## wp1732 ## Source details **Canonical URL:** [wp1732](https://www.imf.org/-/media/files/publications/wp/wp1732.pdf) ## Other formats - [Markdown version](/-/media/files/publications/wp/wp1732.pdf.md) - [Structured JSON version](/-/media/files/publications/wp/wp1732.pdf.json) --- ### Six Principles of Inflation Targeting (Box 1) - Core definition and operational implications - Inflation-forecast targeting (IFT) is systematic, operational, flexible inflation targeting. - The central bank’s forecast contains all information relevant to the outlook for inflation—including policymakers’ preferences regarding the short-run trade-off between output and inflation, and estimated effects of shocks—making it an ideal intermediate target over the relevant policy horizon. - The analytical framework works back from the nominal anchor to derive feasible medium-term paths for the policy rate that guide the short-term interest rate so the inflation objective is achieved. - In this framework the policy interest rate must be endogenous, determined ultimately by the goal—otherwise the system has no nominal anchor. - Actual inflation may deviate from the target following shocks; due to lags in monetary transmission and concerns for output deviations from potential, it is not desirable to aim at keeping inflation exactly on target at all times. - Occasional deviations from the glide path should not automatically be interpreted as monetary policy errors; the speed of adjustment depends on the nature and magnitude of shocks and the policy response. - Six principles (exact wording preserved) - The primary role of monetary policy is to provide a nominal anchor (i.e., low, stable long-run inflation expectations) for the economy; the weights given to any other objective must be consistent with this. - Effective inflation targeting has beneficial first-order effects on welfare by reducing uncertainty, anchoring inflation expectations and reducing the incidence and severity of boom-bust cycles. - Fiscal and other government policies may make the task of monetary policy easier and more credible, or more difficult and less credible. - Because of - lags in the monetary transmission mechanism, and - concern for deviations of output from potential, as well as of inflation from the long-run target, following shocks it is not desirable to aim at keeping inflation exactly on target. - In view of possible short-run trade-offs between the inflation targets and other objectives, the conduct of monetary policy must have sufficient independence from the political process to achieve the announced objectives. - Effective monitoring and accountability mechanisms are required to ensure that central banks behave in a manner consistent with announced objectives and sound practice. - Policy-relevant takeaways and institutional requirements - A successful FIT/IFT regime provides an anchor to all nominal values, resulting in a significant reduction of uncertainty. - The central bank should set the policy rate with the objective of keeping the short-term market rate at any desired level; in advanced economies this link is strong, while in developing economies such as India these linkages are weaker—one of the implementation challenges. - Fiscal policy and other government interventions can materially affect the credibility and ease of achieving the inflation objective. - Monetary policy needs sufficient independence to manage short-run trade-offs and maintain credibility. - Monitoring and accountability mechanisms are essential to ensure central bank behavior aligns with announced objectives and sound practice. ### Inflation target, institutional setup, and motivation for FIT in India - Operational inflation target and tolerance band - Adopted operational target: 4.0 percent, with 6.0 percent and 2.0 percent as the upper and lower tolerance levels respectively, for the period up to March 31, 2021. - Institutional change - Six-member MPC constituted in September 2016 by the Government and the Reserve Bank. - Motivation and historical context - Lack of an explicit nominal anchor before FIT allowed relative price shocks (notably fuel and food) to transmit rapidly into persistent generalized inflation. - Large role of food price shocks and energy price shocks in Indian inflation dynamics underscores the need for a strong nominal anchor to anchor inflation and inflation expectations. ### International experience and modelling practice - Countries with previously weak price stability (New Zealand, Canada, Czech Republic) used inflation targeting to reduce long-run inflation and stabilize expectations, with transition output and employment losses. - United States policy evolved toward a regime resembling FIT without explicit self-identification; long-run behavior of inflation and inflation expectations over last 3 decades resembles FIT countries. - Most central banks adopting FIT set up a forecasting and policy analysis system (FPAS) and relied on calibrated monetary policy models rather than purely equation-by-equation statistical estimation. ### Challenges for implementing FIT in India - Transmission mechanism weaknesses - Multiple channels; interest rate channel is the most important. - Bank lending channel exists but transmission to medium-term bank lending rates historically sluggish. - Asset price and exchange rate channels found to be feeble in India. - Impediments: administered interest rates, statutory preemptions, rigidities in deposit rate structure, lack of external benchmarks. - Administered small saving interest rates can act as a floor for deposit rates; Government announced alignment measures on February 16, 2016. - Large retail deposit shares and fixed-tenure deposits create rigidity in banks’ funding costs; lack of transparent external money market benchmark limits floating deposit product creation. - High statutory preemptions can crowd out credit and suppress long-term risk-free interest rates. - Exogenous capital-flow-induced volatility in domestic liquidity conditions can materially affect transmission. - Informal finance usage weakens monetary policy efficacy on aggregate demand. - Base Rate computation changes: from April 2016 Base Rate mandatory on marginal cost of funds. - Importance of food prices to CPI - Food group constitutes about 46 percent of the CPI basket in India. - High share of food implies susceptibility to supply shocks (rainfall, agricultural output) and structural shifts in relative price of food vs non-food can create secular divergence. - Interventions (minimum support prices, employment guarantees, minimum wages) complicate transmission and relative price adjustment. - Monetary policy affects inflation via output gap on non-food non-fuel prices (sticky core consumption); high food weight dilutes medium-term effect of policy rate changes on overall CPI and introduces noise into inflation signal. - FIT should not be rejected because of food volatility; FIT provides a nominal anchor to limit pass-through of food price shocks into generalized inflation via anchored expectations and published medium-term forecast paths. - Trending relative prices create communication challenges: core inflation could be systematically downward-biased relative to headline inflation, complicating reassurance when target is headline inflation. - No track record — challenge of building credibility - Before FIT, RBI had no explicit overarching price stability mandate; public lacked historical record to judge RBI commitment. - Credibility must be earned over time by achieving announced objectives and transparent communication; inconsistency can erode credibility. - Expectations mechanism: credible, assertive policy response to shocks can absorb shocks (stabilize long-term expectations, raise real rate, appreciate exchange rate, open negative output gap and return inflation to target). Lack of credibility can amplify shocks and produce prolonged inflation spirals. - Credibility evolves gradually during FIT adoption and must be explicitly accounted for in policy model calibration. ### Quarterly Projection Model (QPM) — structure, calibration, India-specific features - Model structure - Forward-looking, 4-equation, open-economy model: endogenous variables are output gap, inflation, interest rate, and exchange rate. - Core-QPM omits sectoral details (covered in production-QPM) and includes a quadratic loss function capturing policymakers’ aversion to large deviations and dark corners. - Output gap responds to real interest rate and real exchange rate. - Expectations-augmented Phillips curve: short-run trade-off between output and inflation; no long-run trade-off. - Exchange rate via uncovered interest parity with risk premium, modified for reduced sensitivity to interest differentials. - Loss function penalizes deviations of inflation from target, output gaps, and interest rate variability. - Expectations are a mix of model-consistent (rational) and backward-looking components. - Core-QPM behavioral equations and calibrations (notations and calibrations preserved exactly as presented) - Output gap: - ŷ_t = α1 E_t[ŷ_{t+1}] + α2 ŷ_{t-1} + α3 r̂_{t-1} + α4 ẑ_{t-1} + ε^y_t - α1; α2; α3; α4 = .05.0;08.0;60.0;07.0 - Inflation: - π_t = β1 E_t[π_{t+1}] + β2 π_{t-1} + β3 ŷ_t + β4 ẑ_t + ε^π_t - β1; β2; β3; β4 = .005.;0;4.;0;06.;0;33.;0 - Monetary policy loss: - Loss L = Σ_{i=0}^∞ β^i [ λ1 (π̂_{t+i} − π^*)^2 + λ2 ŷ_{t+i}^2 + λ3 (Δ i_{t+i})^2 ] - λ1; λ2; λ3; β = .5 .0; 1 ; 1 ; 98 .0 3 2 1 = = = = λ λ λ β - Uncovered interest parity with risk premium: - S_t − E_t S_{t+1} = σ_t + (i_t − i^f_t)/4 + ε^S_t - δ1; δ2 = .3 .0;6. .0 2 1 = = δ δ - Weakened UIP parameter: γ1 = .7 .0 1 = γ - Inflation expectations formation (credibility and weights): - κ = .1 ; b_π = .25 .0 - Credibility process and calibration (Table 2 preserved) - c_t = ρ_c c_{t-1} + (1−ρ_c) ξ_t ; ρ_c = .80 .0 - ξ_t = (ε^L_{t+1})^2 − (ε^H_{t+1})^2 - ε^L_t = [ρ·π_{t-1} + (1−ρ)·π^*] − π^4_t with ρ = .4 ; π^* = .5 .0 - ε^H_t = [ρ·π_{t-1} + (1−ρ)·π^H] − π^4_t with π^H = .8 - Boundary conditions: If π^4_t − [ρ·π^4_{t-1} + (1−ρ)·π^*] < 0, then ξ_t = 1. If π^4_t − [ρ·π^4_{t-1} + (1−ρ)·π^H] > 0, then ξ_t = 0. - India-specific model features - Phillips curve includes a non-linear output gap term implying increasing marginal effect on inflation as gap increases; becomes very flat at wide negative output gaps. - Expectations formation explicitly includes endogenous credibility-building: credibility stock c_t evolves with signals based on relative squared forecast errors between optimists and skeptics. - Monetary policy minimizes quadratic loss including penalty for steep policy rate changes to reflect policymakers’ preference for gradualism and information transmission. ### Policy experiments and illustrative results (preserved exactly) - Disinflation experiment (from 5 percent to 4 percent) - Initial equilibrium: 5 percent inflation and nominal interest rate 7 percent (real rate 2 percent). - Baseline with initial low credibility: central bank hikes policy rate; rupee appreciates; negative output gap opens; inflation declines via exchange rate effect first and output gap later. - Cost in cumulative forgone output: 2 percent of annual GDP (sacrifice ratio of 2). - Credibility stock starts low and builds as inflation declines; as credibility approaches 1, lagged expectation and bias terms disappear improving output-inflation trade-off. - Hawkish policymakers: achieve target faster but with higher policy rate increases, sharper appreciation, wider negative output gap, larger sacrifice ratio. - Dovish policymakers (higher weight on output): tighten less, lower sacrifice ratio. - Disinflation with perfect credibility - 1-percent reduction in inflation achieved within a 6-quarter horizon at lower cumulative output cost: one-half percent of annual GDP. - With perfect credibility, tightening can be achieved without policy interest rate increase (real rate rise comes from lower expected inflation). - Policymaker preference over output gap matters little under perfect credibility. - Demand shocks (divine coincidence) - Optimal policy raises (cuts) policy rate to address positive (negative) demand shocks; this generally keeps inflation close to baseline while moderating output—no major conflict between output and inflation objectives. - Given flat Phillips curve under excess supply, negative demand shocks require somewhat larger output gap widening than positive shocks. - Demand shocks have little impact on credibility when inflation is well controlled. - Supply shocks (trade-offs and stagflation) - Nasty supply shock requires interest rate increase and larger negative output gap to maintain path to 4 percent target; trade-off between speed of return to target and output gap size. - Prompt, aggressive tightening prevents ratcheting up of long-term expectations and preserves credibility but at higher short-run output cost. - Favorable supply shock: inflation moderates faster, reaches 4 percent sooner, monetary policy eases, output gap closes faster. - Sequence of nasty supply shocks: requires more aggressive tightening and steep output gap widening; medium-term inflation can increase considerably and credibility may take a hit, but committed policy can still prevent long-term inflation expectations from ratcheting up. - Importance of prompt versus delayed responses - Delays in policy response to large supply shocks require much larger subsequent interest rate hikes and lead to larger cumulative output gaps and higher inflation — substantial deterioration in medium-term output-inflation trade-off. - Under perfect credibility, delay does less damage initially, but repeated delays can still undermine credibility. - Importance of credibility - Even with perfect credibility, long sequences of nasty shocks can worsen the policy trade-off with rising interest rates, widening negative output gaps, and higher inflation in the medium term; restoring reputation and getting inflation back to target incurs substantial output costs. ### Key quantitative points and indicators (preserved exactly) - Operational inflation target: 4.0 percent, with 6.0 percent and 2.0 percent as the upper and lower tolerance levels respectively. - Food group weight in CPI: about 46 percent. - Disinflation initial and target values in experiment: from 5 percent to 4 percent. - Initial nominal interest rate in disinflation experiment: 7 percent (real rate of 2 percent). - Sacrifice ratio in baseline disinflation experiment: cumulative forgone output is 2 percent of annual GDP (i.e., a sacrifice ratio of 2). - Sacrifice ratio with perfect credibility: one-half percent of annual GDP for 1-percent disinflation achieved in 6 quarters. - Expectations/credibility calibration parameters (as presented) - Output-gap coefficients: .05.0;08.0;60.0;07.0 (α1; α2; α3; α4 as listed). - Inflation coefficients: .005.;0;4.;0;06.;0;33.;0 (β1; β2; β3; β4 as listed). - Loss-function parameters: .5 .0; 1 ; 1 ; 98 .0 3 2 1 = λ1; λ2; λ3; β (as shown). - UIP/PRIME parameters: δ1; δ2 = .3 .0;6. .0 2 1 ; γ1 = .7 .0 1 - Expectations weights: κ = .1 ; b_π = .25 .0 - Credibility process: ρ_c = .80 .0 ; ρ = .4 ; π^* = .5 .0 ; π^H = .8 ### Policy implications and recommendations - Establish a strong nominal anchor via FIT to reduce amplitude and pass-through of supply shocks by anchoring expectations. - Build and preserve credibility: credible, prompt, and appropriately aggressive policy responses reduce long-run costs and improve output-inflation trade-offs. - Strengthen monetary transmission before and during FIT implementation: address administered rates, deposit-rigidity issues, external benchmarks, statutory preemptions, and capital-flow sterilization practices. - Communication strategy must explicitly account for high food weight and trending relative prices; publish medium-term forecast paths showing route back to headline inflation target and explain transmission channels and expected duration of relative price effects. - Use calibrated FPAS and QPM-style models that incorporate credibility formation, weakened UIP, and non-linear Phillips curve features to evaluate policy trade-offs and timing under India-specific frictions. *Source: wp1732 - 4.0 percent, with 6.0 percent and 2.0 percent as the upper and lower tolerance levels (IMF working paper content).* ### Box 1. Six Principles of Inflation Targeting ........................................................................... ### Box 1. Six Principles of Inflation Targeting ### Core definition and operational implications - Inflation-forecast targeting (IFT) is systematic, operational, flexible inflation targeting. - The central bank’s forecast contains all information relevant to the outlook for inflation—including policymakers’ preferences regarding the short-run trade-off between output and inflation, and estimated effects of shocks—making it an ideal intermediate target over the relevant policy horizon. - The analytical framework works back from the nominal anchor to derive feasible medium-term paths for the policy rate that guide the short-term interest rate so the inflation objective is achieved. - In this framework the policy interest rate must be endogenous, determined ultimately by the goal—otherwise the system has no nominal anchor. - Actual inflation may deviate from the target following shocks; due to lags in monetary transmission and concerns for output deviations from potential, it is not desirable to aim at keeping inflation exactly on target at all times. - Occasional deviations from the glide path should not automatically be interpreted as monetary policy errors; the speed of adjustment depends on the nature and magnitude of shocks and the policy response. ### Six principles (exact wording preserved) - The primary role of monetary policy is to provide a nominal anchor (i.e., low, stable long-run inflation expectations) for the economy; the weights given to any other objective must be consistent with this. - Effective inflation targeting has beneficial first-order effects on welfare by reducing uncertainty, anchoring inflation expectations and reducing the incidence and severity of boom-bust cycles. - Fiscal and other government policies may make the task of monetary policy easier and more credible, or more difficult and less credible. - Because of - lags in the monetary transmission mechanism, and - concern for deviations of output from potential, as well as of inflation from the long-run target, following shocks it is not desirable to aim at keeping inflation exactly on target. - In view of possible short-run trade-offs between the inflation targets and other objectives, the conduct of monetary policy must have sufficient independence from the political process to achieve the announced objectives. - Effective monitoring and accountability mechanisms are required to ensure that central banks behave in a manner consistent with announced objectives and sound practice. ### Policy-relevant takeaways and institutional requirements - A successful FIT/IFT regime provides an anchor to all nominal values, resulting in a significant reduction of uncertainty. - The central bank should set the policy rate with the objective of keeping the short-term market rate at any desired level; in advanced economies this link is strong, while in developing economies such as India these linkages are weaker—one of the implementation challenges. - Fiscal policy and other government interventions can materially affect the credibility and ease of achieving the inflation objective. - Monetary policy needs sufficient independence to manage short-run trade-offs and maintain credibility. - Monitoring and accountability mechanisms are essential to ensure central bank behavior aligns with announced objectives and sound practice. *Source: Adapted from Freedman and Laxton (2009); content as presented in Box 1 of the source document.* ### 4.0 percent, with 6.0 percent and 2.0 percent as the upper and lower tolerance levels ### wp1732 - 4.0 percent, with 6.0 percent and 2.0 percent as the upper and lower tolerance levels ### Inflation framework, nominal anchor, and motivation for FIT - Adopted operational target: 4.0 percent, with 6.0 percent and 2.0 percent as the upper and lower tolerance levels respectively, for the period up to March 31, 2021. - Six-member MPC constituted in September 2016 by the Government and the Reserve Bank. - Historical narrative: lack of an explicit nominal anchor before FIT allowed relative price shocks (notably fuel and food) to transmit rapidly into persistent generalized inflation. - Large role of food price shocks and energy price shocks in Indian inflation dynamics underscores the need for a strong nominal anchor to anchor inflation and inflation expectations. ### International experience with inflation targeting (IFT) - Countries that previously had weak price stability (New Zealand, Canada, Czech Republic) used inflation targeting to address entrenched high and variable inflation; achieved low long-run inflation and stabilized expectations, albeit with transition output and employment losses. - United States policy evolved toward a regime resembling FIT without explicit self-identification as an inflation targeter; long-run behavior of inflation and inflation expectations over last 3 decades resembles FIT countries. - Most central banks adopting FIT set up a forecasting and policy analysis system (FPAS) and relied on calibrated monetary policy models rather than purely equation-by-equation statistical estimation—calibration valued for embodying theoretical principles and yielding empirically plausible predictions, especially where data deficiencies make econometric estimation fragile. ### Challenges for implementing FIT in India - Transmission mechanism weaknesses - Multiple channels; interest rate channel is the most important. - Bank lending channel exists but transmission to medium-term bank lending rates historically sluggish. - Asset price and exchange rate channels found to be feeble in India. - Impediments highlighted: administered interest rates, statutory preemptions, rigidities in deposit rate structure, lack of external benchmarks. - Administered small saving interest rates can act as a floor for deposit rates and impede transmission; Government announced alignment measures on February 16, 2016. - Large retail deposit shares and fixed-tenure deposits create rigidity in banks’ funding costs; lack of transparent external money market benchmark limits floating deposit product creation. - High statutory preemptions can crowd out credit and suppress long-term risk-free interest rates. - Exogenous capital-flow-induced volatility in domestic liquidity conditions can materially affect transmission. - Informal finance usage weakens monetary policy efficacy on aggregate demand. - Pricing structure for loans (Base Rate computed on average cost of funds historically) made lending rates less sensitive to policy rate changes; from April 2016 Base Rate mandatory on marginal cost of funds. - Importance of food prices to CPI - Food group constitutes about 46 percent of the CPI basket in India. - High share of food implies susceptibility to supply shocks (rainfall, agricultural output) and structural shifts in relative price of food vs non-food can create secular divergence; Figure 8 reports ratio of Food Group Index to Overall CPI for Industrial Workers (source: RBI). - Interventions (minimum support prices, employment guarantees, minimum wages) complicate transmission and relative price adjustment. - Conceptual effect: monetary policy affects inflation via output gap on non-food non-fuel prices (sticky core consumption), so high food weight dilutes medium-term effect of policy rate changes on overall CPI and introduces noise into inflation signal. - FIT should not be rejected because of food volatility; instead, FIT provides a nominal anchor to limit pass-through of food price shocks into generalized inflation via anchored expectations and published medium-term forecast paths. - Trending relative prices create communication challenges: core inflation could be systematically downward-biased relative to headline inflation, complicating reassurance when target is headline inflation. - No track record — the challenge of building credibility - Before FIT, RBI had no explicit overarching price stability mandate; public lacked historical record to judge RBI commitment. - Credibility must be earned over time by achieving announced objectives and transparent communication; inconsistency can erode credibility. - Expectations mechanism: credible, assertive policy response to shocks can absorb shocks (stabilize long-term expectations, raise real rate, appreciate exchange rate, open negative output gap and return inflation to target). Lack of credibility can amplify shocks and produce prolonged inflation spirals. - Credibility evolves gradually during FIT adoption and must be explicitly accounted for in policy model calibration. ### Quarterly Projection Model (QPM) — core model overview and calibration - Model structure - Forward-looking, 4-equation, open-economy model: endogenous variables are output gap, inflation, interest rate, and exchange rate. - Core-QPM omits sectoral details (covered in production-QPM) and includes a quadratic loss function capturing policymakers’ aversion to large deviations and dark corners. - Output gap responds to real interest rate and real exchange rate. - Expectations-augmented Phillips curve: short-run trade-off between output and inflation; no long-run trade-off. - Exchange rate via uncovered interest parity with risk premium, modified for reduced sensitivity to interest differentials (to capture capital controls and market frictions). - Loss function penalizes deviations of inflation from target, output gaps, and interest rate variability. - Expectations are a mix of model-consistent (rational) and backward-looking components. - Core-QPM behavioral equations and calibrations (as presented) - Output gap (notation preserved): - ŷ_t = α1 E_t[ŷ_{t+1}] + α2 ŷ_{t-1} + α3 r̂_{t-1} + α4 ẑ_{t-1} + ε^y_t - α1; α2; α3; α4 = .05;.0;08.0;60.0;07.0 (as listed in table: " .05.0;08.0;60.0;07.0 4321 = = = = α α α α") - Inflation (notation preserved): - π_t = β1 E_t[π_{t+1}] + β2 π_{t-1} + β3 ŷ_t + β4 ẑ_t + ε^π_t - β1; β2; β3; β4 = .005.;0;4.;0;06.;0;33.;0 (as listed: " .005 .0; 4. .0; 06. .0; 33. .0 4 3 2 1 = = = = β β β β") - Monetary policy loss function (parameters preserved): - Loss L = Σ_{i=0}^∞ β^i [ λ1 (π̂_{t+i} − π^*)^2 + λ2 ŷ_{t+i}^2 + λ3 (Δ i_{t+i})^2 ] - λ1; λ2; λ3; β = .5;.0;1;1;98.;0 3 2 1 = = = = λ λ λ β (as shown: " .5 .0; 1 ; 1 ; 98 .0 3 2 1 = = = = λ λ λ β") - Uncovered interest parity with risk premium (as presented): - S_t − E_t S_{t+1} = σ_t + (i_t − i^f_t)/4 + ε^S_t (and extended formulation in table) - δ1; δ2 = .3 .0;6. .0 2 1 = = δ δ (as presented) - Weakened uncovered interest parity with risk premium parameter: - γ1 = .7 .0 1 = γ - Inflation expectations formation (credibility and weights): - κ = .1 ; b_π = .25 .0 = κ π b - Notations explained in table (output gap ŷ_t, real interest rate gap r̂^m_t, real exchange rate gap ẑ_t, shocks ε, inflation π, inflation expectations E_t[π_{t+4}], credibility stock c_t, etc.). - Note: The calibration of coefficients is based on the production-QPM paper (Benes and others (2016) per text). - Specific model features addressing Indian context - Phillips curve includes a non-linear output gap term implying increasing marginal effect on inflation as gap increases; becomes very flat at wide negative output gaps. - Expectations formation explicitly includes endogenous credibility-building: credibility stock c_t evolves with signals based on relative squared forecast errors between optimists and skeptics. - Credibility process calibration (Table 2): - c_t = ρ_c c_{t-1} + (1−ρ_c) ξ_t ; ρ_c = .80 .0 - Signal for revision ξ_t = (ε^L_{t+1})^2 − (ε^H_{t+1})^2 - Forecast error expected by optimists: ε^L_t = [ρ·π_{t-1} + (1−ρ)·π^*] − π^4_t with ρ = .4 ; π^* = .5 .0 - Forecast error expected by skeptics: ε^H_t = [ρ·π_{t-1} + (1−ρ)·π^H] − π^4_t with π^H = .8 - Boundary conditions: If π^4_t − [ρ·π^4_{t-1} + (1−ρ)·π^*] < 0, then ξ_t = 1. If π^4_t − [ρ·π^4_{t-1} + (1−ρ)·π^H] > 0, then ξ_t = 0. - Monetary policy minimizes quadratic loss including penalty for steep policy rate changes to reflect policymakers’ preference for gradualism and information transmission. ### Policy experiments and illustrative results from core-QPM - Disinflation experiment (from 5 percent to 4 percent) - Initial equilibrium: 5 percent inflation and nominal interest rate 7 percent (real rate 2 percent). - Baseline with initial low credibility: central bank hikes policy rate; rupee appreciates (exchange rate drops); negative output gap opens; inflation declines via exchange rate effect first and output gap later. - Cost in cumulative forgone output: 2 percent of annual GDP (sacrifice ratio of 2). - Credibility stock starts low and builds as inflation declines; as credibility approaches 1, lagged expectation and bias terms disappear improving output-inflation trade-off. - Hawkish policymakers: achieve target faster but with higher policy rate increases, sharper appreciation, wider negative output gap, larger sacrifice ratio. - Dovish policymakers (higher weight on output): tighten less, lower sacrifice ratio. - Disinflation with perfect credibility - 1-percent reduction in inflation achieved within a 6-quarter horizon at lower cumulative output cost: one-half percent of annual GDP. - With perfect credibility, tightening can be achieved without policy interest rate increase (real rate rise comes from lower expected inflation). - Policymaker preference over output gap matters little under perfect credibility. - Demand shocks (divine coincidence) - Optimal policy raises (cuts) policy rate to address positive (negative) demand shocks; this generally keeps inflation close to baseline while moderating output—no major conflict between output and inflation objectives. - Given flat Phillips curve under excess supply, negative demand shocks require somewhat larger output gap widening than positive shocks. - Demand shocks have little impact on credibility when inflation is well controlled. - Supply shocks (trade-offs and stagflation) - Nasty supply shock requires interest rate increase and larger negative output gap to maintain path to 4 percent target; trade-off between speed of return to target and output gap size. - Prompt, aggressive tightening prevents ratcheting up of long-term expectations and preserves credibility but at higher short-run output cost. - Favorable supply shock: inflation moderates faster, reaches 4 percent sooner, monetary policy eases, output gap closes faster. - Sequence of nasty supply shocks: requires more aggressive tightening and steep output gap widening; medium-term inflation can increase considerably and credibility may take a hit, but committed policy can still prevent long-term inflation expectations from ratcheting up. - Importance of prompt versus delayed responses - Delays in policy response to large supply shocks require much larger subsequent interest rate hikes and lead to larger cumulative output gaps and higher inflation — substantial deterioration in medium-term output-inflation trade-off. - Under perfect credibility, delay does less damage initially, but repeated delays can still undermine credibility. - Importance of credibility - Even with perfect credibility, long sequences of nasty shocks can worsen the policy trade-off with rising interest rates, widening negative output gaps, and higher inflation in the medium term; restoring reputation and getting inflation back to target incurs substantial output costs. ### Key quantitative points and indicators (preserved exactly as in source) - Operational inflation target: 4.0 percent, with 6.0 percent and 2.0 percent as the upper and lower tolerance levels respectively. - Food group weight in CPI: about 46 percent. - Disinflation initial and target values in experiment: from 5 percent to 4 percent. - Initial nominal interest rate in disinflation experiment: 7 percent (real rate of 2 percent). - Sacrifice ratio in baseline disinflation experiment: cumulative forgone output is 2 percent of annual GDP (i.e., a sacrifice ratio of 2). - Sacrifice ratio with perfect credibility: one-half percent of annual GDP for 1-percent disinflation achieved in 6 quarters. - Expectations/credibility calibration parameters (as presented in tables): - Output-gap coefficients: .05.0;08.0;60.0;07.0 (α1; α2; α3; α4 as listed). - Inflation coefficients: .005.;0;4.;0;06.;0;33.;0 (β1; β2; β3; β4 as listed). - Loss-function parameters: .5 .0; 1 ; 1 ; 98 .0 3 2 1 = λ1; λ2; λ3; β (as shown). - UIP/PRIME parameters: δ1; δ2 = .3 .0;6. .0 2 1 ; γ1 = .7 .0 1 - Expectations weights: κ = .1 ; b_π = .25 .0 - Credibility process: ρ_c = .80 .0 ; ρ = .4 ; π^* = .5 .0 ; π^H = .8 ; π^* reported as .5 .0 in table and ρ reported as .4 (see Table 2). - Note: All parameter notations and equation forms preserved exactly as in source tables and text. ### Policy implications and recommendations drawn from model experiments - Establishing a strong nominal anchor via FIT can reduce the amplitude and pass-through of supply shocks by anchoring expectations. - Building and preserving credibility is central: credible, prompt, and appropriately aggressive policy responses reduce long-run costs and improve output-inflation trade-offs. - Strengthening monetary transmission is critical before and during FIT implementation: address administered rates, deposit-rigidity issues, external benchmarks, statutory preemptions, and capital-flow sterilization practices. - Communication strategy must explicitly account for high food weight and trending relative prices; publish medium-term forecast paths showing route back to headline inflation target and explain transmission channels and expected duration of relative price effects. - Use of calibrated FPAS and QPM-style models that incorporate credibility formation, weakened UIP, and non-linear Phillips curve features helps to evaluate policy trade-offs and timing under India-specific frictions. *Source: wp1732 - 4.0 percent, with 6.0 percent and 2.0 percent as the upper and lower tolerance levels (IMF working paper content).* ### References ### References ### Journal articles - Aleem, A., 2010, “Transmission mechanism of monetary policy in India,” Journal of Asian Economics, Vol. 21, pp. 186–197. - Basu, K., 2011, “Understanding Inflation and Controlling It,” Economic and Political Weekly, Vol. 46, No.41, Oct 8–14, pp. 50–64. - Bhaumik, S. K., V. Dang, and A. M. Kutan, 2011, “Implications of Bank Ownership for the Credit Channel of Monetary Policy Transmission: Evidence from India,” Journal of Banking & Finance, Vol. 35, No. 9, pp. 2418–2428. - Blanchard, O. and J. Galí, 2007, “Real Wage Rigidities and the New Keynesian Model,” Journal of Money Credit and Banking, Vol. 39 (s1), pp. 35–65. - Gokarn, S., 2011, “The Price of Protein,” Macroeconomics and Finance in Emerging Market Economies, Vol. 4, No. 2; 327–335. - Mohanty, D. and J. John, 2015, “Determinants of inflation in India,” Journal of Asian Economics, Vol. 36, pp. 86–96. - Singh, B. and S. Pattanaik, 2012, “Monetary Policy and Asset Price Interactions in India: Should Financial Stability Concerns from Asset Prices be Addressed through Monetary Policy?” Journal of Economic Integration, Vol. 27, pp. 167–194. - Svensson, L. E. O., 1997, “Inflation Forecast Targeting: Implementing and Monitoring Inflation Targets,” European Economic Review, 41(6), pp. 1111-46. ### IMF working papers and related IMF outputs - Alichi, A., K. Clinton, C. Freedman, M. Juillard, O. Kamenik, D. Laxton, J. Turunen, and H. Wang, 2015, “Avoiding Dark Corners: A Robust Monetary Policy Framework for the United States,” IMF Working Paper No. 15/134. - Anand, R., D. Ding, and V. Tulin, 2014, “Food inflation in India: The Role for Monetary Policy,” IMF Working Paper No. 14/78. - Bhattacharya, R., I. Patnaik and A. Shah, 2011, “Monetary Policy Transmission in an Emerging Market Setting,” IMF Working Paper No. 11/5. - Clinton, K., C. Freedman, M. Juillard, O. Kamenik, D. Laxton, and H. Wang, 2015, “Inflation-Forecast Targeting: Applying the Principle of Transparency,” IMF Working Paper No. 15/132. - Das, S., 2015, “Monetary Policy in India: Transmission to Bank Interest Rates,” IMF Working Paper No. 15/129. - Freedman, C. and D. Laxton, 2009, “Why inflation targeting?” IMF Working Papers No. 09/86. - Patra, M. D. and M. Kapur, 2010, “A Monetary Policy Model without Money for India,” IMF Working Paper No. 10/183. - Patra, M. D. and P. Ray, 2010, “Inflation Expectations and Monetary Policy in India: An Empirical Exploration,” IMF Working Paper No. 10/84. ### Reserve Bank of India and RBI-affiliated working papers - Benes, J., K. Clinton, A. George, P. Gupta, J. John, O. Kamenik, D. Laxton, P. Mitra, G.V. Nadhanael, R. Portillo, H. Wang, and F. Zhang, 2016, “Quarterly Projection Model for India: Key Elements and Properties,” Reserve Bank of India Working Paper WPS 08/2016. - Kapur, M. and H. Behera, 2012, “Monetary Transmission Mechanism in India: A Quarterly Model,” RBI Working Paper No. 09/2012. - Khundrakpam, J. K., 2008, “How Persistent is Indian Inflationary Process, Has it Changed?,” Reserve Bank of India Occasional Papers Vol. 29, No. 2, Monsoon 2008. - Khundrakpam, J. K. and R. Jain, 2012, “Monetary Policy Transmission in India: A Peep Inside the Black Box,” Reserve Bank of India, Working Paper No. 11/2012. - Mohanty, D., 2012, “Evidence on Interest Rate Channel of Monetary Policy Transmission in India,” RBI Working Paper No. 6/2012. - Nadhanael, G. V., 2012, “Recent Trends in Rural Wages: An Analysis of Inflationary Implications,” Reserve Bank of India Occasional Papers, Vol. 33, No. 1 & 2. - Pandit, B. L., A. Mittal, M. Roy, and S. Ghosh, 2006, “Transmission of monetary policy and the bank lending channel: analysis and evidence for India,” DRG Study No. 25, Reserve Bank of India. - Patra, M. D., J. K. Khundrakpam, and A. T. George, 2014, “Post-Global Crisis Inflation Dynamics in India: What has Changed?” in Shekhar Shah, Barry Bosworth and Arvind Panagariya eds. India Policy Forum 2013-14, Volume 10, Sage Publications, July. - Reserve Bank of India, 2005, Report on currency and finance, 2003–04. - Reserve Bank of India, 2014, Report of the Expert Committee to Revise and Strengthen the Monetary Policy Framework, January. - Sonna, T., H. Joshi, A. Sebastian, and U. Sharma, 2014, “Analytics of Food Inflation in India,” RBI Working Paper Series (DEPR): 10/2014. ### Working papers, discussion papers, and chapters (non-IMF/RBI) - Bhatt, V. and K. N. Kishor, 2013, “Bank Lending Channel in India: Evidence from State-Level Analysis,” Empirical Economics, Vol. 45, No.3. - Bhattacharya, R. and A. S. Gupta, 2015, “Food Inflation in India: Causes and Consequences,” NIPFP Working Paper No. 2015-151, June. - Bhattacharya, R., I. Patnaik, and A. Shah, 2008, “Exchange rate pass-through in India,” Macro/Finance Group at NIPFP. - Darbha, G. and U. R. Patel, 2012, “Dynamics of Inflation ‘Herding’: Decoding India's Inflationary Process,” Working Paper 48, Global Economy and Development, Brookings. - Gulati, A., S. Jain, and S. Nidhi, 2013. “Rising Farm Wages in India: The ‘Pull’ and ‘Push’ Factors,” Commission for Agricultural Costs and Prices Discussion Paper No. 5. - Khundrakpam, J. K., 2007, “Economic reforms and exchange rate pass-through to domestic prices in India,” BIS Working Papers 225, Bank for International Settlements. - Kletzer, K., 2012, “Financial Friction and Monetary Policy Transmission in India,” in Chetan Ghate, ed., The Oxford Handbook of the Indian Economy, Oxford/New Delhi: Oxford University Press. - Mohan, R., 2008, “Monetary policy transmission in India,” in Transmission Mechanisms For Monetary Policy In Emerging Market Economies, Bank for International Settlements 2008, Vol. 35, pp 259–307. - Patra, M. D. and P. Ray, 2010, “Inflation Expectations and Monetary Policy in India: An Empirical Exploration,” IMF Working Paper No. 10/84. - Rajan, R., 2014, “Fighting Inflation,” speech delivered at FIMMDA–PDAI Annual Conference, February 26. ### Government and institutional documents - Government of India, 2015, “Agreement on Monetary Policy Framework between the Government of India and the Reserve Bank of India,” February. - Government of India, 2016, “Amendments to The Reserve Bank of India Act, 1934, Chapter XII, Miscellaneous, Part I, The Finance Act 2016,” pp. 82-87, May. *wp1732 - References* --- _Source: https://www.imf.org/-/media/files/publications/wp/wp1732.pdf_