IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1810.01654.html
   My bibliography  Save this paper

Granger causality on horizontal sum of Boolean algebras

Author

Listed:
  • M. Bohdalov'a
  • M. Kalina
  • O. N'an'asiov'a

Abstract

The intention of this paper is to discuss the mathematical model of causality introduced by C.W.J. Granger in 1969. The Granger's model of causality has become well-known and often used in various econometric models describing causal systems, e.g., between commodity prices and exchange rates. Our paper presents a new mathematical model of causality between two measured objects. We have slightly modified the well-known Kolmogorovian probability model. In particular, we use the horizontal sum of set $\sigma$-algebras instead of their direct product.

Suggested Citation

  • M. Bohdalov'a & M. Kalina & O. N'an'asiov'a, 2018. "Granger causality on horizontal sum of Boolean algebras," Papers 1810.01654, arXiv.org.
    • Handle: RePEc:arx:papers:1810.01654
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1810.01654
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Granger, C. W. J., 1980. "Testing for causality : A personal viewpoint," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 329-352, May.
    2. 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.
    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. Loperfido, Nicola, 2010. "A note on marginal and conditional independence," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1695-1699, December.
    2. Fali Huang & Myoung-Jae Lee, 2010. "Dynamic treatment effect analysis of TV effects on child cognitive development," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(3), pages 392-419.
    3. Bentour, El Mostafa, 2013. "Oil Prices, Drought Periods and Growth Forecasts in Morocco," MPRA Paper 52892, University Library of Munich, Germany.
    4. Cathy W. S. Chen & Sangyeol Lee, 2017. "Bayesian causality test for integer-valued time series models with applications to climate and crime data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 797-814, August.
    5. Jose Perez-Montiel & Carles Manera Erbina, 2019. "Investment Sustained by Consumption: A Linear and Nonlinear Time Series Analysis," Sustainability, MDPI, vol. 11(16), pages 1-15, August.
    6. Ruixiaoxiao Zhang & Geoffrey QP Shen & Meng Ni & Johnny Wong, 2020. "The relationship between energy consumption and gross domestic product in Hong Kong (1992–2015): Evidence from sectoral analysis and implications on future energy policy," Energy & Environment, , vol. 31(2), pages 215-236, March.
    7. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
    8. Tomaso Aste, 2019. "Cryptocurrency market structure: connecting emotions and economics," Digital Finance, Springer, vol. 1(1), pages 5-21, November.
    9. Zapata, Hector O. & Gil, Jose M., 1999. "Cointegration and causality in international agricultural economics research," Agricultural Economics, Blackwell, vol. 20(1), pages 1-9, January.
    10. Claude Diebolt & Cédric Doliger, 2005. "Becker vs. Easterlin. Education, Fertility and Growth in France after World War II," Working Papers 05-03, Association Française de Cliométrie (AFC).
    11. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 240-253, April.
    12. Robert A. Weigand, 1996. "Trading volume and firm size: A test of the information spillover hypothesis," Review of Financial Economics, John Wiley & Sons, vol. 5(1), pages 47-58, December.
    13. Gao, Wei & Cui, Wanqi & Ye, Wenna, 2017. "Directed information graphs for the Granger causality of multivariate time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 701-710.
    14. Tomaso Aste, 2019. "Cryptocurrency market structure: connecting emotions and economics," Papers 1903.00472, arXiv.org.
    15. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Stanley, H. Eugene, 2016. "Extreme risk spillover effects in world gold markets and the global financial crisis," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 55-77.
    16. Pedro Antonio Martín Cervantes & Nuria Rueda López & Salvador Cruz Rambaud, 2020. "The Effect of Globalization on Economic Development Indicators: An Inter-Regional Approach," Sustainability, MDPI, vol. 12(5), pages 1-18, March.
    17. Wang, Lu & Ma, Feng & Niu, Tianjiao & Liang, Chao, 2021. "The importance of extreme shock: Examining the effect of investor sentiment on the crude oil futures market," Energy Economics, Elsevier, vol. 99(C).
    18. Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
    19. Jonathan B. Hill, 2005. "Causation Delays and Causal Neutralization up to Three Steps Ahead: The Money-Output Relationship Revisited," Econometrics 0503016, University Library of Munich, Germany, revised 23 Mar 2005.
    20. Ahmed Ali & Granberg Mark & Troster Victor & Uddin Gazi Salah, 2022. "Asymmetric dynamics between uncertainty and unemployment flows in the United States," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 155-172, February.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:1810.01654. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.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.