A Study of a Combining Model to Estimate Quarterly GDP Kang, Chang-Ku;
Various statistical models to Estimate GDP (measured as a nation`s economic situation) have been developed. In this paper an autoregressive distributed lag model, factor model, and a Bayesian VAR model estimate quarterly GDP as a single model; the combined estimates were evaluated to compare a single model. Subsequently, we suggest that some combined models are better than a single model to estimate quarterly GDP.
Combining estimates;quarterly GDP;factor model;
Bates, J. M. and Granger, C. W. J. (1969). The combination of forecasts, Operational Research Quarterly, 451-468.
Collopy, F. and Armstrong, J. S. (1992). Rule-based forecasting: Development and validation of an expert systems approach to combining time series extrapolations, Management Science, 38, 1394-1414.
Diebold, X. (1988). Serial correlation and the combination of forecasts, Journal of Business Economic Statistics, 6, 105-111.
Granger, C. W. J. and Ramanathan, R. (1984). Improved methods of combining forecasts, Journal of Forecasting, 3, 197-204.
Harvey, D. I., Leybourne, S. J. and Newbold, P. (1997). Testing the equality of prediction mean square errors, International Journal of Forecasting, 13, 281-291.
Min, K. S., Park, J. H. and Park, S. O. (2002). Quaterly Projection Model by using monthly indicators, Journal of The Korean Official Statistics, 7, 97-126.
Newbold, P. and Granger, C. W. J. (1974). Experience with forecasting univariate time series and the combination of forecasts, Journal of the Royal Statistical Society, 137, 131-164.
Reijer, A. H. J. (2005). Forecasting Dutch GDP using large scale factor models, Working paper, 1-27.
Schneider, M. and Spitzer, M. (2004). Forecasting Austrian GDP using the generalized dynamic factor model, Working paper, 1-36.
Shim, S. and Lee, H. (1992). Short-term Forecasting Domestic Demand using the monthly economic indicators, KDI Quarterly Economic Outlook, 63-75.
Stock, J. H. and Watson, M. W. (2002). Forecasting using principal components from a large number of predictors, Journal of American Statistical Association, 97, 1167-1179.