1 February 2002 Banco Central do Brasil Inflation Targeting in Brazil Inflation Targeting in Brazil Ilan Goldfajn
2 Brazilian IT Framework Implementation in July 1st, 1999Implementation in July 1st, 1999 Headline IPCA was chosenHeadline IPCA was chosen Targets were 8%, 6% and 4% for 1999, 2000 and 2001, with a ± 2% tolerance intervalTargets were 8%, 6% and 4% for 1999, 2000 and 2001, with a ± 2% tolerance interval Targets are 3.5% for 2002 and 3.25% for 2003, with a ± 2% tolerance intervalTargets are 3.5% for 2002 and 3.25% for 2003, with a ± 2% tolerance interval Absence of escape clausesAbsence of escape clauses
3 Inflation in Brazil - IT Regime Annual IPCA X Targets TargetIPCA
4 12-month IPCA X Targets Dotted lines represent the inflation targets for 1999, 2000, 2001 and 2002 Inflation Rate - IPCA (% over year ago) Inflation Targeting 0% 2% 4% 6% 8% 10% Jan-97Jul-97Jan-98Jul-98Jan-99Jul-99Jan-00Jul-00Jan-01Jul-01Jan
5 IPCA and Exchange Rate Sep-99 Nov-99 Jan-00 Mar-00 May-00 Jul-00 Sep-00 Nov-00 Jan-01 Mar-01 May-01 Jul-01 Sep-01 Nov-01 Jan Exchange Rate t-3 (3-month annualized accumulated variation; left scale) IPCA t (3-month annualized accumulated variation; right scale )
6 Interest Rate 45% Over-Selic Rate % p.y. (daily figures: January 4, 1999 to February 26, 2002) Jan 99 MaySepJan 00 MaySepJan 01 MaySepJan 02
7 Inflation Targeting Regime: Practical Issues –To Core or not to Core –Supply versus Demand Shocks (expected supply effect?) –Transparency Issues –Different expectations from market’s
8 Macroeconomic Models Instrumental for managing monetary policy under ITInstrumental for managing monetary policy under IT Powerful tool for communicating monetary policy (inflation fan charts)Powerful tool for communicating monetary policy (inflation fan charts)
9 Main Technical Challenges Exchange rate determination: UIP, random walk, PPP, other approaches.Exchange rate determination: UIP, random walk, PPP, other approaches. Exchange rate pass through.Exchange rate pass through. Estimation of potential output.Estimation of potential output. Inflation expectations: backward vs forward.Inflation expectations: backward vs forward. How to deal with government managed prices.How to deal with government managed prices. How to input board´s assumptions not covered by the model.How to input board´s assumptions not covered by the model.
10 Monetary Policy Decision Process Use the broadest information set as possible.Use the broadest information set as possible. Judgmental analysis is very important.Judgmental analysis is very important. Use macro models to discipline and make discussion more rigorous.Use macro models to discipline and make discussion more rigorous. Use several models to check consistency, but choose the main one.Use several models to check consistency, but choose the main one.
11 Forecasting Process ScenariosScenarios –Model specification The Copom defines which relations are relevant for the monetary policy decision.The Copom defines which relations are relevant for the monetary policy decision. –Exogenous variables The most likely path for the exogenous variables are set by the Copom after interacting with the staff.The most likely path for the exogenous variables are set by the Copom after interacting with the staff. –Shocks The timing, magnitude, variance and skewness are set by the Copom after interacting with the staff.The timing, magnitude, variance and skewness are set by the Copom after interacting with the staff.
12 Forecasting Tools Small-scale macroeconomic modelsSmall-scale macroeconomic models VARs modelsVARs models Leading IndicatorsLeading Indicators Core inflationCore inflation
13 VAR Models for Short-run Inflation Forecasting Objective: provide short-run forecasts for the structural modelObjective: provide short-run forecasts for the structural model Endogenous variables: interest rate, exchange rate, money, GDP, industrial production, unemployment and construction price indexEndogenous variables: interest rate, exchange rate, money, GDP, industrial production, unemployment and construction price index Sample: post Real PlanSample: post Real Plan Frequency: monthly and quarterlyFrequency: monthly and quarterly
14 Leading Inflation Indicators Composite index built as a combination of economic variables that show leading relation to inflation.Composite index built as a combination of economic variables that show leading relation to inflation. The methodology used to combine the economic series extracts their common movements related to inflation process.The methodology used to combine the economic series extracts their common movements related to inflation process. The main objective is to predict turning points of inflation in real time.The main objective is to predict turning points of inflation in real time. Also provides linear forecast using a VAR system combining the index with inflation.Also provides linear forecast using a VAR system combining the index with inflation. Components follow a general pattern: monetary, real sector, financial and external shocks variables.Components follow a general pattern: monetary, real sector, financial and external shocks variables.
15 Leading Indicators :0198:0799:0199:0700:01 Inflation Indicator 1 Indicator 2
16 Core Inflation Broad consumer price index (IPCA) - 52 components (items)Broad consumer price index (IPCA) - 52 components (items) Trimmed-mean with smoothing itemsTrimmed-mean with smoothing items Trim 20% of each tail to minimize the difference with a 13-month centered moving average of inflationTrim 20% of each tail to minimize the difference with a 13-month centered moving average of inflation
17 IPCA and Core Measure IPCA and core measure - monthly changes Jan 97 Apr 97 Jul 97 Oct 97 Jan 98 Apr 98 Jul 98 Oct 98 Jan 99 Apr 99 Jul 99 Oct 99 Jan 00 Apr 00 Jul 00 IPCACore PeriodIPCACore Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep
18 IPCA and Core Measure IPCA and core measure - 12-month changes Jan 98 Apr 98 Jul 98 Oct 98 Jan 99 Apr 99 Jul 99 Oct 99 Jan 00 Apr 00 Jul 00 IPCACore PeriodIPCACore Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep
19 General Structure of Models Other determinants Risk Premium Fiscal Variables Exchange Rate Aggregate Demand Inflation Interest Rates UIPIS Phillips Interest Rate Rules / Exogenous Path IS UIP
20 Building Blocks Demand (IS Curve)Demand (IS Curve) Supply (Phillips Curve)Supply (Phillips Curve) exchange rate passthroughexchange rate passthrough forward x backward lookingforward x backward looking inflation expectationinflation expectation Exchange-rateExchange-rate exogenousexogenous endogenous x exogenousendogenous x exogenous
21 Modeling the Pass Through where: p F log of foreign producer price index e log of exchange rate E exchange rate constant 4 t e ))(( t F t ep t t E E
22 Treatment of Inflation Expectations Forward-looking Phillips curveForward-looking Phillips curve AlternativesAlternatives –Institutional approach i t fortargetinflation the theis where * it E it it it itt , 2 1)( * * *
23 Treatment of Inflation Expectations AlternativesAlternatives –Model Consistent (recursive solution)* where a b means that b is in a neighborhood of a. * The convergence is usually achieved in less than 20 iterations. )1( 1 )1( 1 )( until n t n tt E )( 1 )1( 1 and )( n t n tt E )0( guess} initial{)( itt E Do model the theSolve modelthesolve
24 Exchange Rate Determination Exchange rate follows the equation below, based on a UIP:Exchange rate follows the equation below, based on a UIP:where: e log of exchange rate i F log of foreign interest rate x log of risk premium residual including the expectation variations assumed white noise ttt F tt t F ttttt ixie xiieeE 1
25 Exchange Rate Determination Modeling the risk premiumModeling the risk premium –exogenous path –endogenous determination depends on PSBR/GDP ratio (primary) and other risk premium determinants.depends on PSBR/GDP ratio (primary) and other risk premium determinants.where: X risk premium (SOT) in basis points PR PSBR/GDP ratio (primary) Z j other risk premium determinants Nj ttjjttt j ZPRXX 3,3211
26 Forecasting Fan ChartFan Chart –Measure of central tendency median: the model estimate the mean, median is obtained using the variance and skewness of a two-piece normal distribution.median: the model estimate the mean, median is obtained using the variance and skewness of a two-piece normal distribution. –Shocks stylization The magnitudes are obtained from out of model estimation. The assessment of variance and skewness are subjective.The magnitudes are obtained from out of model estimation. The assessment of variance and skewness are subjective. –Variance It is calculated using the historical forecast error as benchmark. However, it can be adjusted by subjective assessment.It is calculated using the historical forecast error as benchmark. However, it can be adjusted by subjective assessment.
27 Inflation Forecast Forecasted IPCA - Inflation with interest rate fixed at 19.00% p.y. (accumulated inflation in 12 months)
28 Forecast: IPCA Central Projection YearQ Confidence Interval 50% 30% 10% IPCA with 19.00% p.y. fixed interest rate Note: Accumulated inflation in 12 month, in % p.y. The values correspond to the ones shown in inflation fan chart.
29 Inflation Market Expectations Jun 24 Jul 29 Sep 02 Oct 08 Nov 17 Dec 22 Jan 28 Mar 03 Apr 11 May 18 Jun 23 Jul 28 Sep 01 Oct 09 Nov 16 Dec 21 Jan 29 Mar 07 Apr 11 May 18 Jun 26 Jul 31 Sep 04 Oct 10 Nov 20 Dec 26 Jan 31 Source: Investor Relations Group / Banco Central (%) Inflation Market Expectations median of IPCA for 1999, 2000, 2001, 2002 and 2003 (daily figures: June 24, 1999 to February 22, 2002
30 Interest Rate Market Expectations Over-Selic Rate Market Expectations Median of Over-Selic Rate for 2001, 2002 and 2003 (daily figures: August 1st, 2001 to February 22, 2002) /1/01 8/8/01 8/15/018/22/018/29/01 9/5/01 9/13/019/20/019/27/0110/4/01 10/11/0110/19/0110/26/01 11/6/01 11/13/0111/21/0111/28/01 12/5/01 12/12/0112/19/0112/27/01 1/4/02 1/11/021/18/021/25/02 2/1/022/8/02 % p.y Source: Investor Relations Group / Banco Central
31 Exchange Rate Market Expectations Exchange Rate (R$/US$) Market Expectations Median of R$/US$ for 2001, 2002 and 2003 Source: Investor Relations Group/Banco Central /1/01 8/10/018/21/018/30/019/11/019/20/0110/1/01 10/10/0110/22/0110/31/0111/13/0111/23/01 12/4/01 12/13/0112/24/01 1/4/02 1/15/021/24/02 2/4/02 2/14/02 R$/US$ (daily figures: August 1st, 2001 to February 22, 2002)
32 GDP Market Expectations Source: Investor Relations Group/Banco Central GDP Growth Market Expectations Median of GDP growth for 2001, 2002 and 2003 Median of GDP growth for 2001, 2002 and 2003 (daily figures: August 1st, 2001 to February 22, 2002) (daily figures: August 1st, 2001 to February 22, 2002) /1/01 8/9/01 8/17/018/27/01 9/4/01 9/13/019/21/0110/1/0110/9/01 10/18/0110/26/01 11/7/01 11/16/0111/26/01 12/4/01 12/12/0112/20/0112/31/01 1/9/02 1/17/021/25/02 2/4/02 2/13/02 % p.y
33 Recent Challenges –Nominal (and real) exchange rate changes –Prices administered by contracts –Quarterly targets within IMF program –Fiscal dominance? Recent Challenges in an Inflation Targeting Regime
34 Exchange Rate Changes –How to deal with large RER adjustments –Pass through and repressed pass through –Future exchange rate Bonus
35 Nominal Exchange Rate Evolution of the Nominal Exchange Rate JanMaySepJanMaySepJanMaySepJan Figures updated up to Feb 26th, 2002 R$/US$
36 Exchange Rate Exchange Rate: January February 2002 (R$/US$) Inflation Targeting Jan-98 May-98 Sep-98 Jan-99 May-99 Sep-99 Jan-00 May-00 Sep-00 Jan-01 May-01 Sep-01 Jan-02
37 Real Exchange Rate at January 2002 wholesale prices Evolution of the Real Exchange Rate (R$/US$) (January 2002=100) Average in the period Real Exchange Rate at Jan 2002 prices (WPI) Jan 1989 Jan 1990 Jan 1991 Jan 1992 Jan 1993 Jan 1994 Jan 1995 Jan 1996 Jan 1997 Jan 1998 Jan 1999 Jan 2000 Jan 2001 Jan 2002
38 Real Exchange Rate at January 2002 consumer prices Evolution of the Real Exchange Rate (R$/US$) Real Exchange Rate at Jan 2002 prices (CPI-Fipe) Average in the period (January 2002=100) Jan 1989 Jan 1990 Jan 1991 Jan 1992 Jan 1993 Jan 1994 Jan 1995 Jan 1996 Jan 1997 Jan 1998 Jan 1999 Jan 2000 Jan 2001 Jan 2002
39 –Is inflation targeting inconsistent with an IMF program? –Inflation targeting and prices administered by contracts. Two Interesting Issues
40 Inflation and Prices Administered by Contracts 12-Month Jan 99 May 99 Sep 99 Jan 00 May 00 Sep 00 Jan 01 May 01 Sep 01 Jan 02 IPCAAdmin.Livres (%) Prices administered by contracts IPCA Free prices
** Reflects the effect of the updated projection of the prices only from February to December * Includes the January inflation effect. * Includes the January inflation effect. (2002:4.68 => 4.80; 2003:4.0 => 4.0) Oil-by products (constant since Feb 9) Basic Scenario Gasoline 2002 (-13.95) Diesel 2002 (-1.93) Bottled Gas (14.80) E( ) 2002 (5.44 -> 5.72) 2003 (3.47 -> 3.85) Dollar Gasoline and Diesel ** Gasoline 2002 ( > -11.9) Bottled Gas ** 2002 (9.0 -> 17.9) 2003 Copom January Observations January * 2002 (0.40 -> 0.52) Considers a updating for the prices administered by contracts in January Administered by contracts (Total) ** (2.37 -> 2.42) Transition Table - Fixed Interest
42 IMF Inflation Targets Jan-99 Mar-99 Jun-99 Sep-99Dec-99 Mar-00 Jun-00 Sep-00Dec-00 Mar-01 Jun-01 Sep-01Dec-01 Mar-02 Jun-02 Sep-02 IPCA 12-month Central target Inner band Outer band IMF Inflation Targets
43 IMF Agreement IMF Agreement - IPCA Targets Interval
44 Fiscal Targets - Primary Surplus Fiscal Targets - IMF Primary Surplus R$ billion Target Occurred Year cumulative data Mar-99 Jun-99 Sep-99 Dec-99 Mar-00 Jun-00 Sep-00 Dec-00 Mar-01 Jun-01 Sep-01 Dec-01 Mar-02 Jun-02 Sep-02
45 Net Public Sector Debt Dynamics 36.9 Up to Dec 2001: occurred Forecasted from December % of GDP
46 –Why has monetary policy been credible in Brazil? –What is the sustainable growth rate in Brazil? –What is the current pass through coefficient? A Few Important Questions
47 GDP Growth (% real variation) /* 2001 and 2002 projections * 2002 *
48 GDP and Potencial GDP In R$ millions of ,000 1, GDP Potencial GDP GDP Potential GDP
49 Potential GDP AnnualHP Total Factor Productivity Annual and HP Smoothed
50 (*) In 1999 prices Potencial GDP: Scenarios and Forecasts INVESTMENT * Hip. 1 Hip. 2 Hip % 3.30%3.55%3.62% 1.00% 3.60%3.78%3.85% 1.20% 3.81%3.99%4.06% TFP 1.50% 4.11%4.30%4.37% Hip.1 - Investment equals to 19,5% - 20%-20,5%-21%-21,5% in , respectively. Hip.2 - Investment equals to 20%-21%-22%-23% -24% in , respectively. Hip.3 - Investment equals to 20%-21,2%-22,4%-23,6%-2,84% in , respectively. Potential GDP
51 Pass Through Evolution of the Pass Through Coefficient :11997:21997:31997:41998:11998:21998:31998:41999:11999:21999:31999:42000:12000:22000:32000:42001:12001:22001:3
52 Pass Through Pass Through Comparison MonthsShortLongG&W w/for w/for /2 America (2)(4) 3 months months after 1 year months
53 –Credibility is a moving average concept. Fiscal is important. –Growth rate in Brazil depends on external financing restriction and reforms. –Pass through from exchange rate has been moderate. Future? –Two issues: IMF and IT and prices administered by contracts. Assessments
54 –Strong fiscal performance. –GDP did not collapse. Long-awaited crisis allowed private sector hedging. –Low pass through: output gap, overvaluation, and initial inflation. –Credibility of the IT Regime. Relative Success, Why?