Editing Consumer price index (section)

===The nature of the data used for weighting===
No firm rules can be suggested on this issue for the simple reason that the available statistical sources differ between countries. However, all countries conduct periodical household-expenditure surveys and all produce breakdowns of consumption expenditure in their [[national accounts]]. The expenditure classifications used there may however be different. In particular:
* Household-expenditure surveys do not cover the expenditures of foreign visitors, though these may be within the scope of a consumer price index.
* National accounts include [[imputed rent]]s for owner-occupied dwellings which may not be within the scope of a consumer price index.

Even with the necessary adjustments, the national-account estimates and household-expenditure surveys usually diverge.

The ''statistical sources'' required for regional and outlet-type breakdowns are usually weak. Only a large-sample Household Expenditure survey can provide a regional breakdown. Regional population data are sometimes used for this purpose, but need adjustment to allow for regional differences in living standards and consumption patterns. Statistics of retail sales and market research reports can provide information for estimating outlet-type breakdowns, but the classifications they use rarely correspond to COICOP categories.

The increasingly widespread use of bar-code scanners in shops has meant that detailed cash register printed receipts are provided by shops for an increasing share of retail purchases. This development makes possible improved Household Expenditure surveys, as Statistics Iceland has demonstrated. Survey respondents keeping a diary of their purchases need to record only the total of purchases when itemized receipts were given to them and keep these receipts in a special pocket in the diary. These receipts provide not only a detailed breakdown of purchases but also the name of the outlet. Thus response burden is markedly reduced, accuracy is increased, product description is more specific and point of purchase data are obtained, facilitating the estimation of outlet-type weights.

There are only two general principles for the estimation of weights: use all the available information and accept that rough estimates are better than no estimates.