Research
Research
The effect of the stock market collapse during the 2007-2008 financial crisis on households' consumption decisions
This paper develops a new methodology for estimating a household's utility function from a micro-panel data without calibrating. According to the literature, a household's utility function is not identified from micro-panel data using the Euler equation estimation, due to the lack of variation in return on household savings caused by the shortness of time horizon of a micro-panel data. On the other hand, this study shows that a household's utility function can be identified from micro-panel data using the Euler equation estimation by explicitly taking into account the cross-sectional variation in the portfolio composition of household savings.
I evaluate the effects of the stock market collapse and the monetary policy change during the 2007-2008 financial crisis on households' consumption decisions as an application of this new methodology. I construct and estimate a dynamic model, where households optimally choose their stock market participation decisions, using the Panel of Study Income Dynamics (PSID) dataset to conduct this evaluation. I find that the stock market collapse and the monetary policy change during the recent financial crisis triggered a significant decrease in consumption inequality of households in the U.S
Working paper
Estimation of Relative Risk Aversion with wealth heterogeneity
In this paper, I estimate the relative risk aversion of households with different positions of wealth by using non-parametric structural estimation method. Relative risk aversion is an important measure of the extent of a household's reaction towards future uncertainty, and conventionally estimated as being constant across households. However, there can be a significant heterogeneity in risk aversion across households with dissimilar characteristics. I employ a combination of extremum estimation and non-parametric kernel estimation methods to estimate the degree of heterogeneous relative risk aversion varying across households with different wealth positions. Data for my analysis is sourced from the Panel Study of Income Dynamics for the US, and the Survey on Household Income and Wealth for Italy.
What are the main determinants of the home owning decision among households?
I model and estimate households’ home ownership decision making using the Panel of Study Income Dynamics (PSID) dataset following the framework of dynamic logit model from the life-cycle perspective. I estimate how households’ age and wealth position affect households’ home owning decision using the conditional choice probability estimation method. Moreover, I explicitly include households’ portfolio composition decision in the model as I consider that households hold three different types of assets such as the stock holding (risky asset), the home equity, and the risk-free asset (bond, cash, etc.). This enables to evaluate the spillover effects between the main financial markets of the stock market and the housing market on households’ decisions such as the portfolio composition decision, home ownership decision, and savings decision.