جستجوی مقالات مرتبط با کلیدواژه "panel threshold regression" در نشریات گروه "علوم انسانی"

Although the use of the happiness economy approach does not have much history, since policy makers generally make decisions in the direction of increasing well-being and public satisfaction, it becomes important to quantify the concept of mental well-being and examine the factors affecting it in order to improve happiness in society.

The purpose of this research is to investigate the effect of government size on people's happiness in two different regimes according to the level of human development in 110 selected countries for the period of 2006 to 2017. For this purpose, threshold panel regression has been used. The information needed for this research includes the happiness variable from the World Happiness Information Bank, economic growth rate, unemployment rate, inflation rate and government size from the World Bank database and human development index from the United Nations Development Program.

The model estimation results show that the variables of government size, economic growth, inflation and unemployment have a significant effect on happiness. According to the threshold limit calculated for the human development variable (0.577), the effect of government size on happiness is different in two regimes.

According to the findings of the research, increasing the size of the government below the threshold of human development leads to a decrease in the happiness of the people of the society, but after crossing the threshold of human development with the increase in the size of the government, the happiness of the people increases, which shows the efficiency of the government policies. Also, with the increase in economic growth, happiness increases and with the increase in inflation and unemployment, happiness decreases, and the noteworthy point is that the negative effect of unemployment is greater than the negative effect of inflation.

Banking, by its very nature, involves a wide range of risks. Banking supervisors should identify their risks and evaluate and manage them. Therefore, the factors affecting banking stability should be identified and applied in proportion to the importance of each relevant strategy. 

The method of the present research is descriptive and applied and using descriptive and inferential methods, the data have been analyzed and then the obtained results have been analyzed. It has been used to identify the impact of credit and liquidity risks on banking stability in selected member countries of the Mena region using the Panel Gentle Transfer Regression (PSTR) model, which is one of the prominent regime change models. 

According to the results of MATLAB software, it was found that the variables of liquidity risk and credit risk in both regimes have the greatest impact on the stability of the banking system of MENA member countries and also the impact of credit risk in both regimes is greater than liquidity risk. Therefore, formulating appropriate policies to manage credit risk reduction can lead to the stability of the country's banking system, which in turn will strengthen the monetary system.  Analyzing the relationship between economic factors and risks on banking stability is an important issue that has been addressed in this study. The thresholds of credit risk as a turning point and distinguishing point of the two regimes expressed in the PSTR model, for these equations, have been estimated according to the Akaik and Schwartz tests (3.36 and 3.83), respectively. The results of parameter slope estimation showed that the adjustment speed from one regime to the second regime was equal to 0.194, which indicates their gentle adjustment speed. In the first regime before the threshold, ie the linear part of the PSTR model, the variables of credit risk, payment facilities, inflation and crisis and shocks to countries have a negative and significant effect on the banking system. In contrast, the variables of facility to deposit ratio, liquidity risk, bank size, return on assets, efficiency of banks and GDP have a positive and significant effect on the banking system. In the second regime, the nonlinear part of the PSTR model, the variables of facility to deposit ratio, bank size, inflation, capital to asset ratio, facilities and crises and shocks that have hit a country have a negative and significant effect on the banking system. In contrast, the variables of liquidity risk, credit risk, return on assets, efficiency of banks, gross national product and payment facilities of banks have a positive and significant effect on the banking system. 

According to the results of this study (first and second scenarios), liquidity risk, in addition to a positive effect on banking stability, intensifies its positive effect on the banking stability of countries. Credit risk also has a significant effect on off-line banking stability, which has been confirmed. In other words, according to the results of the estimated model, the variables of liquidity risk and credit risk in both regimes have the greatest impact on the stability of the banking system of MENA member countries, so that the effect of credit risk in both regimes is greater than liquidity risk. Therefore, formulating strategies to reduce instability in the country's banking system, credit risk management can be an important factor to increase banking stability, which will strengthen the monetary system.

Given the importance of income inequality, which is one of the major problems of macroeconomics, especially in developing countries, and considering the direct impact of remittances on the income of recipient households, the purpose of this study is to investigate the effect of remittances on income inequality. In this regard, the panel threshold regression approach for selected developing countries in the period 2018-2000 using the bootstrap simulation method has been used to approximate the asymptotic distribution of test statistics in Stata software. Findings from estimating the non-threshold linear model showed that the relationship between remittances and income inequality is negative and statistically significant, so that increasing the amount of remittances reduces the income inequality by 0.12 units. On the other hand, estimating the threshold fixed effects model indicates the existence of a threshold of 8.43% for the inflation rate and different effects of remittances on income inequality in two different inflation regimes. Considering the threshold effect, in order to investigate the effects of remittances on income inequality, the results show that remittances before the inflation threshold (low inflation regime), remittances reduce income inequality, but after the threshold (High inflation regime) remittances had a negative effect on income inequality but were not statistically significant. Therefore, the existence of high inflation can neutralize the effect of remittances on income inequality in countries with inflation above the threshold. Also, according to the results of the present study, the economic growth variable has reduced income inequality, but the variables of government size, trade openness, population growth rate and unemployment rate have increased income inequality.

Replacement of labourers by robots and automation has been one of the oldest concerns in the labour market, and many people have attributed rising unemployment to the growth of innovation and technology. Some researchers have linked the impact of technology on employment to breadth and depth of markets. Available evidence suggests that the impact of innovation and technology on employment depends on the international competitiveness of countries and the quality of their workforce. Since the economic complexity index measures both exports and the level of available knowledge in economies, it can be a good candidate for considering the breadth and depth of markets. The present study examines the effect of economic complexity on unemployment by controlling for GDP and inflation and asks whether there is a level of innovation determining the relationship between the economic complexity and unemployment. For this purpose, we use a panel threshold regression for a period 2008- 2017. Findings show that the relationship between economic complexity and unemployment is non-linear. Moreover, there is the evidence of substitution of labour by robots when the innovation index is in the range of [0.456, 0.493).

If happiness is a good feature of society and development is considered as a gradual movement towards good society, happiness can be one of the goals of developmental policies. In the field of happiness economics, the focus of studies is on analyzing the impact of various economic factors on happiness. But so far, no study has investigated the effect of economic variables on happiness with the panel threshold regression models. In the present study, the effect of eight variables on happiness using panel data for 100 countries in the period 2005 to 2016 in three scenarios was investigated using panel threshold regression method. The results of the research show that the happiness relationship with per capita income, health, consumption, government expenditures and economic freedom is positive and there is a negative relationship between happiness and income inequality, inflation and unemployment. In each scenario, only a threshold value was detected. Consumption expenditures and economic freedom have a positive effect on happiness, and the size of this effect increases with increasing per capita income (threshold variable). Per capita income has a positive effect on happiness, but with increasing income inequality (threshold variable), the effect of per capita income will decrease. It seems, therefore, that the formulation of appropriate policies to reduce income inequality can lead to more social happiness for the society, which will result in increased productivity and economic growth.