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Generalizations of the point‐optimal panel unit root tests of Moon, Perron and Phillips (MPP) are developed to cover cases of serially correlated errors. The resulting statistics involve two modifications relative to those of MPP: (a) the error variance is replaced by the long‐run variance;...
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. This latter test is equivalent to the well-known pooled t test proposed by Levin et al. (2002, Journal of Econometrics 108, 1--24), and its power depends only on the mean of the local-to-unity parameters. This implies that it has the same power against homogeneous and heterogeneous...
Persistent link: https://www.econbiz.de/10005100146
This paper studies nonstationarities in a panel of Canadian and US interest rates of different maturities and risk. We focus on methods which model the cross-sectional dependence within the panel as a linear dynamic factor model, and decompose our data into common and idiosyncratic components...
Persistent link: https://www.econbiz.de/10005582425
The asymptotic local powers of various panel unit root tests are investigated. The power envelope is obtained under homogeneous and heterogeneous alternatives. It is compared with asymptotic power functions of the pooled t-test, the Ploberger-Phillips (2002) test, and a point optimal test in...
Persistent link: https://www.econbiz.de/10005586905
This paper studies testing for a unit root for large n and T panels in which the cross-sectional units are correlated. To model this cross-sectional correlation, we assume that the data is generated by an unknown number of unobservable common factors. We propose unit root tests in this...
Persistent link: https://www.econbiz.de/10005729558
This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance...
Persistent link: https://www.econbiz.de/10005353140
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This paper studies the efficient estimation of seemingly unrelated linear models with integrated regressors and stationary errors. We consider two cases. The first one has no common regressor among the equations. In this case, we show that by adding leads and lags of the first differences of the...
Persistent link: https://www.econbiz.de/10009279884