نشریه پژوهش های اقتصاد صنعتی
پیاپی 20 (تابستان 1401)

Abuse of the dominant position is one of the anti-competitive practices in the automotive sector. Consequently, this abuse can lead to monopolising the automobile market, the lack of competition, unfair contract terms, and the expansion of a few companies' market power. The main objective of this study is to answer the following questions: What are the causes and examples of abuse of dominant position in the Iranian and European automotive industries? What solutions are there to limit and prevent the abuse of dominance in this market? The questions are addressed by using a descriptive-analytical approach. Study results indicate that Iranian automotive industry failure factors include failed and non-targeted state aid, impediments to private sector practice, and tariff and non-tariff barriers to foreign automakers' practices on the Iranian market. A review of successful competition law enforcement strategies enacted by the EU will be conducted with the objective of improving the Iranian automotive market.

This study attempts to quantify the impact of various factors on the value-added distribution quantiles of 24 ISIC codes for industrial factories in Iran. It examines the impact of the variables human capital index, rental price index, R&D index, financing index, number of employees of industrial factories, number of industrial factories, and economic openness index on the value-added of Iran’s manufacturing industries from 2002 to 2019 using the panel quantile model. According to the findings of the study, the funding index has a greater impact on small- and medium-sized enterprises, but economic openness has a lesser impact on these companies. In addition, the rent index, human capital index, and R&D index have had the most significant impact on the value-added of larger enterprises. Based on these findings, the facilitation of the financing process, particularly for small and medium-sized businesses, has resulted in an increase in the value-added of these companies, and in light of the lesser effectiveness of these enterprises, as measured by the economic openness index, against sanctions and currency shocks, it increases the economy’s resilience to a certain amount.

In recent decades, the inflation rate in Iran, in addition to having an upward trend, has also experienced many fluctuations over time. On the other hand, the industry index, as one of the important indices of the stock market, shows the performance of the stock market and the state of the industry and production of each country, which is also affected by macroeconomic variables such as inflation. Therefore, investigating the effect of inflation on the industrial index of the Iranian stock market provides important results. Therefore, this paper has experimentally investigated the effect of time varying inflation on the Iranian stock market industry index using conditional regression (WLS-Rolling Window) with monthly data during the period from April 2018 to March 2018. Conditional regression results show that the effect of inflation on the industry index is not constant over time, in the sense that inflation has had a positive effect on the industry index at some times and a negative effect on the industry index at some times. In addition, this effect has had a drastic change since August 2019, when the trend of the industry index has changed.

Recent research has examined the impact of economic policy uncertainty (EPU) on various aspects of macroeconomics, but limited studies have been conducted in the field of energy, especially renewable energy. In this study, the effect of EPU on renewable energy consumption (REC) in the Middle East and North Africa (MENA) during the period 2002-2020 has been done using the integrated Pooled Mean Group (PMG) approach. The variable used in EPU is obtained with a composite index that uncertainty in monetary, monetary and fiscal policies is calculated using ARCH and GARCH econometric models. The results of the study using the PMG econometric approach show that EPU has a negative and significant effect on REC, so that in the short run it reduces /159% and in the long run it reduces REC by 0.186% . According to the research results, the control variables of foreign direct investment, credits granted to the private sector and the market value of the capital market in both time, short and long term have increased the REC. The results of Granger causality analysis also show that there is a one-way causality relationship from EPU to REC.

High-tech industries are a factor of competitive advantage between countries.Technology is knowledge, and the economic complexity of a society is dependent on the high amount of knowledge of the people of that society, which can be seen in the products produced by them.People with knowledge and skills or in other words human capital interact with each other and combine their knowledge to produce a product (productive output).A reliable indicator of human capital is intelligence, which is also related to innovation The purpose of this study is to investigate the infrastructure of national IQ, innovation, educational attainment, nutrition which is supposed to explain part of the efficiency of nations in the production of high-tech. For this purpose, quantitative indicators of national IQ and nutrition infrastructures are considered as primary inputs in the first stage, and innovation and educational attainment are considered as outputs for primary inputs. In the second stage, innovation and educational attainment as input and production of high technology as the final output of a network model, of the type of data envelopment analysis series for 23 selected countries are considered. The data were collected from official international sources. The results show the differences between the efficiency of selected countries in producing high-tech products and also estimate the weight of each infrastructure. The findings show that the highest weight / importance is related to national IQ and nutrition infrastructure, which can be achieved by upgrading these two infrastructures in the studied countries to maximize the production of high technology.

Gas to liquid (GTL), is an industry that uses special chemical methods that converts natural gas or other light gaseous hydrocarbons into heavier chain hydrocarbons such as gasoline, gas oil, and other heavier products usually obtained in the crude oil refining process. In this study, the global supply function of GTL industry was investigated. The necessary information was obtained from a valid source from 1987 to 2019 and the autoregressive distributed lag model was used to investigate the impact. The results of estimating the model with dynamic, long-term and error correction models were estimate, and the results show that the interval of logarithm variable of GTL supply has a positive and significant effect on the logarithm of GTL supply in the current period and its coefficient is equal to 0.01 units. The results also show that the first interval of the logarithm of the oil and gas gross production variable with 0.25 units influences the logarithm of GTL supply in the current period and the logarithm of natural gas price with a coefficient of 0.09 units has a positive and significant effect on the logarithm of GTL supply. According to the obtained results, it is suggested to increase the surplus of gas production by improving and reducing wastage in consumption on the one hand and investing in increasing production on the other hand. Also, competitive pricing to encourage investors in the development of this industry should not be overlooked.