This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and...

A panel data method is used to evaluate the impact of the Closer Economic Partnership Agreement (CEPA) signed between Mainland China and Hong Kong. Using the time series data of Hong Kong, Austria, Denmark, Finland, France, Germany, Italy, Japan, Korea, Netherlands, Norway, Singapore, Taiwan,...

We propose a panel data approach to disentangle the impact ofgone treatmenth from the gother treatmenth when the observed outcomes are subject to both treatments. We use the Great Hanshin-Awaji earthquake that took place on January 17, 1995 to illustrate our methodology. We find that there were...

We propose a panel data approach to disentangle the impact of “one treatment” from the “other treatment” when the observed outcomes are subject to both treatments. We use the Great Hanshin-Awaji earthquake that took place on January 17, 1995 to illustrate our methodology. We find that...

We use a quasi-likelihood function approach to clarify the role of initial values and the relative sample size of the cross-section dimension N and the time series dimension T on the asymptotic properties of estimators for dynamic panel data models with the presence of individual-specific...

We examine the asymptotic properties of IV, GMM or MLE to estimate dynamic panel data models when either N or T or both are large. We show that the Anderson and Hsiao (1981, 1982) simple instrumental variable estimator (IV) or maximizing the likelihood function with initial value distribution...

This note discusses the pros and cons of using the conditional mean approach of Mundlak (1978) and Chamberlain (1980) and the linear difference approach to deal with the incidental parameters issue in estimating fixed effects dynamic panel data models. The importance of the data generating...

This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and...

This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and...