Joint UNECE/ILO Meeting on Consumer Price Indices The interpretation of the divergences between CPIs at territorial level: Evidence from Italy Biggeri L*., Brunetti* A. and. Laureti° T *Italian National Statistical Institute (Istat), Rome, Italy; ° University of Tuscia, Viterbo, Italy Geneva, 8-9 May 2008 1 Joint UNECE/ILO Meeting on Consumer Price Indices Structure of the paper 1. Introduction 2. The divergence between CPIs at territorial level: a method for decomposing and interpreting it 3. The organisation of the decomposition analyses on Italian data 4. Analysis of the results 5. Concluding remarks 2 Geneva, 8-9 May 2008 Joint UNECE/ILO Meeting on Consumer Price Indices 1. Introduction The aim of the paper is twofold Method for the decomposition CPIs divergences Empirical analyses to show the usefulness of the method For the construction of CPIs most NSIs make use of the Laspeyres formula n n ptk r wk r Pk ,t r wk [1] r Pt p k 1 rk k 1 Considering the same basket of products and services, the divergence between two CPIs in different areas l and j n Pt r P r P r w j r l t k 1 j k ,t j k n k 1 r Pkl,t r wkl [2] 3 Geneva, 8-9 May 2008 Joint UNECE/ILO Meeting on Consumer Price Indices 2. The divergence between CPIs at territorial level From a different point of view, by considering area j as reference area: n r n P r Pt r P r w r Pk j,t r wkj l t j k 1 l k ,t l k [5] k 1 A comparison between two local CPIs depends on • Elementary indices • Weighting system Examine and decompose these divergences Understand which are the factors that cause them Four equivalent decomposition formulae 4 Geneva, 8-9 May 2008 Joint UNECE/ILO Meeting on Consumer Price Indices 2. A method for decomposing and interpreting the differences (a) n n n n j P P P w P w P w P r r r r r r r k ,t r w r t r j l t k 1 j k ,t j k r k 1 l k ,t l k wkl r Pk j,t r Pkl,t j k ,t k 1 l k k 1 r Pk j,t r wkj r wkl k k [3] Elementary Price Index Effect d k r wkj r wkl k r Pk j,t r Pkl,t Weight Effect j l P P r t r t n swl s Rwl , n sP j sd RP j ,d Factors influencing the Elementary Price Index Effect [3bis] Factors influencing the Weight Effect 5 Geneva, 8-9 May 2008 Joint UNECE/ILO Meeting on Consumer Price Indices 2. A method for decomposing and interpreting the differences (b) n n n n l j P P P w P w P w P w r r r r r r r k ,t r k r r t l t j k 1 l k ,t l k k 1 j k ,t j k k 1 l k ,t j k r wkj r Pkl,t r Pk j,t r Pkl,t r wkl r wkj k k n sw j s Rw j , n sPl sd RPl ,d k 1 [6] The factors can give different results since they are defined relating to different distributions of elementary price indices and weights difference between the two arithmetic means of elementary price index distributions j l 1 1 j l r Ptk r Ptk r Pt r Pt n k n k interesting interpretation from an economic point of view determining the “price effect” influencing the overall difference between the two CPIs considered. 6 Geneva, 8-9 May 2008 Joint UNECE/ILO Meeting on Consumer Price Indices 3. Data set description and organisation of analyses on Italian data DATA DESCRIPTION: Monthly CPIs for the whole nation for elementary aggregates • 40,000 outlets; • 85 municipalities; •400,000 elementary prices; •540 representative products System of weights for 85 municipalities using household expenditure shares Period: January 2002-December 2007 CALCULATIONS: analysis limited to December of the years 2002 and 2007 Similar basket of products and services Selection of 9 chief regional towns Considering the cities where it is reasonable to assume a different behaviour of the sellers and consumers and a different evolution of attitude regarding sale and purchase. The territorial location of the cities in the north, centre and south Italy 7 Geneva, 8-9 May 2008 Joint UNECE/ILO Meeting on Consumer Price Indices 4. Analysis of the results (a) Table 2 Overall Differences between pairs of cities Nic dic_02 TURIN TRENTO VENICE TRIESTE FLORENCE ROME NAPLES POTENZA PALERMO 102.940 102.726 103.334 102.815 102.134 103.003 103.825 102.222 102.839 0.214 -0.394 0.125 0.806 -0.064 -0.885 0.718 0.101 -0.608 -0.089 0.592 -0.278 -1.099 0.504 -0.113 0.519 1.200 0.331 -0.491 1.112 0.495 0.681 -0.189 -1.01 0.593 -0.024 -0.87 -1.691 -0.088 -0.705 -0.822 0.781 0.165 1.603 0.986 TURIN 102.940 TRENTO 102.726 -0.214 VENICE 103.334 0.394 0.608 TRIESTE 102.815 -0.125 0.089 -0.519 FLORENCE 102.134 -0.806 -0.592 -1.2 -0.681 ROME 103.003 0.064 0.278 -0.331 0.189 0.870 NAPLES 103.825 0.885 1.099 0.491 1.010 1.691 0.822 POTENZA 102.222 -0.718 -0.504 -1.112 -0.593 0.088 -0.781 -1.603 PALERMO 102.839 -0.101 0.113 -0.495 0.024 0.705 -0.165 -0.986 -0.617 0.617 Comparing Naples with the other cities the differences t 1,12 Pt j m t 1,12 Ptlm (all positive but with different values) have a “hidden meaning” concerning the degree of importance of the various factors 8 Geneva, 8-9 May 2008 Joint JointUNECE/ILO Meeting on UNECE/ILO Meeting on Consumer Price Consumer Indices Naples Price Indices 4. Analysis of the results (b) (j) –Turin (l) CPI difference 0.885 factors Price Effect 0.516 Weight Effect 0.369 Mean Standard Deviation Skewness Kurtosis -0.639 swl 0.0035 s 13.029 Rwl , 0.0441 factors Price change distribution NAPLES 102.40 12.34 -6.900 58.908 TURIN 103.03 5.25 2.252 16.616 sP j 12.335 sd 0.002 RP j , d 0.034 Correlation coefficient between elementary indices and weights Naples 0.056 Turin -0.01 9 Geneva, 8-9 May 2008 JointUNECE/ILO Joint UNECE/ILO Meeting on Meeting on Consumer Price Consumer Price Indices Indices 4. Analysis of the results (c) Naples (j) –Florence (l) CPI difference 1.691 factors Price Effect 1.396 Weight Effect 0.295 Mean Standard Deviation Skewness Kurtosis 0.596 swl 0.0037 s 12.131 Rwl , 0.031 factors Price change distribution NAPLES 102.40 12.34 -6.900 58.908 FLORENCE 101.80 6.07 -7.541 144.262 sP j 12.335 sd 0.0018 RP j , d 0.0240 Correlation coefficient between elementary indices and weights Naples 0.056 Florence 0.026 10 Geneva, 8-9 May 2008 Joint UNECE/ILO Meeting on Consumer Price Indices 4. Analysis of the results (d) The evolutions of local CPIs is quite different across Italy and influence the divergences between the CPIs in different ways and degrees. The divergences in the evolution of the CPIs depend: mostly on the price effects. in same cases on the different share of expenditures (two southern cities with all the other cities) on the characteristics of the corresponding distribution of the elementary price indices and on the value of the correlation between elementary indices and weights Similar results from the comparisons for December 2007 11 Geneva, 8-9 May 2008 Joint UNECE/ILO Meeting on Consumer Price Indices 5. Concluding remarks A simple method for calculating the decomposition of the divergence between two CPIs to obtain a measure of the importance of the factors that affect it. Very interesting results Understanding why the local CPIs often differ among one another Further research improve the method of the decomposition of the divergences between the CPIs Analysis for CPIs by classes and groups of products to understand the importance of the different products in affecting the price and weights effects analyse the degree of the price and weights effects during periods with different inflation rates. 12 Geneva, 8-9 May 2008 Joint UNECE/ILO Joint UNECE/ILO Meeting Meeting onon Consumer Price Consumer Price Indices Indices Thank you for your kind attention! 13
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