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Price: EUR 125.00The Journal of Economic and Social Measurement (JESM) is a quarterly journal that is concerned with the investigation of all aspects of production, distribution and use of economic and other societal statistical data, and with the use of computers in that context. JESM publishes articles that consider the statistical methodology of economic and social science measurements. It is concerned with the methods and problems of data distribution, including the design and implementation of data base systems and, more generally, computer software and hardware for distributing and accessing statistical data files. Its focus on computer software also includes the valuation of algorithms and their implementation, assessing the degree to which particular algorithms may yield more or less accurate computed results. It addresses the technical and even legal problems of the collection and use of data, legislation and administrative actions affecting government produced or distributed data files, and similar topics.
The journal serves as a forum for the exchange of information and views between data producers and users. In addition, it considers the various uses to which statistical data may be put, particularly to the degree that these uses illustrate or affect the properties of the data. The data considered in JESM are usually economic or social, as mentioned, but this is not a requirement; the editorial policies of JESM do not place a priori restrictions upon the data that might be considered within individual articles. Furthermore, there are no limitations concerning the source of the data.
Authors: Ikudo, Akina | Lane, Julia I. | Staudt, Joseph | Weinberg, Bruce A.
Article Type: Research Article
Abstract: Characterizing people’s occupations is important for both policy and research. However, as large scale administrative records are increasingly being used to describe labor market activity, it will become important to find new automated approaches to describing occupations. We apply new machine learning techniques to new sources of data and investigate the potential of using algorithms to classify occupations. We find that job titles are both inherently noisy and inconsistent across organizations, but a subset of them can be assigned algorithmically, with little impact on accuracy.
Keywords: Machine learning, occupations, UMETRICS, administrative data
DOI: 10.3233/JEM-190463
Citation: Journal of Economic and Social Measurement, vol. 44, no. 2-3, pp. 57-87, 2019
Authors: Felettigh, Alberto | Giordano, Claire
Article Type: Research Article
Abstract: A country’s price competitiveness is generally proxied by the real effective exchange rate of its currency. In this article we present a novel three-market breakdown (domestic, euro-area and non-euro area markets) of this measure, with an application to the four main euro-area countries. Price-competitiveness developments are indeed found to be heterogeneous across markets, thereby confirming the usefulness of this decomposition. In particular, we find that in the 1999–2018 period only Germany recorded comparable (large) gains in both euro and non-euro area markets. France posted a larger gain, and Spain marked a smaller loss, in euro-area markets; conversely, Italy’s mild improvement …was greater in non-euro area markets. Finally, competitiveness in the domestic market and that in non-euro area markets are found to be the main, equally important, drivers of overall developments since 1999 in Italy and in Germany. Show more
Keywords: Price-competitiveness indicators, real effective exchange rates, producer prices, destination markets, import competition
DOI: 10.3233/JEM-190466
Citation: Journal of Economic and Social Measurement, vol. 44, no. 2-3, pp. 89-116, 2019
Authors: Hurd, Michael D. | Meijer, Erik | Moldoff, Michael | Rohwedder, Susann
Article Type: Research Article
Abstract: Survey measures of household wealth often incorporate measurement error. The resulting excess variability in the first difference in wealth makes meaningful statistical inference difficult on changes in household-level wealth. We study the effects of two methods intended to reduce this problem: Asset verification confronts respondents with large discrepancies between wealth reports from the current wave and from the previous wave. Cross-wave imputation uses adjacent wave information in the imputation procedures for missing data. In the U.S. Health and Retirement Study, the corrections from asset verification substantially reduced wave-to-wave changes in wealth. The cross-wave imputations also reduced variation, but …to a lesser extent. Show more
Keywords: Wealth measurement, imputation, panel data, survey design
DOI: 10.3233/JEM-190465
Citation: Journal of Economic and Social Measurement, vol. 44, no. 2-3, pp. 117-139, 2019
Authors: Uriarte, Juan I. | Ramírez Muñoz de Toro, Gonzalo R. | Larrosa, Juan M.C.
Article Type: Research Article
Abstract: We describe a case of web scraping data-based price indices implemented in a mid-size city in a moderate inflationary country. Full consumer price (CPI) and construction cost (CCI) indices were implemented for an entire city obtaining efficient results compared to statistics using traditional data collection methods. We state that web scraping combined with big data techniques will allow estimating more individualized and efficient metrics comparable in quality to official statistics. Web scraping technologies empower civil society and small research groups alike by allowing them gather and interpret socioeconomic data. It also helps to create new dimensions of analysis by allowing …changes in frequency and focus on specific groups of products and services. Show more
Keywords: Big data applications, heterogeneous data sources, web scrapping, inflation, Argentina
DOI: 10.3233/JEM-190464
Citation: Journal of Economic and Social Measurement, vol. 44, no. 2-3, pp. 141-159, 2019
Authors: Kposowa, Augustine | Baker, Jack | Swanson, David A.
Article Type: Research Article
Abstract: The Infant Mortality Rate (IMR) is an important population health statistic often used as one of the indicators of the health status of a nation. In many countries lacking adequate vital registration systems, sample methods are used to estimate IMRs. However, evaluations of this approach are rare and the literature contains no assessments of the stochastic uncertainty underlying these estimated IMRs. Stochastic uncertainty reflects the fact that even where the underlying IMR is constant in a small population over time, there is a likelihood of yearly fluctuation in its empirical observations even if it is measured from a complete count …of the events of interest. In this study a method is presented that can be used to assess this stochastic uncertainty. We use the country of Ghana as a case study for this purpose. The method, a beta-binomial model, is described, tested for validity, and illustrated using 2014 sample-based estimates of IMR for 13 sample regions in Ghana. As such, the approach we described regarding the revision of sample-based IMR estimates is aimed at taking into account of the stochastic uncertainty while preserving the information concerning the uncertainty due to sampling. In applying the method to Ghana, we find that the sample-based IMR estimates perform well in accounting for stochastic uncertainty and could be applied elsewhere. Show more
Keywords: Representational data, estimate, Beta Binomial model, validity
DOI: 10.3233/JEM-190462
Citation: Journal of Economic and Social Measurement, vol. 44, no. 2-3, pp. 161-175, 2019
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