IDEAS home Printed from https://ideas.repec.org/p/sce/scecf0/161.html
   My bibliography  Save this paper

Applications Of Public Global Optimization Software To Difficult Econometric Functions

Author

Listed:
  • Max Jerrell

    (Northern Arizona University)

Abstract

The location of the global optimum is very desirable in nonlinear parameter estimation problems. Using a local rather than global optimum most likely will result in inconsistent estimators. While many commercial software packages have good optimization routines, these usually only find local optima. Some of these commercial packages also have only limited capability to express constraints. Likewise, these packages often do not allow users to define their own functions.There is a large and growing amount of freely available software that has a good chance of locating the global optimum. New techniques are being developed and existing methods are being refined. Much of the software can be downloaded over the Internet.This research will survey this software and compare different techniques. Methods of obtaining the software will also be discussed. Finally some of the more promising software will be applied to difficult econometric functions (GARCH models and disequilibrium models).

Suggested Citation

  • Max Jerrell, 2000. "Applications Of Public Global Optimization Software To Difficult Econometric Functions," Computing in Economics and Finance 2000 161, Society for Computational Economics.
    • Handle: RePEc:sce:scecf0:161
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/cef00/papers/paper161.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Dorsey, Robert E & Mayer, Walter J, 1995. "Genetic Algorithms for Estimation Problems with Multiple Optima, Nondifferentiability, and Other Irregular Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 53-66, January.
    3. Maddala, G S & Nelson, Forrest D, 1974. "Maximum Likelihood Methods for Models of Markets in Disequilibrium," Econometrica, Econometric Society, vol. 42(6), pages 1013-1030, November.
    4. Goffe, William L & Ferrier, Gary D & Rogers, John, 1992. "Simulated Annealing: An Initial Application in Econometrics," Computer Science in Economics & Management, Kluwer;Society for Computational Economics, vol. 5(2), pages 133-146, May.
    5. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    6. Stephen P. Brooks, 1995. "A Hybrid Optimization Algorithm," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 44(4), pages 530-533, December.
    7. Mayer, Walter J., 1989. "Estimating disequilibrium models with limited a priori price-adjustment information," Journal of Econometrics, Elsevier, vol. 41(3), pages 303-320, July.
    8. Fair, Ray C & Kelejian, Harry H, 1974. "Methods of Estimation for Markets in Disequilibrium: A Further Study," Econometrica, Econometric Society, vol. 42(1), pages 177-190, January.
    9. Fair, Ray C & Jaffee, Dwight M, 1972. "Methods of Estimation for Markets in Disequilibrium," Econometrica, Econometric Society, vol. 40(3), pages 497-514, May.
    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. Mayer, Walter J. & Dorsey, Robert E., 1998. "Maximum score estimation of disequilibrium models and the role of anticipatory price-setting," Journal of Econometrics, Elsevier, vol. 87(1), pages 1-24, August.
    2. Tucci, Marco P., 2002. "A note on global optimization in adaptive control, econometrics and macroeconomics," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1739-1764, August.
    3. Zilinskas, Julius & Bogle, Ian David Lockhart, 2006. "Balanced random interval arithmetic in market model estimation," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1367-1378, December.
    4. Max E. Jerrell, "undated". "Automatic Differentiation and Interval Arithmetic for Estimation of Disequilibrium Models," Computing in Economics and Finance 1996 _028, Society for Computational Economics.
    5. Tensie Steijvers & Wim Voordeckers, 2009. "Collateral And Credit Rationing: A Review Of Recent Empirical Studies As A Guide For Future Research," Journal of Economic Surveys, Wiley Blackwell, vol. 23(5), pages 924-946, December.
    6. M. Bierlaire & M. Thémans & N. Zufferey, 2010. "A Heuristic for Nonlinear Global Optimization," INFORMS Journal on Computing, INFORMS, vol. 22(1), pages 59-70, February.
    7. Manfred GILLI & Peter WINKER, 2008. "A review of heuristic optimization methods in econometrics," Swiss Finance Institute Research Paper Series 08-12, Swiss Finance Institute.
    8. Debrecht, Dennis Michael, 1981. "Lending limits and the availability of credit to agricultural borrowers," ISU General Staff Papers 198101010800008411, Iowa State University, Department of Economics.
    9. Lee, Lung-Fei, 1997. "A smooth likelihood simulator for dynamic disequilibrium models," Journal of Econometrics, Elsevier, vol. 78(2), pages 257-294, June.
    10. Juan Luis Vega, 1992. "El papel del crédito en el mecanismo de transmisión monetaria," Estudios Económicos, Banco de España, number 48.
    11. Seyedeh Asieh H. Tabaghdehi, 2018. "Market collusion and regime analysis in the US gasoline market," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 7(1), pages 1-14, December.
    12. Eric Wong & Andrew Tsang & Steven Kong, 2014. "How Does Loan-To-Value Policy Strengthen Banks' Resilience to Property Price Shocks - Evidence from Hong Kong," Working Papers 032014, Hong Kong Institute for Monetary Research.
    13. Hurlin, Christophe & Kierzenkowski, Rafal, 2007. "Credit market disequilibrium in Poland: Can we find what we expect?: Non-stationarity and the short-side rule," Economic Systems, Elsevier, vol. 31(2), pages 157-183, June.
    14. Amilon, Henrik, 2008. "Estimation of an adaptive stock market model with heterogeneous agents," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 342-362, March.
    15. Dilip M. Nachane & Prasad P. Ranade, 2005. "Relationship banking and the credit market in India: An empirical analysis," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2005-10, Indira Gandhi Institute of Development Research, Mumbai, India.
    16. Ogawa, Shogo, 2022. "Survey of non-Walrasian disequilibrium economic theory," MPRA Paper 115011, University Library of Munich, Germany.
    17. Mika Meitz & Daniel Preve & Pentti Saikkonen, 2023. "A mixture autoregressive model based on Student’s t–distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 52(2), pages 499-515, January.
    18. Paul D. McNelis & G.C. Lim, 1998. "Parameterizing Currency Risk in the EMS: The Irish Pound and Spanish Peseta against the German Mark," International Finance 9805001, University Library of Munich, Germany.
    19. Henrik Amilon, 2002. "A Score Test for Discreteness in GARCH Models," Research Paper Series 76, Quantitative Finance Research Centre, University of Technology, Sydney.
    20. Harvey, A. & Chakravarty, T., 2008. "Beta-t-(E)GARCH," Cambridge Working Papers in Economics 0840, Faculty of Economics, University of Cambridge.

    More about this item

    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:sce:scecf0:161. 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/sceeeea.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.