Do renewable energy and human capital facilitate the improvement of environmental quality in the United States? A new perspective on environmental issues with the load capacity factor.

Recently, countries have been making intensive efforts to alleviate the burden on the environment and to make environmental conditions sustainable. In this context, our study aims to investigate the long-term impact of renewable energy consumption (REC) and human capital (HC) by considering the load capacity factor (LCF). We also investigate the long-term impact of economic growth (Y) and non-renewable energy consumption (NREC) on the LCF. In this context, we analyze annual data for the U.S. for the period 1965-2018 using the newly developed augmented ARDL (AARDL) approach. The long-term empirical results show the following. i) Increases in Y negatively affect LCF and deteriorate environmental quality. ii) Increases in NREC negatively affect LCF and accelerate the deterioration of environmental quality. iii) REC has no significant impact on environmental quality. iv) Increases in HC support the improvement of environmental quality. The empirical results show that contrary to expectations, renewable energy consumption does not have a significant impact on environmental quality in the U.S., whereas human capital is an important factor in improving environmental quality. In this context, US policymakers should pave the way for more investment in eco-friendly renewable energy investments and human capital to establish sustainable environmental quality. Policymakers should also take steps to reduce the use of fossil fuels.

Investigation of the effect of human capital on environmental pollution: empirical evidence from Turkey.

Reducing environmental pollution is a highly important issue that must be resolved globally. Improving human capital (HC) can significantly contribute to lowering environmental pollution. Using the Fourier ADL (FADL) method, this study examines the long-term effect of HC on carbon emissions (CO2 emissions) and ecological footprint (EF) in Turkey from 1980 to 2018. In addition, the study examined the long-term effects of economic growth (GDP), financial development (FD), and globalization (KOF) on CO2 emissions and EF. According to empirical results, HC has a negative effect on both CO2 emissions and EF. Furthermore, the findings indicate that GDP and FD have a positive effect on CO2 emissions and EF, whereas KOF has no statistically significant effect on CO2 emissions and negative EF. According to the FFFF-TY causality test results, there is bidirectional causality between FD and EF and a unidirectional causality from HC to EF and from EF to KOF. This study underlines the importance of human capital in improving environmental quality in Turkey. In this context, the results of this study will assist policy makers in the development of precise policies to enhance human capital in order to improve environmental quality.

Determinants of Turkish households' out-of-pocket expenditures on three categories of health care services: A multivariate probit approach.

This study identifies the driving forces that contribute to the probabilities of incidence of out-of-pocket (OOP) expenditures by households in Turkey. Factors affecting the probability of OOP expenditures on medical products/devices/supplies (MP), outpatient services (OTS), and inpatient services (ITS) are examined using the Household Budget Survey data gathered by the Turkish Statistical Institute in 2018. The study applies the multivariate probit model. The incidence of OOP spending varied with 48.9% of the households reporting OOP expenditure on MP, 22.4% on OTS, and 25.4% on ITS. The largest probability changes were associated with household disposable annual income, household type and size, age category, and having private health insurance. Gender and marital status also influenced expenditures in some categories. Lifestyle choices had small and mixed effects, with smoking and alcohol consumption lowering the probability of OOP spending. From a policy standpoint, households with the lowest incomes, large households, and those where the household head was 'others' (retiree, student, housewife, not actively working, etc.) or had a condition preventing employment seemed to report OOP expenditures less frequently and may have chosen not to receive healthcare services, leading to the need for more healthcare services later.