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 on the fact that...

In this paper we test for the existence of a long-run savings-investments relationship in 18 OECD economies over the period 1970-2007. Although individual modelling provides only very weak support to the hypothesis of a link between savings and investments, this cannot be ruled out as individual...

This article analyzes the main existing theories on income and population city growth: the existence of increasing returns to scale, the importance of locational fundamentals, and random growth. To do this we develop a nonlinearity test that is implemented to a dataset on urban, climatological...

The purpose of this paper is twofold: 1) to highlight the widely ignored but fundamental problem of ‘superpopulations’ for the use of inferential statistics in development studies. We do not to dwell on this problem however as it has been sufficiently discussed in older papers by...

Constant factor loadings is a standard assumption in the analysis of large dimensional factor models. Yet, this assumption may be restrictive unless parameter shifts are mild. In this paper we develop a new testing procedure to detect big breaks in factor loadings at either known or unknown...

This article analyzes empirically the main existing theories on income and population city growth: increasing returns to scale, locational fundamentals and random growth. To do this we implement a threshold nonlinearity test that extends standard linear growth regression models to a dataset on...

The paper proposes statistics to test the null hypothesis of no cointegration in panel data when common factors drive the cross sectional dependence. We consider both the case in which regressors are independent of the common factors and the case in which regressors are correlated with the...

The purpose of this study is to provide guidance to those who analyze data from repeated-game experiments. In particular, I propose the use of heteroskedasticity-autocorrelation consistent (HAC) covariance estimators for panel data, which allows researchers to conduct hypothesis tests without...

We evaluate whether a lack of guidance on how to choose the matching variables used in the Synthetic Control (SC) estimator creates specification-searching opportunities. We first provide theoretical results showing that specification-searching opportunities would be asymptotically irrelevant...

We show that existing inference methods used in Differences-in-Differences might not perform well with few treated groups and heteroskedastic errors. This is restrictive because variation in the number of observations per group inherently leads to heteroskedasticity in the group x time aggregate...