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Projected Economic Growth in China and India:

The Role of Demographic Change*

Rod Tyers, Jane Golley and Iain Bain

College of Business and Economics

Australian National University

November 2006

Key words:

China, India, demographic change and economic growth

JEL codes:

C68, E27, F43, J11, O53

Presentated at the conference on Shaping the Future: Prospects for Asia's Long Term Development over the Next Two Decades, 11-12 December, 2006, ADB Thailand Resident

Mission, Bangkok.

* Funding for the research described in this paper is from Australian Research Council Discovery Grant No. DP0557889. Thanks are due to Siew Ean Khoo and Ming Ming Chan for assistance demographics, and to Terrie Walmsley for technical help with the GTAP Database and the migration data and to David Canning, Fan Zhai and Dominique van der Mensbrugghe to valued comments on an earlier draft. 2

Projected Economic Growth in China and India:

The Role of Demographic Change*

Abstract:

Within the next decade, China's labour force will begin to contract, while that of India will expand faster than its population. Relative labour abundance will bring higher capital returns and an increasing share of global FDI to India. Yet China may relax its One Child Policy further and India's fertility could follow the pattern elsewhere in Asia and decline faster than expected. These linkages are explored using a global demographic sub-model that is integrated with an adaptation of the GTAP-Dynamic global economic model in which regional households are disaggregated by age and gender. Even with a two-child-policy, China's growth is projected to slow in future with India becoming the fastest growing economy in the world on the strength of its continued population expansion. While GDP depends positively on fertility in both countries, the price of more GDP growth in terms of lost per capita income is higher in

India than in China, a result that depends critically on India's initially higher fertility, its higher

youth dependency and the age-gender pattern of its participation rates. India therefore has considerably more to gain, at least in per capita terms, from further reducing its fertility.

1. Introduction

As the third decade of Chinese economic reforms draws to an end, its remarkable growth performance appears almost unstoppable. Between 1995 and 2005, GDP and per capita GDP grew at average annual rates of 8.8% and 8.0% respectively. The central government's ambition to raise the level of GDP in 2020 to four times the level in 2000, which requires an annual growth rate of 7.2%, seems well within reach. India's economic reforms began in earnest in the early 1990s and, like China's, signal a systemic shift towards an increasingly market-driven economy. Despite the fact that India's average annual GDP growth performance of 6% in the last decade is enviable by virtually any standards, Indian authorities have increased their growth target to 8%, indicating some degree of disappointment with the growth rates achieved in the first decade of reforms (Ahluwalia, 2002). In both countries, there is no question that achieving high and sustainable rates of GDP growth is a major policy objective. In China, a potential threat to GDP growth in the future is low fertility and the associated ageing of the population. The United Nations (2005) projects a rise in the proportion of over

60s in China's population from 10% in 2000 to 20% in 2025, and further to 31% by 2050.

Meanwhile, the proportion of the population of working age (15-59 years) is predicted to fall from 65% in 2000 to 62% in 2025 and 53% in 2050. By 2020, the growth of the working age population will be negative, suggesting that GDP growth will suffer as a consequence. India, by contrast, began the millennium with a much younger population than China. Its aged population was only 7.5% of the total population in 2000 and is predicted to rise to 12% in 2025 and 21% in 2050. The share of India's working age population will rise from 58% in 2000 to a peak of

364% in 2035. India's relatively youthful population and high fertility rate suggest that its

"demographic dividend" could continue for another two decades at least, in stark contrast with

China's.

The demographic transition to slower population growth and the associated ageing of China's population have been profoundly affected by the One Child Policy. Yet fertility rates would have declined anyway, affected as they have been in China's Asian neighbours by urbanisation, female education, increased labour force participation rates and the improved life- expectancy of new-born children. Indeed, while the associated fall in fertility has not been as spectacular as China's, India's fertility rates have also declined steadily since the 1970s. Critically, however, the different age structures of the world's two most populous countries has elicited different population policy responses: in China, with a transition to a declining and ageing population in prospect, there is now public discussion of more relaxed family planning policies, while in India, with a rapidly growing population and high youth dependency rates, the focus continues to be on fertility reduction (Xinhuanet, 2005; Padmadas et al., 2005). In this paper the linkages between demographic change and economic growth in China and India are explored using a new global demographic sub-model that is integrated with an adaptation of the GTAP-Dynamic global economic model in which regional households are disaggregated by age and gender. The paper is organised as follows. Section 2 discusses the theoretical and practical links between demographic change and economic growth in China and India. In Section 3 the demographic sub-model and the GTAP-Dynamic economic model are described. The composite model provides a means to examine quantitatively the interactions between demographic change and economic performance. Section 4 constructs a baseline scenario for the global economy through to 2030, while Section 5 presents alternative fertility scenarios for the two nations. In China, a transition to a two-child-policy is considered, while in India, the alternative scenario explores the possibility that fertility could decline more quickly than in the baseline. Simply put, while more rapid population growth in China might ultimately ease some of the burden of an ageing population and contribute to higher rates of growth in GDP, it is shown to be contradictory to the goal of delivering improvements in real per capita income. For India, the benefits of reduced fertility, in terms of real per capita income, are shown to be substantial. Conclusions are offered in Section 6. 4

2. Demographic Change and Economic Growth

At a basic level, faster population growth should yield stronger GDP growth, but lower per capita income growth. This expectation stems from the standard Solow-Swan model of growth that realistically incorporates diminishing factor returns, but less realistically assumes constant labour participation rates across an ageless population. This ensures that faster population growth generates faster-growing labour forces, which yield steady states with lower levels of capital per worker and hence lower per capita income. 1

In reality, changing populations have

changing age distributions, and this alters average labour force participation rates and youth and aged dependency ratios. In a developing country with large numbers of dependent children, a fall in fertility not only slows population growth, it also reduces the total dependency ratio and raises the proportion of the working aged population. Income per capita is boosted by the fall in dependency so that the basic Solow-Swan result is strengthened, giving rise to a "demographic dividend". 2 As Bloom and Canning (2005a) point out, however, the per capita income boost is not an automatic consequence of changes in the age distribution, but instead depends on the wide range of economic policies that affect labour market flexibility, including education, child- care, pension and immigration policies. In addition to these supply-side effects of demographic change on growth, changes in age distributions also have demand-side implications. Lower fertility raises the average age of the population, changing the scale and product composition of final consumption to more strongly reflect the preferences of adults and the aged. More importantly, the associated rise in the proportion of the working aged population tends to raise the share of households' disposable incomes devoted to saving. In a developing country, following a fertility decline, this tends to increase the average saving rate. If investment is also raised, the demographic dividend is further bolstered. Higgins (1998) notes that the demographic "centre of gravity" for investment demand occurs earlier in the age distribution than for savings supply, because the former is most closely related to the youth share in the population - via its connection to labour force growth - while the latter is most closely related to the share of mature adults - via their retirement needs. The divergence between these two centres of gravity means that the effect of the demographic transition on savings and investment depends on the country's openness to capital flows. The more open is the capital account the more investment and capital growth depends on the economy's comparative performance and not, narrowly, on its saving behaviour. Thus, as China 1

See Solow (1956) and Swan (1956), and the detailed analytical review offered by Pitchford (1974: Ch.4).

2

See Bloom and Williamson (1998) for a generic discussion of the demographic dividend in developing countries,

Bloom and Canning (2003 and 2005a) for recent reviews, Bloom et al. (2000) for a detailed examination of the

implications for Asia, and Cai and Wang (2005) for implications for China.

5and India trend toward more open capital accounts, the effects of ageing on their saving rates are

likely to diminish. 3 Indeed, in affecting growth performance, the supply-side effects of demographic change, acting as they do through the size of the labour force, tend to dominate demand side changes in average saving rates and in the product composition of consumption. 4 Complexities arise, however, when the interdependence of fertility, longevity, labour force participation and saving rates are fully accounted for. In one theoretical study, Bloom et al. (2005) predict that improvements in health and longevity will result in rising natural retirement ages (increased aged labour force participation) but declining average saving rates, the latter occurring because longer working lives reduce the need to save for retirement in each successive age cohort. However, this may not be observed in practice, particularly if policy regimes prevent or discourage later retirement, in which case increased longevity will require higher average saving rates in order to finance a longer retirement period. Consider China, for example, where current retirement ages of 60 for men and 55 for women were set at a time when life expectancy was only 50 years, compared with over 70 years now. As longevity continues to rise, later retirement ages would be a simple way of expanding the proportion of workers and thereby reducing the burden placed on the fiscal system of a rapidly ageing population. 5 Much more complicated is the impact of alternative pension systems on retirement decisions and savings, since different measures to deal with pension-related budgetary pressures will have profoundly different effects. 6 Additional complexities include the link between labour force growth, capital returns and foreign investment. While the attraction of investment from abroad boosts GDP growth, the new capital returns are repatriated and the contribution to per capita income growth then depends on real wage changes. 7 Faster labour force growth necessarily slows real wage growth even while it attracts foreign investment. Also dependent on the growth path of real wages is the pattern of migration. Both India and China are substantial suppliers of (mainly skilled) migrants to the rest of the world. Growth due to boosted fertility, and its slower real wage growth path, would raise skilled emigration and reduce skill endowments in both. Finally, any labour-supply-driven acceleration of GDP growth tends to shift the terms of trade adversely by 3

The problems that arise in the closed capital markets that are common in developing countries are weak

intermediation and hence mal-distributed investment and a low level of embodied technical change. These are just

two of the reasons for the switch to openness that is under way in China and India. 4

See, for example, Tyers and Shi (2007).

5 Indeed, this recommendation was made in a World Bank report (1997). 6

Heller's (2006) recent review of Asian countries' preparedness for future population ageing suggests that both

China and India lag behind the more advanced but smaller Asian economies in the development of policy regimes

to cover pensions, health insurance and labour market change. See Golley and Tyers (2006) for details on China's

pension system reforms. 7

See Tyers and Golley (2006).

6raising output relative to consumption and exports relative to imports.

8

This also tends to weigh

down the growth of per capita income. While the integrated model of demography and economic growth to be presented in the next section does not activate all of these interactions, it offers scope to experiment with alternative assumptions about each. Fertility is obviously one of the key determinants of demographic change and, according to Padmadas et al. (2005), it is the main driving force of population change (in absolute terms) in both China and India. They also argue that fertility rates are the most uncertain component of population change in both countries, largely because of rising gender imbalances, changing social attitudes towards reproduction and family structure and the uncertain impacts of policy responses. 9 In China, while debates over the extent of fertility decline continue, it is widely accepted that by the turn of the century fertility rates had fallen to well below the replacement level of 2.1 births per woman. According to the National Bureau of Statistics, the total fertility rate in 2000 was 1.22 children per woman, although even the Chinese government recognises that the true figure was more like 1.8 because of the incentive the policy creates to underreport births in surveys and censuses (Sharping, 2003). Zhang and Zhao (2006) provide an extensive survey of the literature on fertility decline in China during the last two decades and conclude that the total fertility rate probably fell to around 1.6 by the year 2000. There is no question that the One Child Policy has been fundamental in facilitating this decline. Sharping (2003) controls for numerous other factors that affect population growth - including urbanisation, female education, increases in labour force participation and improved life expectancy, all of which would have contributed to declining fertility in China, regardless of its population policy - and estimates that, in the absence of the state's birth control policies, China's population would have been 1.6 billion instead of the 1.27 billion reported at the end of the 20 th century. China's One Child Policy has always been a highly controversial topic outside of China, and is now being openly challenged within China on the grounds of related ageing and gender imbalance issues. 10 The government is certainly prepared to consider the implications of higher fertility rates, as indicated by research conducted by the Development Research Centre of the State Council of China (2000), which projects population under a variety of fertility scenarios 8 Equivalently, lower wage costs relative to other regions tend to cause real depreciation. 9

The gender issue is particularly critical in China, where the ratio of males to females in the 0-9 age group reached

1147 per 1000 in the year 2000. This is significantly higher than the ratio of 1092 per 1000 in the 10-19 age group,

suggesting that the issue is getting worse, not better. India's ratio is also very high compared to international

standards, with a ratio of 1058 males to 1000 females in the 0-9 age group in 2000, but at least this figure has fallen

slightly from the ratio of 1070 to 1000 in the 10-19 age group. See Padmadas et al. (2005) for further details.

10

A Xinhuanet (2005) news article reported that a number of Chinese scholars challenged China's family planning

policy at a forum on China's population and economy at Beijing University, where the main issues were the

'expanding grey generation' and the gender issue.

7including a "two-child policy". Of course, it is impossible to know the extent to which such a

policy would impact on actual future fertility rates. According to Demeny (2003), in the past the family planning programs that have been most effective in reducing fertility rates inquotesdbs_dbs19.pdfusesText_25

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