240 research outputs found
Ecological Resources Depletion, Inequality and Poverty
In this paper, I develop a part of what I have been calling an ecological global political economy approach. I motivate the discussion by focusing on the links between ecological crisis and income distribution. I have chosen the concrete context of Bangladesh, a country likely to be affected severely by global warming and climate change to illustrate through simulation the theoretical results. Using a fairly neutral and conservative assumption of uniform distribution of loss it can be shown axiomatically that inequality increases when effective income is considered leading to ecologically adjusted income distributions. The simulations presented here for Bangladesh demonstrate that both inequality and poverty measured by some popular indexes increase significantly under even this mild assumption and the assumption of moderate income loss
Normative validity: the case of poverty measures
Drawing from Anna Alexandrova’s (2017) work on the measurement of well-being, I expand on what she termed “normative validity,” using poverty measures as a case study. Normative validity refers to a measure’s ability to accurately capture the moral and political aspects of its target concept. Initially, I outline its characteristics, comparing it with data-driven validity and discussing how it fits in measurement theory. I then show how researchers in poverty measurement employ various tools to ensure their measures capture the normative elements of this concept. I conclude by exploring how normative validity sheds light on the tension between normative and data-driven poverty measures
Normative validity: the case of poverty measures
Drawing from Anna Alexandrova’s (2017) work on the measurement of well-being, I expand on what she termed “normative validity,” using poverty measures as a case study. Normative validity refers to a measure’s ability to accurately capture the moral and political aspects of its target concept. Initially, I outline its characteristics, comparing it with data-driven validity and discussing how it fits in measurement theory. I then show how researchers in poverty measurement employ various tools to ensure their measures capture the normative elements of this concept. I conclude by exploring how normative validity sheds light on the tension between normative and data-driven poverty measures
ECOS 2012
The 8-volume set contains the Proceedings of the 25th ECOS 2012 International Conference, Perugia, Italy, June 26th to June 29th, 2012. ECOS is an acronym for Efficiency, Cost, Optimization and Simulation (of energy conversion systems and processes), summarizing the topics covered in ECOS: Thermodynamics, Heat and Mass Transfer, Exergy and Second Law Analysis, Process Integration and Heat Exchanger Networks, Fluid Dynamics and Power Plant Components, Fuel Cells, Simulation of Energy Conversion Systems, Renewable Energies, Thermo-Economic Analysis and Optimisation, Combustion, Chemical Reactors, Carbon Capture and Sequestration, Building/Urban/Complex Energy Systems, Water Desalination and Use of Water Resources, Energy Systems- Environmental and Sustainability Issues, System Operation/ Control/Diagnosis and Prognosis, Industrial Ecology
School-level inequality and learning achievement: measurement, theory, and analysis based on the Programme for International Student Assessment (PISA)
Exogenous socioeconomic characteristics in schools, or school socioeconomic compositional effects (SCE), heavily influence students’ cognitive and noncognitive outcomes. The influence of SCE on learning achievements varies across individuals, schools, and wider contexts. SCE reflect structural individual and societal conditions that affect people’s future lives and development. In this respect, understanding their complexity provides a greater opportunity to address disparities and enable people and societies to reach their potential.
The most common aspects studied in the academic literature are the student’s socioeconomic status (SES) and the school socioeconomic status. This thesis focuses on a less studied SCE dimension, namely within-school economic inequality (hereafter school inequality). This aggregated measure of inequality reflects the distribution of students’ household wealth in each school and provides an understanding beyond the usual SCE aspects. The presence of school inequality matters to educational and development studies and practice because it sheds further light on the role of SCE inside schools. Studying school inequality across a range of contexts enables the development of appropriate policies to address its potential influence on students’ learning outcomes.
I use data from the Programme for International Student Assessment (PISA), which measures learning outcomes as the Reading, Mathematics and Science skills of 15-year-old students across the world. I use waves 5, 6 and 7 corresponding to years 2012, 2015 and 2018.
I focus on four aspects related to the phenomenon of school inequality: i) its measurement based on categorical data using tools provided by Item Response Theory models, which is axiomatised and validated with other inequality measurements; ii) a review of how socioeconomic inequalities affect schooling outcomes identifying four distinct academic bodies of literature, namely, difficulties in terms of access to education; the corrosive effect of inequality in the social fabric; relative deprivation and interpersonal comparisons; and, finally, social reproduction theory. Based on that, I develop a set of inferential analysis models to study the relationship between both school inequality and learning scores. I consistently find negative associations between them across the different PISA waves, model specifications and inequality measurements. I also find that school wealth interacts differently with school inequality, finding that students in wealthier schools tend to be more negatively influenced by inequality.
iii) I theorise potential channels of how school inequality affects schooling outcomes suggesting mechanisms such as social isolation, interpersonal comparisons and anomie. By understanding schools as socialising spaces and based on a social cohesion framework, I study how certain attitudes operate as mitigating resources – in terms of compensation, moderation and mitigation – of the negative consequences of inequality on learning scores. However, the negative effects remain in place after the inclusion of those explanatory variables.
iv) Finally, I develop an exploratory study addressing a theoretical and empirical trade-off between school inequality and country school segregation, showing how both factors coexist and negatively affect learning scores. Learning scores are used as a synthetic measurement of school achievement, and at the same time, are a relevant predictor of further academic advancement and economic development
A european equivalence scale for public in-kind transfers
This paper introduces a theory-based equivalence scale for public in-kind transfers, which justifies comparison of distributions of extended income (cash income plus the value of public services) between European countries. We demonstrate the usefulness of the proposed equivalence scale in an empirical analysis of the effects of public health care, long-term care, education and childcare expenditure on estimates of income inequality and poverty for 24 European countries. The empirical results show significant effects of public in-kind transfers on the level of income inequality and poverty for all countries. Over the period 2006–2018, inequality and poverty estimates display rather different trends across European countries.This work has been supported by the second Network for the analysis of EU-SILC (Net-SILC2) coordinated by CEPS/INSTEAD (Luxembourg). Financial support from Eurostat, the Norwegian Ministry of Finance, and the Norwegian Research Council (grant number 261985) is gratefully acknowledged
A multivariate extension of the Lorenz curve based on copulas and a related multivariate Gini coefficient
We propose an extension of the univariate Lorenz curve and of the Gini coefficient to the multivariate case, i.e., to simultaneously measure inequality in more than one variable. Our extensions are based on copulas and measure inequality stemming from inequality in every single variable as well as inequality stemming from the dependence structure of the variables. We derive simple nonparametric estimators for both instruments and apply them exemplary to data of individual income and wealth for various countries
Social Mobility in Developing Countries
Social mobility is the hope of economic development and the mantra of a good society. There are disagreements about what constitutes social mobility, but there is broad agreement that people should have roughly equal chances of success regardless of their economic status at birth. Concerns about rising inequality have engendered a renewed interest in social mobility—especially in the developing world. However, efforts to construct the databases and meet the standards required for conventional analyses of social mobility are at a preliminary stage and need to be complemented by innovative, conceptual, and methodological advances. If forms of mobility have slowed in the West, then we might be entering an age of rigid stratification with defined boundaries between the always-haves and the never-haves—which does not augur well for social stability. Social mobility research is ongoing, with substantive findings in different disciplines—typically with researchers in isolation from each other. A key contribution of this book is the pulling together of the emerging streams of knowledge. Generating policy-relevant knowledge is a principal concern. Three basic questions frame the study of diverse aspects of social mobility in the book. How to assess the extent of social mobility in a given development context when the datasets by conventional measurement techniques are unavailable? How to identify drivers and inhibitors of social mobility in particular developing country contexts? How to acquire the knowledge required to design interventions to raise social mobility, either by increasing upward mobility or by lowering downward mobility
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