فصلنامه پژوهشهای اقتصادی (رشد و توسعه پایدار)
سال بیست و دوم شماره 1 (بهار 1401)

Along with the increased trade integration of countries and the expansion of international production fragmentation, Global Value Chains (GVCs) amount to a huge part of trade today, and participation in a network of trade partners at downstream and upstream of the value chains brings about considerable potentials such as the improvement of the flow of knowledge and more advanced production technologies and techniques, particularly for developing countries. It would not be unexpected for GVCs and participating in them from an environmental aspect to have potential benefits for countries as well.
In this regard, the present study discusses the role that GVCs play in countries' environmental performance. For this purpose, a sample of 65 developing and 36 developed countries was investigated using spatial panel data econometrics, conditional convergence, spatial auto-correlation, and GVCs participation spillover and direct impacts for countries in the form of south-south, north-south, and north-north bilateral added-value trade. The results indicated that there was spatial auto-correlation and conditional convergence based on GVCs for all countries although they are more intense in the case of north-north trade in developed countries. Besides, participation in GVCs has spillover impacts on the trading partner countries if developed countries are included in the bilateral value-added trade but this impact is not statistically acceptable in south-south trade of developing countries according to estimations. Thus, establishing trading relations with developed countries through GVCs is a potentially beneficial policy to improve developing countries’ environmental performance.

In recent years, the most important philosophy agreed upon by organizations has been to create both economic, social, and environmental value in the form of the concept of sustainable management. Circular economy is a new concept to account for the sustainable management. The main purpose of this study is to analyze the performance of manufacturing industries from the perspective of the circular economy components. This research was conducted in the second half of 2020. The statistical population of this study includes the food industries in Bushehr province, which due to the limited size of the population, all of them were selected as statistical sample. The data collection tool of this research is a researcher-made questionnaire whose validity was checked by face content analysis method and its reliability was checked by Cronbach's alpha method. In this research, first, by studying the theoretical foundations and empirical background, effective components in circular economics were identified. Then, using the k-means algorithm, clustering of selected food industries was performed. The results showed that the food industries are in two industrial clusters: circular and linear. Next, the species detection function was obtained. It is suggested that linear industrial cluster managers pay more attention to energy efficiency, water consumption management, and sales of recyclable materials in order to transition to a circular economy. This research is of innovative nature in terms of developing the theoretical concept of circular economy and applying it to improve the performance of the food industry.

Iran with arid and semi-arid climate needs to save water and energy resources. In this study, the two regions of Isfahan and Yazd as two critical points in terms of water and energy have been studied. In this research, the two-region Input-Output model is used to measure and analyze the water and energy relations between the economic sectors of Isfahan and Yazd provinces and the link model is used to investigate the hybrid flow of two sources and the extent of link effects in each region in 2016. The results of combined water and energy flow indicate that the two sectors "water, electricity and gas" and "agriculture" are the most consuming sectors or the most effective sectors in terms of consumption in two regions, so that the most important management node in the relationship between water and energy are considered. Also, the calculations made in the total flow section of the two sources of water and energy indicate that the two sectors "water, electricity and gas" and "coke production, products from oil refining and nuclear fuels, and manufacturing of chemical materials and products” account for the highest output (export) and input (import) of water and energy from other sectors, respectively.  In addition, "Building" and "water, electricity and gas" are the most important sectors in water and energy imports, respectively. The total flow of water and energy resources between Isfahan and Yazd provinces indicate that each economic sector of Isfahan province is an exporter in the field of water and energy importing from other sectors, and each economic sector of Yazd province is an importer in the field of water and energy.

The role of money in the design and implementation of monetary policies for price stability, especially since 2007-2009 global financial crisis, has been reintroduced as a major policy issue in both developed and developing countries. In this regard, the money demand function is one of the most important components of any monetary system, which plays a decisive role in the mechanism of transfer of monetary policy to the real sector of the economy. Therefore, in order to analyze monetary issues and to provide appropriate solutions for overcoming economic problems, it is necessary for the policymaker to have a correct understanding of the money demand function. This paper answers the question of whether sudden changes in money supply cause instability in money demand function. Hence, the present study, with Markov switching approach and using simple sum and Divisia, estimates the demand for money function in the Iranian economy during 1988q2 -2020q2 and evaluates its stability. The results indicate that demand for money function is stable in regime one but being in regime two and three, namely the average growth of money and the sharp growth of money, has led to instability in the demand for money function, and the diversion of the monetary policy objectives.

The quality of manpower is one of the factors affecting the environmental degradation. According to studies, air pollution is affected by its past values, so a dynamic model should be used to study it. Accordingly, using the GMM method, the present study evaluates the impact of human capital on air pollution in Iran during 1981-2019. Human capital is a latent variable in economics and is often replaced by alternative proxies. In this paper, like most previous studies, the research model was firstly estimated using the average proxy of years of schooling (as an indicator of human capital), which resulted in statistical insignificance and theoretical inconsistency in the estimated coefficients. Based on theoretical foundations, it is argued that the human capital index in addition to the education component is influenced by other aspects such as skills and health. Therefore, using fuzzy logic, an indicator for human capital in the Iranian economy has been constructed, so that it includes three main aspects (education, skills and health) of human capital. The results of estimation of the air pollution model using the human capital index showed that improving the level of human capital had a negative effect on air pollution. Therefore, by increasing human capital and improving the quality of manpower, we can expect to reduce air pollution and environmental degradation. In addition, urbanization, industrialization, trade freedom, economic growth and pollution in the previous period had positive and significant effects on air pollution.

Human capital causes increase in the production factors productivity and in turn affects economic growth positively. In this study, we intend to study the effect of human capital on economic value added in Iran by extracting the type and manner of the influencing of education costs on economic growth and to provide appropriate solutions to promote this role in the economy. The method of this research is descriptive-analytical. To evaluate the short-term equilibrium relationship between the variables, we use the Auto Regressive Distributed Lags (ARDL) method. Based on the results, in the short-term, human capital indicators have positive impacts on growth of economic value added. The long-term results indicate that the gross secondary and university enrollment ratio, the import‎ of goods, services and income growth, the percentage of public education costs to GDP, the percentage of private health spending to GDP, the labor force participation (aged 15 and more), the foreign direct investment growth, government efficiency, quality of rules and annual growth of gross capital formation have positive and significant effects on economic value added growth. Error correction term of ARDL model is ‎- 0.78.‎ that shows in each period 78% of short term shocks will be adjusted to the long-term value. The results of this study can be used by policymakers because identifying the factors affecting economic growth, can make economic planners inform in two important aspects, firstly, by considering new variables in planning and thus the optimal allocation of resources, and secondly,  by reducing errors due to misanalysis of the factors affecting economic growth.

Today, information and communication technology (ICT) has affected human societies in all dimensions. Despite its significant effects on the economic, political and social development of societies, this technology also has adverse effects. Among these effects, we can mention the background of information and communication technology on social actions and conflicts. Accordingly, in this study, using Autoregressive Distributed Lag method the effect of information and communication technology and income distribution (Gini coefficient) on social unrest was investigated in Iran during the period 1984-2018. The Internal Conflict Index presented by the ICRG Political Risk Index was used as a proxy for social unrest. The results showed that information and communication technology and unfair income distribution significantly increases social unrest in Iran. As well as Inflation also significantly increases social unrest in Iran. However, GDP per capita has no significant effect on Iran's social unrest. Therefore, the policy of developing information and communication technology based on the internal Internet network, improving income distribution and curbing inflation in controlling Iran's social unrest seems necessary.