JOURNAL OF SUSTAINABLE GROWTH AND DEVELOPMENT (THE ECONOMIC RESEARCH)
Year:2019 | Volume:19 | Issue:4|Papers Count:8

With regard to the role of fiscal policy in reducing the financial crises, determining the magnitude of the fiscal policy multiplier after the 2007-2008 global crisis became one of the most challenging issues in the field of fiscal policy. In general, the magnitude of the fiscal policy multiplier is estimated larger than one according to the Keynesian viewpoint and smaller than one based on neoclassical viewpoint. The difference in the magnitude of the multiplier comes from the fact that economists believe that the fiscal policy multiplier is influenced by the degree of economic openness, the exchange rate regime, the way monetary policy is applied and the business cycle. Differences about the magnitude of the fiscal policy multiplier among schools of economic thought are evident in both theoretical and empirical dimensions. In this regard, this paper tries to estimate fiscal policy multiplier using structural vector autoregressive model (Blanchard and Peroti, 2002 method and Markov switching approach (Hall, 2009) using the seasonal data for Iran during the period (1990: 1-2017: 3). The results of the structural vector autoregressive model showed that the instantaneous multiplier, 10-quarter cumulative multiplier, and the 20-quarter cumulative multiplier of the government expenditure were equal to 0. 281, 0. 304, and 0. 445, respectively. In addition, the corresponding multipliers for taxes were-0. 079,-0. 107 and-0. 171, respectively. Since the fiscal policy multiplier varies based on the economic conditions, the results of the nonlinear Markov switching model showed that the government expenditure multiplier during the recession is 0. 828 and it is larger than the same coefficient during the boom period (0. 108), on one hand. On the other hand, the tax multiplier during the boom period (-0. 194) is larger than its value during the period of recession (-0. 092 ).

Many studies have confirmed the acceleration of economic growth through financial development, but just a few studies have discussed the disproportionate effect of financial development on the growth of the firms with different sizes. So the distributional effects of financial development among firms are still unclear. Accordingly, using a dynamic panel model, we have examined the role of small firms in different industries on the effect of financial development on industrial development of Iranian economy. This study has been carried out on 22 industries according to ISIC4 two-digit codes for the period 1383-1393 (Iranian Calendar) using the Generalized Moment Method (GMM). The results of the model confirm that the development of financial intermediaries exerts a positive effect on the industries with a bigger technical share of small firms. In other words, financial development through banking development has a more positive effect on small firms than large firms. This result is not valid for the development of the stock market.

The relationship between government spending and revenue during the budgetary disequilibrium can be considered as an important issue in public sector economics. This issue is of high importance in Iran, which oil revenue is the main source of government revenue. The aim of this study is to examine the response of government revenue and spending to budgetary disequilibrium in Iran using a three-variate model, accounting for oil revenue and testing the asymmetry of adjustment process during 1990-2016. The results support the tax-spending hypothesis for Iran. However, according to the long run relationship, the results show that oil revenue stimulates the government to spend more and to collect less tax, which confirms tax displacement hypothesis. Moreover, when the government faces a budget deficit, only government spending responds to budgetary disequilibrium. According to the findings, Iran should reduce its oil-dependence and improve its tax collection system in order to reduce budget deficit.

Panel data constitutes a cornerstone for dynamic analysis, especially in poverty mobility studies. In developing countries such as Iran, household income and expenditure data are collected on a cross-sectional basis because of various reasons. As a result, households’ panel data are not available. Due to the concerns of policymakers in understanding the status of mobility of the poor, researchers have developed several approaches to study poverty mobility among countries using cross-sectional data. In 2013, the World Bank's Poverty Studies Group introduced a synthetic panel data method for poverty dynamics analysis, which provides relatively accurate estimates of poverty mobility. First, the present study calculates the absolute poverty line of urban areas of Iran in 2012, 2015 and 2016. Then, it uses the method of synthetic panel data in order to study the status of poverty mobility. The results show that there is a kind of status dependency in the urban poverty, so that the poor (non-poor) households in 2012/ 2015 were also poor (non-poor) in 2016 with a probability of more than 80 percent. Only with a probability of less than 20 percent, the poor (non-poor) households in 2012/2015 were non-poor (poor) in 2016.

Data Envelopment Analysis (DEA) is a powerful technique for measuring efficiency. The traditional DEA approach is applicable when inputs and outputs are certain. Since, some input and output data, such as CO2 emission are often imprecise or vague in real world, this approach cannot be used efficiently. Therefore, this study uses the fuzzy data envelopment analysis to measure carbon-environmental efficiency. The results show that the average interval carbon-environmental efficiency is 75. 90 percent in the sample and period under study. In addition, the minimum and maximum carbon-environmental efficiency scores in Iran are 61 and 74 percent, respectively, which indicates low environmental efficiency in Iran compared to other countries. Accordingly, using inputs optimally and lowering dependency on resources are recommended for increasing the carbon-environmental efficiency.

This paper aims to examine the effects of access to information and communication technology (ICT) on income distribution in Iranian provinces, with an emphasis on the per capita income and education. Using economic theories, the relationship between access to ICT and income distribution was evaluated within a dynamic panel model by use of Generalized method of moments (GMM) during 2010-2015. The results indicate that access to ICT significantly reduces income inequality. In addition, education as a complement factor for ICT, strengthens the positive impact of access to ICT on reducing income inequality. This impact is greater among provinces having lower GDP per capita than nation-wide GDP per capita. Furthermore, inflation rate leads to an increase in income inequality, and government spending is not an influential factor in the proper distribution of income in the provinces of Iran.

This study is an attempt to identify the persistent obstacles in improving labor productivity path and to give insight to policymakers into the food and beverage industry and related industries about the geographic concentration of industry, educational distribution of employees, and their relationships with labor productivity. For this purpose, a panel data model is applied for explaining labor productivity in the food and beverage industry over the period 2000-2014. In addition, motivational indices (wage per worker), per capita capital stock and physical capital management index (the number of private and public firms) are used as explanatory variables. The results suggest that improvement in labor productivity in food and beverage industry sub-sectors requires reducing educational dispersion of the labor force by employing high-educated workers, increasing geographical concentration, improving incentive system by determining appropriate wage, and enhancing management through reducing state ownership of industrial firms.