Impact of Demographic Changes on Inflation and the Macroeconomy

Yoon, Jong-Won; Kim, Jinill; Lee, Jungjin Article Impact of Demographic Changes on Inflation and the Macroeconomy KDI Journal of Economic Policy Provided in Cooperation with: Korea Development Institute (KDI), Sejong Suggested Citation: Yoon, Jong-Won; Kim, Jinill; Lee, Jungjin (2018) : Impact of Demographic Changes on Inflation and the Macroeconomy, KDI Journal of Economic Policy, ISSN 2586-4130, Korea Development Institute (KDI), Sejong, Vol. 40, Iss. 1, pp. 1-30, https://doi.org/10.23895/kdijep.2018.40.1.1 This Version is available at: https://hdl.handle.net/10419/200817 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-sa/4.0/ INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 KDI Journal of Economic Policy 2018, 40(1): 1 – 30 http://dx.doi.org/10.23895/kdijep.2018.40.1.1 1 Impact of Demographic Changes on Inflation and the Macroeconomy † By J ONG - WON Y OON , J INILL K IM AND J UNGJIN L EE * Ongoing demographic changes have brought about a substantial shift in the size and age composition of the population, which are having a significant impact on the global economy. Despite potentially grave consequences, demographic changes usually do not take center stage in many macroeconomic policy discussions or debates. This paper illustrates how demographic variables move over time and analyzes how they influence macroeconomic variables such as economic growth, inflation, savings and investment, and fiscal balances, from an empirical perspective. Based on empirical findings—particularly regarding inflation—we discuss their implications on macroeconomic policies, including monetary policy. We also highlight the need to consider the interactions between population dynamics and macroeconomic variables in macroeconomic policy decisions. Key Word: Demographic Changes, Population Aging, Inflation, Macroeconomic Impact, Savings and Investment, Monetary Policy, Fiscal Policy JEL Code: J11, E31, E21 I. Introduction emographic change is one of the most important determinants of the future economic and social landscape. Many researchers have looked into how changes in the size and composition of an economy’s population influence macroeconomic outcomes. The channels through which demographic changes affect an economy typically include savings and investment behaviors, labor market decisions, and aggregate demand and supply responses. In the medium to * Yoon: Ambassador of the Republic of Korea to the OECD (e-mail: [email protected]); Kim: (Corresponding Author) Professor, Korea University (e-mail: jinillki[email protected]); Lee: Research Officer, International Monetary Fund (e-mail: [email protected]). * Received: 2017. 12. 28 * Referee Process Started: 2018. 1. 3 * Referee Reports Completed: 2018. 2. 23 † An initial draft was written while the three authors were working at the International Monetary Fund—as Executive Director, Visiting Scholar, and Research Officer, respectively—and was published as IMF Working Paper WP/14/210. Comments from various IMF Departments and Offices of Executive Directors as well as discussants at conferences are gratefully acknowledged. D INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 2 KDI Journal of Economic Policy FEBRUARY 2018 long term, both changes in the labor supply and changes in productivity—either viewed as exogenous or caused by demographic changes—could significantly alter an economy’s aggregate supply and thereby economic growth, as demographic changes affect the amount and combination by which its factor inputs are utilized. Over the short term, demographic transitions are likely to affect aggregate demand given that the amount of consumption and investment would depend critically on structural changes in the population’s age-earnings profiles. This paper intends to analyze the macroeconomic effects of demographic changes from an empirical perspective and to discuss their policy implications— particularly regarding inflation. Effects of demographic changes would depend on the extent of the anticipation of the demographic changes, nominal and real friction, institutional aspects, and behavioral responses. For example, aggregate supply or demand responses may be more flexible when demographic changes are fully anticipated in advance. Macroeconomic dynamics would also be based on the specific types of friction assumed to that are built into a model. In an economy with significant bottlenecks to deter real or nominal adjustments, aggregate supply responses are more likely to lag aggregate demand responses, leading to slower output and price adjustments from the supply side. We attempt to identify the impact of demographic changes on inflation and the macroeconomy using two types of proxies to capture demographic changes. Changes in the total size of the population are captured by its growth rate. With regard to the composition of the population, multiple measures have been proposed to reflect the degree of population aging, such as the percentages of the workingage and elderly in the population, dependency ratios, and life expectancy. We follow earlier empirical work based on these proxies and identify empirical evidence on the impact of demographic changes on economic growth, savings and investment, the external current account balance, and the fiscal balance. Monetary aspects of economic outcomes have received less attention in analyses of demographic changes; here, we pay particular attention to how inflation behavior is affected by demographic changes. This paper proceeds as follows. Section 2 describes a number of stylized facts pertaining to the driving forces of demographic changes and their projections into the near future, including fertility and mortality ratios, population growth, and the shares of the working-age and elderly in the population. Section 3 provides a brief review of the related literature, covering both theoretical and empirical discussions of the impact of demographic changes on macroeconomic variables, including inflation. In Section 4, we elaborate on the data, methodology, and empirical findings with regard to inflation and the macroeconomic impact of demographic changes. The final section concludes the paper and offers some discussion on policy implications. II. Description of Demographic Changes The world is about to experience a drastic shift in the size and composition of the population. Such demographic changes have already begun in some countries, INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 VOL. 40 NO. 1 Impact of Demographic Changes on Inflation and the Macroeconomy 3 including Japan, and will become conspicuous for many other countries in the coming decades. Two fundamental driving forces that underlie such demographic changes are related to birth and death, i.e., fertility and mortality. 1 According to work published by the United Nations (United Nations 2014), the total fertility rate was around 5 on average around the world in the 1960s. This number has decreased consistently over the last fifty years and is currently around 2.5. It is projected to settle just above 2 by the end of the 21 st century. 2 There is, however, a significant difference between more developed areas and less developed regions, as illustrated in Figure 1. The fertility rate was as high as about 6 around 1960 in less developed regions, and in such regions the fertility rate is currently higher than the world average. Even in the 1950s, the fertility rate in more developed areas was less than 3 and currently; it has remained below 2 for nearly thirty years, since approximately 1985. Over the long term, the United Nations projects this to move back up to around 2. Figure 2 provides information about country-wide total fertility rates for several countries. The fertility rate for five industrialized countries (the US, the UK, France, Germany, and Japan) remained between 2 and 4 in the 1950s and 60s and has fluctuated around 2 from the 1970s onward. However, in Korea in the 1950s through to the 1970s, the fertility rate exceeded 4 before taking a rapid downward trajectory afterward. 3 It dropped to less than 2 in the 1990s before stabilizing at F IGURE 1. T OTAL F ERTILITY R ATE (C HILDREN PER W OMAN ) Source: UN Population Prospects, 2012 revision. 1 While past variations in birth/death rates or immigration factors may also trigger demographic changes, they were not included in the description given their relatively weak significance. 2 Our assessments are based solely on baseline projections according to the United Nations (2014). Demographic trends could change depending on various policy efforts, such as those affecting immigration. 3 Japan and Korea were emphasized based on their rapid population aging and lowest fertility levels. China, the country with the largest population in the world, has also been experiencing significant demographic changes, similar to those of Korea, during the last few decades, as summarized in Figure A1. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 4 KDI Journal of Economic Policy FEBRUARY 2018 approximately 2 since then. In particular, Korea’s fertility rate has remained significantly below 1.5 in the last couple of decades and declined recently to about 1.2, one of the lowest rates in the world. Besides the decrease in the fertility rate, mortality has been another factor affecting recent demographic changes. Figure 3 captures the change in mortality by life expectancy as averaged over a cohort group born each year. The world-average F IGURE 2. T OTAL F ERTILITY BY M AJOR E CONOMIES (C HILDREN PER W OMAN ) Source: UN Population Prospects, 2012 revision. F IGURE 3. L IFE E XPECTANCY (Y EARS AT B IRTH ) Source: UN Population Prospects, 2012 revision. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 VOL. 40 NO. 1 Impact of Demographic Changes on Inflation and the Macroeconomy 5 life expectancy of someone who was born in 1955 is close to 50 years, while life expectancy for more developed regions is significantly above 60 years. The life expectancy increases as we move to later cohorts, as one would expect. The increase in life expectancy, together with the decrease in the fertility rate as shown in Figures 1 and 2, caused both a change in the size of the world population and an aging phenomenon in the composition of the population. The demographic consequences brought about by the above drivers include changes in the size and the composition of the population. Elevated fertility rates in the 1950s and 60s—combined with an increase in life expectancy—caused the population to grow, and the growth rate picked up as well in more developed countries. Figure 4 shows that the growth rate of the total population has been following a decreasing trend since then. Though the population growth rate will remain in the positive range for the world as a whole according to United Nations projections, the total population growth for the OECD in total is expected to enter negative territory around 2050. In particular, Figure 4 indicates that the total population began to decline in Japan from 2009, and this occurred in Germany from the mid-2000s with Korea expected to follow suit from the mid-2030s. Such declines in the population size could have disproportionate ramifications on the macroeconomy. Having as much influence on macroeconomic dynamics as the size of population is the composition of the population. Figure 5 displays changes in the share of the working-age population relative to the total population. High fertility rates in the 1950s and 60s were in the background of an increasing trend in the working-age share of the total population in OECD countries until shortly after 2000. Since then, a decrease in fertility and an increase in longevity have caused the working-age population share to decline steadily. We can observe the turnaround in the trend of the working age population share in the recent decade, which divides the rising F IGURE 4. T OTAL P OPULATION G ROWTH (P ERCENT ) Source: UN Population Prospects, 2012 revision. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 6 KDI Journal of Economic Policy FEBRUARY 2018 F IGURE 5. W ORKING - AGE P OPULATION S HARE OF THE T OTAL P OPULATION (P ERCENT ) Source: UN Population Prospects, 2012 revision. trend until the 1990s and the declining trend from about the 2010s. The declines in working-age population share are particularly rapid in Japan and Korea, where the total fertility rates have declined very rapidly. Along with the working-age population share, the dependency ratio has received much attention in macroeconomics—especially in the public finance literature involving pension systems. As shown in Figure 6, the dependency ratio is almost a mirror image of the share of the working-age population. Around the turn of the century, the dependency ratio overall was close to 50%; this number for Korea was as low as 40%. The dependency ratio is projected to increase steadily over time— reaching about 100% for the case of Japan and Korea by 2100. The share of the working age population or the elderly dependency ratio indicates that a significant change in the population structure has been occurring since the 2000s which could have important economic implications with regard to the macroeconomy. 4 As a starting point for understanding the effects of demographic changes on macroeconomic outcomes, we can plot the relationship between demographic variables (elderly share, working-age share, and population growth) and macro variables (per capita real GDP growth, saving/GDP, investment/GDP, current account/GDP, budget balance/GDP, and inflation). If we draw scatter plots for pooled data (both cross-section and time-series)—as shown in Figure A2, A3, and A4—the relationship is not significant, except for government revenue and expenditure. This is not unexpected, as pooled data averages out over countries and over time. It is therefore imperative to conduct a panel analysis based on certain 4 The EU Aging Report is another source that covers demographic projections —up to the year 2060—where, for example, the dependency ratio in Germany converges to around 85% by then. UN projections suggest a further increase to around 90% by 2100. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 VOL. 40 NO. 1 Impact of Demographic Changes on Inflation and the Macroeconomy 7 F IGURE 6. D EPENDENCY R AT IOS F O R M AJOR E CONOMIES Source: UN Population Prospects, 2012 revision. countryor time-specific structures on the macroeconomic effects of demographic changes. III. Literature Review A proper analysis of the macroeconomic effects of demographic changes is crucial when exploring appropriate policy responses to minimize the adverse effects or unwanted distortions. Reflecting their grave consequences, there have been extensive studies analyzing various aspects of demographic changes which affect an economy, covering real, external, fiscal, and financial ramifications. There have been broadly two approaches which have been used to analyze the macroeconomic impact of demographic changes. The standard approach assumes constant age-specific behavior with respect to employment, earnings, consumption and savings and assesses the implications of demographic changes. While this approach is useful for capturing what are known as the accounting effects of demographic transitions, the outcomes could be misleading, as economic behaviors can be altered and institutional aspects can be adjusted. The other approach takes into account the behavioral, institutional, and global responses as well. This approach adds a measure of complexity in order to track various channels and their interactions. However, it allows relative richness in its analysis by including reactions to aging-induced price changes, international diversification, and policy changes. On the macroeconomics side, demographic issues have been most widely addressed in the context of economic growth. In the textbook treatment of growth theories, the growth rate of the population is considered to be exogenous and serves INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 8 KDI Journal of Economic Policy FEBRUARY 2018 as a starting point for growth in real activities. Both population growth and population aging are relevant when determining real interest rates and inflation as well. In particular, the dependency of the (equilibrium) real interest rate on population dynamics is contingent on how population dynamics are incorporated into the utility specification. In an infinite-horizon model with a growing household size, the real interest rate may or may not depend on the growth rate of the population.5 This ambiguity will be a source of difficulty when determining a desirable response by monetary policies in a world of changes in population growth in the medium to short term. Empirical evidence of the growth effect has been studied extensively.6 This includes such channels as lower labor inputs, a potential negative impact due to increasing tax and contribution burdens, savings and investment, and productivity. The demographic impact on aggregate real GDP is somewhat straightforward when the population is growing, declining or aging given the direct implication on the size of labor inputs, while its impact on per capita real GDP is less so, attracting attention for analysis. For example, Chapter 3 of the 2004 World Economic Outlook by Callen et al. (2004) found that per capita GDP growth is positively correlated with changes in the working age population share but is negatively correlated with changes in the elderly share. Based on the decomposition of real GDP growth into productivity and changes in labor input due to both population growth and aging, Choi et al. (2014) also shows that the impending demographic change in Korea has a negative impact on real GDP growth.7 However, Bloom, Cunning, and Fink (2010) find that population aging will tend to lower labor force participation and savings rates, raising concern about a slowing of economic growth, but behavioral responses (including greater female labor-force participation) and policy reforms (including an increase in the legal age of retirement) can mitigate the adverse economic consequences of an older population.8 Population growth affects other real variables as well. The influence of demographic variables has been investigated in the context of the following key economic variables, in addition to growth in real GDP per capita. These include savingsand investment-to-GDP ratios, the current account-to-GDP ratio, and the budget balance-to-GDP ratio. If the life-cycle hypothesis of savings is valid, consumption smoothing through the lifetime would indicate that people move from net borrowers in their youth to net savers in their working years and finally to dis5In the standard case when agents from different generations are treated equally regardless of the size of each generation to which one belongs, the real interest rate is independent of the population growth rate and increases with the rate of technology change and the rate of time preference; under the alternative assumption that the utility of each generation is weighted equally irrespective of its size (i.e., agents from different generations are treated differently), population growth will bring about a one-to-one increase in the real interest rate. See the textbook treatment in Romer (2012) for a more in-depth discussion of this point. 6For a recent reference pertaining to the relationship between demographic changes and economic development, see World Bank Group (2016). 7They decomposed real GDP growth into four components (labor productivity, employment rate, changes in the population age structure, and population growth) and found that, from the 2010s, the contribution of the population to Korea’s GDP growth has fallen to 0.4%p and the change in the age structure has become a negative component. 8Börsch-Supan, Härtl and Ludwig (2014)—based on an overlapping generations model with behavioral reactions—also show that while the negative growth effect from population aging in Europe can be compensated for by reforms and economic adaptation mechanisms, they may be offset by behavioral reactions. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 VOL. 40 NO. 1 Impact of Demographic Changes on Inflation and the Macroeconomy 15 TABLE 2—DEMOGRAPHIC IMPACT ON CURRENT ACCOUNT, SAVINGS, AND INVESTMENT OECD Japan CA/GDP (1) S/GDP (2) I/GDP (3) CA/GDP (4) S/GDP (5) I/GDP (6) Population Growth -0.397 [0.603] -0.776 [0.277] -0.185 [0.836] 2.050 [0.305] -7.740 [0.000]*** -10.113 [0.002]*** Share of 65 and over -0.372 [0.141] -0.942 [0.001]*** -0.486 [0.043]** -0.464 [0.199] 0.270 [0.217] 0.604 [0.239] Share of 15-64 -0.246 [0.163] 0.012 [0.951] 0.249 [0.219] 0.358 [0.339] 0.582 [0.085]* 0.122 [0.836] Life Expectancy 0.379 [0.180] 0.428 [0.019]** -0.210 [0.327] 0.826 [0.085]* -2.222 [0.000]*** -2.942 [0.000]*** Budget Balance/GDP 0.109 [0.215] 0.399 [0.000]*** 0.313 [0.000]*** 0.089 [0.311] 0.516 [0.000]*** 0.445 [0.013]** NFA/GDP 0.026 [0.009]*** 0.028 [0.000]*** 0.002 [0.652] 0.111 [0.059]* 0.018 [0.681] -0.088 [0.296] TOT change 0.110 [0.001]*** 0.063 [0.001]*** -0.049 [0.043]** 0.079 [0.000]*** 0.010 [0.564] -0.072 [0.017]** GDP Growth -0.106 [0.195] 0.180 [0.027]** 0.255 [0.000]*** 0.109 [0.043]** 0.066 [0.294] -0.047 [0.564] Openness 0.033 [0.105] 0.005 [0.754] -0.024 [0.209] 0.078 [0.317] 0.004 [0.948] -0.084 [0.462] Constant -9.447 [0.484] 2.229 [0.824] 31.270 [0.006]*** -85.597 [0.022]** 167.525 [0.000]*** 254.051 [0.000]*** Observations 1,163 1,121 1,163 43 43 43 Number of ifscode 30 29 30 R-squared 0.184 0.439 0.383 0.770 0.973 0.953 RMSE 3.157 2.889 2.834 0.763 0.741 1.170 OECD Japan CA/GDP (7) S/GDP (8) I/GDP (9) CA/GDP (10) S/GDP (11) I/GDP (12) Population Growth -0.654 [0.380] -0.876 [0.258] -0.021 [0.981] 1.681 [0.376] -8.125 [0.000]*** -10.213 [0.001]*** Old Dependency -0.162 [0.215] -0.560 [0.000]*** -0.332 [0.006]*** -0.423 [0.026]** -0.036 [0.813] 0.372 [0.172] Young Dependency 0.143 [0.080]* 0.019 [0.829] -0.121 [0.173] -0.110 [0.547] -0.291 [0.064]* -0.117 [0.680] Life Expectancy 0.448 [0.133] 0.368 [0.038]** -0.339 [0.148] 0.755 [0.087]* -2.341 [0.000]*** -3.013 [0.000]*** Budget Balance/GDP 0.115 [0.184] 0.398 [0.000]*** 0.306 [0.000]*** 0.088 [0.302] 0.525 [0.000]*** 0.459 [0.008]*** NFA/GDP 0.026 [0.009]*** 0.029 [0.000]*** 0.002 [0.566] 0.117 [0.032]** -0.002 [0.967] -0.117 [0.141] TOT change 0.108 [0.001]*** 0.063 [0.001]*** -0.048 [0.044]** 0.079 [0.000]*** 0.012 [0.466] -0.070 [0.015]** GDP Growth -0.109 [0.185] 0.180 [0.025]** 0.259 [0.000]*** 0.112 [0.037]** 0.068 [0.274] -0.048 [0.544] Openness 0.033 [0.109] 0.004 [0.811] -0.025 [0.208] 0.079 [0.302] 0.000 [0.993] -0.090 [0.417] Constant -36.980 [0.097]* 5.890 [0.672] 61.560 [0.002]*** -50.522 [0.170] 229.472 [0.000]*** 272.624 [0.000]*** Observations 1,163 1,121 1,163 43 43 43 Number of ifscode 30 29 30 R-squared 0.188 0.431 0.379 0.780 0.973 0.955 RMSE 3.149 2.909 2.844 0.745 0.739 1.141 Note: 1) Fixed-effect estimation for OECD and OLS for individual country regressions using annual data. 2) Young Dependency= (Ages 0-14) / (Ages 15-64); Old Dependency= (Ages 65 and over) / (Ages 15-64). 3) Pvalues based on robust t-statistics in brackets. * significant at 10%; ** significant at 5%; *** significant at 1%. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 16 KDI Journal of Economic Policy FEBRUARY 2018 TABLE 3—DEMOGRAPHIC IMPACT ON BUDGET BALANCE, REVENUE, AND EXPENDITURE PER GDP OECD Balance Revenue Expenditure (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Population Growth 1.771 [0.009]*** 1.472 [0.034]** 1.489 [0.030]** -3.533 [0.001]*** -1.489 [0.126] -1.703 [0.052]* -5.151 [0.000]*** -3.017 [0.023]** -3.282 [0.008]*** Share of 65 and over -0.288 [0.024]** -0.214 [0.126] -0.051 [0.779] 0.900 [0.000]*** 0.825 [0.000]*** 0.204 [0.469] 1.102 [0.000]*** 0.952 [0.000]*** 0.182 [0.571] Share of 15-64 -0.046 [0.722] 0.035 [0.792] 0.158 [0.340] 0.373 [0.005]*** 0.310 [0.039]** -0.108 [0.642] 0.366 [0.060]* 0.239 [0.277] -0.279 [0.362] Life Expectancy -0.184 [0.319] 0.685 [0.015]** 0.849 [0.010]** TOT Change 0.011 [0.604] 0.015 [0.474] 0.012 [0.550] 0.012 [0.560] 0.039 [0.015]** 0.029 [0.066]* 0.032 [0.051]* 0.024 [0.139] 0.001 [0.961] -0.012 [0.552] -0.005 [0.795] -0.015 [0.483] Openness -0.021 [0.028]** -0.006 [0.508] -0.012 [0.257] -0.006 [0.603] -0.007 [0.806] -0.075 [0.008]*** -0.068 [0.011]** -0.089 [0.001]*** 0.001 [0.981] -0.077 [0.008]*** -0.063 [0.024]** -0.089 [0.002]*** Constant -2.417 [0.001]*** 4.487 [0.568] -2.385 [0.772] 0.929 [0.920] 33.001 [0.000]*** -0.789 [0.923] 4.821 [0.641] -9.84 [0.292] 36.304 [0.000]*** -0.105 [0.993] 11.259 [0.432] -6.917 [0.610] Observations 1,338 1,338 1,338 1,338 1,193 1,193 1,193 1,193 1,193 1,193 1,193 1,193 Number of ifscode 30 30 30 30 30 30 30 30 30 30 30 30 R-squared 0.057 0.051 0.071 0.076 0.113 0.299 0.315 0.362 0.130 0.230 0.267 0.308 RMSE 3.202 3.214 3.182 3.173 3.399 3.021 2.988 2.885 4.489 4.226 4.124 4.011 Note: 1) Fixed-effect estimation for OECD and OLS for individual country regressions using annual data. 2) P-values based on robust t-statistics in brackets. * significant at 10%; ** significant at 5%; *** significant at 1%. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 VOL. 40 NO. 1 Impact of Demographic Changes on Inflation and the Macroeconomy 17 TABLE 3—DEMOGRAPHIC IMPACT ON BUDGET BALANCE, REVENUE, AND EXPENDITURE PER GDP (CONTINUED) Japan Balance Revenue Expenditure (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) Population Growth 1.979 [0.001]*** 1.857 [0.128] -5.381 [0.050]** -8.902 [0.000]*** -1.072 [0.358] -3.558 [0.057]* -10.881 [0.000]*** -2.929 [0.042]** 1.822 [0.307] Share of 65 and over -0.165 [0.012]** -0.006 [0.965] 0.892 [0.000]*** 0.939 [0.000]*** 0.847 [0.000]*** 1.156 [0.000]*** 1.104 [0.000]*** 0.853 [0.000]*** 0.264 [0.192] Share of 15-64 0.235 [0.208] 0.276 [0.201] 2.117 [0.000]*** 0.809 [0.000]*** 0.785 [0.000]*** 1.418 [0.000]*** 0.574 [0.000]*** 0.510 [0.000]*** -0.699 [0.037]** Life Expectancy -1.931 [0.000]*** -0.663 [0.029]** 1.267 [0.000]*** TOT Change -0.058 [0.203] -0.056 [0.220] -0.054 [0.219] 0.016 [0.616] -0.039 [0.482] -0.048 [0.043]** -0.049 [0.056]* -0.025 [0.293] 0.019 [0.734] 0.008 [0.849] 0.005 [0.898] -0.041 [0.295] Openness -0.250 [0.004]*** -0.163 [0.095]* -0.192 [0.060]* 0.289 [0.075]* -0.033 [0.638] -0.167 [0.004]*** -0.151 [0.004]*** 0.015 [0.879] 0.216 [0.012]** -0.004 [0.956] 0.042 [0.594] -0.275 [0.016]** Constant 0.514 [0.774] -14.021 [0.310] -19.244 [0.239] -12.109 [0.309] 21.026 [0.000]*** -47.738 [0.001]*** -44.724 [0.001]*** -42.273 [0.001]*** 20.511 [0.000]*** -33.717 [0.000]*** -25.48 [0.002]*** -30.164 [0.000]*** Observations 54 54 54 54 54 54 54 54 54 54 54 54 R-squared 0.412 0.419 0.431 0.649 0.740 0.886 0.888 0.898 0.839 0.904 0.912 0.934 RMSE 2.400 2.410 2.408 1.913 2.486 1.665 1.669 1.606 2.576 2.004 1.944 1.699 Note: 1) Fixed-effect estimation for OECD and OLS for individual country regressions using annual data. 2) P-values based on robust t-statistics in brackets. * significant at 10%; ** significant at 5%; *** significant at 1%. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 18 KDI Journal of Economic Policy FEBRUARY 2018 C. Inflation Impact As mentioned above, the demographic impact on real variables—summarized in Tables 1 to 3—has also been analyzed in previous studies. What has received much less attention is the demographic impact on inflation, which is ambiguous in theory given various conflicting channels. For example, population aging or shrinking will have multifarious demand-side effects due to changing consumption preferences, possibly leading to a reduction in aggregate demand in the economy and lower inflation. On the other hand, it would reduce the effective supply of labor in the economy, adding inflation pressures. As noted earlier, the demographic impact would depend on how changes in the population size and structure affect aggregate demand and supply, agents’ inflation expectations, and asset prices, which in turn depend on the extent of nominal and real friction, institutional aspects, and behavioral responses. Hence, it is difficult to determine from a theoretical perspective how various changes in demographics affect inflation, and it would ultimately be an empirical issue, to which Table 4 is devoted.13 This table is based on regressing inflation on demographic variables, as well as other relevant conditioning variables; the columns on the left display results for the OECD data and those on the right correspond to the Japanese case. To capture the deviation from the anticipated change in inflation and population changes, the two variables are detrended using a quadratic trend given that there is a slow-moving component in these series.14 As displayed in Column (1), population growth affects inflation positively, as a greater population implies more aggregate demand. This may be due to the fact that the aggregate supply adjustment could be slower than the aggregate demand adjustment in response to demographic shocks in the short or medium term.15 When the share of the elderly is added as an independent variable (Column 2), population growth continues to affect inflation positively and the influence of the elderly share is significantly negative. Conditional on population growth, the aging process will suppress inflation significantly. This is true when the share of those aged 15-64 is coupled with the elderly share (Columns 3 and 4) and when life expectancy is added as well (Column 5). Other conditioning variables used are the changes in terms of trade, GDP growth, M2 growth, and the change in the budget balance, all of which show very significant coefficients with the expected signs.16 13We attempted to estimate the impact of population growth and aging on housing prices, but were not produce to draw meaningful empirical evidence. This may be partly due to the intrinsic difficulties in estimating asset prices. See Terrones (2004), however, for an empirical analysis regarding this issue. Dent (2014) focuses on the influence of demographic changes on asset prices as well as aggregate consumption based on the size of the population cohort with the highest consumption capacity. 14Detrending would also avoid the possibility of a spurious regression due to non-stationary trend elements. The detrended time series can be interpreted as an unanticipated shock from the trend. 15If supply responses are as flexible as demand responses, there could be little impact on inflation. However, there may be other channels through which demographic shocks could impart deflationary pressures on the economy, including its impact through the wealth effect, due to changing asset prices and/or real exchange rate appreciation arising from changes in asset allocations. 16It would be desirable if the coefficients for the share of those aged 15-64 to be positive, which is not true in Table 4. However, if the share of the elderly and the share of those aged 15-64 could be replaced with the population sizes of the two groups, the two coefficients are estimated to have the desirable signs, though the outcomes would not be statistically significant. See the Table A4. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 VOL. 40 NO. 1 Impact of Demographic Changes on Inflation and the Macroeconomy 19 TABLE 4—DEMOGRAPHIC IMPACT ON INFLATION OECD Japan (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) Population Growth 0.339 [0.715] 0.524 [0.577] 0.549 [0.570] 0.317 [0.764] 6.689 [0.005]*** 6.363 [0.003]*** 6.708 [0.001]*** 6.725 [0.001]*** Share of 65 and over -0.176 [0.009]*** -0.125 [0.013]** -0.137 [0.006]*** -0.416 [0.008]*** -0.101 [0.394] -0.321 [0.082]* -0.300 [0.060]* -0.242 [0.227] Share of 15-64 -0.101 [0.226] -0.103 [0.233] -0.330 [0.037]** -0.476 [0.030]** -0.544 [0.008]*** -0.499 [0.026]** Life Expectancy 0.304 [0.043]** -0.092 [0.748] TOT Change -0.145 [0.005]*** -0.144 [0.005]*** -0.145 [0.005]*** -0.144 [0.005]*** -0.143 [0.005]*** -0.169 [0.016]** -0.174 [0.014]** -0.178 [0.013]** -0.148 [0.016]** -0.147 [0.016]** GDP Growth -0.750 [0.000]*** -0.795 [0.000]*** -0.799 [0.000]*** -0.802 [0.000]*** -0.784 [0.000]*** -0.246 [0.015]** -0.319 [0.033]** -0.517 [0.008]*** -0.431 [0.008]*** -0.452 [0.022]** M2 Growth 0.192 [0.000]*** 0.183. [0.000]*** 0.180 [0.001]*** 0.180 [0.001]*** 0.176 [0.000]*** 0.059 [0.118] 0.034 [0.379] 0.007 [0.869] -0.009 [0.826] -0.015 [0.751] Budget Balance Chg. 0.129 [0.051]* 0.153 [0.022]** 0.153 [0.033]** 0.158 [0.018]** 0.150 [0.022]** -0.105 [0.540] -0.086 [0.563] 0.006 [0.971] 0.040 [0.776] 0.059 [0.690] Constant -0.053 [0.910] 2.418 [0.060]* 8.443 [0.149] 8.739 [0.151] 4.132 [0.255] 0.074 [0.821] 1.870 [0.399] 37.962 [0.031]** 42.051 [0.010]** 45.446 [0.038]** Observations 1,167 1,167 1,167 1,167 1,167 53 53 53 53 53 Number of ifscode 30 30 30 30 30 R-squared 0.212 0.216 0.217 0.217 0.222 0.530 0.545 0.462 0.602 0.603 RMSE 5.235 5.227 5.223 5.223 5.209 2.077 2.066 2.246 1.954 1.973 Note: 1) Inflation and population growth are detrended using quadratic filter. 2) Fixed-effect estimation for OECD and OLS for individual country regressions using annual data. 3) P-values based on robust t-statistics in brackets. * significant at 10%; ** significant at 5%; *** significant at 1%. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 20 KDI Journal of Economic Policy FEBRUARY 2018 The columns on the right hand side of Table 4 are generated from the data on Japan. Population growth influences the inflation rate significantly positively in all regressions. The effect from population shares is not as strong as it is in the OECD data.17 Terms of trade and GDP growth are significant in the Japanese data as well, while the insignificant result for the money growth variable is puzzling.18 These results suggest that the ongoing demographic changes could have a significant deflationary impact in the years ahead, particularly on an economy experiencing a rapid decline and a significant aging of its population. Under such circumstances, the macroeconomic policy framework—including monetary and fiscal policies—must be revisited. This will be discussed in the concluding section. V. Conclusion: Policy Implications Demographic changes are among the most crucial long-term challenges that have a grave influence on the economy. Given the current fertility and mortality trends, the recent and coming decades will represent a watershed in demographic structures, in that we will observe a significant drop in population growth and the working-age population share and a rapid rise in the dependency ratio. Such demographic shifts have already accelerated in some countries, including Japan and Korea, and their impact on the economy may already be widespread, traversing economic growth, inflation, savings and investment, asset prices, and fiscal positions. Despite the expected grave consequences on the economy, in many macroeconomic policy discussions or debates, demographic changes do not usually take center stage. For example, most growth models assume that a population grows at a constant rate—sometimes zero for simplicity—and many business cycle models fix the size of the population when analyzing aggregate demand. We have analyzed how demographic variables move over time and how these variables influence inflation as well as real macroeconomic variables. By using a regression analysis, this paper found that population growth affects real economic variables in a negative manner, though the outcomes were insignificant in many instances. The influence of population dynamics on fiscal policy variables is rather mixed. On the inflation side, population growth affects the inflation rate positively, most likely through its influence on lower aggregate demand and the slow supply responses for which specific channels have yet to be examined. In this vein, the ongoing demographic changes—both shrinking and aging—could have a sizable deflationary impact in the coming years. These dynamics involving demographic changes would change the framework of 17The significance of population growth with regard to inflation regression on Japan, which is in stark contrast to that in the other OECD countries, may be due to the rapidly declining population. In addition to reducing aggregate demand, the declining population may have led to falling housing prices, which lowers aggregate demand even further. 18Money growth with a lag could be included in the regression to alleviate the endogeneity problem. However, the inclusion of lagged variables did not change the result significantly. It is possible to use short-term nominal interest rates instead of money growth, but is also well known that short-term rates respond to various macroeconomic variables, notably inflation and the output gap. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 VOL. 40 NO. 1 Impact of Demographic Changes on Inflation and the Macroeconomy 21 macroeconomic policies. Taking the discussion of monetary policy as an example, one of the most popular ways to conduct and/or analyze monetary policy is via a reaction function that relates the policy short-term rate to a few variables that capture the state of the economy. The most well known is the rule set forth by John Taylor, under which the setting of short-term interest rates responds to inflation and the output gap as well as the equilibrium real interest rate. Population dynamics could affect the independent variables in this reaction function. First, the equilibrium real interest rate can depend on both the growth rate of the population and the age composition of the population. It is, furthermore, challenging to nail down this relationship. The dependence on population growth is related to how the society treats different generations when there is population growth. Regarding the population composition, different assumptions with reference to the demand structure in an aging society would yield different implications pertaining to the real interest rate. Second, the concept of the output gap depends on how the potential output is measured, which clearly depends on the population dynamics. Especially when the age structure changes over time, the potential output will depend critically on the assumptions regarding the labor participation rate and retirement age.19 Any disagreement on the potential output would cause different policy prescriptions with regard to the short-term policy rate. Last but not least, the direction of the policy rate depends on whether the actual inflation rate is above or below its target rate. In principle, the target rate can be set independently of any other variables in the economy if we follow the monetarist doctrine.20 However, when population dynamics affect other target variables— such as the equilibrium real rate and the level of potential output—any misspecification in other parts of the economy would amount to unwanted inflation dynamics, and the inflation rate may not converge to its target as policymakers intend.21 If demographic changes bring significant deflationary pressures, an original inflation target will become unrealistic, and sticking to the target will require the central bank to continue inflating its balance sheet, which will soon become unsustainable. For this reason, the potential demographic impact on inflation must be taken into account properly in monetary policy decisions.22 We have just taken monetary policy as an example of how understanding the impact of population dynamics could inform policymakers, but there are many other examples as well. The issue of how to implement fiscal policy is especially important when investigating the interaction with population dynamics. Fiscal policy tools are sometimes geared to specific groups and population dynamics 19Measuring the potential output could become complicated since, as implied by the term 'demographic dividend', productivity may depend on demographic changes instead of moving exogenously. 20That is, whether or not aging exerts downward pressure on prices may be irrelevant as a central bank committed to do whatever it takes should remain capable of anchoring inflation expectations at the target. Anderson, Botman, and Hunt (2014) attributed this monetarist doctrine to the lack of theoretical and empirical research on the relationship between demographics and inflation. 21Rachel and Smith (2015) argued that global real interest rates have fallen by nearly 450 basis points over the past 30 years, referring to demographic forces as among the most important. 22One possible approach is to consider the impact of demographic variables indirectly via a Taylor rule through other variables, such as the real interest rate, output gap or inflation expectations. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 22 KDI Journal of Economic Policy FEBRUARY 2018 would affect fiscal policy directly, while monetary policy more or less affects economic agents without particular regard to individual population groups.23 In this paper, we have examined how population dynamics influence various macroeconomic variables—including the inflation rate—from an empirical perspective. Our empirical results would help researchers form their ideas on how demographic changes could affect inflation or deflation and the macroeconomy. However, population dynamics and their interactions with macroeconomic variables are multifarious, with the macroeconomic impact being different depending on the particular stage of the demographic transition. For this reason, underlying theories about the relationships between demographics and macroeconomic variables and their link with the empirical results, including specific channels through which demographic changes affect inflation and the macroeconomy, were not suggested in this paper. To recap, it would be desirable, therefore, for further research, if the relationship could be analyzed from a theoretical perspective using a macroeconomic model. As alluded to in the preceding paragraphs, the interaction between population dynamics and variables involving macroeconomic policy need be incorporated into such a model based on a certain microeconomic foundation. Additional empirical study would also bring a better understanding of the channels through which demographic changes affect inflation and the macroeconomy and of the macroeconomic consequences. From a policy perspective, it remains crucial to implement appropriate policies without delay through a combination of sound monetary policy, fiscal consolidation, and bold structural reforms to mitigate the perverse effects of the ongoing drastic demographic changes. In addition to advanced countries which are already in the demographic watershed, developing countries facing the opposite demographic challenges with high fertility and younger populations should consider the potential impact when the demographic trends ultimately reverse and make intertemporally consistent policy choices. 23See Park (2012) for an example. INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 VOL. 40 NO. 1 Impact of Demographic Changes on Inflation and the Macroeconomy 23 APPENDIX TABLE A1—SUMMARY OF KEY VARIABLES Variable Obs Mean Std. Dev. Min Max Population Growth 1,354 0.735 0.631 -0.482 3.172 Population Growth (detrended) 1,354 -0.017 0.300 -1.194 1.103 Share of 15-64 1,354 65.299 3.589 49.549 72.942 Share of 65 and over 1,354 12.672 3.769 3.316 25.078 Life Expectancy 1,354 74.992 4.804 47.575 83.580 Old Dependency Ratio 1,354 19.285 5.511 5.956 40.532 Young Dependency Ration 1,354 34.368 12.756 19.904 94.425 Per Capita Growth 1,255 2.343 3.425 -14.613 12.748 CA/GDP 1,329 -0.532 5.004 -28.383 21.266 Savings/GDP 1,295 21.990 5.855 -4.245 40.445 Investment/GDP 1,335 23.561 4.817 10.864 41.170 Budget Balance/GDP 1,354 -2.485 4.222 -25.130 16.652 Revenue/GDP 1,209 30.166 9.534 9.461 55.731 Expenditure/GDP 1,209 32.835 10.112 9.714 58.459 Inflation 1,342 7.323 11.369 -4.480 188.005 Inflation (detrended) 1,342 0.179 7.569 -23.281 150.243 TABLE A2—LIST OF SAMPLE OECD COUNTRIES United States Norway Spain United Kingdom Sweden Turkey Austria Switzerland Australia Belgium Canada New Zealand Denmark Japan Mexico France Finland Korea Germany Greece Czech Republic Italy Iceland Slovak Republic Luxembourg Ireland Hungary Netherlands Portugal Poland INSIDabcdef_:MS_0001MS_0001 INSIDabc def_:MS_0001MS_0001 24 KDI Journal of Economic Policy FEBRUARY 2018 TABLE A3—VARIABLE DEFINITIONS AND SOURCES Demography variables from UN population prospects (future projections based on the 2012 revision) Population Growth, detrended: Population growth after quadratic detrending, where population growth is subtracted by a fitted value determined by regressing it on constant, trend, and trend squared. Share of the Working Age Population: Share of those aged between 15 and 64 years out of the total population. Share of the Elderly Population: Share of those aged over 64 out of the total population. Total Dependency Ratio: Number of persons in the population that are not of working age as a percentage of the working age population. Old Dependency Ratio: Number of persons in the population above the age of 64 as a percentage of the working age population. Young Dependency: Number of persons in the population below the age of 15 as a percentage of the working age population. Fertility Rate: Average number of child births per woman. Life Expectancy at Birth: Average number of years a person born can expect to live given the prevailing mortality rates in that area and period. Variables from World Economic Outlook (WEO) and/or World Development Indicator (WDI) databases Current Account/GDP, Savings/GDP, and Investment/GDP are from WEO and extended by WDI. Inflation rate is based on the CPI and is constructed from WDI and supplemented by WEO. Inflation rate, detrended: Inflation rate after quadratic detrending, where inflation rate is subtracted by a fitted value determined by regressing it on constant, trend, and trend squared. Openness: Sum of exports and imports of goods and services divided by the nominal GDP. It is based on WDI and extended using WEO. Budget Balance/GDP: Central government budget balance divided by the nominal GDP. Government Revenue, Expenditure, and Balance divided by GDP are based on the WDI database and extended using WEO. Budget Balance Change: Change in the budget balance per GDP over the previous period. Secondary School Enrollment: Total is the total enrollment in secondary education, regardless of age, expressed as a percentage of the population of official secondary education age. This variable is from the WDI database. TOT Change: Log difference of goods-and-services terms of trade index from the previous period. Data are based on WEO values. GDP growth: Growth rate of the real GDP from the WDI database. Variables from Other Sources Per Capita GDP growth: Growth of real GDP per capita in PPP terms. The underlying PPP GDP variable is from the PENN World Table version 7.1. NFA/GDP: Net foreign assets divided by GDP is from the updated and extended version of the External Wealth of Nations dataset constructed by Lane and Milesi-Ferretti (2007). M2 Growth: Growth rate of money and quasi money. M2 data are from WDI and are extended using values from the International Financial Statistics (IFS) database.