## wpiea2023012-print-pdf

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### Global financial spillovers and motivation
- US monetary policy shocks impact GDP growth and financial variables across many economies; interest rates in advanced economies display a “global financial cycle.”
- International capital flows are key transmission channels to emerging market economies (EMEs).
- Many EMEs supplement exchange rate flexibility with macroprudential instruments (MaPs), foreign exchange intervention (FXI) and capital flow management measures (CFMs).
- EMEs gradually tightened macroprudential regulation from 2000 to 2016, with remarkable heterogeneity in instruments and stances.

### Model: setup, frictions, and policy instruments
- Framework: extension of Gerali, Neri, Sessa and Signoretti (2010) to a small open economy with external trade and financial sectors; discrete time, infinite horizon.
- Agents: households (savers), entrepreneurs (borrowers), banking sector, central bank.
- Two financial frictions:
  - Bank adjustment costs from deviating from a target capital adequacy ratio (credit supply friction).
  - Collateral constraints for domestic borrowers (credit demand friction).
- Banking sector features:
  - Banks receive deposits D_t, borrow abroad B_t^f, lend domestically B_t; lend with markup μ_B and face quadratic CAR deviation cost with parameter θ.
  - Only a fraction (1−ζ) of foreign borrowing can be hedged; ζ is unhedged share.
  - Foreign credit supply: B_t^f = γ B̄ ( E_t[E_{t+1}]/E_t )^{σ_1} (1 + i_t^f)^{σ_2} with σ_2 < 0, σ_1 < 0.
- Central bank instruments:
  - Monetary policy: deposit rate i_t^D via a Taylor rule (Equation (9)).
  - Macroprudential policy: LTV_t and CAR_t via rules (Equations (10)–(11)); MaPs are uncoordinated in baseline.
- Focus shock: foreign interest rate i_t^f following AR(1) with ρ_{i_f}.

### Mechanisms of external shock transmission
- Loose global financial conditions (US expansionary monetary policy):
  - Bank profits and asset prices rise → banks can increase lending without adjusting leverage → collateral constraints loosen → domestic borrowing and investment increase → external debt can finance investment and GDP growth.
- Tightening external financial conditions (US tightening):
  - Bank profits and asset prices decline → both credit supply and demand contract → external shocks increase volatility of macro-financial variables even as steady-state growth may be higher.
- Tradeoff: supporting growth in good times versus minimizing damage in bad times; countercyclical MaPs compress booms but limit downturns.

### Macroprudential tools and countercyclicality
- Two MaP tools in model:
  - Bank capital adequacy ratio requirements (CAR) — lender-based.
  - Loan-to-value ratio limits (LTV) — borrower-based.
- Countercyclical MaPs: tighten (loosen) CAR and LTV when domestic financial conditions are loosening (tightening).
- Effects of countercyclical MaPs:
  - Mitigate volatility from external financial shocks.
  - Potentially reduce GDP growth during good times by limiting credit expansion.
  - Limit growth of overall and external debt during loosening external conditions by raising CAR and/or lowering LTV.
  - Limit declines in credit supply/demand during tightening external conditions, supporting investment and output.

### Key country-specific parameters shaping MaP effectiveness
- Currency denomination of debt:
  - Unhedged foreign-currency liabilities (net short foreign currency positions) amplify balance-sheet deterioration after depreciation; such countries benefit more from countercyclical MaPs.
- Elasticity of foreign credit supply to the real exchange rate (σ_1 / γ proxy):
  - Countries with more stable capital flows (lower γ) experience milder contractions when external conditions tighten, reducing gains from active countercyclical MaPs.
- Elasticity of the current account to the real exchange rate (ψ_f):
  - Strong expenditure-switching (high ψ_f) improves external balances after depreciation, offsetting financial-channel depreciation effects; low ψ_f increases value of countercyclical MaPs.
  - Under the dominant currency paradigm (DCP), high shares of exports invoiced in US dollars produce muted current-account response (low ψ_f).

### Empirical approach and clustering
- Estimation: local linear projections (LLP) with controls for pre-shock policy instruments, domestic macro variables, and global shocks; sample of 40 countries.
- Macroprudential stance measured by net tightenings/loosings across 17 instruments (indicator captures direction, not intensity).
- Two clusters from MaP impulse responses to US monetary surprises:
  - Countercyclical MaP countries: loosen (tighten) MaP stance when the US tightens (loosens).
  - Non-countercyclical MaP countries.
- Countries classified as countercyclical (10): Belgium, Finland, Indonesia, Israel, Malaysia, Poland, Spain, Sweden, Turkey, United Kingdom.
- Classification rule: average IRF of net MaP tightenings from 0–4 quarters is negative and its 66 percent confidence interval excludes zero; countries with fewer than 10 adjustments excluded.

### Empirical determinants of MaP cyclicality (probit results)
- Probit explanatory variables include sensitivity of net inflows to US surprises, sensitivity of exports to REER, volatility of private capital flows (% GDP), external debt liabilities in foreign currency (% GDP), and currency mismatches (% GDP).
- Key significant determinant:
  - Currency mismatch as % of GDP: coefficients reported 0.641 [0.292] and 0.612 [0.268] (standard errors in brackets); statistically significant at the 10% level.
  - Interpretation: greater net long currency mismatch reduces probability of countercyclical MaPs; countries with negative currency mismatches (foreign currency liabilities > assets) are more likely to adopt countercyclical MaPs.
- Other variables (sensitivity of net inflows to US surprises, export REER sensitivity, volatility of private capital flows, external debt liabilities in foreign currency) are not significant in multivariate specifications.

### SUR local projections: policy and macroeconomic differences by cluster
- Countercyclical countries vs. others after a 1 percentage point US tightening surprise (median patterns):
  - Monetary policy:
    - Immediately after the US surprise, countercyclical countries have less tight monetary policy.
    - After 4 months, countercyclical MAP countries have tightened interest rates by about 15 basis points more than other countries.
    - No differences after 8 quarters.
  - Macroprudential stance: countercyclical countries loosen MaP stance on net relative to others.
  - Credit-to-GDP: countercyclical countries show relatively faster credit-to-GDP growth, peaking at about 8 to 10 quarters after the shock.
  - GDP: no significant differences in GDP paths between clusters.
  - Inflation: initially lower in countercyclical countries; cumulative inflation shows no difference over a 2-year horizon.

### Static model: comparative statics and Proposition 1
- Static equilibrium with three markets: foreign borrowing by banks, domestic borrowing, domestic deposits.
- Key identities (preserved notation):
  - Steady-state UIP: 1 + i_d = 1 + i_f^E (Equation 14).
  - Foreign credit supply: B_f = γ B̄ (E)^{σ1} (1+ i_f)^{σ2} (Equation 15).
  - Market clearing: B_f = B − D (Equation 16).
  - Domestic lending rate (with CAR costs): i_b = i_d − θ (K_B / B − CAR) (K_B / B)^2 (Equation 17).
  - Entrepreneur borrowing (static Euler): 1 + s_E(B, q_k)^{λ_E(R_k)} = β_E (1 + i_b) (Equation 18).
- Three channels for foreign borrowing changes: investment channel (via i_d), net exports channel (via R_K), balance-sheet channel (bank-side CAR friction and borrower-side LTV constraints).
- Proposition 1: A rise in the foreign interest rate leads to a decline in domestic credit if the net export channel is zero; bank and entrepreneur balance-sheet channels amplify the impact; countercyclical MaP policy (inverse relationship between CAR or LTV and B) cushions the decline of credit, while procyclical MaPs magnify it.

### Dynamic model simulations: baseline calibration and shock responses
- Baseline calibration highlights (values preserved):
  - ζ = 0.3 (share of foreign-currency debt).
  - Steady state bank capital to asset ratio = 0.10.
  - Entrepreneur’s loan-to-value ratio = 0.55.
  - Foreign interest rate shock: 1%-pt increase to ε_t^f with autocorrelation coefficient ρ_{i_f} = 0.4.
  - Other calibration entries (Table B1) include: β_H = 0.996; β_E = 0.975; ρ_N = 1; LTV = 0.55; mct_μ = 6/5; α = 0.2; κ = 5; δ = 0.05; π_ss = 1; θ = 11; CAR = 0.10; μ_B = 0.005; ρ_i = 0.77; φ_π = 0.5; φ_Y = 2.5; ρ_A = 0.95; ρ_μ = 0.5; γ = 0.3; B̄ = 0.9; ψ = 0.3; ζ = 0.3; Λ = 0.99; Λ_f = 0.05; ψ (imports) = 0.5; ψ_f (exports) = 0.01; Y_t^f = Exp(-0.8).
- Baseline (no-MaP) response to positive foreign interest rate shock i_t^f:
  - Increase in foreign borrowing cost → sharp decline in total debt, investment and output.
  - Central bank initially reduces policy rates; subsequent depreciation raises import prices → higher inflation → central bank raises policy rate in period after shock.
  - Depreciation raises net exports (automatic stabilizer).
  - Bank profits fall → bank capital falls → bank leverage increases; higher domestic lending rates depress investment and asset prices.
- Countercyclical MaPs (specified MaP response parameters used in simulations):
  - φ_{B,LTV} = −0.5
  - φ_{q,LTV} = −0.5
  - φ_{B,CAR} = 0.5
  - φ_{q,CAR} = 0.5
  - Under countercyclical regime: as total debt and asset prices fall, authorities raise LTV_t and lower CAR_t (per rules), loosening borrowing constraints and reducing bank CAR adjustment costs.
  - Outcome: mitigated fall in domestic lending and investment, reduced fall in output relative to no-MaP; reduced volatility around steady state.
  - Trade-off: MaPs can drag on growth during loose global conditions while reducing depth of recessions during tightness.

### Heterogeneous responses to i_t^f: role of three parameters
- Parameters emphasized:
  1. ζ — share of foreign-currency borrowing within total net borrowing (baseline ζ = 0.3).
     - Higher ζ amplifies depreciation-induced increases in foreign-currency liabilities → larger declines in bank capital and lending.
  2. γ — responsiveness of foreign credit supply to foreign interest rate (baseline γ = 0.3).
     - Higher γ implies larger contractions in foreign credit supply when i_f rises → sharper declines in bank profits, lending, total debt, investment and output.
  3. ψ_f — elasticity of export demand to real exchange rate (baseline ψ_f = 0.01).
     - Higher ψ_f strengthens net-export channel after depreciation, potentially offsetting contractionary effects and insulating output; low ψ_f (e.g., due to exports invoiced in a dominant currency) weakens that channel.
- Comparative summaries from simulations:
  - High ζ and high γ produce large balance-sheet amplification: sharp curtailment of total debt, higher bank leverage, reduced asset prices.
  - High ψ_f produces stronger exchange-rate channel benefits: better current account, dampened inflationary impulse, mitigated investment and asset-price declines.

### MaP design tradeoffs and authority objective
- MaP authority objective: mean-variance utility V(·) = α_1 μ_{ΔY} − α_2 (σ_{ΔY}^2 + σ_{ΔB}^2), choosing φ_MAP = {φ_{LTV,b}, φ_{LTV,q}, φ_{CAR,b}, φ_{CAR,q}}.
  - μ_{ΔY} = E_{i_f}[Y_t − Y_ss]; σ_{ΔY}^2 = Var_{i_f}[Y_t − Y_ss]; σ_{ΔB}^2 = Var_{i_f}[B_t − B_ss].
- Comparative statics:
  - dμ_{ΔY}/dζ > 0 and dμ_{ΔY}/dγ > 0: countries with high ζ or γ derive greater mean growth benefits from unexpected loosening of external conditions.
  - Higher φ_MAP dampens positive mean growth effects from inflows: d^2 μ_{ΔY} / dζ dφ_MAP < 0.
  - Volatility increases with ζ and γ: dσ_{ΔY}^2/dζ > 0 and dσ_{ΔB}^2/dζ > 0; higher ψ_f mitigates output volatility: dσ_{ΔY}^2/dψ_f < 0.
  - Countercyclical MaPs reduce volatility: d^2 σ_{ΔY}^2 / dζ dφ_MAP < 0.
- Policy implication: countries with high ζ, high γ, and low ψ_f face a steeper growth–stability tradeoff and gain more from tighter countercyclical MaPs in volatility reduction, though at potential growth cost.

### Policy implications and caveats
- MaPs can reduce damage from capital flow reversals but may restrain growth during normal times.
- Countries with high external foreign-currency liabilities and large negative currency mismatches have greater potential gains from countercyclical MaPs.
- Interactions with monetary policy and exchange rates are complex:
  - Aggressive countercyclical MaPs can require larger currency appreciation and higher policy rates to clear credit markets, potentially reducing investment and output via investment and exchange-rate channels.
  - Exceptionally aggressive countercyclical MaP regimes can worsen output after initial shock relative to no-MaP baseline.
- Empirical evidence supports that countries net short on foreign currency debt are more likely to adopt countercyclical MaPs; other model-predicted variables showed no robust empirical association in the sample.

*Italic: Source: wpiea2023012-print-pdf (IMF Working Paper).*

### 1. Introduction ........................................................................................................

### 1. Introduction

### Global financial spillovers and motivation
- Empirical literature documents that US monetary policy shocks impact GDP growth and financial variables across a large set of global economies.
- Changes in interest rates in advanced economies have become increasingly correlated with a common global factor in financial conditions, giving rise to a “global financial cycle” that impacts countries across exchange rate regimes.
- International capital flows are an important transmission channel of advanced-economy developments to emerging market economies (EMEs).

### Policy responses and heterogeneity in practice
- Many EMEs have supplemented exchange rate flexibility with macroprudential instruments (MaPs), foreign exchange intervention (FXI) and capital flow management measures (CFMs).
- Comprehensive data show EMEs gradually tightened macroprudential regulation from 2000 to 2016.
- There is remarkable heterogeneity in how countries use MaPs; the large number of instruments and lack of a consistent economic framework make characterizing countries’ macroprudential stance challenging.

### Contribution: model and positive analysis
- The paper extends the banking-sector DSGE model of Gerali, Neri, Sessa and Signoretti (2010), adding external trade and financial sectors, to analyze MaP effectiveness in a small open economy integrated into international financial markets.
- Two sources of financial frictions induce deviations from first-best domestic credit outcomes:
  - Bank adjustment costs from deviating from a target capital adequacy ratio (credit supply friction).
  - Collateral constraints for domestic borrowers (credit demand friction).
- Both frictions create financial channels through which external financial shocks affect domestic variables.

### Mechanisms of external shock transmission
- Under loose global financial conditions (expansionary US monetary policy):
  - Bank profits and asset prices rise.
  - Rising bank profits and capital allow banks to increase lending while maintaining constant leverage ratios, avoiding capital adequacy ratio adjustment costs.
  - Rising asset prices loosen collateral constraints, increasing domestic borrowing.
  - External debt can finance physical investment and contribute to GDP growth.
- Under external financial tightening shocks (e.g., US tightening):
  - Bank profits and asset prices decline, reducing credit supply and demand.
  - External shocks increase volatility of macro-financial variables even as they allow for higher steady-state economic growth.

### Macroprudential tools and countercyclicality
- Policymakers in the model have access to two MaP tools:
  - Bank capital adequacy ratio requirements (lender-based).
  - Loan-to-value (LTV) ratio limits (borrower-based).
- Countercyclical MaPs: tighten (loosen) capital adequacy and LTV limits when domestic financial conditions are loosening (tightening).
- Effects of countercyclical MaPs:
  - Mitigate volatility in domestic macro-financial outcomes from external financial shocks.
  - Potentially reduce GDP growth during good times by limiting credit expansion.
  - Limit growth of overall and external debt during loosening external conditions by raising bank capital requirements and/or lowering LTV limits.
  - Limit declines in credit supply and demand during tightening external conditions, supporting investment and output.

### Tradeoff and key country-specific parameters shaping MaP effectiveness
- The tradeoff: supporting growth in good times versus minimizing economic damage in bad times; more aggressive countercyclical MaPs reduce growth in booms but limit downturns.
- Three country-specific parameters identified:
  - Currency denomination of debt:
    - Countries with unhedged liabilities denominated in foreign currencies (net short foreign currency positions) face perverse dynamics from depreciation that worsen bank balance sheets and lending—these countries gain more from countercyclical MaPs.
  - Elasticity of foreign credit supply to movements in the real exchange rate:
    - Countries with less fickle or more stable capital flows have milder contractions in bank balance sheets and asset prices when external conditions tighten, reducing the benefit from active countercyclical MaPs.
  - Elasticity of the current account to movements in the real exchange rate:
    - Strong expenditure-switching responses to depreciation improve external balances, offsetting financial-channel depreciation effects and reducing recession risk; countries with low current-account elasticity gain more from countercyclical MaPs.
    - Under the dominant currency paradigm (DCP), countries with a larger share of exports invoiced in US dollars are likely to have a more muted current-account response to currency movements, reducing exchange-rate stabilization effectiveness.

### Empirical approach and main findings
- Uses local linear projections (LLP) to estimate country-specific monetary and macroprudential policy impulse responses to US monetary surprises (as in Iacoviello and Navarro, 2019).
- Estimates control for pre-shock policy instrument levels, domestic macro variables, and other exogenous global shocks.
- Finds remarkable heterogeneity in MaP impulse responses to US monetary surprises, enabling classification of countries into two clusters:
  - Countercyclical MaP countries: loosen (tighten) macroprudential stance when the US tightens (loosens).
  - Non-countercyclical MaP countries.
- The countercyclical MaP cluster is geographically well distributed and includes both advanced economies (AEs) and emerging market and developing economies (EMDEs).
- Determinants of membership in the countercyclical cluster:
  - The only significant determinant among considered country characteristics is the net foreign currency mismatch: the greater the net long currency mismatch, the smaller the probability that the country has countercyclical MaPs.
  - Interpretation: countries with negative currency mismatches (foreign currency liabilities > foreign currency assets) have more to gain from countercyclical MaPs.
- Macroeconomic outcomes by MaP cyclicality:
  - Countercyclical MaP countries exhibit stronger credit growth and inflation in the medium-term after US monetary tightening surprises.
  - Some evidence that countercyclical MaPs provide a limited short-term boost to monetary policy autonomy after the initial shock.

### Relation to existing literature
- Cross-country studies find MaPs effective at dampening credit cycles and reducing financial volatility.
- MaPs can have side effects on macroeconomic variables; countercyclical MaPs can reduce economic growth, especially in emerging markets.
  - Example: tightening LTV by 10 percentage points reduces GDP of emerging markets in the sample by approximately 1.1% after four years, with effects on inflation close to zero.
- Literature shows credit conditions in advanced economies are significant drivers of global financial flows; US monetary tightening leads to falling risky asset prices, rising bond spreads and retrenchments in capital flows (especially banking flows).
- The model reproduces risk-taking and pecuniary externality dynamics emphasized in the literature.
- Currency mismatch and large bilateral portfolio equity flows increase susceptibility to monetary policy spillovers; this paper confirms the importance of currency mismatch for exposure to US monetary policy shocks and provides conditions under which MaPs can be effective.

*Source: https://www.imf.org/-/media/files/publications/wp/2023/english/wpiea2023012-print-pdf.pdf*

### 2. Model

### 2. Model

### Overview
- Small-open economy with financial frictions subject to domestic and external shocks.
- Based on Gerali et al. (2010) (closed economy with financial intermediaries), augmented with external debt and trade sectors.
- Agents: households (savers), entrepreneurs (borrowers), banking sector, central bank.
- Central bank sets: policy interest rate and two macroprudential policy instruments — capital adequacy ratios (CARs) and loan-to-value ratios (LTVs).
- Two financial frictions (as in Gerali et al. (2010)):
  - Collateral constraints for domestic borrowers (depend on value of physical capital).
  - Costs to banks of deviating from a capital adequacy target.
- Model in discrete time with infinite horizon.

### Households
- Households maximize period utility from consumption of domestic final output and leisure.
- Household problem each period:
  - max_{C_{H,t},N_t,D_t} { E_0 ∑_{t=0}^∞ β_H^t [ C_{H,t}^{1−ρ_{C,H}} / (1−ρ_{C,H}) − N_t^{1+ρ_{N,H}}/(1+ρ_{N,H}) ] }
- Period budget constraint:
  - P_t C_{H,t} + D_t + T_t = w_t N_t + (1 + i_{t−1}^D) D_{t−1} / π_t
- Notation preserved:
  - C_{H,t} consumption of final good; N_t labor supply; ρ_{C,H} inverse intertemporal elasticity of substitution for consumption; ρ_{N,H} inverse Frisch elasticity; P_t domestic price level; D_t deposits; w_t real wage; i_t^D deposit rate; π_t inflation.
- Optimality conditions: consumption Euler equation and marginal rate of substitution equals marginal cost of consumption-leisure.

### Entrepreneurs
- Entrepreneurs borrow from banks to invest in capital goods, combine capital K_t and labor N_t to produce domestic intermediate good Y_t, and maximize lifetime utility.
- Entrepreneur problem:
  - max_{C_{E,t},B_t,K_{t+1},N_t} { E_0 ∑_{t=0}^∞ β_E^t [ C_{E,t}^{1−ρ_{C,E}} / (1−ρ_{C,E}) ] }
- Constraints:
  - Budget: Y_t + B_t = P_t C_{E,t} + w_t N_t + (1 + i_{t−1}^B) B_{t−1} / (1 + π_t) + q_t (K_{t+1} − (1−δ) K_t)
  - Production: Y_t = A_t K_t^α N_t^{1−α}
  - Collateralized borrowing constraint: (1 + i_t^B) B_t ≤ LTV_t q_t K_t (1−δ)
- Notation preserved:
  - C_{E,t} entrepreneur consumption; B_t borrowing; K_t physical capital; i_t^B borrowing rate; LTV_t maximum loan-to-value ratio; q_t price of capital good; A_t total factor productivity; ρ_{E,H} inverse intertemporal elasticity for entrepreneurs.
- Entrepreneur optimality (consumption Euler with multiplier on borrowing constraint):
  - C_{E,t}^{−ρ_{C,E}} − s_{E,t} = β_E E_t [ C_{E,t+1}^{−ρ_{C,E}} (1 + i_t^B) / (1 + π_{t+1}) ]  (Equation (1))
- s_{E,t} is Lagrange multiplier on borrowing constraint; when s_{E,t} > 0 constraint binds and tightens with falls in q_t or LTV_t.

### Trade
- Entrepreneurs export domestic intermediate output; households and entrepreneurs import foreign intermediate good.
- Single world market for domestic final good; producer currency pricing in baseline; domestic intermediate good is numeraire (price normalized to 1).
- Final consumption CES aggregator:
  - C_{t} = [ Λ (Y_t − EX_t)^ψ + (1−Λ) (IM_t)^ψ ]^{1/ψ}  (Equation (2))
- Notation: Y_t domestic intermediate output; EX_t exports; IM_t imports; Λ home bias parameter.
- Import demand:
  - IM_t = (1/(1−Λ))^{1/(1−ψ)} (z_t P_t)^{1/(1−ψ)} C_t  (Equation (3))
  - Implies import demand declines as real exchange rate z_t = E_t P_t^f rises or foreign price P_t^f rises.
- Export demand:
  - EX_t = (1/(1−Λ_f))^{1/(1−ψ_f)} z_t^{1/(1−ψ_f)} Y_t^f  (Equation (4))
  - Λ_f foreign home-bias parameter; ψ_f export elasticity parameter.
- Domestic price level (with domestic intermediate good as numeraire):
  - P_t = [ 1 + (1−Λ) (1−ψ) z_t^{1−ψ} / ψ ]^{ψ/(1−ψ)}  (Equation (5))
- Real exchange rate defined as z_t = E_t P_t^f; changes in z_t contribute contemporaneously to price inflation.

### Banks
- Banks: receive deposits D_t from households, borrow abroad B_t^f, lend to entrepreneurs B_t; price-takers in deposit and international lending markets, but have market power in domestic lending and charge a markup μ_B.
- Banks maximize profits minus quadratic cost for deviation of bank capital-to-loans ratio K_t^B / B_t from CAR_t:
  - max_{D_t,B_t^f,B_t} J_t^B = (1 + i_t^B) B_t − (1 + i_t^D) D_t − (1 + i_t^f) B_t^f [ ζ E_t[E_{t+1}]/E_t + (1−ζ) ] − K_t^B − (θ/2) (K_t^B / B_t − CAR_t)^2 K_t^B
- Balance sheet and bank capital law of motion:
  - B_t = D_t + K_t^B + B_t^f [ ζ E_t[E_{t+1}]/E_t + (1−ζ) ]
  - K_{t+1}^B = (1−δ_B) K_t^B + J_t^B
- Only a fraction (1−ζ) of foreign borrowing can be hedged; ζ share is unhedged and exposed to exchange rate movements.
- Two first-order conditions:
  - Lending rate determination (spread i_t^B − i_t^D):
    - i_t^B = −θ (K_t^B / B_t − CAR_t) K_t^B / B_t^2 + i_t^D + μ_B  (Equation (6))
    - Lending rate rises when K_t^B / B_t is low relative to CAR_t.
  - Modified UIP-like condition (spread between domestic deposit rate and foreign borrowing rate):
    - 1 + i_t^D = (1 + i_t^f) [ ζ E_t[E_{t+1}]/E_t + (1−ζ) ]  (Equation (7))
    - Correlation of exchange rate expectations with interest differentials increases with ζ (share of unhedged foreign borrowing).
- Exogenous supply of foreign credit to banks:
  - B_t^f = γ B̄ ( E_t[E_{t+1}]/E_t )^{σ_1} (1 + i_t^f)^{σ_2}  (Equation (8))
  - Parameterization: σ_2 < 0 (foreign credit rises as foreign interest rate falls); σ_1 < 0 (foreign credit rises as domestic currency appreciates). γ is scaling parameter.

### Central Bank
- Instruments: deposit rate i_t^D (monetary policy), LTV_t and CAR_t (macroprudential policy).
- Monetary policy: Taylor Rule (interest rate gradually responds to inflation and output deviations):
  - 1 + i_t^D = (1 + i_{ss}^D)^{(1−ρ_i)} (1 + i_{t−1}^D)^{ρ_i} ( (π_t / π_{ss})^{φ_π} (Y_t / Y_{ss})^{φ_Y} )^{ρ_i}  (Equation (9))
- Macroprudential policy rules:
  - LTV rule:
    - LTV_t = LTV_{ss}^{(1−ρ_{LTV})} LTV_{t−1}^{ρ_{LTV}} ( (B_t / B_{ss})^{φ_{B,LTV}} (q_t / q_{ss})^{φ_{q,LTV}} )^{ρ_{LTV}}  (Equation (10))
  - CAR rule:
    - CAR_t = CAR_{ss}^{(1−ρ_{CAR})} CAR_{t−1}^{ρ_{CAR}} ( (B_t / B_{ss})^{φ_{B,CAR}} (q_t / q_{ss})^{φ_{q,CAR}} )^{ρ_{CAR}}  (Equation (11))
- LTV_t is a MaP on credit demand; CAR_t is a MaP on credit supply.
- Baseline assumption: policy vector { i_t^D, LTV_t, CAR_t } is uncoordinated (three separate rules).

### Exogenous Shocks
- Four exogenous shocks, each following AR(1):
  - (i) domestic productivity A_t
  - (ii) foreign demand Y_t^f
  - (iii) domestic markups μ_t
  - (iv) foreign interest rates i_t^f
- Focus of analysis: shock to foreign interest rates i_t^f.
- AR(1) for foreign interest rate:
  - i_t^f = 1 − ρ_{i_f} + ρ_{i_f} i_{t−1}^f + ε_{t}^{i_f}  (Equation (13))

*Source: IMF working paper — Section 2. Model*

### 3. Static Model

### 3. Static Model

### Model setup and purpose
- Introduces a simplified static version that replicates the baseline model’s steady state properties and isolates interactions between shocks to international financial conditions and domestic equilibrium.
- Static model contains three markets: foreign borrowing by banks, domestic borrowing, and domestic deposits.
- Two sources of financial frictions (bank capital adequacy costs and collateralized borrowing constraints) directly affect the three financial markets, enabling comparative static analysis.

### Key equilibrium conditions and equations
- Static UIP (steady state):  
  1+ i_d = 1+ i_f^E  (Equation 14)  
  - 퐸 represents the steady state change in exchange rate so that it equals interest rate differentials in equilibrium.

- Foreign credit supply (adapted from dynamic model):  
  B_f = γ B̅ (E)^{σ1} (1+ i_f)^{σ2}  (Equation 15)

- Market clearing for foreign borrowing by banks:  
  B_f = B − D  (Equation 16)  
  - Assumes B_f > 0 (country is a net debtor). Exchange rate E adjusts to clear this market ceteris paribus.

- Domestic lending rate (bank side, CAR costs):  
  i_b = i_d − θ (K_B / B − CAR) (K_B / B)^2  (Equation 17)  
  - For given i_D and K_B, loan rates i_b are positively related to total loans B because banks incur greater costs of deviating from CAR to make more loans.

- Entrepreneur borrowing demand (static Euler):  
  1+ s_E (B, q_k)^{λ_E (R_k)} = β_E (1+ i_b)  (Equation 18)  
  - λ_E(R_k) is the shadow price of entrepreneurs’ consumption, assumed increasing in R_k.
  - s_E(B, q_k) is the shadow price of borrowing for entrepreneurs, assumed decreasing in B and in q_k.

- Household deposits (static Euler analogue):  
  Λ_H(D) = β_H (1+ i_d)  (Equation 19)  
  - λ_H(D) is the shadow price of household consumption, assumed increasing in deposits D.

- Equilibrium defined as prices {E, i_b, i_d} and quantities {B_f, B, D} solving Equations (14)–(19) with other parameters exogenous.

### Combined foreign credit market identity
- Imposing market clearing and combining Equations (15) and (16):  
  γ B̅ (E)^{σ1} (1+ i_f)^{σ2} = B(i_b, K_B, q_K, R_K) − D(i_d)  (Equation 20)  
  - LHS: foreign credit supply. RHS: foreign credit demand = total debt (depends on i_b, K_B, q_K, R_K) minus domestic deposits (depends on i_d).

### Three channels through which shocks affect foreign borrowing
- Investment channel (via i_d):  
  - An increase in the deposit rate i_d raises household deposits (Equation 19) and induces banks to raise loan rates (Equation 17), reducing demand for domestic borrowing. Net effect: foreign borrowing falls; capital/financial account narrows (S−I gap shrinks).

- Net exports channel (via R_K):  
  - Exchange rate appreciation raises relative domestic output price, reduces net exports, lowers total output/income and reduces R_K, leading to lower credit demand. Associated with worsening current account.

- Balance sheet channel (financial frictions amplify effects):  
  - Two frictions create balance sheet channels that operate in addition to the investment and net exports channels.

  (i) Bank-side friction (deviations from CAR):  
  - A reduction (increase) in K_B raises (lowers) costs of deviating from CAR per Equation (17), causing banks to reduce (increase) credit supply to entrepreneurs, lowering (raising) investment and output.

  (ii) Borrower-side friction (collateralized LTV constraints):  
  - Borrowers’ demand constrained by LTV; a fall in asset prices q_K tightens borrowing constraints, reducing credit demand and generating a financial accelerator.

  - Example: an increase in foreign interest rate i_f reduces bank profits and credit supply; if i_f rise generates depreciation pressure via UIP, foreign-currency liabilities rise for banks with net foreign liabilities, enlarging balance sheet effects and producing larger reductions in net borrowing from abroad than under the exchange rate channel alone.

### Comparative statics and qualitative results
- Shifts in credit supply and demand:  
  - From Equation (17): an increase in i_d shifts bank lending curve leftwards; a fall in K_B shifts bank lending curve leftwards.  
  - From Equation (18): a fall in q_K shifts entrepreneur borrowing curve leftwards; a fall in R_K shifts entrepreneur borrowing curve leftwards.

- Balance sheet channels interact with investment and exchange rate channels to compound initial shock effects on credit and output.

### Proposition 1 (static model result)
- Proposition 1: Under the static model, a rise in the foreign interest rate leads to a decline in domestic credit, if the net export channel is assumed to be zero. Further, the presence of bank and entrepreneur balance sheet channels increases the magnitude of the impact of the foreign interest rate change on domestic credit. A countercyclical MaP policy, defined as an inverse relationship between CAR or LTV with B, cushions the decline of credit in the economy. Conversely, procyclical MaPs magnify the decline in total debt.  
  - Proof: See Appendix.

- Intuition and implications:  
  - Countercyclical MaP regime = looser MaP settings (higher LTV and lower CAR) when total debt declines following a positive foreign interest rate shock.  
  - Higher LTV reduces the extent borrowing constraints bind for entrepreneurs; lower CAR reduces bank costs from increasing borrowing when bank capital falls.  
  - By loosening constraints, countercyclical MaPs reduce the decline in domestic credit when i_f rises by attenuating balance sheet effects on both lender and borrower sides, thereby moderating leftward shifts in domestic credit supply and demand.

*IMF Working Papers — 3. Static Model*

### 4. Model Simulations

### 4. Model Simulations

### Model setup and baseline calibration
- The dynamic model is log-linearized around its steady state, with a solution method akin to the flexible-price equilibrium in Gerali et al. (2010).
- Baseline calibrations:
  - Share of foreign-currency denominated debt: 휁 = 0.3.
  - Steady state bank capital to asset ratio: 0.10.
  - Entrepreneur’s loan-to-value ratio: 0.55.
  - Foreign GDP parameter 푌푓 is set very large so the domestic country is small relative to the rest of the world.
  - Deposit rate in steady state 푖푠푠퐷 is calibrated to exceed foreign borrowing rate 푖푠푠푓 so the country is a net borrower.
  - Standard household/entrepreneur/worker preference parameters (훽퐻, 훽퐸, 휌푁) and production parameters (훼, 훿) follow values from small open economy literature (e.g., Guerrieri et al., 2013).
- Shock specification (Figure 1 notes):
  - The interest rate shock imparts a 1%-pt increase to 휖푡푓 with an autocorrelation coefficient of 휌푖푓 = 0.4.
  - All other parameters as in the baseline model calibration.

### Baseline (no-MaP) response to a positive foreign interest rate shock 푖푡푓
- Under the no-MaP baseline:
  - The central bank varies only the domestic policy rate; 퐿푇푉푡 and 퐶퐴푅푡 are not used (set to zero response).
  - The country is a net external borrower (퐵푓 strictly positive) and holds a net short foreign currency position (incomplete currency hedging).
- Dynamics following a positive shock to 푖푡푓:
  - Increase in foreign borrowing cost → sharp decline in total debt.
  - Falling debt → falling investment and output on impact.
  - Central bank initially reduces policy rates in response to falling output.
  - Currency depreciation increases import prices → higher inflation → central bank raises policy rate in the period after the shock.
  - Depreciation raises net exports, acting as an automatic stabilizer for output.
  - Rising external borrowing costs reduce bank profitability → bank capital falls → bank leverage increases.
  - Higher domestic lending rates (due to temporarily higher deposit rates and foreign borrowing costs) lower investment demand and lead to a fall in asset prices.

### Countercyclical MaPs versus no MaPs
- MaP response specification (Figure 1 notes): under the countercyclical MaPs regime:
  - 휙B,LTV = −0.5
  - 휙q,LTV = −0.5
  - 휙B,CAR = 0.5
  - 휙q,CAR = 0.5
  - Under the no MaPs regime, all four parameters are set to 0.
- Mechanisms and outcomes:
  - As total debt and asset prices fall, authorities raise 퐿푇푉푡 and lower 퐶퐴푅푡 per MaP response functions.
  - Higher 퐿푇푉푡 loosens borrowing constraints on domestic borrowers.
  - Lower 퐶퐴푅푡 reduces costs of increasing bank lending (conditional on bank capital levels).
  - Both policies mitigate the fall in domestic lending and investment, reducing the fall in output relative to the no-MaP case.
  - Countercyclical MaPs constrain volatility of macroeconomic and financial outcomes around the steady state in response to shocks to 푖푡푓.
  - Trade-off: MaPs can drag on growth during periods of loose global financial conditions while reducing the depth of recessions during periods of tightness.

### Key country parameters and heterogeneous responses
- Three country parameters highlighted for sensitivity to shocks to 푖푡푓:
  1. 휁 — share of foreign-currency borrowing within total net borrowing.
  2. 훾 — elasticity of a country’s foreign credit supply to a change in foreign interest rate.
  3. 휓푓 — elasticity of export demand with respect to the real exchange rate.
- Effects by parameter:

  - 휁 (share of foreign-currency debt)
    - Larger 휁 amplifies the impact of a foreign interest rate shock on bank liabilities via currency depreciation increasing foreign-currency liabilities.
    - Implications:
      - Banks must reduce leverage more aggressively → larger decline in bank lending.
      - Domestic lending rates rise → asset prices fall → borrowing constraints tighten → overall borrowing declines.
    - Simulation note (Figure 2): shock modeled as a 1% positive increase in 휖푡푓; varying 휁 (high 휁 increases share of foreign-currency debt) shows larger declines in total borrowing and investment, larger falls in bank capital, and larger rises in bank leverage when 휁 is high.

  - 훾 (responsiveness of foreign credit supply)
    - Higher 훾 means foreign interest rate changes cause larger contractions in foreign credit supply (see Equation 8).
    - Implications:
      - Sharp contraction in foreign credit supply → large declines in bank profits and bank lending.
      - Strong balance sheet effects → larger fall in total debt, investment, and output.
    - Simulation note (Figure 3): shock modeled as a 1% positive increase in 휖푡푓; varying 훾 shows that high 훾 produces sharp declines in foreign credit supply and pronounced increases in domestic borrowing costs for banks.

  - 휓푓 (responsiveness of exports to the real exchange rate)
    - 휓푓 governs export demand sensitivity to real exchange rate changes.
    - Mechanism:
      - Flexible exchange rate depreciation raises current account balance; high 휓푓 amplifies net export gains that offset contractionary investment effects.
    - Implications:
      - High 휓푓 → larger increases in net exports for a given foreign interest rate increase → positive effects on output and consumption.
      - With higher production and import substitution, inflationary pressures from depreciation are dampened; investment and asset price declines are mitigated.
      - Low 휓푓 (e.g., exports invoiced in a dominant currency) → net export channel weak → balance sheet channels dominate → output losses.
    - Simulation note (Figure 4): shock modeled as a 1% positive increase in 휖푡푓; varying 휓푓 shows that the country with higher 휓푓 can experience a positive overall output response despite identical initial depreciation.

- Summary of comparative effects:
  - High 휁 and high 훾 → large balance sheet effects from external monetary shocks: sharp curtailment of total debt, higher bank leverage, reduced asset prices.
  - High 휓푓 → stronger exchange rate channel that improves current account and insulates output.

### Implications for macroprudential policy design
- MaP authority objective and decision variables:
  - Authority maximizes a mean-variance utility function V(·) = 훼1 μΔY − 훼2 (휎ΔY2 + 휎ΔB2), choosing φMAP = {휙LTV,b, 휙LTV,q, 휙CAR,b, 휙CAR,q}.
  - μΔY = Εi f [Yt − Y_ss] is mean deviation of output from steady state under shocks.
  - 휎ΔY2 = Var i f [Yt − Y_ss]; 휎ΔB2 = Var i f [Bt − B_ss].
- Comparative statics and policy tradeoffs:
  - dμΔY/d휁 > 0 and dμΔY/d훾 > 0: countries with high 휁 or high 훾 derive greater mean growth benefits from unexpected loosening of external conditions.
  - Higher φMAP (more countercyclical MaPs) dampens positive mean growth effects from inflows; formally d2 μΔY / d휁 dφMAP < 0.
  - Volatility increases with 휁 and 훾: d휎ΔY2/d휁 > 0 and d휎ΔB2/d휁 > 0; higher 휓푓 mitigates output volatility: d휎ΔY2/d휓푓 < 0.
  - Countercyclical MaPs reduce volatility: d2 휎ΔY2 / d휁 dφMAP < 0.
  - Tightening MaPs for countries with high 휁, high 훾, and low 휓푓 more effectively damps the growth–stability tradeoff.
- Model-implied example (Figures 5–6):
  - Country A: higher 휁, higher 훾, lower 휓푓 — experiences a steeper growth–stability tradeoff from cross-border capital flows than Country B (lower 휁, lower 훾, higher 휓푓).
  - Simulations vary φMAP over ranges: 휙LTV = (−1.5, 0.5) and 휙CAR = (−0.5, 1.5); horizontal axis shows absolute value for all four MaP tightness parameters, with higher values indicating tightening.
  - Low φMAP (procyclical MaPs) associated with higher average GDP growth from negative foreign interest rate shocks but higher volatility in GDP and debt.
  - Country A sees larger reductions in 휎ΔY2 + 휎ΔB2 as φMAP rises than Country B; both countries maximize welfare for approximately the same φMAP in simulations, but Country A gains more marginally from MaP tightening over a wide region.
  - Note: the model does not imply that countries with higher 휁 and 훾 necessarily have higher optimal φMAP; they face a steeper tradeoff—tighter MaPs impose larger negative growth impacts while sharply reducing volatility. For low φMAP values, stability gains from countercyclical MaPs can outweigh growth costs for high 휁 and 훾 countries.

*Italic: Source: IMF Working Paper — 4. Model Simulations (wpiea2023012-print-pdf).*

### 6.2 Identification and Instrumental Variables

### 6.2 Identification and Instrumental Variables

### Identification strategy and local projections
- For each country j, policy response functions are estimated using local projection to estimate impulse response functions (Jordà, 2005) to shocks on variables exogenous to their economies.
- Estimation equation for the response to a US policy rate itUS:
  - The conditional expectation is modeled as:
    - E[Xjt+k | Xjt−1, Zjt−1, itUS] = Xjt−1 θjkX + Zjt−1 φjkZ + itUS θjkUS + VIXt θjkVIX + flowst θjkflows
  - Xjt+k is a policy variable observed k periods ahead (e.g., domestic interest rate, cumulative macroprudential net tightenings).
  - Zjt−1 includes lagged domestic macroeconomic variables (inflation, GDP, credit-to-GDP and real exchange rate) and external drivers (US monetary surprises, VIX and global capital flows).
  - Impulse response function to a US monetary surprise is the sequence of estimated θjkUS for k = 1 to N.
- The specification implies that macroprudential and monetary policy do not react to contemporaneous domestic macroeconomic variables.
- Sample: 40 countries are analyzed.

### Macroprudential stance measure and instruments
- Macroprudential stance is measured using a widely used indicator of net tightenings/loosings (discussion notes limitations: does not account for magnitude and is not suited for cross-country comparisons about the level of macroprudential stance).
- The 17 macroprudential instruments included are:
  - countercyclical capital buffer, capital conservation buffer, capital requirement for banks, limits on bank leverage, loan loss provision requirements, limits on growth or volume of credit by banks, loan restrictions, limits on foreign currency lending, limits to loan-to-value ratios, limits to the debt-service-to-income and the loan-to-income ratios, tax and levies on specific transactions, minimum requirements for liquidity measures, limits to the loan-to-deposit ratio, limits on net or gross open foreign exchange positions, reserve requirements for macroprudential purposes, measures to mitigate risks from global and domestic systemically important financial institutions (SIFIs), and other macroprudential measures not captured in the previous categories.
- Caveats noted: the indicator captures direction (tighten/loosen) but not intensity; it aggregates different instruments that may have heterogeneous effects.

### Instrumental variables and controls
- Estimations control for up to 2 lags of domestic variables in SUR specifications in some exercises (interest rate, number of net tightening macroprudential actions, credit-to-GDP, GDP growth, REER and inflation), plus external shocks (US monetary policy, VIX and global capital flows), seasonal and country fixed effects.
- Confidence intervals reported use 66 percent intervals in selected figures.

---

### 7. Results — Heterogeneity in policy responses
- There is significant heterogeneity in countries’ monetary policy and macroprudential responses to US monetary policy surprises.
- Median country response to a 1 percentage point US policy tightening surprise:
  - An increase in their nominal policy rate.
  - A slight tightening of macroprudential settings.
- Examples of country heterogeneity (responses to a 1 percentage point US surprise):
  - Russia: implies one tightening of macroprudential instrument on net 4 quarters after the US surprise.
  - Turkey: implies 1.5 net tightening actions on average over the same 4-quarter period.
- Figure summaries:
  - Figure 7 shows median and the 10-, 20-, 80- and 90-percentiles of IRFs for 40 countries.

### 7.1 Clusters of Macroprudential Policy Styles
- Classification rule for counter-cyclical macroprudential response:
  - First filter: average of IRF of the number of MAP tightening actions from 0 to 4 quarters is negative and its 66 percent confidence interval does not include zero.
  - Second filter: exclude countries with less than 10 adjustments in macroprudential settings over the sample period.
  - First criterion selects 11 countries; applying the second criterion drops Chile (only made 2 adjustments), yielding 10 countries classified as having counter-cyclical macroprudential policies.
- Countries classified as having counter-cyclical macroprudential response (10):
  - Belgium
  - Finland
  - Indonesia
  - Israel
  - Malaysia
  - Poland
  - Spain
  - Sweden
  - Turkey
  - United Kingdom
- Other countries (30) listed in the source are not classified as counter-cyclical by this rule.
- Note on classification rule wording: countries are classified as having counter-cyclical macroprudential style if the average IRF from 0-4 quarters is negative and greater than one standard error.

### 7.2 Determinants of macroprudential policy response (probit analysis)
- Method: probit model for macroprudential style using a cross-section of 40 countries. Variables (definitions referenced in Table E.2 in Annex) include:
  - Sensitivity of net inflows to US monetary surprises (proxy for σ1 in equation (8))
  - Sensitivity of exports to real exchange rate (proxy for ψf in equation (4))
  - Volatility of net private capital flows as percent of GDP
  - External debt liabilities in foreign currency to GDP as percent of GDP (Benetrix, 2019)
  - Currency mismatches as percent of GDP (Benetrix, 2019)
- Key reported coefficients (from Table 2; standard errors in square brackets; variables standardized to zero mean and unitary standard error; bold indicates significance at the 10% level):
  - Currency mismatch as % of GDP: 0.641 [0.292] (column shown) and 0.612 [0.268] in another specification.
  - Sensitivity of net inflows to US monetary surprises: estimates reported include -0.070 [0.231], -0.108 [0.250], -0.038 [0.221] in different columns (not significant).
  - Sensitivity of exports to real exchange rate: estimates reported include 0.183 [0.232], 0.150 [0.255], 0.184 [0.232] (not significant).
  - Volatility of private capital flows as % of GDP: 0.186 [0.227], 0.217 [0.251], 0.150 [0.212] (not significant).
  - External debt liabilities in foreign currency (% GDP): 0.026 [0.264], -0.058 [0.239] (not significant).
  - Number of observations in reported regressions: 40, 39, 40, 40, 40, 39, 39 (by column).
- Interpretation of results:
  - Countercyclical style is not correlated with sensitivity of net inflows to US monetary surprises, sensitivity of exports to real exchange rate, nor volatility of net private capital flows as % of GDP in the multivariate specifications.
  - Currency mismatch as % of GDP is the only statistically significant variable in the full set: a positive coefficient implies countries that are net short on foreign currency (balance sheet deteriorates when currency depreciates) are more likely to adopt countercyclical macroprudential style.
  - Simple regressions with one explanatory variable yield similar findings for currency mismatch.
- Economic intuition:
  - A net short position in foreign currency increases balance sheet vulnerability to depreciation; the financial channel of exchange rates implies depreciation weakens domestic balance sheets and can propagate negative effects.
  - Evidence is consistent with countries using countercyclical macroprudential policies to mitigate these balance-sheet effects following US monetary tightening.
- Caveats:
  - Results should be interpreted considering small sample size and measurement errors in some estimated dependent variables.

### 7.3 Different responses to a US monetary policy surprise (system SUR local projections)
- Estimation approach: local linear projections estimated in a system of seemingly unrelated regressions (SUR) to account for joint determination of monetary and macroprudential policy.
- Policy response differences (countercyclical countries vs. others):
  - Macroprudential stance: countercyclical countries loosen macroprudential stance on net in the aftermath of surprise US monetary tightening relative to other countries.
  - Monetary policy path differences:
    - Immediately after the US surprise, countercyclical countries have less tight monetary policy.
    - After 4 months, countercyclical MAP countries have tightened interest rates by about 15 basis points more than the other countries.
    - No differences in interest rate response after 8 quarters.
    - Interpretation: countercyclical macroprudential style appears to provide a limited boost to monetary policy autonomy over a very short term; countries take longer to adjust policy interest rates, slightly overshoot after 1 year, but converge after 2 years.
- Domestic macroeconomic outcomes differences:
  - Credit-to-GDP: countercyclical macroprudential style countries show relatively faster growth in credit-to-GDP after a US surprise, with the difference peaking at about 8 to 10 quarters after the shock.
  - GDP: no significant differences in the path of GDP between clusters.
  - Inflation: initially lower in countercyclical style countries, but in cumulative terms there is no difference over a 2-year horizon after the shock.
- Mechanism and model consistency:
  - Countercyclical MaPs (acting on credit supply or demand) dampen balance sheet effects of unexpected foreign interest rate increases, supporting lending capacity of banks and borrowing capacity of domestic borrowers.
  - By reducing balance-sheet-driven depreciation pressures, countercyclical MaPs reduce upward pressure on domestic interest rates and imported inflation, allowing greater short-term monetary policy flexibility.
- Normative implications from the model:
  - Countries net short on foreign currency debt or holding large shares of unhedged foreign currency-denominated debt derive greater benefits from a more countercyclical MaP stance.
  - Empirical evidence (Table 2) provides preliminary support: countries net short on foreign currency debt are more likely to adopt countercyclical MaPs.
  - No similar evidence was found for other country variables predicted by the model to affect MaP stance.

*Source: IMF Working Paper — Section 6.2 and Sections 7–7.3 (Identification, local projections, cluster classification, probit determinants, and SUR local projection results) from the provided PDF content.*

### 8. Conclusions

### 8. Conclusions

### Summary of main findings
- MaPs can have significant impacts when a small-open economy with financial frictions is hit by external financial shocks.
- Policymakers face a tradeoff between supporting growth during periods of capital inflows and minimizing economic impacts in the event of a capital flow reversal shock.
- A more aggressive countercyclical MaPs setting:
  - limits growth during normal times, but
  - limits economic damage during reversals.
- Welfare implications of MaPs stance depend on country characteristics:
  - Countries with high shares of foreign currency debt, high elasticity of capital flows to the real exchange rate, and low elasticity of the current account to the real exchange rate benefit most from countercyclical MaPs.

### Empirical evidence (panel of 40 countries)
- Countries are classified into two clusters by empirical macroprudential style: countercyclical and non-countercyclical MaP countries.
  - Countercyclical MaP countries are those that loosen macroprudential stance when the US tightens monetary policy.
- Empirical contrasts the year after the impact of the shock:
  - Countercyclical MaP countries have lower domestic interest rates.
  - Countercyclical MaP countries have higher aggregate credit.
  - Countercyclical MaP countries have lower inflationary responses.
- Countries with large negative currency mismatches (liabilities larger than assets in foreign currency) are more likely to use countercyclical macroprudential policies—indicative evidence of an optimal response in this dimension.

### Model insights and transmission channels
- Balance-sheet channels amplify the impact of a foreign interest rate shock in the static model:
  - Bank capital 퐾퐵 is given by Equation (A1): 퐾퐵 = (1+푖푏)퐵 − (1+푖푑)퐷 − (1+푖푓)퐵푓 − 휃/2 (퐾퐵/퐵 − 퐶퐴푅)^2 퐾퐵.
  - Asset prices are governed by a Tobin’s q–style relation in Equation (A2): 퐼(푅퐾)퐾 = (푞퐾 − 1) − 푖푏 ∗ 퐿퐸푉.
- Static comparative statics on foreign interest rate 푖푓:
  - Supply of domestic credit 퐵푠 shifts left when 푖푓 rises: 푑퐵푠/푑푖푓 < 0.
  - Demand for domestic credit 퐵푑 also falls via entrepreneur balance-sheet effects: overall demand response includes terms tied to 푞퐾 where 휕푞퐾/휕푖푓 < 0 given 휕푖푏/휕푖푓 > 0.
  - A countercyclical MaP (where 푑퐵/푑퐶퐴푅 < 0 or 푑퐵/푑퐿푇푉 < 0) implies 푑^2퐵/(푑푖푓 푑퐶퐴푅) > 0, i.e., raising 퐶퐴푅 makes the negative impact of a foreign interest rate shock on borrowing more acute in the comparative statics sense described.
- In a dynamic baseline model with financial frictions:
  - A positive domestic price markup shock (1% positive increase in 휖푡휇) causes output to decline, raises inflation temporarily, and induces central bank policy rate increases.
  - Higher policy/deposit rates cause currency appreciation via UIP, increase net capital inflows, and reduce net exports.
  - Financial frictions: higher domestic rates reduce bank profits and bank capital, shifting down domestic credit supply; falling asset prices tighten entrepreneur borrowing constraints, reducing credit demand; combined effects produce a sharp fall in borrowing and investment absent MaPs.
  - Under an aggressive countercyclical MaP response to total debt and asset prices:
    - MaPs can raise lending and borrowing on impact (total debt rises rather than declines), and strongly mitigate the decline in asset prices.
    - However, higher credit demand for external borrowing requires a larger currency appreciation and higher policy/deposit rate to clear credit markets, which can put downward pressure on investment and output via investment and exchange rate channels.
    - Exceptionally aggressive countercyclical MaP regimes can lead to larger negative impacts on output after the initial shock relative to a no-MaP baseline.

### Key calibration parameters and values (Table B1 baseline calibration)
- β퐻 Household discount rate: 0.996
- β퐸 Entrepreneur discount rate: 0.975
- ρ푁 Frisch elasticity of labor supply: 1
- 퐿푇푉 Fixed LTV ratio: 0.55
- 푚푐푡휇 Domestic output good markup: 6/5
- α Domestic output good producer Cobb-Douglas parameter: 0.2
- κ Physical capital good producer adjustment cost parameter: 5
- 훿 Physical capital depreciation rate: 0.05
- 휋푠푠 Steady state domestic inflation: 1
- 푖푠푠퐷 Steady state deposit rate: (1/0.996 – 1)
- 휃 Bank 퐶퐴푅 adjustment cost parameter: 11
- 퐶퐴푅 Fixed capital adequacy ratio: 0.10
- 휇퐵 Bank loan rate markup: 0.005
- 훿퐵 (1/0.996 – 1) + 0.005/0.12
- 휌푖 Adjustment parameter for interest rate monetary policy rule: 0.77
- 휙휋 Weight on inflation gap for monetary policy rule: 0.5
- 휙푌 Weight on output gap for monetary policy rule: 2.5
- 휌퐴 Technology shock autocorrelation parameter: 0.95
- 휌휇 Markup shock autocorrelation parameter: 0.5
- 휌푖푓 Foreign interest rate autocorrelation parameter: 0.4
- 훾 Responsiveness of foreign credit supply to foreign interest rate: 0.3
- 퐵̅ Foreign credit supply stock: 0.9
- 휓 Price elasticity of foreign credit supply: 0.3
- 휁 Share of bank’s unhedged foreign currency debt: 0.3
- Λ Home bias parameter for domestic consumers: 0.99
- Λ푓 Home bias parameter for foreign consumers: 0.05
- 휓 Parameter for elasticity of domestic imports to real exchange rate: 0.5
- 휓푓 Parameter for elasticity of domestic exports to real exchange rate: 0.01
- 푌푡푓 Foreign GDP: Exp(-0.8)

### Policy implications and considerations
- Countercyclical MaPs can reduce the economic damage from capital flow reversals but may restrain growth during normal times.
- Optimal MaP stance depends on country-specific structural characteristics:
  - High external liability in foreign currency and large negative currency mismatches increase the potential gains from countercyclical MaPs.
  - Sensitivities of capital flows and the current account to the real exchange rate matter for the welfare tradeoff.
- Implementation nuance:
  - MaP instruments (e.g., CAR, LTV) have distinct balance-sheet effects; countercyclical settings where 푑퐵/푑퐶퐴푅 < 0 or 푑퐵/푑퐿푇푉 < 0 mitigate some channels but can interact with monetary policy and exchange rates in complex ways.
  - Aggressive countercyclical MaP responses can backfire through exchange rate and monetary-policy-induced investment channels, potentially worsening output outcomes after the initial shock.

*Source: wpiea2023012-print-pdf - 8. Conclusions*

### References

### References

### Cited works
- Adrian, T., Christopher J. Erceg, Jesper Lindé, Pawel Zabczyk, Jianping Zhou, 2020. “A Quantitative Model for the Integrated Policy Framework,” IMF Working Paper 20/122.
- Adler, Gustavo, Camila Casas, Luis Cubeddu, Gita Gopinath, Nan Li, Sergii Meleshchuk, Carolina Osorio Buitron, Damien Puy, and Yannick Timmer, 2020. “Dominant Currencies and External Adjustment”, IMF Staff Discussion Note 20/05.
- Agenor, Pierre and L. Pereira da Silva, 2019. “Integrated inflation targeting – Another perspective from the developing world”, Bank of International Settlements.
- Aizenman, Joshua, Menzie Chinn and Hiro Ito, 2008. “Assessing the Emerging Global Financial Architecture: Measuring the Trilemma’s Configurations Over Time,” NBER Working Paper 14533.
- Aizenman, Joshua, Menzie Chinn and Hiro Ito, 2020. “Financial Spillovers and Macroprudential Policies,” Open Economies Review 31: 529–563.
- Alam, Zohair, Adrian Alter, Jesse Eiseman, Gaston Gelos, Heedon Kang, Machiko Narita, Erlend Nier, and Naixi Wang, 2019. “Digging Deeper—Evidence on the Effects of Macroprudential Policies from a New Database,” IMF Working Paper 19/66.
- Angelini, Paolo, Stefano Neri and Fabio Panetta, 2014. “The Interaction between Capital Requirements and Monetary Policy”, Journal of Money, Credit and Banking 46:6, September 2014: 1073-1112.
- Avdjiev, Stefan, Catherine Koch and Hyun Song Shin, 2017. “Exchange rates and the transmission of global liquidity”, Bank of International Settlements, mimeo.
- Avdjiev, Stefan, Stephan Binder and Ricardo Sousa, 2017. “External debt composition and domestic credit cycles”, Bank of International Settlements Working Paper No. 627.
- Barroso, João B. R. Blanco, Douglas K. Godoy de Araujo and Rodrigo B. Gonzalez, 2020. “Loan-to-value policy and housing finance: Effects on constrained borrowers,” Journal of Financial Intermediation, Vol. 42, April 2020.
- Basu, S., Boz, E., Gopinath, G., Roch, F. and Unsal, F., 2020, “A Conceptual Model for the Integrated Policy Framework”, IMF Working Paper, WP/20/121.
- Benigno, Gianluca, Huigang Chen, Christopher Otrok, Alessandro Rebucci and Eric R. Young, 2013. “Financial Crises and Macro-prudential Policies,” Journal of International Economics Vol. 89, March 2013, pp. 453-470.
- Bergant, K. and K. Forbes, 2021, “Macroprudential Policy during COVID-19: The Role of the Policy Space”, mimeo.
- Blanchard, Olivier, Gustavo Adler and Irineu de Carvalho Filho, 2015. “Can Foreign Exchange Intervention Stem Exchange Rate Pressures from Global Capital Flow Shocks?”, NBER Working Paper 21427.
- Blanchard, Olivier, Jonathan D. Ostry, Atish R. Ghosh and Marcos Chamon, 2017. “Are Capital Inflows Expansionary or Contractionary? Theory, Policy Implications, and Some Evidence,” IMF Economic Review, Palgrave Macmillan; International Monetary Fund, vol. 65(3), pages 563-585, August.
- Bordo, Michael D. and Christopher M. Meissner, 2006. “The role of foreign currency debt in financial crises: 1880–1913 versus 1972–1997,” Journal of Banking & Finance Vol. 30, Issue 12, December 2006, pp. 3299-3329.
- Boz, Emine, Camila Casas, Georgios Georgiadis, Gita Gopinath, Helena Le Mezo, Arnaud Mehl and Tra Nguyen et al., 2020. “Patterns in Invoicing Currency in Global Trade,” IMF Working Paper 20/126.
- Brandao-Marques, L., Gelos, G., Narita, M. and Nier, E., 2020, “Leaning Against the Wind: A Cost-Benefit Analysis for an Integrated Policy Framework”, IMF Working Paper, WP/20/123.
- Brunnermeier, Markus and Yuliy Sannikov, 2014, “A Macroeconomic Model with a Financial Sector”, American Economic Review 104(2): 379-421.
- Bruno, Valentina and Hyun Song Shin, 2012. “Capital Flows and the Risk-Taking Channel of Monetary Policy,” BIS Working Paper No. 400.
- Caballero, Ricardo J & Alp Simsek, 2019. “Prudential Monetary Policy,” NBER Working Papers 25977, National Bureau of Economic Research, Inc.
- Cantú, Carlos, Leonardo Gambacorta and Ilhyock Shim, 2020. “How Effective are Macroprudential Policies in Asia-Pacific? Evidence from a Meta-Analysis,” BIS Paper No. 110b, March 2020.
- Cerutti, Eugenio, Stijn Claessens and Luc Laeven, 2017. “The use and effectiveness of macroprudential policies: New evidence,” Journal of Financial Stability Vol 28, issue C, pp. 203-224.
- Cerutti, Eugenio, Stijn Claessens and Andrew K. Rose, 2019. “How Important is the Global Financial Cycle? Evidence from Capital Flows,” IMF Economic Review 67:24-60.
- De Bock, Reinout and Irineu de Carvalho Filho, 2015. “The Behavior of Currencies During Risk-off Episodes,” Journal of International Money and Finance 53: 218-234.
- Di Giovanni, Julian, Kalemli-Ozcan, Sebnem, Mehmet Fatih Ulu and Yusuf Soner Baskaya, 2021. “International Spillovers and Local Credit Cycles,” Review of Economic Studies forthcoming.
- Dedola, Luca, Giulia Rivolta and Livio Stracca, 2017. “If the Fed sneezes, who catches a cold?” Journal of International Economics 108: S23-S41.
- Ehrmann, Michael and Marcel Fratzscher, 2009. “Global Financial Transmission of Monetary Policy Shocks,” Oxford Bulletin of Economics and Statistics Vol. 71(6): 739-759.
- Farhi, Emmanuel and Iván Werning, 2016. “A Theory of Macroprudential Policies in the Presence of Nominal Rigidities,” mimeo May 2016.
- Forbes, Kristin, 2020. “The International Aspects of Macroprudential Policy,” NBER Working Paper 27698.
- Di Giovanni, Julian, Justin McCrary and Till von Wachter, 2009. “Following Germany’s Lead: Using International Monetary Linkages to Estimate the Effect of Monetary Policy on the Economy,” The Review of Economics and Statistics 91(2): 315-331.
- Gali, Jordi, 2008. Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework XI, 203pp., Princeton University Press, Princeton.
- Gambacorta, Leonardo and Andrés Murcia, 2020. “The impact of macroprudential policies in Latin America: An empirical analysis using credit registry data,” Journal of Financial Intermediation 42, April 2020.
- Gerali, A., Neri, S., Sessa, L., and Signoretti, F. M., 2010. “Credit and banking in a DSGE model of the euro area.” Journal of Money, Credit and Banking, 42(s1):107–141.
- Gopinath, Gita, Emine Boz, Camila Casas, Federico J. Díez, Pierre-Olivier Gourinchas and Mikkel Plagborg-Møller, 2020. “Dominant Currency Paradigm,” American Economic Review 110(3): 677-719, March 2020.
- Han, Xuehui and Shang-Jin Wei, 2018. “International transmissions of monetary shocks: Between a trilemma and a dilemma,” Journal of International Economics 110: 205-219.
- Iacoviello, Matteo and Gaston Navarro, 2019. “Foreign effects of higher U.S. interest rates” Journal of International Money and Finance 95: 232-250.
- Jiang, Zhengyang, Arvind Krishnamurthy and Hanno Lustig, 2019. “Foreign Safe Asset Demand and the Dollar Exchange Rate,” NBER Working Paper 24439.
- Jordà, Òscar, 2005. “Estimation and Inference of Impulse Responses by Local Projections,” American Economic Review 95(1): 161-182.
- Jordà, Òscar, Moritz Schularick & Alan M. Taylor and Felix Ward, 2019. “Global Financial Cycles and Risk Premiums,” IMF Economic Review, Palgrave Macmillan; International Monetary Fund, vol. 67(1), pages 109-150, March.
- Kearns, Jonathan, Andreas Schrimpf and Fan Dora Xia, 2020. “Explaining Monetary Spillovers: The Matrix Reloaded”, CEPR Discussion Paper No. DP15006.
- Klein, Michael W. and Jay C. Shambaugh, 2013. “Rounding the Corners of the Policy Trilemma: Sources of Monetary Policy Autonomy,” NBER Working Paper 19461.
- Levy-Yeyati, Eduardo and Federico Sturzenegger, 2003. “To Float or to Fix: Evidence on the Impact of Exchange Rate Regimes on Growth,” American Economic Review 93(4): 1173-1193.
- Levy-Yeyati, Eduardo and Federico Sturzenegger, 2007. “Fear of Appreciation,” World Bank Policy Research Working Paper 4387.
- Mano, Rui and Silvia Sgherri, 2020. “One Shock, Many Policy Responses”, IMF Working Paper, WP/20/10.
- Miranda-Agrippino, Silvia, and Hélène Rey. 2019. “US Monetary Policy and the Global Financial Cycle.” NBER Working Paper 21722.
- Morais, Bernardo, José-Luis Peydró, Jessica Roldán-Peña and Claudia Ruiz-Ortega, 2018. “The International Bank Lending Channel of Monetary Policy Rates and QE: Credit Supply, Reach-for-Yield, and Real Effects,” Journal of Finance Vol. 74, Issue 1, pp. 55-90.
- Obstfeld, M., Shambaugh, J. C., & Taylor, A. M., 2004. The Trilemma in History: Tradeoffs Among Exchange Rates, Monetary Policies, and Capital Mobility. The Review of Economics and Statistics, 87(3), 423-438.
- Ostry, Jonathan, Atish Rex Ghosh, and Marcos Chamon, 2012. “Two Targets, Two Instruments: Monetary and Exchange Rate Policies in Emerging Market Economies,” IMF Staff Discussion Note SDN/12/01.
- Rajan, Ramkishen S., 2010. “The Evolution and Impact of Asian Exchange Rate Regimes,” ADB Economics Working Paper Series 208, July 2010.
- Rey, H. 2015, “Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence”, NBER Working Paper, no. 21162.
- Richter, Björn, Moritz Schularick and Ilhyock Shim, 2019. “The costs of macroprudential policy”, Journal of International Economics Vol. 118, May 2019, pages 263-282.
- Rojas, Diego, Carlos A. Vegh and Guillermo Vuletin, 2020. “The Macroeconomic Effects of Macroprudential Policy: Evidence from a Narrative Approach”, NBER Working Paper 27687.
- Schmitt-Grohe, Stephanie & Martin Uribe, 2012. “Managing Currency Pegs,” American Economic Review, American Economic Association, vol. 102(3), pages 192-197, May.
- Shambaugh, Jay C., 2004. “The Effect of Fixed Exchange Rates on Monetary Policy,” The Quarterly Journal of Economics, Oxford University Press, vol. 119(1), pages 301-352.
- Shousha, Samer, 2019. “The Dollar and Emerging Market Economies: Financial Vulnerabilities Meet the International Trade System”, mimeo.

*wpiea2023012-print-pdf - References*

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_Source: https://www.imf.org/-/media/files/publications/wp/2023/english/wpiea2023012-print-pdf.pdf_