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RALS-LM unit root test with trend breaks and non-normal errors: application to the Prebisch-Singer hypothesis

Author

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  • Meng Ming

    (Department of Economics, Finance and Legal Studies, University of Alabama, Box 870224, Tuscaloosa, AL 35487, USA)

  • Lee Junsoo

    (Department of Economics, Finance and Legal Studies, University of Alabama, Box 870224, Tuscaloosa, AL 35487, USA)

  • Payne James E.

    (Dean and Professor of Economics, J. Whitney Bunting College of Business, Georgia College and State University, Milledgeville, GA 31061, USA)

Abstract

This study proposes a new unit root test that allows for structural breaks in both the intercept and the slope, and adopts the residual augmented least squares (RALS) procedure to gain improved power when the error term follows a non-normal distribution. The new test using the RALS procedure is more powerful than the usual LM test which does not incorporate information on non-normal errors. Our test is free of nuisance parameters that indicate the locations of structural break. It is also free of the spurious rejection problem. Thus, the rejection of the null hypothesis can be considered as more accurate evidence of stationarity. We apply the new test on the recently extended Grilli and Yang index of 24 commodity series from 1900 to 2007. Our empirical findings provide significant evidence that primary commodity prices are stationary with one or two trend breaks. However, compared with past studies, our findings provide even weaker evidence to support the Prebisch-Singer hypothesis.

Suggested Citation

  • Meng Ming & Lee Junsoo & Payne James E., 2017. "RALS-LM unit root test with trend breaks and non-normal errors: application to the Prebisch-Singer hypothesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 31-45, February.
    • Handle: RePEc:bpj:sndecm:v:21:y:2017:i:1:p:31-45:n:6
    DOI: 10.1515/snde-2016-0050
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    References listed on IDEAS

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    More about this item

    Keywords

    Prebisch-Singer hypothesis; relative commodity prices; residual augmented least squares; trend break; unit root;
    All these keywords.

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • 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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