JOURNAL OF SUSTAINABLE GROWTH AND DEVELOPMENT (THE ECONOMIC RESEARCH)
Year:2008 | Volume:8 | Issue:2|Papers Count:9

Hotels are fundamental elements of tourism industry and provide various services for tourists. Moreover, hotels development has an important impact on tourism industry development. Therefore, an understanding of hotels relative efficiency performance, over a period of time, is important for practitioners, analysts, and policymakers alike.The main objective of this paper is to measure the efficiency of the four and five stars hotels in Tehran. A Data Envelopment Analysis (DEA) is employed to investigate the technical efficiency of eight hotels using the data over the period 1380 - 1384. DEA analysis is a methodology for analyzing the relative efficiency of units having the same multiple inputs and multiple outputs. fu this study, the input variables comprise employee, rooms, restaurants and land and the output variables include hotel income and occupancy rate.The results show that technical and scale efficiency scores in all periods are relatively higher but there is no a regular trend over the period under study. Since 1380 to 1384; 75, 62.5, 75, 62.5, and 50 percent of the selected hotels were respectively efficient under the constant and variable to scale assumptions. Moreover, the findings confirm that more scale efficiency (0.997) refers to 1380 and less scale efficiency (0.894) refers to 1381 and 1382. The results also show that more technical efficiency, on average, under variable to scale assumption (0.964) refers to 1380 and less technical efficiency (0.894) refers to 1384. Finally, the efficiency of the five stars hotels is more than the four stars hotels implying the priority of the five stars hotel's development in Tehran.Overall, the findings indicate that the particular problem is mismanagement in the Tehran's hotels. Consequently, it caused the average scale efficiency to be more than the average technical efficiency. Since management plays a vital role in the efficiency improvement of hotels, this paper suggests the improvements of managerial systems in the hotels. More specifically, education, employment and Customer Reservation Systems (CRS) are the main factors influencing the efficiency.

Defense industry plays an important and strategic function in economy.Defense industry effects economy mainly through security and weapon exports. There has been a growing literature examining military expenditures in developing countries. Theoretically, there is no definite prediction of the direction of causation between economic growth and military spending. The majority of these studies have focused on whether or not defense spending has had a positive, a negative, or no impact whatsoever on economic growth in developing countries.The purpose of this paper is to examine the effects of defense spending on economic growth and private consumption in Iran using time series data for the period 1974 to 2005.A four-sector model based on the Feder approach is employed to detect any likely relationship between those variables. The model comprises consumption sector, defense sector, non-defense government sector, and exports sector.The findings show that there is statistically significant and positive relation between defense spending and economic growth in Iran, while the effects of defense spending on private consumption is negative.

Recent discussions on macroeconomic policy in developing and developed countries have emphasized the crucial role played by the real exchange rate in the adjustment process. There'1s a growing agreement that sustained real exchange rate misalignment will usually generate severe macroeconomic disequilibria through affecting macroeconomic variables.This study aims to investigate the sources of macroeconomic variable Fluctuations in Iran focusing on real exchange rate. We implement the model with a structural VAR model and variance decomposition technique using annual macro-economic time series data of the Iranian economy from 1970to 2005.The findings suggest that real exchange rate fluctuations in Iran are mostly explained by monetary shocks as well as oil price shocks. Moreover, the results show that major part of income fluctuations in Iran are due to the price shocks, oil price shocks, money shocks, and supply shocks.This paper recommends that diversifying the economy,' developing infrastructure, stabilizing prices, increasing investment, reducing money fluctuations, and controlling money supply may well then contribute to improve growth performance in the economy. According to our results, money disturbances and oil prices effect significantly real exchange rate fluctuations. So, this paper suggests that conducting monetary policy requires a greater caution to stabilize the economy.

The worldwide development of information and communication technology (lCT), commonly called lCT revolution, has accelerated dramatically since the second half of twenty century. The main characteristic of this revolution is: the rapidly increasing computing power of new lCT products. Varying results achieved by different countries and regions fuel the debate over exactly how much influence lCT has on economic growth. We provide an insight of results from past studies carried out to confirm the productive relationship between the two, lCT and economic growth.The focus of this paper is to examine the impact of lCT on economic growth in OPEC countries using panel data over the period 1998-2004.Based on the literature, a Cobb-Douglas production function is specified to include lCT indicators. The results of estimates show that lCT contributed significantly to economic growth of OPEC countries over the period under study.

The evolution of financial data shows a high degree of volatility of the series, coupled with increasing difficulties of forecasting financial variables. Some alternative forecasting methods, based on the literature review, have been developed, which can be particularly useful in the analysis of financial time series. Despite of the numerous time series forecasting models, the accuracy of time series forecasting is fundamental to many decision processes. Selecting an efficient technique in unique situations is very difficult task for forecasters. Many researchers have integrated linear and nonlinear methods in order to yield more accurate results.In practice, it is difficult to determine the time series under study are generated from a linear or nonlinear underlying process while many aspects of economic behavior may not be pure linear or nonlinear. Although both ARIMA and Artificial Neural Networks (ANNs) models have the flexibility in modeling a variety of problems, none of which is universally the best model used indiscriminately in every forecasting situation.In this paper, based on the foundations of ARIMA and ANNs models, a hybrid method is proposed to forecast exchange rate. Empirical results indicate that integrating linear and nonlinear ARIMA and Artificial Neural Networks (ANNs) models can be an effective way to improve forecasting accuracy Achieved by either of the above linear and nonlinear models used separately.

In general, the scarce resources are efficiently allocated to achieve the economic and social goals of an economy. This means the factors of production including labour force and capital stock must be allocated using rational and scientific approaches. This means investors need to be able to evaluate the cost-benefit of investment in order to make informed and efficient decisions.In this article, we analyze the cost-benefit of technical and professional trainings in Iran. Three courses which comprise skilled labor force, first class and second-class labor forces are considered in this study and then the cost-benefit methodology is employed. This methodology can be used in future cost-benefit studies of technical and professional trainings.The result obtained from the analysis shows that the educational rate of return in all three courses is higher than the rate of return in the participation papers market in Iran. This result obtained after adjusting the effects of individual ability on their income and correcting the adjustment effects of employment.

Consumer behavior analysis is a fundamental issue in economics. The most prominent methodology that economists use to attribute preferences according to this principle is the revealed preference concept. Therefore, neoclassical utility function is capable to test the rational behavior hypothesis of consumer.In this paper, we formalize a method of revealed preferences in place of Neoclassical utility function to test the hypothesis of rational behavior using the Iranian rural households' consumption data over the period 1982-2005.According to results, we didn't detect any violations in the whole consumption data. But in agriculture commodities group, we detected 4 violations using generalized Afriat index ascribed to measurement error.overall, the findings of the study confirm the hypothesis of rational behavior.Thus, there exists a utility function that is non-satiated, continuous, monotonic, and concave that rationalizes the consumption data of rural households in Iran.

Iran plans to export natural gas (NG) to Western Europe using a system of pipelines running through Iran, Turkey, and Western Europe. International gas pricing is usually undertaken through negotiations between buyers and sellers on a bilateral basis. Currently, Russia is the only exporter of gas from the Former Soviet region. So, Russia competes strongly with Iran to export NG to Western Europe.This paper develops a bargaining model to study natural gas pricing and analyze competition between Iran and Russia as gas suppliers to Western Europe. In this model, it is assumed that NG pricing is usually linked to the prices of alternative fuels as competing energy sources. Therefore, in light of previous evidence, it is reasonable to consider that there is a long-run relationship between NG price and price of alternative fuels.Initially, a regression model is specified to investigate unlagged relationship among variables. This relationship is estimated using the Johansen cointegration technique and then we forecast margins of the Iranian NG price. Finally, a VECM model is identified and used to forecast the lower and upper bounds of future NG price.