IDEAS home Printed from https://ideas.repec.org/a/taf/emetrv/v37y2018i5p534-550.html
   My bibliography  Save this article

Parameter estimation in multivariate logit models with many binary choices

Author

Listed:
  • Koen Bel
  • Dennis Fok
  • Richard Paap

Abstract

Multivariate Logit models are convenient to describe multivariate correlated binary choices as they provide closed-form likelihood functions. However, the computation time required for calculating choice probabilities increases exponentially with the number of choices, which makes maximum likelihood-based estimation infeasible when many choices are considered. To solve this, we propose three novel estimation methods: (i) stratified importance sampling, (ii) composite conditional likelihood (CCL), and (iii) generalized method of moments, which yield consistent estimates and still have similar small-sample bias to maximum likelihood. Our simulation study shows that computation times for CCL are much smaller and that its efficiency loss is small.

Suggested Citation

  • Koen Bel & Dennis Fok & Richard Paap, 2018. "Parameter estimation in multivariate logit models with many binary choices," Econometric Reviews, Taylor & Francis Journals, vol. 37(5), pages 534-550, May.
  • Handle: RePEc:taf:emetrv:v:37:y:2018:i:5:p:534-550
    DOI: 10.1080/07474938.2015.1093780
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07474938.2015.1093780
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/07474938.2015.1093780?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Paulo Guimarães & Octávio Figueirdo & Douglas Woodward, 2003. "A Tractable Approach to the Firm Location Decision Problem," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 201-204, February.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Lorenzo Cappellari & Stephen P. Jenkins, 2006. "Calculation of multivariate normal probabilities by simulation, with applications to maximum simulated likelihood estimation," Stata Journal, StataCorp LP, vol. 6(2), pages 156-189, June.
    4. Altonji, Joseph G & Segal, Lewis M, 1996. "Small-Sample Bias in GMM Estimation of Covariance Structures," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 353-366, July.
    5. D. R. Cox, 1972. "The Analysis of Multivariate Binary Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 21(2), pages 113-120, June.
    6. Bas Donkers & Peter Verhoef & Martijn Jong, 2007. "Modeling CLV: A test of competing models in the insurance industry," Quantitative Marketing and Economics (QME), Springer, vol. 5(2), pages 163-190, June.
    7. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, 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. Angelo Moretti, 2023. "Estimation of small area proportions under a bivariate logistic mixed model," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3663-3684, August.
    2. Qinan Lu & Xiaodong Du & Huanguang Qiu, 2022. "Adoption patterns and productivity impacts of agricultural mechanization services," Agricultural Economics, International Association of Agricultural Economists, vol. 53(5), pages 826-845, September.
    3. Richards, Timothy J. & Hamilton, Stephen F. & Yonezawa, Koichi, 2018. "Retail Market Power in a Shopping Basket Model of Supermarket Competition," Journal of Retailing, Elsevier, vol. 94(3), pages 328-342.
    4. Bel, K. & Paap, R., 2014. "A Multivariate Model for Multinomial Choices," Econometric Institute Research Papers EI 2014-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Ma, Wanglin & Zheng, Hongyun & Gong, Binlei, 2022. "Rural income growth, ethnic differences, and household cooking fuel choice: Evidence from China," Energy Economics, Elsevier, vol. 107(C).
    6. Harald Hruschka, 2022. "Analyzing joint brand purchases by conditional restricted Boltzmann machines," Review of Managerial Science, Springer, vol. 16(4), pages 1117-1145, May.
    7. Lu, Qinan & Du, Xiaodong, 2020. "The Outsourcing Choice of Agricultural Production Tasks: Implications for Food Security - A Multiple-task Based Approach," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304333, Agricultural and Applied Economics Association.
    8. Fok, D. & Paap, R., 2019. "New Misspecification Tests for Multinomial Logit Models," Econometric Institute Research Papers EI2019-24, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Valerie Kilders & Vincenzina Caputo & Jayson L. Lusk, 2024. "Consumer preferences for food away from home: Dine in versus delivery," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(2), pages 496-525, March.
    10. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    11. Sierminska, Eva & Oaxaca, Ronald L., 2022. "Gender differences in economics PhD field specializations with correlated choices," Labour Economics, Elsevier, vol. 79(C).
    12. Steffen Jahn & Daniel Guhl & Ainslee Erhard, 2024. "Substitution Patterns and Price Response for Plant-Based Meat Alternatives," Rationality and Competition Discussion Paper Series 509, CRC TRR 190 Rationality and Competition.
    13. Huong Hoang-Thi & Shah Fahad & Ashfaq Ahmad Shah & Tung Nguyen-Huu-Minh & Tuan Nguyen-Anh & Song Nguyen-Van & Nguyen To-The & Huong Nguyen-Thi-Lan, 2023. "Evaluating the farmers’ adoption behavior of water conservation in mountainous region Vietnam: extrinsic and intrinsic determinants," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(2), pages 1313-1330, January.
    14. Filippopoulou, Chryssanthi & Galariotis, Emilios & Spyrou, Spyros, 2020. "An early warning system for predicting systemic banking crises in the Eurozone: A logit regression approach," Journal of Economic Behavior & Organization, Elsevier, vol. 172(C), pages 344-363.
    15. repec:ags:aaea22:335456 is not listed on IDEAS
    16. Caputo, Vincenzina & Lusk, Jayson L., 2022. "The Basket-Based Choice Experiment: A Method for Food Demand Policy Analysis," Food Policy, Elsevier, vol. 109(C).

    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. Aedín Doris & Donal O’Neill & Olive Sweetman, 2013. "Identification of the covariance structure of earnings using the GMM estimator," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 11(3), pages 343-372, September.
    2. Isacsson, Gunnar, 2007. "The trade off between time and money: Is there a difference between real and hypothetical choices?," Working Papers 2007:3, Swedish National Road & Transport Research Institute (VTI).
    3. Christopher R. Knittel & Konstantinos Metaxoglou, 2008. "Estimation of Random Coefficient Demand Models: Challenges, Difficulties and Warnings," NBER Working Papers 14080, National Bureau of Economic Research, Inc.
    4. Joachim Inkmann, 2000. "Finite Sample Properties of One-Step, Two-Step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation," Econometric Society World Congress 2000 Contributed Papers 0332, Econometric Society.
    5. Shane M. Sherlund, 2004. "Quasi Empirical Likelihood Estimation of Moment Condition Models," Econometric Society 2004 North American Summer Meetings 507, Econometric Society.
    6. Bo Honoré & Thomas Jørgensen & Áureo de Paula, 2020. "The informativeness of estimation moments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 797-813, November.
    7. John Geweke & Joel Horowitz & M. Hashem Pesaran, 2006. "Econometrics: A Bird’s Eye View," CESifo Working Paper Series 1870, CESifo.
    8. Zila, Eric & Kukacka, Jiri, 2023. "Moment set selection for the SMM using simple machine learning," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 366-391.
    9. Lô, Serigne N. & Ronchetti, Elvezio, 2012. "Robust small sample accurate inference in moment condition models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3182-3197.
    10. Jeffrey M. Wooldridge, 2004. "Estimating average partial effects under conditional moment independence assumptions," CeMMAP working papers CWP03/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Guido W. Imbens & Richard H. Spady & Phillip Johnson, 1998. "Information Theoretic Approaches to Inference in Moment Condition Models," Econometrica, Econometric Society, vol. 66(2), pages 333-358, March.
    12. Antoine, Bertille & Bonnal, Helene & Renault, Eric, 2007. "On the efficient use of the informational content of estimating equations: Implied probabilities and Euclidean empirical likelihood," Journal of Econometrics, Elsevier, vol. 138(2), pages 461-487, June.
    13. Jason R. Blevins & Garrett T. Senney, 2019. "Dynamic selection and distributional bounds on search costs in dynamic unit‐demand models," Quantitative Economics, Econometric Society, vol. 10(3), pages 891-929, July.
    14. Francesco Bartolucci & Claudia Pigini, 2018. "Partial effects estimation for fixed-effects logit panel data models," Working Papers 431, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    15. Gagliardini, Patrick & Trojani, Fabio & Urga, Giovanni, 2005. "Robust GMM tests for structural breaks," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 139-182.
    16. La Vecchia, Davide & Moor, Alban & Scaillet, Olivier, 2023. "A higher-order correct fast moving-average bootstrap for dependent data," Journal of Econometrics, Elsevier, vol. 235(1), pages 65-81.
    17. Hlouskova, Jaroslava & Sögner, Leopold, 2020. "GMM estimation of affine term structure models," Econometrics and Statistics, Elsevier, vol. 13(C), pages 2-15.
    18. Francesco Bartolucci & Claudia Pigini, 2017. "Granger causality in dynamic binary short panel data models," Working Papers 421, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    19. Jan F. Kiviet & Qu Feng, 2014. "Efficiency Gains by Modifying GMM Estimation in Linear Models under Heteroskedasticity," UvA-Econometrics Working Papers 14-06, Universiteit van Amsterdam, Dept. of Econometrics.
    20. Roberto González & Hector Sala, 2015. "The Frisch Elasticity in the Mercosur Countries: A Pseudo-Panel Approach," Development Policy Review, Overseas Development Institute, vol. 33(1), pages 107-131, January.

    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:taf:emetrv:v:37:y:2018:i:5:p:534-550. 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: the person in charge (email available below). General contact details of provider: http://www.tandfonline.com/LECR20 .

    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.