Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31917
Predicting the Lack of GDP Growth: A Logit Model for 40 Advanced and Developing Countries

Authors: Hamidou Diallo, Marianne Guille

Abstract:

This paper identifies leading triggers of deficient episodes in terms of GDP growth based on a sample of countries at different stages of development over 1994-2017. Using logit models, we build early warning systems (EWS) and our results show important differences between developing countries (DCs) and advanced economies (AEs). For AEs, the main predictors of the probability of entering in a GDP growth deficient episode are the deterioration of external imbalances and the vulnerability of fiscal position while DCs face different challenges that need to be considered. The key indicators for them are first, the low ability to pay its debts and second, their belonging or not to a common currency area. We also build homogeneous pools of countries inside AEs and DCs. For AEs, the evolution of the proportion of countries in the riskiest pool is marked first, by three distinct peaks just after the high-tech bubble burst, the global financial crisis and the European sovereign debt crisis, and second by a very low minimum level in 2006 and 2007. In contrast, the situation of DCs is characterized first by a relative stability of this proportion and then by an upward trend from 2006, that can be explained by more unfavorable socio-political environment leading to shortcomings in the fiscal consolidation.

Keywords: GDP growth, early warning system, advanced economies, developing countries.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 302

References:


[1] Gerling, K., P. Medas, T. Poghosyan, J. Farah-Yacoub, and Y. Xu, (2017), “Fiscal Crises,” IMF Working Paper No. 17/86 (Washington: International Monetary Fund).
[2] Kaminsky, G., S. Lizondo, and C. Reinhart, (1998), “Leading Indicators of Currency Crises,” IMF Staff Papers, Vol. 45, No. 1, pp. 1–48.
[3] Baldacci, E., I. Petrova, N. Belhocine, G. Dobrescu, and S. Mazraani, (2011), “Assessing Fiscal Stress,” IMF Working Paper No. 11/100 (International Monetary Fund).
[4] Bruns M. & Poghosyan T., 2018. "Leading indicators of fiscal distress: evidence from extreme bounds analysis," Applied Economics, Taylor & Francis Journals, vol. 50(13), pages 1454-1478, March.
[5] Berti, K., M. Salto, M. Lequien (2013) “An early‐detection index of fiscal stress for EU countries”, European Economy. Economic Papers. 475. Brussels.
[6] Cerovic, S. and Gerling, K., Hodge, A. and Medas, P., (2018), “Predicting Fiscal Crises”, August 2018, IMF Working Paper No. 18/181.
[7] Kaminky, Graciela and Pablo Vega-Garcia (2016), “Systemic and Idiosyncratic Sovereign Debt Crises”, Journal of the European Economic Association, 14 (1): 80–114.
[8] Bassanetti, A., Cottarelli, C. and Presbitero, A. (2016), “Lost and found: market access and public debt dynamics”, IMF Working Paper, no. 16/256, December.
[9] Sumner, S. and Berti, K., (2017), “A Complementary Tool to Monitor Fiscal Stress in European Economies,” EC Discussion Paper, 49 (June).
[10] Benassy-Quere, A. and Coupet, M., (2005), "On the Adequacy of Monetary Arrangements in Sub-Saharan Africa". The World Economy, Vol. 28, No. 3, pp. 349-373, March 2005.
[11] Bordo, M D. Meissner, C M. (2016), “Fiscal and Financial Crises”, NBER Working Paper No. 22059
[12] Detragiache, E. and Spilimbergo, A., (2001), “Crises and Liquidity: Evidence and Interpretation”, January 2001, IMF Working Paper No. 01/2.
[13] Chakrabarti, A., and H. Zeaiter, (2014), “The Determinants of Sovereign Default: A Sensitivity Analysis,” International Review of Economics and Finance, 33, pp. 300-318.
[14] Reinhart, C. and K. Rogoff, (2009), “This time is different: Eight centuries of financial folly”, Princeton, NJ: Princeton University Press.
[15] Reinhart, C. and K. Rogoff, (2011). “The Forgotten History of Domestic Debt”, Economic Journal 121 (552), pp. 319-350.
[16] Bruns, M. and T. Poghosyan, (2018), “Leading Indicators of Fiscal Distress: Evidence from the Extreme Bound Analysis,” Applied Economics, 50(13), pp. 1454-78.
[17] Manasse, P., N. Roubini, and A. Schimmelpfennig, (2003), “Predicting Sovereign Debt Crises,” IMF Working Paper No. 03/221 (International Monetary Fund).
[18] Candelon B., Dumitrescu, E-I., Hurlin, C., (2012), “How to evaluate an Early Warning System? Towards a Unified Statistical Framework for Assessing Financial Crises Forecasting Methods”, IMF Economic Review, 2012, vol. 60, issue 1, 75-113.
[19] World Bank Group, DataBank, World Development Indicators, https://databank.worldbank.org/source/world-development-indicators
[20] Diallo, Hamidou, (2018), “Regional heterogeneities and macroeconomic policies in a monetary area: the case of WAEMU”, PhD thesis, Université Paris 2 Panthéon Assas, LEMMA.
[21] Basel Committee on Banking Supervision, (2005), "Studies on the Validation of Internal Rating Systems", working paper no.14, Bank for International Settlements.
[22] Engelmann, B., Hayden, E. and Tasche, D., (2003), "Testing rating accuracy?" Risk No. 16, pp. 82-86.
[23] Renault, O., and De Servigny, A., (2004), “The Standard & Poor's Guide to Measuring and Managing Credit Risk”, 1st ed. McGraw-Hill, 2004.
[24] Stein, R. M., (2005), "The relationship between default prediction and lending profits: integrating ROC analysis and loan pricing", Journal of Banking & Finance, Vol. 29, pp. 1213-1236.