Abstract
In a financially globalized world, managing long-term interest rates through short-term interest rates can be difficult. In this paper, we examine whether net capital inflows contribute to weakening the link between short- and long-term interest rates. We find that more financially open economies or those with more developed financial markets tend to have a greater negative relationship between net capital inflows and short- to long-term interest rate pass-through. We also examine whether macroprudential policies can affect the extent of interest rate pass-through and find that broad-based capital macroprudential tools are effective in retaining control of interest rate pass-through.
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Notes
In her view, the famous monetary trilemma – countries can achieve only two of the three open macro policy goals of monetary independence, exchange rate stability, and financial openness to the full extent – reduces to a dilemma between monetary independence and financial openness. For the trilemma vs. dilemma debate, refer to Aizenman, et al. (2016), Klein and Shambough (2015), Ricci and Shi (2016), and Han and Wei (2018).
Emerging market economies (EMGs) are those classified as either emerging or frontier in 1980–1997 by the International Financial Corporation, plus Hong Kong and Singapore. This group of economies is a subset of the group of less developed countries (LDC). The industrialized countries (IDC) refer to traditional Organization of Economic Cooperation and Development (OECD) member countries whose IMF numerical codes are below 186 plus Australia and New Zealand.
The VIX measures the implied volatility of U.S. S&P 500 index options and is available from the Chicago Board Options Exchange. For the analyses on the factors that affect cross-border capital flows to EMGs, see Ahmed and Zlate (2013), Forbes and Warnock (2012), Ghosh, et al. (2012), Griffin, et al. (2004), and Fratzscher (2012) among many others.
The two dips in the correlations correspond to the time when the U.S. Federal Reserve changed its policy rate rapidly. The Federal Reserve raised the federal fund rate target from 1.00% in June 2004 to 5.25% in June 2006. It lowered the target from 5.25% in September 2007 to the 0.00–0.25 by December 2008.
Negative values mean capital outflows.
For data sources and theoretical predictions of the variables, refer to Appendix 1.
See Appendix 1 for country groups.
KAOPEN is based on information regarding restrictions in the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER), and is constructed as the first standardized principal component of the variables indicating the presence of multiple exchange rates, restrictions on current account transactions, restrictions on capital account transactions, and the requirement of the surrender of export proceeds. Chinn and Ito (2006, 2008) explain the index in great details.
For more on “financial centers,” see Lane and Milesi-Ferretti (2017).
Hence, in the second stage, the time fixed effects capture global financial cycles and the effects of the center economies’ monetary or financial shocks, i.e., “push factors.”.
We continue to use the 2SLS estimation method for the rest of the paper.
In the case of panel (4), the trilemma will not be ‘binding.’ Given that the three policy goals must be linearly related, when both financial openness and exchange rate stability are at low levels, that means policymakers are not optimizing their objective function, which means an inefficient outcome (Ito and Kawai 2014). However, that must indicate the level of monetary independence is higher.
From a slightly different angle, it could be argued that the lack of financial development could lead to high risk premia on the side of emerging markets and make their securities highly correlated with U.S. financial markets because highly leveraged investors may try to recover their losses from investing in risky securities in the U.S. markets. Thought this is not what the estimation results show, it is an important point. We thank Hwee Kwan Chow for raising this point.
The authors also argue that codifying the degree of intensity would involve a certain degree of subjective judgements.
The variables for inflation and output volatilities as well as the constant term and yearly fixed effects are included in the estimation, though their estimates are not reported in the table to conserve space.
For the EMG subsample, the estimate on the MPI is found to be significantly positive with the p-value of 1%. However, the estimate of net capital inflows becomes insignificant.
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Acknowledgement
This research was conducted while Ito was a visiting fellow at RIETI. Ito is grateful for their generous support and hospitality. Ito and Tran thank Portland State University for financial support. All errors are ours.
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Appendices
Appendix 1 Data Descriptions and Country Groups
1.1 Theoretical Predictions and Data Sources
KFlow – Net capital flows as a share of GDP. The data are extracted from the International Monetary Fund’s Balance of Payments database. Positive values of net capital inflows mean capital inflows while negative values mean capital outflows.
Relative income – The more developed a country of our concern is, the more smoothly the interest rate channel of monetary transmission should take place, i.e., the linkage between short-term and long-term interest rates gets stronger. Higher per capita income also reflects better institutional development, which can also contribute to smoother monetary transmission. We measure the level of economic development by using the per capita income data from Penn World Table 9.1 and normalizing it as a ratio to the U.S. per capita income level.
Inflation volatility – measured as the 5-year standard deviations of CPI-inflation. High inflation volatility, on the one hand, introduces uncertainty into the market signals that potentially reduces the effectiveness of the monetary policy transmission. Therefore, the coefficient may appear to be negative. On the other hand, more frequent episodes of high inflation volatility may also cause the risk premium to climb in order to incentivize borrowers to hold a risky asset. Consequently, we could also observe the longer end of the yield curve mounting to higher levels in the presence of inflation volatility. In other words, the term risk makes the yield curve often upward sloping. That instead suggests a positive coefficient.
Output volatility – measured as the 5-year standard deviations of real GDP growth rates. To a lesser extent, the same explanation may apply to output volatility, though it seems more reasonable to assume that greater output stability might lead to greater effectiveness of monetary policy due to increased predictability of both economic conditions and economic policy management, leading to smaller risk premium.
Output gap – the difference between the actual real GDP and the Hodrick-Prescott filtered GDP. Output gap may serve as a good proxy for a country’s level of policy rate, indicating whether the economy is on the state of rising or falling policy rate. Given the tendency of the yield curve to be upward sloping, a fall in the policy rate leads to a smaller response in the longer-term interest rate compared to when the policy rate is rising, which suggests that the coefficient on the output gap variable be negative.
Financial crisis – The dummy for a financial crisis is constructed based on Laeven and Valencia’s (2018) database on the occurrences of currency, banking and sovereign crises. The dummy takes the value of one if either or both of currency and banking crisis happen. This dummy might capture noise in the dependent variable since the policy rate disproportionally changes with respect to long-term interest rates in the case of a financial crisis.
Financial development – Financial development may matter for the interest rate pass-through since obviously more developed financial markets should facilitate monetary transmission. To measure the level of financial development, we use Svirydzenka’s (2016) “index of financial development” which is the first principal component of two sub-indexes, one that captures the development of financial markets (FM) and the other that reflects the development of financial institutions (FI).
Country List
Industrialized countries (IDC):
Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Japan, Luxembourg, Malta, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom, United States.
Emerging Market Economies (EMEs):
Argentina, Bangladesh, Botswana, Brazil, Brunei, Bulgaria, Cote d’Ivoire, Cambodia, Chile, China, Colombia, Czech Republic, Ecuador, Egypt, Arab Rep., Ghana, Hong Kong, China, Hungary, India, Indonesia, Israel, Jamaica, Jordan, Kenya, Korea, Rep., Lithuania, Malaysia, Mauritius, Mexico, Morocco, Nigeria, Pakistan, Peru, Philippines, Poland, Russian Federation, Singapore, Slovak Republic, Slovenia, South Africa, Sri Lanka, Thailand, Trinidad and Tobago, Tunisia, Turkey, Venezuela, RB, Vietnam, Zimbabwe.
Emerging Asia:
China, Hong Kong, China, India, Indonesia, Korea, Rep., Malaysia, Philippines, Singapore, Thailand, Vietnam.
Appedix 2: Macroprudential Policy Index
Variable | Variable Name | Definition |
|---|---|---|
Broad-based capital tools (CAPITAL) | ||
DP | Time-Varying/Dynamic Loan-Loss Provisioning | Dummy for the use of a policy that requires banks to hold more loan-loss provisions during upturns |
CTC | General Countercyclical Capital Buffer/Requirement | Dummy for the use of a policy that requires banks to hold more capital during upturns |
SIFI | Capital Surcharges on Systematically Important Financial Institutions | Dummy for the use of a policy that requires Systematically Important Financial Institutions to hold a higher capital level than other financial institutions |
INTER | Limits on Interbank Exposures | Dummy for the use of a policy that limits the fraction of liabilities held by the banking sector |
Sectoral capital and asset-side tools (ASSET) | ||
LTV_CAP | Loan-to-Value Ratio | Dummy for the use of LTV measures used as a strict cap on new loans as opposed to a loose guideline or merely an announcement of risk weights |
DTI | Debt-to-Income Ratio | Dummy for the use of a policy that constrains household indebtedness by enforcing or encouraging a limit |
LEV | Leverage Ratio | Dummy for the use of a policy that limits banks from exceeding a fixed minimum leverage ratio |
CONC | Concentration Limits | Dummy for the use of a policy that limits the fraction of assets held by a limited number of borrowers |
Liquidity-related tools (LIQUIDITY) | ||
FC | Limits on Foreign Currency Loans | Dummy for the use of a policy that reduces vulnerability to foreign-currency risks |
RR_REV | FX and/or Countercyclical Reserve Requirements | RR is a policy that limits credit growth. It can also be targeted to limit foreign-currency credit growth. RR_REV is a subset of RR that restricts to reserve requirements which i) imposes a specific wedge on foreign currency deposits or are adjusted countercyclically |
CG | Limits on Domestic Currency Loans | Dummy for a policy that limits credit growth |
TAX | Levy/Tax on Financial Institution | Dummy for taxes on the revenue of financial institutions |
MPI | Macroprudential Policy Index (0 – 12) | LTV_CAP + DTI + DP + CTC + LEV + SIFI + INTER + CONC + FC + RR_REV + CG + TAX |
Appendix 3: Estimates of Net Capital Inflow and Macroprudential Policies, 1999 – 2016
Dep. Var.: Est. beta | (1) | (2) | (3) | (4) | (5) | (6) | (7) |
|---|---|---|---|---|---|---|---|
Net K-inflow | -1.925 | -1.814 | -2.226 | -1.678 | -1.931 | -2.014 | -1.800 |
(0.580)*** | (0.612)*** | (0.665)*** | (0.605)*** | (0.688)*** | (0.601)*** | (0.611)*** | |
Loan loss-provision | 0.190 | ||||||
(0.085)** | |||||||
Countercyclical | -0.148 | ||||||
k-requirements | (0.108) | ||||||
K-surcharge on | -0.408 | ||||||
SIFI | (0.151)*** | ||||||
Limits on interbank exposure | 0.118 | ||||||
(0.053)** | |||||||
Loan-to-value ratio | -0.009 | ||||||
(0.063) | |||||||
Debt-to-income ratio | -0.017 | ||||||
(0.075) | |||||||
Leverage ratio | -0.015 | ||||||
(0.080) | |||||||
Concentration limits | |||||||
Limits on foreign currency loan | |||||||
Countercyclical reserve requirements | |||||||
Limits on domestic currency loan | |||||||
Levy on financial institution | |||||||
Adjusted R 2 | 0.39 | 0.39 | 0.35 | 0.41 | 0.38 | 0.37 | 0.39 |
Dep. Var.: Est. beta | (8) | (9) | (10) | (11) | (12) | (13) |
|---|---|---|---|---|---|---|
Net K-inflow | -1.734 | -1.510 | -1.891 | -1.762 | -1.769 | -2.245 |
(0.608)*** | (0.546)*** | (0.636)*** | (0.594)*** | (0.595)*** | (0.678)*** | |
Loan loss-provision | 0.161 | |||||
(0.080)** | ||||||
Countercyclical | -0.118 | |||||
k-requirements | (0.144) | |||||
K-surcharge on | -0.413 | |||||
SIFI | (0.202)** | |||||
Limits on interbank exposure | 0.129 | |||||
(0.056)** | ||||||
Loan-to-value ratio | 0.017 | |||||
(0.068) | ||||||
Debt-to-income ratio | -0.098 | |||||
(0.068) | ||||||
Leverage ratio | 0.030 | |||||
(0.072) | ||||||
Concentration limits | 0.052 | -0.000 | ||||
(0.044) | (0.049) | |||||
Limits on foreign currency loan | 0.177 | 0.158 | ||||
(0.073)** | (0.081)** | |||||
Countercyclical reserve requirements | 0.074 | 0.053 | ||||
(0.069) | (0.070) | |||||
Limits on domestic currency loan | -0.149 | -0.218 | ||||
(0.080)* | (0.089)** | |||||
Levy on financial institution | 0.082 | 0.031 | ||||
(0.106) | 0.108 | |||||
Adjusted R 2 | 0.40 | 0.43 | 0.38 | 0.40 | 0.39 | 0.40 |
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Ito, H., Tran, P. Emerging Market Economies’ Challenge: Managing the Yield Curve in a Financially Globalized World. Open Econ Rev 34, 171–194 (2023). https://doi.org/10.1007/s11079-021-09661-3
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DOI: https://doi.org/10.1007/s11079-021-09661-3