choose a country your own choice and collect time series data for at least three variabls. test for unit root and resolve unit root issue if exist. then use approperiat model to test the results
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This issue has received little attention in the literature in the past to the surprise of many. In fact, most studies assume that the initial value is either zero or bounded in analyzing the role of initialization when testing for a unit root in panel data. In response to this I prefer to consider a model in which the initialization is in the past, which is shown to have several distinctive features that makes it attractive, even in comparison to the common time series practice of making the initial value a draw from its unconditional distribution under the stationary alternative. The results have implications not only for theory, but also for applied work. In particular, and in contrast to the time series case, in panels the effect of the initialization need not be negative but can actually lead to improved test performance.