Statistical Journal of the IAOS - Volume 36, issue 4

Article Type: Editorial

DOI: 10.3233/SJI-200774

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 841-847, 2020

Article Type: Other

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 849-, 2020

Authors: Fu, Haishan | Hereward, Mark | MacFeely, Steve | Me, Angela | Wilmoth, John

Article Type: Research Article

DOI: 10.3233/SJI-200759

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 851-860, 2020

Authors: Castano, Jairo

Article Type: Research Article

Abstract: A review of the status of censuses of agriculture in 150 countries and territories shows that the impact of COVID-19 has not discriminated between developed and developing countries. However, some countries have fared better than others when faced with the challenges posed by the pandemic. Earlier improvements in national statistical systems, a wide range of ICT solutions and the sourcing of census data from administrative registers have enabled these countries to significantly reduce their reliance on physical contact for tasks such as final preparation of field activities, training and data collection. The experience has confirmed the usefulness of these efforts …and will likely further accelerate the pace of innovation, even though most of these countries expect that farmers’ non-response rates will be higher than in the past. At the same time, the COVID-19 crisis has been a lesson to other countries on the need to improve the working environment, diversify census data collection and training methods, and make use of administrative registers in future census rounds. Show more

Keywords: COVID-19, census of agriculture, World Programme for the Census of Agriculture (WCA), alternative data collection methods, administrative registers

DOI: 10.3233/SJI-200752

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 861-865, 2020

Authors: Kissam, Edward

Article Type: Research Article

Abstract: Providing the public with relevant and reliable statistical information about the impact of COVID-19 on vulnerable populations is a crucial weapon in effective public health system response. This article examines the reporting challenges confronted by local public health agencies based on a case study of farmworker communities of the San Joaquin Valley, Eastern Coachella Valley, and Salinas Valley. The analysis includes a quantitative estimate of the impact COVID-19 has on farmworker households and highlights how socioeconomic factors and housing conditions give rise to health disparities. The importance of local data collection and reporting as the foundation for a national …epidemiological tracking system is emphasized. Current shortcomings stemming from flawed national guidance and local political pressures are noted. The discussion includes detailed recommendation for improved reporting including: more systematic tabulations of available data, an expanded set of indicators to monitor public health system response, promising approaches to improve representativeness of test-derived data on COVID-19 by making it easier to access testing and support services, coupled with messaging to broaden farmworkers’ and other socio-politically marginalized populations’ willingness to seek testing. Understanding the challenges faced and lessons learned in the San Joaquin Valley region have practical implications for a wide range of countries. Show more

Keywords: Farmworkers, San Joaquin Valley, California, COVID-19, testing, CDC, messaging, outbreak, hotspot, health equity, COVID-19 dashboards, indicators, monitoring, contact-tracing, case investigation, public health system, local government, congregate housing, crowded housing

DOI: 10.3233/SJI-200763

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 867-898, 2020

Article Type: Other

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 899-, 2020

Authors: Van Halderen, Gemma

Article Type: Research Article

DOI: 10.3233/SJI-200771

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 901-903, 2020

Authors: Siregar, Erika | Prawisudatama, Aris

Article Type: Research Article

Abstract: The longer a decision-maker has to wait for the statistics, the less useful they are likely to be. This statement is not only related to how fast the data is available, but also how fast the data can be understood. As the leading portal in presenting trusted data in Indonesia, the Badan Pusat Statistik (BPS) website provides complete data that covers various areas, subjects, and domains. However, the visualization of these data seems to be lagging. These data are presented in the form of tables and static graphs that are monotonous and the lack of interactivity discourages users from exploring …the data more. To tackle this gap, we developed liteRate which is an interactive web-based visualization/exploration tool that is based on the Shiny R. LiteRate aims to improve the public’s ability to understand the online data of the BPS’ by utilizing web scraping and headless browsers to produce ready-to-visualize data frames. Effective visualization techniques will empower users to quickly gain insight, see patterns, correlation, outliers, and view statistics across topics and areas. LiteRate hopes to increase statistical literacy in Indonesia as BPS continues to generate statistics that leave no one behind. Show more

Keywords: Visualization, interactivity, Shiny R, user experience, Asia Pacific Statistics Week

DOI: 10.3233/SJI-200755

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 905-913, 2020

Authors: Namgay, Tashi

Article Type: Research Article

Abstract: Knowing the quantity and the composition of waste is essential to designing and delivering sound waste management policies and waste management systems. Bhutan’s 12th Five-Year Development Plan emphasizes effective waste management as one of its key performance indicators and globally, the 2030 Agenda for Sustainable Development emphasizes the importance of waste in two of its seventeen Sustainable Development Goals. In 2019, the Bhutan National Statistics Bureau undertook its first ever survey of solid waste management. The survey covered waste generating sectors including households, commercial units, institutes, health centers, industries, Government offices and vegetable markets. Results show Bhutan generated more than …170 metric tons of waste daily – equivalent to 170,000 kilograms of sugar. More than 50 percent of solid wastes came from households, almost 50 percent was food waste, and around 50 percent was potentially recyclable. The survey posed many challenges for Bhutan, a land-locked least developed country in the Eastern Himalayas in South Asia, yet provided the opportunity to strengthen stakeholder engagement in the Bhutan National Statistical System and delivered statistics which meet a practical use for Bhutan and its people. Show more

Keywords: Coordination, trust, collaboration, waste generation, waste account, waste management, Asia Pacific Statistics Week

DOI: 10.3233/SJI-200742

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 915-924, 2020

Authors: Albertha, Winida | Midayanti, Nurma | Firdaus, Putri I. | Kosasih, Ahmad

Article Type: Research Article

Abstract: BPS-Statistics Indonesia plans to carry out its seventh population census in 2020. In contrast to the traditional method in previous censuses, it will use administrative data obtained from the Ministry of Home Affairs combined with field enumeration. Individual information recorded in the administrative data will be used as the initial data source for the field enumeration as well as to ensure adequate coverage. These changes could be a step towards a register-based census in the future. Given the important role of register data in the upcoming Indonesian census, it is necessary to assess the quality of the administrative data which …have been recorded by the Ministry of Home Affairs. Therefore, this study aimed to analyze whether there are significant differences on selected individual variables between the data from the administrative source and the census test results. The census test was conducted in three selected villages using multi-mode data collection. The comparison of the selected individual variables and the statistical test results indicate that this administrative data is of sufficient quality to be used as the data source for a combined method census in Indonesia. Show more

DOI: 10.3233/SJI-200744

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 925-932, 2020

Authors: Usman, Sofoora Kawsar | Moosa, Sheena

Article Type: Research Article

Abstract: An efficient Civil Registration and Vital Statistics (CRVS) system is a development imperative. Data on death registration and causes of death are important for measuring health outcomes. This paper evaluates the completeness and quality of data on death registration and causes of death (CoD) based on analysis of the registration records on death and causes of death for the period 2009–2018. Using established methods and approaches, we observed that CRVS system performed well on death registration completeness, quality of age and sex reporting. However, the quality of cause of death data was poor with 50% of the International …Classification of Diseases (ICD) codes classified as “major garbage codes” and significant time lag was observed in the transmission and production of vital statistics. The CRVS system in Maldives is complete with all deaths occurring within its territory registered and causes of death recorded. The two areas that require attention are the time taken for publication of vital statistics and quality of cause of death reporting. Appropriate re-engineering of the existing business process can build real-time mortality data, and regular quality assessment of death certificates with feedback to health facilities can bring sustained improvements in quality of vital statistics. Show more

Keywords: Quality, CRVS, SDG, Vital Statistics Performance Index, Asia Pacific Statistics Week

DOI: 10.3233/SJI-200748

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 933-941, 2020

Authors: Noviyanti, Isnaeni | Prabawa, Panca D. | Sari, Dwi Puspita | Koswara, Ade | Lestari, Titi Kanti | Fahyuananto, M. Hanif | Setiawan, Edi

Article Type: Research Article

Abstract: Nowadays, the use of so-called big data as a new data source to complement official statistics has become an opportunity for organizations focusing on statistics. The use of big data can lead to a more efficient data collection. However, currently, there has not been any standard business process for big data collection and processing in BPS-Statistics Indonesia. Meanwhile, the adoption of technologies alone cannot determine the success of big data use. It is widely known that big data use can be challenging, since there are issues regarding data access, quality, and methodology, as well as the development of required skillsets. …This paper proposes a framework for a business process that is specifically designed to support the use of big data for official statistics at BPS-Statistics Indonesia along with how existing technology will support it. The development of this framework is based on the wider Statistical Business Process Framework and Architecture (SBFA) developed by BPS-Statistics Indonesia to describe and manage its overall statistical business processes. The paper uses the example of the use of Mobile Positioning Data (MPD) as a big data source to delineate Metropolitan Areas in Indonesia as a way to explain the implementation of the framework. Show more

Keywords: GSBPM, big data use, big data challenges, MPD, metropolitan area, Asia-Pacific statistics

DOI: 10.3233/SJI-200750

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 943-954, 2020

Authors: Zulkarnain, Rizky | Jayanti, Dwi | Listianingrum, Tri

Article Type: Research Article

Abstract: The increasing needs for more disaggregated data motivates National Statistical Offices (NSOs) to develop efficient methods for producing official statistics without compromising on quality. In Indonesia, regional autonomy requires that Sustainable Development Goals (SDGs) indicators are available up to the district level. However, several surveys such as the Indonesian Demographic and Health Survey produce estimates up to the provincial level only. This generates gaps in support for district level policies. Small area estimation (SAE) techniques are often considered as alternatives for overcoming this issue. SAE enables more reliable estimation of the small areas by utilizing auxiliary information from other sources. …However, the standard SAE approach has limitations in estimating non-sampled areas. This paper introduces an approach to estimating the non-sampled area random effect by utilizing cluster information. This model is demonstrated via the estimation of contraception prevalence rates at district levels in North Sumatera province. The results showed that small area estimates considering cluster information (SAE-cluster) produce more precise estimates than the direct method. The SAE-cluster approach revises the direct estimates upward or downward. This approach has important implications for improving the quality of disaggregated SDGs indicators without increasing cost. The paper was prepared under the kind mentorship of Professor James J. Cochran, Associate Dean for Research, Prof. of Statistics and Operations Research, University of Alabama. Show more

Keywords: Asia pacific statistics week, non-sampled area, PAM, SAE, SDGs

DOI: 10.3233/SJI-200741

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 955-961, 2020

Authors: Ira, Abdorahim | Farrokhfal, Mostafa | Mali, Zohreh

Article Type: Research Article

Abstract: High food inflation rate in Iran in recent years places many low-income households at risk of malnutrition. Since food security and nutrition are essential dimensions of the Sustainable Development Goals (SDGs), this paper aims to create a reliable measure of food security in Iran among different income decile groups and urban and rural areas. The paper also attempts for the first time, to extract health-related indicators from the consumer price index (CPI) and the Household Income and Expenditure (HIES) surveys historically conducted by the Statistical Center of Iran (SCI). This study reaggregates CPI price data to calculate the nutritious food …price index (NPI) for urban and rural households in Iran. Moreover, the “Cost of a Recommended Diet (CoRD)” method is used to measure the trends and spatial variations in the costs of nutrition. The paper presents the results of using the CoRD method for regional levels and decile income groups. Results show that the cost of a healthy diet increased in recent years. Likewise, the healthy food price index is higher than the overall food price index. Finally, the results indicate that the NPIs in urban areas are higher than in rural areas. Show more

Keywords: SDGs, NPI, healthy food, data integration, asia pacific statistics week

DOI: 10.3233/SJI-200751

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 963-968, 2020

Authors: Harun, Nurfarahin | Ali, Noraliza Mohamad | Khan, Nur Layali Mohd Ali

Article Type: Research Article

Abstract: With the increase in the labour supply and the labour market imbalances globally, a notable increase is witnessed in the number of temporary employments as well as flexible arrangement in employment. This new development coupled with technological advancement create opportunity for flexible work through digital platforms, and the emergence of a new term in employment – the “gig” employment. Examples of gig workers are ‘independent contractors’, ‘consultants’, or ‘contract professor’, which are working only to complete a task for specific time and specific payment, with no work connection with their hiring institution once the contract ends. In the meantime, digitalisation …has created more opportunities for individuals to engage in gig employment for income generation. The rise of the gig workers calls for new initiatives in human resource development policy as they continue to play important roles in employment creation, production and income generation. From this study, a total of 218 occupations were identified as gig works which offered flexible working hours, flexible workplace and with or without digital presence. This study attempts to measure the gig workers in Malaysia using Labour Force Survey to gauge sociodemographic profiles of this new group of employment. Show more

Keywords: Flexible, income, online, temporary, Asia Pacific Statistics Week

DOI: 10.3233/SJI-200749

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 969-977, 2020

Authors: Zhang, Chunzhen | Hou, Lei

Article Type: Research Article

Abstract: To address the data ‘islandization’ issue in the statistical field and to take advantage of the opportunity of the Statistical Cloud construction, the National Bureau of Statistics of China (NBS) started adopting the concept of a “data middle platform” for data resource planning. With it, NBS aims to build a comprehensive data capability platform that includes data collection and exchange; data sharing and integration; data organizing and processing; data modeling and analyses; data management and governance; and data service and application. The statistical data middle platform provides the basic capability for data application support. It also enables data to form …a closed loop between the data middle platform and the business system, and eventually realizes the ‘servitization’ of statistical data that meets internal and societal requirements. As a new innovative development, the statistical data middle platform will not only solve the long-standing data island problem of NBS but will also provide a basic guarantee for greater use of the data potential, and thus will help official statistics to transform from statistical analysis to predictive analysis, from single-domain to cross-domain, from passive analysis to active analysis, and from non-real-time to real-time analysis. The paper was prepared under the kind mentorship of Ronald Jansen, Assistant Director and Chief of Data Innovation at the UN Statistics Division in New York. Show more

Keywords: Data islandization, data middle platform, data servitization, statistical cloud, data ecology, Asia-Pacific statistics week

DOI: 10.3233/SJI-200754

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 979-986, 2020

Authors: Or, Olivia Oi Yan

Article Type: Research Article

Abstract: The General Household Survey (GHS) of Hong Kong is a monthly household survey on labour force characteristics and household income. Traditionally, data collection was conducted via face-to-face interviews through field visits and computer-assisted telephone interviews (CATI). In July 2017, the Census and Statistics Department (C&SD) introduced an online questionnaire (OQ) in the GHS to enhance its services to survey respondents. Considering the importance of GHS statistics, the tight monthly survey cycle and the complexities involved in adding a new data collection mode, a phase-by-phase approach was adopted with close monitoring of data quality of the survey estimates. With satisfactory trial …results, the OQ was fully implemented in the GHS in January 2019. Being a convenient and privacy-assured channel, the OQ helps entice sampled households to respond to the GHS and increases the contact rate of those households who are more difficult to reach by the conventional data collection methods. During COVID-19 when face-to-face interviews had to be adjourned, the OQ provided a powerful channel for data collection. With targeted messages appealing for response by OQ sent to sampled households in a more proactive manner, the take-up rate of the OQ increased by as much as 10 percentage points, partly compensating the loss due to the suspension of field visits such that monthly labour force statistics could continue to be published during the epidemic. The paper was prepared under the kind mentorship of Ms Lisa Bersales, former Chief Statistician of the Philippines. Show more

Keywords: Data collection mode, online questionnaire, labour force survey, household survey, data quality, Asia Pacific Statistics Week

DOI: 10.3233/SJI-200746

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 987-995, 2020

Authors: Prasetyo, Octavia Rizky | Kadir, | Amalia, Ratna Rizki

Article Type: Research Article

Abstract: A critical issue in the context of food policy in Indonesia is the accuracy of crops statistics, particularly rice and maize. In 2018, Statistics Indonesia (BPS), in collaboration with the Indonesian Agency for Assessment and Application of Technology (BPPT), successfully implemented the area sampling frame (ASF) method to improve the accuracy of paddy harvested area estimation, which previously was estimated by conventional methods, mainly by the human eye (‘eye-estimate’). The achievement has encouraged BPS to replicate the method to estimate the harvested area of maize, for which there were indications it suffered from overestimation. In 2019, BPS initiated a pilot …project on the implementation of the ASF for maize. One of the most challenging aspects in replicating the ASF method for maize is the frame construction. This issue arises due to insufficient spatial information on land that is specifically dedicated to maize cultivation. To address this challenge, BPS constructed the frame by making use of different sources of spatial information. This paper provides a comprehensive look at the development of the ASF for maize statistics. The discussion in this paper covers two main issues, namely the methodology applied and the business process of data collection. Show more

Keywords: Asia pacific statistics week, area sampling frame, objective measurement

DOI: 10.3233/SJI-200743

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 997-1006, 2020

Authors: Lee, Chee You | Mohamad, Ab. Rahman bin | Misran, Rozita binti | Hamid, Halina binti Abdul

Article Type: Research Article

Abstract: Response rates, data quality and data confidentiality were identified as the critical success factors in Malaysia’s short-term economic survey. According to the facts, the Department of Statistics Malaysia (DOSM) has outlined a few initiatives in its strategic plan (2011–2015) and transformation plan (2016–2020) over the past ten years to improve and modernise data collection, processing and dissemination methods. This paper presents the practices of two DOSM short-term economic surveys i.e the monthly manufacturing survey (MM) and the quarterly construction survey (QCS) to raise the response rate, enhance data quality and manage data confidentiality by e-survey. The factors influences the participation …of the MM and QCS e-survey are discussed. This empirical study shows that the response rates of the both short-term surveys have improved through the e-survey. Comparison of data received by various survey modes also indicated that the e-survey provides the best prospects for reducing non-sampling error and protecting data against unintentional disclosure. Show more

Keywords: E-survey, response, confidential, modernisation, establishment, Asia Pacific Statistics Week

DOI: 10.3233/SJI-200753

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1007-1014, 2020

Authors: Fayyaz, Saeed | Hadizadeh, Reza

Article Type: Research Article

Abstract: In a modernized statistical production process, non-traditional data sources such as ‘big’ data are increasingly being considered either as the main or as a supplementary source for official statistics. Their use however has brought new sorts of challenges: messy datasets, duplicate entries, missing information and misspellings to name a few. In many cases, there is also no unique identifier which can be used to unambiguously identify a record for the purpose of data integration. These challenges can be compounded by a non-English based alphabet like the Persian/Farsi alphabet used in Iran. In this paper, two innovative methods have been elaborated …to address such data challenges. More specifically, the application of probabilistic record linkage using an ACSII coding system is an innovative way to deal with both data challenges and lack of unique identifier simultaneously. Moreover, text mining is an innovative way to address categorization and grouping systems that are not suitable for statistical purposes. Both innovative approaches can improve the accuracy and coherency of datasets and for data integration result in higher quality datasets. Results of research undertaken by the authors show the innovations lead to more effective data integration and improve the quality of the resulting official statistics. The innovations have wide applicability especially in non-English alphabet countries. Show more

Keywords: ‘big’ data, administrative data, quality, data integration, probabilistic record linkage, ASCII codes, text mining, alphabetic disorder, official statistics, Asia Pacific Statistics Week

DOI: 10.3233/SJI-200756

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1015-1030, 2020

Article Type: Other

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1031-, 2020

Authors: Radermacher, Walter J.

Article Type: Editorial

DOI: 10.3233/SJI-200773

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1033-1034, 2020

Authors: Prutsch, Markus J.

Article Type: Research Article

Abstract: While science and politics operate according to different logics, they have become considerably intertwined over time. Two opposing, but interrelated, developments can be observed in this regard: on the one hand, a scientization of politics, since science is increasingly relied upon when political and social challenges are being addressed, manifest in the increasing involvement of experts and scientific (policy) advisors; on the other hand, a politicization of science, because of the increasing influence of political decision makers on the objects, methods and processes of scientific research and funding. Both developments are accompanied by clear risks, and open debate is …needed about what scientific evidence – which is often expressed and mediated by means of numbers – can realistically do in and for politics. This is especially true at a time characterized by widespread distrust of experts and even facts, and a re-ideologization of politics that is perhaps best captured by the popular expression of “post-truth politics”. Show more

Keywords: Science, numbers, politics, post-truth politics, alternative facts, scientization of politics, politicization of science, evidence

DOI: 10.3233/SJI-200723

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1035-1041, 2020

Authors: Umbach, Gaby

Article Type: Research Article

Abstract: This article 1 offers reflections on the use of data as evidence in 21 st century policy-making. It discusses the concept of evidence-informed policy-making (EIPM) as well as the governance and knowledge effects of data as evidence. With this focus, it interlinks the analysis of statistics and politics. The paper first introduces the concept of EIPM and the impact of evidence use. Here it focusses on science and knowledge as resources in policy-making, on the institutionalisation of science advice and on the translation of information and knowledge into evidence. The second part …of the article reflects on data as evidence. This part concentrates on abstract and concrete functions of data as governance tools in policy-making, on data as a robust form of evidence and on the effects of data on knowledge and governance. The third part highlights challenges for data as evidence in policy-making, among them, politicisation, transparency, and diversity as well as objectivity and contestation. Finally, the last part draws conclusions on the production and use of data as evidence in EIPM. Throughout the second part of the reflections, reference is made to Walter Radermacher’s 2019 matrix of actors and activities related to data, facts, and policy published in this journal. Show more

Keywords: Evidence-informed policy-making, data, evidence, measurement, policy process, policy-making

DOI: 10.3233/SJI-200735

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1043-1055, 2020

Article Type: Other

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1057-, 2020

Authors: Sallier, Kenza

Article Type: Research Article

Abstract: Under the Modernization programme Statistics Canada has recently undertaken, the Agency is to put forward data access solutions that present greater analytical value to Canadians while maintaining its core values of protecting confidentiality of respondents’ information. One avenue currently explored is Data Synthesis as a means of delivering synthetic data with high analytical value to users. At the time of writing, Statistics Canada has publicly released synthetic versions of two different datasets related to census, mortality and cancer information. In both cases, synthetic data were generated using the R package synthpop . This paper describes the use of Data …Synthesis as a proof of concept for modernizing Statistics Canada’s data access solutions. Show more

Keywords: Synthetic data, data access, confidentiality, digital government, machine learning

DOI: 10.3233/SJI-200682

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1059-1066, 2020

Authors: Bailie, James

Article Type: Research Article

Abstract: Differential privacy (DP) has emerged in the computer science literature as a measure of the impact on an individual’s privacy resulting from the publication of a statistical output such as a frequency table. This paper provides an introduction to DP for official statisticians and discuss its relevance, benefits and challenges from a National Statistical Organisation (NSO) perspective. We motivate our study by examining how privacy is evolving in the era of big data and how this might prompt a shift from traditional statistical disclosure techniques used in official statistics – which are generally applied on a cell-by-cell or table-by-table basis …– to formal privacy methods, like DP, which are applied from a perspective encompassing the totality of the outputs generated from a given dataset. We identify an important interplay between DP’s holistic privacy risk measure and the difficulty for NSOs in implementing DP, showing that DP’s major advantage is also DP’s major challenge. This paper provides new work addressing two key DP research areas for NSOs: DP’s application to survey data and its incorporation within the Five Safes framework. Show more

Keywords: Data privacy, statistical disclosure control

DOI: 10.3233/SJI-200685

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1067-1074, 2020

Authors: MacFeely, Steve

Article Type: Research Article

Abstract: What distinguishes revolution from evolution? What events or movements in the world of official statistics have been sufficiently disruptive or transformational to deserve being called revolutionary? Using the definitions of data revolution put forward by the Independent Expert Advisory Group on a Data Revolution for Sustainable Development in their report A World that Counts to identify potential data revolutions and then deriving a framework to evaluate those definitions from Thomas Kuhn’s work The Structure of Scientific Revolutions , this paper investigates, through the lens of official statistics, whether there has been a data revolution or not.

Keywords: Open data, public good, datacratic, ethical frontier, New Global Data Deal

DOI: 10.3233/SJI-200662

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1075-1094, 2020

Authors: Hoffmeister, Onno

Article Type: Research Article

Abstract: This study analyses to which extent the classification of countries as developing corresponds with their actual development level. It tracks the evolution of the development status classification schemes (DSCSs) of international organisations over time, identifies three broad concepts of a developing country, based on the social sciences literature, and analyses the degree of correspondence between classifications and concepts, based on eight indicators. The results suggest that development status is a fairly accurate measure of development. All DSCSs strongly correspond with all indicators analysed. Over time, the outcomes of DSCSs have become increasingly heterogeneous. As a result, different classification …schemes match different concepts. Schemes of a first generation, which emerged before the 1990s, and which nominate countries for classes, correspond mainly with concepts focusing on difficult starting points or an early stage in systemic transition, whereas schemes of a second generation, set up in the 1990, which classify countries based on specified criteria, typically reflect a welfare-based concept. The paper argues that the growing heterogeneity of DSCSs and deficits in their documentation negatively impact on the quality of international official statistics. It makes proposals for the further development of DSCSs, also in the context of the 2030 Agenda for Sustainable Development. Show more

Keywords: Economic development, classification, logistic regression, cluster analysis

DOI: 10.3233/SJI-200680

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1095-1128, 2020

Authors: Gennari, Pietro | D’Orazio, Marcello

Article Type: Research Article

Abstract: The global SDG indicator framework establishes a set of measurement tools to assess country performances in a comparable way, and helps governments to identify appropriate policy interventions to achieve the SDG targets. Five years into the implementation of the 2030 Agenda, however, still different methods are being used by leading international organizations for assessing whether the SDG targets will be achieved or not. This may lead to different results, sometimes contradictory, generating confusion among users and policy-makers, who therefore cannot base their policy decisions on solid and coherent assessments. This article describes some of the solutions proposed by leading international …organizations to address two distinct measurement objectives: (i) monitor the “current” status of achievement of a SDG target, i.e. the situation as pictured by the latest available data, and (ii) assess whether the SDG targets can be achieved by 2030. These distinct objectives are then translated in various methodological approaches, that often include also a way for identifying the targets when not explicitly set, and the procedure to obtain regional and global aggregates (as well as, aggregates by target and goal). This article provides a critical overview of the different approaches and proposes a unified coherent statistical approach for progress and status assessments, highlighting its advantages over the alternative approaches, and demonstrate its application to a specific FAO indicator. The article focuses mainly on the assessment of (i) and (ii), while is not intended to investigate the issues related the aggregation of results at target/goal level, a topic that is beyond the scope of this work. Show more

Keywords: SDG indicators, status assessment, progress assessment, growth models

DOI: 10.3233/SJI-200688

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1129-1142, 2020

Authors: Kumar, Vikas

Article Type: Research Article

Abstract: Most discussions on data quality overlook the legal framework within which data are collected. This paper examines India’s Census Act, 1948 that provides the legal framework for conducting population censuses. The Act stipulates punishment for interfering with the process of enumeration but the punitive provisions have not been invoked to deal with cases of widespread manipulation of census. Major instances of manipulation were reported in 1951 and 2001 after the government introduced additional punitive measures in 1948 and 1994, respectively. The paper identifies the structural flaws of the Census Act, 1948 vis-à-vis manipulation. It compares the Act with other Indian …laws on the collection of statistics and census laws of other common law countries. It shows that fines are very small compared to per capita income in most countries and yet violators are rarely fined. The paper uses simple games to explain why the punitive provisions might be redundant and suggests that the problem of interference with government statistics can possibly be addressed without recourse to law. The insights drawn from the games are examined in light of the experience of Nagaland and other states of India where census statistics were affected by widespread manipulation in the recent decades. Show more

Keywords: Census, common law, conflict, data quality, game theory, India, Jammu and Kashmir, law, manipulation, Manipur, multiple equilibria, Nagaland, Punjab

DOI: 10.3233/SJI-200651

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1143-1160, 2020

Authors: Shiferaw, Yegnanew A.

Article Type: Research Article

Abstract: Policymakers and healthcare service managers demand reliable, accurate and disaggregated information about child deaths at the sub-national level to plan and monitor healthcare service delivery and health outcomes. In support of this demand, this research aimed at providing reliable local municipality estimates of the under-5 mortality rate (U5MR) in South Africa. The paper used a small area estimation approach to improve the precision of local municipality estimates of U5MR by linking data from the 2016 Community Survey (CS) and the 2011 Population Census (PC). The diagnostic measures and validation of the reliability of the results showed that the local municipality …estimates of U5MR produced by small area estimation are more efficient and precise than direct estimates of U5MR based only on the CS data. Further, accurate and cost-effective local municipality estimates of U5MR were produced without the need for more resources through combining the available data sources. This was achievable since the research did not require a separate survey for this purpose. The results can be used to monitor U5MR at the local level in South Africa since they link directly with the Sustainable Development Goals (SDGs). Show more

Keywords: Under-5 mortality, small area estimation, Fay-Herriot model, community survey, population census

DOI: 10.3233/SJI-200650

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1161-1173, 2020

Authors: Lamarche, Pierre | Oehler, Friderike | Rioboo, Irene

Article Type: Research Article

Abstract: Poverty indicators purely based on income statistics do not reflect the full picture of household’s economic well-being. Consumption and wealth are two additional key dimensions that determine the economic opportunities of people or material inequalities. We use non-parametric statistical matching methods to join consumption data from the Household Budget Survey to micro data from the European Union Statistics on Income and Living Conditions. In a second step, micro data from the Household Finance and Consumption Survey are joint to produce a common distribution of income, consumption and wealth variables. A variety of different indicators is then produced based on this …joint data set, in particular household saving rates. Care has to be taken when interpreting the indicators, since the statistical matching is based on strong assumptions and a limited number of variables common to all of the three original data sets. We are able to show, however, that the assumptions made are justified by the use of strong proxies as matching variables. Thus, the resulting indicators have the potential to contribute to the analysis of inequality patterns and enhance the possibilities of social, and possibly fiscal, policy impact analysis. Show more

Keywords: Statistical matching, CIA, EU-SILC, HBS, HFCS, saving rates

DOI: 10.3233/SJI-190528

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1175-1188, 2020

Authors: Adeboye, Nureni Olawale | Abimbola, Olawale Victor

Article Type: Research Article

Abstract: Machine learning is a branch of artificial intelligence that helps machines learn from observational data without being explicitly programmed and its methods have been found to be very useful in the modern age for medical diagnosis and for early detection of diseases. According to the World Health Organization, 12 million deaths occur annually due to heart-related diseases. Thus, its early detection and treatment are of interest. This research introduces a better way of improving the timely prediction of cardiovascular diseases in suspected patients by comparing the efficiency of two boosting algorithms with four (4) other single based classifiers on cardiovascular …official data. The best model was selected based on performances of 5 different evaluation metrics. From the results, Adaptive boosting is seen to outperform all other algorithms with a classification accuracy of 74.2%, closely followed by gradient boosting. However, gradient boosting was chosen as an acceptable technique because it trains faster than Adaboost with a better precision of 74.9% compared to 74.7% exhibited by Adaboost. Thus boosting algorithms are better predictors compared to single based classifiers with factors of age, systolic blood pressure, weight, cholesterol, height, and diastolic blood pressure as the major contributors to the model building. Show more

Keywords: Cardiovascular diseases, ensemble, boosting algorithms, AdaBoost, gradient boosting

DOI: 10.3233/SJI-190609

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1189-1198, 2020

Authors: Parker, Jennifer | Miller, Kristen | He, Yulei | Scanlon, Paul | Cai, Bill | Shin, Hee-Choon | Parsons, Van | Irimata, Katherine

Article Type: Research Article

Abstract: The National Center for Health Statistics is assessing the usefulness of recruited web panels in multiple research areas. One research area examines the use of close-ended probe questions and split-panel experiments for evaluating question-response patterns. Another research area is the development of statistical methodology to leverage the strength of national survey data to evaluate, and possibly improve, health estimates from recruited panels. Recruited web panels, with their lower cost and faster production cycle, in combination with established population health surveys, may be useful for some purposes for statistical agencies. Our initial results indicate that web survey data from a recruited …panel can be used for question evaluation studies without affecting other survey content. However, the success of these data to provide estimates that align with those from large national surveys will depend on many factors, including further understanding of design features of the recruited panel (e.g. coverage and mode effects), the statistical methods and covariates used to obtain the original and adjusted weights, and the health outcomes of interest. Show more

Keywords: Web survey, measurement error, propensity-score adjustment, recruited panel

DOI: 10.3233/SJI-200678

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1199-1211, 2020

Authors: Fortune, Nicola | Short, Stephanie | Madden, Richard

Article Type: Research Article

Abstract: Statistical classifications are essential for collecting consistent data that can be compared over space and time. However, a publicly-documented body of practice concerning how to undertake the development and testing of a statistical classification is currently lacking. What aspects of the classification should be tested during the development process? How do we judge whether the classification is fit-for-purpose? How should problems and shortcomings be identified so that they can be remedied? To fill this gap, we drew on existing, authoritative sources to develop an analytic structure for use in the development and testing of statistical classifications. It consists of …two components: (1) a statistical classification development and testing framework reflecting the required features of a statistical classification; and (2) a 4-tier model representing the main elements that make up a statistical classification, to use as a heuristic structure within which to locate issues identified and consider how they can be addressed. In this paper, we outline the development of the framework and model, and reflect on their application in testing a draft classification of health interventions. We propose this analytic structure as a new tool to support those engaged in the development of statistical classifications. Show more

Keywords: Statistical classification

DOI: 10.3233/SJI-200633

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1213-1221, 2020

Authors: Tunç, Burcu | Çakmak, Burcu | Gökçe Zeybek, Cansu | Tissot, Bruno

Article Type: Research Article

Abstract: The development of financial accounts is high on the global policy agenda. These accounts have become an essential element of the SNA, drawing from the traditional description of real economic aggregates augmented to present information on financial flows and positions. Several steps have been taken in recent years to refine important aspects of this framework, with the goal of building “integrated sectoral financial accounts”. To this end, two areas of focus are important. One relates to collecting the statistics to “fill” standard economic accounts. Large data collections have been undertaken since the 2007–09 Great Financial Crisis to build better-quality, more …comprehensive and flexible data sets. A second important issue is to highlight how these statistics can be useful and support public policy. These areas are of particular relevance for central banks. As producers, they have been highly involved in the statistical exercises launched to address the challenges highlighted by the 2007-09 crisis. As data users, they have an increasing demand for information in order to understand, and act on, the financial system in pursuing monetary and financial stability policy objectives; financial accounts represent a key opportunity to address these information needs. Show more

Keywords: Financial accounts, public policy, central banking, Great Financial Crisis, data users

DOI: 10.3233/SJI-200664

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1223-1237, 2020

Authors: Daas, Piet J.H. | van der Doef, Suzanne

Article Type: Research Article

Abstract: Producing an overview of innovative companies in a country is a challenging task. Traditionally, this is done by sending a questionnaire to a sample of companies. This approach, however, usually only focuses on large companies. We therefore investigated an alternative approach: determining if a company is innovative by studying the text on its website. For this task a model was developed based on the texts of the websites of companies included in the Community Innovation Survey of the Netherlands. The latter is a survey carried out every two years that focusses on the detection of innovative companies with 10 or …more working persons. We found that the text-based model developed was able to reproduce the result from the Community Innovation Survey and was also able to detect innovative companies with less than 10 employees, such as startups. Model stability, model bias, the minimal number of words extracted from a website and companies without a website were found to be important issues in producing high quality results. How these issues were dealt with and the findings on the number of innovative companies with large and small numbers of employees are discussed in the paper. Show more

Keywords: Innovation, webscraping, text analysis, Big data, concept drift

DOI: 10.3233/SJI-200627

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1239-1251, 2020

Authors: Araveeporn, Autcha | Klomwises, Yuwadee

Article Type: Research Article

Abstract: Markov Chain Monte Carlo (MCMC) method has been a popular method for getting information about probability distribution for estimating posterior distribution by Gibbs sampling. So far, the standard methods such as maximum likelihood and logistic ridge regression methods have represented to compare with MCMC. The maximum likelihood method is the classical method to estimate the parameter on the logistic regression model by differential the loglikelihood function on the estimator. The logistic ridge regression depends on the choice of ridge parameter by using crossvalidation for computing estimator on penalty function. This paper provides maximum likelihood, logistic ridge regression, and MCMC to …estimate parameter on logit function and transforms into a probability. The logistic regression model predicts the probability to observe a phenomenon. The prediction accuracy evaluates in terms of the percentage with correct predictions of a binary event. A simulation study conducts a binary response variable by using 2, 4, and 6 explanatory variables, which are generated from multivariate normal distribution on the positive and negative correlation coefficient or called multicollinearity problem. The criterion of these methods is to compare by a maximum of predictive accuracy. The outcomes find that MCMC satisfies all situations. Show more

Keywords: Logistic ridge regression, Markov Chain Monte Carlo, maximum likelihood

DOI: 10.3233/SJI-200655

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1253-1259, 2020

Authors: Pankowska, Paulina | Pavlopoulos, Dimitris | Bakker, Bart | Oberski, Daniel L.

Article Type: Research Article

Abstract: This paper discusses how National Statistical Institutes (NSI’s) can use hidden Markov models (HMMs) to produce consistent official statistics for categorical, longitudinal variables using inconsistent sources. Two main challenges are addressed: first, the reconciliation of inconsistent sources with multi-indicator HMMs requires linking the sources on the micro level. Such linkage might lead to bias due to linkage error. Second, applying and estimating HMMs regularly is a complicated and expensive procedure. Therefore, it is preferable to use the error parameter estimates as a correction factor for a number of years. However, this might lead to biased structural estimates if measurement error …changes over time or if the data collection process changes. Our results on these issues are highly encouraging and imply that the suggested method is appropriate for NSI’s. Specifically, linkage error only leads to (substantial) bias in very extreme scenarios. Moreover, measurement error parameters are largely stable over time if no major changes in the data collection process occur. However, when a substantial change in the data collection process occurs, such as a switch from dependent (DI) to independent (INDI) interviewing, re-using measurement error estimates is not advisable. Show more

Keywords: Data reconciliation, inconsistent data sources, measurement error, linkage error, hidden Markov model, latent class model, dependent interviewing

DOI: 10.3233/SJI-190594

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1261-1279, 2020

Authors: Alves, Kyle | Ritchie, Felix

Article Type: Research Article

Abstract: Statistical agencies and other government bodies increasingly use secure remote research facilities to provide access to sensitive data for research and analysis by internal staff and third parties. Such facilities depend on human intervention to ensure that the research outputs do not breach statistical disclosure control (SDC) rules. Output SDC can be principles-based, rules-based, or something in between. Principles-based is often seen as the gold standard statistically, as it improves both confidentiality protection and utility of outputs. However, some agencies are concerned that the operational requirements are too onerous for practical implementation, despite these statistical advantages. …This paper argues that the choice of output checking procedure should be seen through an operational lens, rather than a statistical one. We take a popular conceptualisation of customer demand from the operations management literature and apply it to the problem of output checking. We demonstrate that principles-based output SDC addresses user and agency requirements more effectively than other approaches, and in a way which encourages user buy-in to the process. We also demonstrate how the principles-based approach aligns better with the statistical and staffing needs of the agency. Show more

Keywords: Confidentiality, statistical disclosure control, operations management, output checking

DOI: 10.3233/SJI-200661

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1281-1293, 2020

Authors: Wallgren, Anders | Wallgren, Britt

Article Type: Research Article

DOI: 10.3233/SJI-200736

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1295-1297, 2020

Authors: Nastav, Bojan | MacFeely, Steve

Article Type: Research Article

Abstract: In August 2019, the IAOS discussion platform was launched with a special session at the ISI World Congress in Kuala Lumpur, Malaysia. The first paper published as part of that discussion series was ‘You say you want a [data] Revolution: A proposal to use unofficial statistics for the SDG Global Indicator Framework ’. This follow-on paper looks back over the year since the launch, summarizes the online debate, highlights some other relevant papers, and reflects on where the discussion rests today.

Keywords: 2030 Agenda, accreditation, risk management, UN World Data Forum, data revolution

DOI: 10.3233/SJI-200722

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1299-1306, 2020

Article Type: Other

DOI: 10.3233/SJI-200772

Citation: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1307-1309, 2020