Panel regression with nonstationary variables
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I examine the panel regression when variables are nonstationary. Using nonstationary variables might cause the spurious regression problem. A spurious relationship or spurious regression is a mathematical relationship in which two or more events or variables are not causally related to each other, yet it may be wrongly inferred that they are, due to either coincidence or the presence of a certain third, unseen factor. In this research, I start by examining the definition of stationary and nonstationary variables and then I move on to cointegration relationship in time series. Then I examine different methods we should use in different scenarios. I investigate the same problems in panel data. Next, I examine motivations behind remittances and I provide an empirical model that how workers' remittances and host and home countries GNI per capita are nonstationary variables and then I prove that there is a cointegration relation between them. Then I compare the results of the OLS regression with Fully-Modified OLS and Dynamic OLS and conclude that the results are almost similar.