The Value Of Buildings And Structures For Permafrost Damage Prediction: The Case Of Eastern Russian Arctic

The relevance of the study lay in the need to obtain reliable information on the possible economic consequences of changing geocryological conditions in the Russian Arctic, to find methods for preventing (reducing) potential damage, increasing the safety of the population and economy in the areas of the highest geocryological risks, and ensuring balanced socio-economic development in the Russian Arctic permafrost zone for the long term. The study aimed to assess the cost of fixed assets, including their most vulnerable part – buildings and structures (case study: municipalities of the Russian Arctic Asian sector). Economic sectoral structure was evaluated in accordance with the Russian Standard Industrial Classification of Economic Activities using primary statistical data – closed data from companies accounting reports. The work used statistical, cartographic, and visual-graphic methods, as well as methods for analyzing spatial information and microeconomic data. According to calculations, the Russian Arctic Asian sector concentrates the fixed assets of commercial companies with a total value of about 14.8 trillion rubles, including buildings and structures worth 10.7 trillion rubles. The obtained calculated data can be used in modeling the directions of state policy in the field of climate change adaptation and territory protection from natural hazards.

Measuring the ICT Sector in the Digital Economy

The article addresses the problem of measuring the Information and Communication Technology (ICT) sector and its relationship to the digital economy as defined in the OECD «Guidelines for Supply-Use Tables for the Digital Economy». Analysis of various concepts of the digital economy shows that the ICT sector is its key element. It is stressed that, in line with the OECD recommendations, the measurement of the digital economy should be based on the SNA satellite account, the core element of which are the Digital Supply-Use Tables (Digital SUTs). This approach enables to reflect most fully within a single statistical model integration of all phases of digital products (goods and services) circulation in the national economy.It is noted that the construction of ICT Supply-Use Tables (SUTs) is a critical self-contained task, as it provides a measurement framework for both digital (regardless of the model to be adopted) and (more broadly) information economy.It is stressed that the ability to capture the use of ICT products as well as the cost of their production depends significantly on the identification and valuation of digital products and industries in the Digital SUTs. The identification of such industries is now a major challenge because of the lack of separate activities in the existing industrial classifications that are characteristic for their constituent units.The article concludes with a presentation of the pilot estimates of ICT Sector SUTs core indicators obtained by the authors at the Economic Statistics Centre of Excellence, HSE University. The contribution of the sector to the GDP of the Russian Federation is analysed and its inter-sectoral linkages, both on the demand and supply side, are assessed. It is concluded that the full implementation of the Digital SUTs depends on the inclusion in the new International Standard Industrial Classification (ISIC) the additions necessary to identify and evaluate digital products and industries.

Frequency of Anti-Sars-Cov-2 Antibodies in Various Occupational Sectors in an Industrialized Area of Northern Italy from May to October 2020

The results of a voluntary screening campaign for the presence of anti-SARS-CoV-2 serum antibodies are presented, performed on workers in the highly industrialized province of Modena in northern Italy in the period 18 May–5 October 2020. The employment activities of the subjects that tested positive for anti-SARS-CoV-2 IgM and/or IgG antibodies were determined and classified using the International Standard Industrial Classification of All Economic Activities (ISIC). The distribution across different sectors was compared to the proportion of workers employed in the same sectors in the province of Modena as a whole. Workers with anti-SARS-CoV-2 serum antibodies were mainly employed in manufacturing (60%), trade (12%), transportation (9%), scientific and technical activities (5%), and arts, entertainment and recreation activities (4.5%). Within the manufacturing sector, a cluster of workers with positive serological tests was observed in the meat processing sector, confirming recent data showing a possible increased risk of SARS-CoV-2 infection in these workers.

An artificial intelligence-enabled industry classification and its interpretation

PurposeTo overcome the shortcomings of traditional industry classification systems such as the Standard Industrial Classification Standard Industrial Classification, North American Industry Classification System North American Industry Classification System, and Global Industry Classification Standard Global Industry Classification Standard, the authors explore industry classifications using machine learning methods as an application of interpretable artificial intelligence (AI).Design/methodology/approachThe authors propose a text-based industry classification combined with a machine learning technique by extracting distinguishable features from business descriptions in financial reports. The proposed method can reduce the dimensions of word vectors to avoid the curse of dimensionality when measuring the similarities of firms.FindingsUsing the proposed method, the sample firms form clusters of distinctive industries, thus overcoming the limitations of existing classifications. The method also clarifies industry boundaries based on lower-dimensional information. The graphical closeness between industries can reflect the industry-level relationship as well as the closeness between individual firms.Originality/valueThe authors’ work contributes to the industry classification literature by empirically investigating the effectiveness of machine learning methods. The text mining method resolves issues concerning the timeliness of traditional industry classifications by capturing new information in annual reports. In addition, the authors’ approach can solve the computing concerns of high dimensionality.

Accessibility to health care facilities in Montreal Island: an application of relative accessibility indicators from the perspective of senior and non-senior residents

Background Geographical access to health care facilities is known to influence health services usage. As societies age, accessibility to health care becomes an increasingly acute public health concern. It is known that seniors tend to have lower mobility levels, and it is possible that this may negatively affect their ability to reach facilities and services. Therefore, it becomes important to examine the mobility situation of seniors vis-a-vis the spatial distribution of health care facilities, to identify areas where accessibility is low and interventions may be required. Methods Accessibility is implemented using a cumulative opportunities measure. Instead of assuming a fixed bandwidth (i.e. a distance threshold) for measuring accessibility, in this paper the bandwidth is defined using model-based estimates of average trip length. Average trip length is an all-purpose indicator of individual mobility and geographical reach. Adoption of a spatial modelling approach allows us to tailor these estimates of travel behaviour to specific locations and person profiles. Replacing a fixed bandwidth with these estimates permits us to calculate customized location- and person-based accessibility measures that allow inter-personal as well as geographical comparisons. Data The case study is Montreal Island. Geo-coded travel behaviour data, specifically average trip length, and relevant traveller's attributes are obtained from the Montreal Household Travel Survey. These data are complemented with information from the Census. Health care facilities, also geo-coded, are extracted from a comprehensive business point database. Health care facilities are selected based on Standard Industrial Classification codes 8011-21 (Medical Doctors and Dentists). Results Model-based estimates of average trip length show that travel behaviour varies widely across space. With the exception of seniors in the downtown area, older residents of Montreal Island tend to be significantly less mobile than people of other age cohorts. The combination of average trip length estimates with the spatial distribution of health care facilities indicates that despite being more mobile, suburban residents tend to have lower levels of accessibility compared to central city residents. The effect is more marked for seniors. Furthermore, the results indicate that accessibility calculated using a fixed bandwidth would produce patterns of exposure to health care facilities that would be difficult to achieve for suburban seniors given actual mobility patterns. Conclusions The analysis shows large disparities in accessibility between seniors and non-seniors, between urban and suburban seniors, and between vehicle owning and non-owning seniors. This research was concerned with potential accessibility levels. Follow up research could consider the results reported here to select case studies of actual access and usage of health care facilities, and related health outcomes.

Accessibility to health care facilities in Montreal Island: an application of relative accessibility indicators from the perspective of senior and non-senior residents

Background Geographical access to health care facilities is known to influence health services usage. As societies age, accessibility to health care becomes an increasingly acute public health concern. It is known that seniors tend to have lower mobility levels, and it is possible that this may negatively affect their ability to reach facilities and services. Therefore, it becomes important to examine the mobility situation of seniors vis-a-vis the spatial distribution of health care facilities, to identify areas where accessibility is low and interventions may be required. Methods Accessibility is implemented using a cumulative opportunities measure. Instead of assuming a fixed bandwidth (i.e. a distance threshold) for measuring accessibility, in this paper the bandwidth is defined using model-based estimates of average trip length. Average trip length is an all-purpose indicator of individual mobility and geographical reach. Adoption of a spatial modelling approach allows us to tailor these estimates of travel behaviour to specific locations and person profiles. Replacing a fixed bandwidth with these estimates permits us to calculate customized location- and person-based accessibility measures that allow inter-personal as well as geographical comparisons. Data The case study is Montreal Island. Geo-coded travel behaviour data, specifically average trip length, and relevant traveller's attributes are obtained from the Montreal Household Travel Survey. These data are complemented with information from the Census. Health care facilities, also geo-coded, are extracted from a comprehensive business point database. Health care facilities are selected based on Standard Industrial Classification codes 8011-21 (Medical Doctors and Dentists). Results Model-based estimates of average trip length show that travel behaviour varies widely across space. With the exception of seniors in the downtown area, older residents of Montreal Island tend to be significantly less mobile than people of other age cohorts. The combination of average trip length estimates with the spatial distribution of health care facilities indicates that despite being more mobile, suburban residents tend to have lower levels of accessibility compared to central city residents. The effect is more marked for seniors. Furthermore, the results indicate that accessibility calculated using a fixed bandwidth would produce patterns of exposure to health care facilities that would be difficult to achieve for suburban seniors given actual mobility patterns. Conclusions The analysis shows large disparities in accessibility between seniors and non-seniors, between urban and suburban seniors, and between vehicle owning and non-owning seniors. This research was concerned with potential accessibility levels. Follow up research could consider the results reported here to select case studies of actual access and usage of health care facilities, and related health outcomes.

UNEXPLAINED WAGE GAPS IN THE TRADABLE AND NONTRADABLE SECTORS: CROSS-SECTIONAL EVIDENCE BY GENDER IN BOLIVIA

This document analyzes the gender wage gap between in tradable and non-tradable sectors. The tradable sector is defined by the value of exports and imports in an industry based on the four-digit codes of the International Standard Industrial Classification. Based on Gary Becker's work, in an economy prone to discrimination against women, the document proposes a model from which discrimination is possible if companies generate supra-normal profits. These benefits will be determined by market power, which in turn depends on the number of companies participating in the industry, so under the assumption that tradable sectors are directly influenced by international trade and with the possibility of greater competition, this competition will generate a trend towards normal benefits, making it impossible to finance discrimination against women, so the wage gender gap should be lower in tradable than non-tradable sectors. Using the traditional Oaxaca-Blinder decomposition and the Oaxaca-Blinder decomposition with Recentered Influence Function (RIF) regressions for the 2013 Household Survey, we find that unexplained wage differences against women are significantly lower in the tradable sector, suggesting that the impact of international trade on the tradable sector helps to reduce the gender wage gap in Bolivia.

APPROACHES TO THE CLASSIFICATION OF TRADE FLOWS IN THE ANALYSIS OF THE STRUCTURE OF COMMODITY EXPORT

The quality of the analysis of the structure of merchandise exports depends on the groups of trade flows, according to which the study is carried out, therefore, the choice of the classification on the basis of which the analytical study of the export structure is carried out can give answers regarding the choice of the further direction of development of foreign trade. The article discusses the main approaches to the classification of trade flows, identifies their features, advantages and disadvantages. It has been determined that the most common of these are the Standard International Trade Classification (SITC), Lall classification used by the United Nations Conference on Trade and Development (UNCTADstat) and the International Standard Industrial Classification of All Economic Activities (ISGC) or The International Standard Industrial Classification of All Economic Activities (ISIC). The national classification of trade flows includes the Ukrainian Classification of Goods for Foreign Economic Activity (UKT FEA), compiled on the basis of the Harmonized System of Description and Coding of Goods and the Combined Nomenclature of the European Union (used in 207 countries), which promotes the closest relationship between foreign trade statistics and production statistics. Different classifications of trade flows are based on different approaches and different classification features. On the one hand, each classification should cover all groups of goods, on the other hand, show the quality component of exports. The Lall classification, which takes into account the technological complexity of exported goods, is most consistent with these two requirements. This classification is based on the available indicators of technological activity in production. It corresponds to the concept of most analysts regarding the technological rating of manufactured products. The success of a country's export directly depends on the quality of exported goods, therefore, the analysis of the structure of merchandise exports should be based on approaches that take this indicator into account.