Journal of Agricultural Economics & Development
Iranian Agricultural Economics Society (IAES)

Rural-Urban Disparities in Animal-Source Food Demand and Welfare Losses during COVID-19 in Iran: A QUAIDS Approach

Document Type : Research Article-en

Authors

A. Karbasi
S. Jalalian

Department of Agricultural Economics, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

https://doi.org/10.22067/jead.2025.88095.1267
Abstract
Abstract
The COVID-19 pandemic presented major global challenges, including a decline in per capita income growth across all income groups in 2020. The protein sector, particularly Animal-Source Foods (ASF) faced increased pressure on both supply and demand, resulting in price volatility. This study examines how income shocks affected food expenditure patterns and consumption behavior, with a focus on protein-rich ASF. Utilizing the QUAIDS model, budget data from Iranian households in rural and urban areas were analyzed for 2019 (pre-pandemic) and 2020 (during pandemic). The findings yield three key insights: (1) The average food expenditure share rose from 37% to 42%, with a sharper increase in rural areas; (2) Positive expenditure elasticities were observed across the six ASF groups including livestock meat, poultry, aquatic animal products, dairy, eggs, and fats, while own-price elasticities were relatively smaller; and (3) Welfare losses across ASF groups ranged from 2% to 24.2%, driven by policy imbalances, supply chain disruptions, and unequal utility distribution. Rural households experienced greater welfare losses in all ASF categories except fats. The study recommends targeted interventions: price-based support for urban areas and expanded social services for rural regions. To strengthen policy responses and enhance long-term food security, future research should assess the potential for substituting plant-based proteins as sustainable and cost-effective alternatives. These findings offer valuable guidance for policymakers aiming to improve nutritional resilience and economic stability in the post-pandemic era.

Keywords

: Animal-source food (ASF)
COVID-19
Iran
QUAIDS model
Welfare losses JEL Classifications: D12
Q11
Subjects

©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).

  1. Aday, S., & Aday, M.S. (2020). Impact of COVID-19 on the food supply chain. Food Quality and Safety, 4(4), 167–180. https://doi.org/10.1093/fqsafe/fyaa024
  2. Adekunle, C.P., Akinbode, S.O., Shittu, A.M., & Momoh, S. (2020). Food price changes and farm households’ welfare in Nigeria: direct and indirect approach. Journal of Applied Economics, 23(1), 409–425. https://doi.org/10.1080/15140326.2020.1743103
  3. Adelaja, A., George, J., Fox, L., Fuglie, K., & Jayne, T. (2021). Shocks, Resilience and Structural Transformation in Sub-Saharan Africa. Sustainability, 13(24), 13620. https://doi.org/10.3390/SU132413620
  4. Ahmed, M.Y., & Sarkodie, S.A. (2021). How COVID‐19 pandemic may hamper sustainable economic development. Journal of Public Affairs, 21(4). https://doi.org/10.1002/pa.2675
  5. Akaichi, F., & Revoredo-Giha, C. (2014). The demand for dairy products in Malawi. African Journal of Agricultural and Resource Economics, 9(3), 214–225. https://doi.org/10.22004/AG.ECON.183894
  6. Akter, S. (2020). The impact of COVID-19 related ‘stay-at-home’ restrictions on food prices in Europe: findings from a preliminary analysis. Food Security, 12(4), 719–725. https://doi.org/10.1007/S12571-020-01082-3/TABLES/3
  7. Alston, J.M., Norton, G.W., & Pardey, P.G. (1995). Science under scarcity : principles and practice for agricultural research evaluation and priority setting. 585.
  8. Anderson, J.D., Mitchell, J.L., & Maples, J.G. (2021). Invited Review: Lessons from the COVID-19 pandemic for food supply chains. Applied Animal Science, 37(6), 738–747. https://doi.org/10.15232/aas.2021-02223
  9. Angrist, N., Goldberg, P.K., & Jolliffe, D. (2021). Why is growth in developing countries so hard to measure? Journal of Economic Perspectives, 35(3), 215–242. https://doi.org/10.1257/JEP.35.3.215
  10. Araar, A., & Verme, P. (2016). Prices and Welfare. World Bank, Washington, DC. https://doi.org/10.1596/1813-9450-7566
  11. Badolo, F., & Traoré, F. (2015). Impact of rising world rice prices on poverty and inequality in Burkina Faso. Development Policy Review, 33(2), 221–244. https://doi.org/10.1111/dpr.12099
  12. Bai, Y., Costlow, L., Ebel, A., Laves, S., Ueda, Y., Volin, N., Zamek, M., & Masters, W.A. (2022). Retail prices of nutritious food rose more in countries with higher COVID-19 case counts. Nature Food, 3(5), 325–330. https://doi.org/10.1038/s43016-022-00502-1
  13. Banks, J., Blundell, R., & Lewbel, A. (1997). Quadratic engel curves and consumer demand on JSTOR. The Review of Economics and Statistics. https://www.jstor.org/stable/2951405
  14. Barrett, C.B., Benton, T.G., Cooper, K.A., Fanzo, J., Gandhi, R., Herrero, M., James, S., Kahn, M., Mason-D’Croz, D., Mathys, A., Nelson, R. J., Shen, J., Thornton, P., Bageant, E., Fan, S., Mude, A.G., Sibanda, L.M., & Wood, S. (2020). Bundling innovations to transform agri-food systems. Nature Sustainability, 3(12), 974–976. https://doi.org/10.1038/s41893-020-00661-8
  15. Barten, A.P. (1969). Maximum likelihood estimation of a complete system of demand equations. European Economic Review, 1(1), 7–73. https://doi.org/10.1016/0014-2921(69)90017-8
  16. Batlle-Bayer, L., Aldaco, R., Bala, A., Puig, R., Laso, J., Margallo, M., Vázquez-Rowe, I., Antó, J.M., & Fullana-i-Palmer, P. (2020). Environmental and nutritional impacts of dietary changes in Spain during the COVID-19 lockdown. Science of the Total Environment, 748, 141410. https://doi.org/10.1016/J.SCITOTENV.2020.141410
  17. Ceylan, R.F., Ozkan, B., & Mulazimogullari, E. (2020). Historical evidence for economic effects of COVID-19. The European Journal of Health Economics, 21(6), 817–823. https://doi.org/10.1007/s10198-020-01206-8
  18. Christensen, L.R., Jorgenson, D., & Lau, L.J. (1975). Transcendental logarithmic utility functions. American Economic Review, 65(3), 367–383. https://EconPapers.repec.org/RePEc:aea:aecrev:v:65:y:1975:i:3:p:367-83
  19. Christensen, L.R., Jorgenson, D.W., & Lau, L.J. (1973). Transcendental logarithmic production frontiers. The Review of Economics and Statistics, 55(1), 28. https://doi.org/10.2307/1927992
  20. Coelho, A.B., Aguiar, D.R.D. de, & Eales, J.S. (2010). Food demand in Brazil: an application of Shonkwiler & Yen Two-Step estimation method. Estudos Econômicos (São Paulo), 40(1), 186–211. https://doi.org/10.1590/S0101-41612010000100007
  21. Deaton, A., & Muellbauer, J. (1980). An almost ideal demand system. American Economic Review, 70, 312–376. https://www.scirp.org/reference/referencespapers?referenceid=2020105
  22. Engel, E. (1857). Die productions- und consumtionsverhältnisse des Königreichs Sachsen. Zeitschrift Des Statistischen Bureaus Des Königlich Sächsischen Ministerium Des Inneren, 8, 28–29. https://www.statsmodels.org/stable/datasets/generated/engel.html
  23. Fan, S., Teng, P., Chew, P., Smith, G., & Copeland, L. (2021). Food system resilience and COVID-19 – Lessons from the Asian experience. Global Food Security, 28, 100501. https://doi.org/10.1016/j.gfs.2021.100501
  24. (2020a). FIGURE 53. Average protein supply by region and origin. In FAO Statistical Yearbook 2020 Datasets. Food and Agriculture Organization of the United Nations. https://doi.org/10.4060/cb1329en-fig53
  25. (2020b). Global and regional food availability from 2000 to 2017-an analysis based on supply utilization accounts data. https://doi.org/10.4060/cb1120en
  26. Gao, G. (2012). World Food Demand. American Journal of Agricultural Economics, 94(1), 25–51. https://doi.org/10.1093/ajae/aar133
  27. Grinberga-Zalite, G., Pilvere, I., Muska, A., & Kruzmetra, Z. (2021). Resilience of Meat Supply Chains during and after COVID-19 Crisis. Emerging Science Journal, 5(1), 57–66. https://doi.org/10.28991/esj-2021-01257
  28. Hayakawa, K., & Mukunoki, H. (2021). The impact of COVID-19 on international trade: Evidence from the first shock. Journal of the Japanese and International Economies, 60, 101135. https://doi.org/10.1016/j.jjie.2021.101135
  29. Iddir, M., Brito, A., Dingeo, G., Fernandez Del Campo, S.S., Samouda, H., La Frano, M.R., & Bohn, T. (2020). Strengthening the immune system and reducing inflammation and oxidative stress through diet and nutrition: Considerations during the COVID-19 crisis. Nutrients, 12(6), 1562. https://doi.org/10.3390/nu12061562
  30. Kaicker, N., Gupta, A., & Gaiha, R. (2022). Covid-19 pandemic and food security in India: Can authorities alleviate the disproportionate burden on the disadvantaged? Journal of Policy Modeling, 44(5), 963–980. https://doi.org/10.1016/j.jpolmod.2022.08.001
  31. Khan, A.U., Ema, I.J., Afsana, A. S., Khan, A.U., Zannaty, A., & Faruk, Md.R. (2021). Effects of coronavirus disease (COVID-19) on agricultural sectors in Bangladesh: A Review. Nternational Journal for Asian Contemporary Research, 89–97.
  32. Khoiriyah, N., Anindita, R., Hanani, N., & Muhaimin, A.W. (2020). Animal food demand in Indonesia: A quadratic almost ideal demand system approach. Agris On-Line Papers in Economics and Informatics, 12(2), 85–97. https://doi.org/10.7160/aol.2020.120208
  33. Mokari-Yamchi, A., Omidvar, N., Tahamipour Zarandi, M., & Eini-Zinab, H. (2022). The effects of food taxes and subsidies on promoting healthier diets in Iranian households. Frontiers in Nutrition, 9. https://doi.org/10.3389/fnut.2022.917932
  34. Nicola, M., Alsafi, Z., Sohrabi, C., Kerwan, A., Al-Jabir, A., Iosifidis, C., Agha, M., & Agha, R. (2020). The socio-economic implications of the coronavirus pandemic (COVID-19): A review. International Journal of Surgery, 78, 185–193. https://doi.org/10.1016/j.ijsu.2020.04.018
  35. (2002). Three essays in applied econometrics - Brian P. Poi - Google Books. University of Michigan. https://books.google.fr/books?id=cfodAQAAMAAJ&redir_esc=y
  36. Poi, B.P. (2008). Demand-system estimation: Update. The Stata Journal: Promoting Communications on Statistics and Stata, 8(4), 554–556. https://doi.org/10.1177/1536867X0800800407
  37. Pollak, R.A., & Wales, T.J. (1978). Estimation of complete demand systems from household budget data: The linear and quadratic expenditure systems. The American Economic Review, 68(3), 348-359. http://www.jstor.org/stable/1805266
  38. Poudel, P.B., Poudel, M.R., Gautam, A., Phuyal, S., Tiwari, C.K., Bashyal, N., & Bashyal, S. (2020). COVID-19 and its Global Impact on Food and Agriculture. 生物学与当今世界杂志, 9(5). https://chinese.iomcworld.org/abstract/covid19-and-its-global-impact-on-food-and-agriculture-53429.html
  39. Ray, R. (1983). Measuring the costs of children. Journal of Public Economics, 22(1), 89–102. https://doi.org/10.1016/0047-2727(83)90058-0
  40. Rodríguez, L., Cervantes, E., & Ortiz, R. (2011). Malnutrition and gastrointestinal and respiratory infections in children: A public health problem. International Journal of Environmental Research and Public Health, 8(4), 1174–1205. https://doi.org/10.3390/ijerph8041174
  41. Salehzadeh, H., Soori, M.M., Sadeghi, S., Shahsawari, S., Mohammadi, S., Saifi, M., & Mozaffari, P. (2019). The type and amount of household oil consumption and the influential factors in Sanandaj city, Iran. Journal Advanced Environment Health Research, 7, 1–7. https://doi.org/10.22102/JAEHR.2019.125492.1070
  42. Stone, R. (1954). Linear expenditure systems and demand analysis: An application to the pattern of British demand. The Economic Journal, 64(255), 511. https://doi.org/10.2307/2227743
  43. Tian, X., Zhou, Y., & Wang, H. (2022). The impact of COVID-19 on food consumption and dietary quality of rural households in China. Foods, 11(4), 510. https://doi.org/10.3390/foods11040510
  44. Tonsor, G.T., Lusk, J.L., & Schroeder, T.C. (2023). Market potential of new plant‐based protein alternatives: Insights from four US consumer experiments. Applied Economic Perspectives and Policy, 45(1), 164–181. https://doi.org/10.1002/aepp.13253
  45. Vargas-Lopez, A., Cicatiello, C., Principato, L., & Secondi, L. (2022). Consumer expenditure, elasticity and value of food waste: A Quadratic Almost Ideal Demand System for evaluating changes in Mexico during COVID-19. Socio-Economic Planning Sciences, 82, 101065. https://doi.org/10.1016/j.seps.2021.101065
  46. (2014). Global Nutrition Targets 2025: Low birth weight policy brief. Geneva. World Health Organization.
  47. Willett, W., Rockström, J., Loken, B., Springmann, M., Lang, T., Vermeulen, S., Garnett, T., Tilman, D., DeClerck, F., Wood, A., Jonell, M., Clark, M., Gordon, L.J., Fanzo, J., Hawkes, C., Zurayk, R., Rivera, J.A., De Vries, W., Majele Sibanda, L., & Murray, C. J. L. (2019). Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems. The Lancet, 393(10170), 447–492. https://doi.org/10.1016/S0140-6736(18)31788-4
  48. World Development Indicators | DataBank. (n.d.). Retrieved May 30, 2025, from https://databank.worldbank.org/source/world-development-indicators
Send comment about this article
Enter Name.
Enter a valid email address.
Enter a vaid affiliation.
Enter comments (At leaset 10 words)
CAPTCHA Image
Enter Security Code Correctly.

  • Receive Date 27 May 2024
  • Revise Date 26 March 2025
  • Accept Date 22 April 2025
  • First Publish Date 22 April 2025

Home

Editorial Board

Publication Ethics

Contact Us