Dr Teymur Rahmani, Ebrahim Hasanzadeh,
Volume 2, Issue 5 (10-2011)
Abstract
Convergence hypothesis includes two types of beta and sigma. In this study, we examine convergence hypothesis among Iran’s provinces and discuss the effect of internal net migration in that context since 2000 to 2007. The results indicate that poor provinces grow faster than rich ones and there is beta convergence in Iran. About sigma convergence, we found that the dispersion of GDP per capita increase among these provinces over the years.
Immigration is one of the factors that could influence economic growth of provinces and convergence among them. The results show a direct relationship between net immigration and per capita GDP growth of provinces. When the variable of net migration is included into convergence equation, it increases beta coefficient. So, net migration has a negative effect on convergence. Immigration flows more from the poor provinces to rich provinces and increases the gap among them.
Moloud Rahmaniani, Reza Taleblo,
Volume 8, Issue 29 (10-2017)
Abstract
The level of asymmetric information in financial markets is important for its impact on the market formation, price levels and its interaction with investment risk. Also, determining the optimal rules by policy makers and determining the trading strategy by investors is done according to the level of information symmetry in the market. In financial literature, many metrics have been developed to measure the asymmetry of market information. In recent years, another measure known as probability of informed trading (PIN) has been introduced to measure the level of asymmetric information, based on the framework of market microstructure. Larger PINs from 0 to 1 range indicate higher information asymmetry levels. In this study, using the Easley, O'Hara (1992) approach, the probability informed trading as a measure of the level of market information asymmetry for the 12 selected companies from listed companies in Tehran Stock Exchange is estimated. We used maximum likelihood to estimate parameters with R package. The results show that average of PIN varies from 0.35 to 0.4 for different companies.
