The contribution of reduced population growth rate to demographic - PDF document

27 th International Population Conference, Cape Town 30 October – 3 November 2017 The contribution of reduced population growth rate to demographic dividend Jane N. O’Sullivan Honorary Senior Research Fellow, School of Agriculture and Food Sciences, University of Queensland, St Lucia 4072 Australia. j.osullivan@uq.edu.au Theme 14. Population and Development Theme Convener: Cassio M. Turra, Cedeplar, Universidade Federal de Minas Gerais (UFMG) Abstract The economic stimulus experienced in countries following a fall in fertility has been widely attributed to the improvement of dependency ratio, as the proportion of children falls. But age structure can account for less than a third of the stimulus observed in East Asian countries and the correlation has been reported to be inconsistent elsewhere. Population growth rate itself has economic impacts, which have lately been overlooked in economic analysis of the fertility transition. This paper describes measurement of the macroeconomic cost of providing physical capital for additional people. In Australia and the UK, this cost was estimated at 6.5- 7% of GDP per one per cent population growth rate. In rapidly growing, high fertility countries, this implies a debilitating burden. The relationship between population growth rate and economic advance was found to be remarkably consistent when comparing countries with slow and fast fertility decline, demonstrating the strength of the constraint which population growth rate places on economic advance. While growth in GDP per capita was found to be highly dependent on fertility rate, the decline in fertility was not found to be dependent on wealth. The paper concludes that voluntary family planning can be highly effective development stimulus. Introduction It has been observed that countries experience an economic boost after fertility declines. The main explanation to date has been the effect of reducing the numbers of children leading to a higher proportion of working age people, referred to as the ‘demographic dividend’ (Bloom and Williamson 1998, Canning et al. 2015). However, even if the increase in working age proportion fully translates into increased workforce, it accounts for between a fifth and a third of the economic stimulus observed (Wang and Mason 2007; Bloom and Canning 2008). Garenne (2016) found the relationship between economic growth and dependency ratio was inconsistent in longitudinal analyses of African countries. The ‘infrastructure dividend’ is less well appreciated. It is directly related to the population growth rate, and arises from alleviating the need to acquire additional physical capital, including infrastructure, equipment and training of professional service providers, to extend the existing quality of life and employment opportunities to additional people. It is likely to 1

have a greater and more sustained impact on development stimulus than the demographic dividend – indeed, it operates equally in ‘ageing’ countries wh ere age dependency is rising, and even benefits declining populations. The burden of equipping a rapidly-growing population is not a novel idea. It is occasionally alluded to by those who advocate that family planning should be a priority for development, not merely for health and rights. Lee (2009) suggests “[it would seem] so obvious: Larger, more rapidly growing populations have fewer natural resources per person, less physical capital per worker, more dependents, and greater needs for new social infrastructure. Of course they must be economically worse off.” Bongaarts (2016a) defines ‘demographic dividend’ broadly as “ the boost to economic growth that follows a decline in fertility ” , without reference to mechanistic channels. He explicitly incorporates the infrastructure burden alongside age dependency (Bongaarts 2016b), explaining, “ A better-educated workforce has fewer dependents and more resources, and this ‘demographic dividend’ spurs economic growth. Governments are better able to keep pace with – and even get ahead of – meeting infrastructure needs of their citizens. ” Nevertheless, without explicit quantification, it is omitted from metrics and models from which policy advice is derived. Demographic dividend potential is measured only in terms of age dependency ratios, and economic models generate misleading conclusions by ignoring the cost of expanding durable assets. The purpose of this article is to outline the measurement and the scale of this neglected impost, which in many contexts overwhelms other impacts of demographic dynamics. Sauvy (1958) first attempted to calculate what he termed the ‘demographic investment’ required to provide physical capital for additional people. This represents a substantial call on the limited saving capacity of rapidly growing developing countries. It is inevitably the first call on these funds, at considerable opportunity cost, preventing expenditure which would increase the capital/labour ratio and the quality of services delivered. Robinson (1974) applied Sauvy’s concept to the budget for Bangladesh’s first five -year plan. He concluded that the cost of ‘standing still’ at the prevailing 3% per annum population growth represented around 75% of all the investment. With the planned level of investment, incomes might be raised by 30% over 20 years, but if population growth were at the European level (0.45% p.a. at that time) an income increase of 150% would be expected. More recent discourse has referred to ‘demographic investment’ as ‘capital widening’ in contrast to ‘capital deepening’ of improving the provision per person. However, since these early works, there has been little attempt to quantify this impost and its impact on economic development. Sauvy’s work is less remembered than that of Solow (1956) who fram ed physical capital more narrowly as a production factor. Subsequent models have tended to express it as the “capital shallowing effect” of additional labour (eg. Ashraf et al. 2013), and consequently to apply the marginal productivity of capital. This runs the risk of underestimating the productivity of the total industrial capital stock, and ignoring the public and domestic capital stock which are equally prone to dilution and, apart from affecting productivity indirectly, affect the relationship between income per capita and the quality of life it can achieve. Rather than extrapolating the dilution of capital to the point of mass unemployment, modellers tend to assume that capital will adjust, with the help of the expanded economy and diminished labour costs (Rowthorn 2015; Productivity Commission 2016), without quantifying the ongoing cost of such adjustment. Thus they have not adequately dealt with the impact of expenditure diversion on other consumption, nor the complex system failures resulting from chronic failure to keep pace with population growth. 2