Factor models have been widely used in practice. However, an undesirable feature of a high dimensional factor model is that the model has too many parameters. An effective way to address this issue, proposed in a seminar work by Tsai and Tsay (2010), is to decompose the loadings matrix by a...

This paper investigates efficient estimation of heterogeneous coefficients in panel data models with common shocks, which have been a particular focus of recent theoretical and empirical literature. We propose a new two-step method to estimate the heterogeneous coefficients. In the first step,...

The factor-augmented vector autoregressive (FAVAR) model, first proposed by Bernanke, Bovin, and Eliasz (2005, QJE), is now widely used in macroeconomics and finance. In this model, observable and unobservable factors jointly follow a vector autoregressive process, which further drives the...

The theme of my dissertation is emerging capital markets behavior. I utilize three approaches: institutional, experimental and econometric to study the impact of reforms on capital allocation and stock market operation.In Chapter one, using a unique data set on Chinese provincial savings and...

The theme of my dissertation is emerging capital markets behavior. I utilize three approaches: institutional, experimental and econometric to study the impact of reforms on capital allocation and stock market operation.In Chapter one, using a unique data set on Chinese provincial savings and...

An approximate factor model of high dimension has two key features. First, the idiosyncratic errors are correlated and heteroskedastic over both the cross-section and time dimensions; the correlations and heteroskedasticities are of unknown forms. Second, the number of variables is comparable or...

An approximate factor model of high dimension has two key features. First, the idiosyncratic errors are correlated and heteroskedastic over both the cross-section and time dimensions; the correlations and heteroskedasticities are of unknown forms. Second, the number of variables is comparable or...

This paper considers the maximum likelihood estimation of the panel data models with interactive effects. Motivated in economics and other social sciences, a notable feature of the model is that the explanatory variables are correlated with the unobserved effects. The usual within-group...

This note is intended for researchers who want to use the interactive effects model for empirical modeling. We consider how to estimate interactive effects models when some of the factors and factor loading are observable. Observable factors are common regressors which do not vary across...

Spatial panel data models are widely used in empirical studies. The existing theories of spatial models so far have largely confine the analysis under the assumption of parameters stabilities. This is unduely restrictive, since a large number of studies have well documented the presence of...