American Journal of Theoretical and Applied Statistics

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Cross-Country Spillovers in East Africa: A Global Vector Autoregressive Analysis

Received: 20 March 2015    Accepted: 11 April 2015    Published: 21 April 2015
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Abstract

The recent financial crisis raises important issues about transmission of financial shocks across borders. This paper uses the global vector autoregressive model as developed in Dees, di Mauro, Pesaran and Smith (2007) to study cross-country interlinkages among East African countries. The paper uses trade weights to capture the importance of the foreign variables. Results reveal that there is no evidence of strong international linkages across countries in East Africa. Results also reveal that the variable in which a shock is simulated is the main channel through which-in the shortrun-shocks are transmitted, while the contribution of other variables becomes more important over longer horizons.

DOI 10.11648/j.ajtas.20150403.18
Published in American Journal of Theoretical and Applied Statistics (Volume 4, Issue 3, May 2015)
Page(s) 125-137
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Global VAR, Linkages, VARY*, Spillovers, Linkages

References
[1] Dees S., di Mauro F., Pesaran M. H. and Smith L. V. (2007). ‘Exploring the international linkages of the euro area: a global VAR analysis’, Journal of Applied Econometrics 22 (1), 1-38.
[2] Elliott G., Rothenberg T. and Stock J. (1996). ‘Efficient tests for an autoregressive unit-root, Econometrica, 64, 813-836.
[3] Galesi A. and Sgherri S. (2009). ‘regional financial spillovers across Europe: a global VAR analysis, IMF working paper series, WP/09/23.
[4] Harbor I., Johansen S., Nielsen B and Rahbek A. (1998).‘Asymptotic inference on cointegrating rank in partial systems’, Journal of Business and Economic statistics 16(4), 388-399.
[5] Hiebert P. and Vansteenkiste I. (2007). ‘International trade, technological shocks and spillovers in the labor market; a GVAR analysis of the US manufacturing sector, working paper series 731, European Central Bank.
[6] Johansen S. (1992). ‘Cointegration in partial systems and the efficiency of the single-equation analysis’, Journal of Econometrics 52 (3), 389-402.
[7] Leybourne S., Kim T. and Newbold P. (2005). ‘Examination of some more powerful modifications of the Dickey-Fuller Test, Journal of time Series Analysis, Wiley Blackwell, 26 (3), 355-369.
[8] Pantula S. G., Gonzalez-Farias G. and Fuller W. A. (1994).‘ A comparison of unit-root test criteria, Journal of Business and Economic statistics, 12, 449-459.
[9] Park H. J. and Fuller W. A. (1995). ‘Alternative estimators and unit root tests for the autoregressive process’, Journal of Time series analysis 16(4), 415-429.
[10] Pesaran M. H., Schuermann T. and Weiner S. M. (2004a). ‘Modelling regional interdependencies using a global error-correcting macro-econometric model’, Journal of Business and Economic statistics 22 (2), 129-162.
[11] Pesaran M. H. and Shin Y. (1998). ‘Generalized impulse response analysis in Linear multivariate models’, Economics Letters 58 (1), 17-29.
[12] Pesaran M. H., Shin Y. and Smith R. J. (2000). ‘Structural analysis of vector error correction models with exogeneousI(1) variables’, Journal of Econometrics 97(2), 293-343.
[13] Sims C. A. (1980). ‘Macroeconomics and Reality’, Econometrica 48 (1), 1-48.
[14] Smith L. and Galesi A. (2011).GVAR toolbox 1.1.URL www-cfap.jbs.cam.ac.uk/research/gvartoolbox/index.html.
[15] Vansteenkiste I. (2007). ‘Regional housing market spillovers in the US-lessons fron regional divergences in a common monetary policy setting, working paper series 708, European Central Bank.
Author Information
  • Pan African University, Institute of basic Sciences, Technology and Innovation, Department of Mathematics, Nairobi, Kenya

  • University of Ibadan, Department of statistics, Ibadan, Nigeria

  • University of Nairobi, School of Mathematics, Nairobi, Kenya

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  • APA Style

    Daniel Njoora, Olusanya E. Olubusoye, Patrick Weke. (2015). Cross-Country Spillovers in East Africa: A Global Vector Autoregressive Analysis. American Journal of Theoretical and Applied Statistics, 4(3), 125-137. https://doi.org/10.11648/j.ajtas.20150403.18

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    ACS Style

    Daniel Njoora; Olusanya E. Olubusoye; Patrick Weke. Cross-Country Spillovers in East Africa: A Global Vector Autoregressive Analysis. Am. J. Theor. Appl. Stat. 2015, 4(3), 125-137. doi: 10.11648/j.ajtas.20150403.18

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    AMA Style

    Daniel Njoora, Olusanya E. Olubusoye, Patrick Weke. Cross-Country Spillovers in East Africa: A Global Vector Autoregressive Analysis. Am J Theor Appl Stat. 2015;4(3):125-137. doi: 10.11648/j.ajtas.20150403.18

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  • @article{10.11648/j.ajtas.20150403.18,
      author = {Daniel Njoora and Olusanya E. Olubusoye and Patrick Weke},
      title = {Cross-Country Spillovers in East Africa: A Global Vector Autoregressive Analysis},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {4},
      number = {3},
      pages = {125-137},
      doi = {10.11648/j.ajtas.20150403.18},
      url = {https://doi.org/10.11648/j.ajtas.20150403.18},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajtas.20150403.18},
      abstract = {The recent financial crisis raises important issues about transmission of financial shocks across borders. This paper uses the global vector autoregressive model as developed in Dees, di Mauro, Pesaran and Smith (2007) to study cross-country interlinkages among East African countries. The paper uses trade weights to capture the importance of the foreign variables. Results reveal that there is no evidence of strong international linkages across countries in East Africa. Results also reveal that the variable in which a shock is simulated is the main channel through which-in the shortrun-shocks are transmitted, while the contribution of other variables becomes more important over longer horizons.},
     year = {2015}
    }
    

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    T1  - Cross-Country Spillovers in East Africa: A Global Vector Autoregressive Analysis
    AU  - Daniel Njoora
    AU  - Olusanya E. Olubusoye
    AU  - Patrick Weke
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    T2  - American Journal of Theoretical and Applied Statistics
    JF  - American Journal of Theoretical and Applied Statistics
    JO  - American Journal of Theoretical and Applied Statistics
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    EP  - 137
    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.ajtas.20150403.18
    AB  - The recent financial crisis raises important issues about transmission of financial shocks across borders. This paper uses the global vector autoregressive model as developed in Dees, di Mauro, Pesaran and Smith (2007) to study cross-country interlinkages among East African countries. The paper uses trade weights to capture the importance of the foreign variables. Results reveal that there is no evidence of strong international linkages across countries in East Africa. Results also reveal that the variable in which a shock is simulated is the main channel through which-in the shortrun-shocks are transmitted, while the contribution of other variables becomes more important over longer horizons.
    VL  - 4
    IS  - 3
    ER  - 

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