Do unobserved components models forecast inflation in Russia?
AbstractI apply the model with unobserved components and stochastic volatility (UC-SV) to forecast the Russian consumer price index. I extend the model which was previously suggested as a model for inflation forecasting in the USA to take into account a possible difference in model parameters and seasonal factor. Comparison of the out-of-sample forecasting performance of the linear AR model and the UC-SV model by mean squared error of prediction shows better results for the latter model. Relatively small absolute value of the standard error of the forecasts calculated by the UC-SV model makes it a reasonable candidate for a real time forecasting method for the Russian CPI.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by National Research University Higher School of Economics in its series HSE Working papers with number WP BRP 35/EC/2013.
Length: 14 pages
Date of creation: 2013
Date of revision:
Publication status: Published in WP BRP Series: Economics / EC, September 2013, pages 1-14
Stochastic volatility; MCMC; Russia; CPI; forecasting.;
Find related papers by JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-12-06 (All new papers)
- NEP-CBA-2013-12-06 (Central Banking)
- NEP-CIS-2013-12-06 (Confederation of Independent States)
- NEP-FOR-2013-12-06 (Forecasting)
- NEP-MAC-2013-12-06 (Macroeconomics)
- NEP-TRA-2013-12-06 (Transition Economics)
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Shamil Abdulaev) or (Victoria Elkina).
If references are entirely missing, you can add them using this form.