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Instrumental Variables Estimation of Stationaryand Nonstationary Cointegrating Regressions

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  • M. Gerolimetto
  • Peter M Robinson

Abstract

Instrumental variables estimation is classically employed to avoid simultaneousequations bias in a stable environment. Here we use it to improve upon ordinaryleast squares estimation of cointegrating regressions between nonstationaryand/or long memory stationary variables where the integration orders of regressorand disturbance sum to less than 1, as happens always for stationary regressors,and sometimes for mean-reverting nonstationary ones. Unlike in the classicalsituation, instruments can be correlated with disturbances and/or uncorrelated withregressors. The approach can also be used in traditional non-fractionalcointegrating relations. Various choices of instrument are proposed. Finite sampleperformance is examined.

Suggested Citation

  • M. Gerolimetto & Peter M Robinson, 2006. "Instrumental Variables Estimation of Stationaryand Nonstationary Cointegrating Regressions," STICERD - Econometrics Paper Series 500, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Handle: RePEc:cep:stiecm:500
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    Cited by:

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    3. Hualde, J. & Robinson, P.M., 2010. "Semiparametric inference in multivariate fractionally cointegrated systems," Journal of Econometrics, Elsevier, vol. 157(2), pages 492-511, August.
    4. Hualde Javier & Iacone Fabrizio, 2012. "First Stage Estimation of Fractional Cointegration," Journal of Time Series Econometrics, De Gruyter, vol. 4(1), pages 1-32, May.
    5. Phillips, Peter C.B., 2014. "Optimal estimation of cointegrated systems with irrelevant instruments," Journal of Econometrics, Elsevier, vol. 178(P2), pages 210-224.
    6. Garcia-Swartz, Daniel D. & Muhamedagić, Mensur & Saenz, Diana, 2019. "The role of prices and network effects in the growth of the iPhone platform," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 110-122.
    7. Moshi, Goodiel Charles & Mwakatumbula, Hilda Jacob, 2017. "Effects of political stability and sector regulations on investments in African mobile markets," Telecommunications Policy, Elsevier, vol. 41(7), pages 651-661.

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    More about this item

    Keywords

    Cointegration; Instrumental variables estimation; I(d) processes.;
    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

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