پژوهشنامه علوم انسانی و اجتماعی
پیاپی 32 (بهار 1388)

There is long and huge literature about the impact of exchange rate on economy. It is also interesting to investigate the impact of exchange rate volatility on export. In this paper, using volatility of real weighted exchange rate, this investigation is done for non-oil export in Iran. Conditional standard error and standard error of moving average are used to quantify the volatility of exchange rate. Johansen - Juselius Method and ARDL are used for estimation. Positive effect of exchange rate and negative effect of its volatility were approved.

This study investigates the influence of risky factors on returns of companies in the petrochemical industry on the basis of monthly data in the period of 1382-1384 of the Iranian calendar. Using the Arbitrage Pricing Model (APT) excess returns of the market, percentage of the change in the foreign currency rates, percentage of changes in the inflation rates and the percentage changes in the oil prices are used of the variables in this study. Results show that the fluctuation of the excess returns of the market is significant and its coefficient is less than one which indicates that the petrochemical industry has a systematic risk less than that of the market. The percentage changes in the oil price shows a positive and significant correlation with the excess returns of the petrochemical industry. Other variables did not show significant relationships with the excess returns of the petrochemical industry.

Due to the importance of price prediction in providing protein products including chicken, this research uses methods of time series models (ARIMA) and artificial neural networks (ANNs) to forecast the trends of the chicken price in Iran for the various time paths consisting one, six and twelve months, respectively. Accordingly, we investigate the hypothesis in which ANNs are more efficient in chicken price prediction than time series models in doing so. Monthly data are collected for the period 1992:3-2007:2 (1371:1-1385:11), obtaining from the domestic resources related to the agricultural sector. The empirical results confirm that the performance of Back-Propagation Network, which is a type of ANNs, in forecasting the price trend has been mostly more precise than that of ARIMA. Also another ANN-based method, the Elman Network, has more efficiency in one month and twelve months time paths prediction than that of ARIMA. The implication is thus the use of ANNs in prediction of the Iran’s chicken price could assist policymakers in the poultry industry to set up appropriate price policies through predicting correctly market fluctuations.

Innovation is an important factor in economic growth and social welfare, if it diffused in production and consumption by individual of society. The diffusion of innovation is the process by which the use and ownership of a new technology spread over time. If we draw the cumulative of the recipients of a technology with respect to time we will see an S-shape curve. The studies show penetration and diffusion of all innovation have S-shape curve. This paper analyses the pattern and the rate of diffusion T.V, Radio, and laundry by Iranian family. It is shown that the patterns of diffusion T.V and Radio are S-shape but for laundry S shape curve are currently still at the early stage of development. The result show that price of technology, price of substitution goods,disposiable income, imports, domestic production, complexity and imitation have affected the number of potential adaptor. Imitation coefficients for T.V, Radio, and laundry are 0.033,0.04and0.023 respectively.

This article analyzes the inter-relationship between inflation and sect oral production by vector auto regression (VAR) and vector error correction (VEC) models. In this research, we use the data extracted between years 1974-2005.The results show that the inflation is not a mere monetary phenomenon in Iran and its chronicity is related to real variables (production and sect oral production).Also, based on the results of this research, the relation between inflation and production is a long term issue. While, this relation (between sect oral production and inflation) in services sector is shorter run than agriculture and industry. Besides, in the short run, based on the results of variance decomposition, the contribution of agriculture sector in inflation is more than services and the latter is more than industry. Therefore, the government can regulate more the prices of agricultural and services productions in order to control the inflation. On the other hand, results of estimated VAR model indicate that services sector is more sensitive to increase in inflation rather than other sectors. Such that as inflation increases, the production of services sector increases more than other sectors and by increase in production of services sector, inflation reduces more rapidly in relation to other sectors. Also, the application of estimated models in policy making is that for controlling the inflation in Iran one can not rely only on monetary policies and in long run the real sector of economy (production) should be taken into account.

The recent theories of economic growth indicated human capital and technology knowledge have an important role on economic growth. This study is going to investigate the role of human capital on GDP of Iran. We use James Raymo(1995) model which includes three variables: physical capital, labor force and human capital. Using cointegration method of Johanson and Juselius, The results of this paper suggest human capital has a positive impact on GDP in long-run, while it has a little and negative impact on GDP in short-run.