Bibliografie tematiche / Consumer price index

Letteratura scientifica selezionata sul tema "Consumer price index"

Autore: Grafiati
Pubblicato: 4 giugno 2021
Ultima modifica: 26 luglio 2024

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Articoli di riviste sul tema "Consumer price index"

1

Ghodke, Mohammad, e Purushottam Giri. "Consumer Price Index (CPI) – Types & Sources". Indian Journal of Community Health 35, n. 4 (31 dicembre 2023): 520–25. http://dx.doi.org/10.47203/ijch.2023.v35i04.020.

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The consumer price index is an important parameter to measure inflation. It reflects the relative changes in the prices of goods and services and its effect on inflation. These changes affect the real purchasing power of consumers and their welfare. It is used for regulation of wages, calculation of dearness allowance for workers and employees and for policy formations. Consumer price indices are of different types. Each type has its own significance. It is often difficult to identify the sources of consumer price indices and their specific uses.
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2

Wulandari, Sari, e Muhammad Dani Habra. "Analisis Perkembangan Indeks Harga Konsumen di Kota Medan". Journal of Economic, Bussines and Accounting (COSTING) 3, n. 2 (9 maggio 2020): 412–18. http://dx.doi.org/10.31539/costing.v3i2.1162.

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The Consumer Price Index (CPI) is one of the important economic indicators that can provide information about the development of prices of goods and services (commodities) paid by consumers or the public especially the city community. This study aims to analyze the Development of the Consumer Price Index in Medan City. The benefits of this research are a description of the fluctuations in commodity prices for basic needs of the community at the level of consumers or retail traders. This type of research is descriptive qualitative. The subject in this study is the Central Statistics Agency and the object in this study is the Consumer Price Index through seven groups of household expenditure in 2018-2019. The results showed that the development of price indices in Medan City tends to fluctuate from seven types of household expenditure groups. During the January-December 2019 period the highest inflation of the seven types of expenditure was foodstuffs. Keywords: Consumer Price Index, Inflation Rate
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3

Imron, M., Wika Dianita Utami, Hani Khaulasari e Firman Armunanto. "ARIMA MODEL OF OUTLIER DETECTION FOR FORECASTING CONSUMER PRICE INDEX (CPI)". BAREKENG: Jurnal Ilmu Matematika dan Terapan 16, n. 4 (15 dicembre 2022): 1259–70. http://dx.doi.org/10.30598/barekengvol16iss4pp1259-1270.

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The Consumer Price Index (CPI) is a indicator used by Badan Pusat Statistik (BPS) which describes the average change in the prices paid by urban consumers for a market basket of consumer goods and services in a certain period. The case on Consumer Price Index (CPI) of Probolinggo City, if the Consumer Price Index (CPI) increase then describe inflation occurs and conversely. The Consumer Price Index (CPI) of Probolinggo City increase is not fixed. This study is to forecast the Consumer Price Index (CPI) that the results can be used as one of the considerations in carrying out economic development in the future. Research focused on the data of Consumer Price Index (CPI) of Probolinggo City from January 2014 to April 2022. Methodology implemented in this study is Autoregressive Integrated Moving Average (ARIMA). Result show that ARIMA without an outlier was the best model for predicting Consumer Price Index (CPI) of Probolinggo City for the next 8 months. This model shows the value of MAPE is . The value of forecasting results in each month has decreased and increased not so significantly where in May 2022 the forecasting value was 108,391 then in June 2022 the forecasting value became 108,411 and so on until December 2022 the forecasting results using ARIMA model of 107,845.
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Hill, Peter. "Consumer price index manual". Statistical Journal of the United Nations Economic Commission for Europe 21, n. 2 (18 maggio 2005): 87–93. http://dx.doi.org/10.3233/sju-2004-21201.

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5

Gage, Rob, e Patrick Jackman. "Chained Consumer Price Index". Industrial Relations 42, n. 2 (aprile 2003): 299–302. http://dx.doi.org/10.1111/1468-232x.00291.

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6

Hodgson, James. "The Consumer Price Index". Relations industrielles 8, n. 1 (25 febbraio 2014): 101–8. http://dx.doi.org/10.7202/1022980ar.

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Summary A brief study of the new index called Consumer Price Index (C .P. I.) which will replace the Cost of Living Index (C. L. I.). In order to make such a change, specialists were called in to work on this for nearly three years. During the survey begun in 1948, the most modern methods of sampling were used. Instead of 1935-1939, the base period chosen was 1949. In view of the increasing importance of the index in the labour world, the author analyses briefly the changes made in the former index and emphasizes the problems involved in such a changeover.
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7

Białek, Jacek. "Proposition of a hybrid price index formula for the Consumer Price Index measurement". Equilibrium 15, n. 4 (20 dicembre 2020): 697–716. http://dx.doi.org/10.24136/eq.2020.030.

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Research background: The Consumer Price Index (CPI) is a basic, commonly accepted and used measure of inflation. The index is a proxy for changes in the costs of household consumption and it assumes constant consumer utility. In practice, most statistical agencies use the Laspeyres price index to measure the CPI. The Laspeyres index does not take into account movements in the structure of consumption which may be consumers' response to price changes during a given time interval. As a consequence, the Laspeyres index can suffer from commodity substitution bias. The Fisher index is perceived as the best proxy for the COLI but it needs data on consumption from both the base and research period. As a consequence, there is a practical need to look for a proxy of the Fisher price index which does not use current expenditure shares as weights. Purpose of the article: The general purpose of the article is to present a hybrid price index, the idea of which is based on the Young and Lowe indices. The particular aim of the paper is to discuss the usefulness of its special case with weights based on correlations between prices and quantities. Methods: A theoretical background for the hybrid price index (and its geometric version) is constructed with the Lowe and Young price indices used as a starting point. In the empirical study, scanner data on milk, sugar, coffee and rice are utilized to show that the hybrid index can be a good proxy for the Fisher index, although it does not use the expenditures from the research period. Findings & Value added: The empirical and theoretical considerations con-firm the hybrid nature of the proposed index, i.e. in a special case it forms the convex combination of the Young and Lowe indices. This study points out the usefulness of the proposed price index in the CPI measurement, especially when the target index is the Fisher formula. The proposed general hybrid price index formula is a new one in the price index theory. The proposed system of weights, which is based on the correlations between prices and quantities, is a novel idea in the price index methodology.
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8

Chun, Hae-Jung. "The Influence of Consumer Sentiment on Housing Prices by Region: Using the VARX Model". Korea Association Of Real Estate Law 27, n. 3 (30 settembre 2023): 29–42. http://dx.doi.org/10.32989/rel.2023.27.3.29.

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In order to examine the influence of consumer sentiment on housing prices by region, this study conducted an empirical analysis using the VARX model, including apartment sales price index, consumer sentiment index, apartment construction permit performance, corporate bond yield rate, and consumer price index. As a result of the VARX model estimation, the change rate of the housing consumer sentiment index has a significant positive (+) effect on the change rate of apartment sales prices, the change rate of the corporate bond yield has a negative (-), and the change rate of the consumer price index has a positive (+) effect in all regions. Looking at the coefficient values, it was found that consumer sentiment, corporate bond yield, and consumer price index had a greater impact on the rate of change in apartment sales prices in Seoul than in other regions. As a result of the impulse response analysis, the change rate of apartment sales price showed a positive (+) response to the shock of the change rate of housing consumption sentiment in all regions. The change rate of apartment sales price showed a weakly negative (-) response to the shock of the apartment construction permit performance in Seoul, was converged with a positive (+) response in nationwide and in non-metropolitan areas. It was found that the impact of the change rate of housing consumption sentiment in Seoul has a greater impact on the change rate of apartment sales prices than in other regions.
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9

Bonnarens, Joseph. "The Consumer Price Index and Prescription Drug Prices:". Journal of Research in Pharmaceutical Economics 9, n. 2 (3 novembre 1998): 71–81. http://dx.doi.org/10.1300/j063v09n02_06.

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10

Boskin, Michael J., Ellen R. Dulberger, Robert J. Gordon, Zvi Griliches e Dale W. Jorgenson. "Consumer Prices, the Consumer Price Index, and the Cost of Living". Journal of Economic Perspectives 12, n. 1 (1 febbraio 1998): 3–26. http://dx.doi.org/10.1257/jep.12.1.3.

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After presenting major findings and recommendations, the CPI Commission reiterates the estimate of a 1.1 percentage point per annum upward bias. It rejects the contention that the BLS already makes substantial corrections for quality change; that quality improvements and new products accrue only to the rich; and that procedures to make more extensive quality adjustments, valuations of new products, and adjustments for commodity and outlet substitution are impractical. The bias in the CPI can be sharply reduced, as the authors detail in this paper. Coauthors are Ellen R. Dulberger, Robert J. Gordon, Zvi Griliches, and Dale W. Jorgenson.
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Tesi sul tema "Consumer price index"

1

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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2

Chan, Ka-lin Karen, e 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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3

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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4

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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5

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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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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7

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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Akaakar, Alexandra A. "OIL DEPENDENCY AND NATIONAL FOOD SECURITY: A CASE FOR NIGERIA". OpenSIUC, 2019. https://opensiuc.lib.siu.edu/theses/2482.

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Food insecurity is a condition of insufficient access to quality nutritious food; it is often rooted in shocks that interrupt the food production/distribution system in an area. Amidst the capabilities of Nigeria's agricultural system, the number of households across Nigeria experiencing food shortages has increased rapidly. The main reason for this increase were price shocks. This incident highlighted a huge vulnerability in Nigeria's food system, the vulnerability to price shocks. Incidences such as poverty and conflicts magnify the frequency of food insecurity. The ability to reduce vulnerabilities while addressing existing issues in food production and supply depends on a stable economy and innovative policy. As a major oil exporter, Nigeria's economy is affected by oil price fluctuations. This paper analyses the extent of the effect and how such volatility could increase vulnerability in the food system. The analysis in this treatise examines economic and agricultural factors to identify trends that negatively affect Nigeria's current food system.. Oil prices were significant in explaining variation in food price shocks and Gross Domestic Product (GDP). Food price shocks are one of the symptoms of economic downturns. Agricultural innovation, and economic policies need to be formulated to prevent such shocks in the future. Given the dependency of economic performance on oil prices, a major move would be to diversify the Nigerian economy; with adequate attention being paid to agriculture.
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Lopes, Luciana Teagno. "A rigidez nominal de preços na cidade de São Paulo: evidências baseadas em microdados do índice de preços ao consumidor da FIPE". Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/12/12140/tde-13012009-165431/.

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Esta pesquisa investiga o comportamento de determinação de preços na cidade de São Paulo. São analisadas mais de seis milhões de cotações do índice de preços ao consumidor da FIPE. Os principais resultados são: (i) a freqüência média de mudança dos preços é de 32,35% ao mês; (ii) os preços duram em média 2,56 meses; (iii) há grande heterogeneidade entre produtos quanto ao comportamento de mudança dos preços; (iv) 40% das mudanças de preço são para baixo; (v) as mudanças de preço possuem magnitude considerável; (vi) a freqüência de mudança dos preços exibe padrões sazonais em alguns grupos; (vii) a freqüência de mudança dos preços respondeu às incertezas eleitorais de 2002 em alguns grupos; (viii) as funções de risco comum são decrescentes e apresentam picos na duração correspondente a doze meses para alguns subgrupos, e (ix) o risco de mudança dos preços responde ao índice inflacionário para aproximadamente 70% dos subgrupos.
This research investigates the price-setting behavior in São Paulo city. We analyze more than six millions of consumer price index quotes produced by FIPE. The main results are: (i) the average frequency of price change is 32,35% per month; (ii) the prices remain unchanged on average for 2,56 months; (iii) there is a large degree of product heterogeneity related to the behavior of price change; (iv) 40% of price changes are price decreases; (v) the magnitude of price changes is large; (vi) the frequency of price change exhibits seasonal patterns for some groups; (vii) for some groups the frequency of price change was affected by 2002 elections; (viii) the baseline hazard functions are downward-sloping with 12 month spikes for some subgroups, and (ix) the hazard of price change responds to inflation for almost 70% of the subgroups.
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Yuba, Tania Yuka. "Evolução dos preços relativos e da estrutura de gastos com alimentos no município de São Paulo: uma aplicação do banco de dados do IPC-FIPE de 1939 a 2010". Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/89/89131/tde-14092012-140908/.

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Introdução: A análise das principais tendências sobre consumo de alimentos tem apontado para a diminuição do consumo de alimentos in natura e o aumento do consumo de produtos industrializados. Este padrão de consumo pode levar à deficiências nutricionais e propiciar o surgimento de doenças crônicas não transmissíveis como a obesidade, dislipidemias e hipertensão. Os hábitos de consumo alimentar são afetados por uma grande variedade de fatores em que se destacam os econômicos, como preços relativos de alimentos e renda da população. Analisar a evolução dos preços relativos pode nos fornecer subsídios que possibilitam visualizar as tendências da relação entre os grupos alimentares. Objetivos: Analisar a evolução dos preços relativos dos grupos de alimentos a partir da elaboração dos números-índices dos preços relativos para o período de 1939 a 2010 com a utilização do banco de dados do Índice de Preços ao Consumidor da Fundação Instituto de Pesquisas Econômicas (IPC/FIPE). Metodologia: Para analisar a evolução dos preços relativos, foram utilizados o banco de preços da FIPE e as estruturas de ponderação da FIPE (1939-1988) e do IBGE (1989-2010), desagregadas por classe de renda a partir de 1972. O banco de preços foi organizado, sua consistência foi testada e os preços foram deflacionados pelo IPC/FIPE. Os preços relativos foram calculados e depois agregados por grupo alimentar. Por fim, o índice de preços foi calculado por duas fórmulas: Laspeyres e Konüs-Byushgens. Resultados: Comparou-se o índice geral da alimentação com os índices de cada grupo alimentar, e é possível notar que os grupos de gorduras, óleos, condimentos, açúcares e alimentos processados tiveram um seguimento de queda, por outro lado o índice dos alimentos in natura como frutas e verduras tiveram um ligeiro aumento. Os grupos de cereais, farinhas e massas e os grupos de carnes, leite e ovos tiveram uma tendência mais estável. Conclusão: A evolução dos preços relativos dos alimentos indica uma tendência desfavorável para uma alimentação saudável.
Introduction: Analyses of major trends on food consumption point out decreasing fresh food consumption and increasing processed food consumption. Processed food may cause nutritional deficiencies and ease onset of chronic non communicable diseases such as obesity, dyslipidemia and hypertension. Food consumption habits are affected by many factors, and the ones that stand out are the economic factors such as food relative price and population income. Studying the evolution of relative price may give us support to visualize the relationship trends among food groups. Objectives: Analyze the evolution of relative price of food groups by calculating the index-numbers of relative prices from 1939 to 2010 using the Consumer Price Index database from the Fundação Instituto de Pesquisas Econômicas (Institute for Economic Research Foundation) (IPC/FIPE). Methodology: To analyze the evolution of relative price, we used FIPE´s price database and also the weight structure from FIPE (1939-1988) and from IBGE (Brazilian Institute of Geography and Statistics) (1989-2010), which were separated by income class since 1972. Price database was arranged, it´s consistency was tested and prices were deflated by IPC/FIPE. Relative prices were calculated and then associated by food group. Ultimately, price index was calculated according to: Laspeyres and Konüs-Byushgens. Results: When comparing total food index against indexes of each food group we noticed that the groups of fat, oil, spices, sugars and sweets and processed food showed decreased indexes whereas fresh foods such as fruits and vegetables showed swift increased indexes. Grain, flour and pasta groups along with meat, milk and egg groups showed a steadier trend. Conclusion: The evolution of relative price of food points out an unfavorable trend toward healthy eating.
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Più fonti

Libri sul tema "Consumer price index"

1

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

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Kenya National Bureau of Statistics., a cura di. The 2008 consumer price index: CPI. Nairobi: Kenya National Bureau of Statistics, 2008.

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Consumer price index apparel manual. Washington, D.C.?]: U.S. Department of Labor, Bureau of Labor Statistics, 1991.

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Office, International Labour, a cura di. Consumer price index manual: Theory and practice. Geneva: International Labour Office, 2004.

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5

Kenya. Central Bureau of Statistics., a cura di. The new Kenyan consumer price index: Guide for producing the consumer price index. Nairobi, Kenya: Central Bureau of Statistics, Ministry of Finance & Planning, 2002.

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6

Revising the Consumer Price Index. [Washington, D.C.]: Bureau of Labor Statistics, U.S. Dept. of Labor, 1986.

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7

United States. Bureau of Labor Statistics, a cura di. Consumer price index apparel manual. [Washington, D.C.?]: U.S. Dept. of Labor, Bureau of Labor Statistics, 1986.

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8

United States. Bureau of Labor Statistics., a cura di. Consumer price index: Reference checklists. [Washington, D.C.?]: Bureau of Labor Statistics, U.S. Dept. of Labor, 1993.

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United States. Bureau of Labor Statistics, a cura di. Consumer price index: Reference checklists. [Washington, D.C.?]: Bureau of Labor Statistics, U.S. Dept. of Labor, 1993.

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United States. Bureau of Labor Statistics, a cura di. Consumer price index apparel manual. [Washington, D.C.?]: U.S. Dept. of Labor, Bureau of Labor Statistics, 1991.

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Capitoli di libri sul tema "Consumer price index"

1

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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Leaver, Sylvia, e 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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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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Ge, Li, e 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 e 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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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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Momo, Shampa Islam, Md Riajuliislam e Rubaiya Hafiz. "Forecasting of Inflation Rate Contingent on Consumer Price Index: Machine Learning Approach". In Intelligent Computing and Innovation on Data Science, 137–44. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3153-5_17.

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Wang, Hongjie, e Weigang Zhao. "ARIMA Model Estimated by Particle Swarm Optimization Algorithm for Consumer Price Index Forecasting". In Artificial Intelligence and Computational Intelligence, 48–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-05253-8_6.

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Atti di convegni sul tema "Consumer price index"

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Pillay, Khuneswari Gopal, Tivya Ravie e 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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Yalman, İlkay Noyan, e 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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Hou, Keyu, Shunxun Li, Jingjing Li, Wei Xu, Rui Wang e 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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Witharana, W. W. S. K., U. K. D. T. N. Udugama, P. M. R. Fernando, H. M. H. Kaumadi e 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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Jia, Lizhai, e Weidong Li. "Cointegration analysis on the relationship between Consumer Price Index and electricity price". In 2010 2nd IEEE International Conference on Information and Financial Engineering (ICIFE). IEEE, 2010. http://dx.doi.org/10.1109/icife.2010.5609273.

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Dongdong, Weng. "The Consumer Price Index Forecast Based on ARIMA Model". In 2010 WASE International Conference on Information Engineering (ICIE 2010). IEEE, 2010. http://dx.doi.org/10.1109/icie.2010.79.

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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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Budiastuti, Intan Ari, Supeno Mardi Susiki Nugroho e Mochamad Hariadi. "Predicting daily consumer price index using support vector regression method". In 2017 15th International Conference on Quality in Research (QiR): International Symposium on Electrical and Computer Engineering. IEEE, 2017. http://dx.doi.org/10.1109/qir.2017.8168445.

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Du, Yulin. "Prediction of consumer price index based on RBF neural network". In 2018 Chinese Control And Decision Conference (CCDC). IEEE, 2018. http://dx.doi.org/10.1109/ccdc.2018.8407612.

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Tengiz, Yusuf Ziya, e 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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Rapporti di organizzazioni sul tema "Consumer price index"

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Blair, Caitlin. Constructing a PCE-Weighted Consumer Price Index. Cambridge, MA: National Bureau of Economic Research, ottobre 2013. http://dx.doi.org/10.3386/w19582.

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

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

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

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

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Frank, Richard, Andrew Hicks e Ernst Berndt. Auditing the Prescription Drug Consumer Price Index in a Changing Marketplace. Cambridge, MA: National Bureau of Economic Research, settembre 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, maggio 1989. http://dx.doi.org/10.3386/h0002.

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Adams, Brian, Lara P. Loewenstein, Hugh Montag e Randal J. Verbrugge. Disentangling Rent Index Differences: Data, Methods, and Scope. Federal Reserve Bank of Cleveland, dicembre 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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Ganics, Gergely, e María Rodríguez-Moreno. A house price-at-risk model to monitor the downside risk for the Spanish housing market. Madrid: Banco de España, gennaio 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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Ambaw, Dessie, Madhavi Pundit, Arief Ramayandi e Nicholas Sim. Real Exchange Rate Misalignment and Business Cycle Fluctuations in Asia and the Pacific. Asian Development Bank, marzo 2022. http://dx.doi.org/10.22617/wps220066-2.

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This paper investigates the impact of real exchange rate (RER) misalignment on business cycles among 22 economies in Asia and the Pacific from 1990 to 2018. It employs a panel vector autoregression involving consumer price index (CPI) inflation, output gap, short-term interest rate, and RER misalignment. The authors find that RER overvaluation may lead to a reduction in CPI inflation and short-term interest rate. The study also illustrates Asia and the Pacific’s heterogeneity as evidenced by the output gaps of some economies, particularly in Southeast Asia, which are shown to be more susceptible to RER misalignment shocks.
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