National income taxation and the geographic distribution of population

Abstract

We study how different national taxation schemes interact with geographic variation in productivity and consumption amenities in determining regional populations. A neoclassical migration equilibrium model is used to analyze the current nominal income tax system in Norway. The analysis is based on estimated regional income differences accounting for both observable and unobservable individual characteristics and the value of experience. Given regional differences in incomes and housing prices, quality of life and productivity are calibrated to model equilibrium. Compared to an undistorted equilibrium with lump-sum taxation, nominal income taxation creates a disincentive to locate in productive high-income regions. The deadweight loss due to locational inefficiencies is 0.18% of gross domestic product (GDP). We study real income taxation and equal real taxes as alternative tax systems. Both alternatives generate a geographic distribution of the population closer to the undistorted equilibrium, and hence with lower deadweight loss. In an extension of the analysis, we take into account payroll taxes. The existing regionally differentiated payroll taxes to the disadvantage of cities generate a deadweight loss of 0.22% of GDP in an economy with lump-sum income taxation. The two distortionary taxes interact and strengthen each other and the combined distortionary effect of income and payroll taxation in the Norwegian system is 0.46% of GDP.

Appendices

Appendix 1: Hedonic regressions behind the regional measures of wages and housing costs

See Tables 6 and 7.

Table 6 Estimation of regional wages

Table 7 Estimation of regional housing costs

Appendix 2: Parameter values and model calibration

As described in Sect. 3, the model calibration is based on Norwegian data for wages, housing costs, taxes, and population across 89 labor market regions, together with data and stylized facts on model parameters. Values of all parameters are given in Table 8.

To establish the full equilibrium of the model, the remaining variables are calibrated based on the model equations given in Sect. 2. The price index $({\hat{p}}_j )$ and nominal tax payments $({\hat{T}}_j )$ follow directly from Eqs. (2) and (17), respectively. We do not have data on land rent $({\hat{r}}_j )$, so this variable is calculated from Eq. (12) under the assumption that productivity in the housing sector is equal across regions $({\hat{A}}_{Y,j} =0)$. The exogenous levels of quality of life $({\hat{Q}}_j )$ and traded sector productivity $({\hat{A}}_{X,j} )$ follow from Eqs. (4) and (11), respectively. We can then use Eqs. (1) and (3) to solve for per capita consumption of traded goods and housing (${\hat{x}}_j$ and ${\hat{y}}_j$, respectively). Given our data on regional population size $({\hat{N}}_j )$ housing production $({\hat{Y}}_j )$ follows from (16). Factor use in the housing sector $({\hat{L}}_{Y,j} ,{\hat{K}}_{Y,j} ,{\hat{N}}_{Y,j} )$ is calibrated from Eqs. (8)–(10). Labor demand in the traded sector $({\hat{N}}_{X,j} )$ follows from Eq. (15), and traded production $({\hat{X}}_j )$ from Eq. (7). Land and capital use in the traded sector $({\hat{L}}_{X,j} ,{\hat{K}}_{X,j} )$ are calibrated based on Eqs. (5) and (6). Finally, total supply of land and capital in region $j({\hat{L}}_j ,{\hat{K}}_j )$ follow from Eqs. (13) and (14).

Table 8 Calibrated model parameter values