Forecasting annual inflation with power transformations: the case of inflation targeting countries
Download full text from publisher
Other versions of this item:
- Héctor Manuel Záarte Solano & Angélica Rengifo Gómez, 2013. "Forecasting annual inflation with power transformations: the case of inflation targeting countries," BORRADORES DE ECONOMIA 010462, BANCO DE LA REPÚBLICA.
References listed on IDEAS
- Proietti, Tommaso & Lütkepohl, Helmut, 2013.
"Does the Box–Cox transformation help in forecasting macroeconomic time series?,"
International Journal of Forecasting,
Elsevier, vol. 29(1), pages 88-99.
- Lütkepohl, Helmut & Proietti, Tommaso, 2011. "Does the Box-Cox transformation help in forecasting macroeconomic time series?," Working Papers 08/2011, University of Sydney Business School, Discipline of Business Analytics.
- Tommaso Proietti & Helmut Luetkepohl, 2011. "Does the Box-Cox Transformation Help in Forecasting Macroeconomic Time Series?," Economics Working Papers ECO2011/29, European University Institute.
- Tommaso, Proietti & Helmut, Luetkepohl, 2011. "Does the Box-Cox transformation help in forecasting macroeconomic time series?," MPRA Paper 32294, University Library of Munich, Germany.
- Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
- repec:bla:jtsera:v:19:y:1998:i:2:p:147-164 is not listed on IDEAS
- Hosoya, Yuzo & Terasaka, Takahiro, 2009. "Inference on transformed stationary time series," Journal of Econometrics, Elsevier, vol. 151(2), pages 129-139, August.
More about this item
KeywordsARIMA models; power transformations; seasonality; bayesian analysis.;
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-FOR-2013-02-16 (Forecasting)
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bdr:borrec:756. See general 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: (Clorith Angélica Bahos Olivera). General contact details of provider: http://edirc.repec.org/data/brcgvco.html .
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.