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Relevant bibliographies by topics / Consumer price indexes – Data processing

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Academic literature on the topic 'Consumer price indexes – Data processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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Journal articles on the topic "Consumer price indexes – Data processing"

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Saad, Ammar, Ruitao Zhang, and Ying Xia. "The Policy Analysis Matrix (PAM): Comparative Advantage of China’s Wheat Crop Production 2017." Journal of Agricultural Science 11, no. 17 (October 15, 2019): 150. http://dx.doi.org/10.5539/jas.v11n17p150.

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As the third-largest crop in China, wheat production plays an essential role in China's agricultural production, food processing and consumption structure. Besides, China is the world’s largest wheat producer and consumer, where it produces 14.83% of the world's total wheat production in 2017. So it is necessary to analyze and evaluate the government policy for wheat production in China using PAM. This research depends on the data has issued by the National Development and Reform Commission/China statistics press 2018 (National farm production cost-benefit survey 2017). The outcomes of this paper showed that the coefficients measures confirm there is government support for wheat production, that indicates, farmers are getting prices higher than global prices by the continuation of the current policy. While there was no comparable advantage has shown for Chinese wheat product in social prices due to the government intervention in the prices of production outputs. Where this policy representation indexes show that the policy for wheat production 2017 supported the farmers on the consumer cost.

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Asano, Seki, and Eduardo P. S. Fiuza. "Estimation of the Brazilian Consumer Demand System." Brazilian Review of Econometrics 23, no. 2 (November 2, 2003): 255. http://dx.doi.org/10.12660/bre.v23n22003.2726.

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In this study we estimate the Brazilian consumer demand system through family expenditure data, which cover all consumption categories. The model is estimated from family-level expenditures on seven consumption categories, and a new set of regional cost-of-living indexes. The sources for expenditures are the national household expenditure surveys (POFs) conducted in 1987/88 and 1995/96, which collected data from eleven metropolitan areas. To the best of our knowledge this is the first study of this type and extent based on both waves of POF. Corresponding price indexes were constructed from detailed commodity prices, also from each metropolitan area. The salient features of our study are 1) price variations come from both time and regional differences, which allows us to estimate price elasticities with high precision, 2) we have large variations in income (total expenditures), which is rarely available in aggregate data, and 3) we control for time specific factors by exploiting the panel structure of the data set.

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Faryna, Oleksandr, Oleksandr Talavera, and Tetiana Yukhymenko. "What Drives the Difference between Online and Official Price Indexes?" Visnyk of the National Bank of Ukraine, no. 243 (March 29, 2018): 21–30. http://dx.doi.org/10.26531/vnbu2018.243.021.

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This paper examines the associations between online price indexes and official statistics. First, we generate online CPI component sub-indexes, which are later aggregated to an Online Price CPI. This approach is applied to our unique dataset which contains about 3 million observations of online retail prices for consumer goods in Ukraine’s five largest cities. The data span over the period 2016m1 – 2017m12 and cover about 46% of Ukraine’s Consumer Price Inflation basket. We find that online inflation is generally consistent with official estimates, but the matching capability varies across sub-indexes. Although the differences can partially be explained by poor dataset coverage, we find that online prices may indeed represent new information that is not captured by official statistics.

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Krsinich, Frances. "The FEWS Index: Fixed Effects with a Window Splice." Journal of Official Statistics 32, no. 2 (June 1, 2016): 375–404. http://dx.doi.org/10.1515/jos-2016-0021.

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Abstract This article describes the estimation of quality-adjusted price indexes from ‘big data’ such as scanner and online data when there is no available information on product characteristics for explicit quality adjustment using hedonic regression. The longitudinal information can be exploited to implicitly quality-adjust the price indexes. The fixed-effects (or ‘time-product dummy’) index is shown to be equivalent to a fully interacted time-dummy hedonic index based on all price-determining characteristics of the products, despite those characteristics not being observed. In production, this can be combined with a modified approach to splicing that incorporates the price movement across the full estimation window to reflect new products with one period’s lag without requiring revision. Empirical results for this fixed-effects window-splice (FEWS) index are presented for different data sources: three years of New Zealand consumer electronics scanner data from market-research company GfK; six years of United States supermarket scanner data from market-research company IRI; and 15 months of New Zealand consumer electronics daily online data from MIT’s Billion Prices Project.

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Juszczak, Adam. "The use of web-scraped data to analyze the dynamics of footwear prices." Journal of Economics and Management 43 (2021): 251–69. http://dx.doi.org/10.22367/jem.2021.43.12.

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Aim/purpose – Web-scraping is a technique used to automatically extract data from websites. After the rise-up of online shopping, it allows the acquisition of information about prices of goods sold by retailers such as supermarkets or internet shops. This study examines the possibility of using web-scrapped data from one clothing store. It aims at comparing known price index formulas being implemented to the web-scraping case and verifying their sensitivity on the choice of data filter type. Design/methodology/approach – The author uses the price data scrapped from one of the biggest online shops in Poland. The data were obtained as part of eCPI (electronic Consumer Price Index) project conducted by the National Bank of Poland. The author decided to select three types of products for this analysis – female ballerinas, male shoes, and male oxfords to compare their prices in over one-year time period. Six price indexes were used for calculation – The Jevons and Dutot indexes with their chain and GEKS (acronym from the names of creators – Gini–Éltető–Köves–Szulc) versions. Apart from the analysis conducted on a full data set, the author introduced filters to remove outliers. Findings – Clothing and footwear are considered one of the most difficult groups of goods to measure price change indexes due to high product churn, which undermines the possibility to use the traditional Jevons and Dutot indexes. However, it is possible to use chained indexes and GEKS indexes instead. Still, these indexes are fairly sensitive to large price changes. As observed in case of both product groups, the results provided by the GEKS and chained versions of indexes were different, which could lead to conclu- sion that even though they are lending promising results, they could be better suited for other COICOP (Classification of Individual Consumption by Purpose) groups. Research implications/limitations – The findings of the paper showed that usage of filters did not significantly reduce the difference between price indexes based on GEKS and chain formulas. Originality/value/contribution – The usage of web-scrapped data is a fairly new topic in the literature. Research on the possibility of using different price indexes provides useful insights for future usage of these data by statistics offices. Keywords: inflation, CPI, web-scraping, online shopping, big data. JEL Classification: C43, C49.

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Bessonov, Vladimir. "What Opportunities Do New Technologies Bring About for Price Statistics?" Russian Journal of Money and Finance 80, no. 1 (March 2021): 120–26. http://dx.doi.org/10.31477/rjmf.202101.120.

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The paper discusses new opportunities for Russian price statistics that present-day information and communication technologies bring about. The paper is a response to the study Isakov et al. (2021) dedicated to the effort of developing a toolset to build a price quotation database through automated internet data collection and construction of consumer price indexes based on it. Discussed are the potential implications of this activity for price statistics.

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Cavallo, Alberto, and Roberto Rigobon. "The Billion Prices Project: Using Online Prices for Measurement and Research." Journal of Economic Perspectives 30, no. 2 (May 1, 2016): 151–78. http://dx.doi.org/10.1257/jep.30.2.151.

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A large and growing share of retail prices all over the world are posted online on the websites of retailers. This is a massive and (until recently) untapped source of retail price information. Our objective with the Billion Prices Project, created at MIT in 2008, is to experiment with these new sources of information to improve the computation of traditional economic indicators, starting with the Consumer Price Index. We also seek to understand whether online prices have distinct dynamics, their advantages and disadvantages, and whether they can serve as reliable source of information for economic research. The word “billion” in Billion Prices Project was simply meant to express our desire to collect a massive amount of prices, though we in fact reached that number of observations in less than two years. By 2010, we were collecting 5 million prices every day from over 300 retailers in 50 countries. We describe the methodology used to compute online price indexes and show how they co-move with consumer price indexes in most countries. We also use our price data to study price stickiness, and to investigate the “law of one price” in international economics. Finally we describe how the Billion Prices Project data are publicly shared and discuss why data collection is an important endeavor that macro- and international economists should pursue more often.

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Saputra, Igo Septa, Zulfanetti Zulfanetti, and Jaya Kusuma Edi. "Analisis faktor-faktor yang mempengaruhi Tingkat Partisipasi Angkatan Kerja (TPAK) di Provinsi Jambi." e-Jurnal Ekonomi Sumberdaya dan Lingkungan 8, no. 2 (July 1, 2019): 68–81. http://dx.doi.org/10.22437/jels.v8i2.11984.

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This research aim to: First, analyze the development of labor force participation rate, minimum wages, consumer price index and gross regional domestic product in Jambi Province. This study use time series data between 2000-2017 with data analysis method used namely quantitative descriptive analysis and Ordinary Least Square (OLS) method. Based on the result of data processing using the OLS method in multiple regression equations in 2000-2017 results were obtained. That the average development of the labor force participation rate, minimum wage, consumer price index and gross regional domestic product fluctuative from year to year. Based on processing data obtained results: (1) Consumer price index variable have a positive and not significant effect on labor force participation rate in Jambi Province; (2) The variable minimum wages and gross regional domestic product have a positive and significant effect on minimum wages in Jambi Province. Keywords: Labor Force Participation Rate, Minimum Wages, Consumer Price Indexand, and Gross Regional Domestic Product.

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9

Cheng, Andy Wui Wing, and Iris Wing Han Yip. "China’s Macroeconomic Fundamentals on Stock Market Volatility: Evidence from Shanghai and Hong Kong." Review of Pacific Basin Financial Markets and Policies 20, no. 02 (May 18, 2017): 1750014. http://dx.doi.org/10.1142/s021909151750014x.

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This paper examines the effect of Chinese macroeconomic variables, the industrial production growth rate, the producer price index, the 3-month short-term Shanghai Interbank Offer Rate and the consumer price index, on the volatility of the Shanghai and Hong Kong stock markets. We apply the generalized autoregressive conditional heteroskedastic mixed data sampling model for the study. Our empirical findings on various indexes and enterprises in the Shanghai and Hong Kong markets show that Chinese macroeconomic variables have a greater power to explain the volatility in Hong Kong than in Shanghai. They also contribute significantly to Hong Kong’s market volatility.

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Greenlees, John S., and Robert McClelland. "Does Quality Adjustment Matter for Technologically Stable Products? An Application to the CPI for Food." American Economic Review 101, no. 3 (May 1, 2011): 200–205. http://dx.doi.org/10.1257/aer.101.3.200.

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Most indexes in the Consumer Price Index (CPI) use a form of the “matched-model” approach. It is frequently assumed that this approach accurately reflects inflation for items that have no major trend in quality. In this paper we investigate that hypothesis using CPI data for retail food items. We find that CPI analysts may be correct on average when they decide that new and replacement items are similar in quality. We also find, however, that when sample items are replaced by items of significantly different quality the CPI imputation procedures may underestimate price change and overstate quality change.

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Dissertations / Theses on the topic "Consumer price indexes – Data processing"

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Heinze, Christian [Verfasser], Harry [Akademischer Betreuer] Haupt, and Dietmar [Akademischer Betreuer] Bauer. "A framework for spatiotemporal prediction with small and heterogeneous data - and an application to consumer price indexes - / Christian Heinze ; Harry Haupt, Dietmar Bauer." Bielefeld : Universitätsbibliothek Bielefeld, 2016. http://d-nb.info/1119981298/34.

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Ivancic, Lorraine Economics Australian School of Business UNSW. "Scanner data and the construction of price indices." 2007. http://handle.unsw.edu.au/1959.4/40782.

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This thesis explores whether scanner data can be used to inform Consumer Price Index (CPI) construction, with particular reference to the issues of substitution bias and choice of aggregation dimensions. The potential costs and benefits of using scanner data are reviewed. Existing estimates of substitution bias are found to show considerable variation. An Australian scanner data set is used to estimate substitution bias for six different aggregation methods and for fixed base and superlative indexes. Direct and chained indexes are also calculated. Estimates of substitution bias are found to be highly sensitive to both the method of aggregation used and whether direct or chained indexes were used. The ILO (2004) recommends the use of dissimilarity indexes to determine the issue of when to chain. This thesis provides the first empirical study of dissimilarity indexes in this context. The results indicate that dissimilarity indexes may not be sufficient to resolve the issue. A Constant Elasticity of Substitution (CES) index provides an approximate estimate of substitution-bias-free price change, without the need for current period expenditure weights. However, an elasticity parameter is needed. Two methods, referred to as the algebraic and econometric methods, were used to estimate the elasticity parameter. The econometric approach involved the estimation of a system of equations proposed by Diewert (2002a). This system has not been estimated previously. The results show a relatively high level of substitution at the elementary aggregate level, which supports the use a Jevons index, rather than Carli or Dutot indexes, at this level. Elasticity parameter estimates were found to vary considerably across time, and statistical testing showed that elasticity parameter estimates were significantly different across estimation methods. Aggregation is an extremely important issue in the compilation of the CPI. However, little information exists about 'appropriate' aggregation methods. Aggregation is typically recommended over 'homogenous' units. An hedonic framework is used to test for item homogeneity across four supermarket chains and across all stores within each chain. This is a novel approach. The results show that treating the same good as homogenous across stores which belong to the same chain may be recommended.

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Kgantsi, Eugene Modisa. "Comparative study of purchasing power parities for the food component using the consumer price index data in the South African provinces." Thesis, 2013. http://hdl.handle.net/10539/12675.

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A Dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science, 2012.
The purpose of this study is to investigate if the International Comparison Program (ICP) methodology could be used to examine the different buying power (worth) of the currency on the same products or goods amongst South African provinces. The method will be tested on the Consumer Price Index (CPI) food data collected from January 2006 to December 2006 from the main cities in the provinces. The food basket is obtained via the Income and Expenditure Survey (IES), which is generally updated every 5 years. South Africa (SA) has disparities and differentials in economic indicators such as the CPI, Gross Domestic Product and employment, amongst the provinces which are caused by among other things geographic set-up, urbanisation, inflation rates, and expenditure patterns. We use the monthly data to do an inter-provincial comparison of food prices by deriving annual purchasing power parities (PPPs) for each of the provinces, using the Country Product Dummy (CPD) method recommended as best practice by the World Bank. The CPI data is validated using the SEMPER software developed by the African Development Bank (AfDB). The validated data is examined for variability over the months and between the provinces using Analysis of Variance. Significant price differences are found for various products over the months and between provinces. The validated data was used to compute PPPs at the group and basic heading level. PPPs were investigated for differences in the provinces on grouped level of food products using Analysis of Variance. The reliability of PPPs between provinces is investigated both at grouped and basic heading level of products using the Cronbach-alpha statistic. The results show that there are no significant variations in PPPs across provinces. This could be due to the similar business opportunities or developments in the provinces or due to the aggregation of prices from the individual product (basic heading) to the main product group level. This implies that the cost of the food basket is the same across provinces.

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Books on the topic "Consumer price indexes – Data processing"

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missing], [name. Scanner data and price indexes. Chicago, IL: University of Chicago Press, 2002.

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Krueger, Alan B. Assessing bias in the Consumer Price Index from survey data. Cambridge, MA: National Bureau of Economic Research, 1998.

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3

Ramcharan, Rodney. Money, meat, and inflation: Using price data to understand an export shock in Sudan. [Washington, D.C.]: International Monetary Fund, Middle Eastern Department, 2002.

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Office, General Accounting. Medicaid: Changes in best price for outpatient drugs purchased by HMOs and hospitals : fact sheet for the Chairman, Subcommittee on Regulation, Business Opportunities, and Technology, Committee on Small Business, House of Representatives. Washington, D.C: The Office, 1994.

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(Editor), Robert C. Feenstra, and Matthew D. Shapiro (Editor), eds. Scanner Data and Price Indexes (National Bureau of Economic Research Studies in Income and Wealth). University Of Chicago Press, 2002.

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Consumer price index revision: Housing data collection manual. 3rd ed. [Washington, D.C.?]: The Bureau, 1997.

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Macroeconomic data: A user's guide. 3rd ed. Richmond, VA: Federal Reserve Bank of Richmond, 1994.

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H, Webb Roy, and Federal Reserve Bank of Richmond., eds. Macroeconomic data: A user's guide. 2nd ed. Richmond, Va: Federal Reserve Bank of Richmond, 1991.

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United States. Bureau of Labor Statistics, ed. Housing data collection manual. [Washington, D.C.]: U.S. Department of Labor, Bureau of Labor Statistics, 2004.

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Conference papers on the topic "Consumer price indexes – Data processing"

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Karcıoğlu, Reşat, Muhammet Özcan, and Ensar Ağırman. "The Relationship of Petroleum Price and BIST Sector Indexes." In International Conference on Eurasian Economies. Eurasian Economists Association, 2017. http://dx.doi.org/10.36880/c08.01878.

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Energy is not only indispensable element of everyday life, but also underlies industrialization and manufacturing. Energy and manufacturing have become integral parts with the importance of mechanization since the Industrial Revolution. As a result of this emerging situation, businesses, have become sensitive energy and energy prices. For this reason, changes in energy prices directly affect businesses and are thought to have effects on fluctuations in stock prices. Changes in the prices of primary energy sources directly or indirectly affect capital markets. In energy importer countries including Turkey, high energy prices cause an increase in current account deficit and decrease in real national income by increasing the amount of energy imports. In addition, high energy prices lead to cost-based inflation increases as they directly affect raw material prices used in production. All these factors indirectly affect capital markets. Direct effect of energy price changes on the capital market is explained by the fact that energy is an indispensable input in industrial production. In cases where the energy price increase is not reflected to the consumer, the profitability of the enterprise is decreasing. A decrease in profitability affects firm's stock price as well. The aim of this study is to reveal the relationship between sector indices in the Stock Exchange Istanbul (BIST) and oil price changes. Weekly data set for the period for 2006:1 - 2016:4 is used. Johannes co-integration method is used to measure long term relationship in the study.

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