This paper attempts to model the demand function for natural gas in residential and commercial sectors in Iran using econometric approach of smooth transition regression in a continuous and nonlinear manner. To this end, the annual data of natural gas real price and ele More
This paper attempts to model the demand function for natural gas in residential and commercial sectors in Iran using econometric approach of smooth transition regression in a continuous and nonlinear manner. To this end, the annual data of natural gas real price and electricity real price in residential and commercial sectors, revenue, the number of natural gas consumers and mean temperature for the period 1972 to 2009 have been utilized as the impact factors of natural gas demand in residential and commercial sectors. The results indicate that natural gas demand follows a two-regime pattern of LSTR1 considering the real price of natural gas in residential and commercial sectors as the transition variable. The LSTR1 model estimated the regime switching point, or the threshold extreme, to be at 60.95 Rials-Cubic Meter of real price of natural gas, and determined the slope parameter to be 27.6. Variables such as revenue, real price of gas, and the number of consumers affect the natural gas consumption positively in residential and commercial sectors and their effectiveness increase as the threshold extreme is passed. Natural gas demand. On the other hand, it maintains an inverse relation with the real price of natural gas whose effectiveness increases with entry into the second regime.
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This study investigates the relationships between Bitcoin (BTC) prices and fluctuations in relation to gold, USD, and Iran's oil prices from 2019 to 2022. We employed the dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (DCC-GARC More
This study investigates the relationships between Bitcoin (BTC) prices and fluctuations in relation to gold, USD, and Iran's oil prices from 2019 to 2022. We employed the dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (DCC-GARCH) method to model the fluctua-tions of financial variables. Additionally, the smooth transition regression (STR) method was applied to explore the relationships between the variables. The results reveal significant positive correlations between BTC prices and gold, as well as oil, and a negative correlation with USD prices. We observed volatility persistence, causality, and phase differences between BTC and other financial instruments and indicators. Notably, a negative relationship was identified between Bitcoin and the USD in both linear and non-linear aspects, with a larger coefficient in the second regime. Furthermore, a posi-tive relationship was found between Bitcoin and the variables of gold and oil prices, with coefficients being larger in the second regime compared to the first.
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Abstract
One of the factors that play an essential role in achieving the goal of rapid and continuous economic growth is the development of the financial sector of each country. Countries with a more developed financial system are on the path of faster economic growth More
Abstract
One of the factors that play an essential role in achieving the goal of rapid and continuous economic growth is the development of the financial sector of each country. Countries with a more developed financial system are on the path of faster economic growth because they make the economy in question capable of experiencing higher growth rates. The main purpose of this article is to investigate the effect of financial development indicators on economic growth in member countries of the Islamic Conference; Therefore, in order to examine this topic, the present article used one of the newest econometric approaches called the PSTR model and measured the non-linear effect of financial development indicators on economic growth in the member countries of the Islamic Conference during the period from 2008 to 2022. The results obtained from the PSTR model indicate the existence of a non-linear relationship between the studied variables. In the final PSTR model, the slope parameter, which indicates the speed of adjustment from one regime to another regime, is equal to 21.0818, the location of regime change is estimated to be 10.5986. Therefore, if the financial development index (the ratio of internal credits of banks to gross domestic product) exceeds 10.5986 percent, the behavior of the variables will be according to the second regime, and if it is less than the above threshold, it will be placed in the first regime. The coefficients of the variables (percentages) have been estimated. The obtained results show that the financial development index (the ratio of internal credits of banks to gross domestic production) has a different effect on economic growth in both regimes.
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