## wp17135

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### I. Introduction and research question
- Focus: effect of capital account restrictions on corporate bond spreads for corporate bonds placed in international markets by advanced and emerging-market borrowers.
- Contribution: first empirical paper to directly explore the effect of capital controls on the cost of international debt capital using bond-level data and to examine asymmetries across types of restrictions.
- Key motivations:
  - Financial integration has increased over four decades; capital controls have been reintroduced in recent years.
  - Prior literature documents that capital controls can raise cost of equity, constrain smaller firms, and reduce capital stock growth and total factor productivity.
- Primary research question: Do capital account restrictions affect corporate bond spreads, and do effects depend on firm size, domestic financial development, legal origin, EU membership, market structure, and periods of market illiquidity/financial distress?

### II. Data, sample, and variables
- Data construction and sample:
  - Bond dataset builds on Valenzuela (2016); fixed-rate U.S. dollar-denominated corporate bonds available in Bloomberg as of June 2009 (excluding U.S. and England); limited to nonfinancial sector firms.
  - Capital account restrictions constructed using Schindler (2009) methodology and the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER).
- Sample cleaning rules:
  - Eliminate top and bottom 0.5% of spreads.
  - Drop accounting observations exceeding sample mean by more than five standard deviations.
  - Exclude countries with fewer than 30 observations.
  - Restrict to firms with S&P rating between AAA and B-.
- Final sample:
  - 3,740 bond-quarter observations for the period from 2005:Q1 to 2009:Q2.
  - 335 different bonds issued by 166 firms located in 22 countries.
- Key variables:
  - Dependent variable: Corporate option-adjusted spread (OAS) from Bloomberg Professional (basis points).
  - Main explanatory variables:
    - KA_IN: simple average of eight dummy variables capturing restrictions on capital inflows across four asset categories; index range: 0=unrestricted to 1=restricted.
    - KA_OUT: analogous simple average for capital outflows.
  - Controls: bond-level (years to maturity, issue size (US$ in log), coupon rate), firm-level (S&P credit rating 1=D,...,21=AAA; equity volatility (previous 180 days); operating income to sales; short-term debt to total debt; total debt to assets; firm size (total assets, Millions of US$ in log)), country-level (exchange rate, private credit to GDP, private bond market capitalization to GDP, public bond market capitalization to GDP, trade to GDP, political risk (ICRG 0–100), GDP growth, GDP per capita (constant 2000 US$), sovereign credit rating (S&P 1=D,...,21=AAA), financial depth, EU membership (dummy), market-based dummy, English legal origin dummy).
  - Distress measures: Gamma (negative of autocovariance of bond price changes, basis points) and VIX (percentage points).

### III. Empirical framework and identification
- Baseline econometric model:
  - Bond Spread_bfct = α + β X_bfct + φ Y_fct + δ Z_ct-1 + γ KA_IN_ct-1 + θ KA_OUT_ct-1 + A_f + B_t + ε_bfct.
  - KA variables lagged one year (ct-1).
  - Fixed effects: firm (or industry) and time; robustness includes bond fixed effects and industry-time fixed effects.
- Identification strategy:
  - Panel with firm and time fixed effects analogous to difference-in-differences with staggered timing of liberalization.
  - Controls for standard determinants of corporate bond spreads to mitigate omitted variable bias.
  - Use of bond-level data and lagged KA measures to limit reverse causality.

### IV. Main empirical findings
- Baseline effects of capital account restrictions:
  - KA_IN increases corporate bond spreads:
    - Table IV coefficients: KA_IN = 1.895*** (industry FE specification) and KA_IN = 2.260** (firm FE specification).
    - Text summary: a one-standard-deviation increase in KA_IN increases corporate bond spreads by between 45 and 54 basis points.
  - KA_OUT tends to decrease corporate bond spreads in some specifications, but not robust to firm fixed effects:
    - Table IV: KA_OUT = -1.093*** (industry FE); KA_OUT = -0.023 (firm FE).
- Disaggregation by type of security (Table V):
  - Restrictions on inflows involving:
    - Shares: KA_IN = 0.555*.
    - Bonds: KA_IN = 3.398***.
    - Money Market: KA_IN = 1.039 (not significant).
    - Collective Investment: KA_IN = 1.733**.
  - Interpretation: largest effect when restrictions target bond inflows.
  - Capital controls on outflows do not have robust significant effects across transaction types.
- Heterogeneous effects (Table VI):
  - Mitigating factors (KA_IN effect reduced):
    - Larger firms: KA_IN x Size = -1.244***.
    - Deeper financial markets: KA_IN x Financial depth = -2.296* (column 1) and -2.499** (column 5).
    - EU membership: KA_IN x European Union = -6.154* and -7.967**.
    - Market-based financial systems: KA_IN x Market-based = -6.157** and -7.485***.
    - English legal origin: reported mitigation in narrative and definitions.
  - Amplifying factors (KA_IN effect increased):
    - Market illiquidity: KA_IN x Gamma = 0.035** and 0.039** (positive and significant).
    - Global volatility: KA_IN x VIX = 0.110*** and 0.118*** (positive and significant).
  - Overall: KA_IN increases cost of international debt more for financially constrained firms and during market stress; no robust heterogeneous effects for KA_OUT.
- Other control variable relationships:
  - Equity volatility positively related to credit spreads.
  - Higher-quality credit ratings associated with smaller spreads.
  - Higher short-term debt to total debt ratio associated with larger spreads.
  - Trade/GDP, economic growth, and sovereign credit ratings negatively related to spreads.
  - Higher public bond market capitalization to GDP and more depreciated currency associated with higher spreads.
- Robustness:
  - Results robust to excluding bonds with embedded options (unreported regressions).
  - Bond fixed effects and industry-time fixed effects results (Table VII): KA_IN = 2.077** (bond FE, time FE) and KA_IN = 2.413*** (bond FE, industry-time FE); KA_OUT not significant.

### V. Synthesis of substantive findings and policy-relevant implications
- Substantive findings:
  - Capital account restrictions on inflows (KA_IN) significantly and economically increase corporate bond spreads for internationally placed, U.S. dollar-denominated corporate bonds issued by nonfinancial firms.
  - One-standard-deviation increase in KA_IN → increase in corporate bond spreads between 45 and 54 basis points.
  - Disaggregated controls show the largest effect when restrictions target bond inflows.
  - Larger firms and firms in countries with deeper financial markets, EU membership, market-based systems, or English legal origins are less affected by KA_IN.
  - KA_IN effects are amplified during periods of market illiquidity and higher global financial volatility (VIX).
  - No robust significant effect of capital account restrictions on outflows (KA_OUT) on corporate bond spreads.
- Policy implications:
  - Capital controls on inflows can materially raise firms’ cost of international debt financing, particularly harming smaller and more financially constrained firms.
  - Policymakers weighing capital account restrictions should consider heterogeneous firm- and country-level vulnerabilities and potential amplification during times of market stress.
  - Design of capital control regimes that target specific transaction types (e.g., bond inflows) will have direct implications for corporate borrowing costs and firm-level financial constraints.

### VI. Key statistics and exact figures
- Sample and period:
  - Observations: 3,740 bond-quarter observations.
  - Bonds: 335 different bonds.
  - Firms: 166 firms.
  - Countries: 22 countries.
  - Period: 2005:Q1 to 2009:Q2.
- Main coefficient estimates (selected):
  - Table IV: KA_IN = 1.895*** (industry FE), KA_IN = 2.260** (firm FE); KA_OUT = -1.093*** (industry FE), KA_OUT = -0.023 (firm FE).
  - Table V (KA_IN by security type): Shares KA_IN = 0.555*; Bonds KA_IN = 3.398***; Money Market KA_IN = 1.039; Collective Investment KA_IN = 1.733**.
  - Table VI (heterogeneity selected): KA_IN = 14.470*** (col 1); KA_IN x Size = -1.244*** (col 1); KA_IN x Financial depth = -2.296* (col 1); KA_IN x European Union = -6.154* (col 2); KA_IN x Market-based = -6.157** (col 3); KA_IN x VIX = 0.110*** (col 1); KA_IN x Gamma = 0.035** (col 1).
- Descriptive statistics (Table III):
  - Option adjusted spread: Mean = 3.02, Std. Dev. = 3.05, Min = 0.32, Max = 26.71 (basis points).
  - Years to maturity: Mean = 5.80, Std. Dev. = 2.31, Min = 0.09, Max = 13.97 (years).
  - Issue size (log): Mean = 19.64, Std. Dev. = 0.88, Min = 10.92, Max = 21.82.
  - Equity volatility: Mean = 37.56, Std. Dev. = 18.86, Min = 12.57, Max = 140.69 (percent).
  - Credit rating: Mean = 13.22, Std. Dev. = 2.70, Min = 2, Max = 20 (1=D,...,21=AAA).
  - Restrictions on inflows (KA_IN): Mean = 0.17, Std. Dev. = 0.24, Min = 0, Max = 1 (index).
  - Restrictions on outflows (KA_OUT): Mean = 0.24, Std. Dev. = 0.36, Min = 0, Max = 1 (index).
  - Gamma measure: Mean = 18.99, Std. Dev. = 24.79, Min = 3.09, Max = 103.19 (basis points).
  - VIX: Mean = 22.29, Std. Dev. = 10.98, Min = 10.27, Max = 60.72 (percentage points).

*Source: wp17135 - References (IMF Working Paper content provided).*

### References .............................................................................................................

### wp17135 - References

### I. Introduction and research question
- Focus: effect of capital account restrictions on corporate bond spreads for corporate bonds placed in international markets by advanced and emerging-market borrowers.
- Contribution: first empirical paper to directly explore the effect of capital controls on the cost of international debt capital using bond-level data and to examine asymmetries across types of restrictions.
- Key motivations and background:
  - Financial integration has increased over four decades; capital controls have been reintroduced in recent years (Ostry et al., 2010; Blanchard and Ostry, 2012).
  - Prior findings indicate capital controls can raise cost of equity, constrain smaller firms, and reduce capital stock growth and total factor productivity (Henry, 2000a, 2000b; Forbes, 2007a; Bekaert et al., 2011).
  - This paper studies whether capital controls affect corporate bond spreads and whether effects depend on firm size, domestic financial development, legal origin, EU membership, market structure, and periods of market illiquidity/financial distress.

### II. Data, sample, and variables
- Data sources and construction:
  - Bond dataset builds on Valenzuela (2016), includes fixed-rate U.S. dollar-denominated corporate bonds available in Bloomberg as of June 2009 (excluding U.S. and England), limited to nonfinancial sector firms.
  - Capital account restrictions constructed using Schindler (2009) methodology and the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER).
- Sample cleaning rules:
  - Eliminate top and bottom 0.5% of spreads.
  - Drop accounting observations exceeding sample mean by more than five standard deviations.
  - Exclude countries with fewer than 30 observations.
  - Restrict to firms with S&P rating between AAA and B-.
- Final sample (after cleaning):
  - 3,740 bond-quarter observations for the period from 2005:Q1 to 2009:Q2.
  - 335 different bonds issued by 166 firms located in 22 countries.
- Dependent variable:
  - Corporate option-adjusted spread (OAS) from Bloomberg Professional (basis points). Approximately 60% of bonds have embedded call/put features.
- Key explanatory variables:
  - KA_IN: simple average of eight dummy variables capturing restrictions on capital inflows across four asset categories (shares, money market instruments, bonds, collective investment securities); index range: 0=unrestricted to 1=restricted.
  - KA_OUT: analogous simple average for capital outflows.
- Controls:
  - Bond-level: years to maturity, issue size (US$ in log), coupon rate.
  - Firm-level: S&P credit rating (1=D,...,21=AAA), equity volatility (previous 180 days), operating income to sales, short-term debt to total debt, total debt to assets, firm size (total assets, Millions of US$ in log).
  - Country-level: exchange rate (LCU per US$, period average), private credit to GDP, private bond market capitalization to GDP, public bond market capitalization to GDP, trade to GDP, political risk (ICRG 0–100), GDP growth, GDP per capita (constant 2000 US$), sovereign credit rating (S&P 1=D,...,21=AAA), financial depth, EU membership (dummy), market-based dummy (stock market-based =1), English legal origin dummy.
  - Distress measures: Gamma measure (negative of autocovariance of bond price changes, basis points) and VIX (percentage points).

### III. Empirical framework and identification
- Baseline econometric model (panel):
  - Bond Spread_bfct = α + β X_bfct + φ Y_fct + δ Z_ct-1 + γ KA_IN_ct-1 + θ KA_OUT_ct-1 + A_f + B_t + ε_bfct.
  - Subscripts: bond b, firm f, country c, time t. KA variables lagged one year (ct-1) to mitigate reverse causality.
  - Fixed effects: firm (or industry) and time fixed effects; also robustness with bond fixed effects and industry-time fixed effects.
- Identification strategy:
  - Panel with firm and time fixed effects analogous to difference-in-differences with staggered timing of liberalization.
  - Controls for standard determinants of corporate bond spreads to mitigate omitted variable bias.
  - Use of bond-level data and lagged KA measures to limit reverse causality (individual bond spreads unlikely to drive country-level openness decisions).

### IV. Main empirical findings
- Baseline OLS results (controls, errors clustered at country-time):
  - KA_IN (capital account restrictions on inflows) increases corporate bond spreads:
    - Table IV coefficients: KA_IN = 1.895*** (industry FE specification) and KA_IN = 2.260** (firm FE specification).
    - Text summary: a one-standard-deviation increase in KA_IN increases corporate bond spreads by between 45 and 54 basis points.
  - KA_OUT (capital account restrictions on outflows) tends to decrease corporate bond spreads in some specifications, but this result is not robust to inclusion of firm fixed effects (Table IV: KA_OUT = -1.093*** in industry FE; KA_OUT = -0.023 in firm FE).
- Other control variable relationships (Table IV and narrative):
  - Equity volatility positively related to credit spreads.
  - Higher-quality credit ratings associated with smaller spreads.
  - Higher short-term debt to total debt ratio associated with larger spreads.
  - Trade/GDP, economic growth, and sovereign credit ratings negatively related to spreads.
  - Higher public bond market capitalization to GDP and more depreciated currency associated with higher spreads.
- Disaggregation by type of security (Table V):
  - Restrictions on inflows involving shares, bonds, and collective investments have positive and significant effects on corporate bond spreads.
  - Restrictions on inflows: Bonds coefficient notably larger (Column 2 KA_IN for Bonds = 3.398***), consistent with debt being primary corporate financing and pecking-order theory.
  - Money market inflow restrictions positively correlated but not statistically significant.
  - Capital controls on outflows do not have a robust significant effect across transaction types.
- Heterogeneous effects (Table VI):
  - The effect of KA_IN on spreads is mitigated for:
    - Larger firms: interaction KA_IN x Size = negative and significant (e.g., -1.244***).
    - Firms in economies with deeper financial markets: KA_IN x Financial depth = -2.296* (column 1) and -2.499** (column 5).
    - Firms in EU member countries: KA_IN x European Union = -6.154* and -7.967**.
    - Firms in market-based financial systems: KA_IN x Market-based = -6.157** and -7.485***.
    - Firms in English legal origin countries: reported mitigation in narrative and Table II definitions; Table VI shows KA_OUT x English legal origin negative and significant in columns reported for outflows but no robust heterogeneity for KA_OUT overall.
  - The effect of KA_IN is magnified during periods of:
    - Market illiquidity: KA_IN x Gamma = positive and significant (e.g., 0.035**, 0.039**).
    - Financial distress (global volatility): KA_IN x VIX = positive and significant (e.g., 0.110***, 0.118***).
  - Overall, capital controls on inflows increase the cost of international debt more for financially constrained firms and during market stress; no significant heterogeneous effects found for KA_OUT.
- Robustness checks:
  - Results robust to excluding bonds with embedded options (unreported regressions).
  - Results robust to bond fixed effects and industry-time fixed effects (Table VII): KA_IN = 2.077** (bond FE, time FE) and 2.413*** (bond FE, industry-time FE); KA_OUT not significant.

### V. Synthesis of substantive findings and policy-relevant implications
- Substantive findings:
  - Capital account restrictions on inflows (KA_IN) significantly and economically increase corporate bond spreads for internationally placed, U.S. dollar-denominated corporate bonds issued by nonfinancial firms.
  - One-standard-deviation increase in KA_IN → increase in corporate bond spreads between 45 and 54 basis points (text summary).
  - Disaggregated controls show the largest effect when restrictions target bond inflows.
  - Larger firms and firms in countries with deeper financial markets, EU membership, market-based systems, or English legal origins are less affected by KA_IN.
  - KA_IN effects are amplified during periods of market illiquidity and higher global financial volatility (VIX).
  - No robust significant effect of capital account restrictions on outflows (KA_OUT) on corporate bond spreads.
- Policy implications (inference consistent with findings presented):
  - Capital controls on inflows can materially raise firms’ cost of international debt financing, particularly harming smaller and more financially constrained firms.
  - Policymakers weighing capital account restrictions should consider heterogeneous firm- and country-level vulnerabilities and potential amplification during times of market stress.
  - Design of capital control regimes that target specific transaction types (e.g., bond inflows) will have direct implications for corporate borrowing costs and firm-level financial constraints.

### VI. Key statistics and exact figures (preserved)
- Sample and period:
  - Observations: 3,740 bond-quarter observations.
  - Bonds: 335 different bonds.
  - Firms: 166 firms.
  - Countries: 22 countries.
  - Period: 2005:Q1 to 2009:Q2.
- Main coefficient estimates (selected, exact values from tables):
  - Table IV: KA_IN = 1.895*** (industry FE), KA_IN = 2.260** (firm FE); KA_OUT = -1.093*** (industry FE), KA_OUT = -0.023 (firm FE).
  - Table V (KA_IN by security type): Shares KA_IN = 0.555*; Bonds KA_IN = 3.398***; Money Market KA_IN = 1.039 (not significant); Collective Investment KA_IN = 1.733**.
  - Table VI (heterogeneity selected coefficients): KA_IN = 14.470*** (col 1); KA_IN x Size = -1.244*** (col 1); KA_IN x Financial depth = -2.296* (col 1); KA_IN x European Union = -6.154* (col 2); KA_IN x Market-based = -6.157** (col 3); KA_IN x VIX = 0.110*** (col 1); KA_IN x Gamma = 0.035** (col 1).
  - Descriptive statistics (Table III):
    - Option adjusted spread: Mean = 3.02, Std. Dev. = 3.05, Min = 0.32, Max = 26.71 (basis points).
    - Years to maturity: Mean = 5.80, Std. Dev. = 2.31, Min = 0.09, Max = 13.97 (years).
    - Issue size (log): Mean = 19.64, Std. Dev. = 0.88, Min = 10.92, Max = 21.82.
    - Equity volatility: Mean = 37.56, Std. Dev. = 18.86, Min = 12.57, Max = 140.69 (percent).
    - Credit rating: Mean = 13.22, Std. Dev. = 2.70, Min = 2, Max = 20 (1=D,...,21=AAA).
    - Restrictions on inflows (KA_IN): Mean = 0.17, Std. Dev. = 0.24, Min = 0, Max = 1 (index).
    - Restrictions on outflows (KA_OUT): Mean = 0.24, Std. Dev. = 0.36, Min = 0, Max = 1 (index).
    - Gamma measure: Mean = 18.99, Std. Dev. = 24.79, Min = 3.09, Max = 103.19 (basis points).
    - VIX: Mean = 22.29, Std. Dev. = 10.98, Min = 10.27, Max = 60.72 (percentage points).

*Source: wp17135 - References (IMF Working Paper content provided).*

### References

### wp17135 - References

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- Djankov, Simeon, Rafael La Porta, Florencio Lopez-de-Silanes, and Andrei Shleifer, 2003, Courts, The Quarterly Journal of Economics 118, 453-517.
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- La Porta, Rafael, Florencio Lopez-de-Silanes, Andrei Shleifer, and Robert W. Vishny, 1998, Law and Finance, Journal of Political Economy 106, 1113-1155.

### Capital Controls, Financial Openness, and Policy
- Blanchard, Olivier, and Jonathan Ostry, 2012, The multilateral approach to capital controls, article available from VoxEu.
- Edwards, Sebastian, 1999, How effective are capital controls? Journal of Economic Perspectives 13, 65-84.
- Fernández, Andrés, Michael Klein, Alessandro Rebucci, Martin Schindler and Martín Uribe, 2016, Capital control measures: A new dataset, IMF Economic Review 64, 548-574.
- Forbes, Kristin, 2007a, One cost of the Chilean capital controls: Increased financial constraints for small traded firms, Journal of International Economics 71, 294-323.
- Forbes, Kristin, 2007b, The microeconomic evidence on capital controls: No free lunch. In: Edwards, S. (Ed.), Capital Controls and Capital Flows in Emerging Economies: Policies, Practices and Consequences. NBER book, 171-202.
- Gallego, Francisco, and Leonardo Hernández, 2003, Microeconomic effects of capital controls: The Chilean experience during the 1990s, International Journal of Finance and Economics 8, 225-253.
- Ostry, Jonathan D, Atish R. Ghosh, Karl Habermeier, Marcos Chamon, Mahvash S. Qureshi, and Dennis B.S. Reinhardt, 2010, Capital inflows: The role of controls, IMF Staff Position Note SPN/10/04.
- Prati, Alessandro, Martin Schindler, and Patricio Valenzuela, 2012, Who benefits from capital account liberalization? Evidence from firm-level credit ratings data, Journal of International Money and Finance 31, 1649-1673.
- Schindler, Martin, 2009, Measuring financial integration: A new data set, IMF Staff Papers 56, 222-238.

### Financial Openness, Markets, and Growth
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- Gozzi, Juan C., Ross Levine, and Sergio Schmukler, 2010, Patterns of international capital raising, Journal of International Economics 80, 45-47.
- Gozzi, Juan C., Ross Levine, Maria Soledad Martinez, and Sergio Schmukler, 2015, How firms use corporate bond markets under financial globalization, Journal of Banking and Finance 58, 532–551.

### Corporate Finance, Credit Spreads, and Bond Markets
- Bao, Jack, Jun Pan, and Jiang Wang, 2011, The illiquidity of corporate bonds, Journal of Finance 66, 911-946.
- Becchetti, Leonardo, Andrea Carpentieri, and Iftekhar Hasan, 2012, Option-adjusted delta credit spreads: A cross-country analysis, European Financial Management 18, 183-217.
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- Collin-Dufresne, Pierre, Robert S. Goldstein, and J. Spencer Martin, 2001, The determinants of credit spread changes, Journal of Finance 56, 2177-2208.
- Cavallo, Eduardo, and Patricio Valenzuela, 2010, The determinants of corporate risk in emerging markets: An option-adjusted spread analysis, International Journal of Finance and Economics 15, 59-74.
- Huang, Jing-Zhi, and Weipeng Kong, 2003, Explaining credit spread changes: New evidence from option-adjusted bond indexes, Journal of Derivatives 11, 30-44.
- Pedrosa, Monica, and Richard Roll, 1998, Systematic risk in corporate bond credit spreads, Journal of Fixed Income 8, 7-26.
- Valenzuela, Patricio, 2016, Rollover risk and corporate bond spreads, Review of Finance 20, 631-661.
- Merton, Robert C., 1974, On the pricing of corporate debt: The risk structure of interest rates, Journal of Finance 29, 449-470.

### Financial Development, Firms, and Financing Constraints
- Demirguc-Kunt, Asli and Levine, 1999, Financial structures across countries: Stylized facts, Washington, D. C.: World Bank, mimeo.
- Demirguc-Kunt, Asli and Maksimovic, Vojislav, 2002, Funding growth in bank-based and market-based financial systems: evidence from firm-level data, Journal of Financial Economics 65(3), 337-363.
- Demirguc-Kunt, Asli, and Luis Serven, 2010, Are all the sacred cows dead? Implications of the financial crisis for macro- and financial policies, World Bank Research Observer 25, 91-124.
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### Empirical Methods and Evaluation
- Imbens, Guido, and Jeffrey Wooldridge, 2009, Recent developments in the econometrics of program evaluation, Journal of Economic Literature 47, 5-86.
- Pedrosa, Monica, and Richard Roll, 1998, Systematic risk in corporate bond credit spreads, Journal of Fixed Income 8, 7-26.

*Source: wp17135 - References*

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_Source: https://www.imf.org/-/media/files/publications/wp/2017/wp17135.pdf_