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Factors affecting beef demand in Türkiye for 2010-2021 and the effects of restrictions imposed during the Coronavirus disease (COVID-19) period

Year 2025, Volume: 10 Issue: 1, 52 - 59, 30.04.2025

Seyfettin Tuncel , Taylan Taner Doğan , Pınar Ayvazoğlu Demir

https://doi.org/10.31797/vetbio.1550837

Abstract

In this study, the beef price, prices of substitute goods (lamb and chicken meat prices), change in national income and effects of COVID-19 on beef demand for the years 2010-2021 is examined using the ARDL Bounds Test Approach. The study finds that in the long run, an 1% increase in income leads to an approximately, on average, 0.54% increase in demand for beef whereas an 1% increase in beef prices results in, on average, an approximately 0.25% decrease in beef demand. Moreover it is determined that, in the long run, an increase of 1% in the price of lamb meat causes, on average, a 0.37% increase in beef demand, and an 1% increase in chicken meat prices results in on average, a 0.11% decrease in beef demand. This study also uses a dummy variable to account for COVID 19 pandemic effect on the demand of beef. According to the findings for this variable, the pandemic, reduces meat demand, on average, 11% with compared to non-pandemic period. As a result, the demand for beef is found to be affected by the income status of the consumer and the prices of the product itself and its substitutes.

Keywords

ARDL model Beef demand Cattle fattening COVID-19 SHRI (Stay-at-Home Restriction Index)

References

  • 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
  • Aydin, E., & Demir, P. A. (2022). The effect of the pandemic on the consumption of animal products: the case of Kafkas university of Turkey. Online Journal of Animal and Feed Research, 12(1), 37-45. https://doi.org/10.51227/ojafr.2022.6
  • BLS (Bureau of Labor Statistics) (2022). Average Retail Food and Energy Prices. March 2022. https://www.bls.gov/regions/mid-atlantic/data/averageretailfoodandenergyprices_usandwest_table.htm
  • Bracale, R., & Vaccaro, C. M. (2020). Changes in food choice following restrictive measures due to Covid-19. Nutrition, Metabolism and Cardiovascular Diseases, 30(9), 1423-1426. https://doi.org/10.1016/j.numecd.2020.05.027
  • BSG (Blavatnik School of Government) (2022). COVID-19 government response tracker. March 2022. https://www.bsg.ox.ac.uk/research/covid-19-government-response-tracker.
  • Coluccia, B., Agnusdei, G. P., Miglietta, P. P., & De Leo, F. (2021). Effects of COVID-19 on the Italian agri-food supply and value chains. Food Control, 123, 107839. https://doi.org/10.1016/j.foodcont.2020.107839
  • EViews Corporation (2023). EViews-10 package program, USA: EViews Corp.
  • GCDL(Global-Change-Data-Lab) (2022). Our world in data. September 2022. https://ourworldindata.org/ 10, 2023
  • Güney, O. I., & Sangün, L. (2021). How COVID-19 affects individuals' food consumption behaviour: a consumer survey on attitudes and habits in Turkey. British Food Journal, 123(7), 2307-2320. https://doi.org/10.1108/BFJ-10-2020-0949
  • Hatırlı, S. A., Öztürk, E., & Aktaş, A. R. (2008). Kırmızı, tavuk ve beyaz et talebinin tam talep sistemi yaklaşımıyla analizi. Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 6(1), 211-222.
  • Kerr, W. A. (2021). Agriculture after a year with COVID‐19: Any long‐term implications for international trade policy?. Canadian Journal of Agricultural Economics/Revue Canadienne D'agroeconomie, 69(2), 261-267. https://doi.org/10.1111/cjag.12274
  • Laguna, L., Fiszman, S., Puerta, P., Chaya, C., & Tárrega, A. (2020). The impact of COVID-19 lockdown on food priorities. Results from a preliminary study using social media and an online survey with Spanish consumers. Food Quality and Preference, 86, 104028. https://doi.org/10.1016/j.foodqual.2020.104028
  • LMIC (Livestock Marketing Information Center) (2022). Prices-and-production datas. https://lmic.info/spreadsheet/prices-and-production
  • Long, N. N., & Khoi, B. H. (2020). An empirical study about the intention to hoard food during COVID-19 pandemic. Eurasia Journal of Mathematics, Science and Technology Education, 16(7), 1-12. https://doi.org/10.29333/ejmste/8207
  • Mallory, M. L. (2021). Impact of COVID‐19 on medium‐term export prospects for soybeans, corn, beef, pork, and poultry. Applied Economic Perspectives and Policy, 43(1), 292-303. https://doi.org/10.1002/aepp.13113
  • Martin-Neuninger, R., & Ruby, M. B. (2020). What does food retail research tell us about the implications of coronavirus (COVID-19) for grocery purchasing habits? Frontiers in Psychology, 1(11), 1-10. https://doi: 10.3389/fpsyg.2020.01448
  • Narayan, P. K., & Smyth, R. (2006). What determines migration flows from low‐income to high‐income countries? An empirical investigation of Fiji–Us migration 1972–2001. Contemporary Economic Policy, 24(2), 332-342. https://doi.org/10.1093/cep/byj019
  • Nordhagen, S., Igbeka, U., Rowlands, H., Shine, R. S., Heneghan, E., & Tench, J. (2021). COVID-19 and small enterprises in the food supply chain: Early impacts and implications for longer-term food system resilience in low-and middle-income countries. World Development, 141(1), 1-9. https://doi.org/10.1016/j.worlddev.2021.105405
  • Pesaran, H.M., & Shin, Y. (1999). Autoregressive distributed lag modelling approach to cointegration analysis. In Strom, S. (Ed.) Econometrics and Economic Theory in the 20th Century. Century (pp 146-155). Akademic Press Association. https://doi.org/10.1017/CCOL521633230.011UK:
  • Pesaran, H.M., Shin, Y., & Smith, R.J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(2), 289-326. https://doi.org/10.1002/jae.616
  • Rude, J. (2021). COVID‐19 and the Canadian cattle/beef sector: A second look. Canadian Journal of Agricultural Economics/Revue Canadienne D'agroeconomie, 69(2), 233-241. https://doi.org/10.1111/cjag.12277
  • Saygın, Ö., & Demirbaş, N. (2018). Red meat consumption in Turkey: Problems and suggestions. Selcuk Journal of Agriculture and Food Sciences, 32(3), 567-574. https://doi: 10.15316/sjafs.2018.138
  • Snuggs, S., & McGregor, S. (2021). Food & meal decision making in lockdown: How and who has Covid-19 affected? Food Quality and Preference, 89, 104145. https://doi.org/10.1016/j.foodqual.2020.104145
  • STATCAN (Statistics Canada) (2022). Monthly average retail prices for food and other selected products. https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1810024501
  • Toda, H. (1991). Vector autoregression and causality. USA: Connecticut University Publishing.
  • Tuncel, S (2023). Comparison of different levels of restrictions ımposed ın turkey during the covid-19 pandemic with the data on the demand for meat at the outlets of the Meat and Milk Board. Сukurova Agriculture And Veterınary Congress, Turkiye, 111-119. https://www.ziraatkongresi.org/_files/ugd/614b1f_b765b569900843648371b1d707f2d4aa.pdf
  • TSI (Turkish Statistical Institute) (2022a). Annual meat and milk production statistics. https://data.tuik.gov.tr/Bulten/Index?p=Kirmizi-Et-Uretim-Istatistikleri-2022-49696#:~:text=Bu%20kapsamda%20bir%20%C3%B6nceki%20y%C4%B1la,13%20bin%20586%20ton%20oldu.
  • TSI (Turkish Statistical Institute) (2022b). Quarterly meat production statistics. https://data.tuik.gov.tr/Bulten/Index?p=Red-Meat-Production-Statistics-2020-2021-4567
  • TSI (Turkish Statistical Institute) (2022c). Quarterly adjustment statistics. https://biruni.tuik.gov.tr/medas/?kn=79&locale=tr
  • TSI (Turkish Statistical Institute) (2022d). Meat import statistics. https://iz.tuik.gov.tr/#/showcase/SC-2851FY777F34D2R/db-dfr20j85b986782?token=8d79727fff862a891ce574d27220bfebbf66fecd
  • TSI (Turkish Statistical Institute) (2022e). Prices of animal products. https://data.tuik.gov.tr/Bulten/Index?p=Canli-Hayvan-ve-Hayvansal-Urun-Fiyatlari-ve-Uretim-Degeri-2021-45507
  • TSI (Turkish Statistical Institute) (2022f). National income Statistics. https://data.tuik.gov.tr/Bulten/Index?p=Gelir-Dagilimi-Istatistikleri-2022-49745#:~:text=T%C3%BCrkiye'de%20y%C4%B1ll%C4%B1k%20ortalama%20hanehalk%C4%B1,98%20bin%20416%20TL%20oldu.andtext=T%C3%BCrkiye'de%20y%C4%B1ll%C4%B1k%20ortalama%20e%C5%9Fde%C4%9Fer,bin%20642%20TL'ye%20y%C3%BCkseldi
  • Statistical Institute) (2022g). Tüketici fiyat endeksi istatistikleri. https://data.tuik.gov.tr/Bulten/Index?p=Tuketici-Fiyat-Endeksi-Haziran-2023-49658#:~:text=T%C3%9C%C4%B0K%20Kurumsal&text=T%C3%9CFE'deki%20(2003%3D100,%59%2C95%20olarak%20ger%C3%A7ekle%C5%9Fti
  • USDA (United States Department Of Agriculture) (2022). Monthly commercial slaughter of commercial beef, pork, and poultry. https://www.ers.usda.gov/webdocs/outlooks/100071/ldp-m-318.pdf
  • Weersink, A., Massow, MV., Bannon, N., Ifft, J., Maples, J., McEwan, K., Melissa, GS., McKendre, E., Nicholson, C., Novakovic, A., Rangarajan, A., Richards, T., Rickard, B., Rude, J., Schipanski, M., Schnitkey G., Schulz, L., Schuurman, D., Schwartzkopf-Genswein K., Stephenson, M,, Thompson, J & Wood, K. (2021). COVID-19 and the agri-food system in the United States and Canada. Agricultural Systems, 188, 103039. https://doi.org/10.1016/j.agsy.2020.103039

Year 2025, Volume: 10 Issue: 1, 52 - 59, 30.04.2025

Seyfettin Tuncel , Taylan Taner Doğan , Pınar Ayvazoğlu Demir

https://doi.org/10.31797/vetbio.1550837

Abstract

References

  • 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
  • Aydin, E., & Demir, P. A. (2022). The effect of the pandemic on the consumption of animal products: the case of Kafkas university of Turkey. Online Journal of Animal and Feed Research, 12(1), 37-45. https://doi.org/10.51227/ojafr.2022.6
  • BLS (Bureau of Labor Statistics) (2022). Average Retail Food and Energy Prices. March 2022. https://www.bls.gov/regions/mid-atlantic/data/averageretailfoodandenergyprices_usandwest_table.htm
  • Bracale, R., & Vaccaro, C. M. (2020). Changes in food choice following restrictive measures due to Covid-19. Nutrition, Metabolism and Cardiovascular Diseases, 30(9), 1423-1426. https://doi.org/10.1016/j.numecd.2020.05.027
  • BSG (Blavatnik School of Government) (2022). COVID-19 government response tracker. March 2022. https://www.bsg.ox.ac.uk/research/covid-19-government-response-tracker.
  • Coluccia, B., Agnusdei, G. P., Miglietta, P. P., & De Leo, F. (2021). Effects of COVID-19 on the Italian agri-food supply and value chains. Food Control, 123, 107839. https://doi.org/10.1016/j.foodcont.2020.107839
  • EViews Corporation (2023). EViews-10 package program, USA: EViews Corp.
  • GCDL(Global-Change-Data-Lab) (2022). Our world in data. September 2022. https://ourworldindata.org/ 10, 2023
  • Güney, O. I., & Sangün, L. (2021). How COVID-19 affects individuals' food consumption behaviour: a consumer survey on attitudes and habits in Turkey. British Food Journal, 123(7), 2307-2320. https://doi.org/10.1108/BFJ-10-2020-0949
  • Hatırlı, S. A., Öztürk, E., & Aktaş, A. R. (2008). Kırmızı, tavuk ve beyaz et talebinin tam talep sistemi yaklaşımıyla analizi. Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 6(1), 211-222.
  • Kerr, W. A. (2021). Agriculture after a year with COVID‐19: Any long‐term implications for international trade policy?. Canadian Journal of Agricultural Economics/Revue Canadienne D'agroeconomie, 69(2), 261-267. https://doi.org/10.1111/cjag.12274
  • Laguna, L., Fiszman, S., Puerta, P., Chaya, C., & Tárrega, A. (2020). The impact of COVID-19 lockdown on food priorities. Results from a preliminary study using social media and an online survey with Spanish consumers. Food Quality and Preference, 86, 104028. https://doi.org/10.1016/j.foodqual.2020.104028
  • LMIC (Livestock Marketing Information Center) (2022). Prices-and-production datas. https://lmic.info/spreadsheet/prices-and-production
  • Long, N. N., & Khoi, B. H. (2020). An empirical study about the intention to hoard food during COVID-19 pandemic. Eurasia Journal of Mathematics, Science and Technology Education, 16(7), 1-12. https://doi.org/10.29333/ejmste/8207
  • Mallory, M. L. (2021). Impact of COVID‐19 on medium‐term export prospects for soybeans, corn, beef, pork, and poultry. Applied Economic Perspectives and Policy, 43(1), 292-303. https://doi.org/10.1002/aepp.13113
  • Martin-Neuninger, R., & Ruby, M. B. (2020). What does food retail research tell us about the implications of coronavirus (COVID-19) for grocery purchasing habits? Frontiers in Psychology, 1(11), 1-10. https://doi: 10.3389/fpsyg.2020.01448
  • Narayan, P. K., & Smyth, R. (2006). What determines migration flows from low‐income to high‐income countries? An empirical investigation of Fiji–Us migration 1972–2001. Contemporary Economic Policy, 24(2), 332-342. https://doi.org/10.1093/cep/byj019
  • Nordhagen, S., Igbeka, U., Rowlands, H., Shine, R. S., Heneghan, E., & Tench, J. (2021). COVID-19 and small enterprises in the food supply chain: Early impacts and implications for longer-term food system resilience in low-and middle-income countries. World Development, 141(1), 1-9. https://doi.org/10.1016/j.worlddev.2021.105405
  • Pesaran, H.M., & Shin, Y. (1999). Autoregressive distributed lag modelling approach to cointegration analysis. In Strom, S. (Ed.) Econometrics and Economic Theory in the 20th Century. Century (pp 146-155). Akademic Press Association. https://doi.org/10.1017/CCOL521633230.011UK:
  • Pesaran, H.M., Shin, Y., & Smith, R.J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(2), 289-326. https://doi.org/10.1002/jae.616
  • Rude, J. (2021). COVID‐19 and the Canadian cattle/beef sector: A second look. Canadian Journal of Agricultural Economics/Revue Canadienne D'agroeconomie, 69(2), 233-241. https://doi.org/10.1111/cjag.12277
  • Saygın, Ö., & Demirbaş, N. (2018). Red meat consumption in Turkey: Problems and suggestions. Selcuk Journal of Agriculture and Food Sciences, 32(3), 567-574. https://doi: 10.15316/sjafs.2018.138
  • Snuggs, S., & McGregor, S. (2021). Food & meal decision making in lockdown: How and who has Covid-19 affected? Food Quality and Preference, 89, 104145. https://doi.org/10.1016/j.foodqual.2020.104145
  • STATCAN (Statistics Canada) (2022). Monthly average retail prices for food and other selected products. https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1810024501
  • Toda, H. (1991). Vector autoregression and causality. USA: Connecticut University Publishing.
  • Tuncel, S (2023). Comparison of different levels of restrictions ımposed ın turkey during the covid-19 pandemic with the data on the demand for meat at the outlets of the Meat and Milk Board. Сukurova Agriculture And Veterınary Congress, Turkiye, 111-119. https://www.ziraatkongresi.org/_files/ugd/614b1f_b765b569900843648371b1d707f2d4aa.pdf
  • TSI (Turkish Statistical Institute) (2022a). Annual meat and milk production statistics. https://data.tuik.gov.tr/Bulten/Index?p=Kirmizi-Et-Uretim-Istatistikleri-2022-49696#:~:text=Bu%20kapsamda%20bir%20%C3%B6nceki%20y%C4%B1la,13%20bin%20586%20ton%20oldu.
  • TSI (Turkish Statistical Institute) (2022b). Quarterly meat production statistics. https://data.tuik.gov.tr/Bulten/Index?p=Red-Meat-Production-Statistics-2020-2021-4567
  • TSI (Turkish Statistical Institute) (2022c). Quarterly adjustment statistics. https://biruni.tuik.gov.tr/medas/?kn=79&locale=tr
  • TSI (Turkish Statistical Institute) (2022d). Meat import statistics. https://iz.tuik.gov.tr/#/showcase/SC-2851FY777F34D2R/db-dfr20j85b986782?token=8d79727fff862a891ce574d27220bfebbf66fecd
  • TSI (Turkish Statistical Institute) (2022e). Prices of animal products. https://data.tuik.gov.tr/Bulten/Index?p=Canli-Hayvan-ve-Hayvansal-Urun-Fiyatlari-ve-Uretim-Degeri-2021-45507
  • TSI (Turkish Statistical Institute) (2022f). National income Statistics. https://data.tuik.gov.tr/Bulten/Index?p=Gelir-Dagilimi-Istatistikleri-2022-49745#:~:text=T%C3%BCrkiye'de%20y%C4%B1ll%C4%B1k%20ortalama%20hanehalk%C4%B1,98%20bin%20416%20TL%20oldu.andtext=T%C3%BCrkiye'de%20y%C4%B1ll%C4%B1k%20ortalama%20e%C5%9Fde%C4%9Fer,bin%20642%20TL'ye%20y%C3%BCkseldi
  • Statistical Institute) (2022g). Tüketici fiyat endeksi istatistikleri. https://data.tuik.gov.tr/Bulten/Index?p=Tuketici-Fiyat-Endeksi-Haziran-2023-49658#:~:text=T%C3%9C%C4%B0K%20Kurumsal&text=T%C3%9CFE'deki%20(2003%3D100,%59%2C95%20olarak%20ger%C3%A7ekle%C5%9Fti
  • USDA (United States Department Of Agriculture) (2022). Monthly commercial slaughter of commercial beef, pork, and poultry. https://www.ers.usda.gov/webdocs/outlooks/100071/ldp-m-318.pdf
  • Weersink, A., Massow, MV., Bannon, N., Ifft, J., Maples, J., McEwan, K., Melissa, GS., McKendre, E., Nicholson, C., Novakovic, A., Rangarajan, A., Richards, T., Rickard, B., Rude, J., Schipanski, M., Schnitkey G., Schulz, L., Schuurman, D., Schwartzkopf-Genswein K., Stephenson, M,, Thompson, J & Wood, K. (2021). COVID-19 and the agri-food system in the United States and Canada. Agricultural Systems, 188, 103039. https://doi.org/10.1016/j.agsy.2020.103039
There are 35 citations in total.

Details

Primary Language English
Subjects Animal Health Economics and Management
Journal Section Research Articles
Authors

Seyfettin Tuncel 0000-0003-3575-1835

Taylan Taner Doğan 0000-0002-8901-0189

Pınar Ayvazoğlu Demir 0000-0002-7010-0475

Publication Date April 30, 2025
Submission Date September 16, 2024
Acceptance Date February 18, 2025
Published in Issue Year 2025 Volume: 10 Issue: 1

Cite

APA Tuncel, S., Doğan, T. T., & Ayvazoğlu Demir, P. (2025). Factors affecting beef demand in Türkiye for 2010-2021 and the effects of restrictions imposed during the Coronavirus disease (COVID-19) period. Journal of Advances in VetBio Science and Techniques, 10(1), 52-59. https://doi.org/10.31797/vetbio.1550837
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