Browsing by Subject "Income inequality"

Now showing 1 - 4 of 4
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    Do economic recessions cause inequality to rise?
    (Taylor & Francis Group, 2019) Camacho, Maximo; Palmieri, Gonzalo; Métodos Cuantitativos para la Economía y la Empresa
    We use a local projection approach to analyze the effect of economic recessions on income inequality in a comprehensive sample of 43 countries from 1960 to 2016. Although we consider both business-cycle and growth-cycle recessions, we fail to find evidence of significant positive impacts of economic downturns on income distribution, once controls are added to the model. However, we do find important differences across countries, which mainly depend on the degree of economic development.
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    Evaluating OECD’s main economic indicators at anticipating recessions
    (Wiley, 2020-05-31) Camacho, Maximo; Palmieri, Gonzalo; Métodos Cuantitativos para la Economía y la Empresa
    Using receiver operating characteristic (ROC) techniques, we evaluate the predictive content of the monthly main economic indicators (MEI) of the Organization for Economic Co-operation and Development (OECD) for predicting both growth cycle and business cycle recessions at different horizons. From a sample that covers 123 indicators for 32 OECD countries as well as for Brazil, China, India, Indonesia, the Russian Federation, and South Africa, our results suggest that the OECD's MEI show a high overall performance in providing early signals of economic downturns worldwide, albeit they perform a bit better at anticipating business cycles than growth cycles. Although the performance for OECD and non-OECD members is similar in terms of timeliness, the indicators are more accurate at anticipating recessions for OECD members. Finally, we find that some single indicators, such as interest rates, spreads, and credit indicators, perform even better than the composite leading indicators.
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    Evaluating the relationship between income inequality, renewable energy and energy poverty in the V4 countries
    (Elsevier, 2024-06-20) Simionescu, Mihaela; Cifuentes Faura, Javier; Ciencia Política, Antropología Social y Hacienda Pública; Facultad de Economía y Empresa
    The European Union has prioritized addressing energy poverty, as outlined in the "Clean Energy for all Europeans Package". The recent international context dominated by the COVID-19 pandemic and Russia war in Ukraine, have exacerbated this issue because of the substantial energy prices growth. Since eradicating energy poverty necessitates long-term policy implementation, the primary objective of this study is to evaluate the impact of income inequality and other economic and social factors (output per capita, renewable energy use) on energy poverty as measured by three indicators (total utility bill arrears, utility bill arrears for households with dependent children, population unable to maintain adequate). The findings based on mean group estimators for the V4 (Poland, Hungary, Czech Republic, Slovakia) countries from 2005 to 2022 suggest that income inequality, proxied by the Gini index, exacerbates energy poverty. However, sustainable economic growth has the potential to alleviate energy poverty. Policy recommendations include reducing income inequality, reforming renewable energy policies, to encourage the development of renewable energy sector and green industries.
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    Evaluation of the efficiency of european health systems using fuzzy data envelopment analysis
    (MDPI, 2021-09-26) Gómez Gallego, Juan Cándido; García García, Javier Fernándo; Faura Martínez, Úrsula; Gómez Gallego, María; Economía Aplicada
    Abstract: Many studies that assess efficiency in health systems are based on output mean values. That approach ignores the representativeness of the average statistic, which can become a serious problem in estimation. To solve this question, this research contributes in three different ways: the first aim is to evaluate the technical efficiency in the management of European health systems considering a set of DEA (Data Envelopment Analysis) and FDEA (Fuzzy Data Envelopment Analysis) models. A second goal is to assess the bias in the estimation of efficiency when applying the conventional DEA. The third objective is the evaluation of the statistical relationship between the bias in the efficiency estimation and the macroeconomic variables (income inequality and economic freedom). The main results show positive correlations between DEA and FDEA scores. Notwithstanding traditional DEA models overestimate efficiency scores. Furthermore, the size of the bias is positively related to income inequality and negative with economic freedom in the countries evaluated.