Back Matter

Julian Chow, Florence Jaumotte, Seok Park, and Yuanyan Zhang
Published Date:
September 2016
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    Appendix 1. Methodology for Corporate Sensitivity Analysis19

    A. Estimating the share of corporate external debt

    As the breakdown of firm-by-firm foreign currency borrowing is not available through Orbis and other in-house databases, such debts are approximated, at the aggregate level, by external debt statistics and other sources as follows:

    Sources of Corporate BorrowingData
    Foreign currency debtIMF’s Vulnerability Exercise Securities database
    Domestic banksBanking system data from “Financial Soundness Indicators”
    Domestic capital marketsBloomberg

    The share of aggregate corporate external debt to total corporate debt is estimated as:

    B. Estimating the impact of FX movements

    FX movement impacts firms through two channels:

    Interest payments due in the current year

    Exchange rate depreciation would increase the interest burden from FX debts. This is estimated as:

    Share of External Debt × Borrowing Cost × Total Debt × [(Share of USD Debt × Nominal Exch. Rate Depreciation vs. USD) + (Share of EUR Debt × Nominal Exch. Rate Depreciation vs. EUR)]

    The proportion of debts denominated in USD and EUR is approximated by the share of USD and EUR bonds from Dealogic.

    Revaluation of loan and bond principal20

    In the absence of information on the maturity structure of bank loans, we cannot compute realized FX loss from principal revaluation for the current period; instead, we present the impact on the total stock of debt including loss to be materialized in the future periods.

    FX loss on foreign currency debt principal is computed as:

    Share of External Debt x Total Debt x [(Share of USD Debt x Nominal Exch. Rate Depreciation vs. USD) + (Share of EUR Debt x Nominal Exch. Rate Depreciation vs. EUR)]

    We compare FX debt to total income ratio before and after an FX shock. First, we compute ratios at the firm level and then we aggregate to the country level by weighting the ratios by the size of assets to account for the relative importance of large firms.

    C. Accounting for Natural Hedges

    FX losses from interest expense and revaluation of foreign currency debt principal are offset by FX gains from overseas earnings, computed as:

    Share of Foreign Sales x EBIT x [(Share of USD Revenue x Nominal Exch. Rate Depreciation vs. USD) + (Share of EUR Revenue x Nominal Exch. Rate Depreciation vs. EUR)]

    Assumptions underlying this estimation are:

    • Foreign sales are assumed to be in foreign currencies.

    • The share of FX revenues is derived from the country trade weights. USD share of income refers to share of income earned through trade with the United States and China; EUR share refers to trade proceeds with euro area, and the remaining FX proceeds are assumed to be denominated in other currencies. This approach to account for natural hedges has several caveats. First, trade with countries other than the United States, China, and euro area maybe invoiced in USD (e.g., Turkey’s trade with the Middle East [one-fifth of total trade]); and second, we fail to account for dollarization transactions which should be considered natural hedge even though revenues are from domestic sources.

    • The multiplication by EBIT (operating profit) effectively takes into account foreign currency costs as it assumes that the share of these costs are in proportion to foreign currency incomes.

    It is worth noting that the effectiveness of natural hedges is an approximation as it may fall short of expectations. Past episodes have demonstrated that overseas revenues declined in tandem with the depreciating currencies during turbulent periods.

    D. Accounting for Financial Hedges

    Currency hedging of foreign currency debts could also mitigate potential FX losses. Offset from financial hedging of foreign currency debt service is computed as:

    Hedge Ratio x FX losses from FX debt interest

    As information on financial hedging is sparse, this analysis assumes that at least 50 percent of foreign currency debts are hedged, on aggregate basis.

    E. Estimating Nonperforming Loans and Banks’ Buffers

    The corporate nonperforming loans were projected from the aftershock corporate debt at risk owed to banks as follows:

    Corporate Nonperforming Loan After Shock = Probability of Default x Corporate Loan at Risk x Loss Given Default

    • Probability of default: With debt at risk defined as those with ICR below 1.5, the probability of default can be approximated as 15 percent.21

    • Corporate loan at risk: This is derived from the scaling of the sample total debt and aftershock debt at risk by the amount of total lending to the nonfinancial corporate sector.

    • Loss given default: This is derived from an average of the World Bank’s loss given default rate for each country22 and 45 percent. 23

    The aftershock loss absorbing buffers can be computed as:

    (Tier 1 Capital + Loan Loss Reserves - Existing Stock of Nonperforming Loans - Projected Increase in Nonperforming Loans)/ Risk-Weighted Assets


      Bénétrix, A. S., P. R.Lane, and J. C.Shambaugh.2015. “International Currency Exposures, Valuation Effects and the Global Financial Crisis.Journal of International Economics96 (July): S98S109.

      Catão, L. A., and G. M.Milesi-Ferretti.2014. “External Liabilities and Crises.Journal of International Economics94 (1): 1832.

      Ghosh, M. A. R., M. J. D.Ostry, and M. S.Qureshi.2014. Exchange Rate Management and Crisis Susceptibility: A Reassessment.Washington: International Monetary Fund.

      International Monetary Fund. 2014a. Annual Report on Exchange Arrangements and Exchange Restrictions.Washington.

      International Monetary Fund. 2014. Global Financial Stability Report.Washington, April.

      International Monetary Fund. 2015. Global Financial Stability Report.Washington, April.

      International Monetary Fund. and World Bank.2015. Quarterly External Debt Statistics.

      Lane, P. R., and G. M.Milesi-Ferretti.2007. “The External Wealth of Nations Mark II: Revised and Extended Estimates of Foreign Assets and Liabilities, 1970–2004.Journal of international Economics73 (2): 22350.

      Lane, P. R., and J. C.Shambaugh.2010. “Financial Exchange Rates and International Currency Exposures.The American Economic Review51840.

    From a general equilibrium perspective, an appreciation of the USD that is driven by stronger U.S. economic prospects—as is currently the case—may well have a net positive growth impact on its trading partners (through the external demand effect). And this effect would be stronger for exporters (to the United States) that experience a depreciation of their currency vis-à-vis the USD or in real effective terms more generally.

    In contrast, the 1980–85 appreciation episode was driven by a tightening of monetary policy aimed at fighting inflation and by increasing fiscal deficits. In the Global Financial Crisis, the strengthening of the USD had more to do with capital flight to safety in a context of heightened risk aversion and was quickly reversed.

    AE versus EMDE classification follows IMF’s World Economic Outlook Appendix. This note covers 139 EMDE sample countries, including 53 lower-income countries and 27 fuel exporters. AEs excludes the United States in this note, if it is not stated otherwise.

    The list of EM crises in Catão and Milesi-Ferretti (2014) during 1995–2001 includes Argentina (1995, 2001), Mexico (1995), Jordan (1997), Thailand (1997), Indonesia (1998), Pakistan (1998), Ukraine (1998), Brazil (1999, 2001), Ecuador (1999), and Turkey (2000).

    Among the EM countries which experienced an external crisis during the 1995 episode, Argentina, Jordan, Thailand, Indonesia, and Brazil were classified as belonging to the “tied” group.

    In Poland, the large negative net international investment position is driven by significant inflows of foreign direct investment; moreover, a high share of relatively stable intercompany debt is a mitigating factor. According to the Bank Negara Malaysia, there are a number of mitigating factors in Malaysia, including deep-pocketed domestic investors and the encouragement of hedging by Bank Negara Malaysia.

    According to the Hungarian authorities, a lot of the dollar liabilities are hedged, including for the government.

    There is a significant fraction of debt assets in other currencies for Malaysia (21 percent) and China (12 percent).

    While the USD started to appreciate gradually in 2011, most of the USD appreciation in real effective terms took place after 2013. Moreover, debt repayments and contracting of new debt (at different exchange rates) are presumably small relative to the existing stock over a 15-month period, which simplifies the calculations.

    According to the Hungarian authorities, a lot of the dollar liabilities are hedged, including for the government.

    New corporate bond issuance rose 32 percent in 2014, with Asia leading other regions. Issuance in foreign currency amounted to two-thirds of total issuance over the last five years, growing at a compounded annual rate of 21 percent during the period. Sectors such as industry, utilities, and energy accounted for three-quarters of the new debt in 2014. In Latin America and Europe, Middle East, and Africa, the energy sector comprised the largest share of issuance, while in Asia, the lion’s share came from industries. Along with the rise in corporate bond issuance, borrowing from banks has also increased.

    The effectiveness of these financial hedges are also a concern as some derivative hedges are undertaken for the short term, and derivative instruments with knock-out features will terminate once the exchange rate depreciates beyond certain thresholds, thus rendering the hedge worthless.

    The sectoral analysis is based on bond data from Dealogic.

    EBIT (also known as operating profit/loss) is used as a measure of earnings instead of EBITDA (earnings before interest, taxation, depreciation, and amortization) to account for the need for investment and replacement of assets.

    Debt at risk is defined as debt owed by firms where the ICR is below 1.5. An ICR of less than 1 implies that the firm is not generating sufficient revenues to service its debt without making adjustments, such as reducing operating costs, drawing down its cash reserves, or borrowing more. This analysis uses an ICR threshold of 1.5 times to take into account the potential vulnerabilities to funding risks, in addition to earnings risks, that could emanate in a scenario where funding liquidity thins, particularly during times of heightened global risk aversion. This is also a benchmark used widely by analysts as an early warning signal as firms with ICR below 1 may already be in distress.

    They include Argentina, Brazil, Bulgaria, Chile, China, Hungary, India, Indonesia, Malaysia, Mexico, Peru, the Philippines, Poland, Russia, South Africa, and Thailand. Turkey is excluded due to the lack of a representative sample of firm-level data.

    We recognize that some currencies are pegged, or are in a heavily managed regime (e.g., the long-standing currency board arrangement in Bulgaria), which reduces the likelihood of such a scenario. This sensitivity analysis examines what could potentially happen in a very adverse scenario.

    A high share of Brazil’s corporate sector FX liabilities is currently hedged, though one cannot be certain of the hedge effectiveness throughout the tenor of the FX debt.

    This follows the methodology used in the analysis of emerging market corporate vulnerability in the April 2014 Global Financial Stability Report (IMF, 2014).

    In line with IFRS 13 (fair valuation of liabilities).

    Based on Moody’s default probability for corporate debts with ICR of 1.5 for a three-year horizon from 1970–2012.

    See Loss given default is computed as 1-Recovery Rate.

    Based on the Bank for International Settlements’ loss given default for senior claims on firms, sovereigns, and banks not secured by recognized collateral.

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