Juan Carlos  Escanciano

Full Professor (Research Chair in Economics)
Semiparametric and Nonparametric Econometrics; Risk Management and Empirical Asset Pricing
34 91 624 6198 Office: 15.2.19
jescanci@eco.uc3m.es
Personal website - Currículum Vitae

Bio

Juan Carlos Escanciano is Research Chair in Economics and Full Professor at Universidad Carlos III de Madrid. He obtained his P.hD in Economics at Universidad Carlos III de Madrid in 2004.  He obtained an Assistant Professor position at Universidad de Navarra (2004-2006), Full Professor (with tenure) at Indiana University (2006-2018), and Visiting positions at Yale University, Cornell, Rochester and MIT. His research and teaching focus on Econometric Theory, including identification, estimation and specification testing, as well as empirical work in Financial Econometrics and Risk Management.

Juan Carlos is Fellow of Journal of Econometrics. He has published papers in several leading international journals, including Journal of American Statistical Association, Journal of Econometrics, Econometric Theory, Quantitative Economics, Management Science, and The Annals of Statistics. He is Associate Editor of  Series, Econometric Theory, Econometric Reviews, Journal of Business and Economic Statistics, and Co-Editor senior in Advances in Econometrics.

Selected Publications

Escanciano, J.C., and  Goh, C.. “Quantile-Regression Inference With Adaptive Control of Size”, Journal of the American Statistical Association,  forthcoming.

Escanciano, J.C., Pardo-Fernandez J.C., and Van Keilegom, I. “Asymptotic distribution-free tests for semiparametric regressions with dependent data”, The Annals of Statistics, 46, 1167-1196, 2018.

Du, Z. and Escanciano, J.C. “Backtesting Expected Shortfall: Accounting for Tail Risk” Management Science, 63, 940-958, 2017.

Escanciano, J.C. “A Consistent Diagnostic Test for Regression Models Using Projections”, Econometric Theory, 22, 1030-1051, 2006.

Escanciano, J.C. “Goodness-of-fit Tests for Linear and Nonlinear Time Series Models”, Journal of the American Statistical Association, 101, 531-541, 2006.

Recent Research

Escanciano, J.C. “Semiparametric Identification and Fisher Information” 2018.

Chernozhukov, V., Escanciano, J.C., Newey, W.K., H. Ichimura and J. Robins. “Locally Robust Semiparametric Estimation”, 2018.

Bravo, F., Escanciano, J.C., and I. Van Keilegom. “Two-Step Semiparametric Empirical Likelihood Inference” 2018.

Escanciano, J.C., and J. Hualde. “Measuring Asset Market Linkages: Nonlinear Dependence and Tail Risk” 2018.

Escanciano, J.C., and W. Li. “Optimal Linear Instrumental Variables Approximations” 2018.

Teaching

Econometrics I (Master Análisis Económico)

 
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