Behavioral economics
Morteza Khorsandi; Mahnoush abdollahmilani; Teymur Mohamadi; pardis hejazi
Abstract
The effect of income on subjective-wellbeing (as one of the criteria for measuring mental well-being) has been considered in many studies but various dimensions of this effect have not yet been studied. The study aims to investigate the nonlinear effect of income on the subjective-wellbeing of 58 selected ...
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The effect of income on subjective-wellbeing (as one of the criteria for measuring mental well-being) has been considered in many studies but various dimensions of this effect have not yet been studied. The study aims to investigate the nonlinear effect of income on the subjective-wellbeing of 58 selected countries during 2005 to 2020, which has been studied in two scenarios. For this purpose, a PSTR model developed from regime change models has been used. In the present study, the effects of income, unemployment, inflation, life expectancy, and income inequality on subjective-wellbeing have also been investigated. According to the obtained results, in a nonlinear relationship, the effect of GDP on subjective well-being at a certain threshold value of income inequality is decreasing. Therefore, if increasing national income and reducing income inequality as a factor affecting welfare is considered by politicians, it is also important to note that reducing inequality from a certain threshold onwards reduces the impact of income on welfare. This means that from a certain threshold on income inequality, the focus of governments on reducing income inequality should be reduced so that resources are spent on essentials.
Macroeconomics
Zahra Sheikhali Zadeh; Jafar Haghighat; Zahra Karimi Takanlou; Seyed Saleh Akbar Mousavi
Abstract
The present study aimed to explore the impact of banking crisis on income distribution among various income classes in 60 world countries during 1990–2020. In this line, the Generalized Method of Moments (GMM) was used to estimate the six models with different dependent variables that depicted ...
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The present study aimed to explore the impact of banking crisis on income distribution among various income classes in 60 world countries during 1990–2020. In this line, the Generalized Method of Moments (GMM) was used to estimate the six models with different dependent variables that depicted income percentiles for the wealthy, middle, and poor classes. The findings indicated that during a banking crisis, the income share of the wealthy class decreases, while the middle class and the bottom 20% experience an increase in their income share. Consequently, banking crisis could contribute to income equality in the countries under study. In addition to the variable of banking crisis, other variables such as financial development and financial openness could lead to income inequality, while the variables like the ratio of public expenditure to GDP, trade openness, GDP, and GDP squared would cause income distribution equality in the countries. The results suggest that governments support lower-income percentiles through subsidies, support packages, more job opportunities, and provision of low-interest loans, in a bid to mitigate the detrimental effects of banking crisis and reduce income inequality. Furthermore, governments should levy taxes, such as capital gains tax, on higher-income percentiles.IntroductionThe literature offers various definitions for banking crisis. For instance, Liana et al. (2015) define banking crisis as the occurrence of simultaneous bankruptcies within the banking sector, resulting in substantial damage to the capital of the entire banking system, significant economic repercussions, and government intervention. According to Laeven and Valencia (2020), banking crisis occurs when two conditions are met: 1) “significant signs of financial distress within the banking system (indicated by significant bank runs, losses in the banking sector, and/or bank liquidations)” and 2) “significant intervention measures in banking policy in response to significant losses in the banking system.” The year in which both criteria are met is the year when crisis becomes systemic. Banking crisis exerts a myriad of effects, with one notable consequence being the issue of income inequality. There are two points of debate in this respect: the impact of banking crisis on income inequality and the reciprocal influence of income inequality on banking crisis. This research focused on the former. There are various channels through which banking crisis can adversely impact households and their income, including:(a) Loss of deposits in a failed banking institution(b) Loss of employment or earnings directly due to (i) disruption of the payments process, (ii) the bankruptcy of financial institutions (for employees and other stakeholders of these institutions) or (iii) the interruption of credit flows (for borrowing clients with information capital invested in the failed financial institutions)(c) Tax increases or curtailment of public spending due to fiscal cost of bail-outs of financial firms or their customers(d) Temporary or permanent changes in relative prices of (i) consumption goods, (ii) wage rates, (iii) production goods (iv) asset prices, that arise through knock-on effects on the rest of the economy(e) Involuntary unemployment if the crisis leads to a generalized economic downturn. (Honohan, 2005, pp. 6–7)In this context, the present study tried to answer the following questions: How does a banking crisis influence the income distribution of households and contribute to income inequality? Is the presumed impact the same across different income classes (i.e., wealthy, middle, and poor)?Materials and MethodsIn line with El Herradi and Leroy (2022), the present study used the following economic model:(1) In the model, refers to the income share of six different percentiles (p) including Top1%, Top10%, Top20%, Middle-class (21–79 percentile), Bottom20% and Bottom10% in the country i at the time t. is a dummy variable of the banking crisis (1 if a country i faces a banking crisis, otherwise 0). indicates the dependent variable of income distribution, with two lags to show the dynamics of the model. Finally, is a vector of lagged control variables, including GDP and GDP squared, financial development, trade openness, financial openness, the ratio of government public expenditures to GDP and political governance. Also, , and refer to country fixed effects, time fixed effects and an error term, respectively. , and k are model coefficients. The study sample comprised 60 countries worldwide, with annual data spanning the years 1990 to 2020.Results and DiscussionThe occurrence of a banking crisis is linked to significant yet varied effects across the income distribution. Consequently, during a banking crisis, the income shares of the top 1%, top 10%, top 20%, and bottom 10% experienced a decrease. Moreover, a banking crisis resulted in an increase in the income share of the middle-class population (21–79 percentiles) as well as the bottom 20% of individuals. Notably, the rise in the middle class was more substantial. Conversely, the lowest income group (the bottom 10%) exhibited a negative correlation between banking crisis and income share, mirroring the trend observed in the upper percentiles. However, the reduction in the income shares of the lowest income group (the bottom 10%) is considerably less than the losses suffered by higher income groups. According to the findings, the adverse impacts of banking crisis are more pronounced at the right end of income distribution. Therefore, the crisis could contribute to a reduction in income inequality.ConclusionThe findings indicated that a banking crisis adversely affects the income shares of the top 1%, top 10%, and top 20%. In simpler terms, a banking crisis diminishes the income share of these groups in the overall income of society. Notably, the reduction in the income shares of the top 10% (-0.426) is more pronounced compared to the top 1% and top 20% percentiles. Conversely, a banking crisis can increase the income share of the middle class (21–79 percentiles) and of the bottom 20% (i.e., the poor class), with a particularly substantial increase observed in the middle class. Turning to the lowest income group (the bottom 10%), a negative correlation exists between banking crisis and income share. Despite facing a decrease in income similar to the top income percentiles, the decline in their income share is considerably less than the losses experienced by the wealthy percentiles.In summary, a banking crisis could diminish the income share of the wealthy class and increase the income share of the middle and lower classes, contributing to a reduction in income inequality in the studied countries. Consequently, to mitigate the adverse effects of a banking crisis, governments can provide support to low-income percentiles through subsidies, support packages, more job opportunities, and low-interest loans. Additionally, taxes on high-income percentiles, such as capital gains tax, can be helpful. The measures can ultimately lead to a reduction in the income share of the wealthy percentiles and an increase in the share of the lower percentiles, improving income distribution and reducing income inequality.
Habib Ansari Samani; Robabeh Khilkordi
Abstract
The distribution of income, which means the distribution of national income between groups, social classes and economic sectors, is one of the main components of social justice. There are many factors affecting the income distribution. The purpose of this study is to identify the effect of unemployment ...
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The distribution of income, which means the distribution of national income between groups, social classes and economic sectors, is one of the main components of social justice. There are many factors affecting the income distribution. The purpose of this study is to identify the effect of unemployment rate along with other major factors related to income distribution in Iran’s provinces. For this purpose, the annual data for Iran’s provinces during 1999 to 2014, with DOLS estimator have been analyzed. The results show that increasing unemployment in the long run will increase the income inequality in the provinces. Also, inflation rate, economic growth rate and current government spending increase the Gini coefficient in the long run. Error correction model results indicate that, unemployment and government size variables have no significant relationship with the dependent variable in the short run. However Inflation rate and economic growth rate have a positive relationship with inequality in the short run.
Abolghasem Mahdavi Mazdeh; Mohammad Hossein Memarian; Mostafa Mohebi Majd
Abstract
There have been many conflicting studies on income inequality and life expectancy in the past four decades. It seems that many of these studies are affected by a statistical artifact which could lead to measurement error. In this paper, after correcting the statistical artifact, we examine the relationship ...
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There have been many conflicting studies on income inequality and life expectancy in the past four decades. It seems that many of these studies are affected by a statistical artifact which could lead to measurement error. In this paper, after correcting the statistical artifact, we examine the relationship between Gini coefficient (as an index for income inequality) and life expectancy (as an index for public health). To this end, this study uses panel data with random effects for 19 countries (including Iran) over the period 2004 -2012. After correcting the statistical artifact, the results did not suggest any particular association between income inequality and life expectancy.
Yeganeh Mousavi Jahromi; Farhad Khodadad Kashi; Alame Moosapour Ahmadi
Volume 19, Issue 61 , February 2015, , Pages 117-147
Abstract
In the presentstudy,the evaluation of different economic factors’ impact on income inequality in Iran has been considered during the period 1363-1390. In order to achieve this, Auto-Regressive Distributed Lag method is used. The results indicate that the rate ofeconomic growth and inflation rate ...
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In the presentstudy,the evaluation of different economic factors’ impact on income inequality in Iran has been considered during the period 1363-1390. In order to achieve this, Auto-Regressive Distributed Lag method is used. The results indicate that the rate ofeconomic growth and inflation rate havenegative influence and income tax, labour productivity and gas and oil revenue has a positive influence on income equality.Also based on the results, it can be stated that the relationship between economic growth and income distribution confims Kuznets and Kaldor’s view. The structural stability tests indicate the estimated model is stable. In addition, according to calculated elasticities, it can be concluded that revenue fromincome tax has had the most effect on reducing incomeinequality in Iran during the mentioned period.
