This thesis investigates panel unit root and cointegration tests with structural changes that are generalizations of their univariate counterparts. Small-sample properties of two well-established univariate test procedures are first assessed using the bootstrap approach. Extensions of these procedures in the panel framework are then examined.;The first chapter compares two types of univariate endogenous one-break unit root tests, namely the Dickey-Fuller (DF) type and the Schmidt-Phillips Lagrange Multiplier (LM) type tests. To investigate the small-sample properties of these tests, they are applied to the Nelson-Plosser macroeconomic time series with bootstrapped critical values used for unit root inference. Simulation results show that breaks under the null for the observed data are of sufficient magnitude to lead to size distortion for the DF-type tests, whereas the LM-type tests generally exhibit satisfactory size performance and possess the invariance property. Furthermore, in implementing the LM-type tests, the one that uses the minimum sum of squared residuals break selection method demonstrates better performance over the one that employs the minimum statistic break selection method.;The second chapter proposes LM type panel unit root test procedures with structural changes based on the group mean and combination test approaches. The proposed test procedures allow for breaks under both the null and alternative, and capture heterogeneity due to individual specific characteristics. The same set of distributions of the underlying individual LM statistics can be utilized to compute the panel statistics for the cases with no breaks and with intercept breaks as a result of the invariance property. Simulation results demonstrate that the inverse normal test exhibits the best overall finite-sample properties measured in terms of size and power. When break dates are unknown, the minimum sum of squared residuals break selection method is preferred. The bootstrap approach is suggested to account for cross-sectional dependence.;The third chapter studies panel cointegration tests dealing with two manifestations of structural changes, viz. breaks in the cointegrating relationship and breaks in the trend functions of time series. The importance of accounting for these breaks is highlighted using a simulation study. Finite-sample properties of the Gregory-Hansen (GH) type and LM type tests incorporating breaks in the cointegrating relationship are assessed. Two variants of the LM type tests are further examined in the presence of cross-sectional dependence taking on a factor structure. In the course of test comparison, some modifications are also suggested. A novel test procedure, based on the LM approach, is devised when trend functions of time series are subjected to breaks. Unlike existing tests, this procedure permits unknown breaks under both the null and alternative that can differ in locations among the variables under study.
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