02 Jun Question 1. Your textbook modifies the four assumptions for the multiple regression model by adding a newassumption. This represents an extension of the
Question
1. Your textbook modifies the four assumptions for the multiple regression model by adding a newassumption. This represents an extension of the cross-sectional data case, where errors areuncorrelated across entities. The new assumption requires the errors to be uncorrelated across time,conditional on the regressors as well (cov(uit, uis Xit, Xis) = 0 for t ? s.).
(a) Discuss why there might be correlation over time in the errors when you use U.S. state panel data. Does this mean that you should not use OLS as an estimator?
(b) Now consider pairs of adjacent states such as Indiana and Michigan, Texas and Arkansas, New York and Connecticut, etc. Is it likely that the fifth assumption will hold here, even though the “contemporaneous” errors are correlated? If not, can you still use OLS for estimation?
2) . A study attempts to investigate the role of the various determinants of regional Canadianunemployment rates in order to get a better picture of Canadian aggregate unemployment rate behavior. The annual data (1967-1991) is for five regions (Atlantic region, Quebec, Ontario, Prairies, and British Columbia), and four age-gender groups (female and male, adult and young). Focusing on young females, the authors find significant effects for the following variables: the regional relative minimum wage rate (minimum wages divided by average hourly earnings), the regional share ofyouth in the labor force, the regional share of adult females in the labor force, United States activityshocks (deviations of United States GDP from trend), an indicator of the degree of monetary tightnessin Canada, regional union density, and a regional index of unemployment insurance generosity.
Explain why the authors only used region fixed effects. How would their specification have to changeif they also employed time fixed effects?
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