IDEAS home Printed from https://ideas.repec.org/a/ags/aolpei/146270.html
   My bibliography  Save this article

Determinants of Ruminant Meat Demand among Different Income Groups in Maiduguri, Borno State Nigeria

Author

Listed:
  • Yakaka, Bukar Maina
  • Iheanacho, A.C.
  • Babagana, K.

Abstract

This study analyzed the determinant of meat demand among income groups, using multiple regression. Data for the study were obtained from 180 respondents, selected in six (6) wards through stratified random sampling, representing the three income groups, namely low, middle and high earning ≤ N15000, N15, 001- N30, 000 and ≥ N30, 001 respectively. Further more, 30 households each were purposively selected from the six (6) areas making a total of 180 households for the study. This study was restricted to ruminant meat products (cattle, goat and sheep) demand among households in Maiduguri Urban area and covered the period of May-June, 2010. The findings showed that 89.02% of the households were male headed, with 38 years as the mean age, while 77% had one form of formal education or another. The mean household size was eight, while the mean monthly income was N23,843. The multiple regression results revelled that gender was insignificant determinant of expenditure on ruminant for all the income groups, and was negatively related to high income group. However, the coefficients of gender were positive for low and middle income groups. Household size and income had positive coefficients and were significant at 1% level for all the income groups. Age had positive coefficients for all the income groups and was significant at 1% for middle income group. On the contrary it was not significant for low and high income. Educational level of the respondents had positive coefficients for all income groups and was significant at 1% level for low and middle income groups but was insignificant for high income group. The study recommended policies to improve improved income redistribution and the enhancement of the purchasing power of the poor.

Suggested Citation

  • Yakaka, Bukar Maina & Iheanacho, A.C. & Babagana, K., 2012. "Determinants of Ruminant Meat Demand among Different Income Groups in Maiduguri, Borno State Nigeria," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 4(4), pages 1-8, December.
  • Handle: RePEc:ags:aolpei:146270
    DOI: 10.22004/ag.econ.146270
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/146270/files/agris_on-line_2012_4_yakaka_iheanacho_babagana.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.146270?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. Malaga, Jaime E. & Pan, Suwen & Duch-Carvallo, Teresa, 2009. "Did Mexican Meat Demand Change under NAFTA?," 2009 Conference, August 16-22, 2009, Beijing, China 51430, International Association of Agricultural Economists.
    2. J. A. Molina, 1994. "Food Demand In Spain: An Application Of The Almost Ideal System," Journal of Agricultural Economics, Wiley Blackwell, vol. 45(2), pages 252-258, May.
    3. James S. Eales & Laurian J. Unnevehr, 1988. "Demand for Beef and Chicken Products: Separability and Structural Change," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 70(3), pages 521-532.
    4. Awudu Abdulai & Devendra K. Jain & Ashok K. Sharma, 1999. "Household Food Demand Analysis in India," Journal of Agricultural Economics, Wiley Blackwell, vol. 50(2), pages 316-327, May.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Verbeke, Wim & Ward, Ronald W., 2001. "A fresh meat almost ideal demand system incorporating negative TV press and advertising impact," Agricultural Economics, Blackwell, vol. 25(2-3), pages 359-374, September.
    3. Osei-Asare, Yaw Bonsu & Eghan, Mark, 2013. "Food Price Inflation And Consumer Welfare In Ghana," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 1(01), pages 1-13, July.
    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. Justo Manrique & Helen H. Jensen, 2001. "Spanish Household Demand for Seafood," Journal of Agricultural Economics, Wiley Blackwell, vol. 52(3), pages 23-37, September.
    6. Unterschultz, James R., 2000. "New Instruments For Co-Ordination And Risk Sharing Within The Canadian Beef Industry," Project Report Series 24046, University of Alberta, Department of Resource Economics and Environmental Sociology.
    7. Abdoul G. Sam & Babatunde O. Abidoye & Sihle Mashaba, 2021. "Climate change and household welfare in sub-Saharan Africa: empirical evidence from Swaziland," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(2), pages 439-455, April.
    8. Goodwin, Barry K., 1992. "Forecasting Cattle Prices in the Presence of Structural Change," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 24(2), pages 11-22, December.
    9. Cupák, Andrej & Pokrivčák, Ján & Rizov, Marian, 2015. "Food Demand and Consumption Patterns in the New EU Member States: The Case of Slovakia," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 63(4), pages 339-358.
    10. Charlene Ignanga & Yu Chen & Yining Zhao & Heguang Liu & Wen Yu, 2025. "Cross-Sectional Analysis of Household Food Demand in Estuaire Gabon: A Near-Ideal Quadratic Demand System Approach," Agriculture, MDPI, vol. 15(3), pages 1-14, January.
    11. Angulo, Ana Maria & Mtimet, Nadhem & Gil, Jose Maria, 2008. "Análisis de la demanda de alimentos en España considerando el impacto de la dieta sobre la salud," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 8(02), pages 1-28.
    12. Ogura, Manami, 2011. "Testing for structural break in Japanese demand system after the bubble era," Structural Change and Economic Dynamics, Elsevier, vol. 22(3), pages 277-286, September.
    13. James L. Seale & Mary A. Marchant & Alberto Basso, 2003. "Imports versus Domestic Production: A Demand System Analysis of the U.S. Red Wine Market," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 25(1), pages 187-202.
    14. Echeverría, Lucía & Molina, José Alberto, 2021. "Poor vs Non-Poor Households in Uruguay: Welfare Differences from Food Price Changes," GLO Discussion Paper Series 890, Global Labor Organization (GLO).
    15. Andayani, Sri R.M. & Tilley, Daniel S., 1997. "Demand And Competition Among Supply Sources: The Indonesian Fruit Import Market," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 29(2), pages 1-11, December.
    16. Coulibaly, Jeanne Y. & Tebila, Nakelse & Diagne, Aliou, 2015. "Reducing Rice Imports in Côte d'Ivoire: Is a Rise in Import Tariff the Solution?," Agricultural and Resource Economics Review, Cambridge University Press, vol. 44(3), pages 195-213, December.
    17. Mittelhammer, Ronald C. & Shi, Hongqi & Wahl, Thomas I., 1996. "Accounting For Aggregation Bias In Almost Ideal Demand Systems," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 21(2), pages 1-16, December.
    18. McGuirk, Anya M. & Driscoll, Paul J. & Alwang, Jeffrey Roger & Huang, Huilin, 1995. "System Misspecification Testing And Structural Change In The Demand For Meats," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 20(01), pages 1-21, July.
    19. Peltner, Jonas & Thiele , Silke, 2021. "Elasticities of Food Demand in Germany – A Demand System Analysis Using Disaggregated Household Scanner Data," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 70(01), January.
    20. Shumway, C. Richard & Davis, George C., 2001. "Does consistent aggregation really matter?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 45(2), pages 1-34.

    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:ags:aolpei:146270. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/fevszcz.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.