WALS Estimation and Forecasting in Factor-based Dynamic Models with an Application to Armenia

Abstract

Two model averaging approaches are used and compared in estimating and forecasting dynamic factor models, the well-known Bayesian model averaging (BMA) and the recently developed weighted average least squares (WALS). Both methods propose to combine frequentist estimators using Bayesian weights. We apply our framework to the Armenian economy using quarterly data from 20002010, and we estimate and forecast real GDP growth and inflation.

Keywords

• Dynamic Models, Factor Analysis, Model Averaging, Monte Carlo, Armenia

References

1. Bernanke, B.S., J. Boivin and P. Eliasz (2005). Measuring the effects of monetary policy: A factor-augmented vector autoregressive (FAVAR) approach. Quarterly Journal of Economics, 120, 387–422.
2. Danilov, D. and J.R. Magnus (2004). On the harm that ignoring pretesting can cause. Journal of Econometrics, 122, 27–46.
3. De Luca, G. and J.R. Magnus (2011). Bayesian model averaging and weighted average least squares: Equivariance, stability, and numerical issues. The Stata Journal, 11, 518-544.
4. Forni, M., M. Hallin, M. Lippi and L. Reichlin (2000). The generalized dynamic-factor model: Identification and estimation. The Review of Economics and Statistics, 82, 540– 554.
5. Forni, M., M. Hallin, M. Lippi and L. Reichlin (2003). Do financial variables help forecasting inflation and real activity in the euro area. Journal of Monetary Economics, 50, 1243– 1255.
6. Koop, G. and S. Potter (2004). Forecasting in dynamic factor models using Bayesian model averaging. The Econometrics Journal, 7, 550–565.
7. Magnus, J.R. and J. Durbin (1999). Estimation of regression coefficients of interest when other regression coefficients are of no interest. Econometrica, 67, 639–643.
8. Magnus, J.R., O. Powell and P. Prüfer (2010). A comparison of two model averaging techniques with an application to growth empirics. Journal of Econometrics, 154, 139– 153.

9. Magnus, J.R., A.T.K. Wan and X. Zhang (2011). Weighted average least squares estimation with nonspherical disturbances and an application to the Hong Kong housing market. Computational Statistics & Data Analysis, 55, 1331–1341.
10. Mann, H.B. and A. Wald (1943). On the statistical treatment of linear stochastic difference equations. Econometrica, 11, 173–220.
11. Stock, J.H. and M.W. Watson (2002). Macroeconomic forecasting using diffusion indexes. Journal of Business & Economic Statistics, 20, 147–162.
12. Zellner, A. (1986). On assessing prior distributions and Bayesian regression analysis with g- prior distributions. In Bayesian Inference and Decision Techniques: Essays in Honor of Bruno de Finetti, ed. P.K. Goel and A. Zellner. Amsterdam: North-Holland, 233–243.