Hedibert F. Lopes

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corpo_hedibert_lopesPh.D.in Statistics – Duke University
e-mail: hedibertfl@insper.edu.br
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Fields of interest: Bayesian statistics; Factorial analysis; Computational methods; Time series and dynamic models; Multivariate stochastic volatility; Extreme value theorem; Particle filters; Spatial statistics.


Hedibert F. Lopes received a Ph.D. in Statistics and Decision Sciences from the Institute of Statistics and Decision Sciences of Duke University in 2000, and an MSc. in Statistics from the Mathematics Institute of the Federal University of Rio de Janeiro (UFRJ) in 1994. Prior to joining Insper in 2013, he worked for ten years at the University of Chicago as Assistant and Associate Professor of Econometrics and Statistics at the Booth School of Business.

He was Professor of Statistics at the Federal University of Fluminense (UFF) and at UFRJ in 1992-96 and 1996-2003, respectively, and Assistant Researcher at the Institute for Applied Economic Research (IPEA/RJ) in 1991-96. He has lectured various courses in undergraduate, masters and doctorate programs over the last two decades, such Bayesian Econometrics, Computational Statistics and Inference Statistics (doctorate) and Business Statistics (MBA)

He conducts research in Bayesian Statistics, Factorial Analysis, Computational Methods, Time Series and Dynamic Models, Multivariate Stochastic Volatility, Extreme Value Theorem, Particle Filters, Spatial Statistics, Microeconometrics and Macroeconometrics.

He has published six books, with another three to be published by 2016 (Wiley, Chapman&Hall and Springer), and over 70 scientific papers and technical reports. He has served as an expert for more than 30 international journals, given 200 lectures and administered 25 mini-courses and tutorials over the last decade.

He is Associate Editor of the Journal of Business and Economic Statistics and of Bayesian Analysis and has published papers in international journals, such as the Journal of the American Statistical Association, Annals of Applied Statistics, Statistical Science, Statistics and Computing, Biometrics, Bayesian Analysis, Journal of Time Series Analysis, Econometric Reviews and Computational Statistics and Data Analysis.



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