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This paper proposes new unit root tests in the context of a random autoregressive coefficient panel data model, in which the null of a unit root corresponds to the joint restriction that the autoregressive coefficient has unit mean and zero variance. The asymptotic distributions of the test...
Persistent link: https://www.econbiz.de/10010574088
Using data covering 38 countries across the 1965–2005 period, this paper shows that former British colonies tend to exhibit higher levels of carbon dioxide emission than other countries.
Persistent link: https://www.econbiz.de/10010576438
Persistent link: https://www.econbiz.de/10010581441
Practitioners are generally well aware of the fact that most standard approaches for estimation and inference in panel data regressions are based on assuming that the cross-sectional units are independent of each other, an assumption that is surely mistaken in applications, especially in...
Persistent link: https://www.econbiz.de/10010709129
It is well known that in the context of the classical regression model with heteroskedastic errors, while ordinary least squares (OLS) is not efficient, the weighted least squares (WLS) and quasi-maximum likelihood (QML) estimators that utilize the information contained in the heteroskedasticity...
Persistent link: https://www.econbiz.de/10010709950
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This article proposes new unit root tests for panels where the errors may be not only serial and/or cross-correlated, but also unconditionally heteroscedastic. Despite their generality, the test statistics are shown to be very simple to implement, requiring only minimal corrections and still the...
Persistent link: https://www.econbiz.de/10010825846
This paper proposes a new unit root test in the context of a random autoregressive coefficient panel data model, in which the null of a unit root corresponds to the joint restriction that the autoregressive coefficient has unit mean and zero variance. The asymptotic distribution of the test...
Persistent link: https://www.econbiz.de/10008566276
This paper proposes two new unit root tests that are appropriate in the presence of an unknown number of structural breaks. One is based on a single time series and the other is based on a panel of multiple series. For the estimation of the number of breaks and their locations, a simple...
Persistent link: https://www.econbiz.de/10008566277