IDEAS home Printed from https://ideas.repec.org/p/cte/wsrepe/6300.html

Ols-based asymptotic inference in linear regression models with trending regressors and ar(p)-disturbances

Author

Listed:
  • Krämer, Walter
  • Mármol, Francesc

Abstract

We show that OLS and GLS are asymptotically equivalent in the linear regression model with AR(p)-9isturbances and a wide range of trending regressors, and that OLS-based statistical inference is still meaningful after proper adjustment of the teststatistics.

Suggested Citation

  • Krämer, Walter & Mármol, Francesc, 1999. "Ols-based asymptotic inference in linear regression models with trending regressors and ar(p)-disturbances," DES - Working Papers. Statistics and Econometrics. WS 6300, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:6300
    as

    Download full text from publisher

    File URL: https://e-archivo.uc3m.es/rest/api/core/bitstreams/03198124-e948-49c1-863a-c5f32ecbd82f/content
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dolado, Juan José & Mármol, Francesc, 1999. "Asymptotic inference for monstationary fractionally integrated processes," DES - Working Papers. Statistics and Econometrics. WS 6350, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Hansen, Bruce E., 1992. "Convergence to Stochastic Integrals for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, vol. 8(4), pages 489-500, December.
    3. Sowell, Fallaw, 1990. "The Fractional Unit Root Distribution," Econometrica, Econometric Society, vol. 58(2), pages 495-505, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. is not listed on IDEAS
    2. Dedi Rosadi & Shelton Peiris, 2014. "Second-order least-squares estimation for regression models with autocorrelated errors," Computational Statistics, Springer, vol. 29(5), pages 931-943, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alex Maynard & Peter C. B. Phillips, 2001. "Rethinking an old empirical puzzle: econometric evidence on the forward discount anomaly," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(6), pages 671-708.
    2. Christensen, Bent Jesper & Kruse, Robinson & Sibbertsen, Philipp, 2013. "A unified framework for testing in the linear regression model under unknown order of fractional integration," Hannover Economic Papers (HEP) dp-519, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. SangKun Bae & Mark J. Jensen, 1998. "Long-Run Neutrality in a Long-Memory Model," Macroeconomics 9809006, University Library of Munich, Germany, revised 21 Apr 1999.
    4. Arai, Yoichi, 2016. "Testing For Linearity In Regressions With I(1) Processes," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 57(1), pages 111-138, June.
    5. Pentti Saikkonen & Rickard Sandberg, 2016. "Testing for a Unit Root in Noncausal Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(1), pages 99-125, January.
    6. Gadea, Maria Dolores & Sabate, Marcela & Serrano, Jose Maria, 2004. "Structural breaks and their trace in the memory: Inflation rate series in the long-run," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 117-134, April.
    7. Christian Macaro, 2007. "The Impact of Vintage on the Persistence of Gross Domestic Product Shocks," CEIS Research Paper 101, Tor Vergata University, CEIS.
    8. Barbara Rossi & Tatevik Sekhposyan, 2016. "Forecast Rationality Tests in the Presence of Instabilities, with Applications to Federal Reserve and Survey Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 507-532, April.
    9. Kuo, Biing-Shen, 1998. "Test for partial parameter instability in regressions with I(1) processes," Journal of Econometrics, Elsevier, vol. 86(2), pages 337-368, June.
    10. Juan J. Dolado & Jesús Gonzalo & Laura Mayoral, 2005. "What is what?: A simple time-domain test of long-memory vs. structural breaks," Economics Working Papers 954, Department of Economics and Business, Universitat Pompeu Fabra.
    11. Robinson Kruse & Christoph Wegener, 2019. "Explosive behaviour and long memory with an application to European bond yield spreads," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 139-153, February.
    12. Zongwu Cai & Bingyi Jing & Xinbing Kong & Zhi Liu, 2017. "Nonparametric regression with nearly integrated regressors under long‐run dependence," Econometrics Journal, Royal Economic Society, vol. 20(1), pages 118-138, February.
    13. Andrews, Donald W.K. & Guggenberger, Patrik, 2012. "Asymptotics for LS, GLS, and feasible GLS statistics in an AR(1) model with conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 169(2), pages 196-210.
    14. Hwan Seo, Myung, 2011. "Estimation Of Nonlinear Error Correction Models," Econometric Theory, Cambridge University Press, vol. 27(2), pages 201-234, April.
    15. Lui, Yiu Lim & Phillips, Peter C.B. & Yu, Jun, 2024. "Robust testing for explosive behavior with strongly dependent errors," Journal of Econometrics, Elsevier, vol. 238(2).
    16. Bhattacharyya, B.B. & Richardson, G.D. & Flores, P.V., 2006. "Unit roots: Periodogram ordinate," Statistics & Probability Letters, Elsevier, vol. 76(6), pages 641-651, March.
    17. Li, Dao & He, Changli, 2012. "Testing for Linear Cointegration Against Smooth-Transition Cointegration," Working Papers 2012:6, Örebro University, School of Business.
    18. Laura Mayoral, 2007. "Minimum distance estimation of stationary and non-stationary ARFIMA processes," Econometrics Journal, Royal Economic Society, vol. 10(1), pages 124-148, March.
    19. Atsushi Inoue & Lutz Kilian, 2005. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," Econometric Reviews, Taylor & Francis Journals, vol. 23(4), pages 371-402.
    20. Demetrescu, Matei & Georgiev, Iliyan & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2022. "Testing for episodic predictability in stock returns," Journal of Econometrics, Elsevier, vol. 227(1), pages 85-113.

    More about this item

    Keywords

    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cte:wsrepe:6300. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ana Poveda (email available below). General contact details of provider: http://portal.uc3m.es/portal/page/portal/dpto_estadistica .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.