فصلنامه مدلسازی اقتصادی
سال چهاردهم شماره 2 (پیاپی 50، تابستان 1399)

Previous studies in the corruption literature have introduced numerous variables as the determinants of corruption. This articles aims to evaluate the robustness of potential determinants of corruption by addressing the model uncertainty and endogeneitry. The results derived from an instrumental variable Bayesian model averaging analysis indicate that based on the data of 123 countries, rule of law, with a posterior inclusion probability (PIP) of 1 and posterior mean of 0.662 has the most important role in keeping corruption under control among 36 explanatory variables. Government effectiveness, with a PIP of 0.964 and posterior mean of 0.358 is another significant variable in curbing corruption. Also, with a PIP of 0.965 and posterior mean of -0.194 the Asia dummy variable tells that corruption is a serious problem in the Asia region. Further, confining the analysis to 95 developing countries reveals that rule of law with a PIP of 0.999 and posterior mean of 0.684 is the most critical variable in the fight against corruption.

The main purpose of this study is to investigate the relationship between the export diversification in the top industrial sub-sectors and its impact on the volatility of foreign exchange earnings in Iran's industrial sector. Accordingly, quarterly data from 2002-2 to 2018-3 were collected in the top three industrial sub-sectors of the country and the autoregression method with distributed intervals was used for estimation. The findings indicate the positive effects of inflation and global income on short-term and long-term foreign exchange earnings instability and the effect of concentration index of base metals sub-sector on industrial foreign exchange earnings instability was positive and in non-metallic mineral products and workshop textiles has been negative and significant. Therefore, moving towards diversification in the metals sub-sector and focusing on the non-metallic mineral and textile sub-sectors will reduce the volatility of industrial foreign exchange earnings. Based on the results, it is suggested that the government reduce the instability of industrial foreign exchange earnings by granting facilities, setting export and import customs tariffs in industrial sub-sectors, while directing production in terms of diversification or decentralization.

The purpose of this study is to examine the effects of substituting different tax items for each other (or changes in tax mix) on the size of the shadow economy in Iran. To this end, a proposed model is estimated using the autoregressive distributed lag (ARDL) approach for the period 1355-1394. The results show that the substitution of company tax for income tax or commodities tax as well as the substitution of wealth tax for income tax, commodities tax, company tax or import tax reduce the size of the shadow economy. In addition, the substitution of import tax for income tax, corporate tax, or commodities tax leads to a decrease in the size of the shadow economy, while the substitution of commodities tax for income tax has no significant effect on the activities of this sector. The results of this study provide a good basis for adjusting the tax mix to reduce or limit the shadow economy sector in Iran.

This study is aimed of investigating the impact of the offered facilities of the banking system in fields of industry, services, agriculture, construction and housing on the added values of the aforementioned fields which was the steady state approach in the economic growth models, to reach this, systematic generalized method of moments (SYS-GMM) and time period information (data) from 1370 to 1396 have been used in Iran’s economic. The results of investigation from estimated equations indicate that non-duty and duty offered facilities has had a positive and significant effect on the added values in economic areas.Among these, the share of offered facilities to services, industry and mines, construction, housing and agriculture have had the greatest effect on the added values respectively. Prioritization of sectors based on economic return to scale and the amount of optimal allocation of bank credit can have favorable effects on the value added of various economic sectors in Iran.

The aim of this paper is explaining the financial factors affecting turnaround from the insolvency. For explaining financial affecting turnaround from insolvency 54 variables were selected from relevant studies. The information of 200 cases of distressed companies which were under recovery from distress was extracted between 2001 and 2017. Appropriate statistical methods for the process of refining variables have been performed through paired mean comparison tests as well as exploratory factor analysis using main components. Then, by filtering the variables using audit analysis and in the form of linear combinations, audit functions were formed. The results showed that the financial ratios of current liabilities to total assets, net profits to sales and sales to current assets have the most power to explain the companies’ turnaround.

The purpose of this research is to modeling and predicts bankruptcy using real and accrual earnings management variables. Based on this, using logistic regression, the accuracy of bankruptcy models before and after adding Earning management variables were estimated and compared. So, a sample consisting of 1287 years - company during the period 2006 to 2018 has been selected from the companies of Tehran Stock Exchange. The results showed that the predictability power of Altman, Springgate and Zimsky bankruptcy models has increased significantly after adding accrual earnings management variables compared to the initial models. The results also show that the parameters of real earning management weaken the predictability of Altman, Springgate and Zimsky models. Based on the results, accountants, managers, and economic planners are advised to pay special attention to the phenomenon of corporate Earning management in order to make their decisions better.

The purpose of this study is to investigate the impact of human capital and business environment on the economic growth of thirty provinces of Iran by Generalized Method of Moments using panel data during 2010-2016. The results showed that human capital and business environment had a positive and significant effect on the economic growth of the provinces of the country, but human capital had more effect on the economic growth of the provinces than other variables. Based on the results, it is suggested that economic planners and policymakers strengthen the quality level of human capital and business competition environment.