General Equilibrium Resource Elasticity in an Open Resource-Abundant Economy

This study investigates the sensitivity of macro and sectoral variables to natural resource revenues in a resource-abundant developing country. Here, different transmission mechanisms are in effect. The paper considers the exchange rate channel, financial sector channel, capital flow channel, public sector channel, and resource reallocation channel. I employ a large scale real-financial general equilibrium model with especial focus on fossil fuel energy, natural resources, financial sector interactions, inter-sectoral linkages, and public sector responses. The model is used to predict the likely changes in oil and gas exports in Iran. It causes more oil exports but at lower international prices. Our comparative static analysis indicates that resource elasticity for GDP is from +0.10 to +0.13; for public services is from +0.16 to +0.27; for import is from +0.42 to +0.45; for mineral extraction is from -0.50 to -0.10, and for the manufacturing sector is from -0.08 to -0.06. The simulation reveals extraction competition among natural resources

General Equilibrium Resource Elasticity in an Open Resource-Abundant Economy

This study investigates the sensitivity of macro and sectoral variables to natural resource revenues in a resource-abundant developing country. Here, different transmission mechanisms are in effect. The paper considers the exchange rate channel, financial sector channel, capital flow channel, public sector channel, and resource reallocation channel. I employ a large scale real-financial general equilibrium model with especial focus on fossil fuel energy, natural resources, financial sector interactions, inter-sectoral linkages, and public sector responses. The model is used to predict the likely changes in oil and gas exports in Iran. It causes more oil exports but at lower international prices. Our comparative static analysis indicates that resource elasticity for GDP is from +0.10 to +0.13; for public services is from +0.16 to +0.27; for import is from +0.42 to +0.45; for mineral extraction is from -0.50 to -0.10, and for the manufacturing sector is from -0.08 to -0.06. The simulation reveals extraction competition among natural resources

A Survey on Lead-Lag Effect on Small and Large Size Portfolios in Tehran Stock Exchange

In inefficient markets, returns are not distributed normally and they have serial correlations. It is obvious that the price changes are not independent, so there is a pattern in price changes which help investors to gain unusual benefits. One of the patterns which are concerned with an inefficient market is the lead-lag effect. This research investigates the existence of this effect between small and large size portfolios in Tehran Stock Exchange during the period of 2011-2017. This relationship was examined both in short-run by using cross-correlation approach and vector auto-regressive model and long-run by employing cointegration methodology. Cross-correlation matrices imply that there is a lead-lag effect in short-run. Existence profiles and variance decomposition are used for further validation, the results show that all of the shocks were fully absorbed after three weeks but there is no pattern for big portfolios indicating that they absorbed the shocks more rapidly than small portfolios, and also overreaction is observed only in one out of two small portfolios of the sample.With confirming the existence of lead-lag effect in long-run by Cointegration approach, the ability of ECM models in out of sample forecasting is concerned which is measured by root mean squared error and Wilcoxon's signed-rank test. However, the results indicate that the error correction model has superior forecasting performance relative to models without the error correction terms but the Wilcoxon's signed-rank test does not reject the null hypothesis that the two RMSEs are the equal

Estimation of Transverse Mixing Coefficient in Straight and Meandering Streams

Transverse mixing coefficient (TMC) is one of the key factors in the modelling of lateral dispersion of pollutants. Several researchers have attempted to estimate this coefficient using various models. However, robust equations that can accurately estimate lateral mixing in both straight and meandering streams are still required. In this study, novel formulae were developed using the hydraulic and geometric parameters of rivers. The multiple linear regression (MLR), genetic programming based symbolic regression (GPSR) and dimensionless parameters were used for this purpose. Two extensive data sets including data from straight channels/streams and meandering ones were employed to develop the formulae. The main advantage of the developed formula for meandering streams is proper consideration of the effects of aspect ratio, friction, and sinuosity. The formulae performances were then compared quantitatively with those of existing ones using accuracy metrics such as RMSE (Root Mean Square Error). The results illustrated that the proposed formulae outperform others in terms of accuracy and can be used for estimating TMC in straight and meandering streams. In addition, the comparison of MLR and GPSR models showed that the latter is marginally more accurate than MLR specially in meandering streams. However, the MLR models presented a more justifiable relationship between the TMC and governing dimensionless parameters. The main advantages of the presented formulae are that they are more accurate than previous models, can be used in both meandering and straight streams; and can be easily implemented in numerical models to estimate the pollutant concentration and mixing length