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nejati M, Shakibaei A, Gholami M. (2023). Investigating the Relationship between Population Structure and Poverty. refahj. 22(87), : 2 doi:10.32598/refahj.22.87.3957.1
URL: http://refahj.uswr.ac.ir/article-1-3940-en.html
URL: http://refahj.uswr.ac.ir/article-1-3940-en.html
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Introduction: One of the most important goals of the development study is to increase growth and reduce poverty and its interaction with justice, which can be examined through the relationship between economic growth and poverty with changing population levels. In the 1990s, with the rise of the benefits of growth, a general consensus on the weakness of growth tools as the only means of reducing poverty made many researchers turned their attention to other policies alongside economic growth. Therefore, average income and population are referred to as effective factors in reducing poverty. In this regard, in recent studies, there is a discussion entitled growth in favor of the poor, which expresses the relationship between growth and poverty and inequality (population).
Changing population structures in many countries create opportunities for development opportunities and challenges. While aging is a concern in high- and middle-income economies, rapid population growth will continue for decades to come in the poorest countries.
Demographic change can affect economic prosperity and poverty reduction in several ways. First, changes in the working age share of the population increase income and savings, by changing the relative number of people in the economy who can work. Second, age-related changes in the household level can have an infinite impact on poorer families, often with higher child-to-child ratios. The effects of development on changes in age structure are usually broken down into one or more of the first or second dividends. The first benefit is a direct and immediate result after increasing the share of healthy working population. This effect is simple because a larger share of healthy working people means that the economy will be able to produce more people in proportion to the more productive stages of their lives. The second dividend, if there is a change in the structure of age, creates more space for more savings and leads to increased investment in human and physical capital.
Economic growth and its causes have always been the subject of much discussion in economic analysis. Numerous studies have been conducted to identify the effects of various factors on economic growth and poverty, including physical capital, human capital, and labor are introduced as the most important factors. Based on the experiences of different countries, many economic experts believe that the role and importance of physical capital has gradually decreased and attention to human capital as a key factor in economic growth has increased. Therefore, increasing importance of human capital and population has led to more attention to the role of quantity, especially the quality of labor to determine the contribution and impact of this important factor in reducing poverty.
In the case of Iran, given the specific shape of the population pyramid and the significant changes that have occurred in the age structure of the population over time, a comprehensive study on the effects of this issue in various dimensions, especially economic dimensions, seems to be necessary. Because in each stage of the age transition, depending on which age group is in the majority, the type and extent of the economic needs of society change. Therefore, studying the age structure of the population means identifying the current and future needs of society.
In this study, we intend to address the relationship between population structure and poverty and show the extent to which poverty is affected by Iran's population structure. Iran is able to meet the needs of the population due to the vast resources and large area of agricultural land. Therefore, with short-term and long-term planning, the country's officials can prepare the ground for the growth of the active population. In this research, after the introduction, we review the theoretical foundations and studies performed, and in the next step, we specify the model and review it. After examining the long-term relationships as well as the endogenous relationship between the variables, the model is estimated by the GMM method. In the final part, after summarizing, the conclusion is given.
Method:
Mechanisms of how demographic change poverty
The development impact of changes in age structure can be classified as either a first or a second demographic dividend. The first dividend is a direct and immediate consequence of the rise in the working-age share of the population. If a larger share of the population is working, average standards of living will be higher. The potential benefits for poverty reduction are twofold. First, in low-income households that reduce their fertility, standards of living will rise by increasing the number of effective producers per household member. Second, improvements in public finances resulting from an increase in the number of workers in the economy will allow more resources to be devoted to low-income households. The second dividend arises when faster growth of the working-age population leads to greater savings in the short run and higher investment in human capital and investment per worker in the long run.
Demographic dividends in a nutshell.
The first demographic dividend could persist for decades but is ultimately transitory. As fertility rates decline, child dependency ratios fall both within households and within a population, while the share of the working-age population rises and remains high for a few generations. If the increasingly larger working-age population is productively employed, there is potential for an increase in economy-wide living standards. The first dividend is in large part a consequence of a given (growing) labor force supporting fewer children. For some countries, estimates suggest that the contribution of the first demographic dividend explains between 9.2 and 15.5 percent of their per capita economic growth over the 1960–2000 period. The second demographic dividend arises if changes in age structure create space for higher savings and lead to increased investment in human and physical capital. An increase in the share of workers in the economy with respect to the total population leads to higher production and more resources available in the economy, which at the same time can facilitate a rise of savings, investment, and accumulation of physical and human capital. These decisions subsequently influence the productivity of the workforce. Providing capital for a growing labor force is costly, and as labor force growth declines, a given level of investment will lead to greater capital per worker. Demographic change pushes countries toward supplying more capital, further enhancing labor productivity. Because personal assets accumulate over the lifetime of individuals, per capita household wealth rises as a population ages. Table 1 summarizes the first and the second demographic dividends by explaining the transmission mechanisms.
Empirical strategy
The basic association between demographic changes and growth is described by Bloom and Canning (2004) through an accounting identity:
Y N Y L WAP N L WAP
wherein (Y) is income, (N) is total population, (WAP) is the working age population, and (L) is number of workers. Eq. (1) shows that income per capita (Y/N) equals output per worker (Y/L) times the share of the working-age population (WAP/N) times the participation rate (L/WAP). The equation suggests that, everything else constant, an increase in output per worker (Y/L), or an increasing in the share of working-age population (WAP/N), or in the participation rate (L/WAP) is associated with higher GDP per capita. By taking the log of the variables in (1) and presenting the relation in terms of growth, it leads to:
g y g z g w g l
where gy is income per capita growth, gz productivity growth per worker, gw is the growth of the share working-age population, and gl is the growth in the labor force participation rate.
Assuming that productivity growth per worker is a function of X variables, such that gz=a1+bf(x) and growth of labor force participation is constant, such that gl = a2 and a= a1+a2 this leads to the following functional form:
g y a bf x g w ε
where e is the error term.
Eq. (3) suggests that, keeping everything else constant, an increase in the working-age population share leads to higher GDP per capita growth. The main issue behind this association is that, as (3) is derived from an accounting identity, a set of strong assumptions are necessary to suggest a causal relationship between changes in the share of working-age population and growth. To minimize this issue, we use two key variables that determines the changes in share of working age population: changes in the child-dependency and aged-dependency ratios, as described by Eq. (4). These variables have the benefit of do not using the total population in the denominator, which is also present in the per capita growth, and do not impose symmetry on the dependent young and old population.
g y a bf x g CDR g ADR ε
To show the effect of demographic change on poverty, we estimate the following regression based on the growth relationship of Bloom and Canning.
POV t B B CHD t B AGED t B Sc h ool t B Trade t B t
Changes in child dependence (CHD) mean young age dependency burden (0-14 population ratio to active population (15-64)) and age dependency ratio (AGED) mean old age dependency burden (population ratio over 65 years to 15-64 population).
Results:
In this research, in order to achieve the most efficient method for estimating the mana test of variables, Johansen's collective test and also Hausman endogenous test have been performed. Hausmann endogenousity has been performed, which is endogenous in regression between variables. The best method for estimating regression with respect to endogenous method is GMM.
Results of model estimation by GMM method
In general, according to the results, it can be concluded that the dependent population of the child and years of schooling have a negative and significant relationship with the dependent variable, the elderly dependent population has a negative and significant relationship with the dependent variable and also the percentage of trade in GDP and Physical capital inventories have a negative relationship with the dependent variable.
Discussion:
In this study, the years of schooling, the percentage of trade in GDP as well as capital stock are based on the coefficient in accordance with the theory, and increasing each will reduce poverty. In the case of the elderly population, according to the stated demographic mechanism, when the second population benefit occurs, the rapid growth of the population of experienced people will lead to more savings in the short term and more investment and savings in human capital and investment of each worker, and it takes a long time. This savings and investment put more resources at the disposal of the workforce, which in turn reduces poverty. Another result of this study is the positive effect of the elderly population on poverty reduction, which indicates the existence of high savings in old age. This mechanism and effect can be such that the ultimate desire to save for consumption increases in retirement and old age, and this is a potential factor in financing the investment. The greater these savings, the more resources will be available to invest in the manufacturing sector and to invest in human resources, which will increase income and ultimately reduce poverty. According to the results presented in this study, years of education, which is used as an indicator of human capital in the model, has a positive effect on poverty reduction, so it can be concluded that paying attention to the growth of highly educated employees and employing specialized personnel increases interest the labor force side as well as the possibility of creating new methods of production that have significant effects on poverty reduction.
Ethical considerations
The present study is descriptive, analytical and quantitative in terms of method. The principles of trustworthiness in the use of sources have been observed by mentioning the name and date of the work. Also, in the stage of collecting information and analyzing and interpreting data, honesty and respecting the rights of all people are taken into account. Here, it is necessary to thank all the people who helped us in doing this research.
Changing population structures in many countries create opportunities for development opportunities and challenges. While aging is a concern in high- and middle-income economies, rapid population growth will continue for decades to come in the poorest countries.
Demographic change can affect economic prosperity and poverty reduction in several ways. First, changes in the working age share of the population increase income and savings, by changing the relative number of people in the economy who can work. Second, age-related changes in the household level can have an infinite impact on poorer families, often with higher child-to-child ratios. The effects of development on changes in age structure are usually broken down into one or more of the first or second dividends. The first benefit is a direct and immediate result after increasing the share of healthy working population. This effect is simple because a larger share of healthy working people means that the economy will be able to produce more people in proportion to the more productive stages of their lives. The second dividend, if there is a change in the structure of age, creates more space for more savings and leads to increased investment in human and physical capital.
Economic growth and its causes have always been the subject of much discussion in economic analysis. Numerous studies have been conducted to identify the effects of various factors on economic growth and poverty, including physical capital, human capital, and labor are introduced as the most important factors. Based on the experiences of different countries, many economic experts believe that the role and importance of physical capital has gradually decreased and attention to human capital as a key factor in economic growth has increased. Therefore, increasing importance of human capital and population has led to more attention to the role of quantity, especially the quality of labor to determine the contribution and impact of this important factor in reducing poverty.
In the case of Iran, given the specific shape of the population pyramid and the significant changes that have occurred in the age structure of the population over time, a comprehensive study on the effects of this issue in various dimensions, especially economic dimensions, seems to be necessary. Because in each stage of the age transition, depending on which age group is in the majority, the type and extent of the economic needs of society change. Therefore, studying the age structure of the population means identifying the current and future needs of society.
In this study, we intend to address the relationship between population structure and poverty and show the extent to which poverty is affected by Iran's population structure. Iran is able to meet the needs of the population due to the vast resources and large area of agricultural land. Therefore, with short-term and long-term planning, the country's officials can prepare the ground for the growth of the active population. In this research, after the introduction, we review the theoretical foundations and studies performed, and in the next step, we specify the model and review it. After examining the long-term relationships as well as the endogenous relationship between the variables, the model is estimated by the GMM method. In the final part, after summarizing, the conclusion is given.
Method:
Mechanisms of how demographic change poverty
The development impact of changes in age structure can be classified as either a first or a second demographic dividend. The first dividend is a direct and immediate consequence of the rise in the working-age share of the population. If a larger share of the population is working, average standards of living will be higher. The potential benefits for poverty reduction are twofold. First, in low-income households that reduce their fertility, standards of living will rise by increasing the number of effective producers per household member. Second, improvements in public finances resulting from an increase in the number of workers in the economy will allow more resources to be devoted to low-income households. The second dividend arises when faster growth of the working-age population leads to greater savings in the short run and higher investment in human capital and investment per worker in the long run.
Demographic dividends in a nutshell.
| Channel | Transmission mechanisms | Demographic dividend |
| Labor force Savings Human capital |
Increase in the support ratio (ratio of effective labor to effective consumers) holding other factors, including saving and income per effective worker, Constant Changes in saving and capital per effective worker influence income, from labor and assets, per effective worker Lower fertility and the quantity-quality trade-off lead to greater spending on health and education for children |
First Second Second |
The first demographic dividend could persist for decades but is ultimately transitory. As fertility rates decline, child dependency ratios fall both within households and within a population, while the share of the working-age population rises and remains high for a few generations. If the increasingly larger working-age population is productively employed, there is potential for an increase in economy-wide living standards. The first dividend is in large part a consequence of a given (growing) labor force supporting fewer children. For some countries, estimates suggest that the contribution of the first demographic dividend explains between 9.2 and 15.5 percent of their per capita economic growth over the 1960–2000 period. The second demographic dividend arises if changes in age structure create space for higher savings and lead to increased investment in human and physical capital. An increase in the share of workers in the economy with respect to the total population leads to higher production and more resources available in the economy, which at the same time can facilitate a rise of savings, investment, and accumulation of physical and human capital. These decisions subsequently influence the productivity of the workforce. Providing capital for a growing labor force is costly, and as labor force growth declines, a given level of investment will lead to greater capital per worker. Demographic change pushes countries toward supplying more capital, further enhancing labor productivity. Because personal assets accumulate over the lifetime of individuals, per capita household wealth rises as a population ages. Table 1 summarizes the first and the second demographic dividends by explaining the transmission mechanisms.
Empirical strategy
The basic association between demographic changes and growth is described by Bloom and Canning (2004) through an accounting identity:
wherein (Y) is income, (N) is total population, (WAP) is the working age population, and (L) is number of workers. Eq. (1) shows that income per capita (Y/N) equals output per worker (Y/L) times the share of the working-age population (WAP/N) times the participation rate (L/WAP). The equation suggests that, everything else constant, an increase in output per worker (Y/L), or an increasing in the share of working-age population (WAP/N), or in the participation rate (L/WAP) is associated with higher GDP per capita. By taking the log of the variables in (1) and presenting the relation in terms of growth, it leads to:
where gy is income per capita growth, gz productivity growth per worker, gw is the growth of the share working-age population, and gl is the growth in the labor force participation rate.
Assuming that productivity growth per worker is a function of X variables, such that gz=a1+bf(x) and growth of labor force participation is constant, such that gl = a2 and a= a1+a2 this leads to the following functional form:
where e is the error term.
Eq. (3) suggests that, keeping everything else constant, an increase in the working-age population share leads to higher GDP per capita growth. The main issue behind this association is that, as (3) is derived from an accounting identity, a set of strong assumptions are necessary to suggest a causal relationship between changes in the share of working-age population and growth. To minimize this issue, we use two key variables that determines the changes in share of working age population: changes in the child-dependency and aged-dependency ratios, as described by Eq. (4). These variables have the benefit of do not using the total population in the denominator, which is also present in the per capita growth, and do not impose symmetry on the dependent young and old population.
To show the effect of demographic change on poverty, we estimate the following regression based on the growth relationship of Bloom and Canning.
Changes in child dependence (CHD) mean young age dependency burden (0-14 population ratio to active population (15-64)) and age dependency ratio (AGED) mean old age dependency burden (population ratio over 65 years to 15-64 population).
Results:
In this research, in order to achieve the most efficient method for estimating the mana test of variables, Johansen's collective test and also Hausman endogenous test have been performed. Hausmann endogenousity has been performed, which is endogenous in regression between variables. The best method for estimating regression with respect to endogenous method is GMM.
Results of model estimation by GMM method
| probe | Statistics t | Coefficient | Variable |
| 0639/0 | -921509/1 | -803908/0 | AGED |
| 0153/0 | -567605/2 | -630110/0 | CHD |
| 0000/0 | -44201/10 | -227189/0 | Sch |
| 2610/0 | -144923/1 | -054795/0 | TR |
| 4004/0 | -852659/0 | -489818/0 | CAP |
| 0000/0 | 7402/101 | 221165/4 | C |
In general, according to the results, it can be concluded that the dependent population of the child and years of schooling have a negative and significant relationship with the dependent variable, the elderly dependent population has a negative and significant relationship with the dependent variable and also the percentage of trade in GDP and Physical capital inventories have a negative relationship with the dependent variable.
Discussion:
In this study, the years of schooling, the percentage of trade in GDP as well as capital stock are based on the coefficient in accordance with the theory, and increasing each will reduce poverty. In the case of the elderly population, according to the stated demographic mechanism, when the second population benefit occurs, the rapid growth of the population of experienced people will lead to more savings in the short term and more investment and savings in human capital and investment of each worker, and it takes a long time. This savings and investment put more resources at the disposal of the workforce, which in turn reduces poverty. Another result of this study is the positive effect of the elderly population on poverty reduction, which indicates the existence of high savings in old age. This mechanism and effect can be such that the ultimate desire to save for consumption increases in retirement and old age, and this is a potential factor in financing the investment. The greater these savings, the more resources will be available to invest in the manufacturing sector and to invest in human resources, which will increase income and ultimately reduce poverty. According to the results presented in this study, years of education, which is used as an indicator of human capital in the model, has a positive effect on poverty reduction, so it can be concluded that paying attention to the growth of highly educated employees and employing specialized personnel increases interest the labor force side as well as the possibility of creating new methods of production that have significant effects on poverty reduction.
Ethical considerations
The present study is descriptive, analytical and quantitative in terms of method. The principles of trustworthiness in the use of sources have been observed by mentioning the name and date of the work. Also, in the stage of collecting information and analyzing and interpreting data, honesty and respecting the rights of all people are taken into account. Here, it is necessary to thank all the people who helped us in doing this research.
Type of Study: orginal |
Received: 2021/08/2 | Accepted: 2022/11/19 | Published: 2023/02/8
Received: 2021/08/2 | Accepted: 2022/11/19 | Published: 2023/02/8
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