IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v55y2011i9p2605-2618.html
   My bibliography  Save this article

Generalized method of moments estimation for cointegrated vector autoregressive models

Author

Listed:
  • Park, Suk K.
  • Ahn, Sung K.
  • Cho, Sinsup

Abstract

In this study, a generalized method of moments (GMM) for the estimation of nonstationary vector autoregressive models with cointegration is considered. Two iterative methods are considered: a simultaneous estimation method and a switching estimation method. The asymptotic properties of the GMM estimators of these methods are found to be the same as those of the Gaussian reduced-rank estimator. Through Monte Carlo simulation, the small-sample properties of the GMM estimators are studied and compared with those of the Gaussian reduced-rank estimator and the maximum likelihood estimator considered by other researchers. In the case of small samples, the GMM estimators are more robust to deviations from normality assumptions, particularly to outliers.

Suggested Citation

  • Park, Suk K. & Ahn, Sung K. & Cho, Sinsup, 2011. "Generalized method of moments estimation for cointegrated vector autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2605-2618, September.
  • Handle: RePEc:eee:csdana:v:55:y:2011:i:9:p:2605-2618
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947311001010
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Ralf Brüggemann & Helmut Lütkepohl, 2005. "Practical Problems with Reduced‐rank ML Estimators for Cointegration Parameters and a Simple Alternative," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(5), pages 673-690, October.
    3. Matyas,Laszlo (ed.), 1999. "Generalized Method of Moments Estimation," Cambridge Books, Cambridge University Press, number 9780521669672, September.
    4. Kitamura, Yuichi & Phillips, Peter C. B., 1997. "Fully modified IV, GIVE and GMM estimation with possibly non-stationary regressors and instruments," Journal of Econometrics, Elsevier, vol. 80(1), pages 85-123, September.
    5. Ahn, Sung K. & Reinsel, Gregory C., 1994. "Estimation of partially nonstationary vector autoregressive models with seasonal behavior," Journal of Econometrics, Elsevier, vol. 62(2), pages 317-350, June.
    6. Quintos, Carmela E., 1998. "Analysis of cointegration vectors using the GMM approach," Journal of Econometrics, Elsevier, vol. 85(1), pages 155-188, July.
    7. Kim, In-Moo & Park, Joon Y., 2005. "Iterative Maximum Likelihood Estimation of Cointegrating Vectors," Working Papers 2005-02, Rice University, Department of Economics.
    8. Bossaerts, Peter, 1988. "Common nonstationary components of asset prices," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 347-364.
    9. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    10. Gonzalo, Jesus, 1994. "Five alternative methods of estimating long-run equilibrium relationships," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 203-233.
    11. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    12. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679.
    13. Stock, James H, 1987. "Asymptotic Properties of Least Squares Estimators of Cointegrating Vectors," Econometrica, Econometric Society, vol. 55(5), pages 1035-1056, September.
    14. Matyas,Laszlo (ed.), 1999. "Generalized Method of Moments Estimation," Cambridge Books, Cambridge University Press, number 9780521660136, September.
    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. Shang, Wenpeng & Wang, Xiao, 2017. "The generalized moment estimation of the additive–multiplicative hazard model with auxiliary survival information," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 154-169.
    2. Sikora, Grzegorz & Michalak, Anna & Bielak, Łukasz & Miśta, Paweł & Wyłomańska, Agnieszka, 2019. "Stochastic modeling of currency exchange rates with novel validation techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1202-1215.
    3. Nicoleta ISAC & Cosmin DOBRIN & Mehmood HUSSAN & Asad ul Islam KHAN & Alina- Andreea MARIN, 2020. "On The Ranks Of Tests Having Null Of Cointegration: A Monte Carlo Comparison," Management Research and Practice, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 12(2), pages 58-69, June.

    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. W. David Walls & Kelly Busche, 1996. "Betting volume and market efficiency in Hong Kong race track betting," Applied Economics Letters, Taylor & Francis Journals, vol. 3(12), pages 783-787.
    2. Aparicio, Felipe M. & Escribano, Álvaro & Mármol, Francesc, 1999. "A new instrumental variable approach for estimation and testing in fractional cointegrating regressions," DES - Working Papers. Statistics and Econometrics. WS 6298, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Dina Azhgaliyeva, 2013. "What Makes Oil Revenue Funds Effective," International Conference on Energy, Regional Integration and Socio-economic Development 6023, EcoMod.
    4. Kühl, Michael, 2007. "Cointegration in the foreign exchange market and market efficiency since the introduction of the Euro: Evidence based on bivariate cointegration analyses," University of Göttingen Working Papers in Economics 68, University of Goettingen, Department of Economics.
    5. John Geweke & Joel Horowitz & M. Hashem Pesaran, 2006. "Econometrics: A Bird’s Eye View," CESifo Working Paper Series 1870, CESifo.
    6. Mudit Kulsreshtha & Barnali Nag, 2000. "Structure and dynamics of non-suburban passenger travel demand in Indian railways," Transportation, Springer, vol. 27(2), pages 221-241, May.
    7. Hallin, M. & van den Akker, R. & Werker, B.J.M., 2012. "Rank-based Tests of the Cointegrating Rank in Semiparametric Error Correction Models," Other publications TiSEM bc68a2f2-3ca3-443c-b3ac-f, Tilburg University, School of Economics and Management.
    8. Li, Qiaoling & Pan, Jiazhu & Yao, Qiwei, 2009. "On determination of cointegration ranks," LSE Research Online Documents on Economics 24106, London School of Economics and Political Science, LSE Library.
    9. Kulshreshtha, Mudit & Parikh, Jyoti K., 2000. "Modeling demand for coal in India: vector autoregressive models with cointegrated variables," Energy, Elsevier, vol. 25(2), pages 149-168.
    10. Bednarek, Ziemowit, 2016. "Pure technology gaps and production predictability," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 39-50.
    11. Groen, Jan J J & Kleibergen, Frank, 2003. "Likelihood-Based Cointegration Analysis in Panels of Vector Error-Correction Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 295-318, April.
    12. Jaramillo Franco, Miguel & Serván Lozano, Sergio, 2012. "Modeling exchange rate dynamics in Peru: A cointegration approach using the UIP and PPP," MPRA Paper 70772, University Library of Munich, Germany.
    13. Haug, Alfred A., 1999. "Testing linear restrictions on cointegration vectors: Sizes and powers of Wald tests in finite samples," Technical Reports 1999,04, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    14. Masuda, Tadayoshi & Goldsmith, Peter D., 2012. "China's Meat and Egg Production and Soybean Meal Demand for Feed: An Elasticity Analysis and Long-Term Projections," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 15(3), pages 1-20, September.
    15. Herzer, Dierk & Nunnenkamp, Peter, 2013. "Private Donations, Government Grants, Commercial Activities, and Fundraising: Cointegration and Causality for NGOs in International Development Cooperation," World Development, Elsevier, vol. 46(C), pages 234-251.
    16. Chandran, V.G.R. & Tang, Chor Foon, 2013. "The impacts of transport energy consumption, foreign direct investment and income on CO2 emissions in ASEAN-5 economies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 445-453.
    17. Kirstin Hubrich & Helmut Lutkepohl & Pentti Saikkonen, 2001. "A Review Of Systems Cointegration Tests," Econometric Reviews, Taylor & Francis Journals, vol. 20(3), pages 247-318.
    18. Gabriel Pons Rotger, 2000. "Temporal Aggregation and Ordinary Least Squares Estimation of Cointegrating Regressions," Econometric Society World Congress 2000 Contributed Papers 1317, Econometric Society.
    19. Quintos, Carmela E., 1998. "Analysis of cointegration vectors using the GMM approach," Journal of Econometrics, Elsevier, vol. 85(1), pages 155-188, July.
    20. Minxian, Yang, 1998. "System estimators of cointegrating matrix in absence of normalising information," Journal of Econometrics, Elsevier, vol. 85(2), pages 317-337, August.

    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:eee:csdana:v:55:y:2011:i:9:p:2605-2618. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.