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On Measuring Country Risk: A new System Modelling Approach - La misura del rischio paese: un nuovo approccio system modelling

Author

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  • Chopra, Parvesh K.

    (International Centre for Development and Performance Management (ICDPM))

  • Kanji, Gopal K.

    (Kanji Quality Culture Ltd.)

Abstract

Country risk is of increasing importance in the evaluation of overseas investments, international trade flows, foreign direct investments and volatility and predictability in stock market returns. A clear understanding of the concept, measurement and management of the level and magnitude of country risk is imperative for a global investor since the overseas operating profits and the value of assets can be adversely affected. All previous conceptualisations, techniques and methods of measuring the country risk are ad hoc, narrow, partial in approach and suffer from various drawbacks. Also, country risk measures remain notoriously unreliable in predicting unfavourable changes in operating conditions and relatively little time has been given to addressing methodological issues involved in the conceptualisation, assessment and management of country risk. However, in this paper we introduce a new conceptualisation and measurement of country risk. Based on a holistic and system modelling approach, this paper constructs a latent variable structural equations model to measure country risk within certain boundaries of the whole system. The model decomposes the country risk index into political risk index, financial risk index, economic risk index, and operational risk index. This paper describes the general process used to create country risk assessment measure and examines the degree of association among various risk measures. - Il rischio paese sta assumendo una rilevanza crescente sulla valutazione degli investimenti all’estero, dei flussi di commercio internazionale, degli investimenti diretti esteri, della volatilità e prevedibilità dei rendimenti azionari. Una chiara comprensione, la misurazione e la gestione del rischio paese sono imperativi per un investitore globale poiché tale rischio può influenzare negativamente i profitti e il valore degli attivi di operazioni all’estero. Ad oggi vengono adottate concettualizzazioni, tecniche e metodi di misurazione del rischio paese ad hoc, che presentano numerosi inconvenienti. Inoltre, le valutazioni del rischio paese si sono notoriamente rivelate inaffidabili nel predire modifiche sfavorevoli alle condizioni operative e, sino ad oggi, lo studio delle problematiche metodologiche inerenti la concettualizzazione, la valutazione e la gestione del rischio paese è stato trascurato. In questo lavoro viene introdotta una nuova definizione e quantificazione del rischio paese. Sulla base di un approccio olistico e system modelling viene elaborato un modello di equazioni a variabili latenti che suddivide il rischio paese in politico, finanziario, economico e operativo. Lo studio descrive anche il procedimento generale usato per definire il rischio paese ed esamina il grado di associazione tra le misure del rischio.

Suggested Citation

  • Chopra, Parvesh K. & Kanji, Gopal K., 2010. "On Measuring Country Risk: A new System Modelling Approach - La misura del rischio paese: un nuovo approccio system modelling," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 63(4), pages 479-515.
    • Handle: RePEc:ris:ecoint:0607
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    1. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
    2. Ling, Shiqing & McAleer, Michael, 2002. "NECESSARY AND SUFFICIENT MOMENT CONDITIONS FOR THE GARCH(r,s) AND ASYMMETRIC POWER GARCH(r,s) MODELS," Econometric Theory, Cambridge University Press, vol. 18(3), pages 722-729, June.
    3. Shang-Jin Wei, 2000. "How Taxing is Corruption on International Investors?," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 1-11, February.
    4. Michael McAleer & Les Oxley, 2002. "The Econometrics of Financial Time Series," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 237-243, July.
    5. Harvey, Campbell R. & Zhou, Guofu, 1993. "International asset pricing with alternative distributional specifications," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 107-131, June.
    6. Nath, Hiranya K., 2009. "Country Risk Analysis: A Survey of the Quantitative Methods," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 62(1), pages 69-94.
    7. Khalid Sekkat & Marie-Ange Veganzones, 2005. "Trade and foreign exchange liberalization, investment climate and FDI in the MENA," DULBEA Working Papers 05-06.RS, ULB -- Universite Libre de Bruxelles.
    8. Li, W K & Ling, Shiqing & McAleer, Michael, 2002. "Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 245-269, July.
    9. W. K. Li & Shiqing Ling & Michael McAleer, 2002. "Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 245-269, July.
    10. Ling, Shiqing & McAleer, Michael, 2002. "Stationarity and the existence of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 109-117, January.
    11. Suhejla Hoti & Michael McAleer, 2004. "An Empirical Assessment of Country Risk Ratings and Associated Models," Journal of Economic Surveys, Wiley Blackwell, vol. 18(4), pages 539-588, September.
    12. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    13. Ghosh, Baidyanath N. & Li, Eric A.L., 2009. "Macroeconomic Vulnerability and Investment Risks in the Middle East and North Africa Region," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 62(1), pages 1-39.
    14. Gangemi, Michael A. M. & Brooks, Robert D. & Faff, Robert W., 2000. "Modeling Australia's country risk: a country beta approach," Journal of Economics and Business, Elsevier, vol. 52(3), pages 259-276.
    15. Aktham I. Maghyereh & Haitham A. Al-Zoubi, 2006. "Value-at-risk under extreme values: the relative performance in MENA emerging stock markets," International Journal of Managerial Finance, Emerald Group Publishing, vol. 2(2), pages 154-172, July.
    16. Gopal Kanji & Parvesh Chopra, 2007. "Poverty as a System: Human Contestability Approach to Poverty Measurement," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(9), pages 1135-1158.
    17. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    18. Carrera, Jorge Eduardo & Cusolito, Ana Paula & Féliz, Mariano & Panigo, Demian, 2001. "An econometric approach to macroeconomic risk. A cross country study," MPRA Paper 7846, University Library of Munich, Germany, revised 2001.
    19. Richard Dennis & Jose A. Lopez, 2004. "Policy applications of a global macroeconomic model," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue jun11.
    20. Oetzel, Jennifer M. & Bettis, Richard A. & Zenner, Marc, 2001. "Country risk measures: how risky are they?," Journal of World Business, Elsevier, vol. 36(2), pages 128-145, July.
    21. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    1. Chopra, Parvesh K., 2015. "Country Risk: A Theoretical and Empirical Analysis with Special Reference to Northern African Economies - Il rischio paese: un’analisi teorica e empirica con particolare riferimento ai paesi del Nord ," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 68(1), pages 81-137.

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    More about this item

    Keywords

    Country Risk; System Modelling Approach; Kanji-Chopra Country Risk Model; Political Risk; Economic Risk; Financial Risk; Systemic;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity

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