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Calculating marginal effects in dichotomous - continuous models

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  • Atanu Saha
  • Oral Capps
  • Patrick Byrne

Abstract

In many economic settings, individual decisions can be viewed as a sequential process where a dichotomous choice is followed by a continuous choice. These processes are frequently encountered in consumption demand studies, where the decision of whether or not to consume a particular commodity is followed by the choice of how much to consume. The Heckman two-step approach has been extensively used in estimating these models. Expressions are derived for calculating marginal effects of regressors in dichotomous-continuous models. It is proposed that the marginal effect expressions are incomplete in almost all consumption demand studies that use the Heckman approach. In dichotomous-continuous models, a change in an explanatory variable that is common to both stages of the decision process has two effects: (1) it affects the likelihood of whether the commodity will be consumed; and (2) if the commodity is consumed, it affects the expenditure on that commodity. The first effect has so far been omitted from applied demand studies. The correct marginal effect expressions are derived for single-commodity and multiple-commodity demand models. An application to consumption survey data on 12 food commodities shows that erroneous marginal effect expressions can introduce substantial bias in demand elasticity estimates.

Suggested Citation

  • Atanu Saha & Oral Capps & Patrick Byrne, 1997. "Calculating marginal effects in dichotomous - continuous models," Applied Economics Letters, Taylor & Francis Journals, vol. 4(3), pages 181-185.
    • Handle: RePEc:taf:apeclt:v:4:y:1997:i:3:p:181-185
    DOI: 10.1080/135048597355474
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    Cited by:

    1. Ole Boysen, 2016. "Food Demand Characteristics in Uganda: Estimation and Policy Relevance," South African Journal of Economics, Economic Society of South Africa, vol. 84(2), pages 260-293, June.
    2. Byrne, Patrick J. & Capps, Oral, Jr. & Saha, Atanu, 1998. "Analysis Of Quick-Serve, Mid-Scale, And Up-Scale Food Away From Home Expenditures," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 1(1), pages 1-22.
    3. GwanSeon Kim & Tyler Mark, 2023. "What factors make consumers in the USA buy hemp products? Evidence from Nielsen consumer panel data," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 11(1), pages 1-19, December.
    4. Haripriya Gundimeda & Atheendar Gunnar Köhlin, 2006. "Fuel Demand Elasticities for Energy and Environmental Policies: Indian Sample Survey Evidence," Working Papers 2006-09, Madras School of Economics,Chennai,India.
    5. Fade-Aluko, Titilope O. & Sanusi, Rahman A. & Afolami, Carolyn A. & Phillip, Biola B., 2016. "Analysis of Urban Households' Demand for Sweeteners in Ogun State, Nigeria," Nigerian Journal of Agricultural Economics, Nigerian Journal of Agricultural Economics, vol. 6(1), October.
    6. Oral Capps & Muxi Cheng & Jennifer Kee & Samuel L. Priestley, 2023. "A cross‐sectional analysis of the demand for coffee in the United States," Agribusiness, John Wiley & Sons, Ltd., vol. 39(2), pages 494-514, March.
    7. Zhuo Chen & Steven Yen, 2005. "On bias correction in the multivariate sample-selection model," Applied Economics, Taylor & Francis Journals, vol. 37(21), pages 2459-2468.
    8. Roehlano M. Briones, 2009. "Do Small Farmers Borrow Less When the Lending Rate Increases? Interest Rate Elasticity of Rice Farmers in the Philippines," Asian Economic Journal, East Asian Economic Association, vol. 23(4), pages 439-455, December.
    9. Juan Carlos Caro & Shu Wen Ng & Ricardo Bonilla & Jorge Tovar & Barry M Popkin, 2017. "Sugary drinks taxation, projected consumption and fiscal revenues in Colombia: Evidence from a QUAIDS model," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-16, December.
    10. Haripriya Gundimeda & Gunnar Köhlin, 2006. "Fuel Demand Elasticities for Energy and Environmental Policies Indian Sample Survey Evidence," Energy Working Papers 22501, East Asian Bureau of Economic Research.
    11. Akay, Alpaslan & Tsakas, Elias, 2006. "Second Order Approximation for the Average Marginal Effect of Heckman's Two Step Procedure," Working Papers in Economics 239, University of Gothenburg, Department of Economics.
    12. Kim, GwanSeon & Mark, Tyler, 2018. "Who are Consuming Hemp Products in the U.S.? Evidence from Nielsen Homescan Data," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266671, Southern Agricultural Economics Association.
    13. Pedro A. Alviola & Oral Capps, 2010. "Household demand analysis of organic and conventional fluid milk in the United States based on the 2004 Nielsen Homescan panel," Agribusiness, John Wiley & Sons, Ltd., vol. 26(3), pages 369-388.
    14. Alpaslan Akay & Elias Tsakas, 2008. "Asymptotic bias reduction for a conditional marginal effects estimator in sample selection models," Applied Economics, Taylor & Francis Journals, vol. 40(24), pages 3101-3110.
    15. Panagiotis Lazaridis, 2004. "Demand elasticities derived from consistent estimation of Heckman-type models," Applied Economics Letters, Taylor & Francis Journals, vol. 11(8), pages 523-527.
    16. Vega, Jose De Jesus Garcia & Gracia, Marcial Canales, 2000. "The Role Of Economic And Demograhpic Variables In Mexican Food Consumption," Journal of Food Distribution Research, Food Distribution Research Society, vol. 31(1), pages 1-8, March.
    17. Chern, Wen S. & Ishibashi, Kimiko & Taniguchi, Kiyoshi & Tokoyama, Yuki, 2002. "Analysis of food consumption behavior by Japanese households," ESA Working Papers 289108, Food and Agriculture Organization of the United Nations, Agricultural Development Economics Division (ESA).

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