Search

In the Netherlands, there is a growing movement to adopt and consider non-GDP metrics in policymaking, supported by national statistics institutes such as the Centraal Bureau voor de Statistiek (CBS). In 2018, the CBS introduced the Monitor Brede Welvaart (MBW) (van de Sangen, 20180). However, because this movement is still in its early stages, there is little evidence of its adoption in practice (Smit, 2022). This research paper seeks to shed light on this area by exploring the (potential) gap between a recognised need for a broader conception of societal wellbeing, and its adoption in practice. This research will collect qualitative data on the views and experiences of civil servants in the Dutch government (Walker et al., 2020). Exploring the factors that may be facilitating or hindering the adoption of the Brede Welvaart movement into the day to day practice of civil servants is both politically and socially relevant.

The aim of this study is to group OECD countries using the better life index indicators through multidimensional scaling analysis. The Better Life Index consists of thirty-three variables under the dimensions of material living conditions (income and wealth, work and earnings, housing conditions) and quality of life (health status, work-life balance, education and skills, social connections, civic engagement and governance, environmental quality, personal safety and life satisfaction). These thirty-three indicators constitute the variables of the multidimensional scaling analysis. As a result of the analysis, the positions of countries in two-dimensional space were obtained and it was observed that some countries formed distinct clusters. In this way, OECD countries are compared not on the basis of a selected indicator, but on the basis of an approach that encompasses all the indicators of the Better Life Index.

A importância de métricas além das económicas é um tema que tem ganho importância, tendo sido feitos desenvolvimentos significativos nas últimas duas décadas relativamente ao movimento Além do PIB, tópico desta dissertação. A seguinte dissertação incide sobre o estudo de índices de bem-estar em Portugal, que pretendem fornecer uma visão holística sobre a vida das pessoas, assim como na viabilidade de aplicação destes índices ao meio empresarial. Os dados foram recolhidos com recurso a entrevistas a peritos e dois questionários, um aplicado ao público em geral e outro a organizações. As 6 entrevistas realizadas permitiram a compreensão do atual conhecimento e utilização de índices de bem-estar em Portugal. O questionário ao público permitiu conhecer a perceção individual do bem-estar no contexto empresarial e obter conhecimento sobre a relação entre esta perceção e as características sociodemográficas dos participantes (N = 311), corroborando a hipótese que o público tem uma atitude positiva quanto ao bem-estar no contexto organizacional. O questionário aplicado às organizações permitiu estudar as características empresariais que promovem a intenção de aplicar índices de bem-estar, assim como o efeito da apresentação dos resultados do estudo 2 (N = 62), corroborando que a comunicação da valorização do público quanto à utilização de métricas de bem-estar nas organizações promove a sua utilização. Os resultados demonstram pouco conhecimento e utilização do índice de bem-estar português, assim como viabilidade para aplicação de índices de bem-estar no contexto empresarial, comprovando-se que as características estruturais das empresas influenciam a sua intenção de aplicar índices de bem-estar. The importance of metrics beyond economics is a topic that has gained importance, with significant developments in the last two decades regarding the movement Beyond GDP, the topic of this dissertation. The following dissertation focuses on the study of well-being indices in Portugal, which aim to provide a holistic view of people's lives, as well as the feasibility of applying these indices to the businesses. Data were collected using interviews with experts and two questionnaires, one applied to the general public and the other to organizations. The 6 interviews allowed the understanding of the current knowledge and use of well-being indices in Portugal. The public questionnaire allowed to study the individual perception of well-being in the businesses and knowledge about the relationship between this perception and the sociodemographic characteristics of the participants (N = 311), supporting the hypothesis that the public has a positive attitude towards the well-being in the organizational context. The questionnaire applied to organizations allowed the study of the business characteristics that promote the intention to apply well-being indices, as well as the effect of the presentation of the results of study 2 (N = 62), confirming that the communication of the public's appreciation for the use of well-being metrics in organizations promotes their use. The results demonstrate little knowledge and use of the Portuguese well-being index, as well as the feasibility of applying well-being indices in the business context, proving that the structural characteristics of businesses influence their intention to apply well-being indices.

The International Comparison Program (ICP) is a worldwide statistical initiative led by the World Bank under the auspices of the United Nations Statistical Commission. It produces comparable price and volume measures of gross domestic product (GDP) and its expenditure aggregates across economies. Through a partnership with international, regional, sub-regional and national agencies, the ICP collects price data and GDP expenditures to estimate purchasing power parities (PPPs) for the world’s economies. This guide provides an overview of how data and indicators based on these ICP outputs are used in a host of analyses, including monitoring progress towards the Sustainable Development Goals, to inform policy making across the socioeconomic spectrum at the national, regional, and international levels. Seventy charts and maps illustrating these uses are organised under eleven policy-focused chapters: the size of the economy and price levels; poverty and inequality; trade and competitiveness; labor costs, wages, and social safety nets; food and nutrition; health; education; energy and climate; infrastructure; human development; and administrative uses. The indicators are produced by the World Bank and other organizations including Eurostat, the Food and Agriculture Organization, the International Energy Agency, the International Labour Organization, the International Monetary Fund, the International Telecommunication Union, the Organisation for Economic Co-operation and Development, the United Nations Development Program, the United Nations Educational, Scientific and Cultural Organization, the World Economic Forum, and the World Health Organization. The guide also highlights notable uses of underlying ICP data on food prices and on public sector wages, as well as the wealth of data from the ICP database itself, such as price levels, real expenditures, and expenditure shares for aggregates below GDP for each economy. In addition, the guide includes a comprehensive chapter on the uses and limitations of PPPs and analyses for which they are appropriate, as well as a technical note outlining the concepts and definitions of terms used. A web-based version (https://www.worldbank.org/en/programs/icp/brief/PPPs-for-Policy ) is also available, and more information can be found on icp.worldbank.org.

This work proposes a new distribution defined on the unit interval. It is obtained by a novel transformation of a normal random variable involving the hyperbolic secant function and its inverse. The use of such a function in distribution theory has not received much attention in the literature, and may be of interest for theoretical and practical purposes. Basic statistical properties of the newly defined distribution are derived, including moments, skewness, kurtosis and order statistics. For the related model, the parametric estimation is examined through different methods. We assess the performance of the obtained estimates by two complementary simulation studies. Also, the quantile regression model based on the proposed distribution is introduced. Applications to three real datasets show that the proposed models are quite competitive in comparison to well-established models.

Diese Arbeit beschäftigt sich mit der Lebensqualität von MitarbeiterInnen und StammkundInnen in der Gastronomie.Der erste Teil dieser Arbeit behandelt die Gastronomie im Allgemeinen. Hierzu werden auch die Arbeitszeiten und -bedingungen beschrieben.Darauf folgt das Kapitel der MitarbeiterInnen in der Gastronomie. Wie steht es um den Fachkräftemangel und wie stehen MitarbeiterInnen zu den Betrieben, in denen sie arbeiten? Ebenso wird die Bindung zwischen ArbeitgeberInnen und ArbeitnehmerInnen sowie der ständige Wechsel in der Gastronomie behandelt.Danach liegt das Augenmerk dieser Arbeit auf den StammkundInnen. In diesem Kapitel steht die Gästebindung klar im Fokus. Wichtig dabei ist, was sich Gäste vom Personal erwarten, welche Umgangsformen sie als wünschenswert empfinden und wie wichtig Emotionen in diesem Bereich sind.Das letzte Kapitel vor der qualitativen Forschung beschäftigt sich mit dem Better Life Index der OECD. Neben allgemeinen Informationen zum Index, werden die 11 Themenfelder, die zur Messung der Lebensqualität beitragen, behandelt.Im Anschluss folgt die qualitative Forschung. Hierzu wurden jeweils 2 Interviews mit MitarbeiterInnen und StammkundInnen von Gastronomiebetrieben durchgeführt. Als Grundlage für die Erstellung des Interviewleitfadens dienten die Themengebiete des Better Life Index. Die Interviews werden mit der qualitativen Inhaltsanalyse nach Mayring ausgewertet.Eine Steigerung der Lebensqualität lässt sich nicht immer klar erkennen. So lässt sich eine Steigerung der Lebensqualität bei jungen MitarbeiterInnen durchaus erkennen, weniger aber bei den Älteren. Im Bereich der StammkundInnen ist aber ohne Zweifel festzustellen, dass die Lebensqualität durch Besuche in Gastronomiebetrieben gesteigert wird. This work deals with the quality of life of employees and regular customers in the catering industry.The first part of this thesis deals with gastronomy in general as well as with the working hours and conditions.This is followed by the chapter on staff in the catering industry. What about the shortage of skilled workers and how do employees feel about the companies they ́re working for? The bond between employers and employees as well as the constant change in gastronomy are also dealt with.After that, the focus of this work lies on the regular customers. This chapter clearly focuses on guest loyalty. The important thing is what guests expect from the staff, which manners they perceive as desirable and how important emotions are in this area.The last chapter before qualitative research deals with the OECD Better Life Index. In addition to general information on the index, the 11 subject areas that contribute to measuring quality of life are described. This is followed by qualitative research. For this purpose, two interviews were carried out with both employees and regular customers of restaurants. The subject areas of the Better Life Index served as the basis for creating the interview guide. The interviews are evaluated with the qualitative content analysis according to Mayring.An increase in the quality of life cannot always be clearly recognized.An increase in the quality of life can definitely be seen among young employees, but less so among older employees. In the area of regular customers, however, it can be determined without a doubt that the quality of life is increased by visits to restaurants. Jutta Deutsch Abweichender Titel laut Übersetzung der Verfasserin/des Verfassers Bachelorarbeit FH JOANNEUM 2021

DergiPark: 466902 trakyasobed The most significant requirement for people to maintain theirlives comfortably, is to have a specific level of welfare. Therefore, a countryhaving a high level of welfare is preferred as a livable country. This hassignificant influences on the economies of countries. One of most significantresearches conducted for determining the welfare levels of countries is theBetter Life Index (BLI) research conducted by Organization for EconomicCo-operation and Development (OECD) every year on a regular basis. With thisresearch, 38 countries are ranked based on main criteria and sub-criteria, buta general ranking is not made. The aim of this study is to rank the countriesby using Better Life Index data created by OECD. In the study, the criterionweights were determined and then, the countries were ranked with MULTIMOORAmethod. Then, the relationship between ranking of countries and their HumanDevelopment Index (HDI) rankings were investigated with Spearman’s RankCorrelation Coefficient and the results were interpreted. Kişilerin yaşamlarını rahat bir şekildesürdürebilmeleri için en önemli koşul refah düzeyinin belirli bir seviyedeolmasıdır. Dolayısıyla, iyi bir refah düzeyi olan ülke yaşanılabilir ülkeolarak tercih edilmektedir. Bu durum, ülkelerin ekonomileri üzerinde ciddietkiler yaratmaktadır. Ülkelerin refah düzeyini belirlemek adına yapılanaraştırmaların en önemlilerinden biri Ekonomik Kalkınma ve İşbirliği Örgütü (Organisationfor Economic Co-operation and Development: OECD) tarafından her yıl düzenliolarak gerçekleştirilen Daha İyi Yaşam Endeksi (Better Life Index: BLI)araştırmasıdır. Bu araştırma ile 38 ülke ana kriterler ve alt kriterler bazındasıralanmakta ancak genel bir sıralama yapılmamaktadır. Bu çalışmanın amacı,OECD tarafından oluşturulan Daha İyi Yaşam Endeksi verilerini kullanarakülkelerin sıralamalarını elde etmektedir. Çalışmada ilk olarak kriterağırlıkları entropi ile belirlenmiş, daha sonrasında ise MULTIMOORA metodu ileülkeler sıralanmıştır. Bu aşamadan sonra ise ülkelerin elde edilen sıralamalarıile İnsani Gelişme Endeksi (Human Development Index: HDI) sıralamalarıarasındaki ilişki Spearman Sıra Korelasyon Katsayısı ile incelenmiş ve sonuçlaryorumlanmıştır.

DergiPark: 697132 kusbder Daha iyi yaşam endeksi, OECD'nin maddi yaşam koşulları ve yaşam kalitesi alanlarında temel olarak tanımladığı 11 konuya dayanarak ülkeler arasında refahın karşılaştırılmasına olanak sağlamaktadır. Bu endeks 11 ayrı kıstas vasıtasıyla daha iyi yaşamın ipuçlarını ölçmeyi ve ülkelere yol haritası sunmayı amaçlamaktadır. Refahı ölçmede kullanılan kıstaslardan biri de iş-yaşam dengesidir. İş yaşam dengesi, bireyin iş yaşamı ile özel yaşamının dengede olması anlamına gelmektedir. Bir başka deyişle iş yaşam dengesi, bireylerin iş ve iş dışı hayatını en az rol çatışmasıyla dengeye ulaştırması şeklinde tanımlanmaktadır. Mevcut araştırma, OECD Daha İyi Yaşam Endeksi İş-Yaşam Dengesi 2018 yılı verilerini kümeleme analizi ile incelemeyi ve iş yaşam dengesi bağlamında OECD ülkelerinin nasıl sınıflandığını belirlemeyi hedeflemektedir. Gerçekleştirilen analiz sonuçları; 2018 yılında OECD ülkelerinde; 50 saat üzerinde çalışan oranı ortalamasının %8,73, bireysel aktivitelere ayrılan zaman ortalamasının 14,38 saat olduğunu göstermiştir. Ayrıca, 50 saat üzerinde çalışma ile bireysel aktivitelere ayrılan zaman arasında negatif, orta seviyeli ve anlamlı bir ilişki bulunmaktadır (r: -0,533; p The better life index allows to compare welfare between countries based on 11 issues that the OECD defines as the basis for material living conditions and quality of life. This index aims to measure the clues of better life through 11 different criteria and to provide a roadmap to countries. One of the criteria used to measure welfare is work-life balance. Work life balance means the balance between work life and private life. In other words, work life balance is defined as the way individuals balance work and non-work life with the least conflict of roles. The current research aims to examine the OECD Better Life Index Work-Life Balance 2018 data by cluster analysis and to determine how OECD countries are classified in the context of work life balance. The results of the analysis; In 2018, in OECD countries; The average rate of employees working for 50 hours and over was 8.73% and the average time allocated to individual activities was 14.38 hours. In addition, there was a negative, moderate and significant relationship between working 50 hours or more and time allocated to individual activities (r: -0.533; p

For many years there has been a focus on individual welfare and societal advancement. In addition to the economic system, diverse experiences and the habitats of people are crucial factors that contribute to the well-being and progress of the nation. The predictor of quality of life called the Better Life Index (BLI) visualizes and compares key elements&mdash, environment, jobs, health, civic engagement, governance, education, access to services, housing, community, and income&mdash, that contribute to well-being in different countries. This paper presents a supervised machine-learning analytical model that predicts the life satisfaction score of any specific country based on these given parameters. This work is a stacked generalization based on a novel approach that combines different machine-learning approaches to generate a meta-machine-learning model that further aids in maximizing prediction accuracy. The work utilized an Organization for Economic Cooperation and Development (OECD) regional statistics dataset with four years of data, from 2014 to 2017. The novel model achieved a high root mean squared error (RMSE) value of 0.3 with 10-fold cross-validation on the balanced class data. Compared to base models, the ensemble model based on the stacked generalization framework was a significantly better predictor of the life satisfaction of a nation. It is clear from the results that the ensemble model presents more precise and consistent predictions in comparison to the base learners.

Indexing for measuring the quality of life have been developed by various countries or organizations. Probably the most comprehensive among these indexes is the Better Life Index, which is developed by OECD. The sampling of the study consists of 34 countries that are the members of OECD, and two countries that are not members of OECD. The data are obtained from the 2017 criteria of OECD life index. In this way, the welfare levels of the countries were compared through the 11 life index criteria defined by OECD. In the study, correlation and regression analyses were performed to reveal the relationships between the OECD life criteria and to measure the degree of these relationships. Thus, it was attempted to demonstrate to what extent the index criteria, particularly the safety criterion, affect a society's quality of life. When we evaluate these analyses in general sense, it was observed that there is a significant and positive relationship between the safety criterion and other parameters. However, a negative relationship between the safety and the satisfaction criteria was found according to another result of the analyses. This is because of the fact that, after a certain threshold level, an individual won't have a positive attitude towards the interventions to the living space. Metody indeksowania danych w celu zmierzenia poziomu jakości życia są rozwijane przez wiele krajów i organizacji. Prawdopodobnie najbardziej obszernym z tych indeksów jest Better Life Index, opracowany przez OECD. W przypadku tego artykułu dane odnoszą się do 36 krajów, z których 34 należy do OECD, a pochodzą one z OECD Life Index z 2017 r. Poziomy dobrostanu w poszczególnych krajach zestawiono z 11 kryteriami określonymi przez OECD. Przeprowadzono analizy korelacji i regresji, aby wykazać powiązania pomiędzy kryteriami OECD Life i aby określić ich zakres. Umożliwiło to wykazanie w jakim zakresie kryteria indeksowania, w szczególności kryterium bezpieczeństwa, wpływają na jakość życia społecznego. Z ogólnej perspektywy można dostrzec istnienie znaczącego i pozytywnego związku pomiędzy kryterium bezpieczeństwa a innymi parametrami. Jednocześnie zauważono występowanie zależności negatywnej pomiędzy bezpieczeństwem a kryterium zadowolenia. Uwarunkowane jest to istnieniem pewnego poziomu progowego, powyżej którego jednostka nie będzie miała pozytywnego nastawienia do ingerowania w przestrzeń życiową.

One of the most influential measures of multidimensional well-being, the Better Life Index, launched by OECD in 2011, contains a detailed overview of the social, economic, and environmental performances of different countries. Since its launch, a relevant number of empirical studies have been proposed on these data, but the role played by the distance between societal priorities and country-level performance in Better Life Index as well as in multidimensional well-being remains underexplored. We propose to address this issue by means of a multidimensional spatial model. We position the countries in the Euclidean K-dimensional space in which each dimension is a specific aspect of well-being, and we consider each individual's opinion on the same dimensions to calculate the personal optimal point. The distance between the optimal point of well-being and the actual observed point at individual level is the individuals' loss in well-being. We show that the societal loss at country-level is negatively related to the overall well-being and the main indices of quality of democracy. Based on the above evidence, we would argue that a multidimensional spatial framework represents a promising tool for the analysis of the whole class of multidimensional measures of well-being in which a group of individuals expresses the weights individually assigned to a set of dimensions within a pre-established range.

Well-being has become an important policy goal to replace gross domestic product (GDP) as an indicator of national progress. Several multidimensional metrics and indicators of well-being have been developed mostly based on the four-capital model that includes natural, economic, human and social capital. These multidimensional measures of well-being, however, are highly categorical and lack a systems perspective that focuses on underlying mechanisms of the metrics and the interconnections between them. This study aims at bringing a systems thinking approach to understanding and measuring national well-being, particularly from a human capital perspective. For this purpose, we employ a qualitative systems mapping approach and identify the direct or indirect relationships between the well-being indicators related to human capital. The results show that the human capital system is governed by several reinforcing feedback loops through economic progress, health and life expectancy, which gives a central role to human capital to enhance well-being. There are balancing loops, however, that may have adverse effects on human capital formation and well-being, for instance through migration and ageing. Future studies can focus on the other three subsystems in the four-capital model, and on quantifying the relationships between different dimensions of well-being.

An Alternative: Better Life Index as a Measure of Multidimensional Development in Indonesia The purpose of this study is to get value-BLI Better Life Index as a measure of success of development in Indonesia, and to analyze the relationship between BLI with the human development index HDI, index IPR regional development, and economic growth. BLI formation method through three stages: normalization, weighting, and aggregation. The results show that Indonesia’s BLI is in the lower-middle class. Province of Jakarta, East Kalimantan, North Sulawesi, Riau and South Sumatra with the highest value of BLI. BLI size has a positive and significant correlation with IPM and IPR compiled by the BPS-Statistics Indonesia. However, BLI was significantly negatively correlated with economic growth. Keywords: Dimension of Development; Better Life Index; Human Development Index; Regional Development Index; Index Economic Growth Abstrak Tujuan penelitian ini adalah mendapatkan nilai Better Life Index (BLI) sebagai ukuran keberhasilan pembangunan di Indonesia, serta menganalisis hubungan antara BLI dengan Indeks Pembangunan Manusia (IPM), Indeks Pembangunan Regional (IPR), dan pertumbuhan ekonomi. Metode pembentukan BLI melalui tiga tahap: normalisasi, pembobotan, dan agregasi. Hasil penelitian ini menunjukkan bahwa nilai BLI Indonesia termasuk kategori menengah bawah. Provinsi Jakarta, Kalimantan Timur, Sulawesi Utara, Riau, dan Sumatera Selatan dengan nilai BLI tertinggi. Ukuran BLI ini mempunyai korelasi yang positif dan signifikan dengan IPM dan IPR yang disusun oleh Badan Pusat Statistik (BPS). Namun demikian, BLI berkorelasi negatif secara signifikan dengan pertumbuhan ekonomi.

The most significant requirement for people to maintain theirlives comfortably, is to have a specific level of welfare. Therefore, a countryhaving a high level of welfare is preferred as a livable country. This hassignificant influences on the economies of countries. One of most significantresearches conducted for determining the welfare levels of countries is theBetter Life Index (BLI) research conducted by Organization for EconomicCo-operation and Development (OECD) every year on a regular basis. With thisresearch, 38 countries are ranked based on main criteria and sub-criteria, buta general ranking is not made. The aim of this study is to rank the countriesby using Better Life Index data created by OECD. In the study, the criterionweights were determined and then, the countries were ranked with MULTIMOORAmethod. Then, the relationship between ranking of countries and their HumanDevelopment Index (HDI) rankings were investigated with Spearman’s RankCorrelation Coefficient and the results were interpreted., Kişilerin yaşamlarını rahat bir şekildesürdürebilmeleri için en önemli koşul refah düzeyinin belirli bir seviyedeolmasıdır. Dolayısıyla, iyi bir refah düzeyi olan ülke yaşanılabilir ülkeolarak tercih edilmektedir. Bu durum, ülkelerin ekonomileri üzerinde ciddietkiler yaratmaktadır. Ülkelerin refah düzeyini belirlemek adına yapılanaraştırmaların en önemlilerinden biri Ekonomik Kalkınma ve İşbirliği Örgütü (Organisationfor Economic Co-operation and Development: OECD) tarafından her yıl düzenliolarak gerçekleştirilen Daha İyi Yaşam Endeksi (Better Life Index: BLI)araştırmasıdır. Bu araştırma ile 38 ülke ana kriterler ve alt kriterler bazındasıralanmakta ancak genel bir sıralama yapılmamaktadır. Bu çalışmanın amacı,OECD tarafından oluşturulan Daha İyi Yaşam Endeksi verilerini kullanarakülkelerin sıralamalarını elde etmektedir. Çalışmada ilk olarak kriterağırlıkları entropi ile belirlenmiş, daha sonrasında ise MULTIMOORA metodu ileülkeler sıralanmıştır. Bu aşamadan sonra ise ülkelerin elde edilen sıralamalarıile İnsani Gelişme Endeksi (Human Development Index: HDI) sıralamalarıarasındaki ilişki Spearman Sıra Korelasyon Katsayısı ile incelenmiş ve sonuçlaryorumlanmıştır.

How do we understand the synergies and trade-offs of a given policy on area beyond that policy, such as the effect of housing on health and on income? How do we choose between policies in completely different areas, such as an education policy and a health policy? Treasury's Living Standards Framework provides one possible starting point, but it provides little assistance tracing the many dependencies between policy areas. A model that includes those dependencies could help. The Living Standards Analysis Model (LSAM) is designed to do this. A first prototype of the model has just been developed. This model includes all eleven aspects of wellbeing as described by the OECD's How's Life? framework and linkages between the different aspects for a small open economy. Most models for studying wellbeing only include one or two aspects, missing the rich set of interactions that can occur with greater coverage. As an early prototype, this version of the model does have many flaws and requires significant further development, but it forms a basis for creating an improved model as well as providing some qualitatively useful results. The model is loosely based on a stocks-and-flows type of model, with a small general equilibrium model covering the market economy part of the model. This paper is focussed on the description of the model.

International comparisons of health systems are frequently used to inform national health policy debates. These comparisons can be used to gauge areas of strength and weakness in a health system, and to find potential solutions from abroad that can be applied locally. But such comparisons are methodologically fraught and, if not carefully performed and used, can be misleading. In a recent IJHPR article, Baruch Levi has raised concerns about the use of international comparisons of self-reported health data in health policy debates in Israel. Self-reported health is one of the most robust and frequently used measures of health, and the OECD uses a commonly accepted measure specification, which has five response categories. Israel’s survey question, unlike the OECD measure specification, includes only four response categories. While this may be a valid method when applied over time as a scale within Israel, it creates problems for international comparison. To improve comparability, Israel’s Central Bureau of Statistics could revise the survey question. However, revising the question would introduce a “break” in the data series that interrupts comparisons within Israel over time. Israeli policymakers therefore face a decision about priorities: is it more important to them to be able to track health status within Israel over time, or to be able to make meaningful comparisons to other countries? If the priority were international comparisons and the Israel survey was revised, a small study could be conducted among a sample of Israeli respondents to enable crosswalking of self-reported health responses from the four-point scale to the five-point scale. If the Central Bureau of Statistics does not revise its survey, the OECD should examine whether a stronger caveat is possible for its comparisons.

Local health companies have been trying to report quantitative and qualitative information through social reporting tools for a long time. The OECD has been questioning for quite some time how to evaluate satisfaction and quality by not considering the economic aspect alone in the quest for satisfying the needs of the citizen. The aim of the work is to evaluate how the compound indicator of well-being perceived by the population and the composite indicator of the quality of health services can be used to define health policies considering the incidence of other variables. In the analysis, it is therefore assessed how much the two indicators are related and linked to other variables that need to be considered and how independent indicators are used without further evaluations to target policies. The data are updated to October 18, 2017. All statistical analyses were performed using STATA V.13 (Stata Corp, College Station, Texas, USA, 2013) and p value

Since measures of well-being are meant to be an exercise in documentation, but also a tool for policies and priorities, we suggest an operative way to use them. We evaluate both technical and social efficiency of countries in producing the Better Life Index (BLI) objectives. To assess the efficiency test, we use Data Envelopment Analysis integrated with Principal Component Analysis. Our analysis shows that BLI increases with GDP only for poor countries, extending the Easterlin Paradox to the quality of life measurement; that good performances in BLI are not necessarily due to a high efficiency of the whole system; and that social efficiency is the best predictor of development.

V sodobni družbi se pojavlja vprašanje kako meriti blaginjo, vendar je že sama opredelitev le-te težavna. Sestavljena je namreč iz različnih vidikov človekovega življenja, katere lahko izmerimo z objektivnimi in subjektivnimi kazalci. Diplomsko delo z naslovom »OECD-jev Indeks boljšega življenja« je sestavljeno iz teoreti-čnega in praktičnega dela. V teoretičnem delu bomo opisali koncept blaginje, izpostavili nekaj izbranih kazalcev za merjenje blaginje kot alternative BDP ter opisali delovanje OECD-ja na področju merjenja človekove blaginje. V praktičnem delu bomo predstavili dimenzije blaginje v sklopu Indeksa boljšega življenja, ki jih je OECD oblikovala po priporočilih Komisije za merjenje uspešnosti gospodarstva in družbenega napredka ter indikatorje, ki te dimenzije sestavljajo. A common question in modern society is how to measure well-being, although the defini-tion itself of well.being is a rather difficult one. Well-being consists of various aspects of human life, which can be measured with objective as well as subjective indices. Diploma thesis titled »OECD's Better Life Index« consists of theoretical and practical sec-tion. In the theoretical section, the concept of well-being is described, we are also focusing on some chosen indices for measuring well-being as an alternative measure to GDP, and describing OECD's work on measuring human well-being. In the practical section, we introduce well-being dimensions as a part of Better-Life Index, designed according to Commision for measuring economic performance and social pro-gress,and indicators that compose these dimensions.

Across the globe there is growing skepticism about the usefulness of GDP as a measure of national well-being. Consequently, several alternative quality-of-life (QOL) measures were developed which either aim at healing the GDP, complementing it, or replacing it. This chapter portrays some of these new measures and puts them to a happiness test: compared to the GDP, are the new QOL measures better able to capture what makes people happy and satisfied with their lives? Using data for 34 OECD societies, we can show that from a happiness perspective, there is-surprisingly-little wrong with the GDP, and most alternative QOL measures do not outperform GDP. Yet, one measure actually does a better job: the OECD's Better Life Index which is particularly effective when it comes to predicting subjective well-being in the richest OECD countries. In sum, the chapter demonstrates that a happiness perspective can add important insights along the way to facilitate the search for a new, widely accepted, internationally comparable measure of well-being. (author's abstract)

Ne samo, da BDP ne upošteva ključnih elementov kakovosti življenja, ampak v veliko primerih celo spodbuja aktivnosti, ki so v nasprotju z dolgoročno blaginjo skupnosti. Pri tem je smiselno omeniti npr. izkoriščanje naravnih virov, ki vodi v propad ekosistemov. Nič nam ne pove o družbeni neenakosti, ki pogosto vodi k socialnim nemirom. Enako velja za vse elemente socialne razčlenitve (ločitve, kazniva dejanja), ki jih obravnava kot ekonomske koristi. Podcenjuje tudi človeški kapital s tem ko zajema samo obseg končnih proizvodov. Potreben je razvoj, ki zadovoljuje potrebe sedanjosti, ne da bi bila ogrožena možnost zadovoljitve potreb prihodnjih generacij. In takšnega razvoja trenutni koncept ne prinaša. Naš planet je že sedaj preobremenjen zaradi potrošnje in onesnaževanja. Edini način, da se to neravnovesje popravi, je institucionalizacija drugih nacionalnih indikatorjev (okoljskih, povezanih z zdravjem itd.), ki bi odražali tisto pravo kompleksnost človekovega napredka. Ni pa pravega konsenza, koliko indikatorjev bi bilo smiselno vključiti in to je vprašanje, s katerim se že leta ubadajo ekonomisti. Obravnavali smo tudi odnos med gospodarsko rastjo in okoljem ter prišli do zaključka, da je kompleksen in večplasten in da ni res, da gospodarska rast vedno povečuje okoljsko škodo, kot tudi ni res, da se sčasoma vedno zmanjša. Kaj se dogaja je odvisno od števila prebivalstva, vzorcev potrošnje in uporabljene tehnologije. Kar je jasno pa je, da so za dosego trajnostnega razvoja potrebne velike tehnološke spremembe, te pa zahtevajo investicije in akumulacijo kapitala. Analizirali smo tudi vpliv tehnologije, pri čemer smo predvidevali različne scenarije s pomočjo IPAT identitete. Tehnologija, pa čeprav povzročitelj in rešitelj hkrati, je lahko ključni dejavnik izboljšanja okolja. Prav ta tretja komponenta identitete, torej tehnologija, predstavlja največje upanje za tranzicijo v trajnostni razvoj, doslej pa je bila videna kot kontinuiran vir onesnaževanja. Nato smo analizirali osem obstoječih alternativnih kazalnikov, ki smo jih ocenjevali skozi SWOT analizo ter jih spoznali skozi študije primerov. Potrebo po novih kazalnikih smo potrdili z javnomnenjsko raziskavo Globescana, ki je pokazala, da tradicionalna mera BDP ne predstavlja dovolj celovite slike napredka države. Uporaba BDP-ja ima svoje prednosti saj pomaga pri makroekonomski politiki, je enostaven, univerzalen, objektiven in uporablja tržno ceno kot vodilni princip. Rast je sicer pomembna, toda ne smemo rasti na način, ki zanemarja osnovna načela trajnostnega razvoja. GDP not only ignores key elements by which quality of life is defined by, in many cases it even encourages activities that are contrary to long-term prosperity of the community. In this instance it is appropriate to mention the exploitation of natural resources which results in ecosystem collapses. It doesn't tell us anything about the social inequalities that often lead to social unrest. The same is true for all elements of social breakdown (divorce, crime), which are seen as economic benefits. It also underestimates human capital by including only the volume of finished products. What we need is development that meets the needs of the present without jeopardizing the ability to meet the needs of future generations. And the current concept does not bring such development. Our planet is already congested due to consumption and pollution. The only way to rectify this imbalance is the institutionalization of other national indicators (environmental, health related, etc.) to reflect the true complexity of human progress. There is no real consensus, what indicators need to be included, and that is the question with which economists are grappling for years. We also dealt with the relationship between economic growth and the environment and have come to the conclusion that it is complex and multifaceted, and that it's not true that economic growth increases environmental damage, as it’s also not true that in time it always reduces. What happens depends on the number of population, patterns of consumption and technologies used. What is clear is that to achieve sustainable development, major technological changes are required, and these involve investments and capital accumulation. The impact of technology was also the subject of treatment, where we assumed different scenarios using IPAT identity. Technology, the saviour and the culprit at the same time, can be a key factor in improving the environment. It is this third component of the identity (technology) which is the greatest hope for a transition to sustainable development, though so far it might have been seen as an ongoing source of pollution. Then we analyzed the eight existing alternative indicators, which were evaluated through SWOT analysis, and we got to know them through case studies. The need for new indicators was confirmed by GlobeScan’s poll which showed that the traditional measure of GDP does not present a sufficiently comprehensive picture of progress in a country. The use of GDP has its advantages as it helps in macroeconomic policy, is simple, universal, objective and applies the market price as its guiding principle. Growth is important, but we should not grow in a way that ignores the basic principles of sustainable development.