Department of Economics

University of Leicester

Lecicester LE1 7RH

United Kingdom

Curriculum Vitae pdf html |

First Version: 19th July, 2016

given probability distribution and risk in the distribution itself. The latter is captured by the randomness in the parameters underlying the probability distribution

and is referred to as distributional risk. Stochastic volatility, which generally refers to the randomness in the variance, can be viewed as a form of distributional risk.

Necessary and sufficient conditions by which an increase in distributional risk will induce the consumer to save more are derived under two specifications of

preferences: expected utility preferences and Selden/Kreps-Porteus preferences. The connection (or lack of) between these conditions and stochastic volatility is

addressed. The additional conditions under which a prudent consumer will save more under greater volatility risk are identified.

Diversity and Economic Growth in a Model with Progressive Taxation (with Wei Wang)

First Version: 30th October, 2015.

dynamic general equilibrium model with ex ante heterogeneous consumers and progressive taxation. We show that the answer depends crucially on the shape of the

marginal tax function. If this function is concave, then a more heterogeneous population will have a lower average marginal tax rate and a higher level of capital

accumulation. The opposite is true when the marginal tax function is convex. These results are robust in a variety of models with either exogenous or endogenous

economic growth.

Research Policy and U.S. Economic Growth

First Version: August 14, 2013.

achieve this, we develop an endogenous growth model which takes into account both public and private research investment, and the differences between basic and

non-basic research. A calibrated version of the model is able to replicate some important features of the U.S. economy over the period 1953-2009. Our model

suggests that government spending on basic research is an effective policy instrument to promote economic growth. Subsidizing private R&D, on the other hand, has

no effect on economic growth.

Concave Consumption Function and Precautionary Wealth Accumulation*

idiosyncratic labor income risk and borrowing constraints. We begin by characterizing the consumption function of individual consumers. We show that the

consumption function is concave when the utility function has strictly positive third derivative and the inverse of absolute prudence is a concave function. These

conditions encompass all HARA utility functions with strictly positive third derivative as special cases. We then show that when consumption function is concave, a

mean-preserving increase in income risks would encourage wealth accumulation at both the individual and aggregate levels.

* This paper was previously circulated under the title "Concave Consumption Function under Borrowing Constraints."

Technological Advance and the Growth in Health Care Spending

technology improvements and rising incomes in explaining these changes. To achieve this, we develop a dynamic general equilibrium model in which consumers face

idiosyncratic uncertainty in health. Both health care spending and life expectancy are endogenously determined. According to our model, medical technology

improvements and rising incomes can explain all of the increase in health care spending and more than 60% of the increase in life expectancy at age 25 in the United

States between 1950 and 2001.

Asset Bubbles in an Overlapping Generations Model with Endogenous Labor Supply (with Lisi Shi)

under which asset bubbles will lead to an expansion in steady-state capital, investment, employment and output. We also provide a specific numerical example to

illustrate these results.

Time Preference and the Distributions of Wealth and Income

Working paper version

MATLAB Codes

the standard neoclassical growth model to allow for (i) heterogeneity in consumers' discount rates, (ii) direct preferences for wealth, and (iii) human capital

formation. The second feature prevents the wealth distribution from collapsing into a degenerate distribution. The third feature generates a strong positive

correlation between earnings and capital income across consumers. A calibrated version of the model is able to generate patterns of wealth and income inequality

that are very similar to those observed in the United States.

A Quantitative Analysis of Suburbanization and the Diffusion of the Automobile*

with Karen A. Kopecky

Working paper version

to access quantitatively the contribution of automobiles and rising incomes to suburbanization. The model incorporates a number of driving forces of

suburbanization and car adoption, including falling automobile prices, rising real incomes, changing costs of traveling by car and with public transportation, and

urban population growth. According to the model, 60 percent of postwar (1940-1970) suburbanization can be explained by these factors. Rising real incomes and

falling automobile prices are shown to be the key drivers of suburbanization.

*This paper was previously circulated with the title “Suburbanization and the Automobile.”

Finite State Markov-Chain Approximations to Highly Persistent Processes

with Karen A. Kopecky

Longer version

Computer Codes

properties unmatched by other methods. In particular, we prove that it can match the conditional and unconditional mean and variance, and the first-order

autocorrelation of any stationary AR(1) process. These properties make the Rouwenhorst method more reliable than others in approximating highly persistent

processes and generating accurate model solutions. To illustrate this, we compare the performances of the Rouwenhorst method and four others in solving the

stochastic growth model and an income fluctuation problem. We find that (i) the choice of approximation method can have a large impact on the computed model

solutions, and (ii) the Rouwenhorst method is more robust than others with respect to variation in the persistence of the process, the number of points used in the

discrete approximation and the procedure used to generate model statistics.