Identifying the Impact of Exchange Rate Volatility on Corporate Credit Risk: Firm-level Evidence from China

ABSTRACT

This study aims to provide direct evidence of exchange rate volatility’s impact on corporate credit risk by using data from Chinese listed companies. I adopt an identification strategy based on regional heterogeneity across the country and obtain robust results, showing that higher exchange rate volatility increases corporate credit risk, mainly by worsening firms’ profitability and financial flexibility. Additionally, I find that the impact of exchange rate volatility on corporate credit risk through the above channels is primarily concentrated in large enterprises, state-owned enterprises (SOEs), and capital-intensive enterprises.

KEYWORDS:

• Exchange rate volatility
• corporate credit risk
• regional heterogeneity
• RMB exchange rate reform

JEL:

• F31
• F38
• G32
• G33

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Supplementary Material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/1540496X.2022.2072205

Notes

1. Bartram and Bodnar (2012) found that firms in emerging market economies are more exposed to exchange rate risk than those in developed economies. Aggarwal, Chen, and Yur-Austin (2011) and He, Liu, and Zhang (2021) conducted an analysis of the exchange rate risk exposure of Chinese listed companies.

2. Chang, Hsin, and Shiah-Hou (2013) examined the impact of corporate earnings management and the use of foreign exchange derivatives on exchange rate risk exposure.

3. Krapl (2017) further examined the possible asymmetry of cash flow exposures.

4. Cheung and Sengupta (2013) showed that exchange rate volatility could inhibit corporate exports using Indian data. Tunc and Solakoglu (2017) obtained similar findings based on Turkish data.

5. Li, Ma, and Xu (2015) showed that a change in the RMB exchange rate did not have a significant impact on the pricing of export products in RMB among Chinese exporting companies, implying that the exchange rate pass-through of export prices was quite low.

6. Based on Mexican data, Aguiar (2005) confirmed that when an exchange rate depreciated steeply, the balance sheet constraints of companies holding foreign debt had a significant tightening effect on their investment behaviors. However, Dao, Minoiu, and Ostry (2021) showed that a general currency depreciation positively affects corporate profits and investment, while internal financing channels are at work, based on a sample of nearly 33,000 companies in 68 countries. In addition, based on a Colombian sample, Kandilov and Leblebicioğlu (2011) confirmed the inhibitory effect of exchange rate volatility on corporate investment.

7. Gopinath and Stein (2021) theoretically analyzed the reasons why the UIP does not hold.

8. All data are obtained from the CSMAR database, except for the trade globalization index, which is obtained from the KOF Swiss Economic Institute. Due to the limited length of the paper, all appendixes are included in the supplementary materials, which are available online.

9. See more discussions in Appendix D of the supplementary materials.

10. According to the code classification of the “Guidelines for Industry Classification of Listed Companies (Revised in 2012)” of the China Securities Regulatory Commission, A05 (agriculture, forestry, animal husbandry, and fishery services), B11 (mining auxiliary activities), C43 (repair of metal products, machinery, and equipment), F (wholesale and retail trade), G (transportation, warehousing, and postal trade), H (accommodation and catering trade), I (information transmission and software and information technology services trade), K (real estate), L (leasing and business services), M (scientific research and technical services), N (water conservancy, environment, and public facilities management), O (resident services, repairs, and other services), P (Education), Q (Health and Social Work), and R (Culture, Sports, and Recreation) are classified as services and the remaining subcategories in category C are classified as manufacturing.

11. I also conduct a series of placebo tests to validate the robustness of the DID results. See more discussions in Appendix B of the supplementary materials.

12. Note that the number of observations in the first-stage and second-stage regressions are mismatched due to missing data on some variables. However, the principal results are still reliable given a large sample in this study.