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  The aim of this study is to review the causal relations between TFP growth and inflation as one of the attracting issues in Macroeconomic literature. For the first time in Iran, we have used the wavelet decomposition technique to study this relation. Both TFP growth and inflation series between 1960-2006 are decomposed up to three levels. Our analysis of causality relations between all the composed and decomposed series shows that though no statically meaningful effect between original series has been proved, there are some negative relations between decomposed series in first and second level. Moreover, our study reveals some previously unknown spillover effects between various frequencies of both series as explained in paper. Finally, on the basis of relations founded between decomposed series of inflation in different frequencies, we introduce a new instrument to measure the volatility of inflation.

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The concept of “Innovation” has changed considerably in recent years. According to new theories, the innovation emerges in a system of interrelated elements and determinants during which the idea changes to a commercialized output or process. The literature on the innovation has concentrated mainly on various aspects of innovation chain separately. In this paper we tried to investigate the general effects of the whole elements of the innovation chain simultaneously. These elements are: R&D expenditures, physical capital formation, human capital and patent filling (residence and non-residence). We utilized multivariable time-series methods including cointegration and vector error correction model (VECM) to assess the long-run effects of innovation elements on total factor productivity in Iran. Results show that excluding the human capital variable, other elements of innovation chain have positive effects on TFP among them, residence and non-residence patent filling having the normalized long-run coefficients of 0.58 and 0.48 respectively, are the most important factors affecting TFP in Iran.

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Efficiency analysis plays an important role in price regulation in the electricity distribution sector. This paper analyses efficiency and productivity of 38 electric distribution companies in Iran from year 1387 to 1389 (Iranian calendar year) by using slack based model (SBM). Super efficiency analysis is employed to rank full efficient companies. According to results, Tabriz, Ahwaz and north Khorasan companies have best performance among others. To examine importance of losses inclusion as input on super efficiency scores, statistical tests are utilized. Results indicate significant difference in super efficiency scores with and without accounting for losses. Average productivity index of total companies has declined by 4 percent under investigated period. Further, Panel data analysis applied to specify determinants of super efficiency of electricity distribution companies. According to results, Loss rate, network density and transformer load factor are the main determinants of super efficiency.

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Unobservable productivity shocks cause selection and simultaneity problems in firm’s decisions and these problems cause estimators such as ordinary least squares, have biased estimation for coefficients of production function inputs. In this study, data of five automaker companies in the period of 1383-1387 have been used and production function of car industry have been estimated by ordinary least squares, fixed effects, random effects, Olly and Pakes (1996) and Levinsohn and Petrin (2003a) approaches. The results show that fixed effects and Levinsohn and Petrin (2003a) approaches can’t be appropriate for the production function estimation of car industry. In other words, reaction of automaker companies to productivity shocks will not be done through adjustment in labor, capital and energy demands and there is no significant correlation between inputs adjustment and productivity shocks in car industry. But estimated coefficients of energy and capital in semiparametric, random effects and ordinary least squares approaches show that estimated coefficients of energy and capital in random effects and ordinary least squares approaches are upwardly and downwardly biased, respectively. These results are perfectly consistent with the viewpoint of Olly and Pakes (1996) about bias of traditional estimators and show that automaker companies, in response to the productivity shock, adjust their investment level. In addition based on estimation of semiparametric approach, output elasticity of capital and energy will be respectively 0.82 and 0.64.

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Productivity is one of the important factors in exploration, extraction and production of oil and gas. On the other hands, the literature indicates that the process of economic liberalization is an inventible matter and globalization gradually is improving. So it is important that the effect of oil shocks is considered In Iran. Based on International trade statistics, Shanghai’s countries is one of the most important trading partners of Iran. Therefore, this study investigates whether or not the extraction, exploration and production of oil and gas in Iran is affected by productivity shocks in industry sector of Shanghai’s countries. The Computing general equilibrium approach is used for investigating the effect of productivity shocks on four sectors in Iran (including industry, agriculture, services and oil sectors). Social Accounting Matrix Adjusted 2004 is considered for three scenarios including 3, 5 and 7 percent of productivity shocks (based on world economy trend). The results indicate that the increase in productivity in three industry sector scenarios of Shanghai’s countries declines the oil and gas extraction in these countries, representing efficient use of existing resources and superior technology in other industries as well as focus on oil and gas imports from other countries. So, productivity scenarios indicate that increase in the industrial sector productivity of Shanghai’s countries causes increase in oil and gas extraction in Iran. In addition to showing the relationship between economic of Iran and economic situation of Shanghai’s countries, this issue explains the process of economic globalization.