Population aging can turn the demographic dividend into a drag on economic growth. New research indicates automation can lessen the effects of unfavorable demographic change on labor productivity.
Picture in your mind two countries characterized by very different demographics: one with a young population; the other one with an increasing share of elderly people. All else constant, would you expect these demographic differences to lead to different economic performances? In a recently published paper, we address this question and investigate how demographic change affects labor productivity growth in advanced and emerging economies.
Demographic trends can influence economic growth and development via direct and indirect channels. The direct effects are clearly visible in working-age population dynamics. For instance, Asia and the Pacific’s remarkable growth performance over the last three decades was fostered by increasing population and falling dependency ratios—i.e. the ratio of economically dependent persons (children and the elderly) to the working-age population. Conversely, the reduced number of people available for work has become a drag on growth in many advanced economies.
Less immediately evident, but arguably more relevant, are the indirect effects of unfavorable demographics on the growth of labor productivity—that is, the average output produced per worker. This is critically important, as productivity growth is the ultimate engine of long-run economic growth. Our paper zooms in on this issue and produces three main findings.
First, by reducing the share of workers in the economy, increases in the young and old population shares exert significantly negative effects on labor productivity growth. The impact is larger for population aging, becomes stronger in the long run, and works via different channels. For instance, effort as well as physical and mental capabilities decline beyond a certain age, thus denting workers’ productivity. The accumulation of human capital—i.e., the average skills, knowledge, and experience possessed by individuals in an economy—also falls with population aging.
This is because there are more people in retirement and fewer in education, training, or learning by doing while employed. Population aging can also reduce the accumulation of physical capital—that is, all the equipment (machinery, buildings, vehicles, etc.) used to produce goods and services. This is because older populations tend to spend more than they save, to maintain similar consumption habits once retired. This means less savings are available to be channeled to firms for investment in physical capital.
Second, somewhat counterintuitively, population aging has a greater negative impact on emerging economies than on advanced economies. One reason is that, despite being on average younger, emerging economies are also less prepared to deal with the negative effects associated with aging populations.
Policy reforms can help cushion the negative impact of aging on working age population and the labor force.
Meanwhile, governments in advanced economies—which are ahead in the demographic transition toward older societies—have already implemented substantial policy reforms to address these issues. Even more importantly, to a much larger extent than in emerging economies, firms in advanced economies have adopted technological innovations to substitute for missing workers and make older workers more productive.
In this respect, the increasing adoption of automation technologies in production processes is particularly relevant. Robots can substitute for manual labor in tasks where automated machines are more productive than humans, thus complementing workers’ skills and increasing workers’ productivity.
Our third main finding is that greater robotization does indeed reduce the negative effects of unfavorable demographic change—in particular, population aging. Unsurprisingly, richer and older advanced economies are characterized by higher degrees of automation of production processes, as measured by the number of industrial robots per one thousand employees.
However, even for this group, we find that only three economies had enough robots to completely offset the impact of aging on labor productivity growth in 2015: Germany, Japan, and the Republic of Korea.
These findings have important policy implications, including for some economies in Asia and the Pacific, such as the People’s Republic of China, which will see their populations age rapidly in the near future. Policy reforms can help cushion the negative impact of aging on working age population and the labor force.
For instance, measures such as raising the normal retirement age, incentivizing greater labor force participation including by women, and relaxing constraints on migrant inflows would reduce dependency ratios. The same measures are also likely to foster labor productivity growth when combined with policies such as life-long learning programs, on-the-job training, or job-matching frameworks coordinated via employment agencies.
However, the key contribution to reducing the negative effects of population aging can only come from technological progress, which is the main driver of labor productivity growth. In this respect, our results indicate that fully harnessing and exploiting the advantages of automation can go a long way towards managing this problem.