OECD Statistics Working Papers最新文献

{"title":"Recent trends in transport and insurance costs and estimates at disaggregated product level","authors":"","doi":"10.1787/b5dbab02-en","DOIUrl":"https://doi.org/10.1787/b5dbab02-en","url":null,"abstract":"","PeriodicalId":196193,"journal":{"name":"OECD Statistics Working Papers","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124600655","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}

{"title":"Using unit value indices as proxies for international merchandise trade prices","authors":"","doi":"10.1787/27a5abd7-en","DOIUrl":"https://doi.org/10.1787/27a5abd7-en","url":null,"abstract":"","PeriodicalId":196193,"journal":{"name":"OECD Statistics Working Papers","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115449560","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}

{"title":"Estimating regional house price levels","authors":"","doi":"10.1787/b9fec1b2-en","DOIUrl":"https://doi.org/10.1787/b9fec1b2-en","url":null,"abstract":"","PeriodicalId":196193,"journal":{"name":"OECD Statistics Working Papers","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115373877","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}

{"title":"Inequalities in emerging economies","authors":"Costantino Balestra, Ana Llena-Nozal, F. Murtin, Elena Tosetto, B. Arnaud","doi":"10.1787/6C0DB7FB-EN","DOIUrl":"https://doi.org/10.1787/6C0DB7FB-EN","url":null,"abstract":"The paper describes inequality trends in selected emerging economies (Brazil, Colombia, Costa Rica, China, India, Indonesia and South Africa) in a range of monetary (i.e. income) and non-monetary dimensions of people’s life (i.e. education, health status, employment and subjective well-being). Inequalities are analysed not only in terms of overall dispersion, but also as gaps between population groups defined by specific characteristics (i.e. sex, age, educational attainment and place of living). To the extent made possible by the nature of available data, measures of income inequality for these emerging countries, as well as for 7 Latin American countries (Bolivia, Dominic Republic, Ecuador, Panama, Paraguay, Peru and Uruguay), are based on concepts and definitions similar to those used by the OECD for its member countries. All the emerging economies covered in the paper show levels of income inequality higher than in the five most unequal OECD countries, while the picture is more mixed when it comes to inequalities in other dimensions of people’s well-being. An annex complements the analysis by presenting an assessment of the quality of the available data on income distribution for the emerging countries covered in the paper.","PeriodicalId":196193,"journal":{"name":"OECD Statistics Working Papers","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122663310","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}

{"title":"International productivity gaps","authors":"A. Ward, M. Zinni, Pascal Marianna","doi":"10.1787/5B43C728-EN","DOIUrl":"https://doi.org/10.1787/5B43C728-EN","url":null,"abstract":"Cross-country differences in the measurement of labour input contribute to observed productivity gaps across countries. In most countries, labour force surveys (LFS) form a primary source of information for employment related statistics, such as persons employed, employees and hours worked. However, because the coverage of LFS does not fully align with the coverage of activities used to estimate GDP, additional adjustments relying on complementary sources, such as administrative or business statistics, are often applied to bridge conceptual differences, and in many countries, the use of these sources is often preferred to LFS data. Evidence from the 2018 OECD/Eurostat national accounts labour input survey shows that the adjustments made to align measures of labour input with the corresponding measures of production according to the domestic concept, vary considerably across countries, with many countries making no adjustments, in particular, for the measurement of hours worked. This paper demonstrates that countries making no adjustments to average hours worked measures extracted from the original source, such as self-reported hours actually worked in the LFS, appear to systematically over-estimate labour input and, so, under-estimate labour productivity levels. To illustrate the size of this bias, for this group of countries, the paper adopts a simplified component method that introduces a series of explicit adjustments on working time using information available in LFS and complementary sources. The results point to a reduction in relative productivity gaps of around 10 percentage points in many countries compared to current estimates. Although future releases of OECD productivity (levels) statistics will incorporate these changes, it is important to stress that these estimates will only be used as a stop-gap while countries making no, or minimal adjustments, work to leverage all available data sources to produce average hours worked estimates that align with the national accounts domestic concept and that address self-reporting bias; which is the paper’s principal recommendation for those countries that currently make no or only partial adjustments. Indeed, many EU member states, coordinated by Eurostat, are already moving in this direction, with ESA 2010 derogations set to expire by 2020.","PeriodicalId":196193,"journal":{"name":"OECD Statistics Working Papers","volume":"328 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122639546","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}

{"title":"Towards global SEEA Air Emission Accounts","authors":"F. Flachenecker, Emmanuelle Guidetti, Pierre-Alain Pionnier","doi":"10.1787/7D88DFDD-EN","DOIUrl":"https://doi.org/10.1787/7D88DFDD-EN","url":null,"abstract":"This paper describes and evaluates the OECD methodology to estimate Air Emission Accounts (AEAs) for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), in line with the System of Environmental Economic Accounting (SEEA).","PeriodicalId":196193,"journal":{"name":"OECD Statistics Working Papers","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128208172","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}

{"title":"A long-term perspective on the development experience of emerging and industrialised economies","authors":"A. Rijpma, J. L. Zanden, Marco Mira d’Ercole","doi":"10.1787/AD930641-EN","DOIUrl":"https://doi.org/10.1787/AD930641-EN","url":null,"abstract":"This paper describes development patterns beyond GDP in a long-term historical perspective. It revisits the discussion on the goals of development in light of the current discussions on ‘Beyond GDP’, provides evidence on GDP and well-being outcomes since 1820 in a broad range of developing and emerging countries, and compares the experience of early industrialising countries and more recently emerging ones.","PeriodicalId":196193,"journal":{"name":"OECD Statistics Working Papers","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126729375","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}

{"title":"Diversity statistics in the OECD","authors":"Costantino Balestra, L. Fleischer","doi":"10.1787/89BAE654-EN","DOIUrl":"https://doi.org/10.1787/89BAE654-EN","url":null,"abstract":"Data on ethnic, racial and indigenous identity can help render certain minorities statistically visible, and expose potential discrimination and inequalities. This paper systematically reviews diversity data collection practices in OECD countries and selected key partners and identifies three common challenges: the legal treatment of ‘sensitive’ data and concerns around privacy; the use of different data sources for different policy purposes; and issues of comparability over time since identities are dynamic and multiple constructs. When relevant, recommendations and best practices to improve diversity data are put forward. These include: expanding the collection of data on ethnic and racial identities where legal frameworks permit; ensuring the representation of hard-to-reach populations such as indigenous communities; developing national diversity statistical standards to standardise information and allow linking data across sources; raising the timeliness and policy relevance of diversity data by including questions in both regular sample surveys and population censuses; and involving communities in the data collection process.","PeriodicalId":196193,"journal":{"name":"OECD Statistics Working Papers","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130914689","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}

{"title":"Measuring the impact of businesses on people’s well-being and sustainability","authors":"Michal Shinwell, Efrat Shamir","doi":"10.1787/51837366-EN","DOIUrl":"https://doi.org/10.1787/51837366-EN","url":null,"abstract":"Businesses have a significant impact on people’s economic and social conditions, as well as on environmental outcomes. This paper presents an overview of the various kinds of initiatives aimed at measuring or reporting on business’ impact, or certain aspects of it. It shows that despite the proliferation of information and frameworks to measure these impacts, there is currently no common understanding and practice on how to assess the performance of businesses in different social and environmental areas. Building on the OECD’s work on measuring well-being at the national level, the paper aims at better understanding how businesses can impact people’s well-being and sustainability. It contributes to, and complements, other initiatives undertaken by the OECD on responsible business conduct and inclusive growth. This analysis is a first attempt at extending to businesses the approach used by the Organisation to assess and benchmark the well-being performance of countries and sub-national regions, in view of creating a common language and improving the quality, comparability, and coherence of information on the impact of businesses on societal progress and people’s life.","PeriodicalId":196193,"journal":{"name":"OECD Statistics Working Papers","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123348530","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}

{"title":"Policy use of well-being metrics","authors":"Carrie Exton, Michal Shinwell","doi":"10.1787/d98eb8ed-en","DOIUrl":"https://doi.org/10.1787/d98eb8ed-en","url":null,"abstract":"The last decade has seen major advances in the measurement of well-being in national statistics – but what are governments doing to incorporate these metrics and frameworks into policy decision making? This paper describes the progress made in many countries on measuring well-being at a national level, and the mechanisms being developed to mainstream both concepts and evidence on well-being into policy settings. In all cases, countries are adopting a multidimensional approach to the measurement of well-being, and several initiatives have been informed by extensive public consultation processes. For seven countries, detailed case studies in the Annex describe the development and implementation of policy mechanisms for integrating well-being evidence: Ecuador, France, Italy, New Zealand, Scotland, Sweden, and the United Kingdom. The paper finds that well-being evidence is applied at several different stages of the policy cycle, from strategic analysis and prioritization to evaluations of policy interventions. In most cases these initiatives are only a few years old, and institutional support will be vital for the durability of these mechanisms over time and through different political cycles.","PeriodicalId":196193,"journal":{"name":"OECD Statistics Working Papers","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128215340","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}