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Econometrics 2016, 4(1), 9; doi:10.3390/econometrics4010009

Computational Complexity and Parallelization in Bayesian Econometric Analysis

1
Department of Quantitative Economics, School of Business and Economics, Maastricht University, Maastricht, 6211LM, The Netherlands
2
Department of Economics, University Ca’ Foscari of Venice, Venice, 31022, Italy
3
Faculty of Economics and Management, Free University of Bozen-Bolzano, Bolzano, 39100, Italy
4
Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam, Amsterdam, 1081HV, The Netherlands
5
Tinbergen Institute, Amsterdam, 1082 MS, The Netherlands
6
Econometric Institute, Erasmus School of Economics, Erasmus University, Rotterdam, 3062 PA, The Netherlands
*
Author to whom correspondence should be addressed.
Academic Editor: Kerry Patterson
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)
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Note: In lieu of an abstract, this is an excerpt from the first page.

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Challenging statements have appeared in recent years in the literature on advances in computational procedures.[...] View Full-Text
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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

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