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Statistical Implications of Inflation Targeting : Getting the Right Numbers and Getting the Numbers Right

Statistical Implications of Inflation Targeting : Getting the Right Numbers and Getting the Numbers Right
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Series:
Books
Author(s):
Carol Carson, Claudia Dziobek, and Charles Enoch
Publisher:
INTERNATIONAL MONETARY FUND
Published Date:
September 2002
DOI:
http://dx.doi.org/10.5089/9781589061323.071
ISBN:
9781589061323
Page:
396
This book brings together the experience of central banks and national statistical agencies in countries that focus their monetary policy on inflation targets. Inflation targeting has led to a close interface between these two sets of institutions. When the performance of a central bank is measured in terms of specified price indices, which are usually compiled and disseminated by the national statistical agency, the role of national statistical agencies becomes central to the credibility of monetary policy. Data needs and uses have also shifted, with implications for national and international statistics compilation: market data have gained in importance; less emphasis is placed on traditional monetary aggregates; and greater attention is paid to timeliness, adherence to sound economic accounting standards, and other aspects of data quality.
Statistical Implications of Inflation Targeting
Front Matter

Front Matter

Author(s):
Carol Carson, Claudia Dziobek, and Charles Enoch
Published Date:
September 2002
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Statistical Implications of Inflation Targeting

GETTING THE RIGHT NUMBERS

AND

GETTING THE NUMBERS RIGHT

EDITORS

CAROL S. CARSON

CHARLES ENOCH

CLAUDIA DZIOBEK

Papers presented at the

IMF Seminar on Statistical Implications

of Inflation Targeting, Washington, D.C.,

February 28-March 1, 2002

STATISTICS DEPARTMENT

INTERNATIONAL MONETARY FUND

© 2002 International Monetary Fund

Production: IMF Graphics Section

Cover design: Lai Oy Louie

Figures: Theodore F. Peters, Jr.

Typesetting: Choon Lee

Cataloging-in-Publication Data

Statistical implications of inflation targeting : getting the right numbers and getting the numbers right / editors, Carol S. Carson, Charles Enoch, Claudia Dziobek — [Washington, D.C.] : International Monetary Fund, Statistics Dept., 2002.

p. cm.

Papers presented at the IMF Seminar on Statistical Implications of Inflation Targeting, Washington, D.C., February 28-March 1, 2002. ISBN 1-58906-132-2

1. Inflation (Finance) — Statistics — Congresses. 2. International Monetary Fund — Congresses. I. Carson, Carol S. II. Enoch, Charles. III. Dziobek, Claudia Helene, 1956– IV. International Monetary Fund. Statistics Dept.

HG229.S73 2002

Price: $42.50

Please send orders to:

International Monetary Fund, Publication Services

700 19th Street, N.W., Washington, D.C. 20431, U.S.A.

Tel.: (202) 623-7430 Telefax: (202) 623-7201

E-mail: publications@imf.org

Internet: http://www.imf.org

Contents

The following conventions are used in this volume:

… to indicate that data are not available or not applicable;

— to indicate that the figure is zero or less than half the final digit shown;

– between years or months (for example, 1991–92 or January-June) to indicate the years or months covered, including the beginning and ending years or months;

/ between years or months (for example, 1991/92) to indicate a fiscal or financial year.

“Billion” means a thousand million; “trillion” means a thousand billion.

“Basis points” refer to hundredths of 1 percentage point (for example, 25 basis points are equivalent to ¼ of 1 percentage point).

Minor discrepancies between constituent figures and totals are due to rounding.

* * *

As used in this report, the term “country” does not in all cases refer to a territorial entity that is a state as understood by international law and practice. As used here, the term also covers some territorial entities that are not states but for which statistical data are maintained on a separate and independent basis.

Foreword

In recent years, macroeconomic policy formulation has moved to more explicit use of statistics; at the same time, added attention is being given to the development of forward-looking indicators. A prominent example is the monetary policy framework of inflation targeting that is being adopted by a growing number of countries. While many of the conceptual aspects of inflation targeting have been studied in detail in recent years, there has been little attention to statistical issues: Which statistics are needed? What does it take to compile them? And what is the role of the public sector, including the IMF, in encouraging good practice in compilation and use?

Monetary policy committees, rather than focusing exclusively on money and credit aggregates, look increasingly at market-based statistics—for instance, at asset prices and market-derived implicit inflation forecasts. Such data have traditionally not been integrated into a country’s typical data framework. The Seminar on the Statistical Implications of Inflation Targeting, held in Washington, D.C., during February 28-March 1, 2002, provided an opportunity for statistical agencies and central banks to explore together the issues that are of common interest in this regard. The importance of developing new forms of collaboration between statistical agencies and central banks emerged as a central theme of the seminar.

The seminar examined country experience in these areas. Some areas were identified where inflation targeting requires additional or more detailed statistics from those used hitherto. Even more important, seminar participants emphasized the greater discipline involved in handling information, the added transparency, and hence the enhanced focus on data quality. We hope that the seminar proceedings provide central banks, statistics agencies, academics, and outside observers with some new ideas and some guidance on the information aspects of inflation targeting regimes.

Carol S. Carson

Charles Enoch

Claudia Dziobek

Acknowledgments

Many of our colleagues helped to put this volume together. The editors gratefully acknowledge overall guidance from Thomas McLoughlin; editorial support from James McEuen, Ellen Coughlin, and Joan Gibson; research support from Silvano Spencer and Mbaye Gueye; and administrative assistance from Niccole Braynen-Kimani, Elia Cadena, Janice Irving, Lidia Tokuda, and Kris Bengtson. Jennifer Kelly coordinated the administrative arrangements for the seminar.

Abbreviations

1993 SNA

System of National Accounts 1993

ADSPI

Adjusted domestic supply price index

ARCH

Autoregressive conditional heteroskedasticity

BDR

Banco de la República (Colombia)

BOM

Bank of Mexico

BOT

Bank of Thailand

bp

Basis point

BPM5

Balance of Payments Manual, fifth edition

BSP

Bangko Sentral ng Pilipinas

CAEMC

Central African Economic and Monetary Union

CAPM

Capital asset pricing model

CBB

Central Bank of Brazil

CBC

Central Bank of Chile

CCAPM

Consumption-based capital asset pricing model

CEPR

Centre for Economic Policy Research

CII

Core inflation index

CNB

Czech National Bank

COICOP

Classification of individual consumption by purpose

COLA

Cost-of-living adjustment

COLI

Cost-of-living index

COPOM

Monetary Policy Committee (Brazil)

CPI

Consumer price index

CPI-W

Consumer price index for wage earners and clerical workers

CPIX

Consumer price index excluding interest rates on mortgage bonds or excluding fuel prices (South Africa)

CPIX

Consumer price index excluding fuel prices (Chile)

CSO

Central Statistical Office (U.K.)

DANE

Departamento Administrativo Nacional de Estadísticas (Colombia)

DBCC

Development Budget Coordination Committee (Philippines)

DMO

Debt Management Office (U.K.)

DQAF

Data Quality Assessment Framework (IMF)

DSBB

Dissemination Standards Bulletin Board (IMF)

DSPI

Domestic supply price index

DFP

Domestic final purchases

EC

European Commission

ECB

European Central Bank

ECCU

Eastern Caribbean Currency Union

ECOFIN

Economic and Financial Affairs Council

ECU

European currency unit

EMU

Economic and Monetary Union

ERM

Exchange rate mechanism

ERM II

Exchange rate mechanism, phase II

ESA

European System of Accounts

ESCB

European System of Central Banks

EU

European Union

EUT

European Union Treaty

f.o.b.

free-on-board

FSI

Financial soundness indicator

FTSE

Financial Times Stock Exchange

G-10

Group of Ten countries

GDDS

General Data Dissemination System (IMF)

GDP

Gross domestic product

GTCF

Gross fixed capital formation deflator

GNP

Gross national product

HICP

Harmonized index of consumer prices

HM

Her Majesty’s (U.K.)

IBGE

Institute of Geography and Statistics (Brazil)

IFS

International Financial Statistics (IMF)

IICP

Interim index of consumer prices (EU)

IL

Index-linked

ILG

Index-linked gilt

INE

Instituto Nacional de Estadísticas (Chile)

IOPI

Implicit output price index

IRP

Inflation risk premium

ITS

Inflation term structure

LAPFs

Life assurance and pension funds (U.K.)

LIBOR

London interbank offered rate

MBIEs

Market-based inflation expectations

MBRE

Market-based interest rate expectations

MCI

Monetary Conditions Index (IMF)

MFR

Minimum funding requirement

MPC

Monetary Policy Committee (U.K.)

MPR

Monetary Policy Report (Chile)

MUICP

Monetary Union index of consumer prices (EU)

NDA

Net domestic assets

NIR

Net international reserves

NSDP

National Summary Data Page

NSO

National Statistics Office (Philippines)

OECD

Organization for Economic Cooperation and Development

OLS

Ordinary least squares

ONS

Office for National Statistics (U.K.)

OPEC

Organization of Petroleum Exporting Countries

PPI

Producer price index

QPM

Quarterly Projection Model (Bank of Canada)

RBA

Reserve Bank of Australia

REH

Rational expectations hypothesis

ROSC

Report on the Observance of Standards and Codes (IMF)

RODS

Regime-oriented data coverage standard

RPI

Retail price index (U.K.)

RPIAC

Retail Prices Index Advisory Committee (U.K.)

RPIX

Retail price index excluding mortgage interest payments (U.K.)

RSDF

Real stochastic discount figure

SDDS

Special Data Dissemination Standard (IMF)

SDR

Special drawing right (IMF)

SLA

Service-level agreement (U.K.)

SPC

Statistical Program Committee

TASE

Tel Aviv Stock Exchange

TIPS

Treasury Inflation Protected Securities (U.S.)

TIS

Manual on Statistics of International Trade in Services

VAR

Vector auto regression

VRP

Variable roughness penalty

WAEMU

West African Economic and Monetary Union

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