Demographic Transition and Inflation in Emerging Economies

ABSTRACT

Demographic transition has been shaping the age structure of emerging countries, leading to huge swings between the working-age and the dependent population. In this paper, we focus on the impact of demography on inflation in emerging market economies by analyzing the inflationary impact of different age cohorts. Our empirical findings suggest that while the dependent population (net dis-savers) is associated with inflationary pressures, the working-age population (savers) is associated with deflationary pressures. The findings also suggest that demographic transition has contributed to disinflation in these countries over the last two decades.

KEYWORDS:

• Demography
• life-cycle behavior
• inflation
• emerging economies

Disclosure Statement

No potential conflict of interest was reported by the authors.

Notes

1. Since the demographic transition is discussed extensively in other studies, we keep the concept short and introduce the related data in this section. Readers inquiring about the subject may refer to second section of the study by Kalafatcılar (2019) in addition to Bloom and Williamson (1998) for more details.

2. Trailers refer to the country group that follows forerunners, Western Europe and the other Anglo-Saxon countries, where demographic transition was first observed.

3. According to the World Bank, upper-middle-income countries are those which have per capita gross national income between 3,956 and 12,235 US dollars (2016). Just like the classification employed in Reher (2004), this is the second group following the top income group.

4. The reason why we also present low variant birth rate projections is that there is an uncertainty around these projections. M. Shirakawa, former deputy governor of Bank of Japan, remarked in 2012 that in Japan between 1976 and 2012, the declines in fertility were always deemed to be transitory and convergence to the long-run trend was presumed, Shirakawa (2012). He claimed that projection failures resulted in questioning of the sustainability of the pension system and public finances.

5. In other words, the share of the working-age population in the total population is 56%, and the remaining 44% consists of the dependent.

6. The NTA project is conducted by the “Center for the Economics and Demography of Aging” (University of California at Berkeley) and the “East-West Center”. The project is led by Andrew Mason (University of Hawai, Department of Economics) and Ronald Lee (University of California, Berkeley, Department of Economics, emeritus). The NTA collects data related to consumption, labor income and transfers for more than 60 countries in collaboration with local and regional institutes. The interested reader may reach the dataset via http://www.ntaccounts.org/web/nta/show/Indicators and learn more about the method of data collection and processing by reading the “National Transfer Accounts Manual: Measuring and Analyzing the Generational Economy”. NTA (2013).

7. The NTA Project employs the smoothing method of Friedman to mitigate the noise in the data. The smoother uses number of observations as weights and gives less weight to age averages with fewer observations.

8. We selected the degree of the polynomial following Juselius and Takats (2015). Interested readers may refer to the discussions around the Graph 4 of that study.

9. United Nations, Department of Economic and Social Affairs, Population Division, World Population Prospects (2017 revision).

10. The disinflation dummy variables take the value of 1 up to 2000 for Mexico and Hungary and up to 2004 for Turkey, otherwise taking the value of 0.

11. As a robustness analysis, we work with alternative samples, excluding Asian and Latin American countries from the sample. Our conclusions regarding the role of demographics do not change.

12. Since the population growth rate is frequently used in empirical analyses to measure the demographic impact on macroeconomic variables, we included this variable in our empirical analysis as well. However, we do not find a statistically significant impact of population growth rate on inflation after controlling for detailed demographic variables. For this reason, we do not report these results separately.

13. Lindh and Malmberg (2000) also reach a similar conclusion. They find that net savers are negatively correlated with inflation. Basic differences between this study and our work are that Lindh and Malmberg (2000) work with larger age cohorts (15–29, 30–49, 50–64, 65–74, 75+) and in order not to fall into the perfect collinearity problem, they cannot include the share of one cohort (0–14) in their estimations. In this case, all demographic coefficients are interpreted as a comparison with this base group. The most remarkable point that needs to be highlighted in Lindh and Malmberg (2000) is that while the coefficient on the share of 65–74 age cohort variable turns to positive (implying this age cohort is inflationary), that of 75+ cohort becomes negative (deflationary) again, in line with our results.

14. In the Appendix Figure A1, we present the age cohort effects calculated from the robustness analysis for the full sample of countries. The figure reveals that while there is variation between the estimated effects, models almost unanimously determine the inflationary and deflationary cohorts. Moreover, the range of effects from different models can be interpreted as a sort of confidence interval for estimated effects of the demography.