Capital Controls and the Cost of Debt


Using a panel data set for international corporate bonds and capital account restrictions in advanced and emerging economies, we show that restrictions on capital inflows produce a substantial and economically meaningful increase in corporate bond spreads, with a one-standard-deviation increase in our capital controls index increasing spreads by up to 35 basis points. The effect of capital controls on inflows differs across firms and across countries; the effect is particularly strong for firms that face more restricted access to alternative sources of external financing. Our findings establish a novel channel through which capital controls affect economic outcomes.

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  1. 1.

    The data set constructed by Valenzuela (2016) covers the 2005–2009 period.

  2. 2.

    These economies were excluded, given their disproportionate size in terms of bond issuances and their lack of variation in terms of capital controls. Thus, the inclusion of these two economies would have implied a very high processing cost that probably would not add much to our insights. Additionally, in the particular case of the USA, the dollar-denominated bonds constitute mainly domestic debt, while the paper focuses on the effect on international debt.

  3. 3.

    Argentina, Belgium, Brazil, Canada, Chile, Finland, France, Germany, Ireland, Republic of Korea, Malaysia, Mexico, Netherlands, Norway, Peru, Philippines, Singapore, Spain, Sweden, Switzerland, and Thailand.

  4. 4.

    Burger et al. (2017) document that foreign-currency-denominated bonds represented 11.8% of local GDP in a sample of 13 EMEs. Of those foreign-currency-denominated bonds, 84% were denominated in US dollars ($714 billion out of $851 billion).

  5. 5.

    Valenzuela (2016) compares the average OASs from his data with OAS indexes reported by the Bank of America (BofA) Merrill Lynch for identical credit rating categories. The indexes constructed from the data set used in this paper adequately mimic the behavior of the BofA Merrill Lynch OAS indexes.

  6. 6.

    For details on the OAS computation, see Cavallo and Valenzuela (2010) and Valenzuela (2016). Other studies using OASs include Becchetti et al. (2012), Huang and Kong (2003), and Pedrosa and Roll (1998).

  7. 7.

    As a proxy for political risk, we employ the “Political Stability and Absence of Violence” indicator from the Worldwide Governance Indicators (WGI) project.

  8. 8.

    For robustness purposes, we also consider both bond and industry-time fixed effects. The results are qualitatively identical.

  9. 9.

    A decline in the US interest rate may produce massive capital inflows in some emerging economies, triggering the imposition of capital controls and a mechanical increase of the credit spreads of bonds denominated in US dollars.

  10. 10.

    Specifically, the market-based variable is a dummy that takes the value 1 for higher than mean values of an aggregate Structure index. Structure index is the means-removed average of relative size, relative activity and relative efficiency measures. Relative size is given by the ratio of stock market capitalization to total assets of deposit money banks; relative activity is defined as the total value of stocks traded divided by bank credit to the private sector; and, finally, relative efficiency is given by the product of total value traded on the stock market and average overhead costs of banks in the country.

  11. 11.

    The coefficient associated with capital controls on inflows is slightly higher once we control for net capital inflows. This is consistent with the negative correlation between net capital inflows and corporate bond spreads and the positive correlation between net capital inflows and capital controls on inflows observe in the data.


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We particularly thank the editor, Linda Tesar, and two anonymous referees for their extensive comments and suggestions. We have also benefited from helpful comments from Arpad Abraham, Franklin Allen, Elena Carletti, Oren Levintal, Peter Lindner, Jun “QJ” Qian, Tsuyoshi Sasaki and seminar participants at the Central Bank of Chile, the University of Santiago of Chile, the University of San Andrés, the 2018 International Risk Management Conference, the 2018 International Atlantic Economic Conference, the 2014 Latin America and the Caribbean Economic Association Annual Meeting, the IFABS 2016 Barcelona Conference, the MBF 2016 Rome Conference and the 43rd Annual Conference of the Eastern Economic Association. Eugenia Andreasen wishes to thank the Fondecyt Initiation Project #11160494 and Dicyt (Universidad de Santiago de Chile), for their financial support. Patricio Valenzuela wishes to thank the Institute for Research in Market Imperfections and Public Policy (ICM IS130002). We thank Chris Dunnett for excellent research assistance. The views expressed in this paper are those of the authors and do not necessarily represent those of the IMF, its Executive Board, or IMF policy.

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Correspondence to Martin Schindler.

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See Tables 9 and 10.

Table 9 Capital controls by income level
Table 10 Capital controls by country

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Andreasen, E., Schindler, M. & Valenzuela, P. Capital Controls and the Cost of Debt. IMF Econ Rev 67, 288–314 (2019).

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