The random coefficient approach for estimating tax revenue stability and growth

The issue of tan revenue stability and growth has been of concern to policy makers and economists for many years. One important focus of the literatur e is the optimal tax portfolio, which assumes that revenue variance is enti rely unpredictable. However as evidenced by Fox and Campbell, some revenue variance arising from changes in economic conditions is predictable. The pu rpose of this study is to revisit Fox and Campbell's work. They studied rev enue growth and stability with a efficient model (FCM). This study uses a r andom coefficient model (RCM). The RCM approach appears to provide improved estimates and confirms the conclusions of their earlier work. The response of short-run elasticities to the business cycle appears both strong and va riable across commodities, and no single commodity dominates revenue growth or stability. Although this study supports the design of an optimal tax po rtfolio, it emphasizes the need to explicitly model for economic: condition s and to continually adjust the tax portfolio. However given the political and budgetary process, these adjustments may not be feasible.