Forecasting macroeconomic variables using disaggregate survey data
AbstractWe assess the forecast ability of Norges Bank’s regional survey for inflation, GDP growth and the unemployment rate in Norway. We propose several factor models based on regional and sectoral information given by the survey. The analysis identifies which information extracted from the ten sectors and the seven regions performs particularly well at forecasting different variables and horizons. Results show that several factor models beat an autoregressive benchmark in forecasting inflation and unemployment rate. However, the factor models are most successful in forecasting GDP growth. Forecast combinations based on past performance give in most cases more accurate forecasts than the benchmark, but they never give the most accurate forecasts.
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Bibliographic InfoPaper provided by Norges Bank in its series Working Paper with number 2011/04.
Length: 35 pages
Date of creation: 11 Apr 2011
Date of revision:
Note: First version:
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Keywords: Factor models; macroeconomic forecasting; qualitative survey data.;
Other versions of this item:
- Martinsen, Kjetil & Ravazzolo, Francesco & Wulfsberg, Fredrik, 2014. "Forecasting macroeconomic variables using disaggregate survey data," International Journal of Forecasting, Elsevier, vol. 30(1), pages 65-77.
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-04-16 (All new papers)
- NEP-CBA-2011-04-16 (Central Banking)
- NEP-FOR-2011-04-16 (Forecasting)
- NEP-MAC-2011-04-16 (Macroeconomics)
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