Showing papers in "Social Indicators Research in 2021"

The Impact of Socio-economic and Environmental Sustainability on CO2 Emissions: A Novel Framework for Thirty IEA Countries

Abstract: The extent to which socio-economic factors other than income and household size are associated with household CO2 emissions and whether associations vary across emission domains remains contested in the literature. We explore the impact of socio-economic and environmental sustainability indicators on CO2 emissions in the presence of combustible renewables, and the economic growth of thirty International Energy Agency (IEA) member countries. We develop a comprehensive empirical analysis using panel data and apply advanced econometric techniques for the period from 1995 to 2018. The panel co-integration analysis indicates long-run relationships among the variables. In addition, augmented mean group analysis and common correlated effects mean group analyses explain that environmental sustainability reduces CO2 emissions in the short run. Findings of fully modified least square estimates and long-run dynamic least squares estimates confirm that socio-economic sustainability increases CO2 emissions and environmental sustainability decreases them. The results of Dumitrescu and Hurlin Granger causality analysis reveal that combustible renewables, environmental sustainability, and economic growth bidirectionally Granger cause CO2 emissions, but socio-economic sustainability unidirectional Granger causes environmental quality. Policymakers in the IEA economies are encouraged to establish policies that promote a sustained lifestyle, ecological awareness, clean technological innovations, limit CO2 emissions, ecological trade-offs, and CO2 emissions ceilings to avoid rebound effects and limit environmental degradation. The study’s limitations are discussed, and useful directions for future research in the area are proposed.

Trust in Government Actions During the COVID-19 Crisis.

Abstract: The worldwide COVID-19 pandemic puts countries and their governments in an unprecedented situation. Strong countermeasures have been implemented in most places, but how much do people trust their governments in handling this crisis? Using data from a worldwide survey, conducted between March 20th and April 22nd, 2020, with more than 100,000 participants, we study people's perceptions of government reactions in 57 countries. We find that media freedom reduces government trust directly as well as indirectly via a more negative assessment of government reactions as either insufficient or too strict. Higher level of education is associated with higher government trust and lower tendency to judge government reactions as too extreme. We also find different predictors of perceived insufficient reactions vs. too-extreme reactions. In particular, number of COVID-19 deaths significantly predicts perceived insufficient reactions but is not related to perceived too-extreme reactions. Further survey evidence suggests that conspiracy theory believers tend to perceive government countermeasures as too strict.

Energy Poverty and Low Carbon Just Energy Transition: Comparative Study in Lithuania and Greece

Abstract: EU has set ambitious commitment to achieve low carbon energy and economy transition up to 2050. This low carbon transition means sustainable energy development path based on renewable energy sources and first of all should address the energy poverty vulnerability and justice issues. The main goal of the paper is to develop indicators framework for assessing low carbon just energy transition and to apply this framework for analysis how climate change mitigation policies in households targeting enhancement of energy renovation of residential buildings and promotion of the use of micro-generation technologies and other policies are affecting household’s energy poverty and vulnerability in selected countries: Lithuania and Greece. This framework allows to assess three main dimensions of sustainable energy development: environmental, social and economic. The paper provides policy recommendations how to deal with just low carbon energy transition which means addressing energy poverty issues during moving to 100% renewables in power generation based on performed case studies.

Measuring Sustainable Development by Non-aggregative Approach

Abstract: The paper deals with the issue of sustainable development, considering the three dimension that traditionally define the phenomenon: economy, environment and society. By using data from the European Foundation for the Improvement of Living and Working Conditions (Eurofound), which provide information on the perception of the sustainable development in the European countries. We want to analyse the situation of European countries by providing synthetic measures for each dimension of sustainable development. In doing this, we adopted two different methods of synthesis a non-aggregative approach, based on the theory of the partially ordered set. To test the validity and consistency of the measurement obtained, the results will be compared with those obtained by applying some of the most common aggregative methods.

Higher-Order PLS-PM Approach for Different Types of Constructs

Abstract: Partial least squares path modeling (PLS-PM) has become very popular in recent years, for measuring concepts that depend on different aspects and that are based on different types of relationships. PLS-PM represents a useful tool to explore relationships and to analyze the influence of the different aspects on the complex phenomenon analyzed. In particular, the use of higher-order constructs has allowed researchers to extend the application of PLS-PM to more advanced and complex models. In this work, our attention is focused on higher-order constructs that include reflective or formative relationships. Even if the dispute between formative models and reflective models is not exactly recent, it is still alive in current literature, for the most part within the context of structural equation models. This paper focuses attention on theoretical and mathematical differences between formative and reflective measurement models within the context of the PLS-PM approach. A simulation study is proposed in order to show how these approaches fit well in different modeling situations. The approaches have been compared using empirical application in a sustainability context. The findings from the simulation and the empirical application can help researchers to estimate and to use the higher-order PLS-PM approach in reflective and formative type models.

Synthesis of Multi-indicator System Over Time: A Poset-based Approach

Abstract: In recent years, sustainable development has become one of the main issues of scientific and institutional debate. The literature on this concept is wide and often presents conflicting positions. This leads to considering sustainable development as a contested concept. The growing interest and importance of this topic has also led to an increasing focus on the aspect of its measurement. Dealing with the measurement of complex phenomena, like sustainable development, means dealing with synthesis. The traditional and dominant approach to the synthesis of multi-indicator systems of cardinal variables is the use of the aggregative-compensative approach. Despite its success, this approach presents a series of critical issues. In this paper, we propose a method of synthesizing multi-indicator systems over time based on the Partial Order Theory. Applying and comparing the method we proposed and an aggregative method, the Adjusted Mazziotta–Pareto Index, to one of the 15 sustainable development goals, we highlight the strengths of the new methodological proposal.

Does Financial Development Reduce the Poverty Gap

Abstract: Financial development may affect poverty directly and indirectly through its impact on income inequality, economic growth, and financial instability. Previous studies do not consider all these channels simultaneously. To proxy financial development, we use the ratio of private credit to GDP or an IMF composite measure. Our preferred measure for poverty is the poverty gap, i.e. the shortfall from the poverty line. Our fixed effects estimation results for an unbalanced panel of 84 countries over the 1975–2014 period suggest that financial development does not have a direct effect on the poverty gap. However, as financial development leads to greater inequality, which, in turn, results in more poverty, financial development has an indirect effect on poverty through this transmission channel. Only if we use poverty lines of $3.20 or $5.50 (instead of $1.90 a day as in our baseline model) to define the poverty gap, we find that economic growth reduces poverty. This implies that in those cases the overall effect of financial development on poverty may be positive or negative, depending on which indirect effect, i.e. that of income inequality or growth, is stronger. Financial instability does not seem to affect the poverty gap. These results are consistent across various robustness checks.

Economic Complexity and Income Inequality: Does Country Risk Matter?

Abstract: This research sets out to determine the nexus among economic complexity (ECI; which reflects a country’s productivity), income inequality, and country risk and whether country risk affects the complexity-inequality nexus. By applying balanced panel data of 43 countries from 1991 to 2016 to a data-driven econometric methodology-finite mixture model, we provide fresh insight into this relationship from the perspective of country risk. The results indicate that the two-group finite mixture model is able to best fit our data, and that increasing economic complexity has no impact on income inequality in group A, whereas improving the structure of productivity mitigates the income gap in group B. Furthermore, country risk and the subcomponents of the former (i.e., economic risk, financial risk, and political risk) all exert effects on the complexity-inequality nexus. Specifically speaking, an increase in ECI is associated with more equal income distribution in a country with low country risk, while the improvement in productive structure cannot improve an unequal income distribution in countries under high country risk. Finally, it is noteworthy that the finite mixture model also captures information about the transformation of this nexus, with evidence demonstrating that 5 countries experience a variation in their complexity-inequality relationship over the sample period.

Sustainable Tourism as a Driving force of the Tourism Industry in a Post-Covid-19 Scenario.

Abstract: The tourism industry is probably one of the most affected by the crisis caused by Covid-19. It is the responsibility of politicians, tourism professionals and researchers to look for solutions to revive this important industry. This article shows how the development of Sustainable Tourism can help in the sustenance of the tourism industry, since one of the premises on which Sustainable Tourism is based is the non-overcrowding of tourist destinations (essential factor in the current context). Considering this argument and the existing regulations on lockdown rules, social distancing and meet up, it is considered that the practices in Sustainable Tourism can become a potential solution to stimulate tourist movements and help the revival of the tourism industry. Therefore, more specifically, the main objective of this article is to know tourist´s perception among about Sustainable Tourism and to determine which factors help its development. In this sense, the use of structural equation models in a research of 308 tourists has determined how factors related to the tourists’ attitude, motivation and perceived benefits provided by the development of Sustainable Tourism increase the intention to consume this type of tourism.

Socio-economic Drivers of Food Security among Rural Households in Nigeria: Evidence from Smallholder Maize Farmers

Abstract: Issues relating to food availability, accessibility/affordability, and food utilization remain paramount among different stakeholders such as policymakers and academics. Using data from 250 maize farming households in Nigeria, the study used Foster–Greer–Thorbecke and probit regression model to investigate the factors determining households food security. The food insecurity measure shows that 23.2% points of the households express the incidence of food insecurity while 5.5% points and 1.8% points were found to have depth and severity of food insecurity, respectively. After controlling for households’ socio-economic and demographic characteristics, the probit regression model suggested that, among others, value of output sold, education, credit access and participation in government safety nets program significantly influenced food security among the maize farmers in the study area. Based on our findings, effort should be intensified to enhance the productivity of land through improved production practices. There should be high-level awareness that will increase farmers’ participation in safety net programs. Thus, government at all levels (local, state, and federal) should have adequate budget allocation to this course in order to improve the livelihood outcomes of the farming households.

Convergence Between Developed and Developing Countries: A Centennial Perspective

Abstract: Are countries at a low level of socio-economic development catching up with developed countries over time or rather falling further behind? Existing work on the subject is not conclusive, partially due to methodological differences. The aim of the paper is to carry out a broader analysis with longer time series and a more diverse set of indicators. The study divides countries of the world into 21 developed "benchmark" countries and 156 developing countries. The distance between the benchmark and developing countries is measured using the "time lags" method, applied here to nine indicators covering topics such as the economy, health, education and the environment. The study further utilizes a probabilistic approach to extrapolate missing historical data for developing countries, so that the analysis can cover a full century starting in 1920 and ending with short-term projections to year 2020. The study finds that a majority of developing countries, and the population-weighted developing world as a whole, has reduced its lag in most indicators between 1920 and 2020. Progress was unevenly distributed, with East Asian and European countries converging the most with the benchmark, while most African countries have diverged along with some American ones. Catch-up in education attainment and life expectancy has been more successful than in infant survival rate, GDP per capita or technology adoption. The findings are put in context of United Nations' Sustainable Development Goals, showing how the time lag method could improve setting targets for some of the goals. Further, time lags are used to analyze the current demographic, economic and political situation of developing countries, identifying opportunities and risks for future catch-up with developed countries.

Stay at Home! Governance Quality and Effectiveness of Lockdown.

Abstract: In order to control the spread of the COVID-19 pandemic, during the first wave of the pandemic numerous countries decided to adopt lockdown policies. It had been a considerable time since such measures were last introduced, and the first time that they were implemented on such a global scale in a contemporary, information intensive society. The effectiveness of such measures may depend on how citizens perceive the capacity of government to set up and implement sound policies. Indeed, lockdown and confinement policies in general are binding measures that people are not used to, and which raise serious concerns among the population. For this reason governance quality could affect the perception of the benefits related to the government’s choice to impose lockdown, making citizens more inclined to accept it and restrict their movements. In the present paper we empirically investigate the relation between the efficacy of lockdown and governance quality (measured through World Governance Indicators). Our results suggest that countries with higher levels of government effectiveness, rule of law and regulatory quality reach better results in adopting lockdown measures.

Multidimensional Energy Poverty in Pakistan: Empirical Evidence from Household Level Micro Data

Abstract: This paper estimates household level incidence and intensity of multidimensional energy poverty in Pakistan using a multidimensional energy poverty index with seven dimensions weighted based on their relative importance. Although being widely discussed in the literature as a basic human right for addressing energy access, reliable background estimates, and official statistics of national-level energy poverty are not available for Pakistan. This study thus provides necessary support in understanding energy poverty severity and the incidence with multiple dimensions. Some of the existing measurement approaches analyse multiple dimensions like lack of electricity access, access to clean cooking and heating fuels and inability to obtain sufficient and reliable amount of different energy services but are deficient in other vital dimensions. Hence, the study carried out a more comprehensive measurement with additional dimensions and indicators. Results analysing the Pakistan Social and Living Standards Measurement (PSLM) survey data for 2014–15 suggest that 55 percent of the households are multi-dimensionally energy-deprived in 30 percent of the selected dimensions in Pakistan. Robustness analysis depicts the change in multidimensional energy poverty estimates as a result of changes in energy poverty cut-off scores and weights. Results also provide insights into the underlying factors affecting multidimensional energy poverty in Pakistan.

Cross-Sectional Model-Building for Research on Subjective Well-Being: Gaining Clarity on Control Variables

Abstract: Happiness/well-being researchers who use quantitative analysis often do not give persuasive reasons why particular variables should be included as controls in their cross-sectional models. One commonly sees notions of a “standard set” of controls, or the “usual suspects”, etc. These notions are not coherent and can lead to results that are significantly biased with respect to a genuine causal relationship. This article presents some core principles for making more effective decisions of that sort. The contribution is to introduce a framework (the “causal revolution”, e.g. Pearl and Mackenzie 2018) unfamiliar to many social scientists (though well established in epidemiology) and to show how it can be put into practice for empirical analysis of causal questions. In simplified form, the core principles are: control for confounding variables, and do not control for intervening variables or colliders. A more comprehensive approach uses directed acyclic graphs (DAGs) to discern models that meet a minimum/efficient criterion for identification of causal effects. The article demonstrates this mode of analysis via a stylized investigation of the effect of unemployment on happiness. Most researchers would include other determinants of happiness as controls for this purpose. One such determinant is income—but income is an intervening variable in the path from unemployment to happiness, and including it leads to substantial bias. Other commonly-used variables are simply unnecessary, e.g. religiosity and sex. From this perspective, identifying the effect of unemployment on happiness requires controlling only for age and education; a small (parsimonious) model is evidently preferable to a more complex one in this instance.

Restarting "Normal" Life after Covid-19 and the Lockdown: Evidence from Spain, the United Kingdom, and Italy.

Abstract: In this article, we examine the expectations of the economic outlook, fear of the future, and behavioural change during the first Covid-19 wave, for three European countries (Spain, the United Kingdom, and Italy) that have been severely hit. We use a novel dataset that we collected to monitor the three countries during the crisis. As outcome variables, we used expectations (e.g., economic outlook, labour market situation, recovery), fear (e.g., scenario of new outburst, economic depression, restriction to individual rights and freedom), and behavioural change across the following dimensions: savings, cultural consumption, social capital, and risky behaviour. We provide descriptive evidence that is representative of the population of interest, and we estimate the impact of exposure to shock occurred during the crisis on the same outcome variables, using matching techniques. Our main findings are the following: we detected systematically negative expectations regarding the future and the recovery, majoritarian fears of an economic depression, a new outbreak, and a permanent restriction on freedom, a reduction in saving and in social capital. Exposure to shocks decreased expected job prospects, increased withdrawal from accumulated savings, and reduced contacts with the network relevant to job advancement, whereas it had inconclusive effects over fears.

Poverty Vulnerability and Poverty Causes in Rural China

Abstract: Data from China’s Ministry of Civil Affairs show that more than 75% of the country’s poor live in rural areas. Therefore, to achieve the goal of poverty alleviation by 2020, the problem of rural poverty requires urgent attention. Based on the entropy method, we herein assess the level of poverty vulnerability in each province in China to guide the direction of future poverty alleviation efforts. In addition, based on the logarithmic mean Divisia index method and the grey relational analysis method, we studied the effects and contributions of rural poverty incidence, rural agricultural outcomes per capita, the proportion of agricultural outcomes, gross domestic product per capita, and total population on rural poverty. We found that, when it comes to natural resources, human resources, physical assets, financial assets, and social resources, the most vulnerable areas are concentrated in western China. We suggest the government pay close attention to the interests of individuals in this region to balance economic development, distribute the benefits of economic development to the rural poor, and narrow the income gap between urban and rural areas.

Intergenerational Support and Life Satisfaction of Older Parents in China: A Rural–Urban Divide

Abstract: In the past few decades, Chinese families have experienced unprecedented economic growth. In addition to growth, public policies have changed and developed, internal migration has rapidly increased, and social conditions have generally evolved. Living arrangements in particular have transformed, which likely affects the expectations and preferences of older parents to rely on their children. We use the first two waves of the China Health and Retirement Longitudinal Study (CHARLS), a nationally representative sample of older adults in China, to examine the relationship between intergenerational support and life satisfaction in both rural and urban China. In rural villages, we find that living with grandchildren is associated with a higher level of life satisfaction; this is true even in households without parents (i.e., skip-generation households). Higher life satisfaction is also attributable to receiving instrumental support (i.e., help with self-care and household tasks) from children and exchanging financial and emotional support with them. In urban neighborhoods, in contrast, living in a skip-generation household is associated with a lower level of life satisfaction, and only one type of functional support from children is beneficial for older parents’ life satisfaction—instrumental support. Our findings indicate that there is a rural–urban divide in the relationships between life satisfaction and intergenerational support in contemporary China and suggest that development has weakened historical relationships in both rural and urban areas.

Drying Climates and Gendered Suffering: Links Between Drought, Food Insecurity, and Women’s HIV in Less-Developed Countries

Abstract: HIV/AIDS represents the leading cause of death among women of reproductive age globally, and gender inequalities in the burden of HIV/AIDS are most pronounced in poorer countries. Drawing on ideas from feminist political ecology, we explore linkages between suffering from drought, food insecurity, and women’s vulnerability to HIV. Using data from 91 less-developed countries, we construct a structural equation model to analyze the direct and indirect influence of these factors, alongside other socio-economic indicators, on the percentage of the adult population living with HIV that are women. We find that droughts are significant in shaping gender inequalities in the HIV burden indirectly through increased food insecurity. We draw on prior research to argue that due to gendered inequalities, food insecurity increases women’s vulnerability to HIV by intensifying biological susceptibilities to the disease, reducing access to social and health resources, and motivating women to engage in risky sexual behaviors, such as transactional sex. Overall, our findings demonstrate that droughts serve as an important underlying factor in promoting HIV transmission among vulnerable women in poor countries, and that food insecurity is a key mechanism in driving this relationship.

Effect of COVID-19 on Household Food Insecurity and Poverty: Evidence from Ghana.

Abstract: Following the outbreak of COVID-19 and its heavy toll on the global community and humanity, a fierce debate on the pandemic and Sustainable Development Goals (SDGs) performance nexus has emerged. While the literature on this subject remains highly contested, evidence within the Ghanaian contest is sparse. Thus, we present micro-level evidence on how COVID-19 poses a threat to hunger and poverty as SDGs in Ghana. Precisely, we examined the effect of COVID-19 on households' food insecurity and poverty and further analysed gender and locational sub-samples for differential effects. Data on 3905 households were obtained via concurrent online survey and telephone interviews. The results indicate that, on several occasions, a significant number of the sampled households (57.76%) did not get enough food to eat due to the pandemic. The proportion of households that went on several times without clean water for home use and access medicines/medical treatments were 50.52% and 52.22%, respectively. About 60.72% of the sampled households affirmed that, on several times, they did not have enough income due to the pandemic. At the same time, the share of households that suffered food insecurity due to the pandemic was 69.04%. Instrumenting for COVID-19 using distance to the affected communities, we find that a standard deviation increase in COVID-19 is associated with a rise of 0.232 and 0.289 standard deviations in poverty and food insecurity, respectively. Our results are robust to alternative estimation approaches to addressing the endogeneity of COVID-19 and other sensitivity checks. We conclude that Ghana would need to develop a new spectrum of gender- and location-sensitive policies that engender social inclusion as a conduit to expediate the attainment of zero poverty and hunger.

Mapping Poverty of Latin American and Caribbean Countries from Heaven Through Night-Light Satellite Images

Abstract: The adoption of the Sustainable Development Goals in September 2015 by the United Nations General Assembly is calling National Statistics Offices worldwide to underpin a data revolution. Indeed, these organizations should extend both the scope and disaggregation of the data traditionally produced, and measure new economic, social and environmental phenomena, leaving none behind. There is a growing consensus that, in the digital era, earth observation might strengthen traditional data sources and statistics in monitoring sustainable well-being, facilitating the transformative agenda that official statisticians should implement in the forthcoming years. This research analyses how earth observation, under the form of observable nightlights, might help in mapping poverty data, thus filling in existing gaps of official statistics for a core sustainable development indicator. The empirical analyses show that there are indeed considerable advantages from the use of satellite remote sensing information, the so-called ‘views from the above’, in facing the increasing demand from policy makers and the public at large. The analysis shows that publicly and freely available information from the space might be a key source of information to derive—through an unbalanced fractional panel-data model—spatially disaggregated and continuous-time estimations of poverty gap, headcount, and Gini indices for 20 Latin American and Caribbean countries.

Social Media and Twitter Data Quality for New Social Indicators

Abstract: Social media represent an excellent opportunity for the construction of timely socio-economic indicators. Despite the many advantages of investigating social media for this purpose, however, there are also relevant statistical and quality issues. Data quality is an especially critical topic. Depending on the characteristics of the social media a researcher is using, the problems that arise related to errors are different. Thus, no one unique quality evaluation framework is suitable. In this paper, the quality of social media data is discussed considering Twitter as the reference social media. An original quality framework for Twitter data is introduced. A reformulation of the traditional quality dimensions is proposed, and the new quality aspects are discussed. The main sources of errors are identified, and examples are provided to show the process of finding evidence of these errors. The conclusion affirms the importance of using a mixed methods approach, which involves incorporating both qualitative and quantitative evaluations to assess data quality. A collection of good practices and proposed indicators for quality evaluation is provided.

Social Exclusion and Anti-Immigration Attitudes in Europe: The mediating role of Interpersonal Trust

Abstract: Managing immigration is a challenge at the political, economic, and social levels Clarifying the social psychological antecedents behind the onset of negative attitudes towards immigrants might help overcome this challenge The present study investigates the relationships between people’s experience of social exclusion, feelings of generalized interpersonal trust, and anti-immigrant attitudes across 23 European countries We used data from the European Social Survey 8 (2016), employing a representative sample of the European population A 1–1–1 multilevel mediation model showed that: (a) the higher the experience of social exclusion, the lower the generalized trust towards others; (b) the experience of social exclusion related positively and directly with anti-immigration attitudes; and (c) generalized interpersonal trust mediated the relationship between experienced social exclusion and anti-immigrant attitudes so that the experience of being socially excluded reduced feelings of generalized interpersonal trust that, in turn, promoted hostile attitudes towards immigrants Taken together, these results create a platform for future research on the emergence of negative attitudes towards immigrants and factors that might facilitate the development of a climate of integration and acceptance

Development of the India Patriarchy Index: Validation and Testing of Temporal and Spatial Patterning

Abstract: While existing indices of gender equality measure the role of women’s status and position, they inadequately contextualize the broader construct of patriarchy, a social system that underlies many gender inequitable practices. An index capturing patriarchy may afford increased understanding of this social system, and may serve to complement other gender equality indices. This paper involves the development and testing of a novel composite measure, the India Patriarchy Index, to quantify the social and ideological construct of patriarchy using empirical data on family structure and gender roles. Using data from India’s National Family Health Survey, we develop an India Patriarchy Index to measure gendered social positioning in families based on sex by age, patrilocality, sex ratio imbalance among offspring, and gendered economic roles. Psychometric testing demonstrates good internal reliability and construct validity of this index, with validity indicated by its association with three gender equality indices used in India. Spatial and temporal analyses further indicate much state-level variation in India Patriarchy Index scores as well as slow change on this indicator over time, based on time trend analyses from 1992–93 to 2015–16. Results demonstrate the utility of the India Patriarchy Index to measure and track gender equality progress in India.

The Human Development Index with Multiple Data Envelopment Analysis Approaches: A Comparative Evaluation Using Social Network Analysis

Abstract: The objective of this work is to use multiple Data Envelopment Analysis (DEA)/Benefit of the Doubt (BoD) approaches for the readjustment and exploitation of the Human Development Index (HDI). The HDI is the leading indicator for the vision of “development as freedom”; it is a Composite Index, wherein three dimensions (income, health, and education), represented by four indicators, are aggregated. The DEA-BoD approaches used in this work were: the traditional BoD; the Multiplicative BoD; the Slacks Based Measure (SBM) BoD; the Range Adjusted Model (RAM) BoD; weight restrictions; common weights; and tiebreaker methods. These approaches were applied to raw and normalized HDI data from 2018, to generate 40 different rankings for 189 countries. The resulting indexes were analyzed and compared using Social Network Analysis (SNA) and information derived from DEA itself (slacks, relative contributions, targets, relative targets and benchmarks). This paper presents useful DEA derived indexes that could be replicated in other contexts. In addition, it contributes by presenting a clearer picture of the differences between BoD models and offering a new way to appreciate the world's human development panorama.

Mobile Internet Use and Multidimensional Poverty: Evidence from A Household Survey in Rural China

Abstract: Although reducing poverty has become an important issue for rural development in China, few studies have analyzed the role of mobile Internet use in multidimensional poverty. To fill this gap, this study investigated the impact of mobile Internet use on multidimensional poverty, using data collected from a household survey in rural China. Because households generally decide whether to use mobile Internet by themselves, an endogenous switching regression model was employed to control for potential selection bias. In total, 9.63% of the households were identified as multidimensionally poor and the adjusted multidimensional poverty incidence was 5.47%. The results also showed that mobile Internet use has a significant negative impact on multidimensional poverty. Further, we provide evidence of heterogeneity in the effect of mobile Internet use across regions. These findings highlight the importance of mobile Internet use in multidimensional poverty reduction strategies for rural households.

Financial Development, Technological Innovation and Income Inequality: Time Series Evidence from Turkey

Abstract: The main aim of the study is to analyze the link between technological innovation and income inequality for Turkey in terms of financial Kuznets curve (FKC) hypothesis. The study uses time-series data from 1987 to 2018. We employ the Hatemi-J cointegration, ARDL bounds test and VECM Granger causality techniques to investigate the relations between the variables. We also employ the DOLS, FMOLS and CCR approaches to estimate the long-run parameters. The results reveal that the series are cointegrated under the structural breaks. The results also reveal that the FKC is valid for Turkish economy in the long run. Technological innovation positively affects income inequality while economic growth is negatively linked with income inequality. There exists a bi-directional causal linkage between financial development and income inequality. Technological innovation and income inequality cause each other. In addition, economic growth causes income inequality. Empirical results suggest a twofold policy implication: i) improvement of the financial system and ii) to eliminate the adverse effects of technological innovations on income distribution.

A Distributional Analysis of Uni-and Multidimensional Poverty and Inequalities in Ethiopia

Abstract: This study analyzes uni-and multidimensional poverty and inequalities in rural and small towns in Ethiopia Unlike the unidimensional measure, the multidimensional measure of poverty shows all the channels through which poverty may manifest itself; it also shows the extent of deprivation The analysis uses 6 dimensions with 14 indicators to construct a multidimensional index of poverty and inequalities using Ethiopian Households’ Socioeconomic Survey dataset The study also uses multiple correspondence analyses for determining relative weights in computing a multidimensional index and conducts a stochastic dominance analysis of distribution of poverty for different population segments The paper sheds light on the degree of inequalities in consumption expenditure and multidimensional deprivations In addition, it also compares the degree of poverty using the conventional measure of poverty and the multidimensional approach It also examines the determinants of household poverty status using both unidimensional and multidimensional measures using the logit model The results show that the intensity, severity, and depth of poverty varies substantially across the 2 measures The unidimensional measure of poverty shows that 36 percent of the households were poor as compared to 46 percent multidimensionally poor households Moreover, demographic, regional, and household heads’ characteristics also affect households’ poverty status

Does Financial Inclusion Diminish Poverty and Inequality? A Panel Data Analysis for Latin American Countries

Abstract: Despite great developmental efforts in recent decades, Latin America still presents high levels of poverty and inequality when compared to developed nations. As explored widely in the literature, one potential instrument to diminish these issues is financial inclusion, including the access and usage of financial services by all people. Specifically, this paper verifies if financial inclusion and technology adoption decrease the poverty headcount ratio and the Gini index (i.e., inequality) of 13 Latin America countries (Argentina, Bolivia, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Panama, Paraguay, Peru, and Uruguay). To perform such analysis, an unbalanced panel dataset was built, and the Feasible Generalized Least Squares (FGLS) and the Limited Information Maximum Likelihood (LIML) techniques were employed. The results suggest that, in accordance with previous studies, financial inclusion is a powerful tool to tackle poverty and inequality. Additionally, the combined effects of financial inclusions and technology (i.e., mobile use) are also capable of decreasing the poverty and inequality levels. We discuss the policy implications of our findings and suggest a future research agenda.

Measuring Sustainable Development Using an Extended Hellwig Method: A Case Study of Education

Abstract: Benchmarking the analysis of countries' performance in terms of sustainable development helps to understand the success factors of countries that over perform and to target priority issues of others with lower performance. However, assessing sustainable development comes with methodological challenges, including indicator standardization, aggregation and weighting. Our study significantly contributes to the measure of sustainable development by providing a new approach based on an extended Hellwig method. After describing the main limitations of existing methodologies, this paper's aim is twofold. First, we show that the proposed analytical framework allows for comparing the sustainable performance of EU countries on the national level. The extended Hellwig method takes into consideration EU targets and/or national targets in building patterns of development. Second, this framework is tested as a part of the evaluation of the implementation of the Europe 2020 strategy in the education area. The results obtained using the extended Hellwig method were compared with those obtained by means of the Education Index, TOPSIS and Ward technique. Our analysis showed the significant disparities in the implementation of the Europe 2020 strategy recommendations in the education area in 2015.

Drivers of Youth Labour Market Integration Across European Regions

Abstract: Territorial disparities and youth labour markets have been often considered as separated themes, due to challenges in data availability. Comparative regional or sub-regional research on youth labour market integration (YLMI) have been therefore scarce. In this article, we address this gap by presenting a composite measure of YLMI that covers a wide range of indicators and sheds light on the EU territorial divide of young peoples’ opportunities at regional level. In order to build the YLMI index, we use benefit-of-the-doubt-weighting, a seminal methodology on composite indicators (CI) that combines sequence with conditional weights based on the range of each sub-indicator. To proof the usefulness of YLMI, we analyze the evolution of regional YLMI in the EU before and after the economic crisis; and the trends of homogenization or differentiation across EU territories. Furthermore, we investigate to what extent employment conditions, skills supply and technological resources explain cross-regional variations in YLMI.