Thursday, September 10, 2015
Jason Oh (UCLA) & Christopher Tausanovitch (UCLA), Quantifying Legislative Uncertainty: A Case Study in Tax Policy, 69 Tax L. Rev. ___ (2016):
Whether a legislature will or will not enact law is often uncertain. This Article offers an empirical model for quantifying that uncertainty, and it develops this argument in the context of federal income tax rates. Specifically, we estimate a model of legislator preferences on tax rates and show that the political process can be well understood in terms of the preferences of key legislators. We use our statistical model to quantify the uncertainty of tax rates and forecast the direction of likely rate changes in the future.
This argument has several implications for policymaking and the analysis of legislative uncertainty more generally. First, quantifying legislative uncertainty offers insight into the behavioral effects of the law. How people respond to the law depends on their perception of the law’s future trajectory. Second, our analysis allows us to explore the stability of major legislative reform. Our methodology allows us to demonstrate that reforms are sometimes predictably unstable. Such reforms can have the perverse result of increasing future legislative uncertainty.