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The Impact of Integrated Measurement Errors on Modelling Long-run Macroeconomic Time Series

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  • James Duffy
  • David Hendry

Abstract

Abstract Data spanning long time periods, such as that over 1860–2012 for the UK, seem likely to have substantial errors of measurement that may even be integrated of order one, but which are probably cointegrated for cognate variables. We analyze and simulate the impacts of such measurement errors on parameter estimates and tests in a bivariate cointegrated system with trends and location shifts which reflect the many major turbulent events that have occurred historically. When trends or shifts therein are large, cointegration analysis is not much affected by such measurement errors, leading to conventional stationary attenuation biases dependent on the measurement-error variance, unlike the outcome when there are no offsetting shifts or trends.

Suggested Citation

  • James Duffy & David Hendry, 2017. "The Impact of Integrated Measurement Errors on Modelling Long-run Macroeconomic Time Series," Economics Series Working Papers 818, University of Oxford, Department of Economics.
    • Handle: RePEc:oxf:wpaper:818
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    References listed on IDEAS

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    1. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Felix Pretis, 2015. "Detecting Location Shifts during Model Selection by Step-Indicator Saturation," Econometrics, MDPI, vol. 3(2), pages 1-25, April.
    2. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    3. Hendry David F & Mizon Grayham E, 2011. "Econometric Modelling of Time Series with Outlying Observations," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-26, February.
    4. Neil R. Ericsson & James G. MacKinnon, 2002. "Distributions of error correction tests for cointegration," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 285-318, June.
    5. Hendry, David F. & Massmann, Michael, 2007. "Co-Breaking: Recent Advances and a Synopsis of the Literature," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 33-51, January.
    6. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
    7. Boyer, George R. & Hatton, Timothy J., 2002. "New Estimates Of British Unemployment, 1870–1913," The Journal of Economic History, Cambridge University Press, vol. 62(3), pages 643-675, September.
    8. Davidson, James E H, et al, 1978. "Econometric Modelling of the Aggregate Time-Series Relationship between Consumers' Expenditure and Income in the United Kingdom," Economic Journal, Royal Economic Society, vol. 88(352), pages 661-692, December.
    9. Haldrup, Niels & Meitz, Mika & Saikkonen, Pentti (ed.), 2014. "Essays in Nonlinear Time Series Econometrics," OUP Catalogue, Oxford University Press, number 9780199679959.
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    Cited by:

    1. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2021. "Modelling non-stationary ‘Big Data’," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1556-1575.
    2. Hendry, David F., 2018. "Deciding between alternative approaches in macroeconomics," International Journal of Forecasting, Elsevier, vol. 34(1), pages 119-135.
    3. David F. Hendry, 2020. "First in, First out: Econometric Modelling of UK Annual CO_2 Emissions, 1860–2017," Economics Papers 2020-W02, Economics Group, Nuffield College, University of Oxford.
    4. Bruns, Stephan B. & Csereklyei, Zsuzsanna & Stern, David I., 2020. "A multicointegration model of global climate change," Journal of Econometrics, Elsevier, vol. 214(1), pages 175-197.
    5. Santiago José Gahn & Alejandro González, 2020. "On the ‘utilisation controversy’: a comment," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 44(3), pages 703-707.
    6. Eric Hillebrand & Søren Johansen & Torben Schmith, 2020. "Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature," Econometrics, MDPI, vol. 8(4), pages 1-19, November.
    7. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2022. "The historical role of energy in UK inflation and productivity and implications for price inflation in 2022," Economics Series Working Papers 983, University of Oxford, Department of Economics.
    8. David F. Hendry, 2020. "A Short History of Macro-econometric Modelling," Economics Papers 2020-W01, Economics Group, Nuffield College, University of Oxford.

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    More about this item

    Keywords

    Integrated Measurement Errors; Location Shifts; Long-run Data; Cointegration;
    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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