Philip Shaw

Ph.D., University of Connecticut

• Macroeconomics
• Economic Growth
• Computational Economics
• Econometrics

Dr. Shaw's research focuses on educational corruption, nonparametric econometrics, computational methods for economics and finance, and economic growth. Currently Dr. Shaw is looking at instrumental variable estimation of functions when the unknown function to be estimated is only additively separable with respect to unobservables. His research also looks into the impact educational corruption has on economic growth, the college wage premium, and educational attainment rates in a theoretical framework. Dr. Shaw is also in the process of developing nonparametric computational methods that aid in the solution of stochastic general equilibrium models when the joint determination of covariates is completely unknown.

Journal Articles

Nonparametric Instrumental Variable Estimation in Practice, with Michael Cohen and Tao Chen. Journal of Econometric Methods, 5(1), 2016, pp. 153-177. https://doi.org/10.1515/jem-2013-0002.

On the Determinants of Educational Corruption: The Case of Ukraine, with Marina-Selini Katsaiti and Brandon Pecoraro. Contemporary Economic Policy, 33(4), 2015, pp. 698-713.

A Nonparametric Approach to Solving a Simple One-sector Stochastic Growth Model. Economics Letters, 125(3), 2014, pp. 447-450.

Can We Reject Linearity in an HAR-RV Model for the S&P 500? Insights from a Nonparametric HAR-RV, with Jerome Lahaye. Economics Letters, 125(1), 2014, pp. 43–46.

Intelligence and Bribing Behavior in a One-Shot Game, with F. William Vasquez and Mark LeClair. The Journal of Socio-Economics 44, 2013, pp. 91–96,.

Corruption and Growth Under Weak Identification, with Marina-Selini Katsaiti and Marius Jurgilas. Economic Inquiry 49(1), 2011, pp. 264-275.