National Statistical Agencies Research Articles

Carbon dioxide emissions, population, foreign direct investment, and renewable energy nexus: New insights from Thailand

This study investigates the multifaceted interplay between carbon dioxide emissions, population dynamics, foreign direct investment (FDI), and renewable energy (RE) within the unique context of Thailand. Amidst rapid economic growth and urbanization, Thailand faces pressing environmental challenges, making it an ideal case study for understanding the complex relationships between these variables. As a nation experiencing rapid economic growth and urbanization, Thailand provides a compelling case study for understanding the complex relationships between these variables. The paper uses the unrestricted random panel data method. Data is gathered from the World Bank from 2000 to 2022. The research addresses several critical issues using a mixed-methods approach and drawing data from national statistical agencies and environmental databases. The paper's primary objective is to explore how population dynamics, FDI, and RE adoption influence carbon emissions in Thailand. The rigorous analysis unveils key insights: a positive correlation between population growth and carbon emissions, nuanced relationships between FDI and emissions across sectors, and the significant impact of RE adoption on emissions reduction, particularly in high-emission sectors. This work contributes to the existing literature by offering novel findings and policy recommendations tailored to Thailand's environmental challenges. By addressing identified issues, such as sector-specific emissions patterns and the influence of FDI on emissions, the study provides actionable insights for policymakers striving to balance economic growth with environmental sustainability. Significantly, this manuscript advances the field by emphasizing the need for an integrated approach to environmental policymaking and highlighting the potential of RE as a critical driver of emissions reduction. The study's originality lies in its comprehensive analysis of the intricate nexus between carbon emissions and socio-economic factors within the Thai context. In conclusion, this research underscores the importance of informed environmental policymaking and offers practical implications for fostering sustainable development in Thailand and beyond. By leveraging the innovative insights and recommendations presented in this manuscript, policymakers can navigate the complexities of environmental stewardship while driving positive change towards a greener and more sustainable future.

Implications of Developing Fayd Al-Barakat Book on Learning Qiraat sab’ah in the Digital Era

The discourse of the digital era qiraat sab’ah study in Indonesia faces theoretical and practical problems. Theoretical problems are shown by the minimal number of qiraat sab’ah experts, while practical problems are evidenced by the low interest in learning qiraat sab’ah. The DITPD Pontren survey in 2021 explained that only 65 of 26,975 Islamic boarding schools in Indonesia teach qiraat sab’ah. The next survey from the National Statistics Agency in 2021 shows that only two universities in Indonesia teach qiraat sab’ah. This requires further investigation to solve theoretical and practical problems in qiraat sab’ah. This study aims to discuss the implications of developing Fayd al-barakat book on learning qiraat sab’ah in the digital era. This study uses qualitative methods to explore the genealogical aspects and development models of the Fayd al-barakat book in the digital era and its implications for learning qiraat sab’ah at Ponorogo. The data source was obtained from the manuscript of the qiraat sab’ah KH. Husein Ali and interviews with 1 Kiai, 5 ustadz, and 6 students. The method of tracing genealogical books and chain paths uses Rahman's hermeneutics. Data analysis uses content analysis methods through data reduction, data display, and conclusions. Display data using domain analysis. The results of this study showed that the development of the fayd al-barakat book at PPTQ al-Hasan Ponorogo produced a manuscript of the qiraat sab’ah book, while its implications for learning qiraat sab’ah were relevant to the characteristics and realities of the digital era society.

Sintesis Silika Alam dari Kalsinasi Sekam Padi

Indonesia is an agricultural country, where 40% of the livelihood of the majority of the population is farming. The factor that makes Indonesia an agricultural country is that apart from its population working in the agricultural sector, Indonesia is also crossed by fertile mountain ranges. In an agricultural country like Indonesia, agriculture makes an important contribution to the economy and fulfills people's basic needs. The increase in population will be proportional to the increase in the number of basic needs available. Survey results from the National Statistics Agency show that in 2022 Indonesia will experience an increase in rice production of 1.25 million tons from the previous year. Along with the increase in agricultural production, a new problem that arises is the large number of agricultural residues that are not used optimally, for example, such as rice husks. On average, every 1 kilogram of rice produced can produce 0.28 kg of rice husks. Rice husks contain a high silica content. Based on research that has been carried out, it was found that the silica content was 98-99.9% silica using the sol gel method.

Methods to control disclosure risk of synthetic data created by National Statistics Agencies

ObjectivesWith the recent explosion of interest in using synthetic data (SD) for disclosure control many NSAs are releasing, or considering releasing. synthetic versions of their administrative data. This presentation will review the methods that NSAs can use to limit the disclosure risk of any planned release of synthetic data. MethodsThis paper will review the ways in which methods of creating can be adapted to control the disclosure risk that could arise by the release of such data either to trusted researchers or to a wider group. Methods that will be evaluated will include: The use of Statistical Disclosure Control (SDC) methods on the synthetic data before its release Selecting methods producing low fidelity synthetic data Adapting the synthesis method until it satisfies measures of disclosure risk Incoporating differential privacy (DP) into the method of creating synthetic data ResultsNSAs can use different methods to create SD based on real data (RD); see e.g. https://unece.org/info/publications/pub/373531. Tthe disclosure risk of SD depends on the context of its release, to whom, in what environment etc. Even if the planned method of release ensures low disclosure risk, NSAs will want to know what the disclosure risk might be if the SD got into the wrong hands. The SD can reveal that an identified person is in the RD (identity disclosure) or can disclose information about other measures for an individual that are part of the RD. Measures of identity disclosure and attribute disclosure are described. Results will be presented on the disclosure risk of examples of SD created for real examples by the methods 1 to 4. ConclusionEach of the methods 1 to 4 have strengths and weaknesses. Methods 2 and 4 will be ruled out for many applications because of poor fidelity to the RD. A practical way forward is suggested by combining methods 1 and 3.

ANALYSIS OF DEMOGRAPHIC PROCESSES IN THE REPUBLIC OF AZERBAIJAN AND THEIR IMPACT ON THE LABOR MARKET

Topicality. Regarding the relevance of the article, it is necessary to note that the demographic process develops under the influence of other social processes: economic, political and others. In turn, the demographic process affects the course of all other social processes. Demographic processes in the Republic of Azerbaijan and their impact on the labor market are studied in the article. In the study, a systematic approach was used, which allows applying the best scientific ideas of economic theory to analyze the modern labor market in the context of the development of population decline processes.Aim and tasks. The study aims to investigate various aspects of demographic processes, such as population growth, birth and death rates, migration patterns, age structure, and urbanization trends in Azerbaijan. By analyzing these factors, the study seeks to provide insights into the changing composition and dynamics of the population in the country.Materials and methods. Data collection, demographic analysis, literature review, policy implications were used in the study. The study would require collecting relevant data on demographic processes and labor market indicators in Azerbaijan. This data can be obtained from various sources such as national statistical agencies, labor market surveys, census data, administrative records, and other relevant databases. The study would involve analyzing demographic processes in Azerbaijan, including population growth rates, birth and death rates, fertility rates, mortality rates, migration patterns, age distribution, and urbanization trends. This analysis can be conducted using statistical methods and demographic models to understand the dynamics and trends of the population.Research results. In the course of the research, the national concept of labor market management was studied, state programs on demographic, socio-economic development, effective socio-economic policy and labor market development models in non-standard conditions were reviewed.Conclusion. The study involves analyzing the labor market in Azerbaijan, including labor force participation rates, employment rates, unemployment rates, occupational patterns, wage levels, skill requirements, and other relevant labor market indicators. This analysis can be conducted using statistical techniques and econometric models to assess the impact of demographic factors on the labor market. The future study on the topic would aim to provide policy recommendations based on the findings and analysis. These recommendations can inform policymakers, government agencies, and other stakeholders about potential interventions, strategies, or policy changes that could address the challenges or harness the opportunities arising from demographic changes in Azerbaijan's labor market.

A framework for measuring and modelling low-carbon lifestyles

Lifestyle is an integral and inevitable feature of transformation pathways consistent with the Paris Climate Agreement and United Nations Sustainable Development Goals. Studies differentiating lifestyle types, clusters, or segments vary in their focus, purpose, reach, generalizability and availability. Universal frameworks are largely proprietary in nature, developed and used by market research companies for targeted communication and behaviour change strategies. There is a need for a more accessible lifestyle typology to promote understanding of lifestyle and its main drivers.In this paper we present a lifestyle typology for application to low-carbon research based on publicly available data from national statistical agencies. Drawing on substantive, inter-disciplinary literature, we define lifestyles as the interplay between cognitions and behaviours in specific material and social contexts. Using this definition, we develop a generalisable analytical framework for measuring and classifying lifestyles empirically, based on perspectives from public health, marketing, and pro-environmental research.We apply our framework using hierarchical cluster analysis of nationally representative household social survey data. We select four countries with contrasting contexts and lifestyles: UK (n = 5000 respondents), USA (n = 900 respondents), Australia (n = 5000 respondents) and China (n = 5000 respondents). We identify four low-carbon lifestyle types – 'Resourceful', 'Active', 'Constrained' and 'Cautious' – that are consistent across countries and robust to variation in analytical approach. Each lifestyle type is characterised by its low-carbon cognitions, by its propensity for low-carbon behaviours, and by its contextual markers. We use this differentiated lifestyle typology to identify major sources of heterogeneity in the opportunities, capacities, and constraints to leading a low-carbon lifestyle.Our approach is transparent and replicable, and our lifestyle framework is empirical-based and generalisable to different country contexts. Our findings can guide policy interventions for enabling low-carbon lifestyles, and enhance research efforts to model lifestyle. An improved understanding of lifestyle and its contribution in achieving the Paris Agreement climate targets, could also enhance efforts to visualise and plan for the low-carbon transition.

Multidimensional Poverty and its Effect on the Economy of Aceh Province

The first goal of Sustainable Development Goals, eliminating poverty in all forms, is closer to multidimensional poverty rather than official poverty statistics, which are measured using the basic need approach. Examining the trend of economic growth in Aceh during the past few years reveals the limitations of this strategy. Economic improvement has little effect on the poverty rate because it is only measured in one dimension. This research measures the poverty rate from various aspects by examining the forming factors first. The formed index will then be analyzed for its properness by involving other related variables and compared to the basic-need-based poverty measurement. Furthermore, every impact of each dimension on economic growth will also be assessed. Using the confirmatory factor analysis (CFA), multidimensional poverty is measured to give another perspective on the poverty rate. Multiple linear regression is employed to identify the relationship between the poverty dimension and the economy. The result shows that the new poverty rate measurement gives more proper poverty distribution across the region in Aceh Province. Concerning the human development index, multidimensional poverty is more relevant than basic need poverty. Asset ownership and education are the dimensions that significantly affect the economy. Our study concludes that multidimensional poverty should complement the monetary poverty produced by national statistical agencies and provide a new direction of poverty alleviation policy, such as increasing physical investment in households or creating vocational programs to improve the quality of the population.

Introducing a new data resource for comparative child welfare research: The ROCKWOOL-Duke global child welfare database

The Rockwool–Duke Global Child Welfare Database (RDGCWD) is a cross-national aggregate longitudinal data resource created to facilitate comparative research on children’s involvement with child welfare systems (CWS) and child protective services (CPS) across national contexts. The basis for the RDGCWD is harmonized data collected from national and transnational child welfare and statistical agencies on three types of contact: maltreatment investigation, substantiated maltreatment, and out-of-home placement. The database covers 44 countries for the period 2000–2020 with 33 country–year observations of children investigated by CWS/CPS, 104 country–year observations of investigations by CWS/CPS, 194 country–year observations of CWS/CPS confirmations of maltreatment, 66 country-year observations of children maltreated, 233 country–year observations of children entering out-of-home care, 402 country–year observations of children residing in out-of-home care at a specific point in time, and 55 country-year observations of entrances into care. Interested researchers can access the data at the National Data Archive on Child Abuse and Neglect (NDACAN).

Romanya’da tarım sektörü ve arazi mülkiyet durumu (1990-2020).

Romanya 13,8 milyon hektar tarım arazisiyle Avrupa Birliği Ülkelerinin toplam tarım alanın % 7,2’sine sahiptir. Ülkede yaşanan siyasi rejim değişikleri ve Avrupa Birliği üyeliği, arazi mülkiyetinde yapısal değişime sebep oldu. 1990 sonrasında büyük çiftlik arazilerinin halka dağıtılması sonucu tarlalar küçük parsellere bölündü. Romanya’nın AB’ye katılım sürecinde ve 2007’de gerçekleşen tam üyelik sonrasında yapılan yasal düzenlemeler, çok uluslu şirketlerin kiralama ve satın almalar yoluyla büyük arazilere sahip olmalarını sağladı. 1990 ile 2020 yılları arasını kapsayan bu çalışmada, Romanya’daki arazi mülkiyetinin devlet, bireysel üretici ve tüzel kişiliğe sahip işletmeler şeklinde yıllara göre değişimi ortaya konulmaktadır. Mısır, buğday ve ayçiçeğinin ekim alanı, üretim miktarı ve verimliliğin yıllara göre değişimi, örnek teşkil etmesi adına tablolar şeklinde gösterilmektedir. AB ülkelerinde kullanılan NUTS sınıflandırması ile Romanya 8 bölgeye ayrılarak incelenmiştir. Kaynak olarak, FAOSTAT ve Romanya Ulusal İstatistik Ajansı esas alınmıştır. Arazi kullanımı verileri CORINE tarafından sağlanmış ve ARCMap ortamında oluşturulmuştur.

A new data driven method for summarising multiple cause of death data

BackgroundNational mortality statistics are based on a single underlying cause of death. This practice does not adequately represent the impact of the range of conditions experienced in an ageing population in which multimorbidity is common.MethodsWe propose a new method for weighting the percentages of deaths attributed to different causes that takes account of the patterns of associations among underlying and contributing causes of death. It is driven by the data and unlike previously proposed methods does not rely on arbitrary choices of weights which can over-emphasise the contribution of some causes of death. The method is illustrated using Australian mortality data for people aged 60 years or more.ResultsCompared to the usual method based only on the underlying cause of death the new method attributes higher percentages of deaths to conditions like diabetes and dementia that are frequently mentioned as contributing causes of death, rather than underlying causes, and lower percentages to conditions to which they are closely related such as ischaemic heart disease and cerebrovascular disease. For some causes, notably cancers, which are usually recorded as underlying causes with few if any contributing causes the new method produces similar percentages to the usual method. These different patterns among groups of related conditions are not apparent if arbitrary weights are used.ConclusionThe new method could be used by national statistical agencies to produce additional mortality tables to complement the current tables based only on underlying causes of death.

An algorithm for predicting job vacancies using online job postings in Australia

Timely and accurate statistics on the labour market enable policymakers to rapidly respond to changing economic conditions. Estimates of job vacancies by national statistical agencies are highly accurate but reported infrequently and with time lags. In contrast, online job postings provide a high-frequency indicator of vacancies with less accuracy. In this study we develop a robust signal averaging algorithm to measure job vacancies using online job postings data. We apply the algorithm using data on Australian job postings and show that it accurately predicts changes in job vacancies over a 4.5-year period. We also show that the algorithm is significantly more accurate than using raw counts of job postings to predict vacancies. The algorithm therefore offers a promising approach to the timely and reliable measurement of changes in vacancies.

Assessing economic damage to the health care system caused by climate change (through the example of Moscow)

Aim. The presented study aims to assess economic damage to the health care system caused by climate change in Moscow.Tasks. The authors examine methods for assessing economic damage to the health care system caused by climate change; describe research methodology; assess economic damage to the health care system caused by climate change in Moscow in 2010–2020.Methods. To assess economic damage, this study uses the method of calculating the cost of the disease and the methodology of the World Health Organization (WHO), which involves analyzing many statistical indicators of the health care system collected by national statistical agencies. The period of study is from 2010 to 2020.Results. Climate change in Moscow can cause significant economic damage, which varies depending on the number of dangerous weather events from 0.05 to 5.63% of Moscow’s gross regional product (GRP) (7.78–471.87 billion rubles). The greatest economic damage was in 2010, when the number of days with dangerous weather events in Moscow exceeded 180 days.Conclusions. Significant economic damage to the health care system caused by climate change in Moscow manifested by dangerous weather events calls for an effective climate policy. Further studies should assess the city’s current climate policy, focusing on the implementation of adaptation measures and recommendations for its improvement.

Abstract P564: Prevalence of Metabolic Syndrome in a Young Sub-Saharan African Community

Background: Metabolic syndrome is known as a predictor of cardiovascular disease (CVD), a leading cause of death globally. The factors that comprise metabolic syndrome are on the rise in Sub-Saharan Africa, and data regarding the prevalence of metabolic syndrome in communities of aged less than 40 years old remain scarce. Methods: Data were collected between March and April 2013 from 3 regions of the Northern Senegal (i.e., Saint-Louis, Matam et and Louga) using a cluster sampling method and the survey base of the national statistical and demographical agency. Subjects aged between 18 and 80 years were recruited, however, the present study focused on adult populations below 40 years of age. Participants underwent a face-to-face questionnaire to collect demographics and data on cardiovascular history/risk factors. Blood pressure (BP) and anthropometric measurements were performed in addition to a blood test measuring fasting triglycerides, high density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol, and plasma glucose. Metabolic syndrome was defined as fasting plasma glucose ≥110 mg/dl, serum triglycerides ≥150 mg/dl, serum HDL cholesterol <40 mg/dl, BP ≥130/85 mmHg or on BP medication, or waist girth >102 cm in males or >89 cm in females. Comparisons used the χ2 test for categorical variables and Student’s t test for continuous variables. Multiple logistic regression was used to identify factors associated with CFI, after considering potential confounders. Covariates with significant association (P<0.05) in univariate analysis were included in the multivariate logistic model. Results: Of the 2,440 subjects recruited, 1080 participants were less than 40 years old and included in the current analysis. The mean age of these participants was 31 ± 7.53I. There were 296 (27%) male participants in our study. . Overall, there were 41 participants (3.8%) with metabolic. For individual components of metabolic syndrome, body mass index of 25 or higher was present in 32% of the population with a significant increase among women (38 vs 15% vs 3,7%, p<0,001). The prevalence of hypertension was28% and more than half of the population presented with dyslipidaemia (554 participants). Among those with dyslipidemia, 339 have a high total cholesterol index (61%, 95% CI: 57-65%). Conclusion: Our community-based cross-sectional study revealed a low prevalence of metabolic syndrome among younger participants in northern Senegal. However, the prevalence of dyslipidaemia was high.

Abstract P566: Prevalence of Renal Failure in a Young Community-Based Sub-Saharan African Population

Background: Patients with renal failure have a higher risk or cardiovascular events. However, the prevalence of renal failure in Sub Saharan Africa communities remain poorly documented. Methods: Data were collected between March and April 2013 from 3 regions of the Northern Senegal (i.e., Saint-Louis, Matam et and Louga) using a cluster sampling method and the survey base of the national statistical and demographical agency subjects aged between 18 and 80 years. However, the present study focused on adult populations below 40 years of age. Participants underwent a face-to-face questionnaire to collect demographics and data on cardiovascular history/risk factors. Blood pressure and anthropometric measurements were performed in addition to blood tests including plasma creatinine. Renal failure was defined as a GFR < 60 ml/min/1.73 m 2 using the MDRD method adapted to the African population. Continuous data were reported as mean ± standard deviation (SD). Comparisons used the χ2 test for categorical variables and Student’s t test for continuous variables. Multiple logistic regression was used to identify factors associated with CFI, after considering potential confounders. Covariates with significant association (P<0.05) in univariate analysis were included in the multivariate logistic model. Results: Among the 2440 subjects in this study the mean age was 44 ± 15.99, 692 (28%) were male. Among the 1080 participants who were aged less than 40 years old (mean: 31 ± 7.54), 296 (27.4%) were male. Body mass index higher than 25 was present in 32% of the studied population with a significant increase in women (38% vs 15%, p<0,001). The prevalence of hypertension was 28%. The prevalence of renal failure was 3.1% (95%CI: 2.1-4.3%) with a mean glomerular filtration rate of 55 ± 23.58. None of the participants with renal failure had diabetes. Conclusion: This community-based cross-sectional study showed a low prevalence of renal failure in younger participants in Northern Senegal. Further investigations are needed to assess chronic kidney failure and its determinants.

Abstract P351: Prevalence of Diabetes in a Sub-Saharan African Community

Background: Diabetes is a major cardiovascular disease (CVD) risk factor. There has been a epidemiological shift and chronic CVD is increasing in Sub-Saharan Africa, however, the extent is unknown. Methods: Data were collected between March and April 2013 from 3 regions of the Northern Senegal (i.e., Saint-Louis, Matam etand Louga) using a cluster sampling method and the survey base of the national statistical and demographical agency, we included subjects aged between 18 and 80 years old. Participants underwent a face-to-face questionnaire to collect demographics and data on cardiovascular history/risk factors. Blood pressure and anthropometric measurements were measured in addition to blood tests including fasting plasma glucose. Diabetes was defined as fasting plasma glucose >= 1.26 g/L. Continuous data were reported as mean ± standard deviation (SD). Comparisons used the chi-squared test for categorical variables and Student’s t test for continuous variables. Multivariable adjusted logistic regression was used to identify factors associated with diabetes. Covariates with significant association (P<0.05) in univariate analysis were included in the model. Results: Among the 2440 subjects in this study (mean age: 44 years old, SD: 15.99), 692 (28%) were male. Nearly half of the sample never attended school (48%, 95%CI: 46-50%). Body mass index (BMI) higher than 25 was present in 43% of the sample (95%CI: 29-35%), with a significant increase in women (51% vs 22%, p<0,001).. The prevalence of diabetes was 5.9% (95%CI: 5-6,9%). Among them, 93% had at least two cardiovascular diseases (95% CI: 87-96%), 71% had dyslipidemia (95%CI: 63-78%) and 67% had a BMI over 25 (95%CI: 58-74%). Conclusion: This community-based study revealed a low prevalence of diabetes. However, the prevalence of additional CVD risk factors in this population was high. Preventive measures should be implemented to avoid increasing rates of diabetes in Sub-Saharan Africa.

Disaster mortalities and the Sendai Framework Target A: Insights from Zimbabwe

In many parts of the world, human losses to disasters have been on the increase during the past three decades. This has slowed down the human development process. In an attempt to curb disaster impact, the world adopted an action-oriented Sendai Framework for Disaster Risk Reduction (SFDRR) in 2015. Target A of the SFDRR seeks to substantially reduce disaster mortalities by 2030. This study contributes to the SFDRR by bringing in disaster-disaggregated mortality data to assess the progress of Zimbabwe’s commitment in attaining Target A. The data came from the Zimbabwe National Statistics Agency, the Traffic Safety Council of Zimbabwe, the Department of Civil Protection and the EM-DAT database. To analyse the data, we conducted 3-year and 5-year moving averages for a period of thirty years to frame a holistic picture of the disaster mortalities in Zimbabwe. We also applied the methodology developed by the Open-Ended Intergovernmental Expert Working Group to determine the mortality rates for the overall and individual disaster type. Results clearly showed that Zimbabwe is making progress in reducing disaster mortalities despite a few spikes across its range of disasters. Major deaths were caused by drought, diarrhoea, malaria and tropical cyclones. Therefore, Zimbabwe needs to invest in drought monitoring and mitigation, cyclone forecasting and early warnings, and the surveillance and prevention of diarrhoeal diseases and malaria in order to substantially reduce the disaster mortality by the year 2030.

Norwegian and Russian settlements on Svalbard: An analysis of demographic and socio-economic trends

Abstract The Svalbard archipelago is a centre of global research on climate change and also an example of a rapidly changing Arctic area with tourism replacing the traditional mining industry. We compared the different development paths of the Norwegian (Longyearbyen and Ny-Ålesund) and Russian settlements (Barentsburg and Pyramida) on Spitsbergen as part of the Svalbard archipelago using demographic and socio-economic data until 2022 when available, but not focusing on the impacts of COVID-19 and changing geopolitics after 2022. We analysed strategy documents produced by Norway and Russia and by organisations connected to Svalbard. The analysis continued by scrutinising the statistical data available to ascertain if this supported the strategic goals outlined in the documents. Data collection was by direct enquiry to national statistical bureaus, agencies and institutions in Norway and Russia. Secondary data were collected from media publications and social media accounts. Statistics Norway provided very detailed data on demographics and industrial structure, turnover, investments and comprehensive statistics on employees by industry on Norwegian settlements on Svalbard. The results revealed disparities in socio-economic development, striking differences in data availability and in transparency between the Norwegian and Russian settlements. The population in the Norwegian settlements continued to grow during the period 1990–2022 with an increasing number of foreign nationals, and the population in the Russian settlements decreased by 85% at the same time period. The Norwegian settlements exemplify a diversified economy with a growing private sector, and the Russian settlements continued to rely on the town-forming Russian state unitary coal mining enterprise, Trust Arktikugol. While Svalbard presented a prime example of open data and transparency in the environmental sciences, the socio-economic and demographic statistics were lagging behind. Several practical proposals are presented for improved data collection on the Svalbard settlements.

РОЛЬ ГОСУДАРСТВА В ВОССТАНОВЛЕНИИ РЫНКА ТРУДА В ПОСТПАНДЕМИЙНЫЙ ПЕРИОД (НА ПРИМЕРЕ СТРАН ОЭСР)

The goal of this study is to analyze the features of the OECD labor markets’ recovery in the post-Covid period, evaluate various national strategies for overcoming the negative consequences of the coronavirus crisis in the field of employment, and assess public policy measures after the end of the acute phase of the pandemic in comparison with previous crises. To analyze the situation on the labour market in OECD countries in the post-pandemic period, the author used data from international statistical organizations, primarily the International Labour Organization, OECD and Eurostat, and publications of national statistical agencies. A comparative analysis of employment policies in OECD countries at the stage of post-Covid economic recovery allowed us to come to the conclusion that, firstly, measures aimed at maintaining support for affected industries and population groups were continued, and secondly, policies on resolving structural issues in the labour market, including strengthening labour mobility, restoring and expanding the system of professional retraining, and increasing the efficiency of the public employment service, were activated.

INVESTMENT IN INFRASTRUCTURE AS A KEY TO SUSTAINABLE ECONOMIC RECOVERY: THE ROLE OF THE BUILDING INDUSTRY

The focus of this paper is the role of the building industry in post-COVID-19 economic recovery plans. Investment in infrastructure forms a major part of many countries’ strategies to engender economic growth and construction is the pivotal industry in enabling the implementation of the plans in a sustainable manner. This study looks at the effects of investment in infrastructure on the economy with reference to the role of the construction industry in delivering this investment. Basic issues are considered, particularly concerning how relevant investment can be measured and how the contribution of the construction sector can be realistically assessed. A review of data sources and empirically peer-reviewed papers is undertaken. Based on longitudinal time series data from national statistics agencies and international organizations, analysis is undertaken to discover the relationship between infrastructure investment and economic growth. The study focuses on the UK, but comparisons are made with other countries to consider alternative approaches to stimulus investment policies with digitalization, and sustainability and green investment being a growing feature of investment plans. Potential issues of these approaches are examined and the main barriers to their achievement are identified. Emerging trends and a set of policy agendas are proposed to guide future directions.

Penerapan Algoritma K-Means clustering Untuk Mengelompokkan Provinsi Berdasarkan Banyaknya Desa/Kelurahan Dengan Upaya Antisipasi/Mitigasi Bencana Alam

Natural disasters are one of the natural phenomena that threaten human survival. The negative impacts can be in the form of material or non-material losses. However, with the ability to recognize the early symptoms of a disaster, humans can prepare themselves for disaster. Application of the K-Means clustering Algorithm in Grouping Provinces Based on the Number of Villages / Sub-districts with Anticipation / Mitigation Efforts for Natural Disasters Using the WEKA Application. The data sources for this research were collected based on documents describing the Number of Villages/ Urban According to Natural Disaster Anticipation/Mitigation Efforts produced by the National Statistics Agency. The data used in this study is provincial data which consists of 34 provinces. There are 4 variables used, namely Natural Disaster Early Warning System, Tsunami Early Warning System, Safety Equipment, Evacuation Path. The data will be processed by clustering in 2 clusters, namely clusters with high anticipation/mitigation levels and low anticipation/mitigation levels. The results obtained from the assessment process are that there are 5 (14.71 %) provinces with a high level of anticipation/mitigation and 29 (85.29%) other provinces including a low level of anticipation/mitigation. This can be an input for the government to pay more attention to the Village/Kelurahan based on the clusters that have been carried out