## dpea2024nes ## Source details **Canonical URL:** [dpea2024nes](https://www.imf.org/-/media/files/publications/dp/2024/english/dpea2024nes.pdf) ## Other formats - [Markdown version](/-/media/files/publications/dp/2024/english/dpea2024nes.pdf.md) - [Structured JSON version](/-/media/files/publications/dp/2024/english/dpea2024nes.pdf.json) --- ### Executive summary: scope, IPF relevance, and pilots - ASEAN-4 defined as Indonesia, Malaysia, Philippines, Thailand. - ASEAN-4 are relatively small open economies and "highly susceptible to external shocks—both financial and real—that could induce large capital flows and exchange rate volatility that could lead to foreign exchange (FX) market dysfunction." - Central bank frameworks and toolkits: - With the exception of Bank Negara Malaysia, ASEAN-4 central banks mostly have flexible inflation targeting frameworks; objectives include medium-term price stability, sustainable economic growth, and financial stability. Indonesia also includes exchange rate stability. - Central banks routinely use multiple tools besides the policy rate: macroprudential measures (MPMs), foreign exchange interventions (FXIs), and capital flow management measures (CFMs). - Integrated Policy Framework (IPF) role: - IPF offers a frictions-based approach to coordinate monetary policy, FXIs, MPMs, and CFMs by linking tools to underlying frictions and vulnerabilities. - IPF informed changes to IMF Institutional View (IMF 2022a) and guidance on FXIs in IMF surveillance (IMF 2023a). - Exchange rate adjustment remains the first line of defense for inflation-targeting countries facing external nonfundamental shocks; FXIs may be warranted for large shocks in the presence of well-identified frictions as part of the overall mix. - ASEAN-4 IPF pilots and engagement: - Early pilots in 2022–23 used QIPF and empirical implementations to analyze trade-offs; used in 2022–23 Article IV consultations for Thailand, Philippines, Indonesia, Malaysia. - Inputs included Article IV materials, country team discussions, and two high-level technical events (August 22, 2023; July 17, 2023). ### Key frictions identified and measurement gaps - Three IPF frictions potentially justifying FXIs under certain shocks: - lack of FX market depth, - unhedged FX debt, - risk of inflation expectations de-anchoring. - FX market depth and measurement: - FX markets can appear deep in normal times but become shallow in stress. - Measurement challenges: bid-ask spreads, FX turnover, and UIP premium are endogenous to FXI; lack of official FXI data complicates accurate assessment. - QIPF parameters and country posterior results (Γ = FX market depth; low Γ = deeper market): - Γ prior (R1: Deep): Beta, Mean 0.01, Std 0.005 - Γ prior (R2: Shallow): Beta, Mean 0.075, Std 0.01 - Indonesia: posterior Gamma means: Deep 0.01 Std 0.005; Shallow 0.075 Std 0.01; Probability of deep FX markets 0.89; Change in log marginal likelihood 3.2 - Malaysia: posterior Gamma means: Deep 0.01 Std 0.005; Shallow 0.076 Std 0.01; Probability of deep FX markets 0.99; Change in log marginal likelihood 14.7 - Philippines: posterior Gamma means: Deep 0.001 Std 0.072; Shallow 0.001 Std 0.072; Probability of deep FX markets 0.99; Change in log marginal likelihood −14 . 8 - Thailand: posterior Gamma means: Deep 0.001 Std 0.072; Shallow 0.001 Std 0.072; Probability of deep FX markets 0.99; Change in log marginal likelihood 4.0 - Unhedged FX debt and hedging markets: - Available data suggest no broad unhedged FX balance sheet exposures across ASEAN-4, but nonlinear impacts from large depreciations could amplify balance-sheet vulnerabilities. - Sectoral FX mismatches generally limited; prudential hedging requirements and low external corporate debt mitigate broad risks. - Philippines caveat: bank buffers exist but opacity in some conglomerate structures impedes full borrower resilience assessment. - Other amplifiers: - Foreign holdings of local-currency government bonds considerable (notably Malaysia). - Trade invoicing in US dollars ranges from around 75 percent in Thailand to about 90 percent in Indonesia (dominant currency pricing). - Strong correlation between exchange rate volatility and CDS spreads in ASEAN-4. - Inflation expectations and exchange rate pass-through: - Inflation expectations mostly well anchored. - Pass-through is generally low and asymmetric; depreciations have larger inflation impact than appreciations. - Nonlinear state dependence: - Pass-through "triples when an exchange rate depreciation is driven by US monetary policy tightening" (Carrière-Swallow and others 2023). - Pass-through becomes nonlinear when depreciation exceeds 24 percent in a sample of emerging markets (Caselli and Roitman 2019). - Indonesia historical depreciations about 27 to 64 percent in 2000–01, 2008–09, 2013–14 with marked inflation increases. ### QIPF model applications, simulations, and principal findings - Model and scenario setup: - QIPF: infinite-horizon New Keynesian model with financial frictions producing UIP premiums and sudden stops; empirical implementation linearized and estimated with Bayesian methods. - Pilots simulated shocks including a large supply shock (Russia–Ukraine and commodity price rises), abrupt contractionary advanced-economy monetary policy, capital outflows, and an associated risk-off shock. - Main model findings: - Monetary policy remains the first line of defense against persistent inflationary pressures; exchange rate flexibility should act as shock absorber for fundamental shocks. - For large nonfundamental risk-off shocks that abruptly spike UIP premiums and produce inefficiently tight financial conditions, coordinated use of monetary policy, FXI, and fiscal policy improves trade-offs between price, financial, and output stability. - FXI effects in model simulations: - Mitigates inefficiently tight financial conditions and abrupt UIP premium spikes by limiting depreciation and pass-through to inflation. - Lowers burden on monetary policy, allowing a looser stance relative to no-FXI scenarios and improving output-inflation trade-offs. - In negative output gap contexts, complementary FXIs can alleviate output-inflation trade-offs. - Caveat: if depreciation is relatively small and short-lived, FXI gains may be limited and costs may exceed benefits. - FXI effectiveness estimate: - Model-aligned estimate: a 1 percent of GDP FXI leads to about 1 percent movement in the exchange rate on average (consistent with Blanchard and others 2015). - Large uncertainties: absence of official FXI data limits confidence in effectiveness estimates for ASEAN-4. ### Authorities’ rationale, practice, and operational realities with FXIs and CFMs - Authorities’ practice: - FXIs feature prominently to smooth excessive volatility, especially when exchange rate moves are inconsistent with historical normal market functioning and risk drying up liquidity or disorderly conditions. - FXIs usually sterilized and conducted in the spot market; recorded monthly large FX sales during the taper tantrum (2013), 2018 stress episode, and the 2022 risk-off shock. - FXI appears generally negatively correlated with UIP premiums, but episodes exist where FXI occurred during low UIP deviation, indicating potential inconsistencies with IPF guidance. - Intervention timing and motivation: - While preemptive FXI is not recommended ex ante under IMF IPF guidance, authorities may intervene preemptively if they judge herd behavior could dry liquidity or cause excessive volatility. - Clear evidence of elevated market dysfunction (for example, sharply increased UIP/covered interest parity premiums or bid-ask spreads) may justify FXI under IPF as proactive prevention. - CFMs usage: - CFMs used sparingly as last resort; some long-standing measures remain in place. - Preemptive CFMs/MPMs may be desirable where elevated stock vulnerabilities exist. ### Policy guidance, operational criteria, and recommended ex-ante actions - IPF-derived use cases for FXI once a shock has materialized: - Use case A: FXI in shallow FX markets to smooth changes in hedging/financing premia (UIP, covered interest parity, and FX financing) that threaten macro/financial stability. Not warranted after fundamental shocks unless clear ex post evidence of nonfundamental shocks. - Use case B: FXI to counter financial stability risks from FX mismatches when large depreciation increases default risk, provided reserves sufficient. - Use case C: FXI to counter risks to price stability when sharp exchange rate changes risk de-anchoring expectations, provided costs of using monetary policy alone are high, reserves are sufficient, costs of FXI are low, and FXI does not substitute for warranted monetary adjustment. - Ex-ante policy recommendations: - For use case A: structural reforms to deepen FX and local-currency debt markets; consider preemptive CFMs/MPMs to contain stock vulnerabilities. - For use case B: ex-ante MPMs/CFMs to limit vulnerabilities from elevated FX debt stocks. - For use case C: build central bank credibility to anchor inflation expectations and reduce exchange rate pass-through. - Operational criteria and metrics to consider before FXI: - FX market volatility (one-month at-the-money implied volatility, exponentially weighted moving average daily volatility, excessive volatility vs model-determined equilibrium). - Bid-ask spreads. - FX market turnover. - Sharp increases in UIP/covered interest parity premiums or bid-ask spreads indicating elevated risk of market dysfunction. ### Operational challenges, data gaps, and needed work - Data and measurement gaps: - Lack of official FXI data complicates measuring FX market depth and assessing FXI appropriateness and impact. - Absence of granular data on unhedged FX exposures prevents accurate assessment of FX mismatches. - Time-varying frictions and nonlinear shock effects make it challenging to determine when FXI benefits outweigh costs. - High-frequency FXI data absence hampers assessment of brief or instantaneous intervention impacts; authorities caution against low-frequency data usage. - Institutional and operational frictions: - Integrating policies with different implementation lags: macroprudential measures operate over financial cycle (long horizon), monetary policy works over months, FXI acts immediately. - Internal operational frameworks not fully integrated: FX operations teams often manage FXIs while policy departments manage monetary and macroprudential policy; Monetary Policy Committees could play a stronger coordination role. - Modeling and nonlinearities: - More work needed to quantify potential nonlinearities, time variation of frictions, and thresholds where FXI is inadvisable. - Customizing QIPF/QPM to country-specific features improves assessments, but quantitative results must be combined with judgment. ### Annex and capacity development lessons - High-level policy dialogue and workshops (Annex 1 & 2) highlighted: - IPF relevance for small open Asian emerging markets prone to capital flow swings and exchange rate volatility. - Practical challenges in communication, model gaps, and need for operational FXI guidance. - BIS view: preventive policies, buffers, and macroprudential tools remain important given real-time shock assessment limits. - Philippines model development and capacity building (Annex 3 & 4): - BSP modernized forecasting with an extended QPM providing endogenous monetary policy, fiscal and macro-financial linkages, FXI and CFM representations, and macroprudential policy incorporation. - QIPF extensions for the Philippines added supply side, liquidity-constrained households, commodity prices, richer fiscal side, and Markov-switching FX market depth; results stress state-dependent intervention rules and the importance of liquidity-constrained households for transmission. - Annex model diagnostics show variables and axes for risk-appetite shock responses, including FXI measured in "Percent of annual GDP." ### Costs, risks, and practical considerations of FXI (summary) - Potential long-term costs and risks to internalize in policy decisions: - Impeding financial market development. - Encouraging excessive buildup of foreign currency debt. - Risk of large and destabilizing reserve losses if risk-off sentiment persists or reserve losses trigger repricing of risk premiums. - Authorities emphasized internalizing these costs when calibrating trade-offs; omission may bias FXI toward appearing more effective. *Source: Executive Summary, Navigating External Shocks in Southeast Asia’s Emerging Economies (IMF Departmental Paper).* ### Executive Summary ...............................................................................................v ### Executive Summary ### Overview - ASEAN-4 refers to Indonesia, Malaysia, Philippines, Thailand. - As relatively small open economies, ASEAN-4 are highly susceptible to external shocks—both financial and real—that could induce large capital flows and exchange rate volatility that could lead to foreign exchange (FX) market dysfunction. - With the exception of Bank Negara Malaysia, ASEAN-4 central banks mostly have flexible inflation targeting frameworks for monetary policy implementation. Their main policy objectives include medium-term price stability, sustainable economic growth, and financial stability. In the case of Indonesia, this also includes exchange rate stability. - ASEAN-4 central banks routinely use multiple policy tools besides the monetary policy rate, including macroprudential measures (MPMs), foreign exchange interventions (FXIs), and capital flow management measures (CFMs). ### IPF approach and relevance - The Integrated Policy Framework (IPF) offers a frictions-based approach to the coordinated use of multiple policy tools. IPF models link FXIs—and MPMs and CFMs—to underlying frictions and vulnerabilities and examine how they fit into the overall policy framework (IMF 2020). - Insights from IPF work fed into changes to the IMF’s Institutional View on the liberalization and management of capital flows (IMF 2022a). A recent note provides guidance on IMF advice on the use of FXIs as part of the IPF in IMF surveillance (IMF 2023a). - Although exchange rate adjustment remains the first line of defense for inflation-targeting countries facing external nonfundamental shocks, FXIs might be warranted if shocks are large and occur in the presence of well-identified frictions as part of the overall policy mix. ### ASEAN-4 IPF pilots and country engagement - ASEAN-4 economies were early pilots in IPF operationalization in 2022–23 and welcomed the IPF as a structured, frictions-based approach to analyze trade-offs across policy objectives. - The IPF operationalization in ASEAN-4 drew on the Quantitative Model for the Integrated Policy Framework (QIPF) (Adrian and others 2021) and its empirical implementation (Chen and others 2023). - The 2022 Article IV consultations for Thailand (IMF 2022b) and the Philippines (IMF 2023b) and the 2023 Article IV consultations for Indonesia (IMF 2023c) and Malaysia (IMF 2023d) used IPF approaches and quantitative models to analyze policy trade-offs under alternative scenarios. - The paper draws on inputs including Article IV materials, discussions with ASEAN-4 country teams, a high-level policy dialogue jointly organized by Bank Indonesia and Bank of Thailand on August 22, 2023 (Annex 1), and a technical peer learning event at the Singapore Training Institute on July 17, 2023 (Annex 2). ### Key frictions identified in ASEAN-4 - ASEAN-4 countries experience at least one of three IPF frictions that might justify the use of FXIs under certain shocks: - lack of FX market depth, - unhedged FX debt, - risk of inflation expectations de-anchoring. - FX markets can become shallow during market stress episodes, though they may appear deep by most metrics during normal times. - Limited evidence exists of broad unhedged FX balance sheet exposures across ASEAN-4, but large exchange rate depreciations could have nonlinear impacts on private sector balance sheets. - Inflation expectations are mostly well-anchored, but exchange rate pass-through to inflation can be subject to nonlinearities and tends to be larger during periods of high inflation and elevated uncertainty, which could de-anchor expectations. ### QIPF model applications and main findings - IMF teams used the QIPF model to assess policy trade-offs under a risk-off shock. QIPF applications highlighted that under some scenarios a coordinated use of monetary, FXI, and fiscal policies improves trade-offs between price and output stability. - Specific model findings include: - The use of FXIs in response to a large nonfundamental risk-off shock mitigates the impact of inefficiently tight financial conditions and abrupt spikes in uncovered interest parity premiums, lowering the burden on monetary policy by limiting the extent of depreciation and pass-through to inflation. - In countries with a negative output gap, complementary use of FXIs could alleviate output-inflation trade-offs. - Authorities and country teams view QIPF as helpful: it provides a fully consistent micro-founded framework to assess IPF policies. However, they stressed that policy advice also requires judgment and consideration of factors beyond the models. - Authorities emphasized the importance of internalizing costs associated with FXIs and CFMs (for example, impeding financial market development and encouraging excessive buildup of foreign currency debt) to accurately identify policy trade-offs. ### Operational challenges and measurement gaps - Country teams at times lacked sufficient information to assess the extent of frictions: - Accurately measuring FX market depth was difficult in the absence of official FXI data. - Granular data on unhedged FX balance sheet exposures would improve assessment of FX mismatches that could amplify risk-off shocks. - It is important to ex ante identify country-specific structural and idiosyncratic factors that can amplify or mitigate shocks to appropriately calibrate policies. Assessing the nature and magnitude of shocks in real time was also challenging; authorities noted decisions on FXIs often need to be made quickly, mostly within a day. - More work is needed to assess potential nonlinearities: the time-varying nature of IPF frictions and nonlinear effects of shocks make it difficult to know when benefits of complementary FXI use outweigh costs. - Remaining operational challenges in IPF implementation include: - Integrating policies that operate with different implementation lags: macroprudential policy works over the financial cycle (longer horizon), monetary policy works with shorter lags of a few months, and FXI has an immediate effect on the exchange rate. - Internal operational frameworks are not fully integrated: different central bank departments often manage different tools (for example, FXIs led by operations departments versus macroprudential and monetary policy). Monetary policy committees could play a more active coordination role. ### Authorities’ rationale and practice with FXIs - The ASEAN-4 pilots confirmed FXIs feature prominently in authorities’ toolkits. Central banks indicated FXIs are deployed to smooth excessive volatility, particularly when exchange rate movements are inconsistent with historical patterns of normal market functioning and could risk drying liquidity or creating disorderly market conditions. - Although preemptive FXI is not recommended under IMF guiding IPF principles for FXIs, authorities noted they may intervene preemptively if they assess that herd behavior could dry up liquidity and/or result in excessive volatility. Where risks of market dysfunction are elevated, central banks find it prudent to act promptly rather than waiting for risk materialization. - If there is clear evidence of elevated risk of market dysfunction—indicated by sharply increased uncovered interest parity/covered interest parity premiums or bid-ask spreads—there may be a case for FXI under the IPF. Addressing these premiums is a proactive way to prevent later macroeconomic destabilization. - IMF country teams noted lack of official FXI data hampered assessment of appropriateness and impact of FXI in ASEAN-4, including during the combined large supply and risk-off shocks experienced during 2022. ### Lessons and way forward - Model-based IPF pilots were useful in illustrating policy trade-offs in downside scenarios and assisting IPF operationalization. ASEAN-4 authorities appreciated the evolution of IMF thinking embodied in the IPF. - Authorities’ familiarity with models, in particular the QIPF supported by IMF capacity development, facilitated structured policy discussions in Article IV surveillance at technical and senior policymaker levels. - All ASEAN-4 central banks currently use semi-structural models to integrate various macro-financial channels and policy instruments. Authorities recognize that a fully-fledged dynamic stochastic general equilibrium model would be superior for normative policy scenario analysis. - The pilots fostered ongoing engagement between IMF and ASEAN-4 authorities, supported by capacity development to help central banks implement model enhancements based on authorities’ feedback. *Source: Executive Summary, Navigating External Shocks in Southeast Asia’s Emerging Economies (IMF Departmental Paper).* ### 2. Background ### 2. Background ### External vulnerabilities and historical episodes - ASEAN-4 economies are susceptible to external shocks—both financial and real—that can induce large capital flows and exchange rate volatility. - Key external shock channels: - sudden shifts in global risk sentiment and advanced economies’ monetary policy; - external demand and supply shocks, particularly from China; - changes in global commodity prices (noting Indonesia and Malaysia are commodity exporters). - Historical crisis episodes with significant capital outflows cited: the 2013 taper tantrum, renminbi devaluation in 2015, US election in 2016, emerging market sell-off in 2018, and COVID-19 pandemic in 2020. - Resulting market outcomes documented in the chapter: - highly volatile capital flows (Figure 1: Nonresident Portfolio Flows to ASEAN-4 Countries, three-month rolling sum, Billions of US dollars); - heightened exchange rate volatility (Figures 2 and 3: 30-day realized volatility, percent; intraday volatility, percent). ### Policy buffers, macroeconomic space, and financial stability - Policy buffer and fiscal stance: - Public debt is around 60 percent of GDP or lower, providing sufficient policy space to address downside risks. - Public debt to external creditors is around 20 percent of GDP or lower in ASEAN-4 countries. - Reserves and financial system: - ASEAN-4 accumulated FX reserves for precautionary reasons and in response to large capital inflows. - Banking systems are well-capitalized and have ample liquidity; financial stability risks are well-contained. - Inflation and output: - Closing or already positive output gaps with declining inflation allow ASEAN-4 countries to normalize monetary and fiscal policies. ### Monetary policy frameworks and instruments - Monetary frameworks: - ASEAN-4 central banks mostly have flexible inflation targeting frameworks; main policy objectives include medium-term price stability, sustainable economic growth, and financial stability. - Bank Negara Malaysia does not have an inflation (or flexible inflation) targeting framework; its principal objective is to promote monetary and financial stability conducive to sustainable growth. - Primary instruments and practices: - The policy rate is the primary tool to achieve price stability; monetary policy transmission channels are not very strong, but policy stances have historically been responsive to inflation movements. - Purchases of government bonds, mostly from the secondary market, are used to manage aggregate demand and support fiscal policy implementation. - Bank Indonesia also purchased government bonds from the primary market to mitigate destabilizing volatility in interest rates and to support the needed fiscal expansion during the COVID-19 pandemic. ### Macroprudential measures (MPMs) and foreign-exchange-related prudential rules - MPM deployment: - Since the aftermath of the 2007–09 global financial crisis, MPMs have been increasingly employed to preserve and promote financial stability. - MPMs used include loan-to-value limits, caps on open FX exposures, and capital requirements. - Box 1: Foreign exchange–related macroprudential measures in ASEAN-4 (country-level specifics) - Indonesia: - Regulation 16/21/PBI/2014 initially required nonbank corporates with external debt to meet a minimum hedging ratio of 20 percent of the negative difference between maturing foreign currency assets and foreign currency liabilities in the next three months and in the next three to six months. - Hedging ratio increased to 25 percent since 2016. - Nonbank corporates must meet the minimum FX liquidity ratio of a minimum of 70 percent to cover foreign currency liabilities with maturities less than three months. - Prudential regulations limit banks’ net open foreign exchange positions. - Malaysia: - Part of Malaysia’s foreign currency external debt is subject to Bank Negara Malaysia’s prudential and hedging requirements. - Philippines: - Prudential regulations limiting banks’ net open foreign exchange positions (overall net open position [end of day] of 20 percent or $50 million). - Higher risk weights for compliance with the risk-based capital requirement: 15 percent capital charge from 10 percent capital charge on non-deliverable forward transactions. - Limits on a bank’s gross exposures to peso non-deliverable forward transactions: 20 percent and 100percent of unimpaired capital for domestic banks and foreign bank branches, respectively. - Thailand: - Commercial banks must maintain a net open position in each currency at the end of each day in a proportion to its capital not exceeding 15 percent or $5 million, whichever is greater, and an aggregate position at the end of each day in a proportion to its capital not exceeding 20 percent or $10 million, whichever is greater. - Retail banks must maintain an aggregate position at the end of each day in a proportion to its capital not exceeding 20 percent or $2 million, whichever is greater. - Finance companies must maintain, at the end of each day, an aggregate position of net short in a proportion to its Tier 1 capital not exceeding 20 percent or an aggregate position of net long in a proportion to its Tier 1 capital not exceeding 25 percent. ### Foreign exchange intervention (FXI) and capital flow measures (CFMs) - FXI usage: - Exchange rate flexibility is the first line of defense, but FXIs—usually sterilized and conducted in the spot market—have been used, concentrated during periods of severe FX market stress. - FXI appears generally negatively correlated with UIP premiums based on an intervention database. - ASEAN-4 central banks seem to have conducted monthly FX sales (“large FXI”) during the taper tantrum (2013), emerging market stress episode (2018), and during the risk-off shock in 2022 triggered by the Federal Reserve’s interest rate hikes (Figure 5). - FXI interventions often coincided with periods of higher UIP premiums but there are also episodes of FXI during periods of low UIP deviation, reflecting potential inconsistencies with IPF guidance. - CFMs: - CFMs are used very sparingly as a last resort to address excessive volatility in capital flows; some long-standing measures remain in place in ASEAN-4. - Preemptive CFMs/MPMs may be desirable in countries with elevated stock vulnerabilities (see Institutional View revision, IMF 2022a). ### IPF principles, use cases for FXI, and modeling support - IPF guidance and principles: - IPF links FXI, MPMs, and CFMs to underlying frictions and vulnerabilities; operational guidance on FXI use has been formulated recently to complement disorderly-market intervention guidance in the Integrated Surveillance Decision. - Three IPF use cases for FXI once a shock has materialized: - Use case A: FXI in the presence of premiums in shallow FX markets to smooth large changes in hedging and financing premia (UIP, covered interest parity, and FX financing) that generate risks to macroeconomic and financial stability. FXI is not warranted after fundamental shocks unless there is clear ex post evidence of nonfundamental shocks. - Use case B: FXI to counter financial stability risks from FX mismatches (for example, private sector defaults) when a large depreciation increases these risks, provided reserves are sufficient. - Use case C: FXI to counter risks to price stability when sharp exchange rate changes risk de-anchoring inflation expectations, provided: - costs of using monetary policy alone are high; - reserves are sufficient for FXI to be effective; - the costs of including FXI are low; and - FXI does not substitute for the warranted monetary adjustment. - FXI should be used only if shocks are large and pose significant risks to central bank price and financial stability objectives, should not substitute for warranted macroeconomic policy adjustments, and requires strong central bank governance and communication. - Ex-ante policy recommendations aligned with IPF use cases: - For use case A: structural reforms to deepen FX and local currency debt markets; consideration of preemptive CFMs/MPMs to contain stock vulnerabilities. - For use case B: ex-ante policies such as MPMs and MPMs/CFMs to limit vulnerabilities from elevated FX debt stocks. - For use case C: building central bank credibility to anchor inflation expectations and reduce exchange rate passthrough. - Modeling and operationalization: - The quantitative IPF model (QIPF) is an infinite horizon New Keynesian model with financial frictions that lead to UIP premiums and occasional sudden stops, creating a role for FXIs and CFMs to complement monetary policy. - The empirical implementation used a linearized version of QIPF estimated with Bayesian methods and standard macroeconomic time series to generate baseline projections and alternative scenarios. - QIPF has been further developed to include the supply side, commodities, and fiscal policy; work is ongoing to add macroprudential policy. - ASEAN-4 central banks have received IMF technical assistance using micro-founded QIPF (Indonesia, Malaysia, Thailand) and a semi-structural quarterly projection model (QPM) in the Philippines; this technical assistance facilitated policy discussions in Article IV surveillance and regional peer learning events. *IMF Departmental Papers — Navigating External Shocks in Southeast Asia’s Emerging Economies: Section 2. Background.* ### 4. Implementing the Integrated Policy ### 4. Implementing the Integrated Policy Framework with Multiple Shocks and Policy Trade-Offs in ASEAN-4: Main Findings and Early Lessons ### A. Identifying and Measuring Integrated Policy Framework Frictions and Shocks - FX market depth and time-variation - ASEAN-4 FX markets have seen significant deepening over the past decade (including FX derivatives) but can become shallow—especially during stress times. - Common market-depth indicators: FX trading volume, average bid-ask spreads, average UIP premium (the average UIP premium has declined significantly over the past decade). - Time-varying market depth evidence (Quantitative IPF model, Table 1): - Γ (FX market depth) prior: Beta, Mean 0.01, Std 0.005 (R1: Deep) - Γ (FX market depth) prior: Beta, Mean 0.075, Std 0.01 (R2: Shallow) - Posterior parameterization and results by country (deep vs shallow regimes and associated priors/posteriors): - Indonesia: posterior Gamma means: Deep 0.01 Std 0.005; Shallow 0.075 Std 0.01; Probability of deep FX markets 0.89; Change in log marginal likelihood 3.2 - Malaysia: posterior Gamma means: Deep 0.01 Std 0.005; Shallow 0.076 Std 0.01; Probability of deep FX markets 0.99; Change in log marginal likelihood 14.7 - Philippines: posterior Gamma means: Deep 0.001 Std 0.072; Shallow 0.001 Std 0.072; Probability of deep FX markets 0.99; Change in log marginal likelihood −14 . 8 - Thailand: posterior Gamma means: Deep 0.001 Std 0.072; Shallow 0.001 Std 0.072; Probability of deep FX markets 0.99; Change in log marginal likelihood 4.0 - Note: Γ is the model parameter reflecting depth of the foreign exchange (FX) market, with a low value of Γ corresponding to deeper FX markets. - Measurement challenges: - FX market depth measures (bid-ask spreads, FX turnover, UIP premium) are endogenous to FX interventions (FXI) and may overstate market depth if FXI are effective or preemptive. - Lack of official FXI data complicates accurate assessment; model-based estimates can contradict authorities’ own assessments (example: Thailand). - Unhedged FX debt and FX hedging markets - Available data suggest ASEAN-4 do not appear to face significant frictions from unhedged FX balance sheet exposures, but nonlinearities and amplifying factors could generate frictions even at relatively low exposure levels. - Sectoral FX mismatches generally limited; low external corporate debt and prudential/hedging requirements limit broad financial stability risks. - Philippines caveat: banks have buffers, but opacity of some conglomerate structures impedes full assessment of borrower resilience. - Underdeveloped FX hedging markets complicate corporate risk management; nonlinear impacts of large depreciation depend on: - Size of unhedged exposures, - Persistence of exchange rate depreciation (hedging requirements apply mainly to near-term exposures), - Whether exposures are systemic. - Interaction with other frictions can amplify effects (examples): - Large foreign investor share of local-currency debt markets, - High co-movement between exchange rate depreciation and private credit risk premiums, - Low resilience of private sector balance sheets. - Other amplifying structural factors - Foreign holdings of local currency government bonds remain considerable, particularly in Malaysia. - Exchange rate volatility and CDS spreads are strongly correlated in ASEAN-4. - High degree of trade dollarization: trade invoicing in US dollars ranges from around 75 percent in Thailand to about 90 percent in Indonesia (dominant currency pricing). - Dominant currency pricing can weaken the macro stabilization role of exchange rate flexibility and may require greater exchange rate flexibility to achieve the same stabilization. - Idiosyncratic factors noted by authorities: - Large share of nonresidents in FX markets (Thailand) can expose countries to portfolio flow reversals and make nonresidents price-setters. - Resident activities (e.g., gold trading, investment in foreign investment funds) can add to exchange rate volatility. - Inflation expectations and exchange rate pass-through - Inflation expectations broadly well anchored; ASEAN-4 central banks have credibility (inflation targeting in Indonesia, Philippines, Thailand; Malaysia anchored around Bank Negara Malaysia’s forecast lower limit). - Exchange rate pass-through is generally low and asymmetric (depreciations have larger impact on inflation than appreciations). - Nonlinearities and state dependence: - Carrière-Swallow and others (2023): pass-through tends to be significantly larger during periods of high inflation and elevated uncertainty; rate of pass-through triples when an exchange rate depreciation is driven by US monetary policy tightening. - Caselli and Roitman (2019): pass-through becomes nonlinear when exchange rate depreciates by more than 24 percent in a sample of emerging markets. - Indonesia historical episodes: large depreciations of about 27 to 64 percent in 2000–01, 2008–09, 2013–14; inflation increased markedly during these episodes, with indications of higher risk of de-anchoring expectations in 2000–01 and 2008–09. ### B. Findings from Model Simulations of Adverse External Shocks and ASEAN-4 Policy Mix in 2022 - Simulation setup and scenario elements (pilots during 2022–23 using the QIPF) - Common scenario elements across pilots: - Large supply shock (predominantly from Russia’s war in Ukraine and rising commodity prices), - Abrupt contractionary monetary policy in advanced economies resulting in capital outflows, - Associated risk-off shock. - Pilots focus: quantifying policy trade-offs under a risk-off shock and assessing appropriate policy mix given combinations of fundamental and nonfundamental shocks. - Main model findings and policy guidance - Monetary policy as first line of defense: - Monetary policy should be first line of defense against persistent inflationary pressures. - Exchange rate should remain flexible and act as a shock absorber following fundamental shocks. - Coordinated policy under large nonfundamental risk-off shocks (use case C): - For large, nonfundamental shocks that abruptly spike UIP premiums and generate inefficiently tight financial conditions that could hurt growth or risk de-anchoring inflation expectations, coordinated use of monetary policy, FX intervention (FXI), and fiscal policy improves trade-offs between price, financial, and output stability. - Use of FXI in response to nonfundamental risk-off shocks: - Improves FX market functioning and alleviates financial stability risks. - Limits inflationary pressures due to depreciation, helping monetary policy keep inflation expectations anchored. - Grants monetary policy additional space to maintain a looser stance compared with the scenario without FXI, improving output-inflation trade-offs. - Less tight monetary policy also prevents further rise in debt at risk in the corporate sector, mitigating financial stability risks. - Caveat: if the depreciation is relatively small and short-lived, the gains from FXI may be limited and the cost of FXI may exceed its benefits. - Estimation of FXI effectiveness and data limitations - Model’s estimate of FXI effectiveness aligns with Blanchard and others (2015) for a sample of emerging markets: - A 1 percent of GDP FXI leads to about 1 percent movement in the exchange rate on average. - Large uncertainties surround these estimates; absence of official FXI data makes it difficult to ascertain FXI impact in ASEAN-4 economies and to draw firm conclusions. *Italic: Source: IMF staff — "4. Implementing the Integrated Policy Framework with Multiple Shocks and Policy Trade-Offs in ASEAN-4: Main Findings and Early Lessons" (extracted from the chapter content).* ### conclusions, given the unavailability of historical FXI data. In addition, the authorities (for example, B ### Conclusions ### Key findings from IPF pilots - ASEAN-4 authorities use multiple policy tools (MPMs, monetary policy, FXIs) and value the evolution of IMF thinking embodied in the IPF. - The ASEAN-4 model-based IPF pilots: - Proved useful in illustrating policy trade-offs in a downside scenario and assisting operationalization of the IPF. - Benefited from authorities’ familiarity with the models, in particular the QIPF supported by IMF capacity development. - Initiated dynamic engagement with authorities, with model enhancements based on feedback and continued capacity development (for example, the 2023 Article IV consultation to the Philippines used an expanded QIPF model). - The IPF application reaffirmed: - The importance of using monetary policy to address persistent inflationary pressures from fundamental shocks. - Allowing exchange rate flexibility to act as a shock absorber. - That a complementary use of FXI could improve trade-offs between price, financial, and output stability when economies face large and nonfundamental shocks that cause abrupt spikes in UIP premiums and inefficiently tight financial conditions that could hurt growth or risk de-anchoring inflation expectations. ### Operational challenges and data gaps - Assessing frictions and shocks that might justify FXI is challenging for country teams due to limited information. - Key data limitations include: - Lack of official FXI data, which complicates assessment of FX market depth because FXI itself impacts market indicators used to measure depth. - Absence of granular data on the magnitude of unhedged FX balance sheet exposures, making it difficult to assess FX mismatches that could amplify risk-off shocks. - Time-varying nature of IPF frictions and nonlinear effects of shocks, which make it difficult to determine when benefits of FXI outweigh costs. - The absence of high-frequency data on FXI makes assessing the brief or instantaneous impacts of interventions particularly difficult. - Authorities cautioned against using low-frequency data to assess timing and effectiveness of FXI, noting that the impact of FXI on the exchange rate tends to be very brief, even instantaneous within the day. ### Costs, risks, and practical considerations of FXI - The cost of FXI needs to be properly assessed and incorporated into decision-making to identify policy trade-offs. - Potential longer-term costs and risks from FXI include: - Impeding financial market development. - Encouraging excessive buildup of foreign currency debt. - Risking large and potentially destabilizing losses of reserves if risk-off sentiment is more persistent than anticipated, or if large reserve losses trigger further repricing of risk premiums. - Not accounting for these costs may erroneously make FXI appear more effective in minimizing output/inflation trade-offs. ### Policy guidance and operational criteria from the IPF pilots - FXI may be justified under the IPF in periods of nonfundamental risk-off shocks when FX markets are or turn shallow and market sentiment is vulnerable—marked by high exchange rate volatility, significantly high bid-ask spreads, and heightened risk of market dysfunction as captured by elevated measures of risk premiums. - ASEAN-4 central banks do not rely on a single volatility threshold to intervene. Interventions are deployed when exchange rate movements are inconsistent with historical patterns of regular market functioning and could dry up liquidity, induce herd behavior, or cause disorderly conditions. - Key metrics used to determine whether to intervene include: - FX market volatility (measured using one-month at-the-money implied volatility, exponentially weighted moving average daily volatility, and excessive volatility against a model-determined equilibrium exchange rate). - Bid-ask spreads. - FX market turnover. - Guidance from the IPF: - If there is clear evidence of an elevated risk of market dysfunction, indicated by sharply increased UIP/covered interest parity premiums or bid-ask spreads, there may be a case for FXI under the IPF as a proactive way to prevent later macroeconomic destabilization. - If there is an exchange rate depreciation without clear evidence of market dysfunction, there would not be a case for FXI under the IPF until evidence of destabilized premiums emerges. - Authorities may intervene both ex post after observing market dislocations and preemptively to avoid disorderly market conditions, especially when signs of herd behavior (for example, a rush to hedge measured by exporters’ and importers’ forward transactions) are present. ### Modeling, nonlinearities, and future work - Customizing quantitative models to reflect country-specific features can improve assessment of policy trade-offs, but broader IPF principles beyond quantitative results should guide staff’s assessment of a suitable policy mix. - Important lessons and needs for further work: - More work is needed to assess potential nonlinearities in the data and their effects, since normally deep FX markets and well-anchored inflation expectations can turn shallow or de-anchor under elevated exchange rate volatility or very large depreciations. - Identifying thresholds where FXI is not desirable because nonlinearities are not salient remains difficult. - Future work should address the absence of high-frequency FXI data and seek to better identify circumstances in which FXI’s costs outweigh benefits. *IMF DEPARTMENTAL PAPERS • Navigating External Shocks in Southeast Asia’s Emerging Economies* ### Annex 1. Key Takeaways from the Bank ### Annex 1. Key Takeaways from the Bank ### Purpose and participants - High-level policy dialogue: Indonesia–Bank of Thailand High-Level Policy Dialogue on Frameworks for Integrated Policy: Experiences and the Way Forward (Jakarta, Indonesia, August 22, 2023). - Objective: take stock, discuss, and exchange experiences to identify lessons and gaps in policy frameworks guiding the use of multiple tools to deal with multiple shocks; facilitate dialogue between ASEAN policymakers, the IMF, and the Bank for International Settlements. - Participants (selected): Governors Perry (Bank Indonesia) and Suthiwartnarueput (Bank of Thailand); Deputy Governor Francis Dakila (Bangko Sentral ng Pilipinas); IMF Economic Counselor Pierre-Olivier Gourinchas; Assistant Governor Piti Disyatat (Bank of Thailand); Claudio Borio (Bank for International Settlements); Executive Director Firmin Mokhtar (Bank Indonesia). ### Rationale for the Integrated Policy Framework (IPF) in Asian emerging markets - IPF suitability: - Small open economies with sudden and large swings in capital flows and high exchange rate volatility that could lead to market dysfunction. - Integrated framework helps think through trade-offs of multiple tools and relieves burden on monetary policy. - Justifications for FXI use in IPF: - Time-varying market depth. - Nonlinear exchange rate pass-through. - Risks of de-anchoring inflation expectations. - Interventions are two-sided and exchange rate path remains allowed to reflect fundamentals. - Positive institutional development: open and constructive dialogue about when to use instruments other than monetary policy. ### Key operationalization challenges (as expressed by governors) - Communication: - Difficulty explaining consistency of using multiple policy tools with the inflation-targeting regime. - Having an explicit integrated policy framework might help alleviate communication challenges. - Models and judgment: - Gaps in models persist; no “cookbook approach.” - Country-specific circumstances require flexible application and judgment. - Guidance on FXI: - Limited operational guidance for FXIs compared with well-established tools for monetary policy (e.g., Taylor rules). ### Practical considerations from the second panel and IMF interventions - IMF evolution in institutional thinking: - Upgraded beyond traditional Mundell-Fleming by considering three financial frictions: shallow FX markets, currency mismatches, high exchange rate pass-through that might threaten to de-anchor inflation expectations. - When frictions are small or interventions have large effects (for example, depletion of foreign reserves), use of tools other than standard monetary or fiscal policy remains suboptimal. - Real-time challenges: - Assessing the nature, size, and duration of shocks and measuring frictions in real time is difficult. - Some frictions imply that certain instruments are preferable depending on the shock; FXIs in IPF pilots have been shown to be better for risk-off shocks. - Need to account for interactions of policy tools: FXIs can help avoid de-anchoring of inflation expectations if used judiciously alongside monetary policy. - IMF forward-looking agenda for operationalizing IPF: - Work on use of macroprudential toolkit in IPF context. - Add specific considerations for low-income countries to IPF framework. - Continue refining the IPF quantitative model. - Conduct analytical work on robust policies and diagnosing shocks. - Continue support of IPF applications with targeted capacity development and integration in surveillance. - BIS perspective: - Inability to assess shocks in real time makes preventive policies important: prudent macroeconomic policies, adequate buffers, and strong frameworks to maintain macro-financial stability, including adequate deployment of macroprudential policies. - Central bank operational realities: - Monetary Policy Committee plays an important role integrating views across departments (macroprudential, FX markets, etc.). - Operationalizing an integrated policy framework remains challenging in practice. *Italic: Source: Annex 1. Key Takeaways from the Bank (dpea2024nes)* ### Annex 2. Key Takeaways from Singapore Training Institute Technical Workshop on Quantitative Models for Macrofinancial Policy Analysis: The Experience of ASEAN-4 ### Workshop scope and participants - Hosted by IMF (Singapore Training Institute); jointly organized by Asia and Pacific Department, Institute for Capacity Development, and Monetary and Capital Markets Department. - Objective: discuss IMF IPF pilots, hear ASEAN-4 central bankers on policy frameworks, and exchange views on quantitative models for policymaking. ### Central findings on modeling and tools - Current practice: - ASEAN-4 central banks frequently use multiple instruments to achieve multiple objectives. - Gaps remain in quantitative frameworks to guide an integrated policy mix. - Central banks rely on one or more semi-structural core models with multiple satellite models to integrate macro-financial channels and policy instruments. - Model preference and consistency: - IMF staff view: a micro-founded structural general equilibrium model is best suited to capture interactions between frictions, policies, and transmission channels consistently. - Central bank participants acknowledged frameworks were not always fully internally consistent, especially between high-frequency short-term interventions (e.g., FXIs) led by FX operations teams and semi-structural macro frameworks used by policy departments. - Participants appreciated IMF’s IPF pilots and related capacity development. - FXI guidance need: - IMF principles for MPMs and CFMs are well documented; operational guidance on FXIs (outside disorderly market conditions) is still missing. - FXI decisions are often higher frequency (for example, daily) and fall under FX operations teams rather than teams supporting quarterly macrofinancial policy advice; guiding principles for FXIs would help ensure consistency between high-frequency decisions and lower-frequency macrofinancial modeling. - Operationalization pathway: - Expect further engagement in surveillance, policy, and capacity development to facilitate IPF operationalization in ASEAN countries and at the IMF. - Initial pilots in ASEAN-4 focused on using the QIPF model in downside scenarios covered in Article IV consultations. - Consensus on need to use models capable of assessing IPF tools in realistic scenarios in Article IV discussions and capacity development contexts. - The latest version of the QIPF model and evaluation of different policy combinations in response to current forecasts seen as a way forward. - Transition to QIPF-type dynamic stochastic general equilibrium models considered gradual with IMF capacity development playing important role (Indonesia, Malaysia, Thailand). - IPF-consistent semi-structural models like the QPM presented by the Institute for Capacity Development seen as complementary (the Philippines). *Italic: Source: Annex 2. Key Takeaways from Singapore Training Institute Technical Workshop (dpea2024nes)* ### Annex 3. Experience from Capacity Development on the Use of the Extended Multipolicy Quarterly Projection Model in the Philippines ### Background and motivation - Bangko Sentral ng Pilipinas (BSP) prior core medium-term forecasting model: multi-equation econometric model that supported disinflation in the 2000s. - Limitations: assumptions such as a constant future interest rate made it unsuitable to incorporate changes in monetary policy stance during volatile periods after the global financial crisis. - Technical assistance: Institute for Capacity Development began a technical assistance project in April 2022 to modernize BSP’s forecasting and policy analysis system with a semi-structural QPM at its core. ### QPM features and extensions - QPM design: - Provide forward-looking baseline and risk scenario projections with endogenous monetary policy (Dakila and others 2024). - Extensions added: - Fiscal policy and macro-financial linkages. - Additional policy tools such as FXIs and CFMs. - Explicit incorporation of macroprudential policy to enhance coordination among monetary, financial supervision, and macroprudential policymakers. ### Operational and policy impact - Milestone: developing and fully operationalizing the QPM was a major milestone for BSP. - Usefulness: - Enhanced ability to evaluate in real time the potential impact of policy decisions across domains. - Senior managers found model extensions useful to navigate trade-offs between policy tools in a complex macro-financial landscape. - Extensions that incorporated macroprudential policy should support enhanced coordination. - Complementarity with QIPF: - BSP’s QPM and the extended QIPF provide complementary inputs into monetary policy decisions. - QIPF’s rich theoretical structure helps consider merits of different policy regimes beyond quarter-to-quarter considerations. - QPM’s relative simplicity and calibration to Filipino data aids baseline projections and alternative scenarios for regular policymaking. - BSP staff value checking consistency between the two models, notably regarding FXI and monetary policy shocks in the IPF. ### IMF country team usage - Asia and Pacific Department country team uses a model along the lines of BSP’s QPM in policy discussions with the authorities, supported by ICD (IMF 2023e). - Analytical foundation has facilitated a common understanding of how economic assumptions, shocks, and policies drive forecasts and enriched discussions of baseline projections and risks. *Italic: Source: Annex 3. Experience from Capacity Development on the Use of the Extended Multipolicy Quarterly Projection Model in the Philippines (dpea2024nes)* ### Annex 4. Extending the QIPF Model: The Case of the Philippines ### Original QIPF model and initial extensions - Original model: - IPF model (gap model) discussed during 2022 Article IV; estimated linearized variant of Adrian and others (2021). - Featured financial intermediation frictions à la Gabaix and Maggiori (2015), a balance sheet channel to capture capital flow and exchange rate pressures, and an indexation mechanism to proxy for imperfect monetary policy credibility. - Further expansion: - Added a supply side with an estimated wage block to endogenously account for growth and generate baseline forecasts. - Updated QIPF used during 2023 staff visit to analyze implications of changes in minimum wage regulations debated by Congress and compared with a calibrated QPM-style model. ### Model realism and additional development motivations - Identified limitation: - Negative response of domestic demand to a persistent positive wage markup shock appeared counterintuitive; linked to absence of liquidity-constrained households with high marginal propensity to consume. - Extended model features: - Allows for, and estimates, the share of liquidity-constrained consumers. - Adds commodity prices and a richer fiscal side. - Allows FX market depth to follow a Markov process, consistent with empirical evidence in Annex Figure 4.1. - Markov-switching insights: - Benefits of estimation and importance of allowing coefficients of the central bank’s intervention rule to be state-dependent. - More aggressive interventions associated with periods of lower liquidity in FX markets. ### Implications for transmission and policy judgment - Model application: - New estimated QIPF model could be applied along many dimensions, but further work is needed to explore impact on transmission of key IPF disturbances, such as the risk appetite shock. - Comparative transmission (Annex Figure 4.2 summary): - Risk-appetite shock transmits similarly in model extended with a supply side, but differs more notably in the variant with liquidity-constrained households. - Differences should inform judgment in formulating policy recommendations. ### Notes on policy rules in the QIPF model - Policy rules in model: - Meant to be descriptively realistic—capture how policymakers have typically responded in the past. - Because many corresponding interventions predated IPF development, these rules may not always align exactly with current IPF recommendations. - Exploring integrated use of policy tools (an IPF goal) requires additional analysis and judgment, potentially based on assessment of shocks and frictions implied by the estimated model. ### Annex Figure 4.1 (Philippines: Bid-Ask Spread, Spot Rates) - Measure: Basis points, calculated as ask minus bid. - Axis and period shown (labels from figure): 0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20; Mar. 2017, Mar. 18, Mar. 19, Mar. 20, Mar. 21, Mar. 22, Mar. 23, Mar. 24. - Sources: Bloomberg L.P.; Refinitiv; and IMF staff estimates. ### Annex Figure 4.2 (Impact of a Risk-Appetite Shock in Different Vintages of the Philippines QIPF Model) - Variables illustrated (per figure panels and axis labels preserved): 1. Output Gap (axis values shown: −0.3, −0.2, −0.1, 0, 0.1, 0.2; horizon 0 2 0 1 0 3 0 4 0 in figure layout). 2. Domestic Demand (Percent contribution to GDP; axis values shown: −0.4, −0.3, −0.2, −0.1, 0, 0.1; horizon 0 2 0 1 0 3 0 4 0). 3. CPI Inflation (APR; axis values shown: 0, 0.05, 0.10, 0.15; horizon 0 2 0 1 0 3 0 4 0). 4. Policy Rate (APR; axis values shown: 0, 0.05, 0.10, 0.20, 0.15; horizon 2 0 1 0 0 3 0 4 0 in figure layout). 5. Real Exchange Rate (Consumption; axis values shown: 0, 0.5, 1.5, 2.0, 1.0, 2.5, 3.0; horizon 0 2 0 1 0 3 0 4 0). 6. 10-Year Rate (APR; axis values shown: 0, 0.05, 0.10, 0.15; horizon 0 2 0 1 0 3 0 4 0). 7. Real Trade Balance (axis values shown: 0, 0.05, 0.10, 0.15, 0.20, 0.25; horizon 0 2 0 1 0 3 0 4 0). 8. FXI (Percent of annual GDP; axis values shown: −1.5, −1.0, −0.5, 0.5, 0; horizon 2 0 1 0 0 3 0 4 0). - Source: IMF staff estimates. - Note: APR = annual percentage rate; CPI = consumer price index; FXI = foreign exchange intervention. *Italic: Source: Annex 4. Extending the QIPF Model: The Case of the Philippines (dpea2024nes)* ### References ### References ### Integrated Policy Framework, DSGE and Quantitative Models - Adrian, Tobias; Christopher J. Erceg; Jesper Lindé; Pawel Zabczyk; and Jianping Zhou. 2020. “A Quantitative Model for the Integrated Policy Framework.” IMF Working Paper 2020/122, International Monetary Fund, Washington, DC. - Adrian, Tobias; Christopher Erceg; Marcin Kolasa; Jesper Lindé; and Pawel Zabczyk. 2021. “A Quantitative Microfounded Model for the Integrated Policy Framework.” IMF Working Paper 2021/292, International Monetary Fund, Washington, DC. - Basu, Suman; Emine Boz; Gita Gopinath; Francisco Roch; and Filiz Unsal. 2020. “A Conceptual Model for the Integrated Policy Framework.” IMF Working Paper 2020/121, International Monetary Fund, Washington, DC. - Basu, Suman S., and Gita Gopinath. 2024. “An Integrated Policy Framework (IPF) Diagram for International Economics.” IMF Working Paper 2024/038, International Monetary Fund, Washington, DC. - Chen, Kaili; Marcin Kolasa; Jesper Lindé; Hou Wang; Pawel Zabczyk; and Jianping Zhou. 2023. “An Estimated DSGE Model for Integrated Policy Analysis.” IMF Working Paper 2023/135, International Monetary Fund, Washington, DC. - Dakila, Francisco G. Jr.; Dennis M. Bautista; Jasmin E. Dacio; Rosemarie A. Amodia; Sarah Jane A. Castañares; Paul Reimon R. Alhambra; Jan Christopher G. 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Eklou; Tidiane Kinda; Vatsal Nahata; Umang Rawat; and Ara Stepanyan. 2023. “ASEAN-5: Further Harnessing the Benefits of Regional Integration amid Fragmentation Risks.” IMF Working Paper 2023/191, International Monetary Fund, Washington, DC. - Corbacho, Ana, and Shanaka J. Peiris. 2018. The ASEAN Way: Sustaining Growth and Stability. Washington: International Monetary Fund. - International Monetary Fund (IMF). 2022b. “Thailand: 2022 Article IV Consultation-Press Release; Staff Report; and Statement by the Executive Director for Thailand.” IMF Country Report 2022/300, Washington, DC. - International Monetary Fund (IMF). 2022c. “Philippines: Selected Issues.” IMF Country Report 2022/370, Washington, DC. - International Monetary Fund (IMF). 2023b. “Philippines: 2023 Article IV Consultation-Press Release; Staff Report; and Statement by the Executive Director for Philippines.” IMF Country Report 2023/414, Washington, DC. - International Monetary Fund (IMF). 2023c. “Indonesia: 2023 Article IV Consultation-Press Release; Staff Report; and Statement by the Executive Director for Indonesia.” IMF Country Report 2023/221, Washington, DC. - International Monetary Fund (IMF). 2023d. “Malaysia: 2023 Article IV Consultation-Press Release and Staff Report.” IMF Country Report 2023/185, Washington, DC. - International Monetary Fund (IMF). 2023e. “The Philippines Quantitative Integrated Policy Pilot: Increasing Analysis Scape and Depth.” IMF Country Report 2023/415, Washington, DC. ### Market Structure and Regional FX Markets - Bank for International Settlements (BIS). 2022. “Foreign Exchange Markets in Asia-Pacific.” Basel. *Source: dpea2024nes - References (dpea2024nes - References, DP/2024/007).* --- _Source: https://www.imf.org/-/media/files/publications/dp/2024/english/dpea2024nes.pdf_