Journal articles: 'Price indexes – Data processing'

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Cottle, David, and Euan Fleming. "Do price premiums for wool characteristics vary for different end products, processing routes and fibre diameter categories?" Animal Production Science 56, no. 12 (2016): 2146. http://dx.doi.org/10.1071/an14744.

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No Australian wool price hedonic studies have separated auction data into different end product-processing groups (PPR) on the basis of all fibre attributes that affect the suitability of wool sale lots for PPR. This study was conducted to assess: (1) whether including information about PPR groupings is more useful in understanding price than clustering by broad fibre diameter (FD) categories, and (2) if the ‘noise’ of macroeconomic effects on price can be reduced by using a clean price relative to the market indicator (RelPrice) formula or a log RelPrice formula compared with log price or clean price. Hedonic models using data derived from 369 918 Australian auction sale lots in 2010–2011 were estimated for these four dependent price variables. Linear FD models predicted less of price’s variance than quadratic or exponential models. Segmenting wool sale lots into 10 PPR before wool price analyses was found to increase the proportion of price variance explained and thus be worthwhile. The change in price with a change in FD, staple length and staple strength differs significantly between PPR. Calculating RelPrice or log RelPrice appears a better price parameter than clean price or log price. Comparing the RelPrice and clean price models, the mean absolute percentage errors were 6.3% and 16.2%, respectively. The differences in price sensitivity to FD, staple length and staple strength across PPR implies a complex set of price-setting mechanisms for wool as different users place different values on these wool properties. These price-setting mechanisms need to be incorporated in hedonic models for agricultural products that possess this characteristic. The wool price premiums can be used to estimate relative economic values when constructing sheep breeding selection indexes and can help determine the most profitable wool clip preparation strategies.

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Mendoza Urdiales, Román Alejandro, Andrés García-Medina, and José Antonio Nuñez Mora. "Measuring information flux between social media and stock prices with Transfer Entropy." PLOS ONE 16, no. 9 (September 23, 2021): e0257686. http://dx.doi.org/10.1371/journal.pone.0257686.

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Transfer Entropy was applied to analyze the correlations and flow of information between 200,500 tweets and 23 of the largest capitalized companies during 6 years along the period 2013-2018. The set of tweets were obtained applying a text mining algorithm and classified according to daily date and company mentioned. We proposed the construction of a Sentiment Index applying a Natural Processing Language algorithm and structuring the sentiment polarity for each data set. Bootstrapped Simulations of Transfer Entropy were performed between stock prices and Sentiment Indexes. The results of the Transfer Entropy simulations show a clear information flux between general public opinion and companies’ stock prices. There is a considerable amount of information flowing from general opinion to stock prices, even between different Sentiment Indexes. Our results suggest a deep relationship between general public opinion and stock prices. This is important for trading strategies and the information release policies for each company.

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Antoniuk, Olena, Natalya Kuzyk, Iryna Zhurakovska, Roman Sydorenko, and Liudmyla Sakhno. "The role of «BIG FOUR» auditing firms in the public procurement market in Ukraine." Independent Journal of Management & Production 11, no. 9 (November 1, 2020): 2483. http://dx.doi.org/10.14807/ijmp.v11i9.1432.

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The authors conducted a study aimed to identify the role of «Big Four» («Big 4») audit firms in the public procurement market in Ukraine.The purpose of the article is to answer the questions: whether Ukraine is in a general trend of most countries in the concentration of audit market; what is the share of revenues of the «Big Four» audit firms in the performance of audit services in the public procurement system in Ukraine. First of all, in order to get answers to these questions, the authors conducted a study of the main trends in the development of the «Big Four» companies in Ukraine. It was found that the characteristic competitive environment in the market of audit services, the impact on competitiveness of pricing policy and regulatory requirements, relating to the acquisition of audit services by public sector entities through a public procurement system "ProZorro". An element of price regulation and compliance with the transparent conditions of the competitive environment is the participation of audit firms in the public procurement system. As a result of processing data on procurement of audit services for the period 2008-2019, the authors calculated key indicators that characterize the concentration of the audit market. Based on the data on the amount of remuneration for various types of audit services using the public procurement system "ProZorro", aspects of pricing policy and the role of the companies of the "Big Four" in the market were established. The values indexes indicate that the companies of the «Big 4» do not have a complete monopoly in the segment of procurement of audit services, having certain dominant positions in some years, and the indexes indicate a trend towards effective competition in the audit services market in Ukraine.

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Tarrío-Saavedra, Javier, Elena Orois, and Salvador Naya. "Estudio métrico sobre la actividad investigadora usando el software libre R: el caso del sistema universitario gallego." Investigación Bibliotecológica: archivonomía, bibliotecología e información, sp1 (January 19, 2018): 221. http://dx.doi.org/10.22201/iibi.24488321xe.2017.nesp1.57891.

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Este trabajo representa una nueva alternativa para el estudio, clasificación y comparación de la producción científica de centros de investigación, utilizando las funciones de tratamiento de datos del paquete Citan del software estadístico R. En particular, se muestra el análisis bibliométrico de las publicaciones de las universidades de A Coruña, Santiago de Compostela y Vigo, en el periodo 2000-2011, recopiladas por la base de datos Scopus. Entre las técnicas usadas se aplicaron modelos de Lotka y Price, modelización no paramétrica y paramétrica de los datos, así como el cálculo y análisis de indicadores de la cantidad y calidad de la producción científica, los índices h y g, y otros menosconocidos como los rp1, lp, Ge1, Ge5 y Slp1. Como novedad, se propone una variante del índice h (hh) que define el grupo de investigadores que forman la élitemás productiva de cada universidad y estima su calidad investigadora.AbstractThis work represents a new alternative for the study, classification and comparison of the scientific production corresponding to research entities. It consists on the application of statistical data processing functions available in the R software’s Citan package. In particular, the bibliometric study of publications of universities of A Coruña, Santiago de Compostela and Vigo, in the period 2000-2011, compiled by the Scopus database. The study was conducted using the statistical analysis of the data, the application of models of Lotka and Price, nonparametric and parametric modeling (Pareto) of the data, and the calculation and analysis of indicators of the scientific production like the h and g indexes, and others lesser known as rp1, lp, Ge1, Ge5 and Slp1. A novelty consists in a variant of the h index (hh) that defines the group of researchers who are the most productive of each university, the elite, and estimates the researching quality of such representative elites.

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Kőműves, Zsolt, and Viktória Horváthné Petrás. "A sertéshústermelést és -fogyasztást befolyásoló tényezők." Élelmiszer, Táplálkozás és Marketing 13, no. 1 (February 27, 2019): 3–9. http://dx.doi.org/10.33567/etm.2253.

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The decrease in the number of pigs grew to a drastic proportion during the past few decades. before the change of the regime therewere approximately 10 million pigs counted, but today this number is slightly beyond 3 million. The decline in livestock has anegative effect on the competitive position of both this sector and that of other branches of industry as well weakening significantlythe economic importance of the sector. The underlying causes of the process leading to the decline are diverse. to reveal thesolution a versatile analysis of the economic situation is essential, which should be started in the first place by the examination ofthe factors defining the competitiveness of the pig sector. The aim of this work is to reveal and characterize the national capacities,the physical and biological, as well as the social, economic (market) and human factors pointing to the most important differencesat the same time. This study analyzes the efficiency of the chosen farms according to the size of plant, standard of production, technologyand capacity of maintenance. summarizing the farmers’ opinions and the data obtained, it can be stated that farmers in thecurrent situation are satisfied with the buying price as one of the most essential factors of production. however, they emphasizedthe role of prices as a factor of uncertainty. As a result of changing the out-of-date technology considerable improvement could beobserved in the natural indexes. Unfortunately, significant changes should be accomplished in the feasibility of support andfinancing investment. The strict environmental regulations of animal keeping make the operation of farms – mainly of those thatdo not possess arable land – more difficult. reforms would provide relief for the operating farms. The market price regulation ofthe alternative fodder and the existent substitute products could appear as a significant cost efficiency factor during production.Workers with unsuitable education – and often being incompetent –, trade unions operating as false organizations as well as thelack of cooperation with the food processing industry affect the sector sensitively.

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

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

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Oleinik, A. N. "Uses of content analysis in economic sciences: An overview of the current situation and prospects." Voprosy Ekonomiki, no. 4 (April 8, 2021): 79–95. http://dx.doi.org/10.32609/0042-8736-2021-4-79-95.

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The article discusses the status of quantitative and qualitative data in economic sciences, as well as methods for transforming data into information and knowledge. Particular attention is devoted to content analysis as a set of methods for aggregating, processing and analyzing qualitative data; its forms (qualitative, quantitative and mixed methods) and uses by economists. Content analysis appears to be particularly suitable for non-orthodox economists because of their refusal to consider price as the only source of economic information. The content analysis of metadata of articles indexed in Web of Science and eLibrary suggests that Russian economists still have insufficient familiarity with the principles of content analysis and their applications to research compared with their Western counterparts. It is argued that the creation of on-line platforms for content analysis and on-line banks of qualitative data may become a trigger for changing this situation.

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Zulqarnain, Muhammad, Rozaida Ghazali, Muhammad Ghulam Ghouse, Yana Mazwin Mohmad Hassim, and Irfan Javid. "Predicting Financial Prices of Stock Market using Recurrent Convolutional Neural Networks." International Journal of Intelligent Systems and Applications 12, no. 6 (December 8, 2020): 21–32. http://dx.doi.org/10.5815/ijisa.2020.06.02.

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Financial time-series prediction has been long and the most challenging issues in financial market analysis. The deep neural networks is one of the excellent data mining approach has received great attention by researchers in several areas of time-series prediction since last 10 years. “Convolutional neural network (CNN) and recurrent neural network (RNN) models have become the mainstream methods for financial predictions. In this paper, we proposed to combine architectures, which exploit the advantages of CNN and RNN simultaneously, for the prediction of trading signals. Our model is essentially presented to financial time series predicting signals through a CNN layer, and directly fed into a gated recurrent unit (GRU) layer to capture long-term signals dependencies. GRU model perform better in sequential learning tasks and solve the vanishing gradients and exploding issue in standard RNNs. We evaluate our model on three datasets for stock indexes of the Hang Seng Indexes (HSI), the Deutscher Aktienindex (DAX) and the S&P 500 Index range 2008 to 2016, and associate the GRU-CNN based approaches with the existing deep learning models. Experimental results present that the proposed GRU-CNN model obtained the best prediction accuracy 56.2% on HIS dataset, 56.1% on DAX dataset and 56.3% on S&P500 dataset respectively.

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Zhen, Chen, Eric A. Finkelstein, Shawn A. Karns, Ephraim S. Leibtag, and Chenhua Zhang. "Scanner Data‐Based Panel Price Indexes." American Journal of Agricultural Economics 101, no. 1 (June 18, 2018): 311–29. http://dx.doi.org/10.1093/ajae/aay032.

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Bourassa, Steven C., Eva Cantoni, and Martin Hoesli. "Robust hedonic price indexes." International Journal of Housing Markets and Analysis 9, no. 1 (March 7, 2016): 47–65. http://dx.doi.org/10.1108/ijhma-11-2014-0050.

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Purpose – The purpose of this paper is to demonstrate the application of robust techniques to the estimation of hedonic house price indexes. Design/methodology/approach – The authors use simulation analysis to compare an index estimated using ordinary least squares (OLS) with several indexes estimated using robust techniques. The analysis uses sales transactions data from a US city. The authors then explore how robust methods can correct for omitted variables under some circumstances and how they affect the revision problem that occurs when longitudinal hedonic indexes are updated. Findings – Robust methods can resolve missing variable problems in some circumstances and also can substantially reduce the revision problem in longitudinal hedonic indexes. Practical implications – Robust techniques may be preferable to OLS when constructing longitudinal hedonic indexes. Originality/value – This is the first paper to undertake a systematic analysis of the applicability of robust techniques in constructing hedonic house price indexes.

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Melser, Daniel. "Scanner Data Price Indexes: Addressing Some Unresolved Issues." Journal of Business & Economic Statistics 36, no. 3 (June 1, 2017): 516–22. http://dx.doi.org/10.1080/07350015.2016.1218339.

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Bourassa, Steven C., and Martin Hoesli. "High-Frequency House Price Indexes with Scarce Data." Journal of Real Estate Literature 25, no. 1 (January 1, 2017): 207–20. http://dx.doi.org/10.1080/10835547.2017.12090448.

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Nowak, Adam D., and Patrick S. Smith. "Quality-Adjusted House Price Indexes." American Economic Review: Insights 2, no. 3 (September 1, 2020): 339–56. http://dx.doi.org/10.1257/aeri.20190337.

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The constant-quality assumption in repeat-sales house price indexes (HPIs) introduces a significant time-varying attribute bias. The direction, magnitude, and source of the bias varies throughout the market cycle and across metropolitan statistical areas (MSAs). We mitigate the bias using a data-driven textual analysis approach that identifies and includes salient text from real estate agent remarks in the repeat-sales estimation. Absent the text, MSA-level HPIs are biased downward by as much as 7 percent during the financial crisis and upward by as much as 20 percent after the crisis. The geographic concentration of the bias magnifies its effect on local HPIs. (JEL C43, E31, R11, R31)

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Webster, Michael, and Rory C. Tarnow-Mordi. "Decomposing Multilateral Price Indexes into the Contributions of Individual Commodities." Journal of Official Statistics 35, no. 2 (June 1, 2019): 461–86. http://dx.doi.org/10.2478/jos-2019-0020.

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Abstract This article describes methods for decomposing price indexes into contributions from individual commodities, to help understand the influence of each commodity on aggregate price index movements. Previous authors have addressed the decomposition of bilateral price indexes, which aggregate changes in commodity prices from one time period to another. Our focus is the decomposition of multilateral price indexes, which aggregate commodity prices across more than two time periods or countries at once. Multilateral indexes have historically been used for spatial comparisons, and have recently received attention from statistical agencies looking to produce temporal price indexes from large and high frequency price data sets, such as scanner data. Methods for decomposing these indexes are of practical relevance. We present decompositions of three multilateral price indexes. We also review methods proposed by other researchers for extending multilateral indexes without revising previously published index levels, and show how to decompose the extended indexes they produce. Finally, we use a data set of seasonal prices and quantities to illustrate how these decomposition methods can be used to understand the influence of individual commodities on multilateral price index movements, and to shed light on the relationships between various multilateral and extension methods.

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Edronova, V. N. "International digital development indexes: A methodology for data collection, systematization and processing." Regional Economics: Theory and Practice 18, no. 7 (July 16, 2020): 1374–96. http://dx.doi.org/10.24891/re.18.7.1374.

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Subject. This article provides a comprehensive comparative review of the present-day used International Digital Development Indexes of countries and regions. Objectives. The article aims to review and compare the characteristics and methodologies of digitalization indexes developed by international institutions. Methods. For the study, I used a comparative analysis. Results. The article presents an overview of the methods of calculating the largest international indexes and compiling ratings of digital development of countries. It defines the content of the indexes, and describes the characteristics of the digital development of Russia on the basis of major international indexes. Conclusions. The methodology for calculating all international digital development indexes is identical in terms of objectives, methods of forming a primary base, data systematization, and calculation of composite indexes and sub-indexes. An objective assessment of the level and trends of digital development requires a comprehensive analysis of the totality of ratings and an understanding of the methodology for calculating indexes on the basis of which ratings are defined.

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Ramalho, Esmeralda A., Joaquim J. S. Ramalho, and Rui Evangelista. "Combining micro and macro data in hedonic price indexes." Statistical Methods & Applications 26, no. 2 (August 30, 2016): 317–32. http://dx.doi.org/10.1007/s10260-016-0367-6.

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

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

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Ivancic, Lorraine, W. Erwin Diewert, and Kevin J. Fox. "Scanner data, time aggregation and the construction of price indexes." Journal of Econometrics 161, no. 1 (March 2011): 24–35. http://dx.doi.org/10.1016/j.jeconom.2010.09.003.

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de Haan, Jan, and Heymerik A. van der Grient. "Eliminating chain drift in price indexes based on scanner data." Journal of Econometrics 161, no. 1 (March 2011): 36–46. http://dx.doi.org/10.1016/j.jeconom.2010.09.004.

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Horowitz, Stanley, and Bruce Harmon. "Inflation and Price Escalation Adjustments in Estimating Program Cost: F-35 Case Study." Defense Acquisition Research Journal 27, no. 92 (April 1, 2020): 194–217. http://dx.doi.org/10.22594/dau.19-836.27.02.

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Applying price indexes presents a challenge in estimating the costs of new defense systems. An inappropriate price index—one not closely linked to the inputs to the systems being costed—can introduce errors in both development of cost estimating relationships (CER) and in development of out-year budgets. To help cost analysts understand the impacts of different price indexes, this article applies two sets of price indexes to the F-35 program. Using hedonic price indexes derived from CERs, the authors isolate changes in price due to factors other than changes in quality by developing a “Baseline” CER model using data on historical tactical aircraft programs available early in the F-35 program. The focus of the work is to improve estimates of acquisition costs. All the data used in the econometric analysis are acquisition cost data. Better cost estimates should improve projections of budget requirements.

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Fares, Florencia Melisa, Guido Zack, and Ricardo Gabriel Martínez. "Sectoral Price and Quantity Indexes of Argentine Foreign Trade." Lecturas de Economía, no. 93 (July 9, 2020): 297–328. http://dx.doi.org/10.17533/udea.le.n93a338277.

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Argentina does not have a sufficiently complete and developed system of sectoral statistical data on foreign trade. This paper tries to make a contribution showing a methodology to calculate foreign trade indexes, based on unit values obtained from Foreign Trade Consultation System of INDEC. This methodology is applied to the quarterly data of Argentine sectoral imports and exports and its accuracy is shown from the comparison with price indexes published by INDEC (aggregate level) and Brazilian statistical institute (sectoral level). Our indexes show a correlation above 80% and variability close to the benchmark in almost all sectors. Finally, we analyzed the contribution of each sector to foreign trade growth during 1996-2016 using the estimated quantity indexes, something impossible to obtain without the estimated price indexes. Both real exports and imports show a weak growth pace of 2.3% and 2.4% per year, respectively. The leading sectors are Foodstuff industry and Agricultural products in exports, and Motor vehicles and Chemical products in imports for the whole period

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Shimizu, Chihiro, W. Erwin Diewert, Kiyohiko G. Nishimura, and Tsutomu Watanabe. "Estimating quality adjusted commercial property price indexes using Japanese REIT data." Journal of Property Research 32, no. 3 (July 3, 2015): 217–39. http://dx.doi.org/10.1080/09599916.2015.1059875.

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Gu, Wei. "Data Processing and Information Technology with an Iterative Correction Evaluation Model." Advanced Materials Research 978 (June 2014): 201–4. http://dx.doi.org/10.4028/www.scientific.net/amr.978.201.

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In our paper, we used data processing and information technology to build an iterative correction evaluation model.First,we collect the data of college coaches of football, basketball and hockey. Based on the two characteristic indexes of college coaches, such as the basic quality and the competition results, we discuss the characteristic indexes of excellent college coaches and set up two basic models: the one is fuzzy comprehensive evaluation model established by simplified DHFG algorithm and the other is Self-evaluation DEA model built on the hierarchy structure of the evaluation indexes and incompleteness of weight set. Then, the ranking lists can be obtained respectively. After that, we use four combined evaluation methods, such as average value method, Boarda method, Compeland method and fuzzy Boarda method, to combine the results of two basic models above. We establish the iterative correction model and Spearman test is applied until the results satisfy the homogeneity test. Thus, the more accuracy results are gained and the top 5 coaches are picked out more correctly.

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JÜRGERNS, MARCUS, and HANS-J. LENZ. "TREE BASED INDEXES VERSUS BITMAP INDEXES: A PERFORMANCE STUDY." International Journal of Cooperative Information Systems 10, no. 03 (September 2001): 355–76. http://dx.doi.org/10.1142/s0218843001000382.

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Data warehouses are used to store large amounts of data which is often used for On-Line Analytical Processing (OLAP). Short response times are essential for on-line decision support. Common approaches to reach this goal in read-mostly environments are the precomputation of materialized views and the use of index structures. This paper focuses on the use of index structures for supporting fast access to data. The performance of index structures depends on many different parameters. Here, we focus on a set of nine parameters. Two approaches are presented to support the decision making process which index structure should be applied. The first approach is based on classification trees. The second approach uses an aggregation and scatter diagram method. Both approaches are applied to four distinct index structures: a tree-based index structure without aggregated data, a tree-based index structure with aggregated data and two bitmap index structures. This paper presents results of the comparison with both approaches.

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Zeng, Xiang Gui, Ge Ying Lai, Fa Zhao Yi, and Ling Ling Zhang. "GIS Based Spatialization of Population Data in Meijiang River Basin." Applied Mechanics and Materials 295-298 (February 2013): 2378–83. http://dx.doi.org/10.4028/www.scientific.net/amm.295-298.2378.

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This paper used GIS spatial analysis and data processing technologies and multi-source data fusion technology to spatialize the population data of Meijiang river basin. Land use was selected as the index factor and the settlements as the indicative factor. Selected terrain, roads and rivers were the main influencing factors and were further classified into several sub-factors. During the simulation, we first calculated the weight indexes of sub-factors on the settlements distribution and then fused the indexes to calculate the weight indexes of the main factors. Second we calculated the weight indexes of settlements on the population distribution. Last we fused the weight indexes of the main factors and the weight indexes of settlements to obtain the population density indexes of whole region and then generated the 100m×100m resolution raster population density map.

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Silver, Mick, and Brian Graf. "Commercial Property Price Indexes: Problems of Sparse Data, Spatial Spillovers, and Weighting." IMF Working Papers 14, no. 72 (2014): 1. http://dx.doi.org/10.5089/9781484364543.001.

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de Haan, Jan, and Frances Krsinich. "Scanner Data and the Treatment of Quality Change in Nonrevisable Price Indexes." Journal of Business & Economic Statistics 32, no. 3 (July 3, 2014): 341–58. http://dx.doi.org/10.1080/07350015.2014.880059.

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Fox, Kevin J., and Daniel Melser. "Non-Linear Pricing and Price Indexes: Evidence and Implications from Scanner Data." Review of Income and Wealth 60, no. 2 (November 29, 2012): 261–78. http://dx.doi.org/10.1111/roiw.12000.

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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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Li, Pei Lin. "Data Processing and Modelling with Information Technology in Choosing College Best Trainer." Advanced Materials Research 978 (June 2014): 221–25. http://dx.doi.org/10.4028/www.scientific.net/amr.978.221.

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Choosing a good college trainer needs to consider various factors. In the paper, I take advantage of relevant data of the college trainers, and then establish an effective model with information technology to choose the best college trainer. First I collect the data of college trainers of football using information technology. Based on the two characteristic indexes of excellent college trainers, such as the basic quality and the competition results, I discuss the characteristic indexes of excellent college trainers using data processing and set up the model: fuzzy comprehensive evaluation model established by simplified DHFG algorithm. Thus, the results are gained and the top 5 trainers are picked out. Finally, I compare the results with the real ranking on Bleacher Report, and the results prove well.

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Brown, Leonard, and Le Gruenwald. "Tree-Based Indexes for Image Data." Journal of Visual Communication and Image Representation 9, no. 4 (December 1998): 300–313. http://dx.doi.org/10.1006/jvci.1998.0399.

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Mohamed, Mohamed Attia, Manal A. Abdel-Fattah, and Ayman E. Khedr. "Challenges and Recommendations in Big Data Indexing Strategies." International Journal of e-Collaboration 17, no. 2 (April 2021): 22–39. http://dx.doi.org/10.4018/ijec.2021040102.

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Index structures are one of the main strategies for effective data access applied for indexing data. According to expansion of data, traditional indexing strategies on big data meets several challenges that lead to weak performance; they haven't abilities to handle the rapid increase of data in terms of accurate retrieval results and processing time. So, it is necessary to substitute traditional index with another efficient index structure called learned index. Learned index goes to use machine learning models to tackle such issues and achieve more enhancements of processing time and accurate results. In this research, the authors discuss different indexing strategies on big data both traditional and learned indexes, demonstrate the main features of them, perform comparison in terms of its performance, and present big data indexing challenges and solutions. Consequently, the research suggests replacing traditional indexes by dynamic index models, which lead to less processing time and more accurate results taking into consideration specification of hardware used.

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Pan, Chung-Lien, and Yu-Chun Pan. "The Index and Stock Price Synchronicity: Evidence from Taiwan." E3S Web of Conferences 198 (2020): 04029. http://dx.doi.org/10.1051/e3sconf/202019804029.

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Research on stock synchronization has always been a topic of concern to scholars and investors. In the past, the focus was mainly on equity concentration, foreign shareholding, audit quality, and other issues, not including indexes. This article uses the monthly data of the Taiwan Stock Exchange Capital Weighted Stock Index (TAIEX) to solve the problem of the index and stock synchronization. And use the technical theory of the gray system to solve the small sample and uncertain problem. The discovery of the synchronization between these indexes and stock prices may provide investors with sufficient reference to make investment decisions.

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Hill, Robert J., and Michael Scholz. "Can Geospatial Data Improve House Price Indexes? A Hedonic Imputation Approach with Splines." Review of Income and Wealth 64, no. 4 (July 27, 2017): 737–56. http://dx.doi.org/10.1111/roiw.12303.

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Cotterill, Ronald W. "Scanner Data: New Opportunities for Demand and Competitive Strategy Analysis." Agricultural and Resource Economics Review 23, no. 2 (October 1994): 125–39. http://dx.doi.org/10.1017/s1068280500002240.

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This paper reviews prior research by agricultural economists on the demand for food products using scanner data. Thereafter, a differentiated product's oligopoly model with Bertrand price competition is developed and used to specify brand level demand and oligopoly price reaction equations. The model has sufficient detail to estimate brand level price elasticities and price response elasticities which in turn can be used to estimate three indices of market power. The first index estimated is the familiar Rothschild Index. The paper develops estimates two new indexes, the observed index and the Chamberlin quotient for tacit collusion. It concludes with comments on how the proposed method for the measurement of market power in a differentiated oligopoly can be improved.

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Gábor-Tóth, Enikő, and Philip Vermeulen. "Elementary Index Bias: Evidence for the Euro Area from a Large Scanner Dataset." German Economic Review 20, no. 4 (December 1, 2019): e618-e656. http://dx.doi.org/10.1111/geer.12182.

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Abstract We provide evidence on the effect of elementary index choice on inflation measurement in the euro area. Using scanner data for 15,844 individual items from 42 product categories and 10 euro area countries, we compute product category level elementary price indexes using eight different elementary index formulas. Measured inflation outcomes of the different index formulas are compared with the Fisher ideal index to quantify elementary index bias. We have three main findings. First, elementary index bias is quite variable across product categories, countries and index formulas. Second, a comparison of elementary index formulas with and without expenditure weights shows that a shift from price only indexes to expenditure weighted indexes would entail at the product level multiple percentage points differences in measured price changes. And finally, we show that elementary index bias is quantitatively more important than upper level substitution bias.

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Rudzkis, Rimantas, Roma Valkavičienė, and Virmantas Kvedaras. "Prediction of Baltic Sectorial Share Price Indices." Lietuvos statistikos darbai 53, no. 1 (December 20, 2014): 53–59. http://dx.doi.org/10.15388/ljs.2014.13894.

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Extending the research started in [31], the paper uses econometric methods for the short-term forecasting of quarterly values of sector indexes of stock prices from the OMX Baltic stock exchange. The ARMA models and modelling methodology that was used to build the statistical models in the previous paper are now augmented with the algorithms of time series aggregation and identification of special features of the series. Here, the search for informative factors relies on the study of related literature. The specification of models is further tailored using the traditional significance (p-value) analysis of regressors and a cross-validation analysis. The latter is implemented in this paper using the Jack-knife approach. The data period analysed covers the years 2000–2013. The results of the analysis indicate that the inclusion not only of recent autoregressive terms but also of some aggregated characteristics (as certain special features of indexes) improves the precision of forecasting substantially. The calculations were performed using the statistical analysis software SAS.

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Xue, Chao, Yongfeng Ju, Shuguang Li, Qilong Zhou, and Qingqing Liu. "Research on Accurate House Price Analysis by Using GIS Technology and Transport Accessibility: A Case Study of Xi’an, China." Symmetry 12, no. 8 (August 10, 2020): 1329. http://dx.doi.org/10.3390/sym12081329.

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Based on the symmetrical public transportation network data of Xi’an, China obtained by geographic information system (GIS) technology in 2019, three urban public transportation indexes of walking accessibility, bus accessibility, and metro accessibility were established, and a real estate price prediction model was built by using several machine learning algorithms to predict and analysis the housing price in Xi’an, China. Firstly, the symmetrical road network data and real estate property data of Xi’an were collected and preprocessed, secondly, the spatial syntax theory and distance calculation method were applied to establish three indexes of traffic accessibility; finally, taking the house property data and the calculated traffic accessibility indexes as the characteristic index, the real estate price prediction model of Xi’an was constructed by using the random forest algorithm (RF), lightweight gradient lift algorithm (LGBM), and gradient lifting regression tree algorithm (GBDT). The prediction accuracy of the final model is 89.2% and the root-mean-square error is 1761.84. The results show that the accessibility of bus and metro to some extent represent the convenience of public transportation in different areas of urban space. The higher the accessibility index is, the more convenient the traffic is. The real estate price model has high prediction accuracy and can reflect the real situation of urban real estate price. The importance of the three accessibility features to the real estate price prediction model are nearly more than 20%, which indicates that the accessibility of urban public transportation has an important impact on the change of urban real estate price, and the development of urban public transportation plays an important role in the real estate economy.

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

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

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Hall, Anne E. "Adjusting the Measurement of the Output of the Medical Sector for Quality: A Review of the Literature." Medical Care Research and Review 74, no. 6 (August 11, 2016): 639–67. http://dx.doi.org/10.1177/1077558716663388.

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The Bureau of Economic Analysis recently created new price indexes for health care in its health care satellite account and now faces the problem of how to adjust them for quality. I review the literature on this topic and divide the articles that created quality-adjusted price indexes for individual medical conditions into those that use primarily outcomes-based adjustments and those that use only process-based adjustments. Outcomes-based adjustments adjust the indexes based on observed aggregate health outcomes, usually mortality. Process-based adjustments adjust the indexes based on the treatments provided and medical knowledge of their effectiveness. Outcomes-based adjustments are easier to implement, while process-based adjustments are more demanding in terms of data and medical knowledge. In general, the research literature shows adjusting for quality in the measurement of output in the medical sector to be quantitatively important.

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Vitkovskaya, I. S. "SATELLITE DATA PROCESSING ALGORITHM IN THE PROCESS OF FORMATION OF THE TIME SERIES OF VEGETATION INDEXES." Eurasian Physical Technical Journal 18, no. 2 (June 11, 2021): 90–95. http://dx.doi.org/10.31489/2021no2/90-95.

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The diverse spectral indexes computed from the satellite images are used extensively in the world practice of remote sensing of the Earth from space. This approach proved its validity for the satellite monitoring of the underlying terrain, detection of ongoing changes and trends of their dynamic patters. Accumulated prodigious amount of satellite data, the state-of-the-art methods of thematic interpretation gave rise to creation of services providing free access to both images and to image processing results. Notwithstanding the foregoing, in the furtherance of the local and regional scale it turns out that usage of the end products of thematic processing of space information supplied by the known available services was not efficient on all occasions. Consequently, we may need to generate our own archives of the long-term series of satellite indexes. The volume of files containing the digital index matrices computed based on the MODIS satellite low resolution data subject to the complete coverage of the territory of Kazakhstan surpasses 4 Gb. This often results in the delayed computations, and on frequent occasions in infeasibility of computation of a full matrix when the medium specs computers are employed. This article is focused on the satellite data processing algorithm in the process of formation of the time series of vegetation indexes. As a consequence, the multi-year archive of vegetation indexes (over a period of 2001-2020), which provided a basis for trend analysis of the underlying terrain, determination of their future trends and forecasting of their changes was created within the territory of the Republic.

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Kirikkaleli, Dervis, and Ibrahim Darbaz. "The Causal Linkage between Energy Price and Food Price." Energies 14, no. 14 (July 11, 2021): 4182. http://dx.doi.org/10.3390/en14144182.

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This paper aims to reveal the causal relationship between energy prices and food prices and whether this relationship is similar in the food sub-groups forming the food price index used. As food prices more than doubled during the 2008 economic crisis, this relationship has received considerable attention from researchers. Many researches have been conducted to determine the causes and consequences of the 2008 food price crisis. Researches are mainly focused on crude oil and bio-energy in terms of “energy”. This research is not only differentiated by the data used but also by the methodology employed. The study attempts to add new findings to the empirical food price literature by utilizing relatively newly developed methods, namely Toda–Yamamoto causality, Fourier Toda–Yamamoto causality, and spectral BC causality tests. The spectral BC causality test clearly reveals that there is bidirectional causality between the energy price index and food price indexes (grains, other food, and oils) at different frequencies.

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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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Majewska, Agnieszka. "Using Sectoral Indexes to Discount the Exercise Price of Employee Stock Options." Folia Oeconomica Stetinensia 16, no. 1 (December 1, 2016): 174–85. http://dx.doi.org/10.1515/foli-2016-0010.

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Abstract Employee stock options (ESOs) are an instrument in compensating top management of corporations. In the literature, they are described as a variable component of remuneration of a long-term character (Borkowska, 2012). There are six characteristic elements of the ESO: a grant date, the ESO plan duration, employees entitled to receive options, vesting criteria, a vesting period, and an exercise price. The article refers to the exercise price. The remuneration of employees is determined by the option’s intrinsic value, i.e. the difference between the current stock price and the exercise price. This difference affects the costs incurred by a company in relation with their incentive stock option plan. In this connection, the exercise price of stock options needs to be analysed. The literature shows that usually the strike price is equal to the stock market’s value at the time the option is granted. The options issued with an exercise price equal to the market value of the company’s stock on the date of the grant usually lead to at-the-money options. Walker (2009) mentions that almost all options issued by US firms have been such type of options. Hence, the options with exercise prices less than the prices of the underlying assets have been rarely observed. One of the solutions can be discounting the exercise price by using sectoral indexes, which are sensitive to changes on a particular market. The purpose of this paper is to address several aspects of specifying the exercise price in ESOs. The research shows how sector indexes can be used to discount it. Using sectoral indexes in determining the exercise price can partly limit the unreasonably high profits from the ESO. The literature does not provide ready-made formulas of exercise prices based on specific variables. The aim of the research is to present and apply the formula of the exercise prices in which sectoral indices are used to discount. The data are from the Warsaw Stock Exchange (WSE) and include those companies that revealed the information concerning their incentive programs in 1999–2013. The relevant data come from annual reports, current reports, supervisory boards’ resolutions, and press announcements.

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

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

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KEAWPIBAL, Naphat, Ladda PREECHAVEERAKUL, and Sirirut VANICHAYOBON. "Optimizing Range Query Processing for Dual Bitmap Index." Walailak Journal of Science and Technology (WJST) 16, no. 2 (March 26, 2018): 133–42. http://dx.doi.org/10.48048/wjst.2019.4146.

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Bitmap-based indexes are known to be the most effective indexing method for retrieving and answering selective queries in a read-only environment. Various types of encoding bitmap indexes signiﬁcantly improve query time efficiency by utilizing fast Boolean operations directly on the index before retrieving the raw data. In particular, the dual bitmap index improves the performance of equality queries in terms of the space vs. time trade-off. However, the performance of range queries is unsatisfactory. In this paper, an optimizing algorithm is proposed to improve the range query processing for the dual bitmap index. The results of the experiment conducted show that the proposed algorithm, called Dual-simRQ, reduces the number of bitmap vectors scanned and the Boolean operations performed, which impacts the overall performance for range query processing.

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

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

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Štifanić, Daniel, Jelena Musulin, Adrijana Miočević, Sandi Baressi Šegota, Roman Šubić, and Zlatan Car. "Impact of COVID-19 on Forecasting Stock Prices: An Integration of Stationary Wavelet Transform and Bidirectional Long Short-Term Memory." Complexity 2020 (July 20, 2020): 1–12. http://dx.doi.org/10.1155/2020/1846926.

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COVID-19 is an infectious disease that mostly affects the respiratory system. At the time of this research being performed, there were more than 1.4 million cases of COVID-19, and one of the biggest anxieties is not just our health, but our livelihoods, too. In this research, authors investigate the impact of COVID-19 on the global economy, more specifically, the impact of COVID-19 on the financial movement of Crude Oil price and three US stock indexes: DJI, S&P 500, and NASDAQ Composite. The proposed system for predicting commodity and stock prices integrates the stationary wavelet transform (SWT) and bidirectional long short-term memory (BDLSTM) networks. Firstly, SWT is used to decompose the data into approximation and detail coefficients. After decomposition, data of Crude Oil price and stock market indexes along with COVID-19 confirmed cases were used as input variables for future price movement forecasting. As a result, the proposed system BDLSTM + WT-ADA achieved satisfactory results in terms of five-day Crude Oil price forecast.

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Miyano, Takaya, and Kenichi Tatsumi. "Determining anomalous dynamic patterns in price indexes of the London Metal Exchange by data synchronization." Physica A: Statistical Mechanics and its Applications 391, no. 22 (November 2012): 5500–5511. http://dx.doi.org/10.1016/j.physa.2012.05.068.

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Bokhari, Sheharyar, and David Geltner. "Estimating Real Estate Price Movements for High Frequency Tradable Indexes in a Scarce Data Environment." Journal of Real Estate Finance and Economics 45, no. 2 (July 22, 2010): 522–43. http://dx.doi.org/10.1007/s11146-010-9261-4.

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Journal articles on the topic 'Price indexes – Data processing'

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