درخت حوزه‌های تخصصی

The present study investigates the impact of macroeconomic and bank-specific variables on non-performing loans (NPLs). To avoid the identification problem, two models are employed to address this impact. The first one tests the effect of macroeconomic variables including the growth of oil revenues, inflation, and the growth of GDP without the oil sector on the growth of NPLs. Data is quarterly over the period 2004:3 to 2019:3. The transition variable in this setup is the growth of oil revenues and its threshold is 9 percent, which divides the sample into oil booms and oil recessions. According to the results, inflation has a significant positive effect on NPLs. During the oil boom, oil revenues decrease the NPLs. Due to the immense size of the government and its current and capital expenditures, when oil revenues are lower, the government forces banks to allocate loans to finance projects with long maturity. Furthermore, the present study used PSTR to test the impact of bank-specific variables consisting of interest rate spread, loan loss provision, loan to deposit ratio, and NPLs. To do so, monthly data of 10 banks is used over 2016:04 to 2020:12. The transition variable is the interest rate spread at 1 percent, which categorizes the banks into two groups of good and bad. Good banks collect deposits with a low-interest rate and allocate high-rate loans with less chance of default. So, interest spread is the most important prominent determinant of decreasing NPLs, while the loan to deposit ratio is dependent on the banks belonging to which group. For good banks, the loan to deposit ratio decreases the NPLs, while for bad banks, it worsens the growth of NPLs.

Generally, international flows of capital and foreign direct investment attraction are challengeable issues in the literature of economic growth and development in emerging market countries. However, the fluctuations in foreign direct investment, including sudden flood and stop, will affect emerging markets' output and macroeconomic variables. Using an econometric model with unbalanced panel data during 1990-2014 for 38 emerging countries, this study tries to evaluate the determinants of output losses from the sudden stop of foreign direct investment and consider the role of macroeconomic policies. The results show that the sudden stop phenomena and the financial crises have been identified as the main explanatory variables for the output collapse in the selected countries. Moreover, the role of macroeconomic policies is important, and the output losses can be controlled by using active monetary and exchange rate policies.

Value at Risk model based on a switching regime approach was used in this study to optimize portfolios consisting of industry index (petroleum products, investment, chemical products, and metal products). For this purpose, the VaR of returns on index should first be extracted through parametric models of the (GARCH) family in each of the above industries by using regime transitions. After the risk of return on index is obtained for each industry, the optimal portfolio is created in the next step based on VaR minimization, and the optimal value of each industry is determined in the portfolio. According to the results, (MRS-FIEGARCH) model had no superiority in VaR estimation over the other parametric models of the GARCH family. In fact (MS-EGARCH-t) was introduced as the optimal model. Among the designated industries, returns on indices followed regime transitions only in chemical products and investment by showing asymmetric reactions to external shocks. Moreover, the optimal weights were on the rise in the industries where VaR decreased over time, whereas the optimal weight of the portfolio decreased in the industries where VaR increased over time. The higher share of an optimal portfolio belonged to the industries where stock returns had lower rates of VaR. The risk-return-ratio was employed to show that the optimal portfolio with a risk rate was measured by considering the switching regime was superior over the optimal portfolio with a risk rate extracted without considering the switching effects. To create an optimal portfolio, it is then recommended to make investments in the industries characterized by higher stability in prices and lower fluctuations in stock returns in the long run. This approach can be employed to obtain the best results from optimal portfolio preparation in the worst-case scenario of the market fluctuations.

This study aimed to develop Oil approaches affected by effective factors for the success of economy-based entrepreneurship in the Oil Industry. In other words, efforts were made to identify and prioritize the factors affecting the development of Oil approaches under the impact of effective factors for the success of economy-based entrepreneurship in the Oil Industry. A review of the previous studies in this field revealed that the factors affecting the development of Oil approaches affected by factors involved in the success of economy-based entrepreneurship in the Oil Industry were institutional, organizational, environmental, economic, technological and opportunity recognition criteria. The present research was applied in terms of goal and survey, cross-sectional regarding data collection method and time frame. The statistical population consisted of experts in the country’s oil industry system. In total, 16 individuals were selected from the central bank managers by purpose sampling. Data were collected using an expert questionnaire, and the fuzzy Delphi method was applied to ensure the validity of the identified indicators. In addition, the reliability of paired comparisons was assessed by calculating the incompatibility rates via the Gogus and Butcher method. In this regard, reliability was acceptable in all cases of less than 0.1. The ranking of key criteria showed that economic factors had of the highest importance, followed by institutional, environmental, organizational, opportunity recognition process, and technological factors.