Measuring World Better Life Frontier: A Composite Indicator for OECD Better Life Index
The OECD Better Life initiative recently released a comprehensive set of 11 indicators of well-being covering a group of countries. Each individual indicator corresponds to a key topic that is essential to well-being. However, the problem of aggregating them is left to users of this dataset. Using t...
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description | The OECD Better Life initiative recently released a comprehensive set of 11 indicators of well-being covering a group of countries. Each individual indicator corresponds to a key topic that is essential to well-being. However, the problem of aggregating them is left to users of this dataset. Using these as individual indicators, we propose a composite indicator of overall well-being, which is intended to measure the performance of each country in terms of providing well-being to its people. The 'benefit of the doubt' approach (BOD), a well-known aggregation tool based on a weighed sum, assigns the most favourable weights for each entity under investigation. BOD may also be considered to evaluate the performance of each entity in terms of its efficiency. Regarding individual indicators as outputs, it constructs the benchmark production frontier from observed individual indicators. A composite indicator based on BOD equals the distance between each entity's individual indicator and the production frontier, indicating its efficiency. It is widely considered that the well-being of a country's people stems from its productive base, which is characterized by capital assets and social infrastructures. Thus, the productive base can be considered the input used to produce well-being, which is reflected by individual indicators. Therefore, when we apply BOD to aggregate individual well-being indicators across countries, we implicitly assume that all countries have the same productive base, as BOD addresses only the output and neglects the input. This inaccurate assumption leads to a distored performance measure. Data envelopment analysis (DEA), in which BOD has its roots, is a tool to measure the efficiency of each entity by allowing for differences in inputs as well as outputs across entities. DEA also measures efficiency by using the distance to the production frontier; however, unlike BOD, DEA constructs the production frontier more accurately by utilizing the information of inputs as well as outputs, leading to a better performance measure. We apply DEA to aggregate 11 individual well-being indicators into a composite indicator using the World Bank's estimates of each country's productive base. The composite indicator based on BOD is distributed similarly to and is highly correlated with the existing Human Development Indicator (HDI). It is also positively correlated with GDP per capita. On the other hand, we show that the composite indicator based on DEA is neg |
doi_str_mv | 10.1007/s11205-013-0457-x |
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Each individual indicator corresponds to a key topic that is essential to well-being. However, the problem of aggregating them is left to users of this dataset. Using these as individual indicators, we propose a composite indicator of overall well-being, which is intended to measure the performance of each country in terms of providing well-being to its people. The 'benefit of the doubt' approach (BOD), a well-known aggregation tool based on a weighed sum, assigns the most favourable weights for each entity under investigation. BOD may also be considered to evaluate the performance of each entity in terms of its efficiency. Regarding individual indicators as outputs, it constructs the benchmark production frontier from observed individual indicators. A composite indicator based on BOD equals the distance between each entity's individual indicator and the production frontier, indicating its efficiency. It is widely considered that the well-being of a country's people stems from its productive base, which is characterized by capital assets and social infrastructures. Thus, the productive base can be considered the input used to produce well-being, which is reflected by individual indicators. Therefore, when we apply BOD to aggregate individual well-being indicators across countries, we implicitly assume that all countries have the same productive base, as BOD addresses only the output and neglects the input. This inaccurate assumption leads to a distored performance measure. Data envelopment analysis (DEA), in which BOD has its roots, is a tool to measure the efficiency of each entity by allowing for differences in inputs as well as outputs across entities. DEA also measures efficiency by using the distance to the production frontier; however, unlike BOD, DEA constructs the production frontier more accurately by utilizing the information of inputs as well as outputs, leading to a better performance measure. We apply DEA to aggregate 11 individual well-being indicators into a composite indicator using the World Bank's estimates of each country's productive base. The composite indicator based on BOD is distributed similarly to and is highly correlated with the existing Human Development Indicator (HDI). It is also positively correlated with GDP per capita. On the other hand, we show that the composite indicator based on DEA is negatively correlated with HDI as well as GDP per capita.</description><identifier>ISSN: 0303-8300</identifier><identifier>EISSN: 1573-0921</identifier><identifier>DOI: 10.1007/s11205-013-0457-x</identifier><identifier>CODEN: SINRDZ</identifier><language>eng</language><publisher>Dordrecht: Springer</publisher><subject>Bank capital ; Capital assets ; Composite indices ; Cooperation ; Correlation analysis ; Cultural Capital ; Data envelopment analysis ; Economic indices ; Economic sociology ; Efficiency metrics ; GDP ; Gross Domestic Product ; Happiness ; History, theory and methodology ; Human Geography ; Indicators ; International comparisons ; Karnofsky performance status ; Methodology ; Methodology (Data Analysis) ; Microeconomics ; Natural capital ; OECD ; Per capita ; Performance evaluation ; Public Health ; Quality of Life Research ; Social research ; Social Sciences ; Sociology ; Sociology of economy and development ; Standard of living. 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Each individual indicator corresponds to a key topic that is essential to well-being. However, the problem of aggregating them is left to users of this dataset. Using these as individual indicators, we propose a composite indicator of overall well-being, which is intended to measure the performance of each country in terms of providing well-being to its people. The 'benefit of the doubt' approach (BOD), a well-known aggregation tool based on a weighed sum, assigns the most favourable weights for each entity under investigation. BOD may also be considered to evaluate the performance of each entity in terms of its efficiency. Regarding individual indicators as outputs, it constructs the benchmark production frontier from observed individual indicators. A composite indicator based on BOD equals the distance between each entity's individual indicator and the production frontier, indicating its efficiency. It is widely considered that the well-being of a country's people stems from its productive base, which is characterized by capital assets and social infrastructures. Thus, the productive base can be considered the input used to produce well-being, which is reflected by individual indicators. Therefore, when we apply BOD to aggregate individual well-being indicators across countries, we implicitly assume that all countries have the same productive base, as BOD addresses only the output and neglects the input. This inaccurate assumption leads to a distored performance measure. Data envelopment analysis (DEA), in which BOD has its roots, is a tool to measure the efficiency of each entity by allowing for differences in inputs as well as outputs across entities. DEA also measures efficiency by using the distance to the production frontier; however, unlike BOD, DEA constructs the production frontier more accurately by utilizing the information of inputs as well as outputs, leading to a better performance measure. We apply DEA to aggregate 11 individual well-being indicators into a composite indicator using the World Bank's estimates of each country's productive base. The composite indicator based on BOD is distributed similarly to and is highly correlated with the existing Human Development Indicator (HDI). It is also positively correlated with GDP per capita. On the other hand, we show that the composite indicator based on DEA is negatively correlated with HDI as well as GDP per capita.</description><subject>Bank capital</subject><subject>Capital assets</subject><subject>Composite indices</subject><subject>Cooperation</subject><subject>Correlation analysis</subject><subject>Cultural Capital</subject><subject>Data envelopment analysis</subject><subject>Economic indices</subject><subject>Economic sociology</subject><subject>Efficiency metrics</subject><subject>GDP</subject><subject>Gross Domestic Product</subject><subject>Happiness</subject><subject>History, theory and methodology</subject><subject>Human Geography</subject><subject>Indicators</subject><subject>International comparisons</subject><subject>Karnofsky performance status</subject><subject>Methodology</subject><subject>Methodology (Data Analysis)</subject><subject>Microeconomics</subject><subject>Natural capital</subject><subject>OECD</subject><subject>Per capita</subject><subject>Performance evaluation</subject><subject>Public Health</subject><subject>Quality of Life Research</subject><subject>Social research</subject><subject>Social Sciences</subject><subject>Sociology</subject><subject>Sociology of economy and development</subject><subject>Standard of living. 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Income</topic><topic>Studies</topic><topic>Wealth</topic><topic>Well Being</topic><topic>Wellbeing</topic><topic>World Bank</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mizobuchi, Hideyuki</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Sociological Abstracts (pre-2017)</collection><collection>Access via ABI/INFORM (ProQuest)</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Education Database (Alumni Edition)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Psychology Database (Alumni)</collection><collection>Social Science Database (Alumni Edition)</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Sociological Abstracts</collection><collection>ProQuest One Community College</collection><collection>Education Collection</collection><collection>Sociological Abstracts</collection><collection>ProQuest Central Korea</collection><collection>International Bibliography of the Social Sciences</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Sociology Collection</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Education Database</collection><collection>Healthcare Administration Database</collection><collection>Psychology Database</collection><collection>Research Library</collection><collection>Social Science Database</collection><collection>Sociology Database</collection><collection>Research Library (Corporate)</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Education</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>Sociological Abstracts (Ovid)</collection><jtitle>Social indicators research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mizobuchi, Hideyuki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Measuring World Better Life Frontier: A Composite Indicator for OECD Better Life Index</atitle><jtitle>Social indicators research</jtitle><stitle>Soc Indic Res</stitle><date>2014-09-01</date><risdate>2014</risdate><volume>118</volume><issue>3</issue><spage>987</spage><epage>1007</epage><pages>987-1007</pages><issn>0303-8300</issn><eissn>1573-0921</eissn><coden>SINRDZ</coden><abstract>The OECD Better Life initiative recently released a comprehensive set of 11 indicators of well-being covering a group of countries. Each individual indicator corresponds to a key topic that is essential to well-being. However, the problem of aggregating them is left to users of this dataset. Using these as individual indicators, we propose a composite indicator of overall well-being, which is intended to measure the performance of each country in terms of providing well-being to its people. The 'benefit of the doubt' approach (BOD), a well-known aggregation tool based on a weighed sum, assigns the most favourable weights for each entity under investigation. BOD may also be considered to evaluate the performance of each entity in terms of its efficiency. Regarding individual indicators as outputs, it constructs the benchmark production frontier from observed individual indicators. A composite indicator based on BOD equals the distance between each entity's individual indicator and the production frontier, indicating its efficiency. It is widely considered that the well-being of a country's people stems from its productive base, which is characterized by capital assets and social infrastructures. Thus, the productive base can be considered the input used to produce well-being, which is reflected by individual indicators. Therefore, when we apply BOD to aggregate individual well-being indicators across countries, we implicitly assume that all countries have the same productive base, as BOD addresses only the output and neglects the input. This inaccurate assumption leads to a distored performance measure. Data envelopment analysis (DEA), in which BOD has its roots, is a tool to measure the efficiency of each entity by allowing for differences in inputs as well as outputs across entities. DEA also measures efficiency by using the distance to the production frontier; however, unlike BOD, DEA constructs the production frontier more accurately by utilizing the information of inputs as well as outputs, leading to a better performance measure. We apply DEA to aggregate 11 individual well-being indicators into a composite indicator using the World Bank's estimates of each country's productive base. The composite indicator based on BOD is distributed similarly to and is highly correlated with the existing Human Development Indicator (HDI). It is also positively correlated with GDP per capita. On the other hand, we show that the composite indicator based on DEA is negatively correlated with HDI as well as GDP per capita.</abstract><cop>Dordrecht</cop><pub>Springer</pub><doi>10.1007/s11205-013-0457-x</doi><tpages>21</tpages></addata></record> |
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subjects | Bank capital Capital assets Composite indices Cooperation Correlation analysis Cultural Capital Data envelopment analysis Economic indices Economic sociology Efficiency metrics GDP Gross Domestic Product Happiness History, theory and methodology Human Geography Indicators International comparisons Karnofsky performance status Methodology Methodology (Data Analysis) Microeconomics Natural capital OECD Per capita Performance evaluation Public Health Quality of Life Research Social research Social Sciences Sociology Sociology of economy and development Standard of living. Income Studies Wealth Well Being Wellbeing World Bank |
title | Measuring World Better Life Frontier: A Composite Indicator for OECD Better Life Index |
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