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WHAT'S NEW IN RESEARCH


Asset Pricing with Recursive Utility and Stochastic Volatility: A Bayesian DSGE Analysis, with David E. Rapach, latest manuscript to follow soon, March 2017. Paper link for 2017 NBER-NSF Seminar on Bayesian Inference in Econometrics and Statistics (SBIES) can be found here.

We analyze asset pricing in a richly structured dynamic stochastic general equilibrium (DSGE) model with stochastic volatility when the representative investor has recursive preferences. Our approach combines an affine solution procedure with Bayesian estimation to provide a convenient framework for estimating risk premia in high-dimensional DSGE models. The model’s estimates of the elasticity of intertemporal substitution and coefficient of relative risk aversion are near two and six, respectively. The estimated model largely accounts for key asset pricing puzzles, with permanent technology shocks playing a leading role in allowing the model to explain the large average equity risk premium in the data. Stochastic volatility generates time variation in the expected equity risk premium, and the estimated time-varying expected equity risk premium in the model is highly plausible, exhibiting strong countercyclical behavior. Overall, our findings indicate that DSGE models hold considerable promise for deepening our understanding of risk premia.



An Analytical Approach to New Keynesian Models under the Fiscal TheoryEconomics Letters, Volume 156, July 2017, Page 133--137.

This article illustrates a widely applicable frequency-domain methodology to solving multivariate linear rational expectations models. As an example, we solve a prototypical new Keynesian model under the assumption that primary surpluses evolve independently of government liabilities, a regime in which the fiscal theory of the price level is valid. The resulting analytical solution is useful in characterizing the cross-equation restrictions and illustrating the complex interaction between the fiscal theory and price rigidity. We also highlight some useful by-products of such method which are not easily obtainable for more sophisticated models using time-domain methods.



Interpreting Rational Expectations Econometrics via Analytic Function ApproachEconomics Bulletin, Volume 37, Issue 2, June 2017, Page 1182--1190.

An analytic function method is applied to illustrate Geweke's (2010) three econometric interpretations for a generic rational expectations (RE) model. This delivers an explicit characterization of the model's cross-equation restrictions imposed by the RE hypothesis under each econometric interpretation. It is shown that the degree of identification on the deep parameters is positively related to the strength of underlying econometric interpretation, and observationally equivalent models may arise once the cross-equation restrictions are interpreted in a minimal sense. This offers important insights into the econometric modeling and evaluation of dynamic stochastic general equilibrium (DSGE) models.


PERSONAL


I am an assistant professor of economics at John Cook School of Business, Saint Louis University.

My primary research and teaching interests center on macroeconomics, monetary economics, and time series, with special emphasis on the econometric modeling and evaluation of macroeconomic policy. One line of my recent work employs formal econometric techniques to examine the empirical implications
of the dynamic interactions between U.S. fiscal and monetary policies. Another line develops frequency-domain approaches to solving and estimating dynamic economic models. I also conduct research in evolutionary dynamics with a focus on the evolution of cooperative and altruistic human behavior.

Currently I am teaching ECON 3120 Intermediate Macroeconomics and ECON 4310 Exchange Rates & Global Economy in Spring 2017.

Please send an email to me if you have any difficulty with links or downloads from this page.