Tax rate to maximize the revenue: Laffer curve for the Czech Republic

Abstract

The aim of this article is to model the relationship between the rate of personal income tax and the revenue it generates, and to derive a tax rate that would maximize this revenue within the Czech Republic, using methodologies described in earlier works (Hsing, 1996). This tax rate represents an upper limit. Overstepping it has negative consequences for corporate fi nances and government budgetary funding alike, because it undermines the workers motivation to work, reduces buying power, and shifts work activities in favor of gray economy. The period of interest is a time series from 1993 to 2010. Two models were devised. The basic research instrument was a second-degree polynomial regression with a logarithmic transformation of the input data. The explaining variable was the tax revenue, the explanatory variable in Model 1 was the ratio of tax revenue to personal gross annual income. Model 2 featured the ratio of tax revenue to gross domestic product. To limit model instability, all data was stated per capita, in 2010 prices. Both models are statistically signifi cant. By comparison, it was determined that, in the period of 1994–2010, the historical tax rate was lower than the rate designed to maximize the revenue. It approached the theoretical optimum most closely in 2007, and deviated from it most severely in 1995.

The aim of this article is to model the relationship between the rate of personal income tax and the revenue it generates, and to derive a tax rate that would maximize this revenue within the Czech Republic, using methodologies described in earlier works (Hsing, 1996). This tax rate represents an upper limit. Overstepping it has negative consequences for corporate fi nances and government budgetary funding alike, because it undermines the workers motivation to work, reduces buying power, and shifts work activities in favor of gray economy. The period of interest is a time series from 1993 to 2010. Two models were devised. The basic research instrument was a second-degree polynomial regression with a logarithmic transformation of the input data. The explaining variable was the tax revenue, the explanatory variable in Model 1 was the ratio of tax revenue to personal gross annual income. Model 2 featured the ratio of tax revenue to gross domestic product. To limit model instability, all data was stated per capita, in 2010 prices. Both models are statistically signifi cant. By comparison, it was determined that, in the period of 1994–2010, the historical tax rate was lower than the rate designed to maximize the revenue. It approached the theoretical optimum most closely in 2007, and deviated from it most severely in 1995.