replicating the results in ‘a new model of trend inflation’ using particle markov chain monte carlo (replication data)

An article by Chan et al. (2013) published in the Journal of Business and Economic Statistics introduces a new model for trend inflation. They allow the trend inflation to evolve according to a bounded random walk. In order to draw the latent states from their respective conditional posteriors, they use accept-reject Metropolis-Hastings procedures. We reproduce their results using particle Markov chain Monte Carlo (PMCMC), which approaches drawing the latent states from a different technical point of view by relying on combining Markov chain Monte Carlo and sequential Monte Carlo methods. To conclude: we are able to reproduce the results of Chan et al. (2013).

Data and Resources

Suggested Citation

Nonejad, Nima (2016): Replicating the Results in ‘A New Model of Trend Inflation’ Using Particle Markov Chain Monte Carlo (replication data). Version: 1. Journal of Applied Econometrics. Dataset.