industry different from a focal firm's own but linked to the firm by common ownership) to a focal firm, and I study the consequences of such inter-industry information sharing. Using a quasi-exogenous institutional merger and a difference-in-differences design, I document that common owners facilitate inter-industry information sharing, measured by return synchronicity between a focal firm and a foreign industry. The effect is particularly evident when common owners have higher expertise in the foreign industry, when focal firms have fewer foreign connections, when foreign industries have higher growth opportunities, or when interacting firm-to-industry pairs are more complementary. Further tests show that affected firms have better operating performance, and that affected firms' business activities are more sensitive to those of connected foreign industries. The results imply that common owners facilitate inter-industry information sharing that creates value for markets but impedes diversification for themselves.

Publication

Coauthored with Jeremiah Green

Abstract:  We selectively review recent advancements in research on predictive models of earnings and returns. We discuss why applying statistical, econometric, and machine learning advancements to forecasting earnings and returns presents difficult challenges. In the context of these challenges, we discuss recent papers that confront the challenges and present promising advancements and paths for future research. 

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