IDEAS home Printed from https://ideas.repec.org/a/ibn/jasjnl/v15y2024i7p18.html
   My bibliography  Save this article

Effects of COVID-19 on Food Demand in Rural Indonesia: The Case of Bengkulu Province

Author

Listed:
  • Melli Suryanty SN
  • Toshinobu Matsuda

Abstract

This paper examines food demand before and after the outbreak of COVID-19 and studies the effects of the situation on households’ demand for food in rural Indonesia, in the case of Bengkulu Province. The research data is taken from the Indonesia Socio-Economic Survey (SUSENAS) as a microdata set which is collected annually by Indonesia Central Statistics Agency (BPS) from 2017 to 2021. The effect of COVID-19 on food demand estimates using the Quadratic Almost Ideal Demand System (QUAIDS). The results demonstrate that prepared food expenditure is the largest portion of household expenditure on food in the Bengkulu rural area. Before the outbreak of COVID-19, animal source food is the most sensitive to food expenditure, but after the outbreak, prepared food is the most sensitive. Staple food is the most expenditure-inelastic before and after the outbreak. Expenditure for animal source food, vegetables & fruits, and prepared food have significant differences between before and after the outbreak. All the food groups substitute for each other before the outbreak, whereas staple food and prepared food cannot be regarded as a substitute for each other after the outbreak. There are eleven of the compensated price elasticities whose differences between before and after the outbreak are significant, whereas as a set the compensated price elasticities are significantly different between before and after the outbreak. Other food is the easiest to be substituted for both phases. Prepared food is the most difficult to be substituted before the outbreak, but the staple food is the most difficult to be substituted after the outbreak. After the outbreak of COVID-19, the demand for vegetables & fruits increases, but the demand for staple food and prepared food decreases, ceteris paribus. Family size, children, gender, age, and other demographics variables have an impact on household food demand. These findings imply that after the outbreak, the supply of vegetables & fruits should be increased and that government support for suppliers of staple food and prepared food will be preferable.

Suggested Citation

  • Melli Suryanty SN & Toshinobu Matsuda, 2024. "Effects of COVID-19 on Food Demand in Rural Indonesia: The Case of Bengkulu Province," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 15(7), pages 1-18, April.
    • Handle: RePEc:ibn:jasjnl:v:15:y:2024:i:7:p:18
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/jas/article/download/0/0/48892/52694
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/jas/article/view/0/48892
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Giancarlo Moschini & Karl D. Meilke, 1989. "Modeling the Pattern of Structural Change in U.S. Meat Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 253-261.
    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. Islam Hassouneh & Teresa Serra & José M. Gil, 2010. "Price transmission in the Spanish bovine sector: the BSE effect," Agricultural Economics, International Association of Agricultural Economists, vol. 41(1), pages 33-42, January.
    2. Darko, Francis Addeah & Eales, James S., 2013. "Meat Demand in the US During and After the Great Recession," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150146, Agricultural and Applied Economics Association.
    3. Moschini, G. & Moro, D., 1993. "A Food demand System for Canada," Papers 1-93, Gouvernement du Canada - Agriculture Canada.
    4. Rulon D. Pope & Jeffrey T. LaFrance & Timothy K. M.Beatty, 2004. "Building Gorman's Nest," Econometric Society 2004 Australasian Meetings 26, Econometric Society.
    5. Schroeder, Ted C. & Lusk, Jayson L., 2002. "Effects of Meat Recalls on Futures Market Prices," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 31(01), pages 1-12, April.
    6. Moschini, GianCarlo & Vissa, Anuradha, 1992. "A Linear Inverse Demand System," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 17(2), pages 1-9, December.
    7. Piggott, Nicholas E. & Marsh, Thomas L., 2001. "Impacts of Food Safety on U.S. Meat Demand," 2001 Conference (45th), January 23-25, 2001, Adelaide, Australia 125781, Australian Agricultural and Resource Economics Society.
    8. Harri, Ardian & Brorsen, B. Wade & Muhammad, Andrew & Anderson, John D., 2010. "Estimating a Demand System with Seasonally Differenced Data," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 42(2), pages 321-335, May.
    9. Gale, Fred & Dong, Fengxia, 2023. "China’s Meat Consumption: Growth Potential," Economic Research Report 338955, United States Department of Agriculture, Economic Research Service.
    10. Paul Cashin, 1991. "A Model Of The Disaggregated Demand For Meat In Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 35(3), pages 263-283, December.
    11. Vardges Hovhannisyan & Brian W. Gould, 2014. "Structural change in urban Chinese food preferences," Agricultural Economics, International Association of Agricultural Economists, vol. 45(2), pages 159-166, March.
    12. Goodwin, Barry K. & Harper, Daniel C. & Schnepf, Randall D., 2003. "Short-Run Demand Relationships in the U.S. Fats and Oils Complex," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 35(01), pages 1-14, April.
    13. Poray, Michael C. & Foster, Kenneth A. & Dorfman, Jeffrey H., 2000. "Measuring An Almost Ideal Demand System With Generalized Flexible Least Squares," 2000 Annual meeting, July 30-August 2, Tampa, FL 21796, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    14. Wen S. Chern & Kimiko Ishibashi & Kiyoshi Taniguchi & Yuki Tokoyama, 2002. "Analysis of Food Consumption Behavior by Japanese Households," Working Papers 02-06, Agricultural and Development Economics Division of the Food and Agriculture Organization of the United Nations (FAO - ESA).
    15. Molina Chueca, José Alberto, 1997. "Estimación de la estructura Intertemporal de la demanda de alimentos en España," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 7, pages 67-77, Junio.
    16. Nelson, Mack C. & Liu, Xuanli, 2005. "Demand Potential for Goat Meat in Southern States: Empirical Evidence from a Multi-State Goat Meat Consumer Survey," 2005 Annual meeting, July 24-27, Providence, RI 19224, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    17. Burton, Michael & Young, Trevor & Cromb, Roy, 1999. "Meat consumers’ long-term response to perceived risks associated with BSE in Great Britain," Cahiers d'Economie et de Sociologie Rurales (CESR), Institut National de la Recherche Agronomique (INRA), vol. 50.
    18. Parcell, Joe & Mintert, James & Plain, Ron, 2004. "An Empirical Investigation of Live-Hog Demand," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 36(3), pages 773-787, December.
    19. Abderraouf Laajimi & Boubaker Dhehibi & José Maria Gil, 2003. "The structure of food demand in Tunisai: a differential system approach," Cahiers d'Economie et Sociologie Rurales, INRA Department of Economics, vol. 66, pages 55-77.
    20. Jeon, Younghyeon & Hoang, Hoa K. & Thompson, Wyatt & Abler, David & Miller, J. Isaac, 2022. "Revealing the fundamental parameters of a food demand system using estimated elasticities," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322182, Agricultural and Applied Economics Association.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:ibn:jasjnl:v:15:y:2024:i:7:p:18. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.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.