Forecasting annual inflation with power transformations: the case of inflation targeting countries
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- 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.
- 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. Classification JEL:C22; C52;
- 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
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