Inflation forecasting using dynamic factor analysis. SAS 4GL programming approach
AbstractThe purpose of this article is to introduce an original macro code written in SAS 4GL. This macro is used to automate the process of forecasting with dynamic factor analysis. Automation of the process helps to save significant amounts of time and effort for the researcher. It also enables to compare different model specifications directly and, hence, to make conclusions that would be imperceptible without such automation, which is shown on the empirical study example.
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Bibliographic InfoPaper provided by Department of Applied Econometrics, Warsaw School of Economics in its series Working Papers with number 63.
Date of creation: 16 Sep 2012
Date of revision:
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statistical programming; forecasting; factor models; inflation;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-09-30 (All new papers)
- NEP-FOR-2012-09-30 (Forecasting)
- NEP-MON-2012-09-30 (Monetary Economics)
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