IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/56433.html
   My bibliography  Save this paper

Tests de G-causalité et spécification d’un modèle économétrique: Application sur un panel sectoriel marocain
[G-causality tests and specification of an econometric model: Evidence form Sectoral Moroccan panel]

Author

Listed:
  • Ghassan, Hassan B.
  • ElHafidi, Miloud

Abstract

The paper aims to use the Granger causality to deduce the structure of recursive model. Manipulating data from five sectors of Moroccan economy we form causal chain between endogenous variables to build a recursive system. The findings exhibit two group, the first one consists of agriculture, agro-industry and manufacturing sectors where the investment effort determines the balance trade and influences the cash-flow level. Meanwhile, in the second group formed by energy and mines sectors, the balance trade determines the investment effort and influences the cash-flow. The Granger causality justifies the modeling of the system. But, we cannot avoid ex-post the causality and exogeneity tests for the predetermined endogenous variables as Hausman and Holly tests. There tests are running once the model is estimated.

Suggested Citation

  • Ghassan, Hassan B. & ElHafidi, Miloud, 1999. "Tests de G-causalité et spécification d’un modèle économétrique: Application sur un panel sectoriel marocain [G-causality tests and specification of an econometric model: Evidence form Sectoral Mor," MPRA Paper 56433, University Library of Munich, Germany, revised 13 Jan 2000.
    • Handle: RePEc:pra:mprapa:56433
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/56433/1/MPRA_paper_56433.PDF
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jean-Marie Dufour & Eric Renault, 1998. "Short Run and Long Run Causality in Time Series: Theory," Econometrica, Econometric Society, vol. 66(5), pages 1099-1126, September.
    2. Pierce, David A. & Haugh, Larry D., 1977. "Causality in temporal systems : Characterization and a survey," Journal of Econometrics, Elsevier, vol. 5(3), pages 265-293, May.
    3. Larry D. Haugh & David A. Pierce, 1977. "Causality in temporal systems: characterizations and a survey," Special Studies Papers 87, Board of Governors of the Federal Reserve System (U.S.).
    4. Clive, W.J. & Lin, Jin-Lung, 1995. "Causality in the Long Run," Econometric Theory, Cambridge University Press, vol. 11(3), pages 530-536, June.
    5. Hsiao, Cheng, 1982. "Autoregressive modeling and causal ordering of economic variables," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 243-259, November.
    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. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    8. Granger, C. W. J., 1988. "Some recent development in a concept of causality," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 199-211.
    9. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-552, September.
    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. Andrea Silvestrini & David Veredas, 2008. "Temporal Aggregation Of Univariate And Multivariate Time Series Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 22(3), pages 458-497, July.
    2. Bragoudakis Zacharias G. & Zombanakis George A., 2017. "Earning a Peace Dividend in a Crisis Environment: The Greek Case," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 23(3), pages 1-15, August.
    3. McCrorie, J. Roderick & Chambers, Marcus J., 2006. "Granger causality and the sampling of economic processes," Journal of Econometrics, Elsevier, vol. 132(2), pages 311-336, June.
    4. Al-Sadoon, Majid M., 2014. "Geometric and long run aspects of Granger causality," Journal of Econometrics, Elsevier, vol. 178(P3), pages 558-568.
    5. Zhao, Xiaoli & Ma, Qian & Yang, Rui, 2013. "Factors influencing CO2 emissions in China's power industry: Co-integration analysis," Energy Policy, Elsevier, vol. 57(C), pages 89-98.
    6. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2016. "Testing for Granger causality with mixed frequency data," Journal of Econometrics, Elsevier, vol. 192(1), pages 207-230.
    7. Breitung, Jörg & Swanson, Norman Rasmus, 1998. "Temporal aggregation and causality in multiple time series models," SFB 373 Discussion Papers 1998,27, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    8. Dufour, Jean-Marie & Pelletier, Denis & Renault, Eric, 2006. "Short run and long run causality in time series: inference," Journal of Econometrics, Elsevier, vol. 132(2), pages 337-362, June.
    9. Nidhal Mgadmi & Houssem Rachdi & Hichem Saidi & Khaled Guesmi, 2019. "On the Instability of Tunisian Money Demand: Some Empirical Issues with Structural Breaks," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(1), pages 153-165, March.
    10. Jonathan B. Hill, 2007. "Efficient tests of long-run causation in trivariate VAR processes with a rolling window study of the money-income relationship," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 747-765.
    11. Utku Utkulu & Durmus Özdemir, 2005. "Does Trade Liberalization Cause a Long Run Economic Growth in Turkey," Economic Change and Restructuring, Springer, vol. 37(3), pages 245-266, September.
    12. Jose Sidaoui & Carlos Capistran & Daniel Chiquiar & Manuel Ramos-Francia, 2010. "On the predictive content of the PPI on CPI inflation: the case of Mexico," BIS Papers chapters, in: Bank for International Settlements (ed.), Monetary policy and the measurement of inflation: prices, wages and expectations, volume 49, pages 249-257, Bank for International Settlements.
    13. David Greasley & Les Oxley, 2010. "Cliometrics And Time Series Econometrics: Some Theory And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 24(5), pages 970-1042, December.
    14. 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.
    15. Phipps, Tim, 1982. "Farmland Prices and the Return to Land: An Application of Causality Testing," 1982 Annual Meeting, August 1-4, Logan, Utah 279162, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. S. Gurcan Gulen, 1996. "Is OPEC a Cartel? Evidence from Cointegration and Causality Tests," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 43-57.
    17. Allan Fels & Tran Van Hoa, 1981. "Causal Relationships in Australian Wage Inflation and Minimum Award Rates," The Economic Record, The Economic Society of Australia, vol. 57(1), pages 23-34, March.
    18. Götz, Thomas B. & Hecq, Alain & Smeekes, Stephan, 2016. "Testing for Granger causality in large mixed-frequency VARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 418-432.
    19. Jonathan B. Hill, 2004. "Causation Delays and Causal Neutralization for General Horizons: The Money-Output Relationship Revisited," Econometrics 0402002, University Library of Munich, Germany, revised 23 Mar 2005.
    20. Yazdanpanah, Ahmad, 1994. "The impact of oil price on food security in the Algeria, Iran, and Saudi Arabia: cointegration, vector-error correction model, dynamics, and causality analysis," ISU General Staff Papers 1994010108000011661, Iowa State University, Department of Economics.

    More about this item

    Keywords

    G-Causality; Holly Exogeneity Test; Specification; Sectorial; Morocco.;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • F4 - International Economics - - Macroeconomic Aspects of International Trade and Finance
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior

    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:pra:mprapa:56433. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.