<p> The financial economics profession has determined that identical agents in a dynamic, stochastic, general equilibrium (DSGE) model does not provide price and trading dynamics realized in financial markets. There has been quite a bit of research over the last three decades extending heterogeneity to the Lucas asset pricing framework, to address this issue. Once the assumption of homogeneous agents is relaxed, the problem becomes increasingly complex due to a state space including the wealth distribution, continuation utilities, and wealth distribution dynamics. To establish a more computationally feasible model, specical modifications have been made such as heterogeneity in idiosyncratic shocks and not risk aversion, including aggregate or idiosyncratic risk (but not both), or assuming no growth in the economy (steady state). </p><p> In this research, I will define a DSGE model with heterogeneous agents. This heterogeneity will refer to differing CRRA utilities through risk aversion. The economy will have growth due to the assumed dividend process. Agents will face idiosyncratic and aggregate shocks in a complete markets setting. The framework of the provided algorithm will enable issues to be addressed beyond homogeneous agent models. </p><p> The numerical simulation results of this model provide considerable asset price volatility and high trading volume. These results occur even in the complete markets setting, where investors are expected to fully insure. Given these dynamics from the simulations of the algorithm, I demonstrate the ability to calibrate this model to address specific financial economic issues, such as the equity premium puzzle. More importantly this exercise will assume realistic agent parameters of risk aversion and discount factors, relative to economic theory.</p>
Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:3638074 |
Date | 30 October 2014 |
Creators | Schmerbeck, Aaron J. |
Publisher | The Florida State University |
Source Sets | ProQuest.com |
Language | English |
Detected Language | English |
Type | thesis |
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