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Computational Complexity and Parallelization in Bayesian Econometric Analysis

Department of Quantitative Economics, School of Business and Economics, Maastricht University, Maastricht, 6211LM, The Netherlands
Department of Economics, University Ca’ Foscari of Venice, Venice, 31022, Italy
Faculty of Economics and Management, Free University of Bozen-Bolzano, Bolzano, 39100, Italy
Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam, Amsterdam, 1081HV, The Netherlands
Tinbergen Institute, Amsterdam, 1082 MS, The Netherlands
Econometric Institute, Erasmus School of Economics, Erasmus University, Rotterdam, 3062 PA, The Netherlands
Author to whom correspondence should be addressed.
Academic Editor: Kerry Patterson
Econometrics 2016, 4(1), 9;
Received: 27 January 2016 / Revised: 28 January 2016 / Accepted: 3 February 2016 / Published: 22 February 2016
(This article belongs to the Special Issue Computational Complexity in Bayesian Econometric Analysis)
Note: In lieu of an abstract, this is an excerpt from the first page.

Challenging statements have appeared in recent years in the literature on advances in computational procedures.[...] View Full-Text
MDPI and ACS Style

Baştürk, N.; Casarin, R.; Ravazzolo, F.; Van Dijk, H.K. Computational Complexity and Parallelization in Bayesian Econometric Analysis. Econometrics 2016, 4, 9.

AMA Style

Baştürk N, Casarin R, Ravazzolo F, Van Dijk HK. Computational Complexity and Parallelization in Bayesian Econometric Analysis. Econometrics. 2016; 4(1):9.

Chicago/Turabian Style

Baştürk, Nalan, Roberto Casarin, Francesco Ravazzolo, and Herman K. Van Dijk 2016. "Computational Complexity and Parallelization in Bayesian Econometric Analysis" Econometrics 4, no. 1: 9.

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