IDEAS home Printed from https://ideas.repec.org/a/bla/agecon/v52y2021i2p343-361.html
   My bibliography  Save this article

Estimating demand elasticities for rice in Benin

Author

Listed:
  • Ogoudélé S. Codjo
  • Alvaro Durand‐Morat
  • Grant H. West
  • Lawton Lanier Nalley
  • Rodolfo M. Nayga
  • Eric J. Wailes

Abstract

Rice consumption in Benin is increasing simultaneously with a structural change in consumer demand toward higher quality rice. In this context of changing demands, experimental estimation methods provide an effective way to estimate consumer preferences. We conducted a hypothetical choice experiment in 15 open markets across Benin to analyze the demand for rice and the other staple crops. Our findings indicate that consumer preferences differ across different income groups and between urban and rural households, and that consumers in general are sensitive to changes in rice prices. Lastly, substitution between imported and domestic rice is limited. These findings are relevant for development strategies to foster the growth of the domestic rice industry in Benin.

Suggested Citation

  • Ogoudélé S. Codjo & Alvaro Durand‐Morat & Grant H. West & Lawton Lanier Nalley & Rodolfo M. Nayga & Eric J. Wailes, 2021. "Estimating demand elasticities for rice in Benin," Agricultural Economics, International Association of Agricultural Economists, vol. 52(2), pages 343-361, March.
    • Handle: RePEc:bla:agecon:v:52:y:2021:i:2:p:343-361
    DOI: 10.1111/agec.12622
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/agec.12622
    Download Restriction: no
    File URL: https://libkey.io/10.1111/agec.12622?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
    ---><---

    References listed on IDEAS

    as
    1. Fofana, Ismaël & Goundan, Anatole & Magne Domgho, Léa Vicky, 2014. "Impact simulation of ECOWAS rice self-sufficiency policy:," IFPRI discussion papers 1405, International Food Policy Research Institute (IFPRI).
    2. Bezemer, Dirk & Headey, Derek, 2008. "Agriculture, Development, and Urban Bias," World Development, Elsevier, vol. 36(8), pages 1342-1364, August.
    3. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    4. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    5. Kinkpe, Thierry A. & Adegbola, Patrice Y. & Yabi, Jacob A. & Adekambi, Souleiman & Biaou, Gauthier, 2016. "Analyse conjointe de la préférence des consommateurs pour les attributs de marche du riz au Benin," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 249297, African Association of Agricultural Economists (AAAE).
    6. Jonathan M. Nzuma & Rakhal Sarker, 2010. "An error corrected almost ideal demand system for major cereals in Kenya," Agricultural Economics, International Association of Agricultural Economists, vol. 41(1), pages 43-50, January.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    8. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    9. Laroche Dupraz, C. & Postolle, A., 2013. "Food sovereignty and agricultural trade policy commitments: How much leeway do West African nations have?," Food Policy, Elsevier, vol. 38(C), pages 115-125.
    10. Laurian Unnevehr & James Eales & Helen Jensen & Jayson Lusk & Jill McCluskey & Jean Kinsey, 2010. "Food and Consumer Economics," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(2), pages 506-521.
    11. Demont, Matty & Fiamohe, Rose & Kinkpé, A. Thierry, 2017. "Comparative Advantage in Demand and the Development of Rice Value Chains in West Africa," World Development, Elsevier, vol. 96(C), pages 578-590.
    12. Edith Lazaro & Abdoul G. Sam & Stanley R. Thompson, 2017. "Rice demand in Tanzania: an empirical analysis," Agricultural Economics, International Association of Agricultural Economists, vol. 48(2), pages 187-196, March.
    13. Seale, James L., Jr. & Regmi, Anita & Bernstein, Jason, 2003. "International Evidence On Food Consumption Patterns," Technical Bulletins 33580, United States Department of Agriculture, Economic Research Service.
    14. Per Pinstrup-Andersen & Elizabeth Caicedo, 1978. "The Potential Impact of Changes in Income Distribution on Food Demand and Human Nutrition," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 60(3), pages 402-415.
    15. Tonsor, Glynn T. & Mintert, James R. & Schroeder, Ted C., 2010. "U.S. Meat Demand: Household Dynamics and Media Information Impacts," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 35(1), pages 1-17.
    16. Emiliano Magrini & Jean Balié & Cristian Morales-Opazo, 2017. "Cereal price shocks and volatility in sub-Saharan Africa: what really matters for farmers’ welfare?," Agricultural Economics, International Association of Agricultural Economists, vol. 48(6), pages 719-729, November.
    17. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304.
    18. Jayson L. Lusk & Glynn T. Tonsor, 2016. "How Meat Demand Elasticities Vary with Price, Income, and Product Category," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 38(4), pages 673-711.
    19. Nicholas E. Piggott & Thomas L. Marsh, 2004. "Does Food Safety Information Impact U.S. Meat Demand?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(1), pages 154-174.
    20. Seale, James L., Jr. & Regmi, Anita & Bernstein, Jason, 2003. "International Evidence On Food Consumption Patterns," Technical Bulletins 33580, United States Department of Agriculture, Economic Research Service.
    21. Sarrias, Mauricio & Daziano, Ricardo, 2017. "Multinomial Logit Models with Continuous and Discrete Individual Heterogeneity in R: The gmnl Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i02).
    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. Espérance Zossou & Rose Fiamohe & Simple Davo Vodouhe & Matty Demont, 2022. "Experimental auctions with exogenous and endogenous information treatment: Willingness to pay for improved parboiled rice in Benin," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 806-825, September.

    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. Stefania Troiano & Daniel Vecchiato & Francesco Marangon & Tiziano Tempesta & Federico Nassivera, 2019. "Households’ Preferences for a New ‘Climate-Friendly’ Heating System: Does Contribution to Reducing Greenhouse Gases Matter?," Energies, MDPI, vol. 12(13), pages 1-19, July.
    2. Siikamaki, Juha & Layton, David F., 2007. "Discrete choice survey experiments: A comparison using flexible methods," Journal of Environmental Economics and Management, Elsevier, vol. 53(1), pages 122-139, January.
    3. Galassi, Veronica & Madlener, Reinhard, 2017. "The Role of Environmental Concern and Comfort Expectations in Energy Retrofit Decisions," Ecological Economics, Elsevier, vol. 141(C), pages 53-65.
    4. Carlsson, Fredrik & Grykblom, Peter & Lagerkvist, Carl Johan, 2007. "Farm Animal Welfare - Testing for Market Failure," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 39(1), pages 1-13, April.
    5. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    6. Søren Olsen, 2009. "Choosing Between Internet and Mail Survey Modes for Choice Experiment Surveys Considering Non-Market Goods," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 44(4), pages 591-610, December.
    7. Ajayi, V. & Reiner, D., 2020. "Consumer Willingness to Pay for Reducing the Environmental Footprint of Green Plastics," Cambridge Working Papers in Economics 20110, Faculty of Economics, University of Cambridge.
    8. Ortega, David L. & Wang, H. Holly & Wu, Laping & Hong, Soo Jeong, 2015. "Retail channel and consumer demand for food quality in China," China Economic Review, Elsevier, vol. 36(C), pages 359-366.
    9. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    10. Frick, Bernd & Barros, Carlos Pestana & Prinz, Joachim, 2010. "Analysing head coach dismissals in the German "Bundesliga" with a mixed logit approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 151-159, January.
    11. de Ayala, Amaia & Hoyos, David & Mariel, Petr, 2015. "Suitability of discrete choice experiments for landscape management under the European Landscape Convention," Journal of Forest Economics, Elsevier, vol. 21(2), pages 79-96.
    12. Basu, Debasis & Hunt, John Douglas, 2012. "Valuing of attributes influencing the attractiveness of suburban train service in Mumbai city: A stated preference approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1465-1476.
    13. Deka, Devajyoti & Carnegie, Jon, 2021. "Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey," Journal of Transport Geography, Elsevier, vol. 91(C).
    14. Shimokawa, S. & Niiyama, Y. & Kito, Y. & Kudo, H. & Yamaguchi, M., 2018. "No-tolerant Consumers, Information Treatments, and Demand for Stigmatized Foods: the Case of Fukushima Nuclear Power Plant Accident in Japan," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277198, International Association of Agricultural Economists.
    15. Christian A. Oberst & Reinhard Madlener, 2015. "Prosumer Preferences Regarding the Adoption of Micro†Generation Technologies: Empirical Evidence for German Homeowners," Working Papers 2015.07, International Network for Economic Research - INFER.
    16. Czajkowski, Mikołaj & Bartczak, Anna & Giergiczny, Marek & Navrud, Stale & Żylicz, Tomasz, 2014. "Providing preference-based support for forest ecosystem service management," Forest Policy and Economics, Elsevier, vol. 39(C), pages 1-12.
    17. Michael P. Keane & Nada Wasi, 2013. "The Structure of Consumer Taste Heterogeneity in Revealed vs. Stated Preference Data," Economics Papers 2013-W10, Economics Group, Nuffield College, University of Oxford.
    18. Gillespie Rob & Kragt Marit E., 2012. "Accounting for Nonmarket Impacts in a Benefit-Cost Analysis of Underground Coal Mining in New South Wales, Australia," Journal of Benefit-Cost Analysis, De Gruyter, vol. 3(2), pages 1-29, May.
    19. Tonsor, Glynn T. & Olynk, Nicole & Wolf, Christopher, 2009. "Consumer Preferences for Animal Welfare Attributes: The Case of Gestation Crates," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(3), pages 713-730, December.
    20. Giergiczny, Marek & Valasiuk, Sviataslau & Czajkowski, Mikolaj & De Salvo, Maria & Signorello, Giovanni, 2012. "Including cost income ratio into utility function as a way of dealing with ‘exploding’ implicit prices in mixed logit models," Journal of Forest Economics, Elsevier, vol. 18(4), pages 370-380.

    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:bla:agecon:v:52:y:2021:i:2:p:343-361. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/iaaeeea.html .

    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.