Macroeconomics

World Wide Web

Demography

Ecology

Biology

Statistics

Foreign direct investment

Economics

Computer science

Human development (humanity)

Kuznets curve

Mathematics

Index (typography)

Human Development Index

Econometrics

Environmental quality

Population

Sustainable development

Sociology

Environmental science

Environmental degradation

Economic growth

Ecological footprint

Environmental Science and Pollution Research

The main objective of this study is to evaluate 22 explanatory variables on ecological footprints and rank each of them by using the two approaches of Bayesian model averaging and weighted averaging least square in developing countries. The data is in a 20-year period of 1996–2016. According to the negative weighted averaging coefficient of square of gross domestic production (GDP), the Environmental Kuznets Curve (EKC) hypothesis can be confirmed with a high degree of certainty. The probability of the effect of this variable is 95% and is part of the components of all five optimal models. The two variables of energy consumption and population density were ranked second and third with the probability of the effectiveness of 0.89 and 0.75, respectively. They have positive effects on ecological footprint index. Population growth and value added of the industrial sector have a positive and almost important relationship with ecological footprint. Other variables in this study are not strongly related to the quality of the environment. For example, the variables such as urbanization rate, literacy rate, and foreign direct investment acquired the next ranking with respect to affecting the ecological footprint, respectively. Regarding the positive effect of foreign direct investment, we can say that this leads to environmental degradation. Human development with inclusion probability of 0.26 and a coefficient of 0.009 has resulted in the reduction of environmental degradation. The intensity of economic activities has inclusion probability of 0.48 and a negative impact, which is unexpected. Indicators of financial openness and trade openness have positive and negative coefficients with fewer probabilities. The square of the capital to labor ratio has a negative sign. The square of the capital to relative labor ratio has a negative coefficient and reduces environmental degradation. The product of the trade openness in the capital to relative labor ratio (and its square) is increasing the degradation of the environment. The square of the financial development has a negative sign. This is indicative of a non-uniform relationship between financial development and the ecological footprint, which follows a U-inverse form. The interaction of financial development–economic growth has a negative sign and the inclusion probability of it is 0.31 in the model, which indicates its weak relationship with the ecological footprint. In addition, the results of the analysis of optimal models confirm largely the previous findings based on BMA and weighted averaging least squares methods.

Investigating the determinant factors of environmental quality (based on ecological carbon footprint index)