فصلنامه پژوهشهای اقتصادی (رشد و توسعه پایدار)
سال هفدهم شماره 2 (تابستان 1396)

Underground economy is considered as an important economic component among the world countries, and in particular developing countries. It creates a serious consequence in the economy and could lead to a deviation from the correct diagnosis of economy status and as a result prescription of the mistaken policies. Therefore, identifying the size of underground economy and using corrective measures to reduce and control it is the main concern of policymakers. Financial development is among factors affecting the performance of underground economy. It reduces the cost of credit and decreases the incentives of agents in the underground sector. This study aims to investigate how to financial development affect underground sector. To this end, it uses structural equation modeling and multiple indicators – multiple causes (MIMIC) approach. The results suggest that the average ratio of the underground economy to GDP is equal to 20.68% during 1973-2012. For one unit increase in financial development, on average, the size of the underground economy decreases by 0.05 percent.

Economic theories suggest that increasing uncertainty induces households to reduce the growth of their consumption expenditure. This study aims to examine how to change the consumption expenditure of Iranian households due to uncertainty in government expenditure. To do this, using annual data for 1978-2012, first, a measure for government expenditure uncertainty was introduced, and then its effects on household consumption behavior were analyzed. The results indicate that uncertainty in government expenditure has a negative and significant effect on growth of household consumption expenditure. On the other hand, the effect of government spending uncertainty on consumption expenditure of durable goods is positive. In other words, Iranian households in increasing uncertainty settings face with the growth of consumption spending on durable goods. Thus, the government needs to create transparency in fiscal policy, to reduce policy uncertainty for households as far as possible.

This research examines business-cycle fluctuations by using Knowledge-based Economy Index (KEI). Data have been collected using consolidated method in 116 countries over the period 1990 -2012. Impact of business cycle's fluctuations has been studied according to the level of the countrie's economic knowledge. In this classification, countries were divided to three categories: high, medium and low knowledge-based economies. The generalized method of moments (GMM) and system of simultaneous equations were used to estimate the models, and differential equations were applied for interpreting the results. The findings are described in three parts: top countries with high KEI scores experience decreasing and damped business cycle fluctuations. Those oscillations are convergent, and knowledge-based supply and demand in these countries are proportional. The countries with medium KEI scores have stable and iterative business cycle fluctuations, their movements are nearly convergent, and supply and demand are almost knowledge-based. The countries with low KEI scores are capable of instable and very high business cycle oscillations, and there is knowledge-based demand in these countries, but there is no appropriate supply with it, which results in divergent movements in business cycles.

The issue of asymmetric effects of monetary shocks on the economy is among the new topics that have been studied by the New Keynesians. How to monetary shocks affect macroeconomic variables such as gross domestic product (GDP), prices, private investment in terms of nominal and real sectors, and economic policy-making is of great importance. In this study, according to the New-Keynesian assumptions, the effects of asymmetry in monetary shocks are examined using dynamic stochastic general equilibrium model in Iran's economy during 1979-2012. The results indicate that positive and negative monetary shocks are endogenous and depend on inflationary regimes in the Iranian economy, so that the effects of positive and negative shocks on GDP and private investment in the low inflation regime are more than those of high inflation regime. In addition, the effects of positive and negative shocks on the general price's level in the high inflation regime are higher than those of low inflation regime.

National accounts data are of the most important statistical tools in planning and making economic policy. Therefore, forecasting the main economic variables in the economy is of great importance. Economic growth is one of the key macroeconomic variables, which gets top priority in forecasting. The purpose of this study is to identify the appropriate methodology for forecasting economic growth in Iran. This study introduces fuzzy regression model and its’ ability to forecast economic growth of Iran in comparison with Error Correction Model (ECM). To do this, the Iran’s GDP is modeled through ECM and Fuzzy regression models using annual data form 1959 to 2001. Then, Iran’s GDP growth is predicted for 2002-2012. Finally, the performances of these models are compared using common criteria for evaluating forecast accuracy including mean absolute error (MAE), root mean square Error (RMSE), mean absolute percentage error (MAPE) and Theil’s inequality coefficient (TIC). The results indicate that the performance of fuzzy regression is far better than that of ECM in predicting GDP growth in Iran. Moreover, forecast accuracy of fuzzy regression model is of statistically significant difference in comparison with ECM model.

Energy carriers including elasticity play central roles in development of societies. In this paper, we estimate residential electricity demand among the selected counties of Tehran province, i.e., Tehran, Varamin, Firouzkooh, Damavand, using dynamic panel data model over the period 2000- 2014. The most effective variables which explain demand for residential electricity are per capita income, natural gas real price, weather coldness and hotness index and electricity real price. The estimation results of the short run model reveal that demand for electricity decreases by 0.42 percent for one percent increase in electricity real price. The price of substitute energy carrier such as natural gas is of low effect on electricity demand. There is a positive and significant relationship between electricity demand and household's income. The last period electricity demand is the key effective factor in explaining the current electricity demand with a coefficient of 0.65. The estimation results of the long run model show that one percent change in electricity price changes the demand for electricity by -1.2 percent. In addition, demand for electricity increases by 0.1 percent with one percent increase in income.

Scientific study of the major oil producers has always been one of the issues facing economic experts. The emergence of Organization of the petroleum Exporting Countries (OPEC) as a major player in the world oil market resulted in increasing researches on the behavior of OPEC and its members. Iran as the second largest oil producer in OPEC has achieved the special place in shaping the policies of this organization. This paper investigates the behavior of Iran in OPEC using monthly data from 1973:1 to 2015:12. Therefore, first model is estimated using Griffin linear model, and then it is estimated using a Markov Regime-switching method with two states: probability of fixed transition and probability of time-varying transition. The results of fixed transition probability method showed that the behavior of Iran is nonlinear; and collusion regime is the most common behavior for Iran, so that the chance of staying in competitive regime is 0.005 percent. In other words, over the period under study, Iranian behavior within organization has been frequently consistent with other members based on agreement and collusion and cartel-like rules. However, the findings of the time-varying transition probability method have not clearly determined factors affecting non-linear effects on the production behavior of Iran.

Energy is one of the main production inputs, which indicates potential political and economic power in different countries. Due to higher energy prices, energy productivity is of special importance, and recent applied researches imply the effectiveness of energy productivity on economic growth. In addition, the process of regional economic growth is influenced by geographic conditions, regional and neighborhood specifications and functioning as well as usual regional economic variables including labor, capital, technology and energy. This paper estimates the effect of provincial energy productivity on provincial economic growth, using spatial econometric model and Maximum Likelihood method with applying provincial data from 2001 to 2011. In addition, it investigates β and σ convergence of energy productivity among Iran’s provinces. In spatial econometric method, we can consider the spillover effects and spatial relations among adjacent provinces with defining a distance-weight matrix between regions. Our findings indicate no σ convergence, but there is a conditional β convergence, which is a signal of existence of either spillover or neighborhood effect in provincial energy productivity growth. Meanwhile, the higher economic openness and lower government intervention in the economy improve energy productivity growth, but increasing energy price has no significant effect on the provincial energy productivity.