IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i15p6257-d394073.html

Causality Analysis of the Factors Affecting the Consumer Price of Veal: The Case of Turkey

Author

Listed:
  • Burak Mat

    (Department of Livestock Economics and Management, Faculty of Veterinary Medicine, Selçuk University, TR-42003 Konya, Turkey)

  • Mehmet Saltuk Arikan

    (Department of Animal Health Economics and Management, Faculty of Veterinary Medicine, Fırat University, TR-23119 Elazıg, Turkey)

  • Mustafa Bahadir Çevrimli

    (Department of Livestock Economics and Management, Faculty of Veterinary Medicine, Selçuk University, TR-42003 Konya, Turkey)

  • Ahmet Cumhur Akin

    (Department of Animal Health Economics and Management, Faculty of Veterinary Medicine, Mehmet Akif Ersoy University, TR-15030 Burdur, Turkey)

  • Mustafa Agah Tekindal

    (Department of Biostatistics, Faculty of Medicine, İzmir Katip Çelebi University, TR-35640 İzmir, Turkey)

Abstract

It is interesting to identify the reasons and the direction of the correlation between the input/output prices and the macro/micro parameters in animal production processes. In the present study, the time series of the monthly data between the years 2014 and 2019 were analyzed to examine the factors that affected the consumer price of carcass meat in Turkey. An attempt was made to identify the relationship between the consumer price of carcass meat and the prices of cattle fattening feed, the exchange rate of the dollar, producer price index (PPI), and the agricultural PPI, which were anticipated to affect the consumer price of carcass meat as determined by the Granger causality analysis. According to econometric analysis results, when there is a change in carcass producer price, cattle fattening feed and PPI in the short term, the consumer price of carcass meat is affected by this. The producer price of carcass and PPI variables are determined to be the cause of each other’s Granger. At the same time, the PPI variable and the consumer price of carcass meat and dollar rate variables were found to be the cause of each other’s Granger. If Turkey is to prevent the excessive fluctuations in the consumer- and producer-prices of carcass meat caused by macro variables, an effective price control mechanism should be put into practice. It seems that this change would be possible only by developing and implementing policies to lower the input prices and production costs.

Suggested Citation

  • Burak Mat & Mehmet Saltuk Arikan & Mustafa Bahadir Çevrimli & Ahmet Cumhur Akin & Mustafa Agah Tekindal, 2020. "Causality Analysis of the Factors Affecting the Consumer Price of Veal: The Case of Turkey," Sustainability, MDPI, vol. 12(15), pages 1-11, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:15:p:6257-:d:394073
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/15/6257/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/15/6257/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christopher L. Gilbert, 2010. "How to Understand High Food Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(2), pages 398-425, June.
    2. Yu-Chin Chen & Kenneth S. Rogoff & Barbara Rossi, 2010. "Can Exchange Rates Forecast Commodity Prices?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 1145-1194.
    3. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    4. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    5. Harri, Ardian & Nalley, Lanier & Hudson, Darren, 2009. "The Relationship between Oil, Exchange Rates, and Commodity Prices," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(2), pages 501-510, August.
    6. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    7. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Juan Antonio Galán-Gutiérrez & Rodrigo Martín-García, 2022. "Fundamentals vs. Financialization during Extreme Events: From Backwardation to Contango, a Copper Market Analysis during the COVID-19 Pandemic," Mathematics, MDPI, vol. 10(4), pages 1-23, February.

    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. Ebenezer, Appiah Collins & Jatoe, John Baptist D. & Mensa-Bonsu, Akwasi, "undated". "Food Price Sensitivity To Changes In Petroleum Price And Exchange Rate In Ghana: A Cointegration Analysis," 2018 Conference (2nd), August 8-11, Kumasi, Ghana 277791, Ghana Association of Agricultural Economists.
    2. Ramona Dumitriu & Razvan Stefanescu, 2015. "The Relationship Between Romanian Exports And Economic Growth After The Adhesion To European Union," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 17-26.
    3. Ericsson, Neil R & Hendry, David F & Mizon, Grayham E, 1998. "Exogeneity, Cointegration, and Economic Policy Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 370-387, October.
    4. Farzanegan, Mohammad Reza & Markwardt, Gunther, 2009. "The effects of oil price shocks on the Iranian economy," Energy Economics, Elsevier, vol. 31(1), pages 134-151, January.
    5. Moses M. Kupabado & Juergen Kaehler, 2021. "Financialization, common stochastic trends, and commodity prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 1988-2008, December.
    6. Glass, Anthony, 2009. "Government expenditure on public order and safety, economic growth and private investment: Empirical evidence from the United States," International Review of Law and Economics, Elsevier, vol. 29(1), pages 29-37, March.
    7. Nobel Prize Committee, 2003. "Time-series Econometrics: Cointegration and Autoregressive Conditional Heteroskedasticity," Nobel Prize in Economics documents 2003-1, Nobel Prize Committee.
    8. Federici, Andrea, 2018. "Il rapporto tra capitale pubblico e altre variabili macroeconomiche: un'applicazione empirica [The relationship between public capital and other macroeconomic variables: an empirical application]," MPRA Paper 88516, University Library of Munich, Germany.
    9. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, January.
    10. Borozan, Djula, 2013. "Exploring the relationship between energy consumption and GDP: Evidence from Croatia," Energy Policy, Elsevier, vol. 59(C), pages 373-381.
    11. Soytas, Ugur & Sari, Ramazan, 2006. "Energy consumption and income in G-7 countries," Journal of Policy Modeling, Elsevier, vol. 28(7), pages 739-750, October.
    12. João Leitão, 2004. "Demand Pull And Supply Push In Portuguese Cable Television," Econometrics 0409011, University Library of Munich, Germany.
    13. Imad Jabir, 2009. "The dynamic relationship between the US GDP, imports and domestic production of crude oil," Applied Economics, Taylor & Francis Journals, vol. 41(24), pages 3171-3178.
    14. Fredy Pokou & Jules Sadefo Kamdem & Kpante Emmanuel Gnandi, 2026. "Predictive Accuracy versus Interpretability in Energy Markets: A Copula-Enhanced TVP-SVAR Analysis," Working Papers hal-05478482, HAL.
    15. Christophe Kamps, 2005. "The Dynamic Effects of Public Capital: VAR Evidence for 22 OECD Countries," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 12(4), pages 533-558, August.
    16. Geweke, John F. & Horowitz, Joel L. & Pesaran, M. Hashem, 2006. "Econometrics: A Bird's Eye View," IZA Discussion Papers 2458, IZA Network @ LISER.
    17. Yoon, Seong-Min, 2022. "On the interdependence between biofuel, fossil fuel and agricultural food prices: Evidence from quantile tests," Renewable Energy, Elsevier, vol. 199(C), pages 536-545.
    18. Adämmer, Philipp & Bohl, Martin T., 2015. "Speculative bubbles in agricultural prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 55(C), pages 67-76.
    19. Juergen Amann & Paul Middleditch, 2017. "Growth in a time of austerity: evidence from the UK," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(4), pages 349-375, September.
    20. Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2014. "Causality and contagion in EMU sovereign debt markets," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 12-27.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:gam:jsusta:v:12:y:2020:i:15:p:6257-:d:394073. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.