Research Article
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Year 2023, Volume: 9 Issue: 3, 212 - 229, 05.07.2023

Hande Mutlu Öztürk , Harun Kemal Öztürk

https://doi.org/10.3153/FH23020

Abstract

Keywords

Multiple Linear Regression Meat Consumption Estimation Turkey Polynomial Linear Regression Analysis Logarithmic Linear Regression Analysis Linear Regression Analysis

References

  • Agirre-Basurko, E., Ibarra-Berastegi, G., Madariaga, I. (2006). Regression and multilayer perceptron-based models to fore-cast hourly O-3 and NO2 levels in the Bilbao area. Environmental Modelling & Software, 21(4), 430-446. https://doi.org/10.1016/j.envsoft.2004.07.008
  • Aguiar, M., Hurst, E. (2005). Consumption versus expenditure. Journal of political Economy, 113 (5), 919-948. https://doi.org/10.1086/491590
  • Aiken, L.S., West, S.G., Pitts, S.C. (2003). Multiple linear regression. In Schinka, J. A., Velicer, N. F. (Eds.), Research Methods in Psychology. New Jersey: John Wiley & Sons. https://doi.org/10.1002/0471264385.wei0219
  • Antelo, M., Magdalena, P., Reboredo, J.C. (2017). Economic crisis and the unemployment effect on household food expenditure: The case of Spain. Food Policy, 69, 11-24. https://doi.org/10.1016/j.foodpol.2017.03.003
  • Ásgeirsdóttir, T.L., Corman, H., Noonan, K., Ólafsdóttir, T, Reichman, N.E. (2014). Was the economic crisis of 2008 good for Icelanders? Impact on health behaviours. Economics & Human Biology, 13, 1-19. https://doi.org/10.1016/j.ehb.2013.03.005
  • Aydogdu, M.H., Kucuk, N. (2018). General Analysis of Recent Changes in Red Meat Consumption in Turkey. IOSR Journal of Economics and Finance (IOSR-JEF), 9(6)Ver. IV, 01-08.
  • Azabagaoglu, M.O., Oraman, Y. (2011). Analysis of customer expectations after the recession: Case of food sector. Procedia-Social and Behavioural Sciences, 24, 229-236. https://doi.org/10.1016/j.sbspro.2011.09.008
  • Bagozzi, R.P., Yi, Y. (1988). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science, 16(2), 74-94. https://doi.org/10.1007/BF02723327
  • Baysal, A. (2007). General nutrition, 12. Baskı, Hatipoğlu Yayın Evi, Ankara.
  • Bentolila, S., Ichino, A. (2008). Unemployment and consumption near and far away from the Mediterranean. Journal of Population Economics, 21(2), 255-280. https://doi.org/10.1007/s00148-006-0081-z
  • Bilgic, A., Yen, S. T. (2013). Household food demand in Turkey: A two-step demand system approach. Food Policy, 43, 267-277. https://doi.org/10.1016/j.foodpol.2013.09.004
  • Carroll, C. D., Dynan, K. E., Krane, S. D. (2003). Unemployment risk and precautionary wealth: Evidence from households' balance sheets. Review of Economics and Statistics, 85(3), 586-604. https://doi.org/10.1162/003465303322369740
  • Coelho-Barros, E.A., Simoes, P.A., Achcar, J.A., Martinez E.Z., Shimano A.C. (2008). Methods of Estimation in Multiple Linear Regression: Application to Clinical Data. La revista Colombiana de Estadística, 31(1), 111-129.
  • Demirtas B. (2018). The Effect of Price Increases on Fresh Meat Consumption in Turkey. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 66(5), 1249-1259. https://doi.org/10.11118/actaun201866051249
  • Dogan, V., Yilmaz, C. (2017). Comparison of Independent Variables In Management Sciences and Marketing. Uluslararası Yönetim İktisat ve İşletme Dergisi, 13(2), 385-406.
  • FAO (2019). FAOSTAT: Statistical Database. Food Balance Sheets. Available at: http://www.fao.org/faostat/en/#data/FBS (accessed 15.04.19).
  • FAO-OECD (2019a). OECD-FAO Agricultural Outlook 2017-2026, Meats-OECD-FAO Agricultural Outlook 2017-2026. Available at: https://stats.oecd.org/index.aspx?queryid=76854 (accessed 15.04.19).
  • FAO-OECD (2019b). OECD-FAO Agricultural Outlook 2018-2027, Meats-OECD-FAO Agricultural Outlook 2018-2027.Available at: https://stats.oecd.org/Index.aspx?QueryId=84957 (accessed 15.04.19).
  • Ferraro M.B., Giordani P. (2012). A multiple linear regression model for imprecise information. Metrika, 75(8), 1049-1068. https://doi.org/10.1007/s00184-011-0367-3
  • Gürlük, S., Turan, Ö. (2008). World food crisis: Causes and effects. Uludağ Üniversitesi Ziraat Fakültesi Dergisi, 22(1), 63-74.
  • Ivanova, L., Dimitrov, P., Ovcharova, D., Dellava, J., Hoffman, D.J. (2006). Economic transition and household food consumption: a study of Bulgaria from 1985 to 2002. Economics & Human Biology, 4(3), 383-397. https://doi.org/10.1016/j.ehb.2006.08.001
  • Kovdienko, N.A., Polishchuk, P.G., Muratov, E.N., Artemenko, A.G., Kuz’min, V.E., Gorb, L., Hill, F., Leszczynski, J. (2010). Application of Random Forest and Multiple Linear Regression Techniques to QSPR Prediction of an Aqueous Solubility for Military Compounds. Molecular Informatics, 29(5), 394-406. https://doi.org/10.1002/minf.201000001
  • McAfee, A.J, E.M. McSorley, E.M., Cuskelly, G.J., Moss, B.W., Wallace, J.M.W, Bonham, M.P., Fearon, A.M. (2010). Red meat consumption: an overview of the risks and benefits. Meat Science, 84, 1-23. https://doi.org/10.1016/j.meatsci.2009.08.029
  • Ministry of Development (2014). Animal Husbandry, Special Commission Report, Tenth Development Plan (2014-2018), Ankara.
  • Mutluer, B. (2005). Red meat as compulsory food. Kalite Dergisi, 1, 54.
  • OECD (2019a). OECD-FAO Agricultural Outlook 2016-2025. Available at: https://stats.oecd.org/index.aspx?queryid=76854 (accessed 01.02.12).
  • Pedhazur, E. J. (1997). Multiple Regression in Behavioral Research: Explanation and Prediction. Fort Worth, TX: HarcourtBrace.
  • Ritchie, H., Roser M. (2017). Meat and Seafood Production & Consumption. Our World in Data. Available at: https://ourworldindata.org/meat-and-seafood-production-consumption (accessed 15.04.19). Sepulveda, W., Maza, M.T., Mantecon, A.R. (2008). Factors that affect and motivate the purchase of quality-labelled beef in Spain. Meat Science, 80(4), 1282-1289. https://doi.org/10.1016/j.meatsci.2008.06.012
  • Türkmen-Ceylan, F.B. (2019). Economic crisis and consumption: an almost ideal demand system estimation for Turkey with time-varying parameters. Development Studies Research, 6(1), 13-29. https://doi.org/10.1080/21665095.2019.1566012
  • TURKSTAT (2017). The Results of Address Based Population Registration System, 2017, Available at: https://data.tuik.gov.tr/Bulten/Index?p=The-Results-of-Address-Based-Population-Registration-System-2017-27587 (accessed 23.06.2023).
  • TURKSTAT (2019a). The Results of Address Based Population Registration System, 2019, Available at: https://data.tuik.gov.tr/Bulten/Index?p=The-Results-of-Address-Based-Population-Registration-System-2019-33705 (accessed 23.06.23).
  • TURKSTAT (2019b). Population and Demography. Available at: https://www.tuik.gov.tr/Home/Index (accessed 23.06.23).
  • Worldbank (2019). GDP of Turkey, Available at: https://data.worldbank.org/country/turkey?view=chart (accessed 15.04.19).
  • Yavuz, F., Bilgic, A., Terin, M., Guler, I.O. (2013). Policy implications of trends in Turkey's meat sector with respect to 2023 vision. Meat science, 95(4), 798-804. https://doi.org/10.1016/j.meatsci.2013.03.024
  • Yılmaz, M. (2015). Change and Distribution of Rural Population by Province in Turkey (1980-2012). Eastern Journal of Geography, 20 (33), 161-188. https://doi.org/10.17295/dcd.71070

Estimating meat consumption based on economic indicators using linear regression analysis approach: A case study of Türkiye

Year 2023, Volume: 9 Issue: 3, 212 - 229, 05.07.2023

Hande Mutlu Öztürk , Harun Kemal Öztürk

https://doi.org/10.3153/FH23020

Abstract

The main idea of this study is to investigate Türkiye’s meat consumption, projection and supplies by using the structure of the Turkish meat industry and Turkish economic indicators. This present study develops several models for the analysis of meat consumption and makes future estimations based on the Regression Analysis Meat Consumption Model (RAMCM). Four forms of Regression Analysis models are used to estimate meat consumption. These models are named Multiple Linear Regression Analysis (MULIRA), Linear Regression Analysis (LIRA), Polynomial Linear Regression Analysis (POLIRA), and Logarithmic Linear Regression Analysis. The models developed in the linear and non-linear forms are applied to estimate meat consumption in Türkiye based on social and economic indicators; Population, Gross National Product (GNP) per capita, Imports of goods and services (% of GDP), Exports of goods and services (% of GDP), electricity consumption per capita, unemployment, Gross capital formation (% of GDP) figures. It may be concluded that the Multiple Linear Regression Analysis models can be used as alternative solutions and estimation techniques for any country's future meat consumption values.

Keywords

Multiple Linear Regression Meat Consumption Estimation Polynomial Linear Regression Analysis Logarithmic Linear Regression Analysis Linear Regression Analysis Türkiye

References

  • Agirre-Basurko, E., Ibarra-Berastegi, G., Madariaga, I. (2006). Regression and multilayer perceptron-based models to fore-cast hourly O-3 and NO2 levels in the Bilbao area. Environmental Modelling & Software, 21(4), 430-446. https://doi.org/10.1016/j.envsoft.2004.07.008
  • Aguiar, M., Hurst, E. (2005). Consumption versus expenditure. Journal of political Economy, 113 (5), 919-948. https://doi.org/10.1086/491590
  • Aiken, L.S., West, S.G., Pitts, S.C. (2003). Multiple linear regression. In Schinka, J. A., Velicer, N. F. (Eds.), Research Methods in Psychology. New Jersey: John Wiley & Sons. https://doi.org/10.1002/0471264385.wei0219
  • Antelo, M., Magdalena, P., Reboredo, J.C. (2017). Economic crisis and the unemployment effect on household food expenditure: The case of Spain. Food Policy, 69, 11-24. https://doi.org/10.1016/j.foodpol.2017.03.003
  • Ásgeirsdóttir, T.L., Corman, H., Noonan, K., Ólafsdóttir, T, Reichman, N.E. (2014). Was the economic crisis of 2008 good for Icelanders? Impact on health behaviours. Economics & Human Biology, 13, 1-19. https://doi.org/10.1016/j.ehb.2013.03.005
  • Aydogdu, M.H., Kucuk, N. (2018). General Analysis of Recent Changes in Red Meat Consumption in Turkey. IOSR Journal of Economics and Finance (IOSR-JEF), 9(6)Ver. IV, 01-08.
  • Azabagaoglu, M.O., Oraman, Y. (2011). Analysis of customer expectations after the recession: Case of food sector. Procedia-Social and Behavioural Sciences, 24, 229-236. https://doi.org/10.1016/j.sbspro.2011.09.008
  • Bagozzi, R.P., Yi, Y. (1988). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science, 16(2), 74-94. https://doi.org/10.1007/BF02723327
  • Baysal, A. (2007). General nutrition, 12. Baskı, Hatipoğlu Yayın Evi, Ankara.
  • Bentolila, S., Ichino, A. (2008). Unemployment and consumption near and far away from the Mediterranean. Journal of Population Economics, 21(2), 255-280. https://doi.org/10.1007/s00148-006-0081-z
  • Bilgic, A., Yen, S. T. (2013). Household food demand in Turkey: A two-step demand system approach. Food Policy, 43, 267-277. https://doi.org/10.1016/j.foodpol.2013.09.004
  • Carroll, C. D., Dynan, K. E., Krane, S. D. (2003). Unemployment risk and precautionary wealth: Evidence from households' balance sheets. Review of Economics and Statistics, 85(3), 586-604. https://doi.org/10.1162/003465303322369740
  • Coelho-Barros, E.A., Simoes, P.A., Achcar, J.A., Martinez E.Z., Shimano A.C. (2008). Methods of Estimation in Multiple Linear Regression: Application to Clinical Data. La revista Colombiana de Estadística, 31(1), 111-129.
  • Demirtas B. (2018). The Effect of Price Increases on Fresh Meat Consumption in Turkey. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 66(5), 1249-1259. https://doi.org/10.11118/actaun201866051249
  • Dogan, V., Yilmaz, C. (2017). Comparison of Independent Variables In Management Sciences and Marketing. Uluslararası Yönetim İktisat ve İşletme Dergisi, 13(2), 385-406.
  • FAO (2019). FAOSTAT: Statistical Database. Food Balance Sheets. Available at: http://www.fao.org/faostat/en/#data/FBS (accessed 15.04.19).
  • FAO-OECD (2019a). OECD-FAO Agricultural Outlook 2017-2026, Meats-OECD-FAO Agricultural Outlook 2017-2026. Available at: https://stats.oecd.org/index.aspx?queryid=76854 (accessed 15.04.19).
  • FAO-OECD (2019b). OECD-FAO Agricultural Outlook 2018-2027, Meats-OECD-FAO Agricultural Outlook 2018-2027.Available at: https://stats.oecd.org/Index.aspx?QueryId=84957 (accessed 15.04.19).
  • Ferraro M.B., Giordani P. (2012). A multiple linear regression model for imprecise information. Metrika, 75(8), 1049-1068. https://doi.org/10.1007/s00184-011-0367-3
  • Gürlük, S., Turan, Ö. (2008). World food crisis: Causes and effects. Uludağ Üniversitesi Ziraat Fakültesi Dergisi, 22(1), 63-74.
  • Ivanova, L., Dimitrov, P., Ovcharova, D., Dellava, J., Hoffman, D.J. (2006). Economic transition and household food consumption: a study of Bulgaria from 1985 to 2002. Economics & Human Biology, 4(3), 383-397. https://doi.org/10.1016/j.ehb.2006.08.001
  • Kovdienko, N.A., Polishchuk, P.G., Muratov, E.N., Artemenko, A.G., Kuz’min, V.E., Gorb, L., Hill, F., Leszczynski, J. (2010). Application of Random Forest and Multiple Linear Regression Techniques to QSPR Prediction of an Aqueous Solubility for Military Compounds. Molecular Informatics, 29(5), 394-406. https://doi.org/10.1002/minf.201000001
  • McAfee, A.J, E.M. McSorley, E.M., Cuskelly, G.J., Moss, B.W., Wallace, J.M.W, Bonham, M.P., Fearon, A.M. (2010). Red meat consumption: an overview of the risks and benefits. Meat Science, 84, 1-23. https://doi.org/10.1016/j.meatsci.2009.08.029
  • Ministry of Development (2014). Animal Husbandry, Special Commission Report, Tenth Development Plan (2014-2018), Ankara.
  • Mutluer, B. (2005). Red meat as compulsory food. Kalite Dergisi, 1, 54.
  • OECD (2019a). OECD-FAO Agricultural Outlook 2016-2025. Available at: https://stats.oecd.org/index.aspx?queryid=76854 (accessed 01.02.12).
  • Pedhazur, E. J. (1997). Multiple Regression in Behavioral Research: Explanation and Prediction. Fort Worth, TX: HarcourtBrace.
  • Ritchie, H., Roser M. (2017). Meat and Seafood Production & Consumption. Our World in Data. Available at: https://ourworldindata.org/meat-and-seafood-production-consumption (accessed 15.04.19). Sepulveda, W., Maza, M.T., Mantecon, A.R. (2008). Factors that affect and motivate the purchase of quality-labelled beef in Spain. Meat Science, 80(4), 1282-1289. https://doi.org/10.1016/j.meatsci.2008.06.012
  • Türkmen-Ceylan, F.B. (2019). Economic crisis and consumption: an almost ideal demand system estimation for Turkey with time-varying parameters. Development Studies Research, 6(1), 13-29. https://doi.org/10.1080/21665095.2019.1566012
  • TURKSTAT (2017). The Results of Address Based Population Registration System, 2017, Available at: https://data.tuik.gov.tr/Bulten/Index?p=The-Results-of-Address-Based-Population-Registration-System-2017-27587 (accessed 23.06.2023).
  • TURKSTAT (2019a). The Results of Address Based Population Registration System, 2019, Available at: https://data.tuik.gov.tr/Bulten/Index?p=The-Results-of-Address-Based-Population-Registration-System-2019-33705 (accessed 23.06.23).
  • TURKSTAT (2019b). Population and Demography. Available at: https://www.tuik.gov.tr/Home/Index (accessed 23.06.23).
  • Worldbank (2019). GDP of Turkey, Available at: https://data.worldbank.org/country/turkey?view=chart (accessed 15.04.19).
  • Yavuz, F., Bilgic, A., Terin, M., Guler, I.O. (2013). Policy implications of trends in Turkey's meat sector with respect to 2023 vision. Meat science, 95(4), 798-804. https://doi.org/10.1016/j.meatsci.2013.03.024
  • Yılmaz, M. (2015). Change and Distribution of Rural Population by Province in Turkey (1980-2012). Eastern Journal of Geography, 20 (33), 161-188. https://doi.org/10.17295/dcd.71070
There are 35 citations in total.

Details

Primary Language English
Subjects Food Engineering
Journal Section Research Articles
Authors

Hande Mutlu Öztürk 0000-0002-4404-0106

Harun Kemal Öztürk 0000-0003-4831-1118

Early Pub Date June 25, 2023
Publication Date July 5, 2023
Submission Date November 21, 2022
Published in Issue Year 2023Volume: 9 Issue: 3

Cite

APA Mutlu Öztürk, H., & Öztürk, H. K. (2023). Estimating meat consumption based on economic indicators using linear regression analysis approach: A case study of Türkiye. Food and Health, 9(3), 212-229. https://doi.org/10.3153/FH23020
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