Albis, Manuel Leonard F. and Mapa, Dennis S.
(2014):
*Bayesian Averaging of Classical Estimates in Asymmetric Vector Autoregressive (AVAR) Models.*

Preview |
PDF
MPRA_paper_55902.pdf Download (244kB) | Preview |

## Abstract

The estimated Vector AutoRegressive (VAR) model is sensitive to model misspecifications, such as omitted variables, incorrect lag-length, and excluded moving average terms, which results in biased and inconsistent parameter estimates. Furthermore, the symmetric VAR model is more likely misspecified due to the assumption that variables in the VAR have the same level of endogeneity. This paper extends the Bayesian Averaging of Classical Estimates, a robustness procedure in cross-section data, to a vector time-series that is estimated using a large number of Asymmetric VAR models, in order to achieve robust results. The combination of the two procedures is deemed to minimize the effects of misspecification errors by extracting and utilizing more information on the interaction of the variables, and cancelling out the effects of omitted variables and omitted MA terms through averaging. The proposed procedure is applied to simulated data from various forms of model misspecifications. The forecasting accuracy of the proposed procedure was compared to an automatically selected equal lag-length VAR. The results of the simulation suggest that, under misspecification problems, particularly if an important variable and MA terms are omitted, the proposed procedure is better in forecasting than the automatically selected equal lag-length VAR model.

Item Type: | MPRA Paper |
---|---|

Original Title: | Bayesian Averaging of Classical Estimates in Asymmetric Vector Autoregressive (AVAR) Models |

Language: | English |

Keywords: | BACE, AVAR, Robustness Procedures |

Subjects: | C - Mathematical and Quantitative Methods > C5 - Econometric Modeling C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics |

Item ID: | 55902 |

Depositing User: | Dennis S. Mapa |

Date Deposited: | 12 May 2014 07:03 |

Last Modified: | 09 Oct 2019 00:31 |

References: | Akaike, H. (1973). A New Look at the Statistical Model Identification. IEEE Transactions on Automatic Control, Vol. 19(No. 6), pp. 716-723. Akaike, H. (1974, Dec.). A new look at the statistical model identification. Automatic Control, IEEE Transactions on, Vol. 19(No. 6), pp. 716,723. Braun, P. A., & Mittnik, S. (1993, Oct.). Misspecifications in vector autoregressions and their effects on impulse responses and variance decompositions. Journal of Econometrics, Vol. 59(No. 3), pp. 319-241. Carriero, A., Kapetanios, G., & Marcellino, M. (2009). Forecasting Exchange Rates with a Large Bayesian VAR. International Journal of Forecasting, pp. 400-417. Chen, A.-S., & Leung, M. T. (2003). A Bayesian Vector Error Correction Model in Forecasting Exchange Rates. Computers and Operations Research, Vol. 30, pp. 887-900. Diebold, F. X., & Roberto, M. S. (1995, July). Comparing Predictive Accuracy. Journal of Business & Economic Statistics, Vol. 13(No. 3), pp. 253-263. Fackler, J. S., & Krieger, S. C. (1986, Jan). An Application of Vector Time Series Techniques to Macroeconomic Forecasting. Journal of Business & Economic Statistics, Vol. 4(No. 1), pp. 71-80. Hannan, E. J., & Quinn, B. G. (1979). The Determination of the Order of an Autoregression. Journal of the Royal Statistical Society. Series B (Methodological), Vol. 41(No. 2), pp. 190-195. Harvey, D., Leybourne, S., & Newbold, P. (1997). Testing the Equality of Prediction Mean Squared Errors. International Journal of Forecasting, Vol. 13, pp. 281-291. Hsiao, C. (1981). Autoregressive Modelling and Money-Income Causality Detection. Journal of Monetary Economics, Vol. 7(No. 1), pp 85-106. Hurvich, C. M., & Tsai, C.-L. (1993). A Corrected Akaike Information Criterion for Vector Autoregressive Model Selection. Journal of Time Series Analysis, Vol. 14(No. 3), pp. 271-279. Jorda, O. (2005, March). Estimation and Inference of Impulse Responses by Local Projections. The American Economic Review, Vol. 95(No. 1), pp. 161-182. Kadilar, C., & Erdemir, C. (2002). Comparison of Performance Among Information Criteria in VAR and Seasonal VAR models. Hacettepe Journal of Mathematics and Statistics, Vol. 31, pp. 127-137. Keating, J. W. (1993). Asymmetric Vector Autoregression. Proceedings of the Business and Economic Statistics Section (pp. pp. 68-73). American Statistical Association. Keating, J. W. (1995). Vector Autoregressive Models with Asymmetric Lag Structure. Working Paper. Keating, J. W. (2000). Macroeconomic Modeling with Asymmetric Vector Autoregressions. Journal of Macroeconomics, Vol. 22(No. 1), pp. 1-28. Korobilis, D. (2010, March 4). VAR forecasting using Bayesian variable selection. Retrieved January 24, 2011, from Munich Personal RePec Archive: http://mpra.ub.uni-muenchen.de/21124/ Kullback, S., & Leibler, R. A. (1951). On Information and Sufficiency. Annals of Mathematical Statistics, Vol. 22(No. 1), pp. 79-86. Leamer, E. E. (1983, March). Let's Take the Con Out of Econometrics. The American Economic Review, Vol. 73(No. 1), pp. 31-43. Litterman, R. B. (1980). A Bayesian Procedure for Forecasting With Vector Autoregressions. Working Paper. Lütkepohl, H. (1990, Feb. ). Asymptotic Distributions of Impulse Response Functions and Forecast Error Variance Decompositions of Vector Autoregressive Models. The Review of Economics and Statistics, Vol. 72(No. 1), pp. 116-125. Lütkepohl, H. (2004). Forecasting with VARMA Models. Department of Economics, European University Institute. Ng, S., & Pierre, P. (2001, Nov.). Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power. Econometrica, Vol. 69(No. 6), pp. 1519-1554. Ozcicek, O., & McMillin, W. D. (1999, April). Lag length selection in vector autoregressive models: symmetric and asymmetric lags. Applied Economics, Vol. 31(No. 4), pp. 517-524. Po, H. H., Chi, H. W., Shyu, J., & Hsiao, C. Y. (2002). A Litterman BVAR approach for production forecasting of technological industries. Technological Forecasting and Social Change, Vol.70, pp. 67-82. Ramos, F. F. (2003). Forecasts of market shares from VAR and BVAR models: a comparison of their accuracy. International Journal of Forecasting, Vol. 19, pp. 95-100. Runkle, D. E. (1987, Oct.). Vector Autoregressions and Reality. Journal of Business and Economic Statistics, Vol. 5(No. 4), pp. 437-42. Sala-I-Martin, X. X. (1997, May). I Just Ran Two Million Regressions. The American Economic Review, Vol. 87(No. 2), pp. 178-183. Sala-I-Martin, X., Doppelhofer, G., & Miller, R. (2004, September). Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE). The American Economic Review, Vol. 94(No. 4), pp. 813-835. Schwartz, G. (1978). Estimating the Dimension of a Model. Annals of Statistics, Vol. 6(No. 2), pp. 461-464. Schwarz, G. (1978). Estimating the Dimension of a Model. Annals of Statistics, Vol. 6(No. 2), pp. 461-464. Seghouane, A.-K. (2006, Oct.). Vector Autoregressive Model-Order Selection From Finite Samples Using Kullback’s Symmetric Divergence. Circuits and Systems I: Regular Papers, IEEE Transactions on, Vol. 53(No. 10), pp. 2327-2335. Shibata, R. (1980). Asymptotically efficient selection of the order of the model for estimating parameters in a linear process. Annals of Statistics, Vol. 8(No. 1), pp. 147-146. Sims, C. A. (1980). Comparison of Interwar and Postwar Business Cycles: Monetarism Reconsidered. The American Economic Review: Papers and Proceedings of the Ninety-Second Annual Meeting of the American Economic Association. Vol. 70, No. 2, pp. pp. 250-257. American Economic Association. Sims, C. A. (1980, Jan). Macroeconomics and Reality. Econometrica, Vol. 48(No. 1), pp. 1-48. Sims, C. A., & Zha, T. (1999, Sep.). Error Bands for Impulse Responses. Econometrica, Vol. 67(No. 5), pp. 1113-1155. Stock, J. H., & Watson, M. W. (1996, Jan.). Evidence on Structural Instability in Macroeconomic Time Series Relations. Journal of Business & Economic Statistics, Vol. 14(No. 1), pp. 11-30. Stock, J. H., & Watson, M. W. (2001). Vector Autoregressions. The Journal of Economic Perspective, Vol. 15(No. 4), pp. 105-115. Strachan, R., & van Dijk, H. K. (2007). Bayesian Model Averaging in Vector Autoregressive Processes with an Investigation of Stability of the US Great Ratios and Risk of a Liquidity Trap in the USA, UK and Japan. MRG Discussion Paper Series 1407. Sun, D., & Ni, S. (2004). Bayesian analysis of vector-autoregressive models with noninformative priors. Journal of Statistical Planning and Inference, Vol. 121, pp. 291-309. Tsay, R. S. (2005). Analysis of Financial Time Series (Second Edition ed.). Hoboken, New Jersey: John Wiley & Sons, Inc. Waele, S. d., & Broersen, P. M. (2002, Oct.). Finite sample effects in vector autoregressive modelling. Instrumentation and Measurement, IEEE Transactions on, Vol. 51(No. 5), pp. 917-992. Waele, S. d., & Broersen, P. M. (2003, Feb.). Order Selection for Vector Autoregressive Models. Signal P |

URI: | https://mpra.ub.uni-muenchen.de/id/eprint/55902 |