IDEAS home Printed from https://ideas.repec.org/p/cor/louvco/2004012.html
   My bibliography  Save this paper

Bridging the gap between Ox and Gauss using OxGauss

Author

Listed:
  • LAURENT, Sébastien
  • URBAIN, Jean-Pierre

Abstract

The purpose of this paper is to review and discuss the key improvements brought to OxGauss. Without having to install Gauss on his or her machine, the OxGauss user can run under Ox a wide range of Gauss programs and codes. Even with the consoleOx version (free for academics), Gauss codes can either be called from Ox programs or run and executed on their own. While the new OxGauss version is very powerful in most circumstances, it is of little use once the purpose is to execute programs thatattempt to solve optimization problems using Cml, Maxlik or Optmum. In this paper we propose a set of additional procedures that contribute to bridge the gap between Ox and three well-known Gauss application modules: Cml, Maxlik or Optmum.The effectiveness of our procedures is illustrated by revisiting a large number of freely available Gauss codes in which numerical optimization relies on the above Gauss application modules. The Gauss codes include many programs dealing with nonlinear models such as the Markov regime-switching models STAR models and various GARCH-type models. These illustrations highlight a further potentially interesting implication of OxGauss: it enables non-Gauss users to replicate existing empiricalresults using freely available Gauss codes.

Suggested Citation

  • LAURENT, Sébastien & URBAIN, Jean-Pierre, 2004. "Bridging the gap between Ox and Gauss using OxGauss," LIDAM Discussion Papers CORE 2004012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvco:2004012
    as

    Download full text from publisher

    File URL: https://sites.uclouvain.be/core/publications/coredp/coredp2004.html
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, September.
    2. L. Yang & R. Tschernig, 1999. "Multivariate bandwidth selection for local linear regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(4), pages 793-815.
    3. Francisco Cribari-Neto & Spyros Zarkos, 2003. "Econometric and Statistical Computing Using Ox," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 277-295, June.
    4. repec:bla:jecsur:v:16:y:2002:i:3:p:447-85 is not listed on IDEAS
    5. S»bastien Laurent and Jean-Philippe Peters, 2001. "G@RCH 2.0: An Ox Package for Estimating and Forecasting Various ARCH Models," Computing in Economics and Finance 2001 123, Society for Computational Economics.
    6. Cribari-Neto, Francisco, 1997. "Econometric Programming Environments: GAUSS, Ox and S-PLUS," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(1), pages 77-89, Jan.-Feb..
    7. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, April.
    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. Maus, Stefan & Peters, Hans & Storcken, Ton, 2007. "Anonymous voting and minimal manipulability," Journal of Economic Theory, Elsevier, vol. 135(1), pages 533-544, July.
    2. Lok, R.B. & Romero Morales, D. & Vermeulen, A.J., 2005. "The agents-are-substitutes property in continuous generalized assignment problems," Research Memorandum 009, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    3. Benoit Bellone, 2005. "Classical Estimation of Multivariate Markov-Switching Models using MSVARlib," Econometrics 0508017, University Library of Munich, Germany.

    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. Maus, S. & Peters, H.J.M. & Storcken, A.J.A., 2004. "Minimal manipulability: anonymity and surjectivity," Research Memorandum 007, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    2. Jaehee Kim & Sooyoung Cheon, 2010. "A Bayesian regime‐switching time‐series model," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 365-378, September.
    3. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    4. Richard H. Clarida & Lucio Sarno & Mark P. Taylor & Giorgio Valente, 2006. "The Role of Asymmetries and Regime Shifts in the Term Structure of Interest Rates," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1193-1224, May.
    5. Peter Tillmann, 2003. "The Regime‐Dependent Determination of Credibility: A New Look at European Interest Rate Differentials," German Economic Review, Verein für Socialpolitik, vol. 4(4), pages 409-431, November.
    6. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, October.
    7. Kulaksizoglu, Tamer, 2015. "Object-Oriented Econometrics with Ox," MPRA Paper 62545, University Library of Munich, Germany.
    8. Monica Billio & Laurent Ferrara & Dominique Guegan & Gian Luigi Mazzi, 2009. "Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro," Documents de travail du Centre d'Economie de la Sorbonne 09053, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    9. Sascha Mergner & Jan Bulla, 2008. "Time-varying beta risk of Pan-European industry portfolios: A comparison of alternative modeling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 771-802.
    10. Baik, Hyeoncheol & Han, Sumin & Joo, Sunghoon & Lee, Kangbok, 2022. "A bank's optimal capital ratio: A time-varying parameter model to the partial adjustment framework," Journal of Banking & Finance, Elsevier, vol. 142(C).
    11. Michael Frömmel, 2010. "Volatility Regimes in Central and Eastern European Countries’ Exchange Rates," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 60(1), pages 2-21, February.
    12. Mário Jorge Mendonça & Cláudio H. dos Santos, 2008. "Revisitando a Função de Reação Fiscal no Brasil Pós-Real: Uma Abordagem de Mudanças de Regime," Discussion Papers 1337, Instituto de Pesquisa Econômica Aplicada - IPEA.
    13. Ito, Hiro, 2003. "Was Japan’s Real Interest Rate Really Too High During the 1990s? The Role of the Zero Interest Rate Bound and Other Factors," Santa Cruz Department of Economics, Working Paper Series qt48k5q6vd, Department of Economics, UC Santa Cruz.
    14. Di Sanzo, Silvestro, 2018. "A Markov switching long memory model of crude oil price return volatility," Energy Economics, Elsevier, vol. 74(C), pages 351-359.
    15. Ito, Hiro, 2003. "Was Japan’s Real Interest Rate Really Too High During the 1990s? The Role of the Zero Interest Rate Bound and Other Factors," Santa Cruz Department of Economics, Working Paper Series qt48k5q6vd, Department of Economics, UC Santa Cruz.
    16. Benz, Eva & Trück, Stefan, 2009. "Modeling the price dynamics of CO2 emission allowances," Energy Economics, Elsevier, vol. 31(1), pages 4-15, January.
    17. Rong Liu & Lijian Yang, 2008. "Kernel estimation of multivariate cumulative distribution function," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(8), pages 661-677.
    18. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    19. Mariam Camarero & Juan Sapena & Cecilio Tamarit, 2020. "Modelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzle," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 87-114, June.
    20. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.

    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:cor:louvco:2004012. 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: Alain GILLIS (email available below). General contact details of provider: https://edirc.repec.org/data/coreebe.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.