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  • 1. Services Price Indexes Archived
    Table: 62F0040X
    Description:

    This occasional on-line bulletin series presents price indexes published by the Goods and Services Producing Industries Section, Prices Division. Each issue will contain different service price indexes.

    Release date: 1999-10-14
  • 2. Item selection in the Consumer Price Index: Cut-off versus probability sampling Archived
    Articles and reports: 12-001-X19990014710
    Description:

    Most statistical offices select the sample of commodities of which prices are collected for their Consumer Price Indexes with non-probability techniques. In the Netherlands, and in many other countries as well, those judgemental sampling methods come close to some kind of cut-off selection, in which a large part of the population (usually the items with the lowest expenditures) is deliberately left unobserved. This method obviously yields biased price index numbers. The question arises whether probability sampling would lead to better results in terms of the mean square error. We have considered simple random sampling, stratified sampling and systematic sampling proportional to expenditure. Monte Carlo simulations using scanner data on coffee, baby's napkins and toilet paper were carried out to assess the performance of the four sampling designs. Surprisingly perhaps, cut-off selection is shown to be a successful strategy for item sampling in the consumer price index.

    Release date: 1999-10-08
Data (1)

Data (1) ((1 result))

  • 1. Services Price Indexes Archived
    Table: 62F0040X
    Description:

    This occasional on-line bulletin series presents price indexes published by the Goods and Services Producing Industries Section, Prices Division. Each issue will contain different service price indexes.

    Release date: 1999-10-14
Analysis (1)

Analysis (1) ((1 result))

  • 1. Item selection in the Consumer Price Index: Cut-off versus probability sampling Archived
    Articles and reports: 12-001-X19990014710
    Description:

    Most statistical offices select the sample of commodities of which prices are collected for their Consumer Price Indexes with non-probability techniques. In the Netherlands, and in many other countries as well, those judgemental sampling methods come close to some kind of cut-off selection, in which a large part of the population (usually the items with the lowest expenditures) is deliberately left unobserved. This method obviously yields biased price index numbers. The question arises whether probability sampling would lead to better results in terms of the mean square error. We have considered simple random sampling, stratified sampling and systematic sampling proportional to expenditure. Monte Carlo simulations using scanner data on coffee, baby's napkins and toilet paper were carried out to assess the performance of the four sampling designs. Surprisingly perhaps, cut-off selection is shown to be a successful strategy for item sampling in the consumer price index.

    Release date: 1999-10-08
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