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Estimation with the nested logit model: Specifications and software particularities

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  • Silberhorn, Nadja
  • Boztuğ, Yasemin
  • Hildebrandt, Lutz

Abstract

Due to its ability to allow and account for similarities between pairs of alternatives, the nested logit model is increasingly used in practical applications. However the fact that there are two different specifications of the nested logit model has not received adequate attention. The utility maximization nested logit (UMNL) model and the non-normalized nested logit (NNNL) model have different properties, influencing the estimation results in a different manner. As the NNNL specification is not consistent with random utility theory (RUT), the UMNL form is preferred. This article introduces distinct specifications of the nested logit model and indicates particularities arising from model estimation. Additionally, it demonstrates the performance of simulation studies with the nested logit model. In simulation studies with the nested logit model using NNNL software (e. g. PROC MDC in SAS), it must be pointed out that the simulation of the utility function's error terms needs to assume RUT-conformity. But as the NNNL specification is not consistent with RUT, the input parameters cannot be reproduced without imposing restrictions. The effects of using various software packages on the estimation results of a nested logit model are shown on the basis of a simulation study.

Suggested Citation

  • Silberhorn, Nadja & Boztuğ, Yasemin & Hildebrandt, Lutz, 2006. "Estimation with the nested logit model: Specifications and software particularities," SFB 649 Discussion Papers 2006-017, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  • Handle: RePEc:zbw:sfb649:sfb649dp2006-017
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    Cited by:

    1. Nga Ndjobo, Patrick Marie & Abessolo, Yves André, 2013. "The Impact of Education on the Behaviour of Labor Supply in Cameroon: an Analysis using the Nested Multinomial Logit Model," MPRA Paper 51158, University Library of Munich, Germany.
    2. Peter Berck & Sofia Tano & Olle Westerlund, 2016. "Regional Sorting of Human Capital: The Choice of Location among Young Adults in Sweden," Regional Studies, Taylor & Francis Journals, vol. 50(5), pages 757-770, May.
    3. Paat Rusmevichientong & Zuo-Jun Max Shen & David B. Shmoys, 2010. "Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint," Operations Research, INFORMS, vol. 58(6), pages 1666-1680, December.
    4. Nalin Kumar Ramaul & Pinki Ramaul, 2018. "Regional Incentives and Location Choice of New Firms in India: A Nested Logit Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 501-525, June.
    5. Hackbarth, André & Madlener, Reinhard, 2018. "Combined Vehicle Type and Fuel Type Choices of Private Households: An Empirical Analysis for Germany," FCN Working Papers 17/2018, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised May 2019.
    6. Philip H. Brown & Caroline Theoharides, 2009. "Health‐seeking behavior and hospital choice in China's New Cooperative Medical System," Health Economics, John Wiley & Sons, Ltd., vol. 18(S2), pages 47-64, July.

    More about this item

    Keywords

    nested logit model; utility maximization nested logit; non-normalized nested logit; simulation study;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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