IDEAS home Printed from https://ideas.repec.org/a/bba/j00005/v3y2025i1p1-6d425.html
   My bibliography  Save this article

Which Came First, The Chicken or the Egg? What about Ducks?: Granger Causality Using Philippine Poultry Data

Author

Listed:
  • John Francis Diaz

    (Department of Finance and Accounting, Asian Institute of Management, Makati, Philippines)

Abstract

The paper studies Philippine poultry data and revisits the chicken or the egg causality problem to include ducks data. Using quarterly Philippine poultry production time-series from the first quarter of 1980 to the last quarter of 2014, this research finds that chickens came from eggs, which is consistent with the earlier statistical results of Thurman and Fisher (1988), and genetics-based conclusions of Eriksson et al. (2008). However, no conclusive evidence was found using the Philippine duck and duck eggs data. The chicken or the egg conundrum demonstrates the power of Granger causality testing in answering questions of temporal ordering that has various causal applications using macroeconomic, financial, and agricultural time-series data.

Suggested Citation

  • John Francis Diaz, 2025. "Which Came First, The Chicken or the Egg? What about Ducks?: Granger Causality Using Philippine Poultry Data," Journal of Economic Statistics, Anser Press, vol. 3(1), pages 1-6, March.
  • Handle: RePEc:bba:j00005:v:3:y:2025:i:1:p:1-6:d:425
    as

    Download full text from publisher

    File URL: https://www.anserpress.org/journal/jes/3/1/18/pdf
    Download Restriction: no

    File URL: https://www.anserpress.org/journal/jes/3/1/18
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lee, Tae-Hwy & Yang, Weiping, 2014. "Granger-causality in quantiles between financial markets: Using copula approach," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 70-78.
    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. Chia-Lin Chang & Michael McAleer, 2017. "A Simple Test for Causality in Volatility," Econometrics, MDPI, vol. 5(1), pages 1-5, March.
    2. Corbet, Shaen & Katsiampa, Paraskevi & Lau, Chi Keung Marco, 2020. "Measuring quantile dependence and testing directional predictability between Bitcoin, altcoins and traditional financial assets," International Review of Financial Analysis, Elsevier, vol. 71(C).
    3. Talbi, Marwa & de Peretti, Christian & Belkacem, Lotfi, 2020. "Dynamics and causality in distribution between spot and future precious metals: A copula approach," Resources Policy, Elsevier, vol. 66(C).
    4. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Chi‐Chuan Lee & Matthew Ntow‐Gyamfi, 2023. "Quantile price convergence and spillover effects among Bitcoin, Fintech, and artificial intelligence stocks," International Review of Finance, International Review of Finance Ltd., vol. 23(1), pages 187-205, March.
    5. Danau, Daniel, 2020. "Prudence and preference for flexibility gain," European Journal of Operational Research, Elsevier, vol. 287(2), pages 776-785.
    6. Tan T. M. Le & Franck Martin & Duc K. Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Economics Working Paper Archive (University of Rennes & University of Caen) 2018-04, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    7. Elie Bouri & Rangan Gupta & Chi keung marco Lau & David Roubaud, 2021. "Risk aversion and Bitcoin returns in extreme quantiles," Economics Bulletin, AccessEcon, vol. 41(3), pages 1374-1386.
    8. Chen, Qitong & Zhu, Huiming & Yu, Dongwei & Hau, Liya, 2022. "How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    9. Hong Cheng & Yunqing Wang & Yihong Wang & Tinggan Yang, 2022. "Inferring Causal Interactions in Financial Markets Using Conditional Granger Causality Based on Quantile Regression," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 719-748, February.
    10. Jiang, Cuixia & Li, Yuqian & Xu, Qifa & Liu, Yezheng, 2021. "Measuring risk spillovers from multiple developed stock markets to China: A vine-copula-GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 386-398.
    11. Jalan, Akanksha & Matkovskyy, Roman & Yarovaya, Larisa, 2021. "“Shiny” crypto assets: A systemic look at gold-backed cryptocurrencies during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 78(C).
    12. Albulescu, Claudiu Tiberiu & Aubin, Christian & Goyeau, Daniel & Tiwari, Aviral Kumar, 2018. "Extreme co-movements and dependencies among major international exchange rates: A copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 56-69.
    13. Ruan, Qingsong & Zhang, Manqian & Lv, Dayong & Yang, Haiquan, 2018. "SAD and stock returns revisited: Nonlinear analysis based on MF-DCCA and Granger test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1009-1022.
    14. Hussain Shahzad, Syed Jawad & Raza, Naveed & Shahbaz, Muhammad & Ali, Azwadi, 2017. "Dependence of stock markets with gold and bonds under bullish and bearish market states," Resources Policy, Elsevier, vol. 52(C), pages 308-319.
    15. Wang, Faming & Rong, Xueyun & Yin, Lei, 2024. "The uncertainty of fluctuation correlations in global stock markets," Finance Research Letters, Elsevier, vol. 66(C).
    16. Franch, Fabio & Nocciola, Luca & Vouldis, Angelos, 2024. "Temporal networks and financial contagion," Journal of Financial Stability, Elsevier, vol. 71(C).
    17. Cao, Guangxi & Han, Yan & Li, Qingchen & Xu, Wei, 2017. "Asymmetric MF-DCCA method based on risk conduction and its application in the Chinese and foreign stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 119-130.
    18. Kim, Jong-Min & Lee, Namgil & Hwang, Sun Young, 2020. "A Copula Nonlinear Granger Causality," Economic Modelling, Elsevier, vol. 88(C), pages 420-430.
    19. Ahmed M. Khedr & Ifra Arif & Pravija Raj P V & Magdi El‐Bannany & Saadat M. Alhashmi & Meenu Sreedharan, 2021. "Cryptocurrency price prediction using traditional statistical and machine‐learning techniques: A survey," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 3-34, January.
    20. Bouri, Elie & Gupta, Rangan & Lau, Chi Keung Marco & Roubaud, David & Wang, Shixuan, 2018. "Bitcoin and global financial stress: A copula-based approach to dependence and causality in the quantiles," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 297-307.

    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:bba:j00005:v:3:y:2025:i:1:p:1-6:d:425. 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: Ramona Wang (email available below). General contact details of provider: https://www.anserpress.org .

    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.