Index Numbers

2010

This study attempts to estimate the rate of inflation in Pakistan by a stochastic approach to index numbers which provides not only point estimate but also confidence interval for inflation estimate. There are two approaches to index number theory namely: the functional economic approach and the stochastic approach. The attraction of stochastic approach is that it estimates the rate of inflation in which uncertainty and statistical ideas play a major roll of screening index numbers. We have used extended stochastic approach to index numbers for measuring the Pakistan inflation by allowing for the systematic changes in the relative prices. We use CPI data covering the period July 2001-march 2008.

An Introduction to Efficiency and Productivity Analysis, 1998

Here the ratios p/ps and q/qs measure the relative price and quantity changes and there is no index number problem. In general, when we have M>2 commodities, we have a problem of aggregation. The price relative, Pm/Pms, measures the change in the price level of the m-th commodity, and the quantity relative, qm/qms^ measures the change in the quantity level of the m-th commodity {m = 1,2,...,A/),. Now the problem is one of combining the M different measures of price (quantity) changes, into a single real number, called a price (quantity) index. This problem is somewhat similar to the problem of selecting a suitable measure of central tendency. In the next two sections, we briefly examine some of the more commonly-used formulae for measuring price and quantity index changes. 4.3 Formulae for Price Index Numbers We first focus on the price index numbers and then illustrate how these formulae can also be used in the construction of quantity index numbers. ' Refer to the section on duality in Chapter 2 for a discussion of these properties. ' These indices correspond to the usual Laspeyres and Paascl the base-and current-period technologies and output vectors. ^^ These indices correspond to the usual Laspeyres and Paasche-type index numbers because they rely on '^ This does not imply or follow from the results concerning the translog form we obtained in Section 4.6.3 when dealing with output quantity index numbers.

Statistika: Statistics and Economy Journal, 2019

The Consumer Price Index (CPI) is a common measure of inflation. Similarly to the Harmonised Index of Consumer Prices (HICP), it is determined using the Laspeyres index, thus data on the consumption of the basket of goods do not have to be current. The Laspeyres index, using weights only from the base period, may not reflect changes in consumer preferences that occurred in the studied year. In the ideal case, the CPI should be measured by one of the so called superlative price indices, such as the Fisher, Törnqvist or Walsh index formulas. The main problem with such indices is that they need expenditure data from the current period. The aim of the article is to assess the impact of the choice of the price index formula on the CPI measurement. We verify differences among known index formulas at the lowest and some higher data aggregation levels. We use known bilateral unweighted and weighted formulas together with their chained versions.

Romanian Statistical Review, 2012

The price indices have a long history and a large variety of uses, from the adjustment of the wages, pensions and payments included in a long-term contract, the defl ation of aggregates in National Accounts, to the elaboration of economic policies. Having identifi ed the purpose of the index, we`ll have to choose the target index and the calculation formula, this operation being carried out based on the observed prices and on the quantity and quality weights. In the statistical practice, the price index is often calculated by aggregating the elementary indices using the weighted arithmetic mean, using annual weights from a period that is previous to the reference period. In this situation, the question about the possible impact of the weights update (by prices) on the interpretation of price indices becomes legitimate, also the question about the infl uence of using this approach on measuring the price change. We can get a possible answer to this question using the Lowe and Young indices introduced by the Consumer Price Index international manual.

Journal of Econometrics, 2007

Most countries use either the Dutot or Jevons index number formula for the compilation of their consumer price index at the elementary level of aggregation. The difference between the formulas is shown to be accounted for by changes in price dispersion. In turn, some of this difference is shown to be explained by product heterogeneity. Scanner data on television sets (TVs) are used to calculate Dutot and Jevons indexes. The difference between them is successfully explained in terms of changes in price dispersion and much reduced using an hedonic, heterogeneity-controlled Dutot index. r

Séptima Reunión del Grupo de Ottawa, 2003

The results from different index number formulae can differ and can do so substantially. The main criteria for explaining such differences, and governing choice between them, are their ability to satisfy desirable test properties-the axiomatic approach-and their correspondence with plausible substitution behavior as predicted from economic theory. Yet the numerical differences between such formulae has been shown to be related to the extent of, and changes in, the dispersion of prices. However, within the index number literature there is, to the author's knowledge, no formal attempt to explain differences between the results from individual formulae in terms of theories and evidence on price dispersion. Explaining differences between formulae in terms of changes in the dispersion of prices benefits from the existence of economic theoretical frameworks to explain such dispersion, and thus improve our understanding of why differences from formulae occur. Such frameworks include search cost and menu cost theories and signal extraction models. This paper outlines the nature of the relationships between formulae in term of price dispersion, then considers economic theories of price dispersion and uses them to model price variation both within months and over time using an extensive scanner data set on television sets amounting to over 70,000 observations over 51 months. It concludes by considering the implications for index number construction.

Romanian Statistical Review Supplement, 2012

The index number problem can be framed as the problem of decomposing the value of a well-defined set of transactions in a period of time into an aggregate price term times an aggregate quantity term. It turns out that this approach to the index number problem does not lead to any useful solutions. The problem of decomposing a value ratio pertaining to two periods of time into a component that measures the overall change in prices between the two periods (this is the price index) times a term that measures the overall change in quantities between the two periods (this is the quantity index) is considered.

Journal of Economic Surveys, 1996

Romanian Statistical Review, 2012

The paper starts from the premise: why the statistical agencies do not select the quantitative vector of reference q out of the Lowe formula as being the monthly quantitative vector q 0 that belongs to the transactions of the month 0