نشریه اقتصاد و تجارت نوین
سال هجدهم شماره 1 (پیاپی 58، بهار 1402)

This study examines the impact of financial development on the relationship between human capital and economic growth in selected developing and developed countries during 1980-2016. The fundamental question is whether financial development can strengthen/weaken the impact of human capital on economic growth? Model estimation is performed in two steps. First, the effect of human capital on economic growth has been estimated using the rolling regression method. In the second step, the human capital coefficients extracted from the rolling regression of the first step, have been regressed on the multidimensional index of financial development in two separate groups of developing and developed countries, using a panel data model. This multidimensional index is calculated as a weighted average of seven financial development indices using the principal component analysis method. The findings show that the increase in human capital mostly increases the economic growth, and besides that, the increase in financial development, strengthens the impact of human capital on economic growth. This strengthening is more in developing countries than in developed countries. These findings imply that achieving higher growth rates, especially in developing countries, depends on the optimal combination of sufficiently high levels of human capital and financial development.Keywords: Rolling regression, Financial development, Human capital, Economic growth, Panel data

In recent decades, due to the increase of stress in financial markets and its effect on economic growth, the need to find better models and indicators to deal with crisis events and reduce their effects is felt. This paper seeks to answer this question: What are the effects of the stress of the financial system and its main sub-sectors (banking system, stock market, and foreign exchange market) on economic growth in Iran? For this purpose, the quarterly data of the time-series 1370Q1 to 1395Q2 (1991Q2 to 2016Q3) from the banking sector and the stock and foreign exchange markets have been used. To construct a multi-lateral financial stress index "within" and "between" each sector/market, respectively, the method of Principal Component Analysis (PCA) and Credit Weighting (CW) has been used. Using the Auto-Regressive Moving Average (ARMA) and the Auto-Regressive Distributed Lags (ARDL) approach, the required optimal intervals were estimated and using the Exponential General Auto-Regressive Conditional Heteroskedastic (EGARCH) approach, the conditional variance of the desired indicators, which represents the volatility of the indicators, was calculated. Then, using the Markov-Switching approach, the impact of financial stress on Iran's economic growth has been evaluated. The results indicate that despite periods of financial stress in Iran, its effect on economic growth has been insignificant and meaningless in most cases.

The Effect of Entrepreneurship on Income Inequality in Selected CountriesAbstractIncome inequality is one of the important socio - economic issues that is very important in development economics the study of the factors affecting it. In this regard, the present study has tried to investigate the impact of entrepreneurship on income inequality in two groups of selected developing and developed countries during the period 2009 - 2019 . In order to achieve more accurate results, entrepreneurship is divided into necessity and opportunistic entrepreneurship groups in the model . For this purpose, the research model has been estimated by approaching panel data and Generalized Moment Method ( GMM ) separately for the two groups of selected countries . The results show that necessity-oriented entrepreneurship has a negative and significant effect on income inequality in both groups of selected countries . However, the estimated coefficient is higher in developing countries . Also, opportunistic entrepreneurship has a positive and significant effect on income inequality in both groups of selected countries. However, the estimated coefficient is higher in developed countries .

One of the important categories in investing, especially in the stock market, is to pay attention to the issue of risk management for investors and companies. One of the most widely used measures in risk calculation, which includes both time horizon and confidence level, is the value at risk (VaR), which has been highly regarded by researchers and risk analysts over the past two decades. There are various methods, including parametric, semi-parametric and non-parametric, for calculating the risk arc, which can be used depending on the type of data. In this paper, by combining the generalization of Heterogeneous autoregressive model (HAR), ie Heterogeneous autoregressive quarticity model (HARQ) and extreme value theory, we introduce an efficient method for calculating the risk value of some stocks present in the Tehran Stock Exchange and compare the advantages and comparison with other approaches such as parametric and non-parametric. We will address the disadvantages of the introduced method. The statistical population of this research is an example of active companies that were present in the stock exchange from 1392 to 1397. It is noteworthy that the half-hour time frame has been adopted in order to achieve higher accuracy. It is also a method of data analysis using MATLAB software.

In order to investigate the effect of the devaluation of the national currency on the net export of Iran's economy, the two-stage least squares method was used, considering Iran's special conditions, in the generalized Marshall Lerner conditional equation. The results show simple Marshall Lerner condition is not appropriate for examining the effects of exchange rate variation on the trade balance of the Iranian economy due to its assumptions. This condition, only, consider the demand for exports and imports. Since about 85% of Iran's imports include intermediate and capital goods, the effect of the exchange rate directly affects the cost of output and this has significant effects on the prices and elasticities of export goods. Therefore, it is necessary to amend this condition according to the specific conditions of the Iranian economy. In this paper, the extension Marshall Lerner condition in Iran for the period of 1981-2020 has been estimated. The results show that this condition is not met for Iran's economy. Therefore, the policy of devaluation of the national currency does not have a significant effect on the improvement of the country's trade balance, and the economic policy maker should consider other solutions to increase exports. The policy makers must find an alternative solution to increase exports. For example, consider export diversification to improve export performance.

Examining the dynamics of inflation and its uncertainty, as well as the relationship between inflation and measures of economic conditions are of vital importance for the analysis of economic policies. In the process of globalization and increasing relations between countries, the role of global variables is raised as a factor affecting inflation. In this study, the relationship between global economic policy uncertainty with inflation and inflation uncertainty in Iran has been investigated using monthly data during the April 1997 to September 2022. The correlation of the mentioned variables has been investigated using the dynamic conditional correlation GARCH model (DCC-GARCH). According to the research results, fluctuations in global economic policy have a significant relationship with inflation and inflation volatility. Dynamic conditional correlation of global uncertainty with inflation and inflation uncertainty is positive in some periods and negative in other periods. Numerous reasons such as aggregate demand channel, aggregate supply channel, price stickiness, and central bank policies' response to inflation can explain the different correlation behavior over time. Regarding the fact that global economic policy uncertainty can affect inflation and inflation targeting policies in Iran, and policymakers should pay attention to the structure of correlation between inflation and domestic and global macroeconomic.