Showing 3 results for Provinces of Iran
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.
Hossien Amiri, Fatemeh Samadian,
Volume 8, Issue 30 (12-2017)
Abstract
Construction projects are the basic requirements of sustainable development and growth. Inefficient procedures of implementing the construction projects, regardless of our financial and administrative capacities, has imposed a large amount of unfinished and occasionally stopped projects to national economy. Since there are various components that affect the fate of projects, therefore, the main purpose of this paper is to answer this question that whether the political cycles affect the adoption and implementation of provincial construction projects or not? In order to answer this question, two hypotheses are considered in this paper. Therefore, GMM dynamic method was used to estimate the model and test hypothesis in the years 1997-2014. Hypothesis one: political cycles affect the fate of construction projects, and the second hypothesis: the impact of political cycles on the adoption and implementation of construction projects are larger in the year prior to political cycle (election). Therefore, in order to estimate the model and test the research hypothesis, provincial data during the years was used. Results of testing two hypotheses suggest that parliamentary and presidential political cycles have a significant positive correlation with the construction projects. Results also show that the presidential political cycle has a larger impact on construction projects, meaning that the impact of political cycles on the process of adopting and implementing the construction projects in the year prior to the political cycle is larger. In this regard, in order to eliminate the impacts of the governmental and parliamentary political cycle on construction projects, it is recommended to determine a competent authority that has the necessary qualifications as well as the sufficient degree of independence and supervision power over the project's Feasibility studies. The referenced mentioned will be approve projects based on objective justification-technical and district-based studies and it prevents the adoption of development plans based on the political considerations of the government and parliamentarians.
Javad Barati,
Volume 10, Issue 38 (12-2019)
Abstract
The impacts of the tourism industry on economic growth can be divided into two categories: direct and indirect (spillover) effects. In the field of tourism, direct impacts have been the subject of many studies but the analysis of spillover effects, particularly the effects from tourism infrastructure development, have received less attention. This study, with an analytical approach and along with examining the quantitative methods and analysis of the spillover effects of various variables affecting the development of the tourism industry, has investigated these impacts for each the variables and in each province. For this purpose, it has used spatial econometric models. The results confirmed the existence of spatial fixed effects and was applied Spatial Durbin Model (based on Lagrange coefficient test). The results show a positive and significant impact of transport infrastructure variables (road, rail, air) and travel agencies on the growth of value added in the tourism industry. Investigation of the spillover effects of infrastructure variables on growth of value added has shown that, except for Accommodation services, other tourism infrastructure variables have negative spillover effects for neighboring provinces, and also have positive spillover effects for other (non-neighbor) provinces. The negative spillover effects on the tourism growth of the neighbor provinces are due to competition impact and relative stability in the number of domestic tourists, and the positive spillover effects on non-neighbor provinces are due to factors such as the development of multi-purpose trips and increased market access.
