Gray Calhoun’s academic homepage

I’m Gray Calhoun, an Assistant Professor in the Economics Department at Iowa State. I work on Econometric theory, especially time series and applications to forecasting and forecast evaluation. I graduated with a PhD from UC San Diego in 2009, where I worked with Graham Elliott and Allan Timmermann.

Email: «gcalhoun at iastate dot edu» (university) and «gray at clhn dot org» (personal email and IM)

Office: 467 Heady Hall, (515) 294-6271.

Links: CV, IDEAS, Google Scholar, LinkedIn, GitHub, and Twitter. Let me know if you want the password to my family blog. (Don’t feel left out, it’s mostly pictures of my kids.)

This website was last updated on 2015-07-02.


Current and former PhD students

Anwen Yin. 2015 PhD in Economics, Helle Bunzel and I were co-advisors. Starting in August as an Assistant Professor of Economics at Texas A&M International University.

Matt Simpson. 2015 PhD in Economics and Statitstics, Jarad Niemi and I were co-advisors. Starting in August as a postdoc in Statistics at University of Missouri.

Working papers

Out-of-sample comparisons of overfit models (2014-03-30, revise and resubmit at Quantitative Economics) with supplemental appendix and source code archive.

Block bootstrap consistency under weak assumptions (2014-10-06, revise and resubmit at Econometric Theory) with supplemental appendix.

Improved stepdown methods for asymptotic control of generalized error rates (2015-04-27, revise and resubmit at Journal of Econometrics) with source code archive.

An asymptotically normal out-of-sample test based on mixed estimation windows (2015-01-09, revise and resubmit at Econometrica) with appendix and source code archive.

A graphical analysis of causality in the Reinhart-Rogoff dataset (2015-06-23) with source code archive. (This is a more formal version of a blog post I had written earlier.)

Graphing better Impulse Response Functions for discrete-time linear models, joint with Seth Pruitt (2015-03-27) with source code archive.

A simple block bootstrap for asymptotically normal out-of-sample test statistics (2015-04-21) source code archive.


Hypothesis testing in linear regression when k/n is large. Journal of Econometrics, 165(2), 2011: 163–174. Link, published version, R package, and additional files


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