GDP Decline: US Aging Population to Increase 39% by 2050 - Essay Sample

Introduction

The aging population is cited as a significant concern with regard to economic growth. According to Maestas, Mullen, and Powell (2016), a 10% increase in the aging population results in a 5.5% decline in the GDP per capita growth rate. According to the results of the study, the trend can result in a progressive decline in the annual GDP over the years. According to the study, the US population expects a 39% rise in the aging population by the year 2050. The change in population structure is attributed to the declined fertility rate and mortality rate. The impact of the dramatic shift in the population structure is the decline in the economy, government sustainability programs, and reduced consumption by the population. Key concern on the relationship between demography and economics emanates from the long-run determination of the changing population age structure and the productivity demands as well as correlation to economic growth. Young generations and elderly generation are referred to as net consumers depending on the efforts of the productive adult population. According to Maestas et al. (2016), adults are producers and savers working to meet the productivity needs of the young and elderly. According to Maestas et al. (2016), the variation in productivity across the aging spectrum can be used to determine the impact of age structure on the productivity of a population and GDP growth.

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The age structure does not entirely mean that old age is uniquely linked with limited productivity. According to literature by the National Council's Committee, with regards to the long-run macroeconomics effect of the US' aging population, the productivity effects of the aging population may be insignificant. In an assertion of the research findings, Burtless (2013) hinted that the earnings of the older population are continually rising and therefore has limited influence on impairing the economic productivity of the population. The population age structure has a diverse impact on the productivity and economic growth of a country.

Effects of Aging Population on Economic Growth

A study by Maestas et al. (2016) focused on elaborating on the relationship between the demographic forces and economic growth of the population. The labor input of a population is depended on the employment rate of the country, and human capital presented by the population. The age structure of the population shapes human capital and employment rates. Labor supply in an economy is primarily depended on the age, while human capital varies over the life cycle of an individual and different birth cohorts. The study incorporated the human capital with age-specific employment in expressing the effectiveness of the labor output of the population. The results of the study indicated that the productivity of the population is also dependent on the contribution of the older population. The study highlighted that changes in the older population could affect adequate labor supply by altering the working population and the productive composition of the labor force.

Population productivity is closely linked to the age structure of the population. Age is a determinant of population productivity with a population ranging between 0-19 years and above 60 years, turning out to be less productive. The world population is increasingly aging, with an expected rise to 29% of the world population comprising of the aging population. In the contrary, the young generation aged between 0-19 is slightly dwindling, which also questions the future of productivity of the world's population. A study by Zhang, Zhang, and Zhang (2015) examined the economic implications of the change in the demographic age structure on regional development in China. The study adopted an age structure that was aligned with 28 provinces in China. The study results indicated a correlation between the age structure and growth rates in the respective Chinese provinces. The interprovincial inequality in income and economic growth is attributed to the variations in the age structure across the provinces (Zhang et al., 2015). The study base on two empirical frameworks in the examination of the relationship between demography and economic status. According to the results of the study, the change in the age structure has accounted for 19% growth observed in GDP per capita of the country. According to Zhang et al. (2015), the demographic variations play a significant role in shaping the inequality in the income among Chinese provinces.

A study by Kotschy and Sunde (2016) on the influence of the aging population and the associated change in the distribution of human capital on economic performance indicated that aging and distribution of human capital influence economic growth. The component of human capital in a population determines the productivity of the population (Kotschy & Sunde, 2016). The distribution of human capital in an economy is a critical determinant of productivity and economic growth. The skills in human capital also vary with age. The variations in the age structure have a direct impact on skills and expertise. The study derived that aging positively impacts the productivity of the adult population until after 60 years, where a significant decline is evident (Kotschy & Sunde, 2016). The study based on the standard development accounting model that focuses on the aggregate framework of production.

Peterson (2017) drew historical data to establish the connection in population growth, per capita output and economic growth for 200 years. According to the results of the study, high-income countries with low population growth rates are susceptible to social and economic problems. The contrary, high population growth rate in low-income countries can lead to the slow development process. The study indicated that the solution to population growth disparities lies in international migration establishing a balance in the population of different countries. Based on the findings of the study, the slower growth in population and limited migration increases national and global inequalities in the economy. As highlighted by Peterson (2017), rapid growth in population in low-income countries leads to high numbers of dependent children which is detrimental to the economy of the country. However, the population is only damaging in the short and medium run; in the long run, the it becomes demographic dividends for particular countries as a larger productive adult population dominates the economy.

In the case of Vietnam, a study determining the influence of demographics and the growth of the Vietnam economy indicated a significant rise in the working population of Vietnam (Nguyen, 2009). The increase in the labour force reflects a decreased dependency ration in the country. The change in the population structure aligns to increased human capital which promotes economic growth. According to the study, demographic changes have influenced 15% economic growth over five years. The study also indicated that the elderly lack any negative influence on the economy regardless of being categorized as a dependent population. However, children have a negative effect on the economy. Nguyen (2009), predicted a shift from demographic dividend to demographic debt in the Vietnam population. However, the government can take advantage of the demographic dividend in improving the technology and human capital in preparations for impending demographic debt. The government can streamline the pension scheme and healthcare systems in the medium term of the Vietnamese population. According to Nguyen (2009), the Vietnamese population has realized a substantial decline over the years.

The question of the reason for the decline in aggregate labour productivity is a paradox which should be considered for extensive research. According to a study by Goldin, Koutroumpis, Lafond, Rochowicz and Winkler (2018), the decline in productivity is linked to capital deepening and productivity. Goldin et al. (2018) hint that the diffusion of technology influences the decrease in labour productivity. The gap between the first adopters of technology and late adopters is cited as crucial parts of the disparity in labour force decline. The study aimed at establishing a connection between slowed productivity and technology change.

Feyrer (2007) evaluated the connection between demographics and corresponding productivity. According to the study, a significant correlation exists between demographics and productivity.

References

Feyrer, J. (2007). Demographics and productivity. The Review of Economics and Statistics, 89(1), 100-109.

Goldin, I., Koutroumpis, P., Lafond, F., Rochowicz, N., & Winkler, J. (2018). Why is productivity slowing down. Technical report, Working Paper, Oxford Martin School, University of Oxford.

Kotschy, R., & Sunde, U. (2016). Skills, Aging, and Productivity: Evidence from Panel Data.

Maestas, N., Mullen, K. J., & Powell, D. (2016). The effect of population aging on economic growth, the labor force, and productivity (No. w22452). National Bureau of Economic Research. http://www.nber.org/papers/w22452

Nguyen, T., M. (2009): Dynamic demographics and economic growth in Vietnam, Journal of the Asia Pacific Economy, 14:4, 389-398 http://dx.doi.org/10.1080/13547860903169365

Peterson, E. W. F. (2017). The role of population in economic growth. SAGE Open, 7(4), 2158244017736094.

Sevilla, J. (2007). Age structure and productivity growth. Institute for Future Studies working paper, 10.

Zhang, H., Zhang, H., & Zhang, J. (2015). Demographic age structure and economic development: Evidence from Chinese provinces. Journal of Comparative Economics, 43(1), 170-185.