Measuring and Interpreting core inflation: evidence from Italy - PowerPoint PPT Presentation

11 th Ottawa Group Meeting Measuring and Interpreting core inflation: evidence from Italy Biggeri L*., Laureti° T and Polidoro F*. *Italian National Statistical Institute (Istat), Rome, Italy; ° University of Naples “Parthenope”, Naples, Italy Neuchâtel, 27- 29 May 2009 1

11th Ottawa Group Structure of the paper Meeting 1. Introduction 2. A brief review of the definitions and methods for measuring core inflation 3. The current measures of core inflation in Italy 4. Data set description and organisation of analyses on Italian data 5. Analysis of the results � 5.1 Time series approach � 5.2 Exclusion based methods � 5.3 Stochastic approach: analysis of price change distributions � 5.4 Stochastic approach: asymmetric trimmed means � 5.5 Stochastic approach: Median, Weighted Median, 54 th percentile � 5.6 Stochastic approach: assessing the performance of the estimators 6. Concluding remarks 2 Neuchâtel, 27- 29 May 2009

11th Ottawa 1. Introduction Group Meeting To suggest appropriate measures for estimating and analysing core inflation to be used by the The aim of this paper Bank of Italy and the Italian National Statistical Institute (Istat) To identify reliable measures of core inflation for a specific country analyse the specific economic situation and the distribution of the price changes the choice of method should be tailor-made to the needs of the country We carried out a very detailed analysis based on more than 500 monthly price indices for representative products from 1996 to 2008 3

11th 2. A brief review of the definitions and methods for measuring core inflation Ottawa Group Meeting various definitions more suitably linked to the methods Two broad concepts: � the persistent component of measured inflation � the generalised component of measured inflation Keeping in mind •These concepts •The characteristics of the data necessary for carrying out the estimations The methods can be classified Group 1 Group 2 � time series to � cross-section data on the distinguish trend from distribution of price changes for each temporary shocks month, to obtain adequate and robust smoothing techniques, estimations of core inflation for each moving average, month separately exponential 2.1 Exclusion-Based Methods smoothing, Arima,Multivariate 2.2 Limited influence estimators methods, etc. 4 median, trimmed means, etc. Neuchâtel, 27- 29 May 2009

11th 3. Data set description and organisation of the analyses on Italian data (a) Ottawa Group Meeting Very detailed data set DATA DESCRIPTION: DATA DESCRIPTION: � Monthly CPIs for the whole nation concerning representative elementary � Monthly CPIs for the whole nation concerning representative elementary items items � Revision of the basket and the weighting system annually � Revision of the basket and the weighting system annually � Number of elementary indices differ from year to year (never below 530 ) � Number of elementary indices differ from year to year (never below 530 ) CALCULATIONS: CALCULATIONS: � Period: January 1996-December 2008 � Period: January 1996-December 2008 � Computation of price changes: � Computation of price changes: � Elementary indices and the general CPI � Elementary indices and the general CPI � Horizon k=1 and k=12 � Horizon k=1 and k=12 � Month-on-previous month and year on previous year changes � Month-on-previous month and year on previous year changes 0, t 0, t P P π = − π = − 1 12 i i 1 1 � Elementary index � Elementary index − − it 0, t 1 it 0, t 12 P P i i 0; t I 0; t I Π = − 12 Π = − 1 1 1 � Overall CPI � Overall CPI − t − 0; t 12 t 0; t 1 I I 5 Neuchâtel, 27- 29 May 2009

11th 3. Data set description and organisation of analyses on Italian data (b) Ottawa Group We computed the following measures of underlying or core inflation : Meeting We computed the following measures of underlying or core inflation : � Time series approach, using ARIMA model; � Time series approach, using ARIMA model; � Exclusion Based approach , excluding products on the basis of � Exclusion Based approach , excluding products on the basis of some measure of volatility of their prices; some measure of volatility of their prices; � Stochastic approach , using Median and Weighted median, Mean � Stochastic approach , using Median and Weighted median, Mean Percentile and Asymmetric Trimmed means Percentile and Asymmetric Trimmed means Assessing the performance of the estimators � Tracking trend inflation • Benchmark : 12 month centred moving average • Indicators : a) Root Mean Square Error (RMSE) b) Mean Absolute Deviation (MAD) � Efficient, robust and unbiased � the reduction in volatility •standard deviation •a short term volatility measure � Unbiasedness •Comparing averages •Specific statistical tests 6 Neuchâtel, 27- 29 May 2009

11th 4. The current measures of core inflation in Italy - ISTAT Ottawa Group In order to analyse the inflation process ISTAT calculates decomposition measures Meeting concerning sub-component indices, such as for processed and unprocessed foods, energy products, tobaccos, services, durable and non durable goods etc. Besides, ISTAT computes a measure of core inflation for the general CPI excluding energy and unprocessed food products -EBM1- (42 products excluded) 12 month rates of change of CPIs, EBM1, Energy products and unprocessed food prices indices. Year 1997 – 2009. 5.0 20.0 All items CPI EBMI Energy products (right scale) unprocesed food (right scale) 4.0 15.0 3.0 10.0 2.0 5.0 1.0 0.0 0.0 -5.0 -1.0 -2.0 -10.0 Jan-97 Sep-97 Jan-98 Sep-98 Jan-99 Sep-99 Jan-00 Sep-00 Jan-01 Sep-01 Jan-02 Sep-02 Jan-03 Sep-03 Jan-04 Sep-04 Jan-05 Sep-05 Jan-06 Sep-06 Jan-07 Sep-07 Jan-08 Sep-08 Jan-09 May-97 May-98 May-99 May-00 May-01 May-02 May-03 May-04 May-05 May-06 May-07 May-08 7 Neuchâtel, 27- 29 May 2009

11th Ottawa 4. The current measures of core inflation in Italy - Istat Group Meeting 12 month rates of change of CPIs , BM1, Energy products and unprocessed food prices indices. Year 2007 – 2009. 12- month percentage rates of change, differences 20.0 All items CPI EBM1 Energy products unprocessed food Differences between all items CPI and EBM1 15.0 10.0 5.0 0.0 Apr-07 Aug-07 Apr-08 Aug-08 Jan-07 Feb-07 Mar-07 May-07 Jun-07 Jul-07 Sep-07 Oct-07 Nov-07 Dec-07 Jan-08 Feb-08 Mar-08 May-08 Jun-08 Jul-08 Sep-08 Oct-08 Nov-08 Dec-08 Jan-09 Feb-09 Mar-09 -5.0 -10.0 EBM1 reduces volatility and provides a useful tool for understanding underlying inflation 8 Neuchâtel, 27- 29 May 2009

11th Ottawa 5.1 Time series approach (a) Group Meeting � By using TRAMO SEATS, we identified the SARIMA model (2,1,0)(0,1,1): (1-0.21326B-0.28563B2)(1 –B)(1 – B12)Yt = (1-0.70919B12) α t � we extracted the trend-cycle by adopting an ARMA(3,3) � CPI trend component was extremely dominant � Since in the Italian CPIs the seasonal component is weak TRAMO SEATS mainly removed irregular movements � Trend cycle shows an evolution similar to the Italian CPIs. 9 Neuchâtel, 27- 29 May 2009

11th Ottawa 5.1 Time series approach (b) Group Meeting 12 month rates of change of CPIs, trend cycle and centred moving average. Year 1997 – 2009. 12 months percentage rates of change 4.5 12 month rates of change all items index disseminated by Istat 12 month rates of change Moving average (12 months) 4.0 12 month rates of change all items trend cycle 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Jan-97 Jul-97 Jan-98 Jul-98 Jan-99 Jul-99 Jan-00 Jul-00 Jan-01 Jul-01 Jan-02 Jul-02 Jan-03 Jul-03 Jan-04 Jul-04 Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 10 Neuchâtel, 27- 29 May 2009

11th 5.2 Exclusion based methods (a) Ottawa Group Exclusion Based Approach Meeting � Methods excluding products which are considered volatile a priori; � Data driven methods which exclude products on the basis of some measures of the volatility of their prices. VOLATILITY ANALYSIS Time series Cross section π π 1 π 12 1 π standard deviation of over 12 how many times it it it it the entire period when it is present are outside the interval in the Italian CPI basket ( μ ± σ , μ ± 1.5 σ , μ ± 2 σ , μ ± 2.5 σ ) Two reasons: 1. verify the volatility of the unprocessed food and energy products which are currently eliminated from the EBM1 calculation 2. calculate different indicators of core inflation excluding different groups of products (in terms of their volatility) 11 Neuchâtel, 27- 29 May 2009