Core Inflation for Emerging EconomiesMichael F. Bryan*Vice President and Senior EconomistFederal Reserve Bank of AtlantaGlobal Interdependence Center*Co-authored with Brent Meyer (Federal Reserve Bank of Cleveland) and Ellyn Terry (Federal Reserve Bank of Atlanta)

Core Inflation for an Emerging Economy1. Food represents a huge share of the consumers marketbasket in an emerging economy2. The ex-food and energy approach to core inflation is probably not an efficient guide for an inflation minded central bank and probably more so for a central bank in an emerging economy.3. Some food items are actually good inflation indicatorssome non-food goods are not. 4. Various techniques can be used to improve the signal-to-noise of a high-frequency (monthly) inflation statistic, giving the central bank the opportunity to spot worsening/improving inflation trends earlier than they might otherwise. 5. Trimmed-mean estimators offer a extremely simple technique for improving the inflation signal in the inflation data.

Important Cautions1. I do not necessarily represent the views of the Federal Reserve Board, or the Federal Reserve Bank of Atlanta.2. This work is still incompleteI cannot match the official Zambian CPI exactly using the component data I have.3. I have only a very limited knowledge of Zambian monetary policy (but hope to have greater knowledge on this subject before I return home.)

Whats the Problem that a Core Inflation Measure is the Answer? Federal Reserve Monetary PolicySet the funds rate so to achieve two objectives: 1) maximum sustainable employment and 2) price stability.i ff = (r* + )+ 0.5 (y-y*) + 0.5 ( -*)Zambian Monetary PolicyEstablish a level of reserves that produces the broad money growth consistent with an inflation objective.Policy action Inflation resultIn either case

Zambian Inflation(12-month percent change)Overall CPIInflation objective

Zambian Inflation(12-month percent change)Overall CPIMonthly, nsaInflation objective

How Does a Central Bank Deal with the Volatility in the High-Frequency Price Data?Computes (12-month) TrendsTrends are, of course, very backward looking and can only tell the central bank when it has gone off course, not when it is going off course.Core Inflation StatisticsAn attempt to preserve the timeliness of the data by reducing the noise in the data by statistical techniques.

Alternative Core ApproachesVariance Weighted Price StatisticsReweight the price statistic on the (inverse) basis of its volatility.Dynamic Factor/Kalman Filter StatisticsHave the data identify a common component in the price data.Reweight the price statistic such that the most volatile components get no weightThis is the most common approachthe CPI excluding something.

core inflation statistics OF SELECTED CENTRAL BANKS

(* Inflation targeting countries ** Core statistic used as a target or objective)

Country

Core Inflation Statistic

Australia**

CPI less mortgage interest payments, government controlled prices, and energy items.

Belgium

CPI less energy, potatoes, and fruit and vegetables.

Canada**

CPI less indirect taxes, food and energy items.

Finland**

CPI less housing capital costs, indirect taxes, and government subsidies.

France**

CPI excluding changes in taxes, energy prices, food prices, and regulated prices.

Greece

CPI excluding food and fuels.

Israel*

CPI less government goods, housing, fruit and vegetables.

Japan

CPI less fresh foods.

Netherlands

CPI less vegetables, fruit, and energy.

New Zealand**

CPI less commodity prices, government controlled prices, interest and credit charges.

Philippines

A statistical trend line.

Portugal

10% trimmed mean of the CPI.

Spain*

CPI less mortgage interest payments.

Sweden*

CPI excluding housing mortgage interest and effects of taxes and subsidies (UND1), UND1 excluding petroleum goods (UND2), and UND1 less mainly imported goods (UNDINH).

United Kingdom**

Retail Price Index less mortgage interest payments.

United States

CPI less food and energy items.

Income and Food Expenditure(sample of 114 nations, 1996 data)Food expenditure as a share of total expenditurePer capita GDP ZambiaUnited StatesSub-Sahara Africa

Zambian Retail Price ChangesFebruary 2009 (NSA, annualized)Weighted FrequencyMean = 1.4%Standard Dev. = 6.3%Annualized Year-To-Date Percent ChangeWEIGHTED MEANNormal distribution

Retail Price Change Distribution Characteristics(Arranged by average inflation, annualized)

Sheet1

MonthlyMeanSt. Dev.SkewKurt

Brazil206.24.00.614.6

Argentina123.26.31.211.0

Mexico42.85.12.646.2

Colombia23.22.41.010.1

South Africa12.01.71.613.1

Israel10.01.60.110.6

UK8.11.90.820.1

Sweden6.11.91.119.1

New Zealand*7.21.90.76.9

US5.20.70.311.6

Japan4.51.90.832.9

Canada3.41.50.422.0

Germany2.81.20.026.3

Sheet2

Sheet3

The Menu-Cost Model of Observed Price Changeswith expected inflationfrequencyfrequencyupperlimitlowerlimitDesired Price Change DistributionObserved Price Change Distribution

Hypothetical Mixed Normal DistributionFrequency0Standard normal,variance=1,kurtosis=3High variance normal,variance=9,kurtosis=3

Chart1

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