Aging and inequality: The link and transmission mechanisms

• DOI: http://doi.org/10.1111/rode.12394
• Published date: 01 August 2018
• Author: Zhi Luo,Xun Zhang,Guanghua Wan,Chen Wang
• Date: 01 August 2018

SPECIAL ISSUE ARTICLE

Aging and inequality: The link and transmission

mechanisms

Zhi Luo

3

|

Guanghua Wan

2

|

Chen Wang

1,5

|

Xun Zhang

4,6

1

Shanghai University of Finance and

Economics, Shanghai, P. R. China

2

Institute of World Economy, Fudan

University, Shanghai, P. R. China

3

Economic Development Research

Center, Wuhan University, Wuhan,

Hubei, P. R. China

4

Beijing Normal University, Beijing,

P. R. China

5

Leiden University, The Netherlands

6

Shanghai Finance Institute, Shanghai,

P. R. China

Correspondence

Xun Zhang, Department of Financial

Statistics, School of Statistics, Beijing

Normal University, No. 19,

XinJieKouWai St., HaiDian District,

Beijing 100875, P. R. China.

Email: zhangxun@bnu.edu.cn

Funding Information

This paper is funded by the Bairen Program

of Yunnan Province and the NSF Projects

7113304, 71373186, 71603026, 71703088,

and 71773084 of the National Natural

Science Foundation of China. It is also

funded by Projects 15ZDA027 and

16ZDA006 of the National Social Science

Foundation of China, Shanghai Pujiang

Program (Project 17PJC045), Projects

2015M580055, and 2016T90048 of the

China Postdoctoral Science Foundation, and

Youth Scholars Program of Beijing Normal

University.

[Correction added on 27 June 2018, after

online publication: The order of the author

names has been updated in this current

version.]

Abstract

There exists a shortage of rigorous empirical analyses that

focus on the aging-to-inequality transmission mechanisms

although both developed and some developing countries

have been confronted with the challenge of population

aging. Using cross-country panel data covering the period

of 1975 to 2015, this paper contributes to the literature

by directly modeling the relationship between aging and

inequality and exploring the transmission mechanisms.

Our estimation results show that (1) Aging worsens

income distribution; (2) This adverse impact is attributa-

ble to its negative correlation with the share of labor

income that in general is more equally distributed than

capital income; (3) The labor share-reducing effect of

aging can be further attributed to the significant and neg-

ative impact of aging on both labor input or supply and

wage or labor productivity; and (4) Our findings are

robust to changes in model specifications, use of different

indicators of aging, different inequality and labor share

data sources.

DOI: 10.1111/rode.12394

Rev Dev Econ. 2018;22:885–903. wileyonlinelibrary.com/journal/rode ©2018 John Wiley & Sons Ltd

|

885

1

|

INTRODUCTION

Population aging is taking place in many countries in the world as a result of significant improve-

ment in longevity and declining fertility. In 2014, 868 million people were at the age of 60 or

older—12 percent of the global population. By 2030, this number is expected to increase to 1.2

billion—16 percent of the world population (OECD, 2015). Both industrialized nations such as the

United States and Japan and developing economies like China have been confronted with the chal-

lenge of a grey or greying society. In particular, China is home to 130 million people who are 65

years of age or older and has been aging rather quickly (World Bank, 2016).

Population aging can lead to several adverse socioeconomic consequences. First, as noted by

Bloom, Canning, and Fink (2010), aging implies lower labor supply and less saving, thereby caus-

ing slower economic growth. This is more challenging for developing countries such as China

when the population becomes “old”before getting rich. Second, aging generates demographic

stress, because it means a high dependency ratio and low standard of living for the noneconomi-

cally active, particularly the elderly (Goldin, 2016). Third, aging causes significant fiscal press ure

(OECD, 2007). For example, annual growth in per capita health spending averaged 4.7 percent in

Asia during 2010 to 2014, which is higher than the corresponding GDP growth rate averaged at

4.0 percent. Meanwhile, 61.6 percent of total health spending is funded from government sources

in Asia (OECD, 2016). As another example, the Greek sovereign debt crisis is known to be partly

caused by aging and big welfare spending.

Another consequence of aging lies in its potential adverse impacts on income distribution (Dea-

ton & Paxson, 1994). Razin, Sadka, and Swagel (2002) argued that aging could lead to lower taxes

and less generous social transfers, worsening income distribution. This causal effect could take

several years to realize as government policy changes often take time. In contrast, the elderly are

mostly retirees and they are usually located at the lower part of the income ladder. Thus, an

increase in the population share of the elderly naturally means a rise in income inequality (Lindert,

1978; Repetto, 1978). This causal effect is instant as retirees usually begin to receive pension upon

retirement. In passing, it is noted that Deaton and Paxson (1998) examined the effect of aging on

the dispersion of life-cycle income of a representative individual, not inter-person or inter-house-

hold inequality.

Empirical findings on the aging–inequality link are mixed. A number of studies concluded with

a positive correlation between aging and income inequality. They include Lam and Levison (1992)

for the United States, Deaton and Paxson (1994) for the United Kingdom and Taiwan Province of

China, Jantti (1997) for Canada, the Netherlands and Sweden, Ohtake and Saito (1998) for Japan,

Cameron (2000) for Java of Indonesia and Zhong (2011) for China. Conversely, some scholars

found that the impact of aging on income distribution is limited. These include Jenkins (1995),

Tsakloglou (1997), Qu and Zhao (2008), and Liu (2014). For instance, rises in the population

share of the elderly only accounted for 2.36 percent of the changes in income inequality in Ger-

many from 1999/2000 to 2005/2006 (Biewen & Juhasz, 2012). Finally, aging was found to reduce

inequality in Taiwan Province of China (Chu & Jiang, 1997) and Australia (Barrett, Crossley, &

Worswick, 2000).

A major gap in the literature is the lack of rigorous empirical investigations into mechanisms

that underlie the aging–inequality relationship. Clearly, this kind of investigation is vital for policy-

making by governments and other stockholders. Also, previous studies that focus on the impacts

of aging on inequality mostly employ conventional inequality decomposition frameworks—see

Shorrocks and Wan (2005) and references therein. They usually require the use of unit record data

at the individual or household level and cannot control for fundamental macro determinants of

886

|

LUO ET AL.