This paper considers spatial autoregressive panel data models and extends their analysis to the case where the spatial coefficients differ across the spatial units. It derives conditions under which the spatial coefficients are identified and develops a quasi maximum likelihood (QML) estimation...

This paper proposes a regularisation method for the estimation of large covariance matrices that uses insights from the multiple testing (MT) literature. The approach tests the statistical significance of individual pair-wise correlations and sets to zero those elements that are not...

The presence of cross-sectionally correlated error terms invalidates much inferential theory of panel data models. Recently work by Pesaran (2006) has suggested a method which makes use of cross-sectional averages to provide valid inference for stationary panel regressions with multifactor error...

This paper considers alternative approaches to the analysis of large panel data models in the presence of error cross section dependence. A popular method for modelling such dependence uses a factor error structure. Such models raise new problems for estimation and inference. This paper compares...

We use data from Public Opinion Surveys on Household Financial Assets and Liabilities from 1991 to 2002 to investigate the issues of unobserved heterogeneity among cross-sectional units and stability of Japanese aggregate money demand function. Conditions that permit individual data and...

This paper uses an unbalanced panel dataset to evaluate how repeated job search services (JSS) and other personal characteristics affect the quarterly earnings of the prime-age female welfare recipients in the State of Washington. We propose a joint dependent framework for the probability of...