جستجوی مقالات مرتبط با کلیدواژه « bayesian model averaging (bma) » در نشریات گروه « اقتصاد »

Financial Corruption is one of the aspects of inefficiency in societies that undermines the economic growth and development of countries and is considered by planners and policymakers. Therefore, this study identifies 22 effective variables on financial corruption index and ranks them using the Bayesian Model Averaging (BMA) in 26 countries rich with natural resources during 1996-2017.Inclusion probability indicates that political stability, democracy, economic globalization, property rights, socialist legal origin, ethnic fractionalization and language fractionalization are the most effective factors on financial corruption index.Also the variables of investment freedom, total natural resources rents and GDP per capita take second to fourth rank regarding their effects on financial corruption model.the variables of trade freedom, military expenditure and size of government with 51%, 45% and 21% probability of occurrence have affected corruption in a in a negative direction. On the other hand, there is no significant relationship between the variables of business freedom and monetary freedom and the corruption index in these countries, due to the low probability of these variables in the model. It seems these variables can affect corruption only through other channels of economic freedom in the model.

Financial development is one of the important and effective factors on the countries economic development and it is considered by planners and policymakers. Financial development is a multifaceted concept that, in addition to the monetary and banking dimension, includes other dimensions such as financial freedom, quality of governance and oversight, technological advances and existing institutional capacity. So this study, identifies 16 effective variables on financial development index and ranks them using the Bayesian model averaging (BMA) in Iran during 1991-2017.Inclusion probability indicates that liquidity Ratio and Credit Risk are the most effective economic factors on Iran's financial development. Inclusion probability indicates that the size of the government, the rate of inflation, the openness of trade, the ratio of participation bonds and the size of the banking market take third to seventh rank regarding their effects on financial development model of Iran respectively. These variables have positively affected on the financial development index. Also, corruption control rank and government effectiveness rank with 44% and 36% probability of occurrence are the most effective non-economic and institutional factors in the financial development model of Iran, respectively, and affect the financial development index in a negative direction.On the other hand, there is no significant relationship between government budget deficit and financial development in Iran, due to the low probability of this variable in the model; it seems that this variable can affect financial development only through the channel of other variables included in the model.

Tax revenues are the most important sources of public funding. In other words, the role of tax revenues as the most effective tool of fiscal policy, is very important. Therefore, according to the essential role of tax revenue on governments’ economic situation, and since a prerequisite for effective actions in order to implement appropriate fiscal policies, is to know its determinants, this paper tried to investigate the determinants of tax revenues in Iran during 1350-1392, using a Bayesian Econometric Approach and applying Bayesian Model Averaging. The results show that some variables such as literacy rate, GDP growth, population growth, value added of industry sector, and government expenditure have positive effects, but variables such as exchange rate, GINI index, value added of agricultural sector, oil revenue, and value added of oil sector have negative effects on tax revenues. The policy recommendations resulted from this study are: To increase tax revenues through structural changes in economy by increasing the share of industry sector and industrialization of agricultural sector; To improve tax laws and to find executive effective solutions in order to decrease big investors tax evasion; and to try in order to increase efficiency and effectiveness of the education system.

Banking industry is one of the most important and sensitive economic sectors of countries that in the course of its activities is facing with various types of risk. Liquidity Risk (LR) is one of the risks that banks are highly vulnerable to it. If the LR do not control and manage that leads to bankruptcy of banks. This research by using Bayesian econometric methods deals to identify and investigate the influencing factors on the LR. For this aim, Panel data have been collected of 14 active banks in Iran's banking system for 15 variables including economic and intra-banking factors during 1382-1394. The results indicate the liabilities to Asset Ratio, the ratio of long-term investment deposits, the ratio of capital to assets, bank size, Efficiency Ratio, Credit Risk, net interest margin and the composition of deposits are the most effective variables in the Iranian banks LR pattern. The including the possibility of the other variables such as exchange rates, inflation rate, stock price index growth rate, return on assets, loans to deposit ratio, Cash to Asset Ratio and economic growth are less than 25% in this pattern. Thus there is not strong evidence for their effectiveness on the LR. It seems these variables, especially macroeconomic factors, can affect the LR only through the intra banking factors.

In this research to show how 14 variables affect inflation in period 1974-2007, Bayesian model averaging and weighted average least square methods has been used. And also by using Vselect program optimal model for every independent variable has been identified. Results show that price index growth of imported goods is the main factor for inflation in Iran economic. In ranking this 14 factors –that achieved based on their probability for presence in the model-in turn price index growth of imported goods, GDP growth excluding oil group, lag liquidity are must effective factors.also Vselect results show that the most efficient model among every models that have an independent variable is the model that include price index growth of imported goods. Optimal model with two independent variable –include price index growth of imported goods , GDP growth excluding oil group and optimal model with tree independent variables include price index growth of imported goods , GDP growth excluding oil group, lag liquidity growth.

This paper identifies determinants of economic growth in Iran, by using averaging methods and annual time series data from 1974 to 2012. The results indicate that ratio of oil revenue toGDPis the most important variable affecting economic growth. Also the second and third effective variables on growth are respectively ratio of imported capital and intermediate goods toGDPand labor force which lead to an increase in growth. Endogenous growth factors which are the factors contributing to formation of human capital, not possess a large role in growth process. Investments, especially government investment affects contrary to were expected. In fact, low quality, and productivity of investments and poor allocation reduced importance of investment’s quantity. The nature of Iran’s economy has not endogenous and dynamic features and predominantly, growth has been made by injecting of exogenous sources. Emphasis on formal and informal educational orientation in the quality of human capital instead of increasing in quantity of education is recommended.

The attention to sustainable development and the necessity of environmental protection, and also the adverse effects of environmental pollution on development and quality of life all over the world, have made the environmental protection a major concern of economic officials. For this reason, over the recent decades an extensive literature has been devoted to improve environmental quality and its determinants. Therefore, economic analysts have focused on these issues more than before. In this regard, to know the effects of air pollution determinants can contribute economic officials to reduce pollution. This study attempted to investigate the effects of some variables on CO2 (as one of the most important air pollution indicators) in developing countries during 1992-2014 using Bayesian econometrics approach and applying Bayesian Model Averaging (BMA). Finally, according to the theoretical and empirical evidence, it is found that Environmental Kuznets’ hypothesized inverted U-shaped relationship between economic growth and environmental quality is supported by data. The findings of the study also showed that energy consumption, electricity consumption, and the variables related to industrialization have positive and almost important relationship with CO2 emissions. Against, literacy rate and income inequality have negative effects on CO2 emissions.

This paper has tried to apply Bayesian Model Averaging (BMA) and Weighted Average Least Squares (WALS) approaches as methods of averaging in Bayesian econometrics in order to investigate the impact of 18 macroeconomic variables on Gini coefficient in Iran based on annual data from 1976 to 2010. The results of two approaches indicate that the growth rate of Gross domestic products is the most important determinant of the Gini coefficient, implying economic growth arising from oil booms leads to more unequal distribution of income. As regards to other variables, the results of BMA estimation indicate that second and third effective variables on Gini coefficient are respectively the ratio of government current expenditure to GDP and the ratio of oil revenue to GDP for which an increase in the ratios engenders inequality. Thus the distribution of oil rents and government expenditure is inconsistent with primary purposes of politicians to ameliorate income distribution. Also the results of WALS estimation rank openness and exchange rate as the most effective variables respectively with positive sign. Therefore economic liberalization moving along with oil revenue during the sample period, has been against the favor of lower income groups. According to aforementioned results, it is necessary to revise economic growth policies to the benefit of low-income groups of people. In addition, renovation of budgeting process and allocation of resources with aim to reduce rent-seeking opportunities and more privileges for low-income groups must be considered by policy makers.

The main objective of this study is to investigate the major determinants of exports in developing countries over 2006-2012 using the econometric approach of Bayesian Model Averaging. According to the empirical results of the study، the degree of openness and ratio of gross domestic saving to GDP are key factors in explaining exports in these countries. The impact of other variables such as import tariffs and duties، the number of internet users، and the rate of inflation also have been relatively important. In addition، the results indicate that the share of agriculture in economic activities has a negative impact on exports with a probability of 32%، while the share of industry has a positive but insignificant effect on exports. The study concluded that the variables related to communication facilities (the number of mobile subscribers and Internet users) have positive effects on exports. According to the results، it seems that some policy actions should be taken to reduce inflation rate، enhance education system، allocate more efficiency labor forces among different economic sectors، and implement a reasonable proportionality among different indirect taxes. Central Banks of the countries under study also should take some appropriate foreign exchange policies in order to expand exports.

Due to the significant impact of inflation on macro-economic variables, researchers pay tremendous amount of attention to inflation determinants. Accordingly, the present research investigates the impact of 13 variables on inflation during 1959 and 2012 by using Bayesian Model Averaging (BMA) method. The ranking of the 13 explanatory variables were obtained based on the probability of their inclusion in model. The results show that price of energy and money imbalance (Lag ratio of money to nominal output) have expected and positive effects on the inflation rate with a probability of 100 % and they are the key explanatory variables in inflation equation. The energy price, currency imbalance measure, money growth and market exchange rate growth are the first four determinants of inflation in Iran. The impact of the output growth on inflation is not significant in the short-run but it gradually influences the inflation through money imbalance channel in the long-run. In addition, most anti-inflation effects appear with delay due to a decrease in the money supply. These results imply the dominance of monetary variables or monetary inflation in the Iranian economy and the cost push factors not having significant impact on the prices. Also, variables such as oil revenues and imports can have an impact of inflation only if they are channeled through the exchange rate, output growth and money velocity.

The positive effects of equal income distribution on macroeconomic variables such as productivity, economic growth and poverty reduction and consequently economic and social welfare improvement on one hand, and adverse effects of income inequality on social variables such as crime and delinquency on the other hand, have made equal distribution to one of the major concerns of economic officials of the country. For this reason, over the recent decades, an extensive literature has been devoted to achieve an equitable income distribution and investigation into the determinants of income distribution improvement. This study has attempted to investigate the effects of different types of tax as well as some other factors on one of the most important inequality indicators (GINI index) in Iran’s provinces by a Bayesian Econometrics Approach and applying Bayesian Model Averaging (BMA). Finally, according to the theoretical and empirical evidence, it is found that Kuznets’ hypothesized inverted U-shaped relationship between economic development and income distribution is supported by data.

Identifying the factors that contribute to sustained economic growth of countries is the main concerns of economic researchers. The present paper employs a Bayesian econometrics approach based on Bayesian Model Averaging (BMA) method to investigate the effect of public and private health expenditure on economic growth in developing economies. The empirical findings show that public health expenditure positively and private health expenditure negatively affect on the long-term economic growth of developing countries. Also، hospital beds do have a positive important role in explaining long-term economic growth.

Identifying the factors that contribute to the sustained economic growth of countries is the main concern of economic researchers. The present paper employs the Bayesian Model Averaging (BMA) method based on a Bayesian econometrics approach to investigate the effect of three variables of primary, secondary and tertiary gross enrollment ratios on long-term economic growth in a set of developing economies. The empirical findings show that each of these three variables negatively affects the long-term economic growth of developing countries. Furthermore, the secondary gross enrollment ratio certainly and the other two variables uncertainly affect the long-term economic growth.