Bayesian methods have become increasingly popular in all fields of economics and econometrics, including macro- and micro-economics, industrial organisation, trade, development, labour, financial economics, and others.
Their success has been made possible by recent advances in simulation-based inference that have enabled the analysis of richer and more realistic models, many of which are difficult to analyse by other techniques. Building upon these advances will require continued development of new estimation approaches and improvement of existing ones, coupled with careful implementation in empirical problems that illustrate their practical appeal.
The special issue will highlight new theoretical and applied research in Bayesian modelling and estimation.
Suitable topics include but are not limited to:
- Estimation techniques and refinements, simulation, computation
- Markov chain Monte Carlo ( MCMC ) simulation
- Adaptive samplers
- Importance samplers
- Parallel computing
- Development of new econometric models
- Cross-sectional, time series and panel data models
- Missing data, sample selection, treatment models
- Latent variable models
- Hierarchical modelling
- Nonparametric and semiparametric models
- Simulated likelihood estimation by Bayesian techniques
- Applications of Bayesian techniques and models in any field of economics
- Model comparison and model evaluation.
Full paper submission deadline: 1 December, 2012
Completion of peer review: 1 February, 2013