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This study examined the correlation between economic growth and the impact on the environment, specifically focusing on the concept of environmental sustainability. The World Bank's Adjusted Net Savings (ANS) data is utilized in this study to gauge the strain on the environment, specifically through the measurement of natural disinvestment. This measurement encompasses the cumulative effects of carbon dioxide (CO2) damage, as well as depletions in minerals, energy, and forest resources. This study uses panel data with respect to the endogeneity of explanatory variables to estimate the real effect of per capita income and the other variables on environmental pressure. In this regard, employing the panel Fixed-Effects Instrumental Variable (IV) methodology, the data from 213 countries have been used in the period from 1990 to 2018. Through regression analysis, it has been discovered that there is a direct correlation between income and the impact on the environment in developing nations. However, this relationship is notably more pronounced in low-income countries compared to high-income countries. Additionally, the study reveals that trade expansion contributes to an increase in environmental pressure across all groups of countries. An increase in the school enrolment rate can affect the environment in developed and high-income developing countries. Moreover, the variable effect of capital openness on environmental pressure was estimated to be positive for developed and high-income countries. However, this effect was found to be negative for low-income countries. Finally, the result showed that developing countries should improve their legal structure and also reduce the bureaucracy and complexity of the laws.

Making decisions regarding capital structure is among the most challenging issues ahead for firms and the most critical decisions for their survival. On the other hand, several significant aspects, such as behavioral factors, have been overlooked in this field. Thus, the present study mainly seeks to identify the factors affecting capital structure in Iranian firms, emphasizing the role of behavioral factors. The present study employs mixed qualitative and quantitative research methods. From the qualitative point of view, capital market experts were inquired, and theoretical saturation was achieved using the snowball method. After the interviews, research components were extracted through coding. The opinions of a group of experts and managers of firms listed on the Tehran Stock Exchange were used in the quantitative section, and a structural equation form was used to perform confirmatory factor analysis on the research model. A total of 63 concepts in the form of six categories were identified at the first stage, which was reduced to 58 in the form of six categories and was confirmed after the concepts were sent back to the experts. The principal components included behavioral factors, macroeconomic factors, political factors, socio-cultural factors, firm features, and corporate governance. Results were validated through factor analysis in the quantitative portion of the study. The present study can be considered among the comprehensive studies at the construct level with an integrated approach to firms' capital structure. The emergence of behavioral finance resulted from understanding the importance of measuring human behavior as a factor with transcendent consequences for financial decisions. Hence, most behavioral finance studies are focused on observable behaviors. However, the item response theory presents an integrated method for disciplines that work with cognitive variables. Accepting opportunities for new knowledge is essential for firm decisions to respond to the mental views of financial managers. The present study sought to identify the factors influencing firms' capital structure in Iran. The tool used in the present study reflected the elements making up the capital structure. In this regard, the notable point is how the classic criterion of structural capital components can explain financial managers' perception of decision-making. The research results in this area are interesting since we have confirmed a capital structure theory at the construct level. The conformity of the results and the obtained reliability levels indicate that this theory fits the given dimensions well. Moreover, relevant evidence indicates that senior financial managers adopt various states considering internal and external factors at the structural level, which can cause cognitive bias in decision-making.

This paper attempts to compare a Markov-Switching Dynamic Stochastic General Equilibrium (MS-DSGE) model by including deep habits consumption to a MS-DSGE model without deep habits. It is concluded that the deep habit adjusted model with regime switching is able to fit the Iranian data better. The results of estimating parameters indicate that deep habit formation, together with the persistence of habit stock, are significant parameters. The results also confirm that current and future consumption demand, expected marginal cost and stock of habits are effective driving forces in extracted New Keynesian Philips Curve considering deep habits. However, in contrast with Ravn et al (2006, 2010) findings, it is shown that presence of deep habit consumption in the model for Iranian economy, cannot lead to reduce inflation in response to monetary shock while the amount of increase in inflation in response to monetary shock in the model with deep habit is less than inflation increase in model without deep habits. Furthermore, in response to fiscal shock in the model considering deep habits, the negative effect of wealth could not be compensated in Iranian economy. Therefore, consumption begins to decrease in response to fiscal shock, although these reduction in the model without deep habits takes more longer than in the model with deep habits.