A Discussion Paper version can be found here.
Abstract: We study a small open economy displaying Pareto-distributed wealth resulting from random death. The government runs a distribution scheme on inheritance. We present the mathematical background that allows to study the dynamics of means. We end up with ordinary differential equations for the mean of age and of individual and government wealth. We also study distributional dynamics analytically. Starting from any distribution of age and wealth, the aggregate distribution converges, both on a transition path towards a steady state and on a transition path towards balanced growth, to an exponential distribution of age and a Pareto-distribution of wealth. The findings are illustrated for different distribution schemes.
A Discussion Paper version can be found here. A Poster can be found here.
Abstract: We study the effect of bequests and their taxation on wealth inequality. We allow for random death and birth in a continuous-time, dynastic framework. Individuals behave optimally and accumulate wealth over their lifetime. Bequests above a tax exemption threshold are taxed according to a fixed rate. We derive a stochastic differential equation modeling dynastic wealth and obtain an analytical expression for the coefficient of variation. By calibrating our model to German wealth data, we utilize these analytical results to project empirical wealth inequality across various bequest tax rates and tax exemption thresholds. Most notably, our results indicate that a combination of a high tax exemption threshold paired with a high bequest tax rate reduces wealth inequality strongest when considering revenue-neutral alterations.
A Discussion Paper version can be found here. A Poster can be found here.
Abstract: Using data from the German Socio-Economic Panel, this paper examines how socioeconomic characteristics shape the distribution of happiness in Germany and how these effects translate into happiness inequality. I estimate quantile regressions for 2012 and show that key socioeconomic characteristics affect happiness differently across the happiness distribution. Building on this heterogeneity, I construct a counterfactual 2017 happiness distribution by evaluating the 2017 covariate distribution under the estimated 2012 quantile-regression coefficient structure. I then examine happiness inequality and find that, despite the stability of observed happiness inequality in the data, the counterfactual distribution predicts a more equal distribution of happiness, especially according to the Gini coefficient. To reconcile observed and counterfactual inequality, I distinguish between a mechanical effect arising from changes in observed characteristics under the estimated model and a residual effect capturing the remaining deviation. The results suggest that the persistence of happiness inequality reflects residual factors not captured by observed covariates or by systematic changes in estimated returns.