## 6. Policy Responses in Inflow Surges in EMEs

## Source details

**Canonical URL:** [6. Policy Responses in Inflow Surges in EMEs](https://www.imf.org/-/media/files/publications/wp/2017/wp1769.pdf)

## Other formats

- [Markdown version](/-/media/files/publications/wp/2017/wp1769.pdf.md)
- [Structured JSON version](/-/media/files/publications/wp/2017/wp1769.pdf.json)

---

### Introduction and framing
- Five policy tools available to EMEs: monetary (interest rate) policy; fiscal policy; exchange rate policy; prudential measures; and capital controls.
- Natural mapping between instruments and risks:
  - Monetary and fiscal: inflation/overheating.
  - FX intervention: limit currency appreciation.
  - Prudential measures: curb credit growth and financial-stability risks.
  - Capital inflow controls (or relaxing outflow controls): limit volumes or target balance-sheet vulnerabilities.
- Empirical focus: quarterly data for about 50 EMEs over 2005–13; change-based measures for prudential and capital control intensity.

### Data, sample, and stylized facts
- Sample coverage and measurement:
  - 51 EMEs over 2005–2013 for most macroeconomic variables.
  - Macroprudential change data for 27 EMEs.
  - Legal reserve requirement (RR) quarterly series for 35 EMEs.
  - Capital control change data for 17 EMEs (these 17 collectively receive over 65 percent of total flows to EMEs).
- Capital flow volatility (sample highlights):
  - Net flows to EMEs: USD 73 billion in 2005Q1 → about USD 180 billion in 2007Q2 → net outflows of some USD 185 billion in 2008Q4 → USD 260 billion in 2011Q2.
  - Volatility most pronounced for other investment flows, followed by portfolio flows; FDI flows remained relatively stable.
- Central bank FX intervention and reserves:
  - Strong correspondence between reserve accumulation and net flows.
  - On average, central banks buy some 30-40 percent of capital inflows (country mean around some 40 percent; IV estimate around some 30 percent).
- Fiscal policy:
  - No discernible counter-cyclical relationship; real government consumption spending is nearly always neutral or procyclical.
- Macroprudential and capital control changes:
  - Number of countries tightening macroprudential policies and total number of measures tightened (net of easing) are positively correlated with net capital flows; correlation became more pronounced since the global financial crisis.
  - RRs track swings in net capital flows; regression evidence: a 10 percent of GDP increase in net flows typically elicits a 0.1 percentage point increase in RRs.
  - Across the 17-country capital-control sample, 11 tightened inflow controls over 2005–13; bank-flow-related restrictions are the most common, followed by bond-flow restrictions.
  - Countries with partially liberalized capital accounts (e.g., India and South Africa) relaxed outflow restrictions in face of inflows; fully open accounts (e.g., Mexico, Romania) could not.

### Macroeconomic policy response (empirical findings)
- Empirical specification: panel regressions of policy responses (FX intervention, policy rate, real government consumption) on net capital flows (percent of GDP), global factors (VIX, commodity prices, U.S. real interest rates), and domestic controls (output gap, inflation, currency appreciation).
- FX intervention:
  - Net capital inflows strongly associated with reserve accumulation.
  - Country-average central bank purchases: 0.400*** (0.040) — Net capital flows/GDP coefficient reported in Table 1.
  - On average EME central banks purchase some 40 percent of inflow; IV regression implies about some 30 percent of inflow is purchased.
  - During the global financial crisis (GFC) central banks sold reserves (GFC: -5.653*** (1.497) in Table 1).
- Policy interest rate:
  - Net inflows elicit higher policy rates: an increase in net flows by 10 percent of GDP, on average, raises the policy rate by 10 basis points (Table 1 col. [3]).
  - When output gap, inflation, and real exchange rate are included, the coefficient on capital flows becomes insignificant; policy rate responds to higher inflation and larger output gap, and is lowered in response to REER appreciation.
  - IV estimate: a 10 percent of GDP increase in net capital flows raises the policy rate by about 30 basis points (Table 1 col. [5]); effect attenuates when cyclical controls included.
- Fiscal policy:
  - Real government consumption spending is positively associated with net capital flows (procyclical) in baseline (Table 1 col. [7]); becomes statistically insignificant when output gap and REER included (col. [8]); no systematic tightening found after instrumenting (cols. [9]-[10]).
  - Split sample: coefficient on net flows positive for inflow episodes, negative (statistically insignificant) for outflows (Table 2 cols. [5]-[6]).
- Response by type of flow:
  - FX intervention: symmetric response to asset (resident) and liability (nonresident) flows—central bank purchases some 40 percent of inflows regardless of source (Table 3 col. [1]); strongest intervention for portfolio flows (Table 3 col. [2]).
  - Policy rate: reacts more to liability flows than asset flows (Table 3 col. [3]); disaggregated: reacts more to FDI than to portfolio or other investment—example: a 10 percent of GDP increase in net FDI raises the policy rate by some 30 basis points (Table 3 col. [4]); effect becomes insignificant after adding output gap, inflation, and REER (cols. [5]-[6]).
  - Fiscal spending: positively associated with portfolio and other investment flows, not with FDI (Table 3 cols. [9]-[10]).

### Unorthodox measures: macroprudential actions and capital controls
- Empirical approach: probit models for tightening of prudential measures and inflow controls; easing of outflow controls.
- Macroprudential measures:
  - Unconditional tightening probability: 7.5 percent.
  - A 10 percent of GDP increase in net capital flows raises tightening likelihood by about 0.3 percentage points (Table 4).
  - Stronger reactions for limits on DTI and LTV, and for RRs (cols. [7]-[9]).
  - Instrumenting for endogeneity increases magnitudes and statistical significance for overall macroprudential indicator and RRs (cols. [2], [10]).
  - Country-level significant tightening: Croatia, Indonesia, and Korea (Table A.9); RRs respond significantly in Brazil, Turkey, and Uruguay.
  - Flow-type sensitivity: macroprudential response stronger for portfolio and other investment flows than for FDI (Table 5).
- Capital controls:
  - Inflow controls: baseline unconditional tightening probability 8 percent.
  - A 10 percent of GDP increase in net flows raises predicted tightening probability by about 0.3 percentage points (Table 6 col. [1]); IV estimates almost double coefficient magnitude and remain highly significant (IV-Probit 0.095*** (0.031) reported in Table 6).
  - Country-level significant associations for inflow tightening: Brazil, India, Philippines, and Turkey (Table A.10).
  - Controls are tightened in response to portfolio and other investment inflows; bond controls respond strongly to portfolio flows; financial-sector-related restrictions react to both portfolio and other investment liability flows (Table 7).
  - Outflow controls: probability of relaxing restrictions is higher when net flows surge; likelihood greater in face of liability flows, especially other investment (Table 7 cols. [6]-[10]).
  - Explanation for contrast with other literature: use of change-based measures (intensity), inclusion of currency-based prudential measures, direct link to capital flows, more recent volatile sample, homogeneous EME focus.

### Natural mapping: instrument choice and observed risks
- Descriptive and regression evidence supports the natural mapping:
  - FX intervention more likely when REER is appreciating: when intervention used, REER appreciation averages 3 percent per year vs. −2 percent when not used (5 percentage point differential, statistically significant).
  - Monetary tightening occurs when output gap is larger and domestic credit growth faster; monetary tightening associated with higher output gap (Figure 5[b]).
  - Macroprudential measures (including RRs) are deployed when domestic credit growth is rapid (statistically significant differential; Figure 5[c]).
  - Inflow controls are used when both currency appreciation and financial-stability concerns are present:
    - When both inflow controls and FX intervention are used, REER appreciation is 5 percentage points greater than when FX intervention alone is used.
    - Credit expansion about 2 percentage points faster when inflow controls accompany macroprudential tightening (Figure 5[d]).
- Formal probit regressions confirm:
  - Central banks more likely to intervene when currency appreciating (Table 8 col. [1]).
  - Policy rates raised when economy overheating (Table 8 col. [2]).
  - Macroprudential tightening when credit expands rapidly (Table 8 cols. [3]).
  - Inflow controls likely in presence of competitiveness and financial-stability concerns; outflow controls used to ease currency appreciation (Table 8 cols. [4]-[5]).

### Responding to inflow surges (surge sample and policy use)
- Surge identification: observations in country’s top 30th percentile of quarterly net flows (percent of GDP); normal flows exclude top and bottom 30th percentiles.
- Surge sample:
  - Almost 700 surge observations in 53 countries during 2005Q1–2013Q4.
  - 223 surge observations with full policy measure coverage across 15 countries (Brazil, Chile, Colombia, Hungary, India, Indonesia, Korea, Malaysia, Mexico, Philippines, Poland, Romania, South Africa, Thailand, Turkey).
  - Final dataset for surge analysis: 223 surge observations and 201 normal-flow observations.
- Policy use during surges (percent of observations):
  - FX intervention: 92 percent of surges vs. 75 percent in non-surge observations (statistically significant).
  - Monetary tightening: about 32 percent of surges vs. 29 percent of non-surge (difference not significant); monetary loosening significantly less likely during surges.
  - Macroprudential tightening: about 16 percent of surges.
  - Inflow controls tightened: 11 percent of surges.
  - Outflow controls relaxed: about 10 percent of surges.
- Use of multiple instruments:
  - Only one instrument used: 49 percent of surges vs. 51 percent of normal flows.
  - Two instruments used: 35 percent of surges vs. 27 percent of normal flows (statistically significant).
  - Three or more instruments: 13 percent of surges vs. 7 percent of normal flows (statistically significant).
  - Interpretation: policy makers deploy combinations more often in surges, consistent with multiple risks and convex instrument costs.

### Key empirical estimates and reported coefficients (selected exact figures)
- From Table 1 (Net Capital Flows and Macroeconomic Policy Response in EMEs, 2005Q1-2013Q4):
  - Net capital flows/GDP: 0.400*** (0.040)
  - US interest rate: -0.145* (0.076)
  - Commodity prices: -3.557*** (0.931)
  - GFC: -5.653*** (1.497)
  - Lagged dependent variable: 0.915*** (0.018)
- From Table A.12 (Macro-Financial Risks in Surges and Normal Flows, in percent), group means:
  - Change in real domestic credit: 11.7*** (surges) and 9.0 (normal flows)
  - Output gap: 0.6*** (surges) and 0.1 (normal flows)
  - Change in REER: 2.7 (surges) and 1.8 (normal flows)
- From Table 4 and Table 5 (Macroprudential policy regressions), selected coefficients:
  - Net capital flows/GDP (relation to tightening specific macroprudential tools): 0.018* (col [1] CCR), 0.031** (col [2] LLP), 0.080** (col [7] Credit growth limit) with reported standard errors in source tables.
  - Initial RR (lagged reserve requirement) coefficients: 0.917*** (0.014) and 0.910*** (0.010) reported in specific columns.
- From Table 6 and Table 7 (Capital controls regressions), selected coefficients:
  - Net capital flows/GDP (probability of tightening inflow controls): 0.046** (0.019) in Probit; IV-Probit 0.095*** (0.031).
  - Composition effects (inflow controls related to asset/liability/composition): Asset flows/GDP 0.057** (0.023) and Liability flows/GDP 0.043** (0.020) reported in specified columns.

### Conclusion: empirical implications and policy takeaways
- EMEs typically respond to capital inflows using a combination of instruments:
  - Central banks raise policy interest rates to address inflation and overheating, and lower rates conditional on REER appreciation to reduce appreciation pressures.
  - Central banks intervene heavily; intervention responds most to portfolio inflows.
  - Fiscal policy is the least-used instrument in practice; no strong evidence of systematic fiscal tightening in response to large inflows.
  - EMEs tighten non-discriminatory macroprudential measures and residency- or currency-based measures that affect inflows; countries with relatively closed capital accounts relax outflow restrictions.
  - Responses are stronger to riskier inflows (portfolio and other investment liability flows) with mapping between measure type and flow type.
  - Use of instruments and combinations is even more pronounced during inflow surges.
- Heterogeneity across countries suggests structural and political constraints shape specific policy responses; whether active management has reduced crisis incidence remains an open question for future research.

*Source: "6. Policy Responses in Inflow Surges in EMEs", wp1769 - 6. Policy Responses in Inflow Surges in EMEs (IMF Working Paper; wp1769.pdf).*

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

### wp1769 - References .............................................................................................................

### Appendix: Data and Additional Estimation Results
- Appendix: Data and Additional Estimation Results ............................................................................. 32
- A.1. List of Countries in the Sample .................................................................................................... 32
- A.2. Variable Description and Data Sources. ....................................................................................... 33
- A.3. Tightening of Macroprudential Policies in Selected EMEs, 2005Q1–2013Q4 ............................ 34
- A.4. Changes in Capital Controls in EMEs, 2005Q1–2013Q4 ............................................................ 34
- A.5. Net Capital Flows and FX Intervention in Selected EMEs .......................................................... 35
- A.6. Net Capital Flows and Policy Rate in Selected EMEs ................................................................. 36
- A.7. Net Capital Flows and Policy Rate in Selected EMEs: Additional Covariates ............................ 37
- A.8. Net Capital Flows and Fiscal Policy Response in Selected EMEs ............................................... 38
- A.9. Net Capital Flows and Macroprudential Policy Response in Selected EMEs .............................. 39
- A.10. Net Capital Flows and Inflow Controls in Selected EMEs ........................................................ 40
- A.11. Net Capital Flows and Outflow Controls in Selected EMEs ...................................................... 40
- A.12. Macro-Financial Risks in Surges and Normal Flows ................................................................. 40

### Tables
- 1. Net Capital Flows and Macroeconomic Policy Response in EMEs, 2005Q1–2013Q4 ................... 27
- 2. Net Inflows and Outflows and Policy Response in EMEs, 2005Q1–2013Q4 ................................. 27
- 3. Macroeconomic Policy Response and the Composition of Flows, 2005Q1–2013Q4 ...................... 28
- 4. Net Capital Flows and Macroprudential Policy Response in EMEs, 2005Q1–2013Q4 .................. 29
- 5. Macroprudential Policies and Composition of Flows, 2005Q1–2013Q4 ......................................... 29
- 6. Net Capital Flows and Capital Controls in EMEs, 2005Q1–2013Q4 .............................................. 30
- 7. Capital Controls and Composition of Flows, 2005Q1–2013Q4 ....................................................... 30
- 8. Use of Policy Instruments and Risks, 2005Q1–2013Q4 .................................................................. 31

### Figures
- 1. Capital Flows to EMEs, 2005Q1–2013Q4 ....................................................................................... 23
- 2. Capital Flows and Macroeconomic Policy Response in EMEs, 2005Q1–2013Q4 .......................... 23
- 3. Capital Flows and Macroprudential Measures in EMEs, 2005Q1–2013Q4 .................................... 24
- 4. Capital Flows and Inflow Controls in EMEs, 2005Q1–2013Q4 ...................................................... 24
- 5. Policy Instruments and Risks, 2005Q1–2013Q4 .............................................................................. 25

*Source: wp1769 - References (PDF).*

### 6. Policy Responses in Inflow Surges in EMEs ...........................................................................

### 6. Policy Responses in Inflow Surges in EMEs

### Introduction and framing
- Emerging market economies (EMEs) have five policy tools to manage capital flows: monetary (interest rate) policy; fiscal policy; exchange rate policy; prudential measures; and capital controls.
- Natural mapping between instruments and risks: monetary and fiscal to inflation/overheating; FX intervention to limit currency appreciation; prudential measures to curb credit growth and financial-stability risks; capital inflow controls (or relaxing outflow controls) to limit volumes or target balance-sheet vulnerabilities.
- Empirical focus: quarterly data for about 50 EMEs over 2005–13, and change-based measures for prudential and capital control intensity.

### Data and stylized facts
- Sample: 51 EMEs over 2005–2013 for most macroeconomic variables; macroprudential change data for 27 EMEs; legal reserve requirement (RR) quarterly series for 35 EMEs; capital control change data for 17 EMEs (these 17 collectively receive over 65 percent of total flows to EMEs).
- Capital flow volatility (sample highlights):
  - Net flows to EMEs: USD 73 billion in 2005Q1 → about USD 180 billion in 2007Q2 → net outflows of some USD 185 billion in 2008Q4 → USD 260 billion in 2011Q2.
  - Volatility most pronounced for other investment flows, followed by portfolio flows; FDI flows remained relatively stable.
- Central bank FX intervention:
  - Strong correspondence between reserve accumulation and net flows; on average, central banks buy some 30-40 percent of capital inflows (country mean around some 40 percent; IV estimate around some 30 percent).
- Fiscal policy:
  - No discernible counter-cyclical relationship; real government consumption spending is nearly always neutral or procyclical.
- Macroprudential and capital control changes:
  - Number of countries tightening macroprudential policies and the total number of measures tightened (net of easing) are positively correlated with net capital flows; correlation became more pronounced since the global financial crisis.
  - RRs track swings in net capital flows; regression evidence: a 10 percent of GDP increase in net flows typically elicits a 0.1 percentage point increase in RRs (see econometric section).
  - Across 17-country sample, 11 tightened inflow controls over 2005–13; bank-flow-related restrictions are the most common, followed by bond-flow restrictions.
  - Countries with partially liberalized capital accounts (e.g., India and South Africa) relaxed outflow restrictions in face of inflows; fully open accounts (e.g., Mexico, Romania) could not.

### Macroeconomic policy response (empirical findings)
- Empirical specification: panel regressions of policy responses (FX intervention, policy rate, real government consumption) on net capital flows (percent of GDP), global factors (VIX, commodity prices, U.S. real interest rates), and domestic controls (output gap, inflation, currency appreciation).
- FX intervention:
  - Net capital inflows strongly associated with reserve accumulation (Table 1): on average EME central banks purchase some 40 percent of inflow; IV regression implies about some 30 percent of inflow is purchased (Table 1 col. [2]).
  - During the global financial crisis (GFC) central banks sold reserves (GFC dummy negative).
- Policy interest rate:
  - Net inflows elicit higher policy rates: an increase in net flows by 10 percent of GDP, on average, raises the policy rate by 10 basis points (Table 1 col. [3]).
  - When output gap, inflation, and real exchange rate are included, the coefficient on capital flows becomes insignificant; policy rate is raised in response to higher inflation and larger output gap, but lowered in response to real exchange rate appreciation (Table 1 col. [4]).
  - IV estimate: a 10 percent of GDP increase in net capital flows raises the policy rate by about 30 basis points (Table 1 col. [5]); effect attenuates when cyclical controls included (col. [6]).
- Fiscal policy:
  - Real government consumption spending is positively associated with net capital flows (procyclical) in baseline (Table 1 col. [7]); becomes statistically insignificant when output gap and REER included (col. [8]); no systematic tightening found after instrumenting (cols. [9]-[10]).
  - Split sample: coefficient on net flows positive for inflow episodes, negative (statistically insignificant) for outflows (Table 2 cols. [5]-[6]).
- Response by type of flow:
  - FX intervention: symmetric response to asset (resident) and liability (nonresident) flows—central bank purchases some 40 percent of inflows regardless of source (Table 3 col. [1]); strongest intervention for portfolio flows (Table 3 col. [2]).
  - Policy rate: reacts more to liability flows than asset flows (Table 3 col. [3]); disaggregated: reacts more to FDI than to portfolio or other investment—example: a 10 percent of GDP increase in net FDI raises the policy rate by some 30 basis points (Table 3 col. [4]); effect becomes insignificant after adding output gap, inflation, and REER (cols. [5]-[6]).
  - Fiscal spending: positively associated with portfolio and other investment flows, not with FDI (Table 3 cols. [9]-[10]).

### Unorthodox measures: macroprudential actions and capital controls
- Empirical approach: probit models for tightening of prudential measures and inflow controls; easing of outflow controls.
- Macroprudential measures:
  - Unconditional tightening probability: 7.5 percent; a 10 percent of GDP increase in net capital flows raises tightening likelihood by about 0.3 percentage points (Table 4).
  - Stronger reactions for limits on DTI and LTV, and for RRs (cols. [7]-[9]).
  - Instrumenting for endogeneity increases magnitudes and statistical significance for overall macroprudential indicator and RRs (cols. [2], [10]).
  - Country-level significance: tightening statistically significant for Croatia, Indonesia, and Korea (Table A.9); RRs respond significantly in Brazil, Turkey, and Uruguay.
  - Flow-type sensitivity: macroprudential response stronger for portfolio and other investment flows than for FDI (Table 5).
- Capital controls:
  - Inflow controls: baseline unconditional tightening probability 8 percent; a 10 percent of GDP increase in net flows raises predicted tightening probability by about 0.3 percentage points (Table 6 col. [1]); IV estimates almost double coefficient magnitude and remain highly significant (col. [2]).
  - Country-level significant associations for inflow tightening: Brazil, India, Philippines, and Turkey (Table A.10).
  - Controls are tightened in response to portfolio and other investment inflows; bond controls respond strongly to portfolio flows; financial-sector-related restrictions react to both portfolio and other investment liability flows (Table 7).
  - Outflow controls: probability of relaxing restrictions is higher when net flows surge; likelihood greater in face of liability flows, especially other investment (Table 7 cols. [6]-[10]).
  - Explanation for contrast with other literature: use of change-based measures (intensity), inclusion of currency-based prudential measures, direct link to capital flows, more recent volatile sample, homogeneous EME focus.

### Natural mapping: instrument choice and observed risks
- Empirical and descriptive evidence supports the natural mapping:
  - FX intervention is far more likely when real exchange rate is appreciating: when intervention used, REER appreciation averages 3 percent per year vs. −2 percent when not used (5 percentage point differential, statistically significant).
  - Monetary tightening occurs when output gap is larger and domestic credit growth faster; monetary tightening is associated with higher output gap (Figure 5[b]).
  - Macroprudential measures (including RRs) are deployed when domestic credit growth is rapid (statistically significant differential; Figure 5[c]).
  - Inflow controls are used when both currency appreciation and financial-stability concerns are present; when both inflow controls and FX intervention are used, REER appreciation is 5 percentage points greater than when FX intervention alone is used; credit expansion about 2 percentage points faster when inflow controls accompany macroprudential tightening (Figure 5[d]).
  - Formal probit regressions confirm:
    - Central banks more likely to intervene when currency appreciating (Table 8 col. [1]).
    - Policy rates raised when economy overheating (Table 8 col. [2]).
    - Macroprudential tightening when credit expands rapidly (Table 8 cols. [3]).
    - Inflow controls likely in presence of competitiveness and financial-stability concerns; outflow controls used to ease currency appreciation (Table 8 cols. [4]-[5]).

### Responding to inflow surges
- Surge identification: observations in country’s top 30th percentile of quarterly net flows (percent of GDP); normal flows exclude top and bottom 30th percentiles.
- Surge sample:
  - Almost 700 surge observations in 53 countries during 2005Q1–2013Q4; 223 surge observations with full policy measure coverage across 15 countries (Brazil, Chile, Colombia, Hungary, India, Indonesia, Korea, Malaysia, Mexico, Philippines, Poland, Romania, South Africa, Thailand, Turkey).
  - Final dataset for surge analysis: 223 surge observations and 201 normal-flow observations.
- Policy use during surges:
  - FX intervention used in 92 percent of surges vs. 75 percent in non-surge observations (statistically significant).
  - Monetary tightening in about 32 percent of surges vs. 29 percent in non-surge (difference not significant); monetary loosening significantly less likely during surges.
  - Macroprudential tightening in about 16 percent of surges.
  - Inflow controls tightened in 11 percent of surges; outflow controls relaxed in about 10 percent of surges.
  - Use of multiple instruments:
    - Only one instrument used: 49 percent of surges vs. 51 percent of normal flows.
    - Two instruments used: 35 percent of surges vs. 27 percent of normal flows (statistically significant).
    - Three or more instruments: 13 percent of surges vs. 7 percent of normal flows (statistically significant).
  - Portfolio approach: policy makers deploy combinations more often in surges, consistent with multiple risks and convex instrument costs.

### Conclusion: summary of empirical implications
- EMEs typically respond to capital inflows using a combination of instruments:
  - Central banks raise policy interest rates to address inflation and overheating, and lower rates conditional on REER appreciation to reduce appreciation pressures.
  - Central banks intervene heavily; intervention responds most to portfolio inflows.
  - Fiscal policy is the least-used instrument in practice; no strong evidence of systematic fiscal tightening in response to large inflows.
  - EMEs tighten non-discriminatory macroprudential measures and residency- or currency-based measures that affect inflows; countries with relatively closed capital accounts relax outflow restrictions.
  - Responses are stronger to riskier inflows (portfolio and other investment liability flows) with mapping between measure type and flow type.
  - Use of instruments and combinations is even more pronounced during inflow surges.
- Heterogeneity across countries suggests structural and political constraints shape specific policy responses; whether active management has reduced crisis incidence remains an open question for future research.

*Source: "6. Policy Responses in Inflow Surges in EMEs", wp1769 - 6. Policy Responses in Inflow Surges in EMEs (IMF Working Paper; wp1769.pdf).*

### References

### References

### Bibliographic sources
- Comprehensive list of cited works on capital flows, macroprudential policy, capital controls, FX intervention, and policy responses covering publications by Ahmed et al. (2015); Akinci and Olmstead-Rumsey (2015); Blanchard, Ostry, Ghosh, and Chamon (2014, 2015, 2016); Carrasco et al. (2015); Cerutti, Claessens, and Laeven (2015); Chinn and Ito (2008); Cordella et al. (2014); de Rato (2007); Eichengreen and Rose (2014); Federico, Végh, and Vuletin (2014); Fernández, Rebucci, and Uribe (2015); Frankel, Végh, and Vuletin (2013); Ghosh et al. (2014, 2016); Ilzetzki and Végh (2008); IMF institutional reports (2005, 2012); Judson and Owen (1999); Kaminsky, Reinhart, and Végh (2005); Kawai and Lamberte (2010); McGettigan et al. (2013); Mihaljek (2005); Mohanty and Berger (2013); Ostry et al. (2010, 2011, 2012); Talvi and Végh (2005); Végh and Vuletin (2012); and others cited in the references list.

### Data, sample, and scope (as documented in figures, tables, and appendix)
- Sample period: 2005Q1-2013Q4.
- Geographic coverage: Emerging Market Economies (EMEs) — country list provided in Table A.1.
- Primary data sources cited: IMF’s IFS database, IMF’s WEO database, IMF’s AREAER, Federico et al. (2014), Akinci and Olmstead-Rumsey (2015), Ahmed et al. (2015), Bloomberg, CPI/INS database, Haver analytics, Political Risk Group.
- Key variable definitions and sources are given in Table A.2 (e.g., Net capital flows from IMF’s IFS; Reserve requirement from Federico et al. (2014); Macroprudential measures from Akinci and Olmstead-Rumsey (2015)).

### Key empirical estimates and reported coefficients (select results reproduced exactly as in the source)
- From Table 1 (Net Capital Flows and Macroeconomic Policy Response in EMEs, 2005Q1-2013Q4), select coefficients and standard errors:
  - Net capital flows/GDP: 0.400*** (0.040)
  - US interest rate: -0.145* (0.076)
  - Commodity prices: -3.557*** (0.931)
  - GFC: -5.653*** (1.497)
  - Lagged dependent variable: 0.915*** (0.018)
- From Table A.12 (Macro-Financial Risks in Surges and Normal Flows, in percent), group means:
  - Change in real domestic credit: 11.7*** (surges) and 9.0 (normal flows)
  - Output gap: 0.6*** (surges) and 0.1 (normal flows)
  - Change in REER: 2.7 (surges) and 1.8 (normal flows)
- From Table 4 and Table 5 (Macroprudential policy regressions), selected coefficient examples (preserved exactly):
  - Net capital flows/GDP (relation to tightening specific macroprudential tools): 0.018* (col [1] CCR), 0.031** (col [2] LLP), 0.080** (col [7] Credit growth limit) with respective standard errors in parentheses as reported.
  - Initial RR (lagged reserve requirement) coefficients reported as 0.917*** and 0.910*** (with standard errors (0.014) and (0.010)).
- From Table 6 and Table 7 (Capital controls regressions), selected coefficients:
  - Net capital flows/GDP (probability of tightening inflow controls): 0.046** (0.019) in Probit; IV-Probit 0.095*** (0.031).
  - Composition effects (inflow controls related to asset/liability/composition): Asset flows/GDP 0.057** (0.023) and Liability flows/GDP 0.043** (0.020) in specified columns.

### Figures and stylized empirical patterns (captions and notes preserved)
- Figures cover:
  - Figure 1: Capital Flows to EMEs, 2005Q1-2013Q4 (In USD billion). Notes: "Net financial flows exclude other investment liabilities of the general government and reserve assets. Flows are the sum for all EMEs in the sample."
  - Figure 2: Capital Flows and Macroeconomic Policy Response in EMEs, 2005Q1-2013Q4 — subpanels for FX reserve flows and policy rate; Real government expenditure. Notes: "Statistics are averages for the corresponding samples. Real government expenditure is the cyclical component of real government spending (seasonally adjusted) in percent of trend real government spending."
  - Figure 3: Capital Flows and Macroprudential Measures in EMEs, 2005Q1-2013Q4 — sources include IMF’s IFS database, Federico et al. (2014), and Akinci-Olmstead-Rumsey (2015).
  - Figure 4: Capital Flows and Inflow Controls in EMEs, 2005Q1-2013Q4 — notes: "Net financial flows is the average for the 17 countries in the sample for which information on changes in capital controls is available. Total no. of changes in panels [a] and [b] are the cumulative number of measures tightened net of measures relaxed for the countries in the sample."
  - Figure 5: Policy Instruments and Risks, 2005Q1-2013Q4 — note: "Figures shows the average year-on-year change in real domestic private credit growth and change in REER (in percent), output gap (in percent), and net capital flow/GDP (in percent) for the cases when policy instruments are used, and when they are not used. Sample comprises those observations for which information on all policy instruments is available. *, **, and *** indicate that the difference between the two group means is statistically significant at the 10, 5, and 1 percent levels, respectively."
  - Figure 6: Policy Responses in Inflow Surges in EMEs — subpanels for individual policy response and policy combinations (In percent of surge/normal flow observations). Note: "Figures show the percentage of large inflow/normal flow observations in which the respective policy instruments are deployed. *, **, and *** indicate that the difference between the two group means is statistically significant at the 10, 5, and 1 percent levels, respectively."
- Appendix Figure A.1: Policy Responses in Large Outflows in EMEs, 2005Q1-2013Q4 — "Figure shows the percentage of large outflows/normal flow observations in which the respective policy instruments are deployed."

### Policy instruments, definitions, and measurement (from appendix and table notes)
- Policy instruments and binary definitions (Table A.2):
  - Capital controls on inflows: Binary variable (= 1 for tightening of inflow controls on equity, debt, and bank flows; 0 otherwise).
  - Capital controls on outflows: Binary variable (=1 for relaxation of outflow controls on equity, debt, and bank flows; 0 otherwise).
  - Macroprudential measures: Binary variable equal to 1 for tightening of countercyclical capital requirements, dynamic loan loss provisioning, caps on loan-to-value and debt-to-income ratios, and limits on credit growth and consumer loans; zero otherwise.
  - Reserve requirement: Average of reserve requirements on local currency demand, saving, and term deposits (in percent) — authors' calculations based on Federico et al. (2014).
  - Net capital flows/GDP: Net financial flows scaled by (1/4)*average annual GDP over the sample period (in percent).
- Model specifications and estimation notes:
  - Regressions commonly include country-fixed effects and quarter (or year) effects and report clustered standard errors.
  - FE denotes OLS with country-fixed effects; IV denotes IV-2SLS with net capital flows to the region (percent of regional GDP) used as instrument for net capital flows (percent of GDP).
  - Probit and IV-Probit used for binary dependent variables (tightening/relaxation decisions), with pseudo-R2 reported where applicable.
  - Significance indicators: ***, **, and * indicate statistical significance at the 1, 5 and 10 percent levels, respectively.

### Country coverage and policy-event tallies (as tabulated)
- Table A.1 provides the list of countries in the sample and flags which countries are included in specific estimations (e.g., FX intervention, policy rate reaction functions, capital control estimations, reserve requirement estimations, macroprudential policy estimations).
- Table A.3 reports counts of tightenings of macroprudential measures across countries (example entries preserved exactly in source; total counts reported in table).
- Table A.4 reports changes in capital controls in EMEs with totals for tightening of inflow controls and relaxation of outflow controls (example totals presented in the source tables).

*Content assembled from the document "wp1769 - References" (figures, tables, notes, and appendix material provided in the source PDF).*

---


_Source: https://www.imf.org/-/media/files/publications/wp/2017/wp1769.pdf_