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Robust Inference on Average Economic Growth

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  • H. Peter Boswijk
  • Philip Hans Franses

Abstract

We discuss a method to estimate the confidence bounds for average economic growth, which is robust to misspecification of the unit root property of a given time series. We derive asymptotic theory for the consequences of such misspecification. Our empirical method amounts to an implementation of the subsampling procedure advocated in Romano and Wolf (Econometrica, 2001, Vol. 69, p. 1283). Simulation evidence supports the theory and it also indicates the practical relevance of the subsampling method. We use quarterly postwar US industrial production for illustration and we show that non‐robust approaches rather lead to different conclusions on average economic growth than our robust approach.

Suggested Citation

  • H. Peter Boswijk & Philip Hans Franses, 2006. "Robust Inference on Average Economic Growth," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(3), pages 345-370, June.
    • Handle: RePEc:bla:obuest:v:68:y:2006:i:3:p:345-370
    DOI: 10.1111/j.1468-0084.2006.00165.x
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    Cited by:

    1. Ke-Li Xu & Jui-Chung Yang, 2015. "Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non-stationary Volatility," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 63-86, March.
    2. G. K. Randolph Tan, 2006. "Robust Inference for Measures of Persistence in Singapore Sectoral Property Price Indexes," Journal of Property Research, Taylor & Francis Journals, vol. 23(4), pages 305-321, October.

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