IDEAS home Printed from https://ideas.repec.org/a/agr/journl/vxxiiy2015i1(602)p15-34.html
   My bibliography  Save this article

Predicting balance of payments crises for some emerging economies

Author

Listed:
  • Archana KULKARNI

    (University of Hyderabad, Hyderabad, India)

  • Bandi KAMAIAH

    (University of Hyderabad, Hyderabad, India)

Abstract

The study aims at developing an Early Warning System for predicting balance of payments crises for 17 emerging economies, which constitute a relatively homogenous group, over the period 1975-2012. We construct an index of exchange market pressure, based on monthly depreciations of the nominal exchange rate and declines in reserves, to identify crisis episodes. To construct the index we propose a new weighting scheme using principal components analysis, as an improvement over the conventionally used precisionweighting scheme. Probit regressions are used to identify key macroeconomic indicator variables that can predict the onset of a crisis. These include the ratio of M2 to reserves, short-term debt to reserves, export growth, ratio of total reserves to external debt, change in reserves, openness and overvaluation of the real exchange rate. From alternative specifications, we identify the best model based on various accuracy measures. We use criteria such as area under the Receiver Operating Characteristic, Quadratic Probability Score, Pseudo R2 and Kuiper’s Score to evaluate model performance. Empirical results show the warning system exhibits a high degree of accuracy and performs well. The variables identified show significant ability to signal vulnerability of the external sector of the economy. Policymakers can use the early warning system as the core of a larger set of variables on their radar to take pre-emptive measures to avoid crises or dampen their effects.

Suggested Citation

  • Archana KULKARNI & Bandi KAMAIAH, 2015. "Predicting balance of payments crises for some emerging economies," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(602), S), pages 15-34, Spring.
  • Handle: RePEc:agr:journl:v:xxii:y:2015:i:1(602):p:15-34
    as

    Download full text from publisher

    File URL: http://store.ectap.ro/articole/1054.pdf
    Download Restriction: no

    File URL: http://www.ectap.ro/articol.php?id=1054&rid=118
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrew Berg & Eduardo Borensztein & Catherine Pattillo, 2005. "Assessing Early Warning Systems: How Have They Worked in Practice?," IMF Staff Papers, Palgrave Macmillan, vol. 52(3), pages 1-5.
    2. Bertrand Candelon & Elena-Ivona Dumitrescu & Christophe Hurlin, 2012. "How to Evaluate an Early-Warning System: Toward a Unified Statistical Framework for Assessing Financial Crises Forecasting Methods," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 60(1), pages 75-113, April.
    3. Selen CAKMAKYAPAN & Atilla GOKTAS, 2013. "A Comparison Of Binary Logit And Probit Models With A Simulation Study," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 2(1), pages 1-17, JULY.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rakesh Padhan & K. P. Prabheesh, 2019. "Effectiveness Of Early Warning Models: A Critical Review And New Agenda For Future Direction," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(4), pages 457-484.

    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. repec:agr:journl:v:1(602):y:2015:i:1(602):p:15-34 is not listed on IDEAS
    2. Honda, Jiro & Tapsoba, René & Issifou, Ismael, 2022. "When do we repair the roof? Insights from responses to fiscal crisis early warning signals," International Economics, Elsevier, vol. 172(C), pages 349-367.
    3. Krzysztof Biegun & Jacek Karwowski & Piotr Luty, 2021. "How Effective is Macroeconomic Imbalance Procedure (MIP) in Predicting Negative Macroeconomic Phenomena?," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 822-837.
    4. Ryota Nakatani, 2017. "The Effects of Productivity Shocks, Financial Shocks, and Monetary Policy on Exchange Rates: An Application of the Currency Crisis Model and Implications for Emerging Market Crises," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(11), pages 2545-2561, November.
    5. Ali Ari & Raif Cergibozan, 2016. "A Comparison of Currency Crisis Dating Methods: Turkey 1990-2014," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 12(3), pages 19-37.
    6. Rakesh Padhan & K. P. Prabheesh, 2019. "Effectiveness Of Early Warning Models: A Critical Review And New Agenda For Future Direction," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(4), pages 457-484.
    7. Pablo Hernández de Cos & Enrique Moral-Benito & Gerrit B. Koester & Christiane Nickel, 2014. "Signalling fiscal stress in the euro area: A country-specific early warning system," Working Papers 1418, Banco de España.
    8. Wang, Peiwan & Zong, Lu, 2023. "Does machine learning help private sectors to alarm crises? Evidence from China’s currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    9. Carsten Detken & Olaf Weeken & Lucia Alessi & Diana Bonfim & Miguel M. Boucinha & Christian Castro & Sebastian Frontczak & Gaston Giordana & Julia Giese & Nadya Jahn & Jan Kakes & Benjamin Klaus & Jan, 2014. "Operationalising the countercyclical capital buffer: indicator selection, threshold identification and calibration options," ESRB Occasional Paper Series 05, European Systemic Risk Board.
    10. Ari, Ali & Cergibozan, Raif, 2018. "Currency crises in Turkey: An empirical assessment," Research in International Business and Finance, Elsevier, vol. 46(C), pages 281-293.
    11. Ari, Ali, 2012. "Early warning systems for currency crises: The Turkish case," Economic Systems, Elsevier, vol. 36(3), pages 391-410.
    12. Frankel, Jeffrey & Saravelos, George, 2012. "Can leading indicators assess country vulnerability? Evidence from the 2008–09 global financial crisis," Journal of International Economics, Elsevier, vol. 87(2), pages 216-231.
    13. Liu, Chang & Lin, Boqiang, 2020. "Is increasing-block electricity pricing effectively carried out in China? A case study in Shanghai and Shenzhen," Energy Policy, Elsevier, vol. 138(C).
    14. Hyeongwoo Kim & Wen Shi & Hyun Hak Kim, 2020. "Forecasting financial stress indices in Korea: a factor model approach," Empirical Economics, Springer, vol. 59(6), pages 2859-2898, December.
    15. Marie Bessec, 2019. "Revisiting the transitional dynamics of business cycle phases with mixed-frequency data," Econometric Reviews, Taylor & Francis Journals, vol. 38(7), pages 711-732, August.
    16. Ron Wallace, 2017. "The Signature of Risk: Agent-based Models, Boolean Networks and Economic Vulnerability," Economic Thought, World Economics Association, vol. 6(1), pages 1-15, March.
    17. Cipollini, A. & Kapetanios, G., 2009. "Forecasting financial crises and contagion in Asia using dynamic factor analysis," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 188-200, March.
    18. Matthieu Bussière, 2013. "Balance of payment crises in emerging markets: how early were the ‘early’ warning signals?," Applied Economics, Taylor & Francis Journals, vol. 45(12), pages 1601-1623, April.
    19. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
    20. Mohammad Karimi & Marcel‐Cristian Voia, 2019. "Empirics of currency crises: A duration analysis approach," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 428-449, July.
    21. Davis, E. Philip & Karim, Dilruba, 2008. "Comparing early warning systems for banking crises," Journal of Financial Stability, Elsevier, vol. 4(2), pages 89-120, June.

    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:agr:journl:v:xxii:y:2015:i:1(602):p:15-34. 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: Marin Dinu (email available below). General contact details of provider: https://edirc.repec.org/data/agerrea.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.