The U.S. social security system faces funding pressure due to the aging of the population. This dissertation examines the welfare cost of social security reform and social security policy uncertainty under rational expectations and under learning. I provide an overview of the U.S. social security system in Chapter I.
In Chapter II, I construct an analytically tractable two-period OLG model with capital, social security, and endogenous government debt. I demonstrate the existence of steady states depends on social security parameters. I demonstrate a saddle-node bifurcation of steady states numerically, and demonstrate a transcritical bifurcation analytically. I show that if a proposed social security reform is large enough, or if the probability of reform is high enough, the economy will converge to a steady state.
In Chapter III, I develop a three-period lifecycle model. The model is inherently forward looking, which allows for more interesting policy analysis. With three periods, the young worker's saving-consumption decision depends on her expectation of future capital. This forward looking allows analysis of multi-period uncertainty. Analysis in the three-period model suggests that policy uncertainty may have lasting consequences, even after reform is enacted.
In Chapter IV, I develop two theories of bounded rationality called life-cycle horizon learning and finite horizon life-cycle learning. In both models, agents use adaptive expectations to forecast future aggregates, such as wages and interest rates. This adaptive learning feature introduces cyclical dynamics along a transition path, which magnify the welfare cost of changes in policy and policy uncertainty. I model policy uncertainty as a stochastic process in which reform takes place in one of two periods as either a benefit cut or a tax increase. I find the welfare cost of this policy uncertainty is less than 0.25% of period consumption in a standard, rational expectations framework. The welfare cost of policy uncertainty is larger in the learning models; the worst-off cohort in the life-cycle horizon learning model would be willing to give up 1.98% of period consumption to avoid policy uncertainty.
| Identifer | oai:union.ndltd.org:uoregon.edu/oai:scholarsbank.uoregon.edu:1794/23719 |
| Date | 06 September 2018 |
| Creators | Hunt, Erin |
| Contributors | Evans, George |
| Publisher | University of Oregon |
| Source Sets | University of Oregon |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Rights | All Rights Reserved. |
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