Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM

Econometrics

Lennart Hoogerheide¹  Herman K. van Dijk¹  Nalan Baştürk²  Stefano Grassi³ 

[1] Department of Econometrics and Tinbergen Institute, Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands;Department of Quantitative Economics, School of Business and Economics, Maastricht University, Maastricht 6211LM, The Netherlands;School of Economics, Keynes College, University of Kent, Canterbury CT27NP, UK;

关键词: Importance sampling;    parallel computing;    MitISEM;    MCMC;   

DOI  :  10.3390/econometrics4010011

来源: DOAJ

【 摘 要 】

This paper presents the parallel computing implementation of the MitISEM algorithm, labeled Parallel MitISEM. The basic MitISEM algorithm provides an automatic and flexible method to approximate a non-elliptical target density using adaptive mixtures of Student-t densities, where only a kernel of the target density is required. The approximation can be used as a candidate density in Importance Sampling or Metropolis Hastings methods for Bayesian inference on model parameters and probabilities. We present and discuss four canonical econometric models using a Graphics Processing Unit and a multi-core Central Processing Unit version of the MitISEM algorithm. The results show that the parallelization of the MitISEM algorithm on Graphics Processing Units and multi-core Central Processing Units is straightforward and fast to program using MATLAB. Moreover the speed performance of the Graphics Processing Unit version is much higher than the Central Processing Unit one.

【 授权许可】

Unknown