نشریه اقتصاد و تجارت نوین
سال هجدهم شماره 3 (پیاپی 60، پاییز 1402)

Evaluating the energy demand of the industrial sector is important and necessary for policy making in order to increase production and improve efficiency in this sector. The purpose of this study is to estimate the demand for major energy consumption in the industrial sector, including natural gas energy, electric energy, and petroleum products energy (gas oil and mazut) in the form of a system of equations during the period 1988-2019. The results of this research, based on seemingly unrelated regression equations, show that the demand for natural gas and oil products is inelastic, and natural gas energy input is substituted by electricity and oil product energy is substituted by natural gas. Also, the increase in the added value of the industrial sector has a positive and significant effect on the demand for natural gas energy and petroleum products. In addition, the increase in the ratio of capital to labor in the industrial sector is accompanied by a decrease in the demand for natural gas energy and petroleum products and an increase in the demand for electric energy. In addition, the increase in the ratio of capital to labor in the industrial sector has led to a decrease in the demand for natural gas energy and petroleum products and an increase in the demand for electric energy.

The main purpose of this study is to investigate the impact of the human development index on the expansion of B2B electronic commerce (business-to-business electronic commerce) in Iran and Iran's trading partner countries during the period of 2011-2016 using the Astana panel approach.The research variables include the level of expansion of e-commerce, imposed pressure due to dependence on exports, normative pressure due to consistent global trade relations, imitative pressure due to foreign competition, global common knowledge, Internet access and human development index.According to the results, in countries with a low human development index, this index has a negative effect on the development of B2B e-commerce, which can be affected by the lack of infrastructure, and this relationship is inverse for countries with a high level of human development. Based on the threshold defined in this article, the average in countries with a lower human development index, the human development index in these countries causes a decrease in the level of B2B e-commerce, but in countries where the HDI is higher than the threshold, it did not have a significant effect. The human development index regime has had a negative effect on B2B e-commerce up to a threshold level with a coefficient of 3.667 and has reduced the human development index of e-commerce. India,Pakistan and Tajikistan are less than the threshold value of 0.653, and the rest of the countries studied in this research are more than the threshold value. The threshold effect test was performed, both based on the 95% confidence interval, the numerical value of the threshold is placed between the highest and the lowest value, and based on the critical value, andthe significance levelof theH0 hypothesis that there is no threshold effect is rejected, and theH1 hypothesis ofthe existence of a minimum A threshold is not crossed.

Answering the fundamental question of whether technological progress can lead to unemployment has always been one of the most challenging issues in economics. In this regard, the present study investigates the effect of technology-based innovations (including process innovation and product innovation) on unemployment using panel data techniques (random effects model) and data from a sample of developing countries during the period 2008-2018. To this end, the number of patents registered is considered as an index of process innovation and the ratio of research and development (R&D) expenditure to GDP is considered as an index of product innovation. Moreover, GDP per capita, inflation and trade openness are included in the model as control variables. The results obtained from the estimation of the panel model show that both the growth of process innovation and the growth of product innovation reduce unemployment. In addition, the empirical results indicate that GDP per capita and trade openness have a negative and significant effect on unemployment, but the effect of inflation on unemployment is not statistically significant. Overall, the findings of this study have important policy implications for dealing with the problem of unemployment in developing countries through increased investment in R&D and stronger patent protection.

In the past few years, Bayesian econometrics has provided suitable solutions to overcome uncertainties regarding the selection of parameters and models. This research seeks to identify and prioritize the variables affecting Iran's foreign trade with an emphasis on sanctions and geopolitical risk indicators. For this purpose, Bayesian, dynamic, and selective averaging modeling has been applied using 45 variables affecting foreign trade between 1370 and 1400 (solar year). According to the results, among BMA, TVP-DMA, and TVP-DMS, BVAR, and OLS models; the BMA model was determined as the most efficient model.Based on the BMA model, 11 non-fragile variables affecting foreign trade were identified, which are: sanctions, structural institutional index, real effective exchange rate, export complexity, interest rate, business climate, economic openness, economic growth rate, geopolitical risk, inflation and trade integration index (Grobel and Lloyd index). A sanction, geopolitical risk, and interest rate had a negative effect on foreign trade, and other variables had positive effects. The volume of Iran's foreign trade is facing a high fluctuation because of the high probability of the occurrence of non-fragile variables. To improve the performance of Iran's foreign trade indicators, considering the impact of geopolitical risks and sanctions on the country's foreign trade, improving economic flexibility and resilience policies should be ordered by policymakers.

The main purpose of this article was to measure the effectiveness of industrial trade with an emphasis on the technology gap and the intensity of learning in Iran and high-middle-income countries. To meet these ends, the industrial trade using Grubel-Lioyed criteria for 97 countries over 2002-2021 at four-digit HS codes was calculated. Moreover, this study sought to investigate the specific effects of industry and country on industrial trade in the framework of Tobit Heckman's two-stage model, the databases, and statistical information extracted from the World Bank and the International Trade and Development Organization. The results of the study, while confirming the predominance of inter-industry trade compared to intra-industry trade of Iran with partners, indicate the effect of most variables with the expected sign on industrial trade. Among the indicators of technological achievements, only the human skill gap index has a negative effect on industrial trade while the rest of the technical indicators such as technology diffusion and creation showed a positive and significant effect. The results of the learning intensity also provide evidence of Iran's growing experience in producing domestic products similar to foreign ones at a lower cost and acquiring the knowledge of installing and assembling imported capital goods. In addition, the lack’s effects of foreign investment on intra-industry trade between Iran and its partners can be attributed to barriers to entry, such as the tightening of economic sanctions against Iran

At the current time, the aggravation of the problem of stagflation in the country has caused more emphasis on all policies of the supply-side, and on top of that, the financing of entrepreneurs with an emphasis on reducing inflation. The initial coin offering method is a new method for financing businesses based on blockchain technology, which realizes the possibility of attracting high capital in a short time compared to other methods. In the meantime, small and medium-sized enterprises that, despite the need for small levels of resources, have an undeniable role in production of Countries, can be good candidates for applying this method. The explanation of this method and the identification of factors affecting its success to solve the existing information gaps can provide the process of perfect use and benefiting from its potentials. Therefore, in this article, by collecting 307 ICO in 2016 to the end of 2018, the factors influencing their success-include the characteristics of the team, project, campaign and social networks- in a cumulative process by Random Forest algorithm has been investigated. In the recent article, the total raised capital and Percentage of hard cap raised has been considered as a criterion of success in two series of separate models. By dividing the level of priority of the features into three levels, the findings show that three features of the total number of project tokens, the number of white paper pages, the clarity of the team's share of the token have the priority of level one and have the highest role in the success of an ICOs campaign.