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Is Robust Inference with OLS Sensible in Time Series Regressions? Investigating Bias and MSE Trade-offs with Feasible GLS and VAR Approaches

Listed author(s):
  • Richard T. Baillie

    ()

    (Department of Economics, Michigan State University, USA; School of Economics and Finance, Queen Mary University of London, UK; The Rimini Centre for Economic Analysis, Italy)

  • Kun Ho Kim

    ()

    (Department of Economics, Hanyang University, Republic of Korea)

Registered author(s):

    It has become commonplace in applied time series econometric work to estimate regressions with consistent, but asymptotically inefficient OLS and to base inference of conditional mean parameters on robust standard errors. This approach seems mainly to have occurred due to concern at the possible violation of strict exogeneity conditions from applying GLS. We first show that even in the case of the violation of contemporaneous exogeneity, that the asymptotic bias associated with GLS will generally be less than that of OLS. This result extends to Feasible GLS where the error process is approximated by a sieve autoregression. The paper also examines the trade-offs between asymptotic bias and efficiency related to OLS, feasible GLS and inference based on full system VAR. We also provide simulation evidence and several examples including tests of efficient markets, orange juice futures and weather and a control engineering application of furnace data. The evidence and general conclusion is that the widespread use of OLS with robust standard errors is generally not a good research strategy. Conversely, there is much to recommend FGLS and VAR system based estimation.

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    File URL: http://www.rcfea.org/RePEc/pdf/wp16-04.pdf
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    Paper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 16-04.

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    Date of creation: Mar 2016
    Handle: RePEc:rim:rimwps:16-04
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    1. Inoue, Atsushi & Kilian, Lutz, 2013. "Inference on impulse response functions in structural VAR models," Journal of Econometrics, Elsevier, vol. 177(1), pages 1-13.
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    12. Baillie, Richard T. & Kilic, Rehim, 2006. "Do asymmetric and nonlinear adjustments explain the forward premium anomaly?," Journal of International Money and Finance, Elsevier, vol. 25(1), pages 22-47, February.
    13. Baillie, Richard T. & Bollerslev, Tim, 1990. "A multivariate generalized ARCH approach to modeling risk premia in forward foreign exchange rate markets," Journal of International Money and Finance, Elsevier, vol. 9(3), pages 309-324, September.
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