Statistical Journal of the IAOS最新文献_第4页

Complementary approach to the analysis of countries’ participation in global production networks 分析各国参与全球生产网络情况的补充办法

Statistical Journal of the IAOS Pub Date : 2023-09-12 DOI: 10.3233/sji-220094

Oleksandr Osaulenko, Andriy Krysovatyy, I. Zvarych, Nataliia Reznikova, Oksana Brodovska, Ihor Krysovatyy

{"title":"Complementary approach to the analysis of countries’ participation in global production networks","authors":"Oleksandr Osaulenko, Andriy Krysovatyy, I. Zvarych, Nataliia Reznikova, Oksana Brodovska, Ihor Krysovatyy","doi":"10.3233/sji-220094","DOIUrl":"https://doi.org/10.3233/sji-220094","url":null,"abstract":"The purpose of the article is to explore a complementary approach to the analysis of countries’ participation in global production networks. We have analyzed the methodological aspect from the standpoint of the Micro and Macro theory of international production networks and value chains. In the context of globalization, production networks are actively formed within both individual industries and at the intersectoral level, and they successfully operate not only within limited territories but also at the interstate, interregional and global levels. Therefore, the study of methods for analyzing the participation of countries in global production networks is relevant. The article has used statistical analysis methods. Analytical methods have been used to determine the countries’ leading types of economic activity (fields of specialization, qualitative indicators that characterize each of the industries of the countries). The study of this issue was carried out on the example of the EU countries. One of the methods of analyzing the assessment of bilateral relations of the partner countries’ national economies is complementarity. The article examines the complementarity index as an indicator that determines the trade structure of partner countries. We received a model of the Global map of the International Production Network (nodes of trade) by specific industries, such as Manufacturing, Chemicals and non-metallic mineral products, Rubber and plastics products, computers, electronic and electrical equipment, and transport equipment. To obtain accurate results, we selected specific countries: Germany, the USA, Japan and China, and examined their statistics in two dimensions: gross exports and gross imports, in specifically selected industries.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46493870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning and data augmentation in the proxy means test for poverty targeting 贫困目标代理经济状况调查中的机器学习和数据扩充

Statistical Journal of the IAOS Pub Date : 2023-08-21 DOI: 10.3233/sji-230033

W. Wobcke, Siti Mariyah

{"title":"Machine learning and data augmentation in the proxy means test for poverty targeting","authors":"W. Wobcke, Siti Mariyah","doi":"10.3233/sji-230033","DOIUrl":"https://doi.org/10.3233/sji-230033","url":null,"abstract":"Recent years have seen increased interest in the use of alternative data sources in the definition and production of official statistics and indicators for the UN Sustainable Development Goals. In this paper, we consider the application of data science to the production of official statistics, illustrating our perspective through the use of poverty targeting as an application. We show that machine learning can play a central role in the generation of official statistics, combining a variety of types of data (survey, administrative and alternative). We focus on the problem of poverty targeting using the Proxy Means Test in Indonesia, comparing a number of existing statistical and machine learning methods, then introducing new approaches in the spirit of small area estimation that utilize area-level features and data augmentation at the subdistrict level to develop more refined models at the district level, evaluating the methods on three districts in Indonesia on the problem of estimating 2020 per capita household expenditure using data from 2016–2019. The best performing method, XGBoost, is able to reduce inclusion/exclusion errors on the problem of identifying the poorest 40% of the population in comparison to the commonly used Ridge Regression method by between 4.5% and 13.9% in the districts studied.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41973525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Editorial 社论

Statistical Journal of the IAOS Pub Date : 2023-08-09 DOI: 10.3233/sji-230070

引用次数: 0

Interview with Dominik Rozkrut1 采访Dominik Rozkrut1

Statistical Journal of the IAOS Pub Date : 2023-08-09 DOI: 10.3233/sji-230069

引用次数: 0

The post-pandemic new normal for central bank statistics 大流行后央行统计的新常态

Statistical Journal of the IAOS Pub Date : 2023-08-09 DOI: 10.3233/sji-230050

Saira Jahangir-Abdoelrahman, B. Tissot

引用次数: 0

Accuracy and errors in self-assigned NAICS codes in tax return data 纳税申报资料中自行分配的NAICS代码的准确性和错误

Statistical Journal of the IAOS Pub Date : 2023-08-08 DOI: 10.3233/sji-230035

C. Oehlert

引用次数: 0

The perils of pre-filling: Lessons from the UK’s Annual Survey of Hours and Earning microdata 预填充的危险：英国小时数和赚取微观数据年度调查的经验教训

Statistical Journal of the IAOS Pub Date : 2023-08-02 DOI: 10.3233/sji-230013

D. Whittard, F. Ritchie, Van Phan, A. Bryson, J. Forth, L. Stokes, Carl Singleton

{"title":"The perils of pre-filling: Lessons from the UK’s Annual Survey of Hours and Earning microdata","authors":"D. Whittard, F. Ritchie, Van Phan, A. Bryson, J. Forth, L. Stokes, Carl Singleton","doi":"10.3233/sji-230013","DOIUrl":"https://doi.org/10.3233/sji-230013","url":null,"abstract":"The role of the National Statistical Institution (NSI) is changing, with many now making microdata available to researchers through secure research environments This provides NSIs with an opportunity to benefit from the methodological input from researchers who challenge the data in new ways This article uses the United Kingdom’s Annual Survey of Hours and Earnings (ASHE) to illustrate the point We study whether the use of prefilled forms in ASHE may create inaccurate values in one of the key fields, workplace location, despite there being no direct evidence of it in the data supplied to researchers. We link surveys to examine the hypothesis that employees working for multi-site employers making an ASHE survey submission are more likely to have their work location incorrectly recorded as the respondent fails to correct the work location variable that has been pre-filled. In the short-term, suggestions are made to improve the quality of ASHE microdata, while longer-term we suggest that the burden of collecting additional data could be offset through greater use of electronic data capture. More generally, in a time when statistical budgets are under pressure, this study encourages NSIs to make greater use of the microdata research community to help inform statistical developments.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45980482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

What holds us together? Measuring dimensions of social cohesion in Canada 是什么让我们团结在一起?衡量加拿大社会凝聚力的维度

Statistical Journal of the IAOS Pub Date : 2023-07-30 DOI: 10.3233/sji-230055

Samuel MacIsaac, David Wavrock, G. Schellenberg

{"title":"What holds us together? Measuring dimensions of social cohesion in Canada","authors":"Samuel MacIsaac, David Wavrock, G. Schellenberg","doi":"10.3233/sji-230055","DOIUrl":"https://doi.org/10.3233/sji-230055","url":null,"abstract":"Social cohesion is a multi-dimensional concept referring to social connectedness, or the ‘glue’ that connects members of a society through bonds of solidarity and trust, within and across communities and organizations, and within society at large. The concept of social cohesion continues to garner interest in public and policy circles, perhaps reflecting the intuitive appeal of the concept and the role that cohesion can play in societies’ abilities to respond to challenges, to function effectively, and to support rewarding lives. As a latent concept that is not directly observable or measurable, social cohesion is often measured through key dimensions. In this context, a dimension refers to a constituent part of social cohesion. Using factor analysis and data from Statistics Canada’s 2020 General Social Survey on Social Identity, this study identifies nine key dimensions of social cohesion. Latent class modelling is then used to sort respondents into three latent classes or groups (“Low”, high “Confidence-Belonging” and high “Trust-Participation” cohesion groups) of individuals that share common traits and prioritize certain dimensions of social cohesion. The probabilistic classification of individuals in accordance with latent classes provides valuable insights into social sorting mechanisms and how this extends to cohesiveness within Canadian society.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42245561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How to improve mortality statistics nationally and internationally? 如何改进国家和国际上的死亡率统计?

Statistical Journal of the IAOS Pub Date : 2023-07-01 DOI: 10.3233/sji-230026

M. Gissler, Region Stockholm, Karolinska Institutet

{"title":"How to improve mortality statistics nationally and internationally?","authors":"M. Gissler, Region Stockholm, Karolinska Institutet","doi":"10.3233/sji-230026","DOIUrl":"https://doi.org/10.3233/sji-230026","url":null,"abstract":"Cause-of-death statistics is an essential part of health information system. Finland has collected statistics on causes of death for more than 250 years. Since 1936 medical experts at Statistics Finland has been in charge of the coding. Changes in ICD-classification and coding praxis as well as the use of different standard populations and short-lists hampers time trend analyses and international benchmarking. The five Nordic countries and three Baltic countries has made cause-of-death coding comparisons since 2001. A random sample of death certificates are regularly reviewed. This exercise has demonstrated that national coding systems have not always agreed on the main causes of death. However, there has been a clear trend towards greater agreement, even for specific diagnostic groups, such as cancers, external causes and respiratory conditions. Most of the international data collection is voluntary, but the European Union has adopted a mandatory Regulation to ensure that cause-of-death statistics provide adequate information for all EU Member States to monitor Community actions in the field of public health. Since 2011 the data on causes-of-death have to be provided within 24 months after the end of the reference year. Therefore, causes-of-death statistics at Eurostat is more up-to-date than in other international databases.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47099879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrating big data and survey data for efficient estimation of the median 整合大数据和调查数据，有效估计中值

Statistical Journal of the IAOS Pub Date : 2023-06-28 DOI: 10.3233/sji-230054

Ryan Covey

引用次数: 1