Leading Indicators of Fiscal Distress: Evidence from the Extreme Bound Analysis
February 15, 2016
Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate
Summary
Early warning systems (EWS) are widely used for assessing countries’ vulnerability to fiscal distress. Most EWS employ a specific set of only fiscal leading indicators predetermined by the researchers, which casts doubt on their robustness. We revisit this issue by using the Extreme Bound Analysis, which allows identifying robust leading indicators of fiscal distress from a large set. Consistent with the theoretical predictions of latest generation crisis models, we find that both fiscal (e.g., fiscal balance, foreign exchange debt) and non-fiscal leading indicators (e.g., output, FX reserves, current account balance, and openness) are robust. In addition, we find that a fiscal vulnerability indicator based on fiscal and non-fiscal leading indicators offers a 29% gain in predictive power compared to a traditional one based on fiscal leading indicators only. It also has good predictive power out of sample, with 78 percent of crises predicted correctly and only 34 percent false alarms issued for the period 2008–15. This suggests that both fiscal and non-fiscal leading indicators should be taken into account when assessing country’s vulnerability to fiscal distress.
Subject: Cyclical indicators, Economic growth, External debt, Fiscal policy, Fiscal stance, Foreign exchange, Public debt
Keywords: bond yield, current account, Cyclical indicators, debt to GDP ratio, dependent variable, early warning systems, EBA regression, estimation result, extreme bound analysis, fiscal distress, Fiscal stance, foreign exchange debt, FX reserve, GDP ratio, Global, leading indicators of financial crises, robust leading indicators, standard error, tolerance indicator, WP
Pages:
37
Volume:
2016
DOI:
Issue:
028
Series:
Working Paper No. 2016/028
Stock No:
WPIEA2016028
ISBN:
9781475594799
ISSN:
1018-5941





