Consumer prices: provisional data April 2017

Transcription

1 28 April 2017 Consumer prices: provisional data April 2017 In April 2017, according to preliminary estimates, te Italian consumer price index for te wole nation (NIC) increased by 0.3% on montly basis and by 1.8% compared wit April 2016, up from +1.4% in Marc In April, te speed up of te annual rate of cange of All items index was mainly due to prices of Regulated energy products (+5.7%, from -1.2% in te previous mont), to wic contributed bot Electric energy (+5.4%, from -1.0% in Marc) and Natural gas (+6.0%, from -1.4%), and also to prices of Services related to transport (+5.5%, up from +2.5% in te previous mont). Excluding energy and unprocessed food, core inflation was +1.0%, up from +0.7% in Marc; excluding energy te inflation was +1.2%, stable as in te previous mont. Te annual rate of cange of prices of Goods was +1.8% (up from +1.7% in Marc) and te annual rate of cange of prices of Services was +1.7% (up from +1.0% in te previous mont). As a consequence, te negative inflationary gap between Services and Goods resized wit respect to Marc (-0.1 percentage points from -0.7). Te increase on montly basis of All items index was mainly due to te prices of bot Services related to transport (+3.3%) and Services related to recreation, including repair and personal care (+1.1%), wic increased especially for Easter on April 16 and Liberation Day, a national oliday in Italy tat is annually celebrated on April 25. Prices of Grocery and unprocessed food decreased by 0.4% on montly basis and increased by 1.8% on annual basis (from +2.3% in te previous mont). In April 2017, according to preliminary estimates, te rate of cange of Italian armonized index of consumer prices (HICP) increased by 0.8% compared wit te previous mont and by 2.0% wit respect to April 2016 (te annual rate of cange observed in te previous mont was +1.4%). Te increase on montly basis was mainly due to te final end of te winter sales of Cloting and footwear (+4.2% compared wit Marc 2017), wic are not taken into account in te national index NIC. In April, core inflation, measured by Italian HICP, was +1.2% (up from 0.7% in Marc). Bot inflation excluding Energy, food, alcool and tobacco and inflation excluding Energy increased: te first was +1.3% (from +0.6% in Marc), te second was +1.4% (0.3 percentage points iger tan in te previous mont). ITALIAN CONSUMER PRICE INDICES. April 2017 (a) INDICES Apr-17 Apr-17 April 2017 Mar-17 Apr-16 Italian consumer price index for te wole nation (NIC) Italian armonized index of consumer prices (HICP) (a) Reference base year 2015=100.

2 TABLE 1. ITALIAN CONSUMER PRICE INDEX FOR THE WHOLE NATION (NIC), BY COICOP DIVISION. April 2017, weigts, indices and percentage canges (base 2015=100) Divisions Weigts Indices Apr-17 Apr-17 Mar 17 Apr-16 Mar-17 Apr-16 Mar-16 Mar-16 Food and non-alcoolic beverages 164, Alcoolic beverages, tobacco 32, Cloting and footwear 73, Housing, water, electricity, gas and oter fuels 107, Furnisings, ouseold equipment and routine ouseold maintenance 72, Healt 86, Transport 139, Communication 26, Recreation and culture 78, Education 12, Restaurants and otels 114, Miscellaneous goods and services 92, ALL ITEMS 1,000, TABLE 2. ITALIAN CONSUMER PRICE INDEX FOR THE WHOLE NATION (NIC), BY TYPES OF PRODUCT. April 2017, weigts, indices and percentage canges (base 2015=100) Special aggregates Weigts Indices Apr-17 Apr-17 Mar 17 Apr-16 Mar-17 Apr-16 Mar-16 Mar-16 Food including alcool: 175, Processed food including alcool 105, Unprocessed food 70, Energy: 84, Regulated energy products 41, Non-regulated energy products 43, Tobacco 21, Non energy industrial goods: 254, Durable goods 84, Non-durable goods 66, Semi-durable goods 103, Goods 536, Services related to ousing 77, Services related to communication 19, Services related to recreation, including repair and personal care 176, Services related to transport 76, Services - miscellaneous 114, Services 463, ALL ITEMS 1,000, All items excluding energy and unprocessed food (Core inflation) 845, All items excluding energy, food, alcool and tobacco 718, All items excluding energy 915, Grocery and unprocessed food 198,

3 TABLE 3. ITALIAN HARMONIZED CONSUMER PRICE INDEX (HICP), BY COICOP DIVISION. April 2017, weigts, indices and percentage canges (base 2015=100) Divisions Weigts Indices Apr-17 Apr-17 Mar 17 Apr-16 Mar-17 Apr-16 Mar-16 Mar-16 Food and non-alcoolic beverages 175, Alcoolic beverages, tobacco 34, Cloting and footwear 85, Housing, water, electricity, gas and oter fuels 114, Furnisings, ouseold equipment and routine ouseold maintenance 77, Healt 43, Transport 147, Communication 27, Recreation and culture 62, Education 12, Restaurants and otels 122, Miscellaneous goods and services 98, ALL ITEMS 1,000, TABLE 4. ITALIAN HARMONIZED CONSUMER PRICE INDEX (HICP), BY SPECIAL AGGREGATES. April 2017, weigts, indices and percentage canges (base 2015=100) Special aggregates Weigts Indices Apr-17 Apr-17 Mar 17 Apr-16 Mar-17 Apr-16 Mar-16 Mar-16 Food, alcool and tobacco: 209, Processed food including alcool 117, Unprocessed food 92, Energy 89, Non-energy industrial goods 263, Services 437, ALL ITEMS 1,000, All items excluding energy and unprocessed food (Core inflation) 818, All items excluding energy, food, alcool and tobacco 700, All items excluding energy 910, For more details please refer to te Italian version Date of previous release: 13 April 2017 Date of next release: 15 May 2017 Contact person: Maria Assunta Scelsi Istat Italian National Institute of Statistics Via Cesare Balbo Rome, Italy pone

4 Consumer Price Indices Metodological note Te Consumer Price Index for te wole nation (NIC) is based on te consumption of te entire present population. Te Harmonised index of Consumer Prices (HICP), calculated according to te EU regulations in force, is used for te comparison of inflation between Member States and as a key indicator for te monetary policy of te European Central Bank. Consumer price indices are calculated using a cained Laspeyres formula, in wic te basket of products and te weigting system are updated annually. Montly indices for te current year are calculated wit reference to December of te previous year (calculation base) and subsequently cained over te period cosen as a reference base in order to be able to measure price trends over a period of time longer tan a year 1. Reference base year for NIC and HICP Te NIC indices are expressed wit 2015=100 as a reference base year 2. Te HICP are calculated and publised wit 2015=100 as a reference base, as establised by te EU Regulation 2015/2010 of te European Commission of 11 November Classification for consumer expenditure, basket of goods Classification of consumption so far used for HICP, NIC and FOI is te international classification ECOICOP (European Classification of Individual Consumption by Purpose), wose ierarcical structure as 4 levels of disaggregation: Divisions, Groups, Classes of product and Subclasses of product. Since te final data of January 2016, Istat as been adopted te classification ECOICOP, annexed to te new European framework regulation on armonised indices of consumer prices and te ouse price index, (2016/792), tat introduced an additional level of detail, te subclasses of product. Anyway, in 2011 Istat introduced two disaggregation levels: product sub-classes and consumption segments. Te 2017 basket for te Italian consumer price index for te wole nation (NIC) and for blue and wite-collar ouseolds (FOI) is made up of 1,481 elementary products, wic are grouped into 920 products and into 405 product aggregates. (1,476 in 2016 grouped into 901 products and 400 product aggregates). TABLE 1. CLASSIFICATION NIC AND FOI INDICES. YEAR 2017 Year expenditure divisions 43 product groups 102 product classes 229 product sub-classes 302 consumption segments 405 product aggregates 920 products 1,481 elementary products Te 2017 basket for te Italian armonized index of consumer prices (HICP) is made up of 1,498 elementary products, wic are grouped into 923 products and ten into 409 product aggregates (1,484 in 2016 grouped into 906 products and 404 product aggregates) 3. 1 ISTAT calculates anoter index named Consumer Price Index for blue - and wite-collar worker ouseolds (FOI) based on consumption of ouseolds wose reference person is an employee. 2 Te FOI indices are expressed wit 2015=100 as a reference base year, too. 4

5 Segments of consumption are te most disaggregated level for wic NIC indices referring to te entire national territory are disseminated. For HICP indices, te level of detail of te dissemination is tat of te product classes, but during 2017, it is expected tat of te product subclasses. FOI national indices are disseminated at level of expenditure divisions. At local level (geograpical area, region, province), NIC indices are publised up to te product groups and FOI indices, just at provincial level, up to te divisions. Furtermore, HICP indices by special aggregates (HICP-SA) are released. HICP-SA indices are calculated using te same classification sceme and te same metod adopted by Eurostat (terefore different from te metod used for te calculation of NIC indices by types of product), in order to guarantee comparability among te Italian HICPs and te HICP of te oter EU countries and te HICPs for te EU and te euro area produced by Eurostat 4. All indices and data are available and publised on Istat data wareouse, I.Stat, inside te teme Prices and subteme Consumer prices. In addition to indices at national level, NIC indices at provincial, regional and macro area level and FOI indices at provincial level are publised too. Price collection and calculation metod for seasonal product price indices Te metod for collecting and calculating prices of seasonal products is in accordance wit Regulation (EC) no 330/2009 of 22 nd April 2009, wic sets out minimum standards for dealing wit seasonal products in te HICP 5. Tis metod, also used for te NIC 6, is applied to te product groups and classes Fruit, Vegetables, Cloting and Footwear. Te European Regulation defines as seasonal product tat one consumers may not purcase in certain periods of te year (at least one mont), or tey may purcase in modest or insignificant volumes. It also establises tat in a given mont seasonal products are considered in season or out of season. On te basis of tis standard, Istat defined a montly calendar for te wole 2017, wic establises, in a given mont, wen eac specific product belonging to te above mentioned product groups or classes must be considered in season or out of season. Te adoption of a seasonality calendar entails tat te local consumer price survey is carried out only in monts wen te product in question is defined as in season, wile prices of out of season products will be estimated on te basis of a metod tat is consistent wit standards contained in te aforementioned European Regulation. Survey geograpical basis, rate of coverage and frequency of data collection Data contributing to te compilation of montly consumer price indices are traditionally collected in two distinct surveys: te local survey, carried out by Municipal Offices of Statistics, under Istat supervision and coordination, and te central survey, carried out directly by Istat. In addition to tese two ways, an administrative source is used too, tat is te database of fuel prices of Ministry of Economic Development. Local survey In 2017 te geograpical basis of te survey is made up of 80 municipalities (18 regional capitals and 61 provincial capitals) wic participate in te indices calculation for all te product aggregates of te basket and of oter 16 municipalities participating in te survey for a subset of products, wic includes local tariffs (water supply, solid waste, sewerage collection, gas for domestic use, urban transport, taxi, car transfer ownersip, canteens in scools, public day nursery, etc.) and some local services (building worker, football matces, cinema, teatre sows, secondary scool education, canteens in universities, etc.). Overall, te coverage of te index, measured in terms of resident population in te provinces wit capitals participating in te survey for all items in te basket, is 83.7%. 3 Te difference between te two baskets is due to two elements: on one and in te HICP basket (but not in te NIC/FOI one), contribution to te NHS for parmaceutical products, specialist practices and services of medical analysis (six items) are included; on te oter and in te NIC/FOI basket (but not in te HICP one), Games of cance are included. 4 HICP-SA indices ave been released starting from data referred to February Te description of product classes wic are included in te special aggregates is available on Eurostat web site at te following link: ttp://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?targeturl=lst_nom_dtl&strnom=hicp_2000&strlanguagecode=en &IntPcKey=&StrLayoutCode=. Te HICP-SA calculation metod is described in te HICP Compendium wic is downloadable at te following link: ttp://ec.europa.eu/eurostat/documents/ / /ks-ra en.pdf/59eb2c1c-da1f-472c-b191-3d0c76521f9b?version=1.0. Back series starting from January 2001 are publised on I.Stat, te wareouse of Istat statistics, inside te teme Prices. 5 It as been adopted starting from data referred to January It is used for FOI indices, too. 5

6 Concerning te basket subset including local tariffs and some local services wose weigt on te NIC basket is equal to 6.0% wit te participation of te oter 16 municipalities, te coverage of te survey, measured in terms of provincial resident population, is 92.4%. Central survey In 2017 price quotes collected eac mont directly by Istat are 137,500, of wic: 137,000 via web, also using web scraping tecniques, or collecting data from different providers. Te main data providers for te central price data collection are te following: Italian Customs Agency, for Tobacco products and games of cance; Italian Association of Concessionaries Higways and Tunnels (Aiscat), for motorway tolls; Farmadati, for parmaceutical products; Italian Association of Publisers (AIE), for prices of scool books; Specialized magazine Quattroruote for prices quotes of cars and second and cars; Sanguinetti Editore, for prices of cars, motorcycles and motorbikes, caravans and motoromes; about 500 price quotes directly collected using te data by Insurance Companies. An important news in central survey is tat of Housing insurance services wose prices, montly collected by insurance company, refer to protection against most risks connected to property, suc as fire, teft and oter damages. Te percentage of products observed directly by Istat calculated according to te weigt assigned to eac product witin te NIC is 23.6% in 2017 (as in te previous year). Administrative sources In 2017 automotive fuels price indices (te weigt on te basket is 3.7%) are calculated using te data base supplied by te Ministry of Economic Development, tat collects prices for tese products. 76,000 price quotes are montly used to estimate inflation and tey come from about 13,596 fuel stations on te territory, tat is 69.3% of te ones active and present in Ministry database. Te 13,596 fuel stations cover te entire national territory and tey are located in te different geograpical areas as it follows: 3,600 in te Nort-West; 3,200 in te Nort-East; 3,000 in te Centre; almost 2,400 in te Sout and about 1,400 in te Islands. Frequency of data collection Wit regard to te local survey, price collection is carried out in te first fifteen working days: bi-montly for products wic sow a strong temporal variability of teir prices (fres fruit and vegetables, fres fis; gas in cylinder and eating oil); collecting tree prices for mont for te otel bedroom referring to te first tree Saturday of te mont; once a mont, for te remaining products. For some goods or services, suc as for example, water supply, town gas and natural gas, urban transport by bus and combined urban transport, taxi or tickets (contributions to NHS) for specialist practice, services of medical analysis laboratories and X- ray centres and oter paramedical services, it is detected te price applied te 15t day of te mont to wic te index is referred. Concerning te centralized survey, price collection is widely carried out once a mont in te first fifteen working days. Hereafter te exceptions to te general rule: for some goods and services suc as for example tobacco, games of cance, medicines, telecommunications services, regional railway transport, wagon lits, out of town bus services, out of town combined passenger transport, postal services, igway tolls car transfer ownersip, car overaul, it is detected te price applied te 15t day of te mont to wic te index is referred; tree times per mont, according an annual calendar fixed at te beginning of te year, for national railway transport; bi-montly for passenger transport by air, passenger transport by sea and inland waterway and magazines; 6

7 from te 9 t to te 15 t day of eac mont for daily newspapers; on eac day of te mont for touristic, recreational and cultural services (fun parks entrance ticket, bating establisment, ski lifts, etc.). Concerning te data base supplied by te Ministry of Economic Development, automotive fuel prices applied on te first and te tent working day of eac mont are used to compile consumer price indices. Weigting structure In Table 1 te weigting structure for te year 2017 of NIC and HICP is reported. TABLE 1. WEIGHTS USED FOR CALCULATING CONSUMER PRICE INDICES. BY EXPENDITURE DIVISION. YEAR percentage values Expenditure divisions NIC Weigts HICP Food and non-alcoolic beverages Alcoolic beverages. tobacco Cloting and footwear Housing. water. electricity. gas and oter fuels Furnisings. ouseold equipment and routine ouseold maintenance Healt Transport Communication Recreation and culture Education Restaurants and otels Miscellaneous goods and services All items Harmonized index of consumer prices at constant tax rates Te Harmonized Index of Consumer Prices at constant tax rates (HICP-CT) 7 is calculated as establised by te Regulation (EC) no 119/2013 of te 11 t February It measures te cange of prices at constant tax rates. It follows te same computation principles as te HICP, but it is based on prices at constant tax rates. Prices at constant tax rates are estimated cancelling out te effects due to canges in taxes in te current mont compared to te tax rates system in force in December of previous year (calculation period base). Te taxes considered in te HICP-CT are tose directly linked to final consumption. Tey are mainly VAT, excise duties and oter taxes on some specific items (suc as cars and insurance). Subsidies and taxes paid on intermediate stages (e.g. production, transportation) are not taken into account. In principle, for te compilation of HICP-CT, all taxes sould be included and kept constant; owever, due to practical consideration, taxes wic generate very small tax revenues may not be taken into account. In detail, according to recommendations reported in te Eurostat HICP-CT Manual, taxes wic cover less tan 2% of te total tax revenue can be excluded. On te wole, included taxes must cover a minimum of 90% total tax revenue. Terefore in te compilation of te Italian HICP-CT, taxes kept constant are te following: VAT, excise duties on tobacco and energy items (fuels, eating oil, gas, electricity, etc.), te main local surcarge on electricity and gas, tax for te public liability insurance and contribution to te National Healt Service for transport means insurance. On te basis of National Accounts data taxes wic cover less tan 1% of te total tax revenue are excluded and, on te wole, taxes included cover almost 98% of total revenues carried out wit taxes on final consumption. Te HICP-CT covers te same goods and services as tose covered by te HICP. Te same weigt structure is applied as for te HICP (Table 1). As HICP, it as expressed in 2015=100 as a reference base year. 7 Te HICP-CT as been released starting from data referred to Marc Back series starting from January 2002 are publised on I.Stat, inside te teme Prices ttp://dati.istat.it. 7

8 Te HICP-CT provides a measure of te teoretical impact of canges of indirect taxes on te overall HICP inflation. It as to be empasised tat it does not provide an exact measure of tis impact, rater an indication for its upper limit. In effect, te difference between HICP and HICP-CT growt rates points to te teoretical impact of tax canges on overall HICP inflation, assuming an instantaneous and full pass-troug of tax rate canges on te price paid by te consumer. It as to be pointed out tat, during te year, te Italian HICP-CT may be revised following introduction of metodological canges required by indirect taxation system canges. Data become final in te next year to te reference one. Indices rates of cange calculation Hereafter formulae for te calculation of montly, annual and annual average rates of cange for consumer price indices are described 8. Te HICP formulae apply also to HICP-CT. Te first expression concerns calculation of rates of cange between indices in te same reference base period: Montly rate of cange (NIC, HICP) Te montly rate of cange is te current mont s index in respect to te previous mont s index (wit one decimal place), for example: MOR I Feb, 2012 I Jan, 2012 ;I Feb, 2012 Round ;. 1 I Jan, 2012 Annual rate of cange (NIC, HICP) Te annual rate of cange is te current mont s index in respect to te same mont s index a year previously (wit one decimal place), for example: ANR I I Feb, 2012 Feb, 2011 ;I Feb, 2012 Round ;. 1 I Feb, 2011 Annual average rate of cange (NIC) Te annual average rate of cange is te current annual average index in respect to a previous annual average index (wit one decimal place), for example: AVR I 2012 I2011 ;I2012 Round ;. 1 I2011 Annual average rate of cange (HICP) For te HICP, in a different way compared to NIC, te annual average rate of cange is obtained directly from te montly indices and terefore it is based on te unrounded annual average indices. Tis metod, applied in compliance wit Eurostat, guarantees international comparability of data. For example: AVR I 2011 ;I 2012 I Jan, 2012 I Feb, I Dec, ;. I Jan, 2011 I Feb, I Dec, 2011 Round 1 8 Te expressions and te rounding rules described for NIC are also carried out for FOI. 8

9 Te following expression describes te calculation of montly rate of cange between indices expressed in different reference base year; it can be also used for te calculation of te annual rate of cange and te annual average rate of cange: Montly rate of cange - Indices expressed in different reference base year X, j ; X t n I I X t ;. 1 1 MOR I m I n,, Round CX t ; X t 1 CX t1; X t2... CX 2; X1 were X1 m, j X I 1 m, j is te index, wit one decimal place, of te mont m year j, expressed in te more remote Xt reference base, I n, is te index, wit one decimal place, of te mont n year, expressed in te more recent reference base X t, and C( X i ; X i 1) wit i=2..t are te splicing coefficients between contiguous reference bases. Tese coefficients are equal to te annual average index of te year corresponding to te new reference base expressed in te previous base, divided by 100. Tey are as many as base canges ave been carried out during te considered period. X 1 Flas estimates of HICP: accuracy and computation metodology Flas estimate of Italian HICP (and NIC) are usually publised on te last working day of te reference mont according to te Eurostat release calendar of HICP flas estimate for euro area. Final data are generally publised around 13 days later. Te aim of te inflation flas estimates is to provide a timely information on inflation, predicting as accurately as possible te final HICP (and NIC) annual rate of cange released about two weeks later. Te analysis of teir revisions represents an important tool to evaluate te correct balancing between te two quality dimensions, timeliness and accuracy. Totally in line wit te Eurostat Statistics Explained on Inflation metodology of te euro area flas estimate, tis section analyses te accuracy of te Italian HICP flas estimates and describes te metodology used in teir computation. Accuracy of flas estimates Table 2 compares te flas estimates and te final HICP annual rates of cange for te same reference mont. Over te last tirteen monts, te maximum difference between te flas estimate all items and te HICP all items annual rates of cange was +0.3 in January Over te same period, wit reference to te main special aggregates, te maximum differences between te flas estimate and te final HICP annual rates of cange concerned Food, alcool and tobacco (+1.1 recorded in January 2017), Processed food (including alcool, tobacco) (+1.2 in January 2017), Unprocessed food (+0.9 in January 2017), Energy (-0.8 in April 2016) and Non energy industrial goods (+0.5 in January 2017). Te igest frequency of revisions for Non energy industrial goods (10 monts out of 13) are mainly due to te seasonal sales dynamics of Cloting and footwear, for wic te partial information available as a iger impact on te flas estimate and terefore it turns out to be less accurate. 9

10 TABLE 2. FLASH ESTIMATES AND HICP ANNUAL RATES FOR THE ALL-ITEMS AND MAIN SPECIAL AGGREGATES. MARCH 2016-MARCH 2017, percentage values (Base 2015=100) Special aggregates Mar-16 Apr-16 May-16 Jun-16 Jul-16 Aug-16 Sep-16 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Food including alcool and tobacco: Processed food (including alcool, tobacco) Unprocessed food Energy Non energy industrial goods Services All-items All items excluding energy and unprocessed food (Core inflation) All items excluding energy, food, alcool and tobacco All items excluding energy Flas HICP Flas HICP Flas HICP Flas HICP Flas HICP Flas HICP Flas HICP Flas HICP Flas HICP Flas HICP Te Mean Absolute Deviation (MAD) provides anoter way to measure accuracy. It is calculated as te average of te absolute differences between te flas estimate and te final HICP annual rates of cange over te last tirteen monts. Figure 1 sows te MAD for te all-item index and te main special aggregates. Over te last tirteen monts Non energy industrial goods (0.154 percentage points) and Energy (0.146 percentage points) ave recorded te igest MADs. FIGURE 1. MEAN ABSOLUTE DEVIATION BETWEEN FLASH ESTIMATES AND HICP ANNUAL RATES. MARCH 2016-MARCH 2017, percentage points Food including alcool and tobacco Processed food (including alcool, tobacco) Unprocessed food Energy Non energy industrial goods Services All-items All items excluding energy and unprocessed food (Core inflation) All items excluding energy, food, alcool and tobacco All items excluding energy

11 Te direction of inflation is correctly predicted if bot te flas estimate and te final one sow increasing (declining or no canging) annual rates of cange wit respect to tose ones calculated in te previous mont. Tere are tree possible outcomes for te comparison of te direction of inflation: - te flas estimate correctly predicts te direction of inflation, so te predicted rise, decline or no cange in inflation is confirmed by final data (denoted by ); - te flas estimate wrongly predicts te direction of inflation, namely it predicts an increase wen tere is a decrease or vice versa (denoted by ); - te flas estimate points to an increase or a decrease but te final annual rate of cange remains uncanged; or te flas estimate predicts no cange in inflation but te final figure points to an increase or a decrease (denoted by ). Over te last tirteen monts, te flas estimate accurately predicted te inflation direction in 116 out of 130 estimates. TABLE 3. FLASH ESTIMATE PREDICTION CAPACITY OF THE DIRECTION OF INFLATION MEASURED BY HICP. MARCH 2016-MARCH 2017 Special Aggregates Mar-16 Apr-16 May-16 Jun-16 Jul-16 Aug-16 Sep-16 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Food including alcool and tobacco: Processed food (including alcool, tobacco) Unprocessed food Energy Non energy industrial goods Services All-items All items excluding energy and unprocessed food (Core inflation) All items excluding energy, food, alcool and tobacco All items excluding energy Computation metodology of flas estimates For te Italian HICP (and NIC) flas estimate compilation, eac mont. - prices collected at local level by 61 municipalities (out of 80) are used. Out of tese municipalities, tere are te 38 municipalities wic calculate te preliminary local consumer price indices and publis tem independently, at te same time of Istat national CPI and HICP release. Data collected by te oter 16 municipalities participating in te survey for a subset of products (local tariffs and some local services) are not used; tese data are used for te compilation of final indices; - all prices collected directly by ISTAT (via internet and oter sources) are used. As soon as indices are calculated for aggregate products for wic prices are collected directly by ISTAT, product aggregate indices for te municipalities, wic participate in te flas estimate of inflation rate, are compiled. For te oter municipalities, wic do not participate in te flas estimation, product aggregate indices are generally 9 calculated applying to te indices of te previous mont, te montly rate of cange of te regional product aggregate indices. Te latter are calculated using data of municipalities wic participate in te flas estimate, as follows: R I m, a i i R ir i I i m, a 9 For some product aggregates among oters, rents and local tariffs suc as water supply, solid waste, sewerage collection, urban transport services by road for te municipalities tat do not participate in te flas estimation, indices are estimated by carrying forward te price of te previous mont. Te adoption of tis different estimation tecnique is due to te fact tat te evolution of prices in te oter municipalities of te same region is not considered a satisfactory proxy. 11

12 were m,a i I of year a and is te elementary index of product aggregate at municipality level i of te reference mont m i i ir resident population of te region. is equal to te sare of resident population in te municipality i of region R on te total As soon as product aggregate indices of all municipalities are compiled, regional and, ten, national indices are calculated (by product aggregates, by upper aggregates and for all items). If all municipalities of a certain region are not included in te flas estimate, te product aggregate indices of tis region are calculated applying to te indices of te previous mont, te montly rate of cange of national product aggregate indices. Te latter are calculated using data of regions wic participate in te flas estimate, as follows: were m,a R I 20 m, a R I 20 R I R1 R R1 is elementary index of product aggregate at regional level of te reference mont (m) of year (a) and R is equal to te sare of ouseold consumption expenditure for te product 20 R R 1 aggregate in te region R on te national ouseold consumption expenditure for te same product aggregate. Once product aggregate indices of all regions are compiled, national indices are calculated (by product aggregates, by upper aggregates and for all items). m, a 12