فصلنامه پژوهشهای اقتصادی (رشد و توسعه پایدار)
سال بیست و دوم شماره 2 (تابستان 1401)

Green growth emphasizes the production and supply of eco-friendly products and is considered a suitable strategy for economic growth along with the preservation of natural resources and reducing pollution emission in different countries. Given that Iran as a developing country does not perform well in terms of the green growth index, it is necessary to evaluate energy consumption, pollution of various economic activities, and identifying economic opportunities for green growth in terms of production and employment indicators. This study, using the multi-factor energy input-output method and input-output table data related to 2016, investigates the impact of final demand on primary energy consumption, CO2 emission, economic growth, and energy jobs which in turn identifies green growth potentials in Iran's economic sectors with considering both growth and employment indicators. The results show that the sectors related to the production of agricultural and livestock products, services and food products have the lowest CO2 emissions for each unit of production growth and the growth of energy jobs. On the other hand, due to the low growth potential of transportation services, base metals, rubber and plastic products, encouraging higher final demand for products will not be attractive; so that, structural changes in these sectors are necessary for planning green growth.

The relationship between exchange rate changes and trade balance has always been one of the major issues in theoretical literature and policy circles. A new approach to theoretical literature and empirical work suggest that the interaction of these two variables depends on a number of issues, including how each country's export and import markets interact, and the degree to which exports of goods are dependent on imports. For this purpose, in the paper, the relationship between exchange rate and trade balance in the Iranian economy is examined by considering the crucial role of Intra –industry trade in the form of smooth transition regression model for the period 2001: 4 to 2018: 4. The results showed that the coefficient of effect of the exchange rate on the trade balance in each period is affected by the intra--industry index, so that the lower the index, the less the effect of the exchange rate increase on the trade balance, and as this index improves, the impact is greater. This means that the positive effects of money devaluation on the trade balance can be benefited when the competitiveness of domestic products with similar foreign goods in each sector increases.

In this study, a new composite index, called the SWI (Sustainable Welfare Index) is proposed to assess "sustainable welfare". This index consists of significant social, economic, and environmental variables in flow and monetary forms, and can be directly compared to the GDP. Despite the paucity of statistical data, an attempt has been made to make a relative assessment of sustainable welfare in the Iranian economy during the years 2004 to 2018. According to the comparison of calculated SWI with GDP, it has been shown that the two indicators have similar movements and higher correlations in the period under study. In addition, despite the availability of economic growth during the period, society has been below a sustainable welfare level. In this study, the threshold effect of three SWI sub-indices on the total index was assessed using the smooth transition regression (STR) Model. As a result, the sub-index "Social Expenditure" through changes in "welfare losses due to income inequality" is of threshold effect on SWI.

Iran's membership in Shanghai Cooperation Organization (SCO), in addition to political and security gains, can bring broad economic benefits. In this regard, in this research, the economic impacts of decreasing import tariffs of Iran and the Shanghai Cooperation Organization have been analyzed. In this study, empirical analysis and quantifying the results have been done regarding Global Trade Analysis Project (GTAP) model, as a computable general equilibrium CGE, and global and multi-regional model. Considering the international nature of analysis, a global model and database were required to achieve the purposes of this study, thus, version 10 of GTAP model and its database (published in 2020) was selected for analysis. In this research, the economic impacts (welfare, production, trade) of Iran's presence in the SCO in various economic sectors were analyzed in two scenarios (50% decrease and 100% decrease in bilateral tariffs). The results indicate that sector "Grains and Crops" in terms of high initial tariff rate, sector "Textiles and Clothing" in terms of high initial tariff rate, sector " Light Manufacturing" in terms of high initial tariff rate and sector " Heavy Manufacturing" due to high trade volume is the significant and influential sectors of Iran's membership in Shanghai Cooperation Organization. It is recommended that tariff rate changes of the mentioned sectors be performed with high accuracy. In general, the results indicate that the variables of welfare, production and trade are increasing in Iran.

The purpose of this study is to investigate the impact of adding a non-Ricardian household to a DSGE model in choosing the Ramsey optimal monetary policy and consequently the effects on macroeconomic variables (such as output gap, consumption gap, inflation, and rising nominal exchange rate). Therefore, after estimating a model for the Iranian economy, the Ramsey optimal monetary policy was selected from 6 monetary policy alternatives. Then, in two scenarios, a non-Ricardian household is added to the model. In the first scenario, the non-Ricardian household consists of 20% of households and in the second, it consists of 40% of households. Then, Ramsey optimal monetary policy was selected for these two scenarios. The results show that the when the percentage of non-Ricardian households in the model increases, monetary policy-maker deviates from targeting monetary variables and gives more importance to production targeting. Second, if Ramsey optimal monetary policy is chosen without considering the non-Ricardian household in the model, in facing the shock of falling oil prices, the shock of declining money demand and the shock of rising external inflation, the responses of the production and consumption sectors in scenarios 1 and 2 are significantly different from the baseline model. But the consumption and production sectors have almost the same reactions in three models in response to the shock of the rising nominal exchange rate.

Income inequality and efforts to its reduction it is one of the most important concerns of societies in today's world.  On the one hand, countries are looking for revenue sources and, on the other hand, are trying to reduce income inequalities. In addition, due to the unequal distribution of income and the impact of migration contrary to the policies of societies, migration makes it difficult to achieve the desired economic growth. Therefore, considering the importance of the consequences of migration, the main purpose of this paper is to investigate the nonlinear effects of income inequality on brain drain in developing countries. Based on the findings of the study, the inequality in income distribution has a threshold effect on brain drain in developing countries. As long as inequality is at levels below 0.46, this variable has a negative and significant effect on brain drain, but after exceeding the threshold of 0.46 and being in a high inequality regime, the intensification of inequality increases the brain drain sharply. In other words, society tolerates a degree of inequality, but the intensification of inequality beyond the tolerable level of society causes the elites to migrate to developed countries, which are more equal, in search of a better life and proportionate to their capabilities.

The study of speculators' behavior is very important in explaining the phenomena of the Iranian housing market. Many of the unfavorable phenomena that occur in this market are the results of speculative activity in the housing market. Speculators enter the market at the beginning of the boom period and earn maximum profit of price increases, and as signs of recession appear, they quickly exit the market and invest in parallel markets such as banks, stocks, exchange and gold, which leads to fluctuations in housing prices. In this study, following the Roehner model and using the time varying parameter ordinary least squares method (TVP-OLS), the speculation index in the housing market during the period 1991 to 2020 was estimated, and then the impact of different shocks to stock market, exchange market, gold market, interest rates and housing tax on speculation in the housing market was investigated, and for estimating the effects of these shocks, the Markov-switching vector autoregressive (MSVAR) method was used. The results show that during the period under study, on average, 20% of the increase in housing prices was related to speculation, with the highest growth in 1997 at 320% and the lowest growth in 2005 at -23%. According to the results of the Markov-switching vector autoregressive model (MSVAR), speculation in the housing market had the highest response to the exchange and gold markets, and interest rates and the least response to the stock market and housing tax.

This research examines the macroeconomic variables reaction and banking sector with the financial and monetary shocks using dynamic stochastic general equilibrium model (DSGE). Considering the banking facilities and utilization of seasonal data for the period 1991-2017, the banking sector behavior in the economic dynamics is studied. Therefore, the linear-logarithmic form of the equations is obtained after specifying the model, optimizing, and extracting the first-order conditions. The model is simulated under two different scenarios by considering bank facilities as two types of capital facilities and working capital, and not considering the facilities. The results show that by occurring financial and monetary shocks, the instant reaction of variables is consistent with the theoretical bases of the economy, which indicates the acceptable ability of the model in accurately fitting Iran's economy. Furthermore, comparing the moments of the simulated variables with the real data, the success of the model in simulating the governing facts of the economy is confirmed. Finally, the results show that banking facilities could reduce the range of economic fluctuations and increase the stability of the economy. This issue can be mentioned by the economic policymakers in order to reach economic sustainable development.

Investing in housing is one of the most common methods of investing in Iran. The housing and construction sector has a widespread relationship with other economic sectors. Housing annually attracts a large amount of liquidity in the country, so investing in this sector is more important in the process of growth. In this paper, first the relationship between investing in housing and economic growth is evaluated by the Granger causality test. The results of this test showed that there is a one-way causal relationship from investing in housing to economic growth. Then, using GMM method and time series data from 1981-2019, the impact of investing in housing on Iran's economic growth is studied. The results showed that investing in housing has a positive and significant effect on Iran's economic growth. The lag of variable “economic growth” has a positive effect on economic growth in later years. Also, other results indicate that human capital, capital stock, government expenditure index and industrialization index have positive and significant effects on Iran's economic growth. Based on the results, it can be suggested that the shortcomings and barriers to investment in the housing sector should be removed, and also incentives and facilities for investment in housing can be effective in increasing economic growth.

Universal access to higher education and radical increase in demand for higher education in 2000s necessitated the expansion of higher education institutions. The rise in the number of such institutions was unprecedented. In fact, all districts of Iran had a higher education institution by 2008. Even very small districts received a private or public higher education institution to reduce transportation costs and expand access to higher education. This enhanced access has a more disproportionate effect on women compared to men. In this paper we combine data on higher education institutions between 1999 and 2016 with educational outcomes of individuals aged between 18 to 35 years old in the population census 2016 to estimate the impact of access to higher education on educational attainment and educational gender gap. Using district and age fixed effects, we do not find a significant effect on overall education of individuals. However, women received a significantly larger benefit from the expansion of higher education institutions.