Assessment of inflationary expectations in India: a Markov chain Monte-Carlo based Gibbs sampling approach
Himanshu Joshi
Macroeconomics and Finance in Emerging Market Economies, 2010, vol. 3, issue 2, 213-225
Abstract:
Inflation in India is commonly analyzed in terms of the traditional 'monetarist' and 'structuralist' frameworks. However, these models have not been widely tested for their forecasting ability in practical policy settings. Besides, the important issue of assessment of inflationary expectations is hardly addressed by these models. This paper illustrates an empirical method for high frequency (weekly) forecasting of inflation rate based on mixed estimation and Markov Chain Monte-Carlo led Gibbs sampling procedure and compares the outcomes with respect to those obtained from an analogue classical least squares (CLS) model. Improvement in forecasting performance is observed.
Keywords: autoregression; CUSUM; Markov chain; Monte-Carlo; Gibbs sampler; posterior distribution; smoothness priors (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/17520843.2010.498133 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:macfem:v:3:y:2010:i:2:p:213-225
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/REME20
DOI: 10.1080/17520843.2010.498133
Access Statistics for this article
Macroeconomics and Finance in Emerging Market Economies is currently edited by Subrata Sarkar and Ashima Goyal
More articles in Macroeconomics and Finance in Emerging Market Economies from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().