This study aims to examine the nonlinear and asymmetric effects of macroeconomic variables on the flow of foreign direct investment (FDI) in selected Middle Eastern countries during the period 2007–2022. Using PANEL data from eight countries—Iran, Iraq, Saudi Arabia, the United Arab Emirates, Kuwait, Oman, Qatar, and Bahrain—the study applies the nonlinear autoregressive distributed lag model (PANEL NARDL) to explore both long- and short-run relationships between key macroeconomic variables (exchange rate, inflation, economic growth, trade openness, and innovation) and FDI. Unit root tests, Kao cointegration test, and diagnostic tests were conducted to validate the model. The results indicate that trade openness, economic growth, and innovation exert a positive and statistically significant impact on FDI, whereas exchange rate and inflation have significant negative effects. Moreover, the effects of positive and negative shocks in these variables on FDI are asymmetric; that is, increases and decreases in the same variable lead to differing responses in FDI inflows. The model shows high explanatory power with an R-squared value of 0.91. The findings suggest that macroeconomic variables are not only critical determinants of foreign direct investment but also elicit asymmetric reactions depending on the direction of the shock. This underscores the importance of adopting flexible and differentiated economic policies to enhance FDI inflows in the Middle East region.

The aim of this study was to estimate the nonlinear effect of oil, gas, electricity, and coal energy consumption on carbon dioxide emissions in ten energy-intensive countries (Iran, South Korea, Japan, Germany-Russia-USA-India-Canada-Brazil and China) in the world. Statistics and information used to estimate the nonlinear autoregressive PANEL model with distributed intervals (PANEL NARDL) have been extracted from the database of the World Bank and the World Energy Organization for the period 1985-2019. The results show that increased consumption of gas, electricity, coal, and oil leads to increased carbon dioxide emissions, while a decrease in their consumption reduces carbon dioxide emissions in the long run. Also, the nonlinear relationship between the per capita of consumption of these four types of energy and the emission of carbon dioxide in high-consumption countries was confirmed by the parent test in the long run. Therefore, reducing the use of fossil fuels and shifting the focus to clean and renewable energy consumption is proposed for the five selected countries, especially Iran, and economic policymakers should prioritize environmental protection by enacting applicable laws. In this way, the creation and development of intelligent infrastructure for the carbon economy and industry are essential.

The neoclassical growth model is tested by use of PANEL data procedure in this research. In the econometric test, simoultanously time series and cross detection will be compared on the basis of PANEL data method through which their observed points increase and consequently the estimation efficiency will be increased. The examination of neoclassical growth theory has been done with reference to external & internal factors of 52 selected countries from 1960 to 2000. The independent variable of model has been selected on the basis of the result of previous research which explains the result in three separate models: developed countries, developing countries, and whole countries. These factors are such as: Gross National Products with lag of period, work force age, growth rate, education level, the change of capital accumulation and economic trade volum. The consequences of this research is that: neoclassical growth model can explain the major part of economic growth of the countries with use of internal variables. Also with the use of PANEL procedure of fixed effect, we can see the fundamental differences and structure of the growth process for different countries; and show how the economic, and social conditions affect on the growth.

Protective steel doors are widely used in buildings due to their high resistance against the impact loads. However, its heavy weight has been always considered as a major drawback for these doors. In this paper, a new optimized stiffened impact-protective steel door incorporating sandwich PANEL with aluminum foam core (OSSA) is examined. This door consists of two face sheets, main and secondary stiffeners, and aluminum foam as the inner core. In order to optimize the door, at first the rigidity and weight functions of the stiffened steel door were extracted. Then an optimal door weighing 42% less than the primary door was obtained. Due to the high energy absorption capacity of the combined foam core and stiffened steel door structure, the use of aluminum foam core in the optimized steel door was proposed. By doing numerical analysis, and depending on the thickness of the face sheet of OSSA, 20 to 32% reduction in the maximum displacement was observed. The results also showed that, with 67% increase in the peak overpressure, OSSA has kept almost the same maximum displacement as that of the steel door without an aluminum foam. In other words, by using aluminum foam core in the optimized stiffened door, the door will resist 67% more impact load.

The relationship among institutional quality and economic growth is one of the main issues in economic growth and development and has been considered from the view point of researchers. Hence, the main objective of this article is to investigate the asymmetries effect of good governance index as a suitable proxy to institutional quality on the economic growth in MENA countries during the period of 1996-2022. For achieving this, the econometric model has been estimated y PNADL method in these countries. The empirical findings indicated that there is asymmetry effect between good governance index and economic growth in short and long-run.  Moreover, the other explanatory variables such as FDI, gross capital formation and labor force have positive and significant impacts on the economic growth in long-run. But, the effect of trade openness has not significant on the GDP growth. On the base of research findings, it can be argued that at high levels of governance (low levels of corruption and redundant regulations and political constraints and high levels of political stability and the rule of law and the effectiveness of government) where the quality of institutions is also high, all six good governance components attract domestic and foreign investment, Accelerate economic growth rate.

The government tasks in regard to justice and increase social welfare is offering services and public finance, maintain order through enforce laws and good governance in the regulation of relations between governmental and public relations together with the help of the judicial system. The purpose of this study is to investigate the impact of government spending on public affairs and related chapters, including: legislation, public services, judiciary, financial services and science development on the Amartya Sen social welfare index during business cycles in the Iranian economy. In this regard, the nonlinear self-explanatory model with wide intervals (NARDL) has been used to estimate time series data during the period of 1973-2019. The results show that in Iran, the positive shock of government spending in the science, legislative and public development chapters during business cycles has increased social welfare and in the judicial season decreased social welfare. The negative shock of government expenditures in public affairs and legislative, public and financial services chapters during business cycles and judicial chapter in recesion periods have significantly increased social welfare, significantly. Also, the negative shock of government expenditures in the science development chapter during recesion and boom, respectively, has increased and decreased Social welfare significantly. Thus, government Expenditure on public affairs and related sub-chapters during business cycles has had asymmetric effects on social welfare.

One of the most important economic goals of each country is to increase economic resilience and reduce the damage caused by internal and external shocks. Several factors affect a country's economic resilience. The purpose of this study is to investigate the role of international trade on the resilience of Iran's economy using data from 1990 to 2022 using a regression approach with nonlinear distributive interruptions. The results show that in the long run, with increasing trade, the country's economic resilience will increase. Based on the results, the positive effect of trade shock in the long and short term increases economic resilience, while negative shock has a bigger impact on reducing economic resilience compared to the positive effect of trade, so the existence of an asymmetric relation between positive and negative shocks of trade on resilience is confirmed. Also, an increase in economic growth and liquidity can increase economic resilience, while an increase in the real exchange rate causes a decrease in resilience in Iran's economy. 

This paper uses the non-linear auto-regressive distributed lags (NARDL) model to examine the short-and long-run effects of the negative and positive shocks of the shadow economy on financial development in Iran over the period 1974-2015. For this purpose, the ratio of liquidity to gross domestic product is used as an indicator of financial development. The shadow economy includes all market-based production activities that are deliberately hidden from government officials due to the escape or avoidance of payments, such as taxes and social security contributions. In this study, the MIMIC (multiple indicators and multiple causes) calculations by Piraee and Rajaee (2015) are used for estimating the shadow economy. The results show that the effects of positive and negative shocks of shadow economy on financial development are asymmetric in the short-and long-run. This asymmetry means that in the short-and long-run, the negative shock to shadow economy is more effective than its positive shock. Therefore, in order to maintain the current level of financial development, the government can monitor size of shadow economy through strict control of illegal activities in the short-run, identify the illegal activities, and reduce them in the long run.

Oil price shocks have an undesirable effect on financial stability and banking systems, in addition to creating uncertainty and negative effects on the macroeconomic performance of oil-exporting countries. In fact, the dependency of government spending policies on oil price movements in oil exporting countries creates feedback loops between asset prices and bank credits that could lead to an increase in vulnerability of the financial sector. Therefore, considering the importance of the issue, this study aims to investigate the asymmetric effects of oil prices on non-performing loans (NPLs), as credit risk criteria, by applying data from 18 selected banks in Iran during 2006-2017. In this regard, the relationship between variables has been estimated using PANEL Nonlinear Autoregressive Distributed Lag (PANEL NARDL). The predictability of symmetric and asymmetric PANEL ARDL models is assessed by applying RMSE and Campbell and Thompson (2008) tests. The results show that the asymmetric model has better performance and efficiency than the symmetric model. These asymmetric effects are significant in both short-term and long-term. Based on the results, the impact of oil price on the NPLs of some banks is positive and in the others is negative and significant.

Agriculture is recognized as the driving force of economic growth, especially in developing economies. Attention to agriculture is extremely important, especially during economic sanctions owing to its critical roles such as income for rural people, food security, job creation, and foreign exchange earnings. On the other hand, foreign trade is vital to technology transfer to the country. The present study investigates the linear (nonlinear) relationship between agricultural import shocks and agricultural growth in Iran using annual data for the period 1978-2020 by application of the nonlinear autoregressive distributed lag model (NARDL). The results confirmed asymmetry in the impact of imports on growth. In other words, the superiority of the nonlinear model was in explaining the relationships between variables. To be specific, a positive and negative shock to agricultural imports affected sector growth by 0.18 and -0.05 percent, respectively in the long run. However, the latter was found statistically insignificant. Moreover, we found evidence of the asymmetry in the effect of other variables (except labor) on growth.