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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: Mirzaei Abbasabadi, Hamed | Ghaemi Asl, Mahdi
Article Type: Research Article
Abstract: This article aims at investigating the significant higher education expansion in the Islamic Republic of Iran during 2005–2015 period through employing the production function of higher education. Avoiding simultaneity and selection problems in the presence of shocks, we have used a novel method from industrial organization discipline introduced by Rovigatti and Mollisi [1 ] – which is officially offered embeded in a Stata ® module – by providing different production function estimators (Olley-Pakes, Levinsohn-Petrin, and Wooldridge) using provincial data on Iran. Our empirical results reveal that physical capital is the most critical determinant of higher education graduates. …The results also uncover some important facts about the contribution of academic staff to the process of graduation. Compared to other conventional estimation methods, we also provide evidence on the superiority of this innovative method, which is far beyond its original context. Show more
Keywords: Higher education, production function, productivity shocks, control function
DOI: 10.3233/JEM-200470
Citation: Journal of Economic and Social Measurement, vol. 45, no. 1, pp. 1-64, 2020
Authors: Fagereng, Andreas | Holm, Martin Blomhoff | Torstensen, Kjersti Næss
Article Type: Research Article
Abstract: We provide a new estimate of household-level housing wealth in Norway between 1993 and 2015 using an ensemble machine learning method on housing transaction data. The new housing wealth measure is an improvement over existing data sources for two reasons. First, the model outperforms previously applied regression models in out-of-sample prediction precision. Second, we extend the sample of estimated housing wealth by including cooperative units, non-id apartments, and cabins.
Keywords: Machine learning, housing wealth, house prices
DOI: 10.3233/JEM-200471
Citation: Journal of Economic and Social Measurement, vol. 45, no. 1, pp. 65-81, 2020
Authors: Menezes, Paula | Pastoris, Fausto | Picon-Aguilar, Carmen | Schmitz, Martin | Silva, Nuno | Tissot, Bruno
Article Type: Research Article
Abstract: Globalisation is posing important challenges to external statistics, which have been reinforced in recent decades by rapid digital innovation, the complexity and limited transparency of multinational corporate structures, and the increased importance of global financial centres. Examples of such challenges include the fragmentation of global production chains and the changing nature of foreign direct investment. One fundamental question is whether the multipurpose analytical tool provided by external statistics should be simply adapted or radically transformed to address these issues. The experience of central banks shows that a number of alternative ways can be effectively developed in the medium term to …adapt the current external statistics framework, especially by: collecting supplementary data; enhancing the infrastructure supporting compilation; focusing the analysis on large and global corporate groups; presenting more granular data for the aggregates currently compiled; and revisiting the concept of foreign direct investment. Show more
Keywords: Globalisation, foreign direct investment, multinational enterprises, public policy, international statistical standards
DOI: 10.3233/JEM-200472
Citation: Journal of Economic and Social Measurement, vol. 45, no. 1, pp. 83-102, 2020
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