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Deciding between alternative approaches in macroeconomics

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  • Hendry, David F.

Abstract

Macroeconomic time-series data are aggregated, inaccurate, non-stationary, collinear and rarely match theoretical concepts. Macroeconomic theories are incomplete, incorrect and changeable: location shifts invalidate the law of iterated expectations and ‘rational expectations’ are then systematically biased. Empirical macro-econometric models are non-constant and mis-specified in numerous ways, so economic policy often has unexpected effects, and macroeconomic forecasts go awry. In place of using just one of the four main methods of deciding between alternative models, theory, empirical evidence, policy relevance and forecasting, we propose nesting ‘theory-driven’ and ‘data-driven’ approaches, where theory-models’ parameter estimates are unaffected by selection despite searching over rival candidate variables, longer lags, functional forms, and breaks. Thus, theory is retained, but not imposed, so can be simultaneously evaluated against a wide range of alternatives, and a better model discovered when the theory is incomplete.

Suggested Citation

  • Hendry, David F., 2018. "Deciding between alternative approaches in macroeconomics," International Journal of Forecasting, Elsevier, vol. 34(1), pages 119-135.
  • Handle: RePEc:eee:intfor:v:34:y:2018:i:1:p:119-135
    DOI: 10.1016/j.ijforecast.2017.09.003
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    1. Roman Frydman & Soren Johansen & Anders Rahbek & Morten Tabor, 2019. "The Knightian Uncertainty Hypothesis: Unforeseeable Change and Muth`s Consistency Constraint in Modeling Aggregate Outcomes," Working Papers Series 92, Institute for New Economic Thinking.
    2. Ericsson, Neil R., 2017. "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, vol. 33(2), pages 523-542.
    3. Marta Boczon, 2018. "Balanced Growth Approach to Forecasting Recessions," Working Paper 6487, Department of Economics, University of Pittsburgh.
    4. Huang, Tao & Fildes, Robert & Soopramanien, Didier, 2019. "Forecasting retailer product sales in the presence of structural change," European Journal of Operational Research, Elsevier, vol. 279(2), pages 459-470.
    5. Ragnar Nymoen & Kari Pedersen & Jon Ivar Sjåberg, 2019. "Estimation of Effects of Recent Macroprudential Policies in a Sample of Advanced Open Economies," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 7(2), pages 1-20, May.
    6. Pawel Dlotko & Simon Rudkin & Wanling Qiu, 2019. "Topologically Mapping the Macroeconomy," Papers 1911.10476, arXiv.org.
    7. David F. Hendry, 2020. "A Short History of Macro-econometric Modelling," Economics Papers 2020-W01, Economics Group, Nuffield College, University of Oxford.
    8. Jennifer Castle & Takamitsu Kurita, 2019. "Modelling and forecasting the dollar-pound exchange rate in the presence of structural breaks," Economics Series Working Papers 866, University of Oxford, Department of Economics.
    9. Fakhri J. Hasanov & Jeyhun I. Mikayilov, 2020. "Revisiting Energy Demand Relationship: Theory and Empirical Application," Sustainability, MDPI, Open Access Journal, vol. 12(7), pages 1-15, April.
    10. Jennifer Castle & David Hendry, 2020. "Identifying the Causal Role of CO2 during the Ice Ages," Economics Series Working Papers 898, University of Oxford, Department of Economics.
    11. Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2020. "Smooth Robust Multi-Horizon Forecasts," Working Papers 2020-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    12. Roman Frydman & Soeren Johansen & Anders Rahbek & Morten Nyboe Tabor, 2019. "The Knightian Uncertainty Hypothesis: Unforeseeable Change and Muth�s Consistency Constraint in Modeling Aggregate Outcomes," Discussion Papers 19-02, University of Copenhagen. Department of Economics.
    13. Nymoen, Ragnar & Pedersen, Kari & Sjåberg, Jon Ivar, 2018. "Estimation of effects of recent macroprudential policies in a sample of advanced open economies," Memorandum 5/2018, Oslo University, Department of Economics.
    14. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2020. "Robust Discovery of Regression Models," Economics Papers 2020-W04, Economics Group, Nuffield College, University of Oxford.

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    More about this item

    Keywords

    Model selection; Theory retention; Location shifts; Indicator saturation; Autometrics;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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