thus essential that sampling procedures are clearly defined and well documented.
4.5 When sampling designs are planned, the full universe of locations, outlets and outlettypes, items, and varieties belonging to the scope of the CPI should be considered. All significant parts of that universe should be appropriately represented. An additional challenge is that representativity is not static but evolves over time. The samples that were initially designed for the price reference period may not be fully representative of the current period. Therefore, samples should
3.21 The weights for the COICOP groups, classes, and subclasses are their shares in the total consumption expenditures of the reference population. The data sources used to derive these shares are discussed in the following text. In addition, the weight for a subclass can be further stratified by region, by outlet or outlettype, or by a combination of both region and outlet. The elementary aggregate weights are the stratum weights according to expenditure class or subclass, region, and type of outlet. If no breakdown by region or outlet is used, the
Wageningen) to 258 for ParWan (i.e., Paramaribo and Wanica). The mission advised that this approach is reasonable when there are differences in consumption patterns.
4. The prices are collected from both markets and outlets . For some products the average price over a store type is calculated and then weighted by the relative number of observations. In case this outlettype average price is not needed for other purposes, this step is unnecessary. The number of each outlettype in price collection in each Domain should reflect the purchase habits of residents of the
The Consumer Price Index Manual (2004) provides guidelines for aggregation formulas that are promulgated at IMF training courses and technical assistance missions. This paper develops elementary level aggregation theory to better inform users and compilers. Most countries use either the Dutot or Jevons index formula. These formulas generally give different results; advice on choice of formula matters. Using an approach based on sample estimators, and an illustration based on scanner data, the paper shows how differences in these formulas can be explained by changes in price dispersion and, in turn, by product heterogeneity. Implications for choice of formula are considered.
section of the paper uses highly detailed scanner data from retailers’ barcode readers that amount to about 31,000 observations over 24 months on prices, characteristics, and brands of models of television sets (TVs) sold in different outlettypes.
The focus of the paper is on the difference between two lower-level formulas—the ratio of unweighted arithmetic means of prices (Dutot index) and the ratio of unweighted geometric means (Jevons index). Both formulas are commonly used, both can be justified under particular circumstances, but they can give quite different
This Technical Assistance Report on Suriname constitutes technical advice provided by the staff of the IMF to the authorities of Suriname in response to their request for technical assistance. The mission discussed issues concerning the consumer price index (CPI), the producer price index (PPI) and export price index (XPI). On the CPI, the mission reviewed current practices and provided some recommendations. The main recommendations are to switch from a Dutot to a Jevons index on the elementary aggregate level and to start publishing the CPI according to the Classification of Individual Consumption according to Purpose on a class level provided the number of items permits. On the planned PPI and XPI, the discussion focused on available data sources and next steps for developing a PPI for Suriname. Reliable price statistics are essential for informed economic policymaking by the authorities. They also provide the private sector, foreign investors, rating agencies, and the public in general with important inputs in their decision-making, while informing both domestic economic policy and IMF surveillance.
countries indirect taxes and hence price development may differ between the provinces.
4.12 Regional weights may typically be obtained from the HES or they may be estimated from retail sales data or population data. Regional weights may or may not be introduced into the CPI, depending on the size and structure of the country, data availability, resources and the purpose of the index.
Outlet or outlet-type weights
4.13 Prices are collected from a variety of outlets and outlettypes. Information about the sale or market share of the outlets may be used to form
The 2005 International Comparison Program's (ICP) estimates of economy-wide purchasing power parity (PPP) are based on parity estimates for 155 basic expenditure headings, mainly estimated using country product dummy (CPD) regressions. The estimates are potentially inefficient and open to omitted variable bias for two reasons. First, they use average prices across outlets as the left-hand-side variable. Second, quality-adjusted prices of non-comparable replacements, required when products in outlets do not match the required specifications, cannot be effectively included. This paper provides an analytical framework based on panel data and hedonic CPD regressions for ameliorating these sources of bias and inefficiency.
underlying the endogeneity is conditioned on the X ¯ gj . Endogeneity bias will be minimal if most price-determining variables are included, that is, if the correlation between the endogenous grouping variable and the disturbance is small ( Dhrymes, and Lleras-Muney, 2006 ). 12 Issues of endogeneity are considered further in the context of a panel structure to the data in the next section. A salient compromise is to utilize further stratification, include factors other than product and country (say, location and outlettype) in the regression as dummy variables. The
subdivisions can be introduced where there is further stratification of the sample to include geographical location, outlettype, or a more detailed product level classification. Thus, the weighting structure will depend on the sample design for price collection and compilation and in particular the need for more detailed weights which may be generated by additional sample stratification. In general, NSOs will collect some prices centrally and adopt up to four levels of sampling stratification for local price collection: locations; outlets within locations; items within