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Modelling an Emergent Economy and Parameter Instability Problem

Author

Listed:
  • Emilian DOBRESCU

    (Centre for Macroeconomic Modelling, “Costin C. Kiritescu” National Institute of Economic Research, Romanian Academy.)

Abstract
The paper examines a largely debated and important modelling problem – the instability of the econometric parameters, which has unpleasant consequences on both analytical and predictive planes. The modification of the estimators and/or of the standard deviations of a given model parameter when identical specifications and computational algorithms are applied on different statistical samples is considered to be its main manifestation. Several sources generating such a phenomenon may be identified: (i) statistical properties of the initial sample (mean, skewness, kurtosis, variance, outliers); (ii) econometric specification (selected explanatory factors and their functional connection with the dependent variables); (iii) changes in statistical data due to revisions; and (iv) dynamic instability, resulted from inherent changeability of real economic behaviours (consumer preferences, risk aversion of investors, households saving propensity, input-output coefficients and sectoral inter-flows, taxation system, domestic institutional context, foreign trade, international financial markets, and many other similar circumstances). For all these types, specific indicators and quantifying methodologies are proposed. As an illustration, we analysed the last version (2012) of the Romanian model, the macroeconomic parameters of which (182) were estimated using two computational algorithms (OLS and 2SLS) for seven samples: initial data for 1990-2011, the same series updated, and subsequent from 1990 to 2012, 2013, 2014, 2015, and 2016. Possible solutions to attenuate the parameter instability implications are also described, exemplifying them on the Romanian macromodel predictive simulations for 2017-2018 years. Some practical recommendations and further research topics are commented in the final part of the paper.

Suggested Citation

  • Emilian DOBRESCU, 2017. "Modelling an Emergent Economy and Parameter Instability Problem," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-28, June.
  • Handle: RePEc:rjr:romjef:v::y:2017:i:2:p:5-28
    as

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    File URL: http://www.ipe.ro/rjef/rjef2_17/rjef2_2017p5-28.pdf
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    References listed on IDEAS

    as
    1. Stevanovic Dalibor, 2016. "Common time variation of parameters in reduced-form macroeconomic models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(2), pages 159-183, April.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. Rossi, Barbara, 2005. "Optimal Tests For Nested Model Selection With Underlying Parameter Instability," Econometric Theory, Cambridge University Press, vol. 21(5), pages 962-990, October.
    4. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
    5. Francesco Calvori & Drew Creal & Siem Jan Koopman & Andre Lucas, 2014. "Testing for Parameter Instability in Competing Modeling Frameworks," Tinbergen Institute Discussion Papers 14-010/IV/DSF71, Tinbergen Institute.
    6. Davide Pettenuzzo & Allan Timmermann, 2017. "Forecasting Macroeconomic Variables Under Model Instability," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 183-201, April.
    7. Pasquale Della Corte & Lucio Sarno & Ilias Tsiakas, 2009. "An Economic Evaluation of Empirical Exchange Rate Models," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3491-3530, September.
    8. Hall, Stephen G. & Swamy, P. A. V. B. & Tavlas, George S., 2017. "Time-Varying Coefficient Models: A Proposal For Selecting The Coefficient Driver Sets," Macroeconomic Dynamics, Cambridge University Press, vol. 21(5), pages 1158-1174, July.
    9. Emilian Dobrescu, 2014. "Attempting to Quantify the Accuracy of Complex Macroeconomic Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-21, December.
    10. Dufour, Jean-Marie, 1982. "Recursive stability analysis of linear regression relationships: An exploratory methodology," Journal of Econometrics, Elsevier, vol. 19(1), pages 31-76, May.
    11. Chris Birchenhall & Denise Osborn & Marianne Sensier, 2001. "Predicting UK Business Cycle Regimes," Scottish Journal of Political Economy, Scottish Economic Society, vol. 48(2), pages 179-195, May.
    12. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    13. M. Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2006. "Forecasting Time Series Subject to Multiple Structural Breaks," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 73(4), pages 1057-1084.
    14. Benavides Guillermo, 2006. "Volatility Forecasts for the Mexican Peso - U.S. Dollar Exchange Rate: An Empirical Analysis of Garch, Option Implied and Composite Forecast Models," Working Papers 2006-04, Banco de México.
    15. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
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    More about this item

    Keywords

    macromodel; parameters instability; simulation;
    All these keywords.

    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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