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Testing for Serial Correlation by Variable Addition in Dynamic Models Estimated by Instrumental Variables

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  • Godfrey, L G

Abstract

Instrumental variable tests for serial correlation can be carried out by adding lagged residuals from initial estimation to the regressors of the model under scrutiny and then checking their joint significance. It is shown that asymptotically valid tests are obtained if the lagged residuals are also added to the initial instrument set. Monte Carlo evidence suggests that useful improvements in finite sample behavior under null and alternative hypotheses can be produced when the instrument set is extended to include the relevant lagged residuals. Links with other tests are discussed and a modification allowing for conditional heteroskedasticity is described. Copyright 1994 by MIT Press.

Suggested Citation

  • Godfrey, L G, 1994. "Testing for Serial Correlation by Variable Addition in Dynamic Models Estimated by Instrumental Variables," The Review of Economics and Statistics, MIT Press, vol. 76(3), pages 550-559, August.
  • Handle: RePEc:tpr:restat:v:76:y:1994:i:3:p:550-59
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    Cited by:

    1. Klaus Grobys, 2015. "Size distortions of the wild bootstrapped HCCME-based LM test for serial correlation in the presence of asymmetric conditional heteroskedasticity," Empirical Economics, Springer, pages 1189-1202.
    2. Chengsi Zhang & Denise R. Osborn & Dong Heon Kim, 2009. "Observed Inflation Forecasts and the New Keynesian Phillips Curve," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, pages 375-398.
    3. Chengsi Zhang & Joel Clovis, 2010. "The New Keynesian Phillips Curve of rational expectations: A serial correlation extension," Journal of Applied Economics, Universidad del CEMA, vol. 13, pages 159-179, May.
    4. Gordon H. Hanson & Antonio Spilimbergo, 2001. "Political economy, sectoral shocks, and border enforcement," Canadian Journal of Economics, Canadian Economics Association, vol. 34(3), pages 612-638, August.
    5. Chengsi Zhang & Denise R. Osborn & Dong Heon Kim, 2008. "The New Keynesian Phillips Curve: From Sticky Inflation to Sticky Prices," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(4), pages 667-699, June.
    6. Lei, Chengyao & Lu, Zhe & Zhang, Chengsi, 2015. "News on inflation and the epidemiology of inflation expectations in China," Economic Systems, Elsevier, vol. 39(4), pages 644-653.
    7. Godfrey, L.G. & Tremayne, A.R., 2005. "The wild bootstrap and heteroskedasticity-robust tests for serial correlation in dynamic regression models," Computational Statistics & Data Analysis, Elsevier, pages 377-395.
    8. Gordon H. Hanson & Raymond Robertson & Antonio Spilimbergo, 2002. "Does Border Enforcement Protect U.S. Workers From Illegal Immigration?," The Review of Economics and Statistics, MIT Press, pages 73-92.
    9. Zhang, Chengsi & Murasawa, Yasutomo, 2011. "Output gap measurement and the New Keynesian Phillips curve for China," Economic Modelling, Elsevier, vol. 28(6), pages 2462-2468.
    10. repec:mes:emfitr:v:52:y:2016:i:3:p:625-638 is not listed on IDEAS
    11. Alfred Guender & Yu Xie, 2007. "Is there an exchange rate channel in the forward-looking Phillips curve? A theoretical and empirical investigation," New Zealand Economic Papers, Taylor & Francis Journals, pages 5-28.
    12. Chengsi Zhang & Huidong He, 2016. "Globalization and Changing Inflation Dynamics in China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(3), pages 625-638, March.

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