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Date of Award

Spring 5-15-2018

Author's School

Graduate School of Arts and Sciences

Author's Department


Degree Name

Doctor of Philosophy (PhD)

Degree Type



The first part of this dissertation explores an empirical relevance to understand the equity premium puzzle. Since only the wealthiest people invest significant amounts in the stock market (limited participation), it is reasonable to combine the consumption data of the wealthy, instead of aggregate data, with observed asset returns to estimate the risk aversion coefficient (RRA). I approximate the consumption by the rich from two angles: one explores the income and wealth data to back out synthetic consumption directly, and the other explores the sales data to approximate the expenditure by the rich. By using the created indices, the lowest RRA estimate is around three for the first approach, and slightly below ten for the second one. Furthermore, when I use my indices to fit more moments besides excess return, the estimate of RRA increases modestly, e.g., to fit returns of 25 size and book-to-market portfolios, estimates of RRA are between 2.16 and 18. I conclude that these indices, especially the top consumption processes, provide a useful vantage point from which we can reassess the theory of consumption-based asset pricing. When I used these newly constructed indices in a factor model, my factor model explains cross-sectional excess returns better than CAPM and CCAPM model with aggregate consumption.

The latter two parts are to re-evaluate the Quantity Theory of Money(QTM) using, to the extent possible, the same statistical and economic criteria but a much larger data set covering both a longer period and many more countries. I investigate whether QTM breaks across countries and I find Lucas' result fragile. It appears that the period 1955-1980 is the only period during which QTM fits data well in most of our sample countries. It starts to break down when we go beyond this period. Furthermore, the recent breaking down of QTM is not global when I truncate the sample before the crisis since QTM is not a tight rule across countries. To explain the breaking down for the U.S during Pre-crisis Period (1980-2007), the second part shows $M_2$ is a more robust monetary index by investigating the historical performance of $M_1$. Under the view of endogenous money. Namely, broad money($M_2$) is generated from loan issuing. I decompose the structure of loans for the U.S. I found that real estate is the major collateral asset for Household and Firms. I thus propose money is after real estate and final goods. To confirm our theory, we investigate a historical nominal price index of U.S and find that (long-run) growth of nominal house price co-moves with(leads) growth of broad money more robustly. Furthermore, the timing of recent financial innovation matches with breaking data. I thus propose a channel through which financial innovation can affect the estimation of QTM.


English (en)

Chair and Committee

Costas Azariadis

Committee Members

Michele Boldrin, Gaetano Antinolfi, Werner Ploberger, Ngoc-Khanh Tran,


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