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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: Rivera Drew, Julia A. | Flood, Sarah | Warren, John Robert
Article Type: Research Article
Abstract: Data from the Current Population Survey (CPS) are rarely analyzed in a way that takes advantage of the CPS's longitudinal design. This is mainly because of the technical difficulties associated with linking CPS files across months. In this paper, we …describe the method we are using to create unique identifiers for all CPS person and household records from 1989 onward. These identifiers – available along with CPS basic and supplemental data as part of the on-line Integrated Public Use Microdata Series (IPUMS) – make it dramatically easier to use CPS data for longitudinal research across any number of substantive domains. To facilitate the use of these new longitudinal IPUMS-CPS data, we also outline seven different ways that researchers may choose to link CPS person records across months, and we describe the sample sizes and sample retention rates associated with these seven designs. Finally, we discuss a number of unique methodological challenges that researchers will confront when analyzing data from linked CPS files. Show more
Keywords: Data integration, linking, panel data, Current Population Survey
DOI: 10.3233/JEM-140388
Citation: Journal of Economic and Social Measurement, vol. 39, no. 3, pp. 121-144, 2014
Authors: Phillips, Keith R. | Wang, Jianguo
Article Type: Research Article
Abstract: This paper examines the potential sources behind statistically significant seasonal patterns in the state level seasonally adjusted Local Area Unemployment Statistics (LAUS) released by the U.S. Bureau of Labor Statistics (BLS). We find that these seasonal patterns are likely spurious …and may be due to the pro-rata factors used in benchmarking the states to census regions and national totals. In addition we find that the Henderson 13 filter used by the BLS to smooth the seasonally adjusted state data often makes the data inconsistent with national labor market data. We conclude that the BLS should use seasonally adjusted data when estimating the pro-rata factors used to benchmark states to regional and national totals. Show more
Keywords: Local area unemployment statistics, data revisions, seasonal adjustment, C8
DOI: 10.3233/JEM-140389
Citation: Journal of Economic and Social Measurement, vol. 39, no. 3, pp. 145-152, 2014
Authors: Ulrick, Shawn W.
Article Type: Research Article
Abstract: Disparity in an outcome between two groups is often measured via the coefficient of a dummy variable in a regression that pools both groups. The dummy is interpreted as the disparity. A casual search of the literature in economics and …other social sciences reviews far too many examples of this method to catalog. Unfortunately, if the impact of one (or more) of the control variables differs between the two groups, the measured disparity (i.e., the coefficient on the group dummy) will be biased. We illustrate and derive this bias. Given the bias, we believe that one is better running separate regressions for each group and then implementing decomposition methods or predicting adjusted gaps in outcome (i.e., predicting the but-for world that would exist if the two groups had identical characteristics). Show more
Keywords: Pooling bias, measuring disparity
DOI: 10.3233/JEM-140390
Citation: Journal of Economic and Social Measurement, vol. 39, no. 3, pp. 153-161, 2014
Authors: Grossman, Valerie | Mack, Adrienne | Martínez-García, Enrique
Article Type: Research Article
Abstract: The Database of Global Economic Indicators (DGEI) from the Federal Reserve Bank of Dallas aims to standardize and disseminate economic indicators for policy analysis and scholarly work on the role of globalization. Its main purpose is to offer a broad …perspective on a number of global factors affecting the U.S. economy. DGEI indicators are based on a core sample of 40 countries with aggregates for the rest of the world (ex. the U.S.) and by level of development attainment and openness to trade. DGEI indicators currently include real GDP, industrial production (IP), Purchasing Managers Index (PMI), merchandise exports and imports, headline CPI, core CPI (ex. food and energy), PPI/WPI inflation, nominal and real exchange rates, and short-term interest rates. Here we describe our methodology to transform and combine different time series, for temporal and cross-country aggregation, and to highlight the importance of using representative data in international macroeconomics research. Our paper makes a related contribution to the literature by providing a formal assessment of conventional interpolation methods used to adjust the data frequency. A selection of the DGEI-derived global indicators – to be updated monthly – can be accessed at the following URL: http://www.dallasfed.org/institute/dgei/index.cfm. Show more
Keywords: Aggregation methods, interpolation methods, globalization
DOI: 10.3233/JEM-140391
Citation: Journal of Economic and Social Measurement, vol. 39, no. 3, pp. 163-197, 2014
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