IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/15100.html
   My bibliography  Save this paper

Cross-Entropy Estimation of Linear Cointegrated Equations

Author

Listed:
  • Balcombe, Kelvin

Abstract

The cross-entropy approach is extended to the estimation of cointegrated equations. The entropy estimators for an appropriately constructed moment form, are asymptotically equivalent to Fully Modi�ed estimators since they converge to these estimates su¢ ciently quickly. The performance of the entropy estimators are examined by using some Monte Carlo trials, and in an applied example for the estimation of a production function for South African agriculture.

Suggested Citation

  • Balcombe, Kelvin, 2006. "Cross-Entropy Estimation of Linear Cointegrated Equations," MPRA Paper 15100, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:15100
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/15100/1/MPRA_paper_15100.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peter C. B. Phillips & Bruce E. Hansen, 1990. "Statistical Inference in Instrumental Variables Regression with I(1) Processes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(1), pages 99-125.
    2. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    3. Paris, Quirino, 2001. "Mele: Maximum Entropy Leuven Estimators," Working Papers 11991, University of California, Davis, Department of Agricultural and Resource Economics.
    4. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    5. Xiao, Zhijie & Phillips, Peter C. B., 2002. "Higher order approximations for Wald statistics in time series regressions with integrated processes," Journal of Econometrics, Elsevier, vol. 108(1), pages 157-198, May.
    6. Golan, Amos, 2002. "Information and Entropy Econometrics--Editor's View," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 1-15, March.
    7. Golan, Amos & Perloff, Jeffrey M., 2002. "Comparison of maximum entropy and higher-order entropy estimators," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 195-211, March.
    8. Marsh, Thomas L. & Mittelhammer, Ronald C. & Cardell, N. Scott, 1998. "A Structural-Equation Gme Estimator," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20890, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Harmon, Alice & Preckel, Paul V. & Eales, James S., 1998. "Entropy-Based Seemingly Unrelated Regression," Staff Papers 28682, Purdue University, Department of Agricultural Economics.
    10. Golan, Amos & Judge, George & Perloff, Jeffrey, 1997. "Estimation and inference with censored and ordered multinomial response data," Journal of Econometrics, Elsevier, vol. 79(1), pages 23-51, July.
    11. Paul V. Preckel, 2001. "Least Squares and Entropy: A Penalty Function Perspective," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(2), pages 366-377.
    Full references (including those not matched with items on IDEAS)

    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. Golan Amos, 2003. "An Information Theoretic Approach for Estimating Nonlinear Dynamic Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(4), pages 1-26, December.
    2. R. Carter Hill & Randall C. Campbell, 2001. "Maximum Entropy Estimation in Economic Models with Linear Inequality Restrictions," Departmental Working Papers 2001-11, Department of Economics, Louisiana State University.
    3. Cook, Larry & Harslett, Philip, 2015. "An introduction to entropy estimation of parameters in economic models," Conference papers 332651, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    4. Esteban Fernández-Vázquez & Matías Mayor-Fernández & Jorge Rodríguez-Vález, 2009. "Estimating Spatial Autoregressive Models by GME-GCE Techniques," International Regional Science Review, , vol. 32(2), pages 148-172, April.
    5. Matteo Mogliani, 2010. "Residual-based tests for cointegration and multiple deterministic structural breaks: A Monte Carlo study," Working Papers halshs-00564897, HAL.
    6. Hong, Seung Hyun & Phillips, Peter C. B., 2010. "Testing Linearity in Cointegrating Relations With an Application to Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 96-114.
    7. Ekaterini Panopoulou, 2005. "A Resolution of the Fisher Effect Puzzle: A Comparison of Estimators," Money Macro and Finance (MMF) Research Group Conference 2005 18, Money Macro and Finance Research Group.
    8. Wang, Yafeng & Graham, Brett, 2009. "Generalized Maximum Entropy estimation of discrete sequential move games of perfect information," MPRA Paper 21331, University Library of Munich, Germany.
    9. Arndt, Channing & Simler, Kenneth R., 2005. "Estimating utility-consistent poverty lines," FCND briefs 189, International Food Policy Research Institute (IFPRI).
    10. Amos Golan & Enrico Moretti & Jeffrey M.Perloff, 2004. "A Small-Sample Estimator for the Sample-Selection Model," Econometric Reviews, Taylor & Francis Journals, vol. 23(1), pages 71-91.
    11. Bunzel, Helle, 2006. "FIXED-b ASYMPTOTICS IN SINGLE-EQUATION COINTEGRATION MODELS WITH ENDOGENOUS REGRESSORS," Econometric Theory, Cambridge University Press, vol. 22(4), pages 743-755, August.
    12. Christoph Hanck & Till Massing, 2021. "Testing for Nonlinear Cointegration under Heteroskedasticity," Papers 2102.08809, arXiv.org, revised Oct 2024.
    13. Jungbin Hwang & Gonzalo Valdés, 2020. "Low Frequency Cointegrating Regression in the Presence of Local to Unity Regressors and Unknown Form of Serial Dependence," Working papers 2020-03, University of Connecticut, Department of Economics, revised Aug 2020.
    14. Kejriwal, Mohitosh & Perron, Pierre, 2010. "Testing for Multiple Structural Changes in Cointegrated Regression Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(4), pages 503-522.
    15. Erasmo Papagni & Amedeo Lepore & Emanuele Felice & Anna Laura Baraldi & Maria Rosaria Alfano, 2018. "Public Investment and Growth Accelerations: The Case of Southern Italy, 1951-1995," EERI Research Paper Series EERI RP 2018/10, Economics and Econometrics Research Institute (EERI), Brussels.
    16. Rapach, David E. & Wohar, Mark E., 2002. "Testing the monetary model of exchange rate determination: new evidence from a century of data," Journal of International Economics, Elsevier, vol. 58(2), pages 359-385, December.
    17. Meng Lin, 2022. "The Conflict between Technology and Scale: Evidence from China’s Wooden Furniture Industry," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
    18. Ramzi Issa & Robert Lafrance & John Murray, 2008. "The turning black tide: energy prices and the Canadian dollar," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(3), pages 737-759, August.
    19. Youngsoo Bae & Robert M. de Jong, 2007. "Money demand function estimation by nonlinear cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 767-793.
    20. Fabienne Femenia & Alexandre Gohin, 2007. "Estimating censored and non homothetic demand systems : the generalized maximum entropy appoach," Post-Print hal-02814735, HAL.

    More about this item

    Keywords

    Entropy; Fully Modified; Cointegration;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

    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:pra:mprapa:15100. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.