Testing Slope Homogeneity in Quantile Regression Panel Data with an Application to the Cross-Section of Stock Returns

Antonio Galvao, Ted Juhl, Gabriel Montes-Rojas () and Jose Olmo

Journal of Financial Econometrics, 2018, vol. 16, issue 2, 211-243

Abstract: This article proposes tests for slope homogeneity across individuals in quantile regression fixed effects panel data models. The tests are based on the Swamy statistic. We establish the asymptotic null distribution of the tests under large panels. A prominent advantage of the proposed tests is that they are easy to implement in empirical applications. Monte Carlo experiments show evidence that the tests have good finite sample performance in terms of size and power. The tests are then applied to study the cross-section of firms’ excess asset returns using financial data on U.S. firms. The tests allow us to assess, for a given quantile of the distribution of excess returns, whether the linear effect of the pricing factors in standard linear asset pricing models is the same across stocks. The results confirm the validity of those models for the mean and central quantiles. However, for tail quantiles, the slope homogeneity tests reject the null hypothesis providing empirical evidence of pricing anomalies. This suggests that the effect of firm characteristics on the distribution of excess returns is heterogeneous across stocks during booms and busts.

Keywords: panel data; quantile regression; slope homogeneity; stock returns (search for similar items in EconPapers)
JEL-codes: C12 C23 G10 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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