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Marginal and Interaction Effects in Ordered Response Models

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  • Debdulal Mallick

Abstract

In discrete choice models the marginal effect of a variable of interest that is interacted with another variable differs from the marginal effect of a variable that is not interacted with any variable. The magnitude of the interaction effect is also not equal to the marginal effect of the interaction term. I present consistent estimators of both marginal and interaction effects in ordered response models. This procedure is general and can easily be extended to other discrete choice models. I also provide an example using household survey data on food security in Bangladesh. Results show that marginal effects of interaction terms are estimated by standard statistical software (STATA® 10) with very large error and even with wrong sign.

Suggested Citation

  • Debdulal Mallick, 2009. "Marginal and Interaction Effects in Ordered Response Models," EERI Research Paper Series EERI_RP_2009_22, Economics and Econometrics Research Institute (EERI), Brussels.
    • Handle: RePEc:eei:rpaper:eeri_rp_2009_22
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    References listed on IDEAS

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    1. Spanos,Aris, 1999. "Probability Theory and Statistical Inference," Cambridge Books, Cambridge University Press, number 9780521424080.
    2. Stefan Boes & Rainer Winkelmann, 2006. "Ordered Response Models," Springer Books, in: Olaf Hübler & Jachim Frohn (ed.), Modern Econometric Analysis, chapter 12, pages 167-181, Springer.
    3. Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
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    Cited by:

    1. Ricardo Lima & Aizhi Yu & Qinghua Liu & Jingyi Liu, 2024. "Examining the determinants of food waste behavior in China at the consumer level," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 16(4), pages 867-881, August.
    2. Lan, Jing & Munro, Alistair, 2013. "Environmental compliance and human capital: Evidence from Chinese industrial firms," Resource and Energy Economics, Elsevier, vol. 35(4), pages 534-557.
    3. Jikhan Jeong, 2020. "Identifying Consumer Preferences from User- and Crowd-Generated Digital Footprints on Amazon.com by Leveraging Machine Learning and Natural Language Processing," 2020 Papers pje208, Job Market Papers.
    4. Barrett, Alan & Mosca, Irene, 2012. "Announcing an Increase in the State Pension Age and the Recession: Which Mattered More for Expected Retirement Ages?," IZA Discussion Papers 6325, Institute of Labor Economics (IZA).
    5. Lars Thiel, 2014. "Illness and Health Satisfaction: The Role of Relative Comparisons," SOEPpapers on Multidisciplinary Panel Data Research 695, DIW Berlin, The German Socio-Economic Panel (SOEP).
    6. Alam Asadov, 2024. "Empirical Analysis of Demand for Sukuk in Uzbekistan," Economies, MDPI, vol. 12(8), pages 1-26, August.

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    More about this item

    Keywords

    Marginal effect; interaction effect; ordered probit; discrete choice.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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