This paper surveys the literature on panel cointegration. It starts by dis- cussing cointegrating panel regressions for both cross-sectionally independent and correlated panels. It then introduces three groups of tests for panel coin-tegration : residual-based tests for the null of...

This paper derives Akaike?s (1973) Akaike information criterion (AIC), Hur- vich and Tsai?s (1989) corrected AIC, the Bayesian information criterion (BIC) of Akaike (1978) and Schwarz (1978), and Hannan and Quinn?s (1979) informa- tion criterion for factor models and studies the consistency...

This paper studies the performance of various forecasting models for Ko- rean inflation rates. The models studied in this paper are the AR(p) model, the dynamic predictive regression model with such exogenous variables as the un- employment rate and the term spread, the inflation target model,...

This paper studies the generalized principal component estimator (GPCE) of Choi (2007) for the factor model Xt = Ft + et where Ft is a unit-root process. First, this paper derives asymptotic distributions of the GPCEs of the factor and factor-loading spaces which show that the GPCE enjoys an...

In this paper, Mallows'(1973) Cp criterion, Akaike's (1973) AIC, Hurvich and Tsai's (1989) corrected AIC and the BIC of Akaike (1978) and Schwarz (1978) are derived for the leads-and-lags cointegrating regression. Deriving model selection criteria for the leads-and-lags regression is a...

This paper shows that spurious regression results can occur for a fixed effects model with weak time series variation in the regressor and/or strong time se- ries variation in the regression errors when the first-differenced and Within-OLS estimators are used. Asymptotic properties of these...

This paper considers the factor model Xt = Ft + et. Assuming a nor- mal distribution for the idiosyncratic error et conditional on the factors fFtg, conditional maximum likelihood estimators of the factor and factor- loading spaces are derived. These estimators are called generalized prin- cipal...