IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v95y2000i1p117-129.html
   My bibliography  Save this article

A numerically stable quadrature procedure for the one-factor random-component discrete choice model

Author

Listed:
  • Lee, Lung-fei

Abstract

No abstract is available for this item.

Suggested Citation

  • Lee, Lung-fei, 2000. "A numerically stable quadrature procedure for the one-factor random-component discrete choice model," Journal of Econometrics, Elsevier, vol. 95(1), pages 117-129, March.
  • Handle: RePEc:eee:econom:v:95:y:2000:i:1:p:117-129
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4076(99)00032-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. Borjas, George J. & Sueyoshi, Glenn T., 1994. "A two-stage estimator for probit models with structural group effects," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 165-182.
    2. Butler, J S & Moffitt, Robert, 1982. "A Computationally Efficient Quadrature Procedure for the One-Factor Multinomial Probit Model," Econometrica, Econometric Society, vol. 50(3), pages 761-764, May.
    3. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 225-238.
    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. Heiss, Florian & Winschel, Viktor, 2008. "Likelihood approximation by numerical integration on sparse grids," Journal of Econometrics, Elsevier, vol. 144(1), pages 62-80, May.
    2. Raymond, Wladimir & Mairesse, Jacques & Mohnen, Pierre & Palm, Franz, 2015. "Dynamic models of R & D, innovation and productivity: Panel data evidence for Dutch and French manufacturing," European Economic Review, Elsevier, vol. 78(C), pages 285-306.
    3. Michael Lechner & Stefan Lollivier & Thierry Magnac, 2005. "Parametric Binary Choice Models," University of St. Gallen Department of Economics working paper series 2005 2005-23, Department of Economics, University of St. Gallen.
    4. Mauricio Sarrias, 2020. "Random Parameters and Spatial Heterogeneity using Rchoice in R," REGION, European Regional Science Association, vol. 7, pages 1-19.
    5. T.-F. Lo & P.-H. Ke & W.-J. Tsay, 2018. "Pairwise likelihood inference for the random effects probit model," Computational Statistics, Springer, vol. 33(2), pages 837-861, June.
    6. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
    7. Partha Deb & Furio Rosati, 2002. "Determinants of Child Labor and School Attendance: The Role of Household Unobservables," Economics Working Paper Archive at Hunter College 02/9, Hunter College Department of Economics.
    8. Partha Deb, 2001. "A discrete random effects probit model with application to the demand for preventive care," Health Economics, John Wiley & Sons, Ltd., vol. 10(5), pages 371-383, July.
    9. Partha Deb & Furio Rosati, 2002. "Determinants of Child Labor and School Attendance: The Role of Household Unobservables," Economics Working Paper Archive at Hunter College 02/9, Hunter College Department of Economics.

    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. Hanemann, W. Michael & Kanninen, Barbara, 1996. "The Statistical Analysis Of Discrete-Response Cv Data," CUDARE Working Papers 25022, University of California, Berkeley, Department of Agricultural and Resource Economics.
    2. Laisney, François & Pohlmeier, Winfried & Staat, Matthias, 1991. "Estimation of labour supply functions using panel data: a survey," ZEW Discussion Papers 91-05, ZEW - Leibniz Centre for European Economic Research.
    3. Das, Marcel & van Soest, Arthur, 1999. "A panel data model for subjective information on household income growth," Journal of Economic Behavior & Organization, Elsevier, vol. 40(4), pages 409-426, December.
    4. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    5. Schupp, Fabian & Silbermann, Leonid, 2017. "The Role of Structural Funding for Stability in the German Banking Sector," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168166, Verein für Socialpolitik / German Economic Association.
    6. Jörg Breitung & Michael Lechner, 1996. "Estimation de modèles non linéaires sur données de panel par la méthode des moments généralisés," Économie et Prévision, Programme National Persée, vol. 126(5), pages 191-203.
    7. Hernández-Quevedo, Cristina & Jones, Andrew M. & Rice, Nigel, 2008. "Persistence in health limitations: A European comparative analysis," Journal of Health Economics, Elsevier, vol. 27(6), pages 1472-1488, December.
    8. Aitken, Brian & Hanson, Gordon H. & Harrison, Ann E., 1997. "Spillovers, foreign investment, and export behavior," Journal of International Economics, Elsevier, vol. 43(1-2), pages 103-132, August.
    9. Santiago Pereda-Fernández, 2021. "Copula-Based Random Effects Models for Clustered Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 575-588, March.
    10. Ribar, David C., 2004. "What Do Social Scientists Know About the Benefits of Marriage? A Review of Quantitative Methodologies," IZA Discussion Papers 998, Institute of Labor Economics (IZA).
    11. Laetitia Duval & Francois-Charles Wolff, 2010. "Remittances matter: longitudinal evidence from Albania," Post-Communist Economies, Taylor & Francis Journals, vol. 22(1), pages 73-97.
    12. Breitung, Jörg & Lechner, Michael, 1998. "Alternative GMM methods for nonlinear panel data models," SFB 373 Discussion Papers 1998,81, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    13. Saïd Hanchane & Isabelle Recotillet, 2004. "On gender-specific socio-demographic determinants of the transition from school to work : a longitudinal analysis based on French data," Working Papers halshs-00010141, HAL.
    14. Natalia Isachenkova & John Hunter, 2002. "A Panel Analysis Of UK Industrial Company Failure," Working Papers wp228, Centre for Business Research, University of Cambridge.
    15. Lee, Lung-Fei, 1997. "Simulated maximum likelihood estimation of dynamic discrete choice statistical models some Monte Carlo results," Journal of Econometrics, Elsevier, vol. 82(1), pages 1-35.
    16. Alwyn Young, 2012. "The African Growth Miracle," NBER Working Papers 18490, National Bureau of Economic Research, Inc.
    17. Lucchetti, Riccardo & Pigini, Claudia, 2017. "DPB: Dynamic Panel Binary Data Models in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i08).
    18. Heineck, Guido, 2004. "Does religion influence the labor supply of married women in Germany?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 33(3), pages 307-328, July.
    19. Geoghegan, Jacqueline & Hewitt, Julie A. & Vance, Colin, 2003. "Time Series Analysis Of Satellite Data: Deforestation In Southern Mexico," 2003 Annual meeting, July 27-30, Montreal, Canada 22123, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    20. Andreea Mitrut & François-Charles Wolff, 2014. "Investing in children’s education: are Muslim immigrants different?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 27(4), pages 999-1022, October.

    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:eee:econom:v:95:y:2000:i:1:p:117-129. 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/jeconom .

    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.