فصلنامه سیاستهای مالی و اقتصادی
سال یازدهم شماره 42 (تابستان 1402)

The main aim of this article is to estimate the volume liquidity shocks and its impact along with other effective variables on the exchange rate system’s survival in the 9 countries with an exchange rate anchor monetary system and the 20 countries with an inflation targeting monetary system during the period of 1999-2020. In order to achieve this objective, volume liquidity shocks were first estimated using the residual method, and then low and high inflationary environments were estimated using the Markov rotation method in Ox-Metrix version 7 software. Finally, the survival of foreign exchange systems has been estimated using the quasi-parametric method with the Weibull distribution in Stata software version 17. The main results of the estimation showed that positive and negative shocks had negative, positive and significant effects on the durability or survival of exchange rate systems in both groups of countries, respectively. Moreover, the variables of gross domestic fixed capital formation, the degree of openness and marginal cost have, respectively had positive, positive and negative effects on the survival of currency systems in the group of countries under investigation. The inflationary environment had a negative and significant impact on the survival and permanence of the exchange rate systems in both groups of countries, but the effect of nominal effective exchange rate volatility on the survival of the exchange rate anchor system was not significant due to the adopted exchange rate arrangements of a stabilized currency system with a 2% and limited fluctuation range, which reduces the possibility of aggravating instability.

Consumption of polluting energy against economic welfare puts the policymaker on a dilemma - achieving economic prosperity as the ultimate goal of the economy or increasing energy consumption for economic growth. The main goal of this research is to test this duality and specifically the presence of an inverted U relationship between economic welfare and energy consumption using the Feasible Generalized Least Squares method for panel data of 117 countries (77 countries with low energy intensity and 40 countries with high energy intensity) in the period of 2007-2019. Findings of the present study indicate the existence of an inverted U relationship between energy consumption and economic welfare and confirm the hypothesis of the Kuznets curve. The noteworthy point in the findings of this study is the dynamics of the general pattern of welfare by a change in energy consumption, so that for countries with low energy intensity and also renewable energy, the threshold limit of welfare is reached faster, and after that, welfare decreases at a slower rate than the upward trend of the curve. Based on this, it seems that countries can adjust the path with consistent and optimal policies and delay reaching the stage of welfare reduction.

The beating heart of banking is in financial intermediation and the continuous rotation of loan-deposit-loan. Nonperforming bank loan due to the locking of banks loan in a process outside of this cycle, practically take part of the banks assets out of their credit management and reduce their crediting ability. On the other hand, The use of strict techniques for Collecting Receivables such as bank fines Obtainment has caused a high level of people's mistrust in the banking system. The current research has been done with the aim of benefiting from behavioral economics tools in banks to Collecting receivables. The research is of a qualitative and experimental type, which in the qualitative part of the data was collected using a semi-structured interview, and through theme analysis, components and indicators were identified for the collect bank Receivables. The findings of the research, while emphasizing the benefit of behavioral-based executive policies to collect bank Receivables, show that it is possible to use Nudge tools that include nine main concepts: Messenger, Incentives, Norms, Defaults, Salience, Priming, Affect, Commitments and Ego are useful in the direction of collect bank Receivables.The results of the experiment conducted in 200 loan cases indicate that if collect bank Receivables are followed up only on the basis of telephone calls and without the use of Nudge, 20% of the collect bank Receivables cases will be reduced, but if in a telephone call to collect bank Receivables from if Nudge is also used, the number of will be reduced by 30%, so it is expected that the number of collect bank Receivables files will be reduced by 10% with the use of Nudge.

Individual decisions in the new paradigm of financial science are influenced by emotional factors. These factors can also have an impact on financial markets. First, using the Baker and Wurgler model (2007) to model the Iranian capital market sentiment index, and the capital market is divided into two periods of low and high sentiment. In order to examine the relationship between cross-sectional return and value-at-risk (VaR) in periods of high and low sentiment, two approaches were used: Fama-Macbeth regression model and single-sorting and double-sorting. The statistical population of this study consists of 130 companies represented on the Tehran Stock Exchange, selected using a systematic elimination method. MATLAB software was used to implement the method. It was found that, regarding the sentiment factor, there is a significant relationship between VaR and excess return, such that VaR changes were greater in periods of high sentiment than those in the periods of low sentiments. During periods of high sentiment, shareholders’ transactions are determined solely by emotions and with high risk. Furthermore, the relationship between excess return and VaR was only influenced by momentum

For a long time now, the economic effects of military spending have been one of the most controversial topics in the literature of defense and peace economics. The majority of empirical studies in this field show the negative or insignificant effect of military spending on economic growth in developing countries. But more recent empirical studies show that the existence of external factors such as threats, an abundance of natural resources, and high-quality institutions can indirectly increase economic growth in these countries through military spending and partially compensate for the direct negative effects of military spending on economic growth. In this regard, this article has tried to investigate the role of institutional quality and abundance of natural resources in the relationship between militarization and economic growth in developing countries during the period of 2000-2018 using the dynamic panel data approach. For this purpose, the Global Militarization Index (GMI) and the Generalized Method of Moments (GMM) have been used. The empirical results show that the effect of militarization on economic growth in developing countries is negative and significant. However, the interactive effect of institutional quality and militarization, as well as the interactive effect of abundant natural resources and militarization on economic growth in these countries is positive and significant. This means that militarization in developing countries can increase economic growth in the presence of good institutions and an abundance of natural resources. Also, by separating the studied countries into two categories of countries with relatively better and weaker institutions, it has been shown that militarization from the channel of abundant natural resources increases economic growth in countries with relatively better institutions, while militarization from the channel of abundant natural resources has a negative and significant effect on economic growth in countries with relatively weaker institutions.

One of the most important economic goals of countries is to create the necessary conditions for increasing economic growth. One of the necessary conditions for that is investment in economic infrastructure. The purpose of this research is to examine the weight of indicators and rank 31 provinces of Iran based on the growth of infrastructure. The type of current research is applied in terms of purpose and descriptive-post-event in terms of method. The statistical population of our research is 31 provinces of Iran and the time frame under our investigation is 10 years, from 2011 to 2020. In this research, we will examine the growth of the investigated infrastructures (transportation, healthcare, communication and telecommunications, and water and sewage), then rank the growth of the infrastructures using the Shannon entropy and TOPSIS methods. The results showed that during the 10-year period under investigation, the average growth rate of the infrastructures did not have a regular pattern of increase or decrease, and in some years the infrastructures had growth, and in other years there was no or very slight growth. Regarding the geometric mean, the total growth rate of the investigated infrastructures was 14.81% in the 10-year period.