Do Local Currency Bond Markets Enhance Financial Stability? Some Empirical Evidence

ABSTRACT

It is widely believed that local currency bond markets (LCBMs) can promote financial stability in emerging markets. In this article, we empirically test such conventional wisdom by analyzing and comparing six measures of financial vulnerability of emerging markets during two episodes of financial stress – global financial crisis and taper tantrum. We find that emerging markets, which experienced greater expansion of their LCBMs between the two episodes, experienced a greater improvement in financial stability, indicating a stabilizing role of LCBMs. Our evidence indicates that a gradual expansion of bank loans but not stock market development may also contribute to financial stability.

KEYWORDS:

• Bonds
• local currency bond markets
• financial stability
• emerging markets
• global financial crisis
• taper tantrum

JEL:

• E44
• F34
• F38
• F42
• F62

Notes

1. Eichengreen and Hausmann (1999) emphasized most emerging economies suffer from “original sin”, which means that domestic currency cannot be used to borrow abroad or to borrow long term. Subsequently, Eichengreen, Hausmann, and Panizza (2005) focused more on the problem of currency mismatch.

2. See, for example, Lee (2017).

3. See, for example, Park (2016) for Asian initiatives to develop local currency bonds markets.

4. We would like to thank the anonymous referee for suggesting this discussion.

5. A measure of exchange market pressure is obtained from Patnaik, Felman, and Shah (2017). The calculation of CMAX measure follows Huotari (2015) and Anh et al. (2018).

6. There exists a literature that shows that excessive credit-to-GDP ratio vis-a-vis its long-term trend serves as an indicator for the occurrence of financial crisis (Drehmann 2013; Drehmann and Tsatsaronis 2014; Giese et al. 2014). Such indicators are widely used as benchmarks to set up macroprudential policies such as countercyclical capital buffer. In contrast, in this article, we view the growth of bank credit more as the development of the credit market. We would like to thank the anonymous referee for suggesting this discussion.

7. A number of authors used the BIS (Bank for International Settlements) data to measure the size of LCBMS. See, for example, Bae (2012) and Burger and Francis (2006).

8. The sum of domestic debt securities (DDS) and international debt securities (IDS) is not exactly the same as total debt securities (TDS) due to potential overlaps between DDS and IDS.

9. IDS are compiled from a security-by-security database built by the BIS and the relevant information is supplied by commercial data providers. IDS are mostly compiled from data reported to the BIS by central banks, but for a few markets, the BIS collects data directly from publicly available sources. The BIS does not calculate TDS and their statistics are published only when central banks provide the relevant data to the BIS. See more about the debt securities statistic on the BIS webpage: http://www.bis.org/statistics/about_securities_stats.htm.

10. The nominal GDP data are collected from the World Development Indicators.

11. See Figure 1 in the working paper version of the paper.

12. The size of LCBMs calculated from two different sources, the BIS and the Asian Bond Market Online, is quite similar. See Figure 1 in the working paper version of the paper.

13. The list of emerging markets is in Appendix Table A1.

14. Please refer to Park, Ramayandi, and Shin (2016) for a more comprehensive discussion of the variables and data.

15. Various measures of exchange market pressure have been developed by, to name a few, Eichengreen, Rose, and Wyplosz (1996), Sachs et al. (1996) and Kaminsky, Lizondo, and Reinhart (1998).

16. In Figure 5, Seychelles is an outlier. The regression results do not qualitatively change if we exclude Seychelles. Table 6 reports the regression results when Seychelles is excluded from the sample.

17. Definitions of variables and data sources are explained in Appendix Table A2.

18. Since GDP growth and the rule of law were neve significant in PRS, we decide to omit them.

19. The seven Asian markets are China, Indonesia, India, Korea, Malaysia, Philippines, and Thailand. Vietnam is not included in the Asian dummy since the BIS debt securities data are not available.

20. The reason the number of observations differs is due to capital inflow data. For this article, we downloaded the data on March, 2017 from the website, http://data.imf.org/?sk=5DABAFF2-C5AD-4D27-A175-1253419C02D1, while PRS used IMF (2013), published as a CD-Rom in December 2013. Interestingly observations reported as zeros in the CD-Rom are reported as missing values in the website. We sum up the amounts of bonds, equity and loans flows unless any of the three flows are missing.

21. For the case of EMP, we did not include an exchange rate regime in all cases because the exchange rate regime is already taken care of when the EMP measure is calculated since it adds up an estimated counterfactual of the change in the exchange rate due to the observed exchange market intervention. Even when we include it, its coefficient is not statistically significant in all columns (10)–(12).

22. We focus on the cases where there are at least two columns for which the coefficients are statistically significant.

23. Once we include the size of LCBMs, the number of observations is not large mainly because the data are not widely available. See Table 4.2 in the working paper version for the cases where we increase the degree of freedom by including a limited number of control variables along with the difference in the size of LCBMs. It is found that its coefficient is statistically significant even in many cases.

24. Bank loans are domestic credit to the private sector by banks, collected from the World Development Indicators.

25. See Shin and Shin (2011) for the concept of noncore liabilities. They classify retail deposits as core liabilities and the other components of bank funding as the noncore liabilities. Hahm, Shin, and Shin (2013) show that the noncore liabilities are mostly banking sector liabilities of the foreign sector and a large stock of noncore liabilities serves as an indicator if the erosion of the risk premium and hence of vulnerability to a crisis.

26. In Figure 5, Seychelles is an outlier. The regression results do not qualitatively change if we exclude Seychelles or not. Table 6 reports the regression results where Seychelles is excluded in the sample.

27. Since Jordan is an outlier, we report the results in Table 7 without including it in the sample of markets.

Additional information

Funding

This work was supported by the Asian Development Bank.