Global Purchasing Power Parities and Real Expenditures - Afristat

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Appendix IICP SoftwareAn important innovation introduced in the 2005 ICP bythe World Bank is a suite of well-integrated and specializedsoftware tools to support the collection, storage, validation,and processing of price data to produce PPPs at variouslevels of aggregation. Underlying these tools is a databasein which individual and average prices of products can bestored in a secure manner. The database also stores theGDP expenditure weights (at the basic-heading level), spatialweights, exchange rates, and population data.This set of software tools is called the ICP “ToolPack,”which provides an end-to-end solution for the ICP processand introduces methodological rigor and best practices, aswell as transparency in the computations. The ToolPackcovers activities such as product list preparation for pricing,using structured product description; survey preparation;user and product outlet specification; price data collectionand data entry; data validation at the country level; and dataprocessing and data exchange between the regional coordinatorsand national coordinators. At the regional level, theToolPack has a number of data validation tools for crosscountryanalysis across regions or subregions. Finally, theToolPack has several innovative features for reporting onthe price data aggregation to produce PPPs using a varietyof statistical methods.In the 2005 ICP round, several software componentswere developed. The following highlights some of the featuresand the ToolPack components that support them:m Product list preparation, using a structured productdescription (SPD) method. This component helpsin creating detailed product specifications for all categoriesof products used in the ICP. This supports adialogue between global, regional, and national ICPcoordinators and assists coordinators in comparingdifferent products.m Price survey and data collection for household consumptionitems. The price collection module (PCM)is designed for countries to collect price data on consumptionitems based on a product list and a surveyframework created using another module of theToolPack, the data processing module (DPM). ThePCM has basic data validation features to correctdata-entry errors and also has some data-auditingfunctions.m Data collection for government and gross fixedcapital formation items. Besides the household consumptionitem prices, which are collected using thePCM, the other major GDP categories of expenditure—construction,equipment, and compensation—197
198 Global Purchasing Power Parities and Real Expendituresmmmare not readily amenable for data collection using thePCM. Therefore, the data collection forms (DCF)module is now available, which is well integratedwith the DPM for price data aggregation and indexcomputation.Data processing. The ToolPack’s DPM component isthe main data-processing engine that can be used bothby the national and regional coordinators. Dependingon the user, the software presents the tools forvalidation needed at the national or the regional levels.For example, a national coordinator can use it forthe initial checking of the individual price observationsfor each product in his or her country. Once heor she is satisfied with the individual price data, thenational coordinator can then use the system to calculatethe average prices for each product for whichprices were collected in the country concerned. Thecountries have a choice in providing either individualprices or only the average product prices. TheToolPack accepts submissions from the countries ineither form for further processing.Country diagnostic reports. These reports are producedin the DPM from country submissions and arereviewed by the region and communicated back tothe national coordinator if there are issues with individualprices. The reports pinpoint the observationunder question and the probable causes of the dataerrors, thereby making the dialog between regionsand countries much more efficient.Quaranta tables. After the preliminary data cleaningis completed, the ToolPack provides a more broadlybased set of editing processes. One of the main diagnostictools used at this stage is the Quaranta table,named after Vincenzo Quaranta from the Italiannational statistical office (ISTAT), who developed itas an editing tool for the Eurostat-OECD PPP program.The Quaranta table shows details of the product,the reference period, the mean, the highest andlowest observations, PPP, PLI, exchange rate, weight,and coefficient of variation (the standard deviationdivided by the arithmetic mean) for each productwithin a basic heading, for each country.mmDikhanov tables. Another important innovationintroduced to assist in the editing phase of the 2005ICP is the Dikhanov table, named after Yuri Dikhanovof the World Bank, who developed the methodology.It shows the relationships between product pricesacross the whole range of products up to the levelof GDP for each country in a region, using the CPDmodel as the basis for aggregating and analyzing theprices data. For example, a particular feature of theDikhanov table is a measure of the distribution ofthe prices actually provided by a country comparedwith the estimated (or predicted) prices generated bythe CPD model. A positive residual means that theobserved average price is greater than that estimatedby the model, while a negative residual means thatthe estimated price is greater than the observed one.The residuals show by how much the data divergefrom the mean estimates of the model. Large residualsindicate significant departures from the expectedprices and can identify either unexpected variationsin the product prices between countries or largevariations in the prices for products within a country(or both). Any significant variation in one or theother of these variables can indicate an underlyingproblem with the price data or signal that a countrymay not be pricing the same item that the othercountries did. The ToolPack implementation of theDikhanov tables provides many options for comparingdata anomalies at different levels of aggregation,from major GDP categories downward to the basicheadinglevel. Further, the ToolPack allows drillingdown below the basic-heading level to the averageproduct prices to be able to trace the cause for thedeviations.Equipment, construction, and compensation (ECC)data validation. The data validation module (DVM)is yet another innovation of the ICP 2005 round forvalidating the average prices of construction componentsand the “construction systems” (that is, theequipment and compensation prices). This modulecompares the components of a price observation tobetter understand the differences in prices for the
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© 2008 by the International Bank f
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viContentsPart II: Technical Notes
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Acronyms and AbbreviationsADBAfDBBO
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PrefaceThis publication presents th
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AcknowledgmentsThe ICP shares a com
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Part IPurchasing Power Paritiesand
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2005 ICP:Results and Major Findings
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2005 ICP: Results and Major Finding
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Tables of Results21
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Part IITechnical Notes of the 2005
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Page 162 and 163: Comparison-Resistant AreasSome comp
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Page 222 and 223: Glossary 207Multilateral comparison
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