JOURNAL OF APPLIED ECONOMICS STUDIES IN IRAN
Year:2020 | Volume:8 | Issue:32|Papers Count:9

The main objective of this study is to investigate the non-linear impacts of macroeconomic instability on the relationship between exchange rate and trade balance of Iran. For this purpose, using annual time series over the period 1973 to 2017, computing the combined index of economic instability using variables such as consumer price index, foreign reserves, exchange rate, budget deficit and long run deposits rates. After that the effect on the relationship between exchange rate and trade balance has been estimated applying Markov-Switching technique. The results indicate that Iranian macroeconomic instability is dividable into two regimes including high macroeconomic instability (regime 1) and low macroeconomic instability (regime 2). Increased exchange rate has induced the improvement of trade balance in both regimes. The effect of macroeconomic instability on exchange rate – trade balance relation, is negative and significant in two regimes. In two regimes macroeconomic instability deteriorates the effect of exchange rate on trade balance.

The use of agent-based models on the heterogeneous behavior of agents has expanded considerably over the past years. This paper investigates the model based on the behavior of agents and considers the heterogeneity of agent models. In this study, we examine the effect of different forming of individuals' expectations on macroeconomic variables and the re-distributional effects of monetary policy. This paper revisit the transmission mechanism from monetary policy to household consumption in a Heterogeneous Agent New Keynesian (HANK) model. The model yields empirically realistic distributions of wealth and marginal propensities to consume because of two features: uninsurable income shocks and multiple assets with different degrees of liquidity and different returns. In this model, the indirect effects of an unexpected monetary policy, which operate through a general equilibrium increase in labor demand, far outweigh direct effects such as intertemporal substitution. This finding is in Representative Agent New Keynesian (RANK) economies, where the substitution channel drives virtually all of the transmission from monetary policy to consumption then failure of Ricardian equivalence implies that, in HANK models, the fiscal reaction to the monetary expansion is a key determinant of the overall size of the macroeconomic response. The results indicate that under discretionary circumstances, the attempt of the monetary authority to redistribute wealth to the borrower's households, which have a higher utility of net wealth than the other households, leads to changes in inflationary biases. However, under commitment circumstances, this inflationary pressure will be offset by changes in expectations for future inflation over time.

This study identifies and estimates the effective factors on housing prices over the years 1996 to 2017 in terms of model uncertainty and with BACE approach. The statistical data of 18 variables including 15 external variables (socioeconomic variables) and 3 internal variables (housing sector variables) affecting housing price according to the theoretical foundations and experimental studies have been used for this research. The results suggest that the growth of urban population, household income, the unemployment rate, the average cost of 1-square-meter building, expected inflation, income inequality, oil revenues growth, liquidity, and exchange rate are the most effective variables in housing price pattern in Iran. There is no strong evidence of effectiveness of other variables on housing price over the period of this research. The results can be used for creating appropriate patterns for explaining the issues related to housing price and better management of housing sector policies.

Considering the price of the exchange rate and its volatility plays a significant role in financial decisions and economic transactions affected by large and small economic groups. In this study, we have tried to provide continuous modeling for exchange rate data in Iran with the support of a stochastic differential equation driven by the Levy process (that named continuous GARCH model) and check out the fitting exchange rate volatility on this model. Accordingly, we use the daily data of the unofficial exchange rate (the value of the US dollar against the Iranian Rial in the free market) from March 2009 to March 2018. We also challenge the performance of the models with time-varying volatility under the continuous features in comparison to the discrete GARCH model. Finally, according to investigating the efficiency of this model coinciding with the results of the measurement error criterion, the preference of the new continuous model is expressed.

The economic complexity index is one of the latest published indicators to measure the level of knowledge and technology in countries. In this paper, using a smooth transition regression model, the effect of economic complexity on energy consumption is evaluated for the first time in the Iranian economy during the period 1971-2013. The results of the model estimation confirm the existence of a nonlinear relationship between per capita income, real energy price index, and the complexity of the economy with per capita energy consumption. Also, economic complexity leads to a two-regime structure with a threshold of-1. 15. So that in the first regime, which is related to the low levels of economic complexity, the effect of this variable on energy consumption was positive, that could be due to the rebound effects of technology on energy consumption. In the second regime, which is related to higher levels of complexity, the relationship was negative. Therefore, in the second regime, improving the level of complexity can help to save energy. On the other hand, the elasticity of income and price in both regimes was less than one, but as the complexity passing the threshold, the elasticity has increased in particular with respect to price, which indicates that with the increase of technology and knowledge of the country, the power of the reaction of consumers to the price changes will increase.

The process of economic growth and development depends on the extent to which the national economy interacts with the world economy and is affected by the process of globalization. In this regard, the size of the government has also undergone a great deal of change in the approach of accepting engagement with the issue of globalization and with the anomaly itself has increased the possibility of corruption, especially in developing countries. The purpose of the present study was to investigate the impact of business-financial openness on government size by emphasizing the Corruption Perceptions Index and comparing it in two groups of high-income and low-income countries over the period 2018– 2006 using panel data. It is based on the FGLS approach. The findings show that improving the perception index of corruption has led to an increase in the size of government in high-income countries, while in lowincome countries it has reduced the size of government presence in the economy. Moreover, financial freedom has had a greater impact on government size in high-income countries than commercial freedom, and has resulted in a decrease in the size of government, while commercial freedom has no such effect. In the group of low-income countries, improving the perception of corruption, which indicates improved governance quality, has led to a decrease in the size of governments, but the effect of commercial and financial freedom on the size of the positive government reflects the increasing impact of globalization indicators on the size of the government. The findings indicate the asymmetric impact of commercial and financial freedom on government size in high-income countries. In spite of the asymmetric response of the government size in the two income groups to the perception of corruption index, the improvement in this index in the group of low-income countries has been associated with a larger response to the decline in government volume.

The structure of the tax system and the various sources of tax revenues are one of the most important pillars of countries' economic development. Taxing and expanding tax bases is one of the tools used by governments to play a leading role in economic policies. In this regard, the stability and assured sustainability of the tax structure and revenues is an important issue that needs to be examined and analyzed. Therefore, one of the most important issues in the structure of the tax system is to examine the effect of uncertainty in tax revenues on economic growth or GDP (Gross Domestic Product). Due to the volatility in tax revenues in Iran, investigating the relationship between types of tax revenues and GDP is of great importance in the area of government fiscal policy-making. Therefore, using the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) variance model and the Autoregressive Distributed Lag (ARDL) approach, this study investigates the extent and the impact of uncertainty in the Iranian tax structure on GDP from 1978 to 2017. According to the results, tax uncertainty in Iran can have both positive and negative impacts on economic growth. Thus, the variables of Uncertainty in Tax on Goods and Services (UTGS), Uncertainty in Tax on Imports (UTIM), and Uncertainty in Tax on Wealth (UTW) have had a negative impact on economic growth in Iran. On the other hand, the variables of Uncertainty in Tax on Legal Entities (UTLE) and Uncertainty in Tax on Revenue (UTR) have had a positive impact on Iranian economic growth. In addition, the variable of Budget Spending had a positive but insignificant impact on Iranian economic growth. Finally, GDP has been influenced by a positive, significant and considerable impact of its first lag.

In this study, using a basket of 5 most traded currencies as the base to measure currencies return (a basket with minimum variance in value), and applying variables affecting the exchange rate, we design a model for predicting and determining the best foreign exchange portfolio (in the sense of risk adjusted return), and then the output portfolios of the model, will compete the momentum based portfolio which is commonly used in forex and other financial markets. If there is a significant difference between the two models, the model presented in this study will be introduced as a model with the more ability than momentum investing strategy to predict the currency risk adjusted return. For research, quarterly data from 15 currencies (which includes the 15 most traded currencies) has been used since 1999 to 2018, and the Dynamic Panel method is used to process related data. The research findings indicate the power of the proposed model for predicting risk adjusted return of the currencies Also, the finding shows than the fundamental variables (Interest Rate and Real Exchange Rate) have a positive relationship with the currencies return and the previous lags of currency return has a negative relation with the current return.

The main reason for the decline and extensive change use of wetland resources is often the lack of proper calculation of the environmental (non-market) values of wetlands in development decisions. Fereydunkenar area has a local management system. Due to the condition of the wetland, protecting bio diversity of ecosystems, especially migratory birds, it is not possible managing the wetland without the participation of the local communities, therefore, in this study; we used a price tool to Estimate reduced income and attract predator’ s participation. For this purpose, a choice model was used to estimate the ecosystem value of Fereydunkenar wetland as a value that the operators favor for the benefits of the wetland and also to estimate the reduced income we used a conditional logit model. Then, this calculated income was used as a Incentive to engagement of predators and landowners. The results of the Logit model for each region, show that willingness to accept of the hunters in Sorkhroud, Ezbaran and Ferydoonkenar area are 2386217, 2547214, and 3542100 Rials respectively. The variable coefficient of the wildlife habitat and the cost of payment for all three regions is one percent significant and positive. This means that there is a positive and significant impact on the willingness or marginal utility of predators. In other words, by improving the wildlife habitat status or increasing shelter, and as a result of a decrease in the level of hunting, the desire to get hunters to avoid hunting increases. However, with the improvement or shortening of the hunting season, the final utility of predators is reduced, which means that there is a negative impact on the willingness of people to hunt in the Fereydunknar area of Mazandaran province.