نشریه مدلسازی اقتصاد سنجی
سال ششم شماره 1 (پیاپی 20، زمستان 1399)

In this study, the home market effect on competitive and multilateral monopoly industries was studied concerning double-digit ISIC classification published by Statistical Center of Iran. For this purpose, dynamic panel data were implemented using Generalized Method of Moments (GMM) regarding the period 2001–2015. The results indicate that the demand coefficient in multilateral monopoly market industries is higher than in competitive market industries. The home market effect only exists in “the production of radio and television, and communication devices and machines” industries in multilateral monopoly market industries; thus, investing in this industry can lead to exports. In other industries, there have not been the home market effect, which means relatively higher demand for their products will generally lead to the net imports of the products.That is, the imports’ effect will dominate exports and will lead to imports.

The impact of corruption on economic activity has been widely discussed in the literature. On the one hand, some believe that bribery motivates bureaucracies to give private-sector economic agents the opportunity to overcome cumbersome regulations. In this case, corruption can improve the efficiency of public resource allocation. The second argument is that more bribery distorts the decisions of private sector and reduces allocation efficiency. In recent decades, extensive studies have been conducted in the field of corruption and its effects on various aspects of economic, social and governance, as well as defining indicators of corruption and providing models for its reflection. Researchers have often examined corruption based on perceptual criteria and nationall level. The novelty of this research is to take advantage of the objective documentation and local dimensions in defining the corruption index. This study, using a local and objective variable of corruption, by comparing sample data consisting of selected companies of Tehran Stock Exchange in areas with higher corruption and areas with lower corruption, examines the relationship between corruption, corporate governance and holding the company's cash at the level of selected companies on the Tehran Stock Exchange, using the panel data method. The results show the negative impact of corruption on companies' cash holdings, while board independence and ownership concentration do not have a significant relationship with cash holdings.

This study aimed to demonstrate the inequality of income and wealth in Iran. Therefore, the effects of income inequality and wealth distribution were modeled from 1390 to 1397 on Piketti's dynamic model and based on the analysis of household budget data for the first time in Iran. The results showed that Piketti's hypotheses are valid for Iran and fifty percent of total household wealth belongs to the tenth decile. Furthermore, high Income-share lead to more saving rate and widen the wealth gap between the top and low deciles. It is worth mentioning that this study results owning to the limitation of data gathered, mainly include real estate capital and omit capital like bonds, gold, foreign currency, stocks, and deposits. Consequently, the obtained results are conservative and including the above-mentioned omitted capital into the model would deteriorate the status of inequality. Undoubtedly, establishing a new capital gains tax system would improve equality.

Basically, quantitative specification of sanction effects on economic sectors has undeniable importance to increase the buffering of nations’ economy against their negative effectsThis study examines the impacts of economic sanctions shocks through four indicators: (a) crude oil export revenue shock, (b) non-oil export shock, (c) raw material import shock, capital and intermediate goods, and exchange rate shocks on the construction sector in Iran. For this purpose, the research data were collected from the Central Bank of the Islamic Republic of Iran during the period 1996-1996. Also, structural vector autoregressive model (SVAR) and impulse resonse function (IRF) were used to analyze the data. Results showed that economic sanctions diminished the value added of the construction sector. However, the impact of the economic sanctions indicators examined on this section varies. Among the four indicators of economic sanctions under consideration, respectively: (a) exchange rate shocks; (b) raw material import shocks; intermediate goods and capital; (c) non-oil export shocks; and (d) oil export earnings shocks have the greatest negative impact on the value added of the construction sector.

In natural monopoly conditions, such as the electricity distribution industry, there are various ways to price regulation. In recent years, performance-based regulation or incentive regulation has been more widely considered so these regulation schemes such that price cap regulation and revenue cap reguation becomes the alternative of cost based regulations. The aims of this study is Pricing of electricity distribution services under cost of service, price-cap and revenue-cap regulation schemes. For this aim data of Iranian electricity companies in period of 2006 till 2016, Cross-section specific coefficients in pooled data and a DEA model with both desirable and undesirable outputs and controllable uncontrollable input have been used. The results of pricing in cost of service regulation, electricity distribution service price is more than other regulation schemes in some companies and price cap is more for other.

In this article we constructed a Macro Econometric Model based on Mixed frequency Data to assess the impacts of sanctions that are imposed on the Iranian economy. In doing so, a monthly index is developed to reveal the toughness of imposed sanctions throughout the time. This sanction index is a time series high frequency data which encompasses various types of economic sanctions against Iran and is used as an explanatory variable in foreign sector’s behavioral equations. The constructed model is based on economic theory and stylized facts of the Iranian economy. It contains 27 behavioral equations, 7 connecting equations and 33 identities and definitional equations. The parameters of the model are estimated using time series data for the period of 1959 to 2017. Dynamic simulations are used to confirm the model validation.  To assess the impacts of sanctions, the model is simulated under the scenario of no sanctions and the results are compared with the actual case. According to the findings of this study, the complete lifting of sanctions will have effects such as increasing aggregate demand, increasing investment, increasing production, reducing imports of goods and increasing exports of goods.