Objective: This study is trying to analyze the behavior of monetary policymakers with using Taylor's rule. Policy rules express how monetary policy tools respond to changes in state variables. In recent decades, has been one of the main and mental preoccupations of monetary economists  hat how monetary policymakers react to key economic variables and has led to more studies on the formulation and evaluation of monetary policy rules.Method: Since it is not expected to have a linear relationship between the variables of the model due to the existence of successive STRuctural changes and changes in the political regime, therefore, the smooth transition threshold regression model (STR) has been used for respect to the variables of oil price changes, official exchange rate changes, inflation gap and production gap in the annual period from 2002 to 2019. It should be noted that the variables used in estimating the models are based on the degree of stationarity of the variables. According to the econometric literature, before any estimation, in order to prevent the occurrence of false regressions, it is necessary to ensure that the variables are stationary. For this purpose, the generalized Dickey-Fuller unit root test (ADF) has been used. The results obtained in table (1) show that in all the studied countries, the production gap variables, official exchange rate changes, inflation gap, oil price changes and nominal interest rate changes (for Iran; real interest rate changes) in The surface is static. In the next step, to estimate an STR model, it is necessary to determine the optimal interval for the model variables. After determining the optimal interval for the research variables, the type of model is determined in terms of linearity or non-linearity. For this purpose, the F test statistic was used. In the following, the appropriate transfer variable should be selected for the nonlinear model. To select the transition variable, any potential explanatory variable can be tested, but priority is given to the transition variable that rejects the null hypothesis of the f-test more STRongly. Before estimation, model parameters using Newton-Raphsen algorithm are first checked for the existence or non-existence of collinearity between the variables of the model using the collinearity test of the variance inflation factor (Vif). In the following, the mentioned models are estimated and an attempt is made to analyze the models in which the variables have the greatest impact on the monetary policy maker and Taylor's principle is observed in them.Results: The results showed that, firstly, the reaction function of monetary policy makers in 16 selected countries is non-linear. Secondly; The findings from the estimation of the specified policy rule based on models (1), (2), (3) and (4) have shown that in all the investigated countries, by entering the variables of oil price changes and the official exchange rate into Taylor's model (model 1), the targeting of monetary policy makers is stable. Meanwhile, for the country of Iran, with the inclusion of the variables of oil price changes and official exchange rate in the Taylor model, inflation targeting is changed to production targeting. Thirdly; Based on the results obtained from the estimation of models, it can be seen that the variable of oil price changes in the countries of Algeria, Qatar, Kazakhstan, Ecuador, Colombia, Malaysia, Mexico, Belarus and Bulgaria affects the reaction function of monetary policy makers through the production gap channel and in Iran, Russia, Angola, Nigeria, Brazil, Tunisia and Azerbaijan through the official exchange rate gap channel.Conclusion: It is suggested that the central banks of the countries use key and influential variables such as: changes in oil prices, stock prices, housing prices, exchange rates, etc., because the selection of inappropriate policy goals damages the credibility of the central bank and invalidates the targeting framework.

There have been many studies on the effects of monetary policy on the exchange rate in the Iranian economy. But due to the successive STRuctural changes and changes in the political regime, these effects are not expected to be linear and stable. Therefore, in this study, we want to examine the effect of nonlinear behavior of variable money volume on exchange rate by using STR regression models. For this purpose, we have used the annual data of the variables of GDP, interest rate, inflation rate, money supply and exchange rate during the period 1357-1397. Research shows that a significant nonlinear relationship between money supply and exchange rate is confirmed. Based on the results, the variables of money supply and inflation rate have had a significant negative and positive effect on the real exchange rate, respectively, during the study period. By controlling liquidity growth and transferring it to a low growth regime, the effect of variables such as inflation and interest rates on the exchange rate can be eliminated or reduced. According to the results of this article, at lower threshold levels of money supply, it is possible to use monetary policy to stimulate economic growth and real sector activities with low inflationary effects.

This Paper estimates the determinants of inflation in Iran using a linear and non- linear regression model over the period 1959-2008. In the model specification, the conventional variables (liquidity, production and exchange rate) as well as positive and negative oil revenue shocks, monetary disequilibrium, and demand gap are considered. The results show that nonlinear time series regression model outperforms the linear model in explaining inflation in Iran. The model coefficients are functions of oil price. In the low oil income regime, positive oil shocks decrease the inflation rate while these shocks are not significant in the high oil income regime. Demand gap or excess demand does not have any significant effect on inflation when oil revenues decrease. But in oil boom periods, demand gap affects inflation significantly (probably through government expenditure).

This paper examines the asymmetric effect of inflation on the economic growth in Iran during the period 1990:2–2008:2. To that end, we use a smooth transition regression model which allows having a regime change in the relationship between the variables.We found evidence of threshold behavior in the relationship between the inflation rate and the economic growth in Iran; such that, there is a threshold level of inflation which beyond that the relationship between these variables changes. This estimated threshold for the quarterly inflation rate is 4.56. The results also show that there is a positive contemporaneous relationship between the inflation rate and the economic growth in the first regime, where the inflation rate is below 4.56; however, for the periods with an inflation rate higher than 4.56 there is not any significant relationship between the inflation rate and the economic growth. In addition, the effects of the government expenditures and investment are regime-dependent and change over the time.

This study examines the nonlinear impact of urbanization on public sector expenditure in Iran during the years of 1960-2014. For this purpose, is used the Smooth Transition Regression model (STR) as one of the most prominent regime-switching models. The estimated STR model supports a nonlinear threshold behavior in the relationship between urbanization and public sector expenditure in the country in a two regime STRuctures with a threshold (optimum) level of about 55. 28%. In the first regime, urbanization has a negative impact on public sector expenditure, because of positive external consequences and economies of scale in the production of public goods, but after crossing the threshold level (the amount of 55. 28 percent), in second regime, its impact is positive, due to occurrence of the phenomenon external crowded and some negative external consequences. Accordingly, it can be said that the hypothesis of U-shaped impact of the urbanization on public sector expenditure has been confirmed in the Iran.

This study aimed to evaluate the role of the banking system, particularly monetary policies and the provision of bank facilities, in recession and boom periods, on employment in the labour market. The study considered several key variables, including employment, the bank and financial development index, the volume of facilities provided to the private sector, the bank facilities rate, the wage rate, the workforce, capital stock, liquidity, the degree of economic openness, the inflation rate, direct foreign investment, government expenditures, and oil revenues. The research utilized the smooth transfer regression (STR) model to assess the relationship between these variables from 1989 to 2016. The findings revealed a nonlinear correlation between banking variables and employment. Within the nonlinear model, it was observed that a 2. 87% increase in the inflation rate had a significant and distinct impact on employment in relation to banking indexes such as money market development, the volume of facilities granted, and liquidity. The study identified a weak effect of monetary policy indicators and bank facilities on employment in the country, highlighting an inadequate association between monetary policies and workforce supply and demand in the national labour market.

Regarding the important role of health in economic growth and development, the purpose of the present paper is to investigate the impact of life expectancy, as the most important indicator of health, on economic growth in Iran during 1965-2009. The estimated Smooth Transition Regression (STR) model supports a nonlinear threshold behavior in the relationship between life expectancy and economic growth in the country in a two regime STRuctures with a threshold level of 55.34 years. In other words, our findings are both consistent with Acemoglu and Johnson (2007) for the negative impact and with demographic transition theory for the reducing effect of life expectancy on economic growth in Iran. This shows the country is approaching the stage of the fertility transition, where the increase in life expectancy will bring about a decline in population.

Iran's provinces have experienced high inflationary pressures over the past few decades. This paper models the dynamics of inflation in terms of spatial effects between Iranian provinces using the hybrid Phillips New Keynesian Curve during the period (1392-1380). The results show that, the Phillips Keynesian curve is suitable for investigating the dynamics of inflation in Iran's provinces. Findings indicate that provinces focus on setting prices of their goods based on a combination of forward looking and backward looking rules, and that forward looking behaviors will have a STRonger effect on the rate of inflation in the current period. Also in each province, the output gap as representative of the actual variables has an effect on the inflation rate of its current period. Finally, considering the significance of spatial auto-correlation between Iran's provinces, output gap, expected and lagged inflation rates in adjacent provinces have negative effects on the current inflation rate of the neighboring provinces.

Y-STR, DIP-STR, and SNP-STR are useful alternatives for testing the low quantity of DNA in solving the challenges in interpreting forensic genetic profiling. In an unbalanced mixed DNA, partial DNA is often not detected due to the effect of masking by the dominant DNA. Therefore, in such cases interpretation of the results is limited. Furthermore, profiling of these specimens cannot be performed using conventional forensic genetic methods. Biomarkers including Y-STR, DIP-STR and SNP-STR perform well in detecting DNA contributes in the mixed sample. In the present research, the performance of each is evaluated separately.

The purpose of this paper is to study empirically the convergence of democracy in developing countries. For this purpose, the spatial econometric and panel data approach was used during the period 1990-2014. The results show that the geographic proximity of countries has a positive and significant effect on democracy. In other words, on average, the increase in the level of democracy in the geographic neighbors has led to a 6 percent increase in democracy, which reflects the political influence of each other. Also, foreign aids does not have a significant effect on the spread of democracy in developing countries. In general, the spatial effects of democracy or the theory of diffusion in developing countries are confirmed. Therefore, According to the theory of diffusion and convergence of democracy, increase or decrease in democracy in a country can increase or decrease democracy in neighboring countries.