Energetic Transition in Iran

In this paper, we study the effects of renewable energy consumption on economic growth in Iran in the period 1983 to 2013, through Autoregressive Distributed Lag (ARDL) method. Results show that an increase in renewable energy consumption increases economic growth. In other words, there is a positive and statistically significant relationship between renewable energy consumption and economic growth. The results show that in the long-run 1% increase in consumption of renewable energy leads to 4.06% increase in economic growth; they also show that in a short-run, 1% increase in it also can lead to 7.5% increase in economic growth

Deep sea nature-based solutions to climate change

The deep sea (below 200 m depth) is the largest carbon sink on Earth. It hosts abundant biodiversity that underpins the carbon cycle and provides provisioning, supporting, regulating and cultural ecosystem services. There is growing attention to climate-regulating ocean ecosystem services from the scientific, business and political sectors. In this essay we synthesize the unique biophysical, socioeconomic and governance characteristics of the deep sea to critically assess opportunities for deep-sea blue carbon to mitigate climate change. Deep-sea blue carbon consists of carbon fluxes and storage including carbon transferred from the atmosphere by the inorganic and organic carbon pumps to deep water, carbon sequestered in the skeletons and bodies of deep-sea organisms, carbon buried within sediments or captured in carbonate rock. However, mitigating climate change through deep-sea blue carbon enhancement suffers from lack of scientific knowledge and verification, technological limitations, potential environmental impacts, a lack of cooperation and collaboration, and underdeveloped governance. Together, these issues suggest that deep-sea climate change mitigation is limited. Thus, we suggest that a strong focus on blue carbon is too limited a framework for managing the deep sea to contribute to international goals, including the Sustainable Development Goals (SDGs), the Paris Agreement and the post-2020 Biodiversity Goals. Instead, the deep sea can be viewed as a more holistic nature-based solution, including many ecosystem services and biodiversity in addition to climate. Environmental impact assessments (EIAs), area-based management, pollution reduction, moratoria, carbon accounting and fisheries management are tools in international treaties that could help realize benefits from deep-sea, nature-based solutions

The Impact of Sectorial Economic Growth on Poverty and Social welfare in Provinces of Iran (2000-2007)

Introduction In the recent literature on poverty and growth two main questions are receiving increasing attention: How much do the poor share in aggregate economic growth? And what factors explain differences (across space or over time) in the impacts of economic growth on poverty? In economic activities, with the growth of the agricultural sector, it is expected that extreme poverty will be reduced and income distribution will become more appropriate. Agricultural sector contains employment opportunities, both direct and indirect, which increase national output more than many others sectors. Research shows that the most successful economies are those that push the industry towards increasing exports. Studies show that the growth rate of the service sector (in terms of employment) is higher. Education, health and recreation services, have a positive impact on the quality of the organization. Professional services, including special skills for increasing competitiveness of firms provide special expertise for a business company which is competitive. One of the other policies that come to fight poverty is increasing human capital through training people. Increasing levels of education lead to increasing individual employment. This means that the main level of a nation's life is the ability to use skills, awareness about issues related to health and education. Income inequality is another important factor affecting poverty which is in a close relationship with it. In fact, as income inequality increases, the gap between the poor and the rich becomes wider. Since the growth of agriculture, industry and service sectors and the impact of variables such as education, health and social assistance on them are important, the question is what relationships might exist between these variables and poverty and welfare? Previous research has shown that growth in average income is correlated with reduction in the occurrence and depth of poverty. Looking at 67 countries, Ravallion and Chen (1997) find that inequality changes were uncorrelated with growth rates between 1981 and 1994, implying that poverty declines are strongly correlated with growth in mean incomes. They estimated that the elasticity of poverty incidence (at the “$1-a-day” line) to mean household income was about −3. Ravallion (2001) finds a lower elasticity of −2.1, when an econometric correction is made for measurement errors in surveys. Dollar and Kraay (2002) also found that “growth is good for the poor:” in a sample of 92 countries, over four decades, the mean incomes of the poorest 20% of the population grew on average at the same rate as overall mean incomes. For India, Ravallion and Datt (1996) found that growth in the agricultural and (especially) service sectors had a higher impact on poverty than manufacturing growth. Using state-level data over time for India, Ravallion and Datt (2002) found that the elasticity of poverty to non-agricultural growth varied significantly across states, and was greater in states with higher initial literacy and farm productivity, and lower landlessness and infant mortality. There is a relationship between poverty and social welfare, as it is shown in figure (1). Figure (1)- Poverty and social welfare Material & Methods We studied the poverty and welfare impacts of economic growth in provinces of Iran using information on poverty and social welfare, output by sector and a number of controls variables for a period spanning 8 years. We used value added information for sector growth data bases and household information for calculating the social welfare index and poverty index. We applied sectorial variation in these data to shed light on the determinants of poverty dynamics in Iran. Since we have a panel of 28 provinces in 8 years, we allow the regression coefficients to vary by provinces. The estimation method is GMM. In this method we use instruments and lags for variables. To motivate our specification choice, consider first the following model in levels: Here is social welfare in province i on year t. is the average income and G is Gini coefficient. A is agricultural sector output; I is industrial sector output; and S is service sector output. So there is a lag for all of the variables. Discussion of Result & Conclusions Iran's disappointingly low rate of poverty reduction and high welfare between the 2000 and 2007 was not due only to weak economic growth — though this was certainly key. It also reflected a low growth elasticity of poverty reduction, consistent with the country's high level of inequality. In this paper, we investigated three possible sets of factors that determine the distributional component of poverty reduction and more social welfare. We did find marked differences in the poverty-reducing effect of growth across different sectors, with growth in the service sector being consistently more pro-poor than either in agriculture or industry sectors

The Impacts of Environmental and Socio-Economic Risks on the Fisheries in the Mediterranean Region

The objective of this study is to investigate the impacts of the environmental and socio-economic risks on the fisheries in the Mediterranean region from an economic point of view. A balanced panel of 21 Mediterranean countries for 2001–2018 has been estimated by the GLS method, considering heteroskedasticity and correlation among cross sections. The volume of fish landed and landed values have been considered in two models. The results show that increases in sea bottom and surface temperature, H⁺ ion concentration and salinity threaten the fisheries in the Mediterranean region for the volume of fish landed and that sea surface temperature and salinity negatively influence landed values. In addition, there is an inverse U-shaped relationship between human population and fisheries. Moreover, the Human Development Index (HDI), an indicator of countries’ adaptive capacity, has a positive impact on fisheries and indicates that countries can safeguard fisheries by improving their adaptive capacity. Finally, our results strongly show the risk of climate change for the fisheries in the Mediterranean region and that fisheries are adversely impacted by climate change as well as worsening socio-economic conditions in the absence of adaptation plans.Science, Faculty ofNon UBCOceans and Fisheries, Institute for theReviewedFacultyOthe