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Artykuły w czasopismach na temat "Consumer price indexes – Data processing"
Saad, Ammar, Ruitao Zhang i Ying Xia. "The Policy Analysis Matrix (PAM): Comparative Advantage of China’s Wheat Crop Production 2017". Journal of Agricultural Science 11, nr 17 (15.10.2019): 150. http://dx.doi.org/10.5539/jas.v11n17p150.
Pełny tekst źródłaAsano, Seki, i Eduardo P. S. Fiuza. "Estimation of the Brazilian Consumer Demand System". Brazilian Review of Econometrics 23, nr 2 (2.11.2003): 255. http://dx.doi.org/10.12660/bre.v23n22003.2726.
Pełny tekst źródłaFaryna, Oleksandr, Oleksandr Talavera i Tetiana Yukhymenko. "What Drives the Difference between Online and Official Price Indexes?" Visnyk of the National Bank of Ukraine, nr 243 (29.03.2018): 21–30. http://dx.doi.org/10.26531/vnbu2018.243.021.
Pełny tekst źródłaKrsinich, Frances. "The FEWS Index: Fixed Effects with a Window Splice". Journal of Official Statistics 32, nr 2 (1.06.2016): 375–404. http://dx.doi.org/10.1515/jos-2016-0021.
Pełny tekst źródłaJuszczak, 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.
Pełny tekst źródłaBessonov, Vladimir. "What Opportunities Do New Technologies Bring About for Price Statistics?" Russian Journal of Money and Finance 80, nr 1 (marzec 2021): 120–26. http://dx.doi.org/10.31477/rjmf.202101.120.
Pełny tekst źródłaCavallo, Alberto, i Roberto Rigobon. "The Billion Prices Project: Using Online Prices for Measurement and Research". Journal of Economic Perspectives 30, nr 2 (1.05.2016): 151–78. http://dx.doi.org/10.1257/jep.30.2.151.
Pełny tekst źródłaSaputra, Igo Septa, Zulfanetti Zulfanetti i Jaya Kusuma Edi. "Analisis faktor-faktor yang mempengaruhi Tingkat Partisipasi Angkatan Kerja (TPAK) di Provinsi Jambi". e-Jurnal Ekonomi Sumberdaya dan Lingkungan 8, nr 2 (1.07.2019): 68–81. http://dx.doi.org/10.22437/jels.v8i2.11984.
Pełny tekst źródłaCheng, Andy Wui Wing, i 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, nr 02 (18.05.2017): 1750014. http://dx.doi.org/10.1142/s021909151750014x.
Pełny tekst źródłaGreenlees, John S., i Robert McClelland. "Does Quality Adjustment Matter for Technologically Stable Products? An Application to the CPI for Food". American Economic Review 101, nr 3 (1.05.2011): 200–205. http://dx.doi.org/10.1257/aer.101.3.200.
Pełny tekst źródłaRozprawy doktorskie na temat "Consumer price indexes – Data processing"
Heinze, Christian [Verfasser], Harry [Akademischer Betreuer] Haupt i 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.
Pełny tekst źródłaIvancic, Lorraine Economics Australian School of Business UNSW. "Scanner data and the construction of price indices". 2007. http://handle.unsw.edu.au/1959.4/40782.
Pełny tekst źródłaKgantsi, 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.
Pełny tekst źródłaThe 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.
Książki na temat "Consumer price indexes – Data processing"
missing], [name. Scanner data and price indexes. Chicago, IL: University of Chicago Press, 2002.
Znajdź pełny tekst źródłaKrueger, Alan B. Assessing bias in the Consumer Price Index from survey data. Cambridge, MA: National Bureau of Economic Research, 1998.
Znajdź pełny tekst źródłaRamcharan, 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.
Znajdź pełny tekst źródłaOffice, 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.
Znajdź pełny tekst źródła(Editor), Robert C. Feenstra, i Matthew D. Shapiro (Editor), red. Scanner Data and Price Indexes (National Bureau of Economic Research Studies in Income and Wealth). University Of Chicago Press, 2002.
Znajdź pełny tekst źródłaConsumer price index revision: Housing data collection manual. Wyd. 3. [Washington, D.C.?]: The Bureau, 1997.
Znajdź pełny tekst źródłaMacroeconomic data: A user's guide. Wyd. 3. Richmond, VA: Federal Reserve Bank of Richmond, 1994.
Znajdź pełny tekst źródłaH, Webb Roy, i Federal Reserve Bank of Richmond., red. Macroeconomic data: A user's guide. Wyd. 2. Richmond, Va: Federal Reserve Bank of Richmond, 1991.
Znajdź pełny tekst źródłaUnited States. Bureau of Labor Statistics, red. Housing data collection manual. [Washington, D.C.]: U.S. Department of Labor, Bureau of Labor Statistics, 2004.
Znajdź pełny tekst źródłaStreszczenia konferencji na temat "Consumer price indexes – Data processing"
Karcıoğlu, Reşat, Muhammet Özcan i Ensar Ağırman. "The Relationship of Petroleum Price and BIST Sector Indexes". W International Conference on Eurasian Economies. Eurasian Economists Association, 2017. http://dx.doi.org/10.36880/c08.01878.
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