الهام حشمتی دایاری

Poverty is one of the major problems of human societies that causes many social harms. Therefore, policymakers and economic development planners always aim to eliminate it. In addition, economic growth is one of the important and influential variables of macroeconomics. Therefore, examining the impact of economic growth on poverty through the lens of growth and distribution effects offers valuable insights for policymaking and poverty reduction strategies. In this study, we use the log-normal curve approach introduced by Bourguignon to estimate the growth effect on poverty utilizing data from urban households in Iran over the period 2013-2019. The results indicate that only in the one-year period of 2015-2016, the triangle of poverty, growth, and inequality has worked well and the growth has been pro-poor.Furthermore, provincial-level findings unveil discernible patterns:(a) In provinces experiencing positive growth, urban areas in Qom exhibit pro-poor growth, while those in Alborz, Golestan, and Hamedan provinces observe a trickle-down effect. Meanwhile, in other provinces, growth demonstrates an immiserizing trend.(b) In provinces with negative growth, only urban areas in Markazi province observe a reduction in poverty. However, due to the lack of growth, it cannot be concluded that this province has had pro-poor growth. In the urban areas of other provinces in this group, the situation has been unfavourable for the poor.

Inequality is one of the basic problems of countries. So, it is very important to examine how income is distributed in a society. Therefore, many studies have been conducted in this regard, but in general, in the studies that used the common methods of calculating inequality, the inequality between different groups is ignored in determining the total inequality, therefore, researchers pay less attention to between-group inequality. In this study, in addition to calculating the inequality in Iran's occupational groups, the inequality between occupational groups has also been evaluated with the ANOVA coefficients approach. Since the measurement of inequality is normalized with these coefficients. For this purpose, household cost-income data during 2013-2019 in urban areas of Iran have been used. The results show that inequality has increased in the most occupational groups, but, it has been almost constant in the "administrative and clerical workers" and "artisans and workers in related occupations", and "administrative and clerical workers" has the best income distribution status and the "legislators, high-ranking officials and managers" has the highest level of inequality. Also, the results indicate that the share of inequality between occupational groups was approximately 50% and close to the share of inequality within groups.

The study analyzed inequality in Iran's provinces using the Atkinson index, Zanga index, and Gini coefficient based on occupational groups. Reducing inequality is an essential economic and social issue, and regional disparities impede growth and development of any region. Focusing on each province's regional economy can lead to better development planning. Therefore, the calculation of inequality is required. Considering that the Gini coefficient and the Zanga index are statistical tools for measuring inequality and the Atkinson index is derived from the social welfare of individuals; therefore, the effects of income distribution in society in two dimensions have been measured. For this purpose, the study used cost and income data of urban households in Iran from 2013-2019. The Location Quotient approach is used to determine each province's target occupational group to understand regional inequality better and improve it as much as possible. Accordingly, the "managers" and "employees" have a better income distribution than other occupational groups in most provinces. On the other hand, compared to other occupational groups, in most provinces, the "operators and assemblers of machinery, and drivers" and "simple workers" have a more challenging situation. Thus, they should prioritize the target occupational groups to improve income distribution.

The main goals of this article are to measure pro-poor growth in urban areas of Iran using the Chanona (2020) matrix and to rank the categories of activities and occupational groups in urban areas of Iran based on poverty growth using the Euclidean TOPSIS technique. For this purpose, cost and income data of urban households in Iran during the period 2013-2019 has been used. The results show that during the period under review, only the period of 2016-2017, both growth and income distribution have reduced poverty and the growth has been pro-poor. However, in the period of 2015-2016, poverty has increased and growth has been Immiserizing. In other years, the Chanona index has shown an increase in poverty. The results of the TOPSIS model also show that among the categories of activities "financial and insurance activities" and among the occupational groups; The "Administrative and Office Staff" group ranks first in poverty alleviation. Therefore, to reduce poverty, it is recommended to pay attention to income growth and redistribution in economic planning and policy-making. Because paying attention only to growth such as the period 2015-2016 can increase poverty in Iran. In addition, although the improvement in income distribution can be such that poverty is reduced even in the absence of growth; But in other one-year periods examined, it can be seen that the lack of attention to growth has led to an increase in poverty in Iran and reduce in inequality alone cannot lead to a reduction in poverty

The lack a close relationship between economic well-being and mental well-being have attracted more attention from economists to substituting a subjective approach to dismissing and evaluating individual and social well-being rather than an objective one; for this purpose, an indicator known as happiness has been introduced.Therefore, in this study, based on the variables of the Gross Nationality Happiness Index, an appropriate index for provinces of Iran was introduced and using the multi-criteria decision-making technique and TOPSIS method during period of 2005-2015 to be calculated and ranked.The ranking results show on average during period considered, provinces of Tehran, Kohgiluyeh, Boyer-Ahmad and Esfahan had highest levels of happiness in the country respectively, and provinces of Sistan and Baluchestan, South Khorasan and Kermanshah are respectively, at low levels of happiness. The important point in calculation of happiness is that central provinces are located in higher ranks above the border provinces of country, which indicates the centrality of happiness in center of country due to amenities facilitation in these areas.In order to investigate the distribution of happiness inequality in Iran, Kuznets relationship was used in both ordinary least squares (OLS) and Robust least squares (RLS) methods for cross-sectional information in 30 provinces of the country. The results indicate the inverse U relationship between the happiness and its inequality. In the first, with increasing happiness, happiness inequality increases, but from one point onwards, due to widespread welfare of general public, with increasing happiness, inequality resulting from it decreases.

Poverty is one of the most important social problems that have been always affected the lives of many people, so eliminating this problem is always among the goals of social development. Despite the many efforts that have been made throughout history to eliminate this phenomenon, it has existed for many years and among different countries and continues despite economic growth among underdeveloped or developing countries. In the economics literatures, several factors are effective in creating and spreading poverty, one of which can be considered the exchange rate, which is considered as a key and important economic variable in policy-making. In recent years, the real exchange rate has fluctuated in recent years, and it is important to know its effects on economic policy- making. So, one cannot overlook the significant impact of the exchange rate on poverty. Therefore, the aim of the present study is to try to find out what the asymmetric effects of the exchange rate will be on poverty. 

The research variables include poverty index, the real exchange rate and government support. To study the subject, have been used the latest data of the Iran during the period of 1985 to 2018. In this research, a dynamic panel threshold model is investigated to distinguish the asymmetric effects of real exchange rates on poverty. This approach combines time series models with threshold modeling approaches. In this paper, using NARDL, an attempt is made to investigate the positive and negative asymmetric effects of exchange rates on poverty in the Iranian economy using a nonlinear model. 

The results show that long term exchange rate impacts on poverty in Iran. In the short run, with a period of delay, exchange rate fluctuations increase poverty in Iran, and real exchange rate declines have no effect on poverty reduction. Also government assistance to the poor and low- income groups in the long and short run has not reduced poverty in the country. 

The results show that in both the short and long term, only an increase in the exchange rate will have a devastating effect on poverty and its impact is greater in the long term than in the short term. And in the short and long term, the depreciation of the real exchange rate has no effect on the reduction of poverty, so governments must implement policies that do not cause sharp fluctuations in the real exchange rate, especially in the event of an increase. The possibility of monetary and fiscal policies should be determined in such a way as to minimize exchange rate fluctuations. In addition, although the exchange rate is not a choice for policymakers, if faced with these conditions, the negative effects of an increase in the exchange rate can be mitigated by government support for the poor through transfer payments and indirect payments to vulnerable groups.

Poverty is a fundamental multidimensional phenomenon which has always been and is one of the most important detriments to societies and the root of the problems and hindrances of most parts of the world. Efforts to eliminate this social problem are one of the most prominent goals of economic growth and development; and despite economic growth in underdeveloped or developing countries, this problem persists. .Although growth in income, as one of the macroeconomic variables, has a significant effect on poverty and its reduction, but the existence of inequality and its effect on economic growth plays an important role in benefiting the poor from economic growth. In the process of economic growth, what reduces poverty is an increase in household income; thus, the distribution of income among households should be such that the poor also benefit from this growth. Therefore, economic growth is not sufficient to eliminate poverty on its own, and its effect on poverty is not the same at different times and places, and the manner in which the benefits of growth are distributed is significant as well. Inequality and poverty are two completely different concepts, but they are deeply related. Therefore, paying attention to economic growth and reducing inequality can have good results in reducing poverty. In recent decades, societies that have focused on both economic growth and reducing inequality have been much more successful in reducing poverty. In this regard, to understand the effects of economic growth on poverty, it is necessary to distinguish between the effects of economic growth on poverty and the effect of inequality on poverty. Then, the change in the poverty index is broken down into a change in average incomes and changes in income inequality to properly determine the contribution of income and inequality in poverty decrease.

in the present study, the effects of income and inequality and their resultant on reducing poverty in the provinces of Iran over a fourteen-year period, from 2004 to 2018, have been determined using the Sen Index, the Kakwani method, and various mathematical methods.

As confirmed by our study results, both income effects and inequality effects had performed in favor of the impoverished in the province of Yazd and led to poverty reduction, while in Kermanshah, Khorasan Razavi, Isfahan, and Zanjan the income effects and inequality effects have somewhat neutralized one another. In other words, even though the increase in the average income reduced poverty, the increased inequality led to increased poverty. On the other hand, the situation in the province of Alborz was considerably different. In this province, although decreasing the average income increased poverty, the improvement in income distribution not only eliminated the negative effects of the income share, but also reduced poverty. However, the income effects and inequality effects had moved in the same direction in Gilan, Khuzestan, Fars, Hamedan, Chaharmahal & Bakhtiari, Lorestan, Tehran, Qom, North Khorasan, and Sistan and Baluchestan, to increase poverty. Finally, in other provinces, the distribution of income has changed in a way that despite the increase in average incomes, poverty increased.

Therefore, as the research findings show, poverty has decreased in only a few provinces during the period under review. And the inequality effects and the income effects, or both, have led to increased poverty. Therefore, in order to reduce poverty, economic growth and reduce inequality must be given much attention.

The outbreak and spread of the corona virus in the world have caused great suffering and hardship to human society. But this suffering is not limited to disease and mortality and has put the global economy at risk. The shock caused by this virus on the world economy is very significant. Many countries have extensive quarantines and restrictions to curb the virus. Iran has also tried to control the spread of the disease by using social distancing and closing down non-essential jobs. Hence, Corona has been able to cause major economic problems. Therefore, in this study, the remote labor index (RLI) was calculated. Jobs and activities are classified into essential and non-essential. The data of 1397 for jobs and activities from the Statistics Center of Iran have been used, to calculate the supply shock caused by the Corona virus on the economy of Iran. The results show that the total supply shock was equal to 34% and according to the main occupational groups, the highest supply shocks were in the occupational groups of "artisans and related occupations" and "simple workers" with 70% and 62%, respectively.

Poverty is one of the major problems of human society and efforts to reduce it has been always the most important objectives of government policy. In order to achieve this goal, inclusive growth has a critical role. However, income inequality also affects the pace which economic growth is translated into poverty reduction. The most important challenge for policymakers in creating pro-poor policies is linking micro and macroeconomic field. Lack of coordination between these both can prevent the impact of the pro-poor policies In this study, it has been tried by using information household budget to create coordination and Cointegration between macro analyses of economic growth, and the microanalyses of economic actor's behavior. So how economic growth reduces poverty is a key question that discussed in this study. In addition, the impact of changes in average income and income distribution on poverty is studied. To determine which economic sector has been had pro-poor growth, pro-poor growth indexes are calculated for the services, industry and agriculture sectors in urban and rural areas of Azerbaijan Gharbi, Isfahan, Tehran, Khorasan Razavi, Khuzestan, Sistan & Baluchestan, Fars, Kermanshah, Mazandaran and Markazi provinces during the period 2005-2014. Furthermore, using the results, Gini's coefficient has been investigated as an index of inequality. The research results indicate that economic growth is negative in the majority of cases that has increase poverty through income effect. But income distribution has improved and has led to poverty reduction. According to the balance of these two effects on poverty except for Sistan & Baluchistan where poverty has increased in all sectors, Urban service's sector in Tehran, the urban agricultural sector in Isfahan and rural service's sector in other provinces have had best situation in pro-poor. Compare Gini's coefficient with model results indicates that the Gini coefficient did not report inequality correctly.