Relevant bibliographies by topics / Consumer price indexes

Academic literature on the topic 'Consumer price indexes'

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Published: 4 June 2021
Last updated: 29 July 2024

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Journal articles on the topic "Consumer price indexes"

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White, Alan G. "Measurement Biases in Consumer Price Indexes." International Statistical Review / Revue Internationale de Statistique 67, no. 3 (December 1999): 301. http://dx.doi.org/10.2307/1403708.

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White, Alan G. "Measurement Biases in Consumer Price Indexes." International Statistical Review 67, no. 3 (December 1999): 301–25. http://dx.doi.org/10.1111/j.1751-5823.1999.tb00451.x.

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Benedetti, Ilaria, Tiziana Laureti, Luigi Palumbo, and Brandon M. Rose. "Computation of High-Frequency Sub-National Spatial Consumer Price Indexes Using Web Scraping Techniques." Economies 10, no. 4 (April 14, 2022): 95. http://dx.doi.org/10.3390/economies10040095.

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The development of Information and Communications Technology and digital economies has contributed to changes in the consumption of goods and services in various areas of life, affecting the growing expectations of users in relation to price statistics. Therefore, it is important to provide information on differences in consumer prices across space and over time in a timely manner. Web-scraped data, which is the process of collecting large amounts of data from the web, offer the potential to improve greatly the quality and efficiency of consumer price indices. In this paper, we explore the use of web-scraped data for compiling high-frequency price indexes for groups of products by using the time-interaction-region product model. We computed monthly average prices for five entry-level items according to the Consumer Price Index for All Urban Consumers (CPI-U) classification and tracked their evolution over time in 11 USA cities reported in our dataset. Even if our dataset covers a small percentage of the CPI-U index, results show how web scraping data may provide timely estimates of sub-national SPI evolution and unveil seasonal trends for specific categories.
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Hottman, Colin J., and Ryan Monarch. "Who's Most Exposed to International Shocks? Estimating Differences in Import Price Sensitivity across U.S. Demographic Groups." International Finance Discussion Paper, no. 1380 (September 2023): 1–40. http://dx.doi.org/10.17016/ifdp.2023.1380.

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Differences in consumption patterns across demographic groups mean that international price shocks differentially affect such groups. We construct import price indexes for U.S. consumer groups that vary by age, race, sex, education, and urban status. Black consumers and college graduates experienced significantly higher import price inflation from 1996-2018 compared to other groups, such as high school dropouts, rural consumers, and consumers over 60. Sensitivity to international price shocks varies widely, implying movements in exchange rates and foreign prices, both during our sample and during the Covid-19 pandemic, drove sizable differences in import price inflation – and total inflation – across groups.
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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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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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Prada, Sergio I., Julio C. Alonso, and Julián Fernández. "Exchange rate pass-through into consumer healthcare prices in Colombia." Cuadernos de Economía 38, no. 77 (July 1, 2019): 523–50. http://dx.doi.org/10.15446/cuad.econ.v38n77.66189.

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The exchange rate pass-through into the consumer price index on healthcare goods and services was measured by estimating a FAVAR model for Colombia. Results provide evidence of an incomplete and heterogeneous effect. There is no indication of transmission to the services or insurance indexes, but there is a significant effect on the medicines and devices indexes that have implications for out-of-pocket expenditure. Therefore, this indicates that the Colombian healthcare system effectively protects consumers from exchange rate volatility, but may need to design policies to protect consumers from price rises in medicines and goods that are not covered by the national benefits package.
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Moulton, Brent R., and Kenneth J. Stewart. "An Overview of Experimental U.S. Consumer Price Indexes." Journal of Business & Economic Statistics 17, no. 2 (April 1999): 141. http://dx.doi.org/10.2307/1392469.

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Moulton, Brent R., and Kenneth J. Stewart. "An Overview of Experimental U.S. Consumer Price Indexes." Journal of Business & Economic Statistics 17, no. 2 (April 1999): 141–51. http://dx.doi.org/10.1080/07350015.1999.10524804.

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Dubey, Amaresh, and Palmer-Jones Richard. "Prices, Price Indexes and Poverty Counts in India during 1980s and 1990s: Calculation of Unit Value Consumer Price Indexes." Artha Vijnana: Journal of The Gokhale Institute of Politics and Economics 47, no. 3-4 (December 1, 2005): 223. http://dx.doi.org/10.21648/arthavij/2005/v47/i3-4/115623.

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Dissertations / Theses on the topic "Consumer price indexes"

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Chan, Ka-lin Karen. "Forecasting models for Hong Kong's consumer price index." Hong Kong : University of Hong Kong, 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13787202.

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Chan, Ka-lin Karen, and 陳家蓮. "Forecasting models for Hong Kong's consumer price index." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B3197725X.

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Mazumdar, Tridib. "The effects of learning intentions and choice task orientations on buyers' knowledge of price: an experimental investigation." Diss., Virginia Polytechnic Institute and State University, 1987. http://hdl.handle.net/10919/53645.

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This dissertation examines the process by which buyers encode and store price information in their memories and how the information is retrieved when such a need arises. Using theories in human learning and memory, it has been argued that buyers’ learning of price information is primarily influenced by their learning plans and the criteria they use pin choice decisions. Because of the differences in learning and choice task orientations, buyers are postulated to encode and store the information differently and therefore, different memory tests are necessary to investigate the retrieval mechanisms and thereby making inferences about their knowledge of price. While it is recognized that buyers may encode and retrieve price information in many different ways, this research has examined the differential impact of learning and choice task orientations on their recall, recognition, and ranking performances. The hypotheses developed in this research were tested in a laboratory experiment using ninety women shoppers as subjects. The two levels of learning (incidental and intentional) and the three levels of choice task orientations (non-price, mixed, and price) were fully crossed in a 2 x 3 full-factorial between-subjects design. Subjects, after being randomly assigned to one of the six experimental conditions took part in a simulated grocery shopping. Having made their selections, subjects responded to recall, recognition, and ranking memory tests involving prices of the items selected. Subjects also indicated their confidence about the accuracy of their responses. The accuracy and confidence ratings were used as dependent measures when testing the hypotheses. Since accuracy measures were dichotomous (correct or incorrect) in nature, loglinear modes were tested using maximum likelihood estimation procedure. For continuous dependent measure (e.g. confidence), ordinary least square estimations were carried out in a univariate ANOVA framework. In addition, several multiple comparison procedures were used to test differences between mean accuracy and confidence scores. The data analysis supported fifteen out of sixteen hypothesized relationships. The results supported the argument that buyers’ learning of price information improves with greater use of price in their choice decisions and with greater need to remember the information for later use. Overall, recognition was found to be a more appropriate retrieval mechanism than recall. Need for remembering specific prices did not significantly improve buyers° ability to rank items in terms of their expensiveness. The conceptualization and the research results are expected to make both theoretical and methodological contributions in pricing research. Particularly, the issues involving formation of reference prices and the manner in which the internal reference prices are retrieved and used in iii choice decisions are partially addressed using a consumer information processing perspective. Nonetheless, future research is needed to resolve additional issues in price perception research.
Ph. D.
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Smith, Aaron D. "Stochastic permanent breaks /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1999. http://wwwlib.umi.com/cr/ucsd/fullcit?p9938588.

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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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Baldwin, Andrew. "The treatment of seasonal commodities in the consumer price index." Thesis, University of Ottawa (Canada), 1986. http://hdl.handle.net/10393/4580.

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Joslyn-Battaglia, Kari. "The Relationship Between an Industry Average Beta Coefficient and Price Elasticity of Demand." Thesis, North Texas State University, 1986. https://digital.library.unt.edu/ark:/67531/metadc500999/.

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The price elasticity of demand coefficient for a good or service is a measure of the sensitivity, or responsiveness, of the quantity demanded of a product to changes in the price of that product. The price elasticity of demand coefficients were generated for goods and services in nine different industries for the years 1972 to 1984. A simple linear demand function was employed, using the changes in the Consumer Price Index as a proxy for changes in price and Personal Consumption Expenditures, taken from the National Income and Product Accounts, as a proxy for quantity. Beta measures the sensitivity, or responsiveness, of a stock to the market. An industry average beta coefficient was generated for each of the nine industries over the time period, using the beta coefficients published by Value Line for firms which met certain criteria. In order to test the relationship between the price elasticity of demand and an industry average beta coefficient, a simple regression was performed using the beta coefficient as the dependent variable and the price elasticity of demand coefficient as the independent variable. The results broke down into 3 basic categories: those industries for which there seemed to be no relationship, those industries where there was a fairly strong probability that a relationship exists and the price elasticity of demand explains at least part of the variation in beta coefficients, and those industries where there was a very high probability that a relationship does exist and the variation in the price elasticity of demand coefficients substantially explained the variation in the industry average beta coefficients. The first category includes the food at home, tobacco, and shoe industries. The second category includes the men's clothing, the women's clothing, and the alcoholic beverages industries, and the third includes the automobile, airline, and fast-food restaurant industries.
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Кремень, О. І. "Оцінювання інфляції як фінансово-статистична проблема." Thesis, Українська академія банківської справи Національного банку України, 2012. https://er.knutd.edu.ua/handle/123456789/13253.

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Swanepoel, C. V. "Stock returns as predictors of interest rates and inflation: The South African experience." University of the Western Cape, 1990. http://hdl.handle.net/11394/7892.

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Magister Commercii - MCom
This study analyses the extent to which stock returns provide forecasts of changes in interest rates and inflation for the South African market. The period under investigation, January 1966 - February 1989, is characterised by structural changes in the South African economy, especially in the financial markets. The earnings yield on shares is used as a measure of the return on stocks. Stock returns of 10 specific industries are used in addition to the overall market return. Monthly inflation series were constructed by employing both the Consumer Price Index (CPI) and the Producer Price Index (PPI). Before examining that relationship, tests were done to examine the relationship between nominal stock returns and expected inflation. The relation between the stock market and expected inflation is estimated by using three measures of expected inflation. The results appear to suggest that the stock market reacted positively to expected inflation during the 1966 - 1982 period. Two proxies of expected inflation. Best results inflation are used to were obtained with measure future the Fama-Gibbons measure. In addition, the results suggest that stock returns provide additional information of future inflation to that contained in the Fama-Gibbons and interest rate models. Returns for specific industries, used in this study, appear to provide marginally better forecasts of inflation than the overall market return. The results also suggest that stock returns provide forecasts of changes in interest rates and inflation. There is no evidence that the specific industries used, provide consistent better forecasts of interest rate changes than the overall market.
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Fouché, Elizabeth Maria. "The impact of price discrimination on tourism demand / Elizabeth Maria Fouché." Thesis, North-West University, 2005. http://hdl.handle.net/10394/1162.

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The primary goal of this study was to determine the impact of price discrimination on tourism demand. Four objectives were defined with reference to the primary research goal. The first objective was to analyse the concept of price discrimination and relevant theories by means of a literature study. In this regard it was found that price discrimination between markets is fairly common and that it occurs if the same goods were sold to different customers at different prices. Price discrimination is also possible as soon as some monopoly power exists and it is feasible when it is impossible or at least impractical for the buyers to trade among themselves. Three different kinds of price discrimination can be applied, namely first-degree, second-degree and third-degree price discrimination. The data also indicated that price discrimination is advantageous (it mainly increases profit) and that it has several other effects too. The second objective was to analyse examples of price discrimination by means of international case studies. In these different case studies it was found that demand and supply, therefore consumer and product, formed the basis of price discrimination. If demand did not exist, it would be impossible to apply price discrimination. The findings also indicated that, for an organisation to be able to practice price discrimination, the markets must be separated effectively and it will only be successful if there is a significant difference in demand elasticity between the different consumers. Furthermore, the ability to charge these different prices will depend on the consumer's ability and willingness to pay. If an organisation should decide to price discriminate, it would lead to a higher profit, a more optimal pricing policy and also to an increase in sales. The third objective was to analyse national case studies. This was done through comparing the data of a tourism organisation price discriminating (Mosetlha Bush Camp, situated in the North West) to two organisations that did not implement price discrimination (Kgalagadi Transfrontier Park in the Northern Cape and Golden Leopard Resort, also situated in the North West). It was found that a customer with low price elasticity is less deterred by a higher price than a customer with a high price elasticity of demand. As long as the customer's price elasticity is less than one, it will be very advantageous to increase the price: the seller will in this case get more money for less goods. With the increase in price the price elasticity tends to rise above one. The fourth objective was to draw conclusions and make recommendations. It was concluded that price discrimination could be applied successfully in virtually any organisation or industry. Furthermore, price discrimination does not always have a negative effect; but can have a positive ass well. It can have a positive effect on tourism demand. The findings emphasised that the main reason for implementing price discrimination is to increase profit at the cost of reducing consumer surplus. From the results it was recommended that more research on this topic should be conducted.
Thesis (M.Com. (Tourism))--North-West University, Potchefstroom Campus, 2006.
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Books on the topic "Consumer price indexes"

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Organisation for Economic Co-operation and Development. Statistics Directorate., ed. Consumer price indices. Paris: Organisation for Economic Co-operation and Development, 1994.

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Laraine, Engel, Erdman Linda Anne, and Merchants and Manufacturers Association, eds. Consumer price index manual. [Los Angeles?]: Merchants and Manufacturers Association, 1989.

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Ralph, Turvey. Consumer price indices: An ILO manual. Geneva: International Labour Office, 1989.

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Ung, Bunleng. Seasonality in the Cambodian consumer price index. Phnom Penh: Cambodia Development Resource Institute, 2000.

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Hawaii. Dept. of Planning and Economic Development. Research and Economic Analysis Division., ed. The Honolulu consumer price index, 1940-1986. [Honolulu]: Dept. of Planning & Economic Development, Research & Economic Analysis Division, State of Hawaii, 1986.

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Directorate, Organization for Economic Co-operation and Development (OECD) Statistics. Consumer price indices: sources and methods. Paris: OECD, 1994.

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Kenya. Central Bureau of Statistics., ed. The new Kenya consumer price index: Users' guide. [Nairobi]: The Bureau, 2002.

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Baker, Dean. Getting prices right: A methodologically consistent consumer price index 1953-94. Washington, DC: Economic Policy Institute, 1996.

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United States. Bureau of Labor Statistics., ed. Consumer price index revision reference checklists. [Washington, D.C.?]: U.S. Dept. of Labor, Bureau of Labor Statistics, 1996.

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Library of Congress. Congressional Research Service, ed. The Consumer Price Index: A brief overview. [Washington, D.C.]: Library of Congress, Congressional Research Service, 1987.

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Book chapters on the topic "Consumer price indexes"

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Santioni, Raffaele, Isabella Carbonaro, and Margherita Carlucci. "Consumer Price Indexes: An Analysis of Heterogeneity Across Sub-Populations." In Contributions to Statistics, 133–49. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2140-6_7.

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Fallis, George. "Consumer Price Index." In Encyclopedia of Quality of Life and Well-Being Research, 1217–18. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_544.

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Officer, Lawrence H. "Consumer Price Index." In Essays in Economic History, 173–85. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95925-8_10.

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Fallis, George. "Consumer Price Index." In Encyclopedia of Quality of Life and Well-Being Research, 1337–38. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-17299-1_544.

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Pfister, Ulrich. "Economic inequality in Germany, 1500-1800." In Disuguaglianza economica nelle società preindustriali: cause ed effetti / Economic inequality in pre-industrial societies: causes and effect, 301–24. Florence: Firenze University Press, 2020. http://dx.doi.org/10.36253/978-88-5518-053-5.20.

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The chapter reviews existing evidence regarding four aspects of economic inequality: relative factor rents, which relate to the factorial distribution of income and also underlie the so-called Williamson index (y/wus), which is correlated with the Gini index of household income; real inequality in terms of opposite movements of the price of consumer baskets consumed by different strata of society; the inequality of pay according to gender and skill, as well as between town and countryside; and wealth inequality, particularly with respect to the access to land. The main result is that, with given technology and agrarian institutions, there is a positive correlation between population and inequality.
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Leaver, Sylvia, and Richard Valliant. "Statistical Problems in Estimating the U.S. Consumer Price Index." In Business Survey Methods, 543–66. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118150504.ch28.

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Zhu, Bing. "Exchange Rate and Price: A Granger Causality Test of Consumer Price Index in China." In Advances in Intelligent Systems and Computing, 89–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27711-5_13.

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McNeill, Desmond. "Can Economics Help to Understand, and Change, Consumption Behaviour?" In Consumption, Sustainability and Everyday Life, 317–37. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-11069-6_12.

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AbstractThis chapter assesses the contribution that economics can make to help us understand consumer behaviour and, if necessary, to try and change it. Economic theory of consumer behaviour is sophisticated and rigorous, but very limited. It excludes from consideration many of the factors which are well-recognised by other social sciences as being important. These limitations stem largely from the standard model of homo economicus. Economists are not unaware of this problem, but it is difficult to resolve it: to establish models that are tractable—for example incorporating the idea of interdependent preferences. But even simple economic theory, in which income and price are the main explanatory factors of consumer behaviour, provides the basis for potentially very effective policy instruments. If incomes fall, consumption is indeed reduced; and taxes and subsidies can substantially alter consumer behaviour. The problem is that such instruments are politically very unpopular.
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Ge, Li, and Guisheng Yin. "Application of Process Neural Network on Consumer Price Index Prediction." In Advances in Intelligent and Soft Computing, 427–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27866-2_51.

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De Vitiis, Claudia, Alessio Guandalini, Francesca Inglese, and Marco Dionisio Terribili. "Sampling Schemes Using Scanner Data for the Consumer Price Index." In New Statistical Developments in Data Science, 203–17. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21158-5_16.

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Conference papers on the topic "Consumer price indexes"

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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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Hou, Keyu, Shunxun Li, Jingjing Li, Wei Xu, Rui Wang, and Jin Zhou. "Research on consumer portraits of offline fast fashion shoe stores based on IoT smart hardware." In The 8th International Conference on Advanced Materials and Systems. INCDTP - Leather and Footwear Research Institute (ICPI), Bucharest, Romania, 2020. http://dx.doi.org/10.24264/icams-2020.iii.9.

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There is a close relationship between consumer’s portrait and product’s attributes. Consumer portraits are usually obtained from information provided by consumers or by using data analysis of computer vision technology when they were in store. However, there was few concerns on the product’s attribute which was a critical factor affecting consumer portrait establishment. Therefore, the purpose of this study was to establish IoT based product attributes’ data collection system then to use this system to portrait consumers behaviors. Firstly, we used our own developed smart hardware to collect consumers' attention data on products of fast fashion shoe stores. Then the product attention index was obtained by combining sales data, and the quantitative attributes of the products with the highest attention index were analyzed, including the age, style and price. At last, improved the TOFA model to make it suitable for the conversion analysis of product attributes to consumer portraits. The results showed that there were core hedonic middle-aged consumer groups and potential thrifty youth consumer groups in the store, and the styles of shoes tend to be fashionable and casual. The conclusion was that the new model can effectively analyze the core consumer portraits of shoe stores and provide strategies for shoe store positioning and supply.
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Yalman, İlkay Noyan, and Şerife Merve Koşaroğlu. "Analysis of the Relationship between Consumer Confidence Index and Inflation in Türkiye." In International Conference on Eurasian Economies. Eurasian Economists Association, 2023. http://dx.doi.org/10.36880/c15.02816.

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The course of macroeconomic indicators has an impact on consumers' decisions and expectations. Consumer confidence refers to the tendencies of consumers in the face of economic conditions and the situation regarding the decisions to be taken by other decision units. It is thought that the realized and expected inflation within the economic indicators is important in the consumers' perception of economic developments. Therefore, price stability represents one of the main factors determining consumer decisions regarding income, consumption expenditure and savings. Price stability in Turkey has varied over the years. The devastating effects of inflationary processes in the economic development process were high. From this point of view, investigating the relationship between consumer confidence and inflation in Turkey has been the main motivation of the study. The results of the analysis made with the 2012:01-2023:01 monthly data provided evidence for the existence of a long-term relationship between the variables.
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Tengiz, Yusuf Ziya, and Zehra Meliha Tengiz. "A Study on Beef Price in Turkey." In International Conference on Eurasian Economies. Eurasian Economists Association, 2018. http://dx.doi.org/10.36880/c10.02213.

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Beef prices in Turkey is increased for long time. That outcome is caused to find out the reasons which are variables related to beef prices. The target of this study is to clarify relationship of beef price and its independent variables with a regression model. Data analyzed with SPSS 23.0. Based on the model’s equation, the independent variables which are average world beef unit price (USD), per capita beef consumption in Turkey (kg), government livestock incentives (TRY), consumer price index on beef (%), exchange rate (USD/TRY), real effective exchange rate (%) and gross domestic national product (%) are found as direct proportion with beef prices. On the other hand, poultry meat as an alternative to beef has inverse proportion with the prices.
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Radzikowski, Bartosz, and Adam Śmietanka. "Online CASE CPI." In CARMA 2016 - 1st International Conference on Advanced Research Methods and Analytics. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/carma2016.2016.3133.

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Online CASE CPI is an example of using Big data in public statistics. In principle, it is a consumer price index based entirely on online prices: a combination of Central Statistical Office of Poland’s methodology and online data sets. An innovative method of data collection – data scrapping – allowed us to substantially reduce a time delay between data collection and a publication of results. A short, nine-month period of data collection has not given rise to make important conclusions, hence the aims of this paper are: to discuss a general framework of measuring consumer inflation online, to present preliminary results for Poland and to highlight the strengths and weaknesses of this approach. Finally, we believe that online consumer price indices have a complementary nature to conventional inflation measurement, but it might be a serious alternative, having in mind a huge growth potential of e-commerce in coming years.
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Glaser-Opitzová, Helena. "Use of Scanner Data in Measuring the Consumer Price Index in the Conditions of the Slovak Republic." In EDAMBA 2021 : 24th International Scientific Conference for Doctoral Students and Post-Doctoral Scholars. University of Economics in Bratislava, 2022. http://dx.doi.org/10.53465/edamba.2021.9788022549301.92-102.

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The compilation of the Consumer Price Index (CPI) is, in the conditions of the Slovak Republic, based on the fixed consumer basket. Only the lockdown during pandemics showed us how a fixed basket can very quickly become irrelevant due to a rapidly changing model of consumer behaviour. The changeover from traditional data collection to the usage of data from scanners practically means the passing from static universe of selected sorts of goods to the dynamic universe of all goods consumed. While classical bilateral indices may be appropriate for a fixed basket, the transition to a dynamic approach raises the question of whether traditionally used methods are still valid. Our goal is to publish high quality index and therefore it is necessary to bear in mind that the index number formula selection and methods applied to data from scanners can have a significant impact on achieved results. The paper presents the basic conceptual framework for the use of scanner data for the purposes of compiling the CPI in relation to selected findings of the experimental study performed on real data of five retail chains for the “Food and non-alcoholic beverages” division.
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Bal, Harun, Mehmet Demiral, and Filiz Yetiz. "Exchange Rate Pass-Through to Domestic Prices: Evidence from OECD Countries." In International Conference on Eurasian Economies. Eurasian Economists Association, 2017. http://dx.doi.org/10.36880/c08.01951.

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There is an immense literature on the effects of exchange rate changes on macroeconomic indicators, specifically on the trade balance, growth, inflation, and overall productivity in open economies. One of the main attempts in the related literature is about ascertaining whether the exchange rate fluctuations alter domestic prices. This possible mechanism is called as the pass-through effect which is getting more important since the argument that exchange rate adjustment is a part of the solution for global rebalancing is empirically well-supported. Starting from this claim, this study purposes to explore whether there is an exchange rate pass-through effect in 19 high-income OECD countries over the period 1990-2015. To this end, using a panel data set of consumer price index, producer price index proxied by wholesale price index, the nominal effective exchange rates, and industrial production presented by the value-added share of industry sectors in gross domestic product, structural vector autoregressive (VAR) and autoregressive distributed lag (ARDL) models are estimated in an unbalanced panel data analysis procedure. Results reveal that exchange rate pass-through effects on the domestic prices are significant but not that strong in both the short-run and the long-run. Expectedly, the pass-through effects tend to diminish over time. The study concludes that policy-makers need to consider policy actions accompanying the exchange rate changes to ensure domestic price stability which consequently interacts with many macroeconomic indicators.
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Pillay, Khuneswari Gopal, Tivya Ravie, and Siti Aisyah Mohd Padzil. "LASSO regression in consumer price index Malaysia." In PROCEEDINGS OF SCIEMATHIC 2020. AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0053192.

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Dunuwila, SR, and K. Devapriya. "Analysis of the current housing market in Colombo metro region to enhance the prospective consumer satisfaction." In 10th World Construction Symposium. Building Economics and Management Research Unit (BEMRU), University of Moratuwa, 2022. http://dx.doi.org/10.31705/wcs.2022.9.

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Housing is an essential element of social development. One consumer may purchase such a house once for his/her entire lifetime. Therefore, when making a housing purchasing decision, it is intensively explored more than it is considered in purchasing other consumable products. Property developer has the responsibility of understanding the consumer behaviour. The main research problem is the lack of attention towards the analysis of the current housing market of the Colombo Metro region from the consumer perspective. An extensive literature synthesis was carried out to gather information on the general attributes of the housing market and determinants of housing supply. Furthermore, investigation on the housing demand and consumer behaviour reference to Colombo Metro region were conducted through the literature synthesis. Subsequently, case studies and a survey have been adopted to proceed with the study following the mixed research approach. Semi-structured interviews for case studies and questionnaire survey were employed as the primary data collection. The primary data analysis was conducted through manual content analysis, Relative Important Index (RII) techniques and elementary statistical analysis. The findings revealed, how the prospective consumers are considering Person, Product, Place, Price related factors when purchasing a residential property. For an example this research discovered that quick access to Colombo is the highly considered fact by the consumers. It revealed that the consumer behaviour in Colombo Metro region is different from other contexts. Therefore, carrying out a study to analyse the current housing will be very important to maximize the consumer satisfaction in house purchasing.
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Witharana, W. W. S. K., U. K. D. T. N. Udugama, P. M. R. Fernando, H. M. H. Kaumadi, and T. S. G. Peiris. "Forecasting Consumer Price Index in the United States." In SLIIT International Conference on Advancements in Sciences and Humanities 2023. Faculty of Humanities and Sciences, SLIIT, 2023. http://dx.doi.org/10.54389/raqa6627.

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This report presents the Auto-Regressive Integrated Moving Average (ARIMA) model for forecasting the consumer price index (CPI) in US using monthly data from March 2010 to March 2023. The original series was not stationary, but the first difference series was found to be stationary using the Augmented Dicky Fuller test. The best-fitted model was identified based on the significance of the parameters, volatility (sigma2 ), log-likelihood, Akaike, Schwartz, and Hannan Quinn information criterion. Parameters of the fitted model are significantly deviated from zero. The stability of the model has been checked using the roots of the unit root test. Residuals of the fitted model satisfied the randomness but non constant variance. The monthly forecasted values of CPI from April 2023 to August 2023 are 301.833, 302.444, 303.038, 303.639, and 304.261. The percentage errors of the forecasted values are less than one percent. This method and results provide useful information to policy and market makers for their planning.
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Reports on the topic "Consumer price indexes"

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Garciga, Christian L., Randal J. Verbrugge, and Saeed Zaman. The Effect of Component Disaggregation on Measures of the Median and Trimmed-Mean CPI. Federal Reserve Bank of Cleveland, January 2024. http://dx.doi.org/10.26509/frbc-wp-202402.

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For decades, the Federal Reserve Bank of Cleveland (FRBC) has produced median and trimmed-mean consumer price index (CPI) measures. These have proven useful in various contexts, such as forecasting and understanding post-COVID inflation dynamics. Revisions to the FRBC methodology have historically involved increasing the level of disaggregation in the CPI components, which has improved accuracy. Thus, it may seem logical that further disaggregation would continue to enhance its accuracy. However, we theoretically demonstrate that this may not necessarily be the case. We then explore the empirical impact of further disaggregation along two dimensions: shelter and non-shelter components. We find that significantly increasing the disaggregation in the shelter indexes, when combined with only a slight increase in non-shelter disaggregation, improves the ability of the median and trimmed-mean CPI to track the medium-term trend in CPI inflation and marginally increases predictive power over future movements in CPI inflation. Finally, we examine the practical implications of our preferred degree of disaggregation. Our preferred measure of the median CPI suggests that trend inflation was lower pre-pandemic, while both our preferred median and trimmed-mean measures suggest a faster acceleration in trend inflation in 2021. We also find that higher disaggregation marginally weakens the Phillips curve relationship between median CPI inflation and the unemployment gap, though it remains statistically significant.
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Blair, Caitlin. Constructing a PCE-Weighted Consumer Price Index. Cambridge, MA: National Bureau of Economic Research, October 2013. http://dx.doi.org/10.3386/w19582.

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Griffith, Rachel, Ephraim Leibtag, Andrew Leicester, and Aviv Nevo. Timing and Quantity of Consumer Purchases and the Consumer Price Index. Cambridge, MA: National Bureau of Economic Research, October 2008. http://dx.doi.org/10.3386/w14433.

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Shapiro, Matthew, and David Wilcox. Mismeasurement in the Consumer Price Index: An Evaluation. Cambridge, MA: National Bureau of Economic Research, May 1996. http://dx.doi.org/10.3386/w5590.

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Bryan, Michael, and Stephen Cecchetti. The Consumer Price Index as a Measure of Inflation. Cambridge, MA: National Bureau of Economic Research, October 1993. http://dx.doi.org/10.3386/w4505.

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Krueger, Alan, and Aaron Siskind. Assessing the Bias in the Consumer Price Index from Survey Data. Cambridge, MA: National Bureau of Economic Research, March 1998. http://dx.doi.org/10.3386/w6450.

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Frank, Richard, Andrew Hicks, and Ernst Berndt. Auditing the Prescription Drug Consumer Price Index in a Changing Marketplace. Cambridge, MA: National Bureau of Economic Research, September 2022. http://dx.doi.org/10.3386/w30448.

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Haines, Michael. A State and Local Consumer Price Index for the United States in 1890. Cambridge, MA: National Bureau of Economic Research, May 1989. http://dx.doi.org/10.3386/h0002.

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Ganics, Gergely, and María Rodríguez-Moreno. A house price-at-risk model to monitor the downside risk for the Spanish housing market. Madrid: Banco de España, January 2023. http://dx.doi.org/10.53479/29472.

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We present a house price-at-risk (HaR) model that fits the historical developments in the Spanish housing market. By means of quantile regressions we show that a model including quarterly house price growth, a misalignment measure and a consumer confidence index is able to accurately forecast the developments in the Spanish housing market up to two years ahead. We also show how the HaR model can be used to monitor the downside risk.
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Adams, Brian, Lara P. Loewenstein, Hugh Montag, and Randal J. Verbrugge. Disentangling Rent Index Differences: Data, Methods, and Scope. Federal Reserve Bank of Cleveland, December 2022. http://dx.doi.org/10.26509/frbc-wp-202238.

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Prominent rent growth indices often give strikingly different measurements of rent inflation. We create new indices from Bureau of Labor Statistics (BLS) rent microdata using a repeat-rent index methodology and show that this discrepancy is almost entirely explained by differences in rent growth for new tenants relative to the average rent growth for all tenants. Rent inflation for new tenants leads the official BLS rent inflation by four quarters. As rent is the largest component of the consumer price index, this has implications for our understanding of aggregate inflation dynamics and guiding monetary policy. File is available with NTRR and ATRR indices through 2022q3.
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