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Consumer Price Indices by household characterics

Consumer Price Indices by household characterics. Dominique Place – Insee, France Guillaume Osier – Statec, Luxembourg. Working group  " Statistics on Living Conditions " Eurostat – 13 may 2011. Consumer Price Index (CPI).

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Consumer Price Indices by household characterics

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  1. Consumer Price Indices by household characterics Dominique Place – Insee, France Guillaume Osier – Statec, Luxembourg Working group "Statistics on Living Conditions" Eurostat – 13 may 2011

  2. Consumer Price Index (CPI) • For every country, main measure of inflation for macroeconomic purposes • It aggregates the evolutions of prices for 305 items in France (nomenclature based on COICOP). • Annual weighting of these items with data from National Accounts

  3. Inflation is different for every category of households • CPI reflects price evolution for an "average" household, with a global consumption structure. • But it is well known that the households do not have the same consumption structure and are not equally affected by inflation : • in countryside, greater consumption of petrol • aged households have more health expenditures • By considering different categories of households and their consumption structure known with HBS, we calculate CPI for each of them in order to measure their own inflation.

  4. Definition of CPI by category (D. Guédès, 2006) • Indjis the CPI for an elementary item j. • In France, we considered 85 items to have the same definitions between CPI and HBS : Indj is an aggregation of more elementary CPI. • pj is the weight for the item j. It is computed with data of National Accounts • The (non chain-linked) global CPI is given by :

  5. Definition of CPI by category (continued) • Let k be a category of households (ex : with income in the first decile), we define pk,jthe weight for item j and category k : qj and qk,j are given by HBS : • qj = expenditure on j as proportion of total spending • qk,j = proportion of expenditure on j for category k If the category k spends 10 % more on j than the average household in proportion of the total spending, then : pk,j = 1,1 pj • CPI for category k :

  6. Contributions of items • We have : The contribution of item j is : • This contribution is positive if : and or and

  7. Calculation of weights in France for 1996-2009 series • For years before 2000, use of HBS 2000-2001 (10305 households) • For years after 2005, use of HBS 2005-2006 (10240 households) • Between 2001 and 2004, linear interpolation of quotients qk,j / qj • Adjustmentto get the sum of weights equal to 1

  8. Advantages and drawbacks • Advantages : • the weighting reflects special consumption structure for every considered category of households • the weighting takes into account annual evolutions as measured by National Accounts • Drawback : • does not take into account differences of consumption inside an item : households with lowest incomes buy more down-market cars than richer households, more food in discount stores… But not a problem if no difference in price evolutions.

  9. CPI by decile of income per consumption unit - France

  10. Major contributions by decile of income per consumption unit (1996-2009)

  11. Weighting by decile of income per consumption unit (2009)

  12. CPI by age of reference person

  13. Major contributions by age of reference person (1996-2009)

  14. Weighting by age of reference person (2009)

  15. CPI by type of household

  16. Major contributions by type of household (1996-2009)

  17. Weighting by type of household (2009)

  18. Results in France • The households wich are more affected by inflation are: • Households with lowest incomes per consumption unit : greater expenditure on tabacco, rentals • Households whose reference person is aged 30 to 44 years : greater expenditure on social protection services, mainly day nursery, childminder • Lone-parent families : greater expenditure on tabacco and rentals • Couples with 2 children : greater expenditure on day nursery and for childminder

  19. Results in Luxembourg • Same methodology (Guèdes, 2006) • HBS data over the three-year period 2006-2008 used (4300 households) in order to adjust the weights • Results presented in the STATEC annual report on Labour and Social Cohesion (2010): www.statistiques.public.lu/fr/publications/series/cahiers-economiques/2010/111-cohesion-sociale/index.html

  20. CPI by decile group (base=100 in 12/2002)

  21. Structure of consumption expenditure (‰)

  22. CPI by age of the reference person

  23. Structure of consumption expenditure (‰)

  24. CPI by household type

  25. Structure of consumption expenditure (‰)

  26. CPI by degree of urbanisation

  27. Structure of consumption expenditure (‰)

  28. Conclusions Most exposed sub-populations: • Households in the inferior deciles (rents and energy) • Elderly households (elderly homes) • Single households (rents) • Households in low-populated areas (fuel, purchase of cars, gasoil)

  29. Simulation tool • Calculate your own inflation, using your personal budget (structure of expenditure) as input Available at: www.statistiques.public.lu/fr/economie-finances/prix-consommation/ipcinflation/sip/index.html

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