This article describes a new Stata routine, xtcsd, to test for the presence of cross-sectional dependence in panels with many cross-sectional units and few time-series observations. The command executes three different testing procedures-namely, Friedman's (Journal of the American Statistical Association 32: 675-701) (FR) test statistic, the statistic proposed by Frees (Journal of Econometrics 69: 393-414), and the cross-sectional dependence (CD) test of Pesaran (General diagnostic tests for cross-section dependence in panels [University of Cambridge, Faculty of Economics, Cambridge Working Papers in Economics, Paper No. 0435]). We illustrate the command with an empirical example.

This paper develops a new method for testing for Granger non-causality in panel data models with large cross-sectional (N) and time series (T) dimensions. The method is valid in models with homogeneous or heterogeneous coefficients. The novelty of the proposed approach lies in the fact that under the null hypothesis, the Granger-causation parameters are all equal to zero, and thus they are homogeneous. Therefore, we put forward a pooled least-squares (fixed effects type) estimator for these parameters only. Pooling over cross sections guarantees that the estimator has a $$\sqrt{NT}$$ NT convergence rate. In order to account for the well-known “Nickell bias”, the approach makes use of the well-known Split Panel Jackknife method. Subsequently, a Wald test is proposed, which is based on the bias-corrected estimator. Finite-sample evidence shows that the resulting approach performs well in a variety of settings and outperforms existing procedures. Using a panel data set of 350 U.S. banks observed during 56 quarters, we test for Granger non-causality between banks’ profitability and cost efficiency.

Despite an abundance of empirical evidence on crime spanning over 40 years, there exists no consensus on the impact of the criminal justice system on crime activity. We construct a new panel data set that contains all relevant variables prescribed by economic theory. Our identification strategy allows for a feedback relationship between crime and deterrence variables, and it controls for omitted variables and measurement error. We deviate from the majority of the literature in that we specify a dynamic model, which captures the essential feature of habit formation and persistence in aggregate behaviour. Our results show that the criminal justice system exerts a large influence on crime activity. Increasing the risk of apprehension and conviction is more influential in reducing crime than raising the expected severity of punishment.

Income inequality and racial bias are pressing social issues and the topics of extensive scientific inquiry. Recent increases in income inequality (Piketty & Saez, 2014) have sparked investigations into its impacts on individual and societal well-being (e.g., Wilkinson & Pickett, 2009). Meanwhile, the persistence of racial bias continues to motivate studies of its psychological, social, and institutional precursors and consequences (e.g., Alexander, 2012). Several social-scientific theories converge on the hypothesis that income inequality may increase racial bias. Epidemiologists Wilkinson and Pickett argue that income inequality intensifies social hierarchies, motivating status seeking via derogation and the subordination of lower status others (Wilkinson, 2005). Given that race is intimately associated with social status in the United States (Moller, Alderson, & Nielsen, 2009), this suggests that income-inequality-related processes should increase racial prejudice among dominant racial-group members. Two prominent social psychological theories-socialdominance theory (Sidanius & Pratto, 2001) and systemjustification theory (Jost, Banaji, & Nosek, 2004)-converge on this hypothesis as well, positing that racism functions as a legitimizing myth or mode of rationalization used to justify group-based social hierarchies. To the extent that income inequality is linked with income differences between racial groups, social-dominance theory and system-justification theory predict that income inequality will breed racial bias among members of dominant racial groups. Marxist accounts of economic inequality posit that income inequality leads wealthy elites to promote racial division among the working classes to prevent unified labor movements (Reich, 1983).