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Heterogeneity in the impact of risk on local currency borrowing

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Abstract

This paper uses quarterly public sector debt data for 19 countries from 2008 to 2021 to examine the relationship between inflation, credit, and currency risk with local currency borrowing, and if it is unique to specific subsamples. We find significant heterogeneity in risk correlations with borrowing across both high and low local currency borrowers, and monetary union status. Inflation risk is found to have a significant negative correlation for low non-EMU borrowers, largely made up of emerging markets, supporting the link between inflation volatility and countries who historically had difficulty borrowing in local currency. These significant effects are persistent into future periods. Heterogeneous correlations suggests unique links between risk measures and local currency borrowing for emerging markets and other subgroups, affecting potential policy discussions for shifting portfolios toward domestic currency.

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Data availability

The authors declare that the data supporting the findings of this study is available publically through various sources. Local currency debt data is available through the Quarterly Public Sector Database published jointly by the IMF and the World Bank at https://www.worldbank.org/en/programs/debt-statistics/statistics. Inflation data for countries is available by the World Bank Global Inflation Database published by the World Bank at https://www.worldbank.org/en/research/brief/inflation-database. OECD country inflation data is published by OECD and available at https://data.oecd.org/price/inflation-cpi.htm. Non-EU government bond yield data is available through the International Finance Statistics Database published by the IMF at https://data.imf.org/?sk=4c514d48-b6ba-49ed-8ab9-52b0c1a0179b. EU government bond yield data is published by the OECD and available at https://data.oecd.org/interest/long-term-interest-rates.htm. Exchange rate observation data is published by the Bank for International Settlements and available at https://www.bis.org/statistics/xrusd.htm?m=2675. GDP data is available by the Quarterly National Accounts published by the OECD at https://stats.oecd.org/Index.aspx?DataSetCode=QNA.

Notes

  1. Eichengreen et al. (2005), Hausmann and Panizza (2003), and more recently Ogrokhina and Rodriguez (2018) find little significant relationship between the share of external debt denominated in local currency and the level of volatility in inflation.

  2. Du and Schreger (2016) find that local currency credit spreads have lower means and are less sensitive to global shocks than foreign currency debt.

  3. USA’s and average OECD country data is used as the risk-free benchmarks.

  4. Appendix 1 shows varying levels of country-specific risk measures and local currency debt measures between partitioned groups for both non-EMU and EMU samples.

  5. A standard measure in literature. See, for instance, Longstaff et al. (2011), Ang and Longstaff (2013), Beirne and Fratzscher (2013).

  6. Credit risk and currency risk’s relevance to local currency borrowing is noted by Du and Schreger (2016), as they find the size of the local currency debt spread over the risk-free debt depends on credit and currency risk.

  7. Based on Jorda (2005).

  8. Studies such as Lee (2021) have shown that the risk premium present in LC debt is larger when the exchange rate is more volatile, therefore hampering economies from borrowing in domestic currency.

  9. Consistent with recent literature such as Du and Schreger (2016) highlighting the role of credit risk in local currency bond markets, particularly among emerging market economies.

  10. EMU countries include: France, Ireland, Italy, Lithuania, Luxembourg, Netherlands, Portugal, Slovakia, and Spain. Non-EMU countries include: Australia, Brazil, Columbia, Costa Rica, Hungary, Indonesia, Mexico, Romania, Sweden, and the UK.

  11. GDP growth serving as a proxy for economic development by Hausmann and Panizza (2003), and Eichengreen et al. (2005).

  12. Updated quarterly, there are currently 66 developing or emerging market economies that have agreed to provide data, with 40 countries having provided some measure of public sector debt data by 2021.

  13. The Global Database of Inflation provides annual, quarterly, and monthly inflation data for six inflation measures for 196 countries from 1970 to 2021.

  14. The US dollar is serving as the risk-free currency as it is a vehicle currency in the global economy. See studies such as Devereux and Shi (2013), and Goldberg and Tille (2008).

  15. For the domestic lender, there is less of an impact on exchange rate volatility and their local currency bond, as there their bond does not need to be exchanged to another currency at repayment.

  16. Those in the EMU sample exhibit the second largest global currency, but a lack of independent monetary policy at the country level. Those within the non-EMU sample typically have a much less widespread currency, in terms of foreign denomination, but commonly have more independent monetary policy.

  17. For instance, low inflation volatility has a higher importance among low local currency borrowers due to needing to signal to lenders that their inflation risk is low. High borrowers may have established prior monetary credibility to highlight low inflation risk, suggesting a potentially weaker relationship with LC borrowing.

  18. See studies such as Hausmann and Panizza (2003), Eichengreen et al. (2005), Ogrokhina and Rodriguez (2018), and Engel and Park (2022).

  19. With the euro being a prominent currency in the global economy, a shock to the US/euro exchange rate would be a larger concern to investors than a similar sized shock to a less prominent currency present in the non-EMU sample.

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  1. Department of Economics, University of Wisconsin-Milwaukee, 3210 N. Maryland Ave., Bolton Hall 802, Milwaukee, WI, 53211, USA

    Matthew Theobald

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  1. Matthew Theobald
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Appendices

Appendix 1: Data appendix

See Tables 6, 7, 8 and 9.

Table 6 Data sources
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Table 7 Summary statistics
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Table 8 Summary statistics for non-EMU and EMU partitions
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Table 9 Additional debt measures summary statistics
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Appendix 2: Correlation matrices

See Table 10.

Table 10 Correlation matrices of dependent variables for non-EMU and EMU partitions
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Appendix 3: Local projection results

The following tables present local projection results for the aggregate, non-EMU, and EMU samples of the high versus low LC borrowers’ regression model presented in Sect. 4. The dependent variable is local currency debt as a percentage of GDP. This is done for 0, 1, 2, 4, and 8 quarters ahead from time t where 0 quarters ahead is the high versus low LC borrowers’ regression result. Significant correlations for risk measures from the high versus low LC borrowers’ regression hold into future horizons and inflation risk for high local currency borrowers in the non-EMU sample becomes significant at 1 quarter ahead and at longer horizons. The impulse response functions show the persistent impact of all risk measures, GDP growth, and the constant for 0, 1, 2, 4, 8, and 12 quarters ahead from time t given by the local projection results reported in Tables 11, 12 and 13 (Figs. 3, 4, 5).

Table 11 LC debt percentage of GDP, local projection of aggregate sample
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Table 12 LC debt percentage of GDP, local projection of non-EMU sample
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Table 13 LC debt percentage of GDP, local projection of EMU sample
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Fig. 3
figure 3

Impulse response functions between high and low borrowers, aggregate sample

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Fig. 4
figure 4

Impulse response functions between high and low borrowers, non-EMU sample

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Fig. 5
figure 5

Impulse response functions between high and low borrowers, EMU sample

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Theobald, M. Heterogeneity in the impact of risk on local currency borrowing. Ind. Econ. Rev. 58 (Suppl 2), 319–357 (2023). https://doi.org/10.1007/s41775-023-00176-x

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