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VAR-ing the economy of the Netherlands

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  • Jan Jacobs
  • Albert van der Horst,

Abstract

This paper adopts the vector autoregression (VAR) approach to modelling the economy of the Netherlands. A VAR system with four endogenous variables---gross domestic product, inflation, the capital market interest rate and the money market interest rate---is built. The small, open character of the Dutch economy suggests the inclusion of foreign exogenous variables, so we also construct a VARX system (with world trade and the German capital market and money market rates as exogenous variables). Both the VAR system and the VARX system are estimated with error-correction mechanisms to take proper account of the non-stationarity of the variables. The VAR system and the VARX system are compared to the IBS-CCSO model, a structural macroeconometric model of the economy of the Netherlands. Compared to the IBS-CCSO model, the VAR system gives better results for production and inflation, whereas the structural macroeconometric IBS-CCSO model is to be preferred for the interest rates. The VARX system outperforms not only the VAR system but also the IBS-CCSO model.

Suggested Citation

  • Jan Jacobs & Albert van der Horst,, 1996. "VAR-ing the economy of the Netherlands," Working Papers 24, Centre for Economic Research, University of Groningen and University of Twente.
  • Handle: RePEc:wop:ccsowp:0024
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    File URL: http://www.eco.rug.nl/ccso/zip-file/ccso24.zip
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    References listed on IDEAS

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    1. Christopher A. Sims, 1986. "Are forecasting models usable for policy analysis?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 10(Win), pages 2-16.
    2. Litterman, Robert B, 1986. "A Statistical Approach to Economic Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 1-4, January.
    3. Engle, Robert F & Hendry, David F & Richard, Jean-Francois, 1983. "Exogeneity," Econometrica, Econometric Society, vol. 51(2), pages 277-304, March.
    4. Wallis, Kenneth F & Whitley, John D, 1991. " Large-Scale Econometric Models of National Economies," Scandinavian Journal of Economics, Wiley Blackwell, vol. 93(2), pages 283-314.
    5. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    6. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    7. McNees, Stephen K, 1986. "Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 5-15, January.
    8. John W. Keating, 1992. "Structural approaches to vector autoregressions," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 37-57.
    9. Dolado, Juan J & Jenkinson, Tim & Sosvilla-Rivero, Simon, 1990. "Cointegration and Unit Roots," Journal of Economic Surveys, Wiley Blackwell, vol. 4(3), pages 249-273.
    10. Cooley, Thomas F. & Leroy, Stephen F., 1985. "Atheoretical macroeconometrics: A critique," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 283-308, November.
    11. Ingram, Beth F. & Whiteman, Charles H., 1994. "Supplanting the 'Minnesota' prior: Forecasting macroeconomic time series using real business cycle model priors," Journal of Monetary Economics, Elsevier, vol. 34(3), pages 497-510, December.
    12. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    13. Jacobs, Jan & Sterken, Elmer, 1995. "The IBS-CCSO quarterly model of the Netherlands Specification, simulation and analysis," Economic Modelling, Elsevier, vol. 12(2), pages 111-163, April.
    14. Gerlach, Stefan & Smets, Frank, 1995. "The Monetary Transmission Mechanism: Evidence from the G-7 Countries," CEPR Discussion Papers 1219, C.E.P.R. Discussion Papers.
    15. McNees, Stephen K, 1986. "Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 1-23, January.
    16. Litterman, Robert, 1986. "A statistical approach to economic forecasting : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 1-4," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
    17. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    18. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    19. Jakob De Haan & Jan Egbert Sturm, 1995. "Is it real? The relationship between real deficits and real growth: new evidence using long-run data," Applied Economics Letters, Taylor & Francis Journals, vol. 2(4), pages 98-102.
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    More about this item

    Keywords

    vector autoregression; forecast comparison;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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