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Although fossil fuels consumption may causes to rapid economic growth, but due to related pollutants and its consequences, the world has suffered from climate changes. Moreover, fossil fuel resources such as petroleum, gas, coal and uranium are being exhausted rapidly in the last decades. Therefore, seeking an appropriate as well as low-cost alternative for the above-mentioned energy carriers is one of the most important research topics. Regarding this situation, the utilization of renewable energy sources especially solar and wind energies is very important. In this study, the social welfare is maximized and optimal trajectory of solar and wind energy substitution is derived by using an optimal control approach. The model is solved empirically by genetic algorithm using MATLAB software. The results show that assuming social discount rate of 5% and no reduction in solar and wind energy conversion cost during next years, transition from fossil energy to solar and wind energy must occur in 2089 while assuming a 50 % reduction in solar and wind energy conversion cost in every 10 years period, this transition must take place in 2032.

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One of the empirical relationships that have been used to study the dynamics of labor market is the Beveridge curve -the scatter plot of unemployment rates versus vacancy rates- that is used to summarize the state of that market. The starting point for deriving the Beveridge curve is a matching function between unemployed workers and vacant jobs. In this research, provincial data are combined to estimate the Beveridge curve and the matching function of Iran. The matching function is estimated using provincial data for the period 1993-2008 and for estimating the Beveridge curve, provincial data for period 2005-2008 are used. The outcomes imply that the number of unemployed workers and vacant jobs has a positive and significant relationship with successful job matches. The elasticity of matching function for the unemployed and job vacancies equals 0.24 and 0.79, respectively. The Beveridge curve depicts a convex and negative relationship between unemployment rate and vacancy rate, although the relationship is not strong.