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This chapter studies estimation and inference methods for multi-dimensional quantile regression panel data models. First, we discuss the fixed effects (FE) model. This model imposes a relatively restrictive asymptotic condition on the growth of the time series dimension relative to the cross section dimension. Nevertheless, extending the FE to three or more dimensions allows for larger data availability, and might help to relax the stringent condition on the time series. We also present a model for the smoothed FE quantile regression case. Second, we present a random effects (RE) model. This model has the advantage of allowing for small time-series dimension. Finally, we present a correlated RE model. In this case, the unobservable individual-specific effects are modeled as a function of observables and a disturbance. Fil: Galvao, Antonio F.. No especifíca; Fil: Montes Rojas, Gabriel Victorio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Regression models relating investment demand with firms’ Tobin's q and cash flow are fraught with measurement errors which, in turn, cause endogeneity bias. We propose an alternative solution to this problem based on modelling the interaction between the endogenous Tobin's q and the error term in the investment equation as a function of lagged values of Tobin's q. We then study the identification conditions and asymptotic properties of the resulting estimator. Our analysis of a panel of US firms reveals a larger effect of Tobin's q on firms’ investment demand than that obtained by using available estimators in the literature. Moreover, the estimates highlight the importance of cash flow. We find mixed evidence on the relationship between investment demand and firms’ cash flow with respect to different measures of financial constraints. Nevertheless, this evidence is more supportive of the view that firms’ cash flows have a weaker correlation to investment demand when financial conditions tighten. Fil: Galvao, Antonio F.. University of Arizona; Estados Unidos Fil: Montes Rojas, Gabriel Victorio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Interdisciplinario de Economía Política de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Económicas. Instituto Interdisciplinario de Economía Política de Buenos Aires; Argentina Fil: Olmo, Jose. University of Southampton; Reino Unido Fil: Song, Suyong. University of Iowa; Estados Unidos

This paper proposes an alternative solution to the endogeneity problem by explicitly modeling the joint interaction of the endogenous variables and the unobserved causes of the dependent variable as a function of additional observables. We derive identification of the parameters, develop an estimator, and establish its consistency and asymptotic normality. Fil: Galvao, Antonio F.. University of Iowa; Estados Unidos Fil: Montes Rojas, Gabriel Victorio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Interdisciplinario de Economía Política de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Económicas. Instituto Interdisciplinario de Economía Política de Buenos Aires; Argentina Fil: Song, Hojun. University of Iowa; Estados Unidos

This paper proposes an empirical asset pricing test based on the homogeneity of the factor risk premia across risky assets. Factor loadings are considered to be dynamic and estimated from data at higher frequencies. The factor risk premia are obtained as estimates from time series regressions applied to each risky asset. We propose Swamy-type tests robust to the presence of generated regressors and dependence between the pricing errors to assess the homogeneity of the factor risk premia and the zero intercept hypothesis. An application to US industry portfolios shows overwhelming evidence rejecting the capital asset pricing model, and the three and five factor models developed by Fama and French (Journal of Financial Economics, 1993, 33, 3?56; Journal of Financial Economics, 2015, 116, 1?22). In particular, we reject the null hypotheses of a zero intercept, homogeneous factor risk premia across risky assets, and the joint test involving both hypotheses. Fil: Galvao, Antonio F.. University of Arizona; Estados Unidos Fil: Montes Rojas, Gabriel Victorio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Interdisciplinario de Economía Política de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Económicas. Instituto Interdisciplinario de Economía Política de Buenos Aires; Argentina Fil: Olmo, José. University of Southampton; Reino Unido

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. Fil: Galvao, Antonio F.. University of Iowa; Estados Unidos Fil: Juhl, Ted. University of Kansas; Estados Unidos Fil: Montes Rojas, Gabriel Victorio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Interdisciplinario de Economía Política de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Económicas. Instituto Interdisciplinario de Economía Política de Buenos Aires; Argentina. Universidad de San Andrés; Argentina Fil: de Olmos, Jose Severo Ramon. University of Southampton; Reino Unido

We propose to model endogeneity bias using prior distributions of moment conditions. The estimator can be obtained both as a method-of-moments estimator and in a Ridge penalized regression framework. We show the estimator's relation to a Bayesian estimator. Fil: Montes Rojas, Gabriel Victorio. Universidad de San Andrés; Argentina. City University of London; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Galvao, Antonio F.. University of Iowa; Estados Unidos