New Indicators and Measurement Methods for Welfare in the Global Economy Era

This study discusses the inadequacy of GDP alone as a measure of welfare in the global economic age and examines alternative welfare indicators and measurement methods. This study, which discusses the human development index (HDI), the inequality adjusted human development index (I-HDI), the gender inequality index (GII), the multidimensional poverty index (MPI), the social progress index (SPI), the happy planet index (HPI), the better life index (BLI), the Legatum prosperity index(LPI), the human capital index (HCI), and the ecological footprint (EF) methods, shares the country rankings of these methods and reveals the differences in the results depending on the method. It also draws attention to the differences between the economic size and welfare level by sharing the rankings of the world's 10 largest economies in alternative methods. In addition, the study examines the obstacles to the inability to establish a complete, precise, and generally accepted method of measuring welfare.

The Cross-sectional Average Inequality in Lifespan (CAL†): A Lifespan Variation Measure That Reflects the Mortality Histories of Cohorts

Lifespan variation is a key metric of mortality that describes both individual uncertainty about the length of life and heterogeneity in population health. We propose a novel and timely lifespan variation measure, which we call the cross-sectional average inequality in lifespan, or CAL†. This new index provides an alternative perspective on the analysis of lifespan inequality by combining the mortality histories of all cohorts present in a cross-sectional approach. We demonstrate how differences in the CAL† measure can be decomposed between populations by age and cohort to explore the compression or expansion of mortality in a cohort perspective. We apply these new methods using data from 10 low-mortality countries or regions from 1879 to 2013. CAL† reveals greater uncertainty in the timing of death than the period life table–based indices of variation indicate. Also, country rankings of lifespan inequality vary considerably between period and cross-sectional measures. These differences raise intriguing questions as to which temporal dimension is the most relevant to individuals when considering the uncertainty in the timing of death in planning their life courses.

Ranking and Performance of Indian Universities

ABSTRACT Almost every communication media made the news of three Indian institutions appearing in Quacquarelli Symonds (QS) World Rankings 2022 a headline, highlighting the importance of finding a place in the coveted ranking. Such rankings provide Higher Education Institutions (HEIs) a reason to pursue excellence in their operations. These rankings are also in the interests of the students and other stakeholders. National Institutional Ranking Framework (NIRF), also known as India Ranking, was introduced in 2015 by the Ministry of Education, Government of India (erstwhile Ministry of Human Resource Department). NIRF outlines a methodology to rank institutions across the country. Rankings obtained in the India Ranking 2017-20 have been analyzed in this study to assess the comparative performance of the top 100 universities. Statistical tests of chi square and Friedman tests show that rankings have remained consistent within the range for the top-performing universities. But, other than the top universities, there exists stiff competition for each ranking place. Overall, statistical analysis shows that rankings obtained by universities are not identical.

SOMALIA – STUDIU DE CAZ PRIVIND FRAGMENTAREA UNUI STAT OMOGEN ETNIC ŞI CONFESIONAL

Orice curs de geopolitică internă a statului începe prin a afirma că stabilitatea internă şi integritatea teritorială sunt rezultatul interacţiunii dintre forţele secesioniste, centrifuge, şi forţele unificatoare, centripete. Acelaşi curs de geopolitică mai spune că omogenitatea etnică şi confesională se înscrie în categoria celor mai puternice forţe centripete, alături de o formă cât mai rotundă a teritoriului statal, de centralitatea capitalei, de o distribuţie uniformă a infrastructurii de transport şi comunicaţii, de o distribuţie cât mai echitabilă a bogăţiei, de o puternică idee şi voinţă naţională. Somalia este un stat omogen etnic şi confesional. Mai mult, toţi aceşti etnici nu îşi arogă o altă identitate în afara celei somaleze şi cu toţii vorbesc limba somali, limba oficială a statului, alături de arabă – limba Coranului. În Somalia nu se înregistrează uriaşa diversitate lingvistică specifică altor state africane postcoloniale, nu există diferenţe cultural-civilizaționale, nu există discrepanţe majore în privinţa dezvoltării regionale şi a distribuţiei infrastructurii de comunicaţii şi transport în teritoriu. Şi, cu toate acestea, statul somalez reprezintă expresia noţiunii de stat eşuat, răvăşit de război civil, de secesionism, de piraterie maritimă, de terorism, de criminalitate organizată şi de insecuritate. În ultimii ani, Somalia a fost plasată constant în rândul celor mai periculoase destinaţii de pe glob. În prima jumătate a anului 2021, ea se situa pe locul al şaselea în clasamentul celor mai riscante destinaţii turistice, după Afganistan, Siria, Irak, Sudanul de Sud şi Yemen[i]. Care sunt cauzele secesionismului somalez şi ale prăbuşirii statului? Şi, dacă ar fi să ierarhizăm, în funcţie de intensitatea efectului, factorii secesionişti care acţionează pe teritoriul Somaliei, care ar fi ordinea acestora? [i] *** ”Most Dangerous Countries in the World”, World Population Review, https://worldpopulationreview.com/country-rankings/most-dangerous-countries, accesat la 11.07.2021.

22A Survey-Based Women's Empowerment Index for Low- and Middle-Income Countries: The SWPER Goes Global

Background In 2017, a survey-based women's empowerment index (SWPER) was proposed for African countries, including three domains: social independence, decision making and attitude to violence. We explored the applicability of the SWPER in national health surveys from countries in other world regions. Methods We used data from the latest Demographic and Health Survey for 62 low- and middle-income countries (LMICs) since 2000, and adapted the indicator so that it could be used for any LMIC. Adaptations included the exclusion of women's working status and recategorization of the household decision-making related items. We compared the loading patterns obtained from principal components analysis for each country separately with those obtained in a pooled dataset with all countries combined. Country rankings based on the score of each SWPER domain were correlated with their rankings in the Gender Development Index (GDI) and the Gender Inequality Index (GII). Results Most countries presented similar patterns regarding item loadings for the three SWPER empowerment domains. Correlations between the country-specific and global individual-level scores were 0.89 or higher for all countries. Correlations between the country rankings according to SWPER and GDI were, respectively, 0.74, 0.71 and 0.67 for social independence, decision-making, and attitude to violence domains. The correlations were equal to 0.82, 0.67, and 0.44, respectively, with GDI. Conclusions The SWPER global is a suitable common measure of women's empowerment for LMICs, addressing the need for a single consistent survey-based indicator of women's empowerment and allowing wider comparisons across countries and world regions.

Economic or Public Health? Southeast Asia’s Tackling of COVID-19 a Year Later

The world has been challenged by rapidly spreading COVID-19 outbreaks for a year now. Southeast Asian countries have had different strategies to deal with the pandemic. This review aimed to elaborate on Southeast Asian countries’ strategies in managing the trade-off between economic and public health, with further consideration of how such approaches were associated with the dynamics of the number of cases and the speed of economic recovery. This review evaluated the COVID-19 mitigation efforts spanning one year in the Southeast Asian (SEA) countries listed based on the Bloomberg COVID Resilience Ranking. As of May 24, 2021, three SEA countries (Thailand, Malaysia, and Indonesia) were chosen from the better (27th), moderate (35th), and worst (42nd) SEA country rankings. Peer-reviewed articles were obtained from Google Scholar and PubMed databases, and news articles were retrieved from GoogleNews. The data from government websites were also included. Sources were limited to those in the English and Indonesian languages that could be accessed between January 2020 and May 2021. Thailand, Malaysia, and Indonesia were found to have significantly prioritized consideration of the economy in handling the pandemic. Malaysia and Thailand had more stringent policies of imposing national lockdowns, while Indonesia had a partial lockdown. It was found that a weak pandemic response may result in substantial economic loss.

Sensitivity of excess mortality due to the COVID-19 pandemic to the choice of the mortality index, method, reference period, and the time unit of the death series

Estimating excess mortality is challenging. The metric depends on the expected mortality level, which can differ based on given choices, such as the method and the time series length used to estimate the baseline. However, these choices are often arbitrary, and are not subject to any sensitivity analysis. We bring to light the importance of carefully choosing the inputs and methods used to estimate excess mortality. Drawing on data from 26 countries, we investigate how sensitive excess mortality is to the choice of the mortality index, the number of years included in the reference period, the method, and the time unit of the death series. We employ two mortality indices, three reference periods, two data time units, and four methods for estimating the baseline. We show that excess mortality estimates can vary substantially when these factors are changed, and that the largest variations stem from the choice of the mortality index and the method. We also find that the magnitude of the variation in excess mortality can change markedly within countries, resulting in different cross-country rankings. We conclude that the inputs and method used to estimate excess mortality should be chosen carefully based on the specific research question.

The cross-sectional average inequality in lifespan (CAL†): A lifespan variation measure that reflects the mortality histories of cohorts

Lifespan variation is a key metric of mortality that describes both individual uncertaintyabout the length of life and heterogeneity in population health. We propose a novel andtimely lifespan variation measure, which we call the Cross-sectional Average Inequality in Lifespan. This new index provides an alternative perspective on the analysis of lifespan inequality by combining the mortality histories of all cohorts present in a cross-sectional approach. We demonstrate how differences in the Cross-sectional Average Inequality in Lifespan measure can be decomposed between populations by age and cohort to explore the compression or expansion of mortality in a cohort perspective. We apply these new methods using data from ten low-mortality countries from 1879 to 2013. The Cross-sectional Average Inequality in Lifespan measure reveals greater uncertainty in the timing of death than the period life table-based indices of variation indicate. Also, country rankings of lifespan inequality vary considerably between period and cross-sectional measures. These differences open intriguing questions as to which temporal dimension is the most relevant to individuals when considering the uncertainty in the timing of death in planning their life courses.