فصلنامه برنامه ریزی و بودجه
پیاپی 154 (پاییز 1400)

The purpose of this article is to examine the effect of political power on rule of law as a basis for economic development. Political power consists of two key components: power transition and power distribution. Power might be centralized in the hands of a small group or distributed among different groups. Power transition is also distinguished by democratic or non-democratic power. In the present study, the application of descriptive-analytical approach provides evidence that centralized political power leads to the violation of citizens’ rights by the politicians. Conversely, decentralized political power restricts the politicians and consequently, prevents the violation of legal rights. Then, the application of an empirical approach and the analysis of 102 countries’ data reveal that intensification in political power concentration will reduce the rule of law quality. In addition, the results indicate that controlling the power distribution effect will remarkably reduce the power transition’s effect on the quality of rule of law. Sensitivity analysis also demonstrates the results’ stability after changing the dependent variable, adding other control variables and using the instrumental variable method.

This study investigates the effect of natural resource dependence on energy intensity of 75 countries between 1993 through 2015 in the aggregate level. Natural resource dependence is measured using four different proxies; the ratio of fuel export to GDP and total export, the ratio of mineral resource rent to GDP, and the ratio of natural resource rent to GDP. The effects of these proxies on energy intensity of countries are estimated using Arellano-Bond estimator. The results show a positive effect of subsoil resource dependence on energy intensity of countries. However, this effect is reversed once the forest resource rents are added to the measure of resource dependence. These effects are robust with respect to changes in weather and energy price proxies.

Generalized non-performing loans ratio (GNPLs) is empirically considered as a key prudential soundness indicator which is computed by the ratio of non-performing loans (overdue loans, arrears, doubtful loans, and rescheduled loans) to the total outstanding loan that also affects banks’ lending capacity. The GNPLs is evidently influenced by the macro systematic shocks (GDP growth, foreign exchange rate, inflation, and lending interest rate) which are statistically examined for a sample bank. In this regard, the impact of four systematic shocks on the GNPLs is estimated by a Vector Autoregressive (VAR) model during 2003-2020. In this context, the Impulse Response Function (IRF) of GNPLs is also examined against four contingent shocks while instantaneously variance decomposition of the GNPLs is estimated for the short and long term. The impact of the first and second moments of the shocks on GNPLs is estimated by the Multivariate Stochastic Volatility Model as well. The IRF output indicates that the GNPLs grows due to the shocks of exchange rate depreciation, GDP reduction, and inflation growth in the short time, while lending rate insignificantly affects the GNPLs owing to low historical volatilities as well as big arbitrages among bank lending rates for different economic sectors. The GNPLs Variance Decomposition highlights that GDP growth and inflation affect the GNPLs deviations in the short run, while the foreign exchange rate constantly motivates the GNPLs in the long run. In other words, the foreign exchange rate has strongly affected the GNPLs deviations in the long run, owing to its role as a nominal anchor and financial stability indicator in the macroeconomic environment. The GNPLs high Volatility which is estimated by conditional variance is also recognized in five different periods (2003, 2007, 2010, 2016, and 2019), mainly because of the foreign exchange rate unification in 2003, monetary expansion for self-employed loans in 2007, international sanctions in 2010, and 2009, as well as assets market recession in 2016 respectively. In this regard, the GNPLs deviations have also strongly correlated with output growth and foreign exchange rate Volatility.

Corruption is a well-known and prevalent phenomenon in developing countries such as Iran. One of the effective factors in reducing corruption and increasing the level of transparency is the use of information and communication technology (ICT) tools. This study investigates the impacts of ICT on corruption in the selected OIC countries for the period 2002-2020. Before estimating the model by panel data approach, the existence of cross-sectional dependence has been tested and ratified in the studied countries. Therefore, to obtain reliable results, the Cup-FM Method was used to estimate the model. Based on the results of model estimation, the impact of ICT components on corruption has been negative and significant. Correspondingly, the impact of inflation, per capita income, and the rule of law on corruption are significantly positive, negative, and negative, respectively.  Furthermore, trade openness has a positive, but not statistically significant, impact on the corruption index.

The economic performance to reduce country risk, in which the existing economic, social, and political conditions negatively affect the capacity to repay foreign debt and attract foreign direct investment, is one of the prominent issues in economic growth. Accordingly, the main purpose of this study is to evaluate the impact of country risk management on the economic growth of selected member countries of the Organization of Islamic Cooperation during the period (2006-2019). For this purpose, a composite index was developed by taking into account the most important indicators of economic performance related to country risk, including macroeconomic factors, social, political, and legal conditions, and characteristics of the banking system. Then, by using the Generalized Method of Moments (GMM), the effect of this index on the economic growth of the selected member countries of the Islamic Cooperation Organization was evaluated. The model estimation results show a significant and direct relationship between economic performance to reduce country risk and economic growth. The results also imply the significant and direct effect of trade openness, labor, and gross capital formation on economic growth. Meanwhile, inflation has had a significant and negative impact on economic growth.

The food and beverage industry has always been one of the most popular industries for investors and market participants in Iran. In the present paper, using conditional turbulence method, the model for factors affecting the instability index in the food and beverage industry in Tehran Stock Exchange has been studied and presented. For this purpose, the monthly data from March 2009 to March 2020 have been used. Also based on regression results, turbulence can be caused by factors such as political conflicts and international problems in Iran, and strengthened or weakened by the effects of parallel markets such as oil, gold and currency, as well as inflation and liquidity. Based on regression results, factors outside the stock market in Iran, have a greater impact on turmoil and instability in the stocks of the food and beverage industry (excluding sugar) compared to in-company factors. Therefore, from the point of view of the performed analyses, the most important effect and factor causing volatility of the stock exchange are inflation, exchange rate, liquidity volume, oil price, gold price, and political news. Accordingly, this study provides research and executive proposals with regard to capital market volatility management.