Date of Degree
PhD (Doctor of Philosophy)
Gustavo J. Ventura
I study the role of heterogeneity and idiosyncratic risk in Macroeconomics, and their implications on problems of income taxation. In the first chapter, I study the effects of redistributive taxation in an incomplete market economy with heterogeneous agents and idiosyncratic risk. I focus on the role of distortions in labor supply decisions and the interplay of heterogeneity and uninsurable idiosyncratic shocks, conducting the first general equilibrium analysis of a Negative Income Tax (NIT). I show that a NIT is a serious candidate to replace the current income tax in the United States. I find that the optimal NIT has a marginal tax rate of 28% and a transfer of 10% of per capita GDP, roughly $4600.
The welfare gains of replacing the current US income tax with a NIT are equivalent to a 6.3% increase in annual consumption in every state of the world. Low-ability agents, in the bottom quintile of the productivity distribution, benefit the most, while high-ability agents are worse off. A consequence of the reform is that the composition of the labor force changes, with high-productivity agents working more, in relative terms, than low-productivity agents. Finally, I find that the riskier the economy, the higher the welfare gains of the NIT as a provider of public insurance.
In the second chapter, I study labor income dynamics over the life cycle and introduce a novel methodology that can detect the presence of patterns in the idiosyncratic earnings shocks and recognize economic forces in action. Using a sample from the Panel Study of Income Dynamics (PSID), I estimate a Bayesian Logistic Smoothed Transition Autoregressive model of order 1 (LSTAR(1)) with a rich level of heterogeneity in the innovations. I find that there is a life-cycle pattern in the earning shocks: before the age 29, young workers experience shocks with higher variance and a positive probability of lower persistence than older workers. A comparison with conventional models shows that an incorrect model specification introduces bias in the estimates. The proposed model can be easily approximated with a discrete Markov process. This means that this model can be used by macroeconomists to calibrate income processes.
Copyright 2012 Martin Eduardo Lopez Daneri
Lopez Daneri, Martin Eduardo. "Essays on income taxation and idiosyncratic risk.." dissertation, University of Iowa, 2012.