Asymptotic power of the sphericity test under weak and strong factors in a fixed effects panel data model

This paper studies the asymptotic power for the sphericity test in a Öxed e§ect panel data model proposed by Baltagi, Feng and Kao (2011), (JBFK). This is done under the alternative hypotheses of weak and strong factors. By weak factors, we mean that the Euclidean norm of the vector of the factor loadings is O(1). By strong factors, we mean that the Euclidean norm of the vector of factor loadings is O(√n), where n is the number of individuals in the panel. To derive the limiting distribution of JBFK under the alternative, we Örst derive the limiting distribution of its raw data counterpart. Our results show that, when the factor is strong, the test statistic diverges in probability to inÖnity as fast as Op(nT). However, when the factor is weak, its limiting distribution is a rightward mean shift of the limit distribution under the null. Second, we derive the asymptotic behavior of the di§erence between JBFK and its raw data counterpart. Our results show that when the factor is strong this difference is as large as Op(n). In contrast, when the factor is weak, this di§erence converges in probability to a constant. Taken together, these results imply that when the factor is strong, JBFK is consistent, but when the factor is weak, JBFK is inconsistent even though its asymptotic power is nontrivial

Fixed Effect Estimation of Large T Panel Data Models

This article reviews recent advances in fixed effect estimation of panel data models for long panels, where the number of time periods is relatively large. We focus on semiparametric models with unobserved individual and time effects, where the distribution of the outcome variable conditional on covariates and unobserved effects is specified parametrically, while the distribution of the unobserved effects is left unrestricted. Compared to existing reviews on long panels (Arellano and Hahn 2007; a section in Arellano and Bonhomme 2011) we discuss models with both individual and time effects, split-panel Jackknife bias corrections, unbalanced panels, distribution and quantile effects, and other extensions. Understanding and correcting the incidental parameter bias caused by the estimation of many fixed effects is our main focus, and the unifying theme is that the order of this bias is given by the simple formula p/n for all models discussed, with p the number of estimated parameters and n the total sample size.Comment: 40 pages, 1 tabl

Parameter heterogeneity, persistence and cross-sectional dependence: new insights on fiscal policy reaction functions for the Euro area

A number of novelties have emerged in the study of the discretionary fiscal policy within the Euro area during the last decade. Among the others, the availability of up-to-date information on fiscal indicators for the years following the Great Recession, the introduction of cutting-edge econometric methods, and a renewed interest about the sustainability of fiscal policy and public debt. The aim of this paper is to address the challenges posed by the estimation of the discretionary fiscal reaction function for the Euro area. We exploit recently introduced testing and estimation strategies for heterogeneous dynamic panels with cross-sectional dependence and propose a new parsimonious approach. Using real-time data over the period 1996-2016, we investigate whether the fiscal policy reaction function is still a benchmark after the Great Recession. We find evidence of strong cross-sectional dependence in the panel, and clear support to a valid cointegration relationship among the main determinants of the function. Newly added covariates, such interest rate spreads, come out to play a relevant role in explaining discretionary actions

Semi-Autonomous Revenue Authorities in Sub-Saharan Africa: Silver Bullet or White Elephant

A major component of tax administration reform in sub-Saharan Africa for the last 30 years has been the creation of semi-autonomous revenue authorities (SARAs). The effects of their creation on revenue performance have been much debated, although there are only a few quantitative studies. The core argument of this paper is that existing research suggesting diverse and contradictory outcomes has not taken account of trends in revenue performance in the years before the establishment of SARAs. Allowing for this revenue history our analysis based on 46 countries over the period 1980-2015 provides no robust evidence that SARAs induce an increase in revenue performance. This does not imply that SARAs may not provide benefits for tax collection, but they do not demonstrably increase (or decrease) revenue collected