ICT & Sustainable Development through a Preston Curve Lens

ByAndrew Williamson

September 4, 2020

Andrew Williamson

It is generally accepted that Information Communications Technologies (ICT) will play a crucial enabling role for countries in reaching the United Nation’s sustainable development goals (SDGs). Indeed, UN Secretary-General António Guterres stated as much formally in 2017 by stating “The 2030 Agenda…recognizes the great potential of global connectivity to spur human progress.”

But can we better quantify the impact ICTs can make on the SDGs for developing countries in particular, where the returns are likely to be greater and more impactful? And does digital connectivity accelerate certain SDGs faster than others? To better investigate the longitudinal relationship between ICTs and the SDGs (and across countries at different levels of ICT development), I used an adaptation of Preston Curve analysis.

Preston Curves are graphical relationships between life expectancy (an important and measurable health outcome) and real per capita income. They were first advanced by the economist Samuel H. Preston in 1975 [1]. Preston studied the relationship between wealth and health for the 1900s, 1930s and 1960s and established that a strong correlation held for each of the three decades. What he discovered in essence was that at low levels of per capita income, further increases in income lead to large gains in life expectancy. But at higher levels of income, increased incomes per capita led to much smaller gains in longevity. Accelerating economic development from low starting bases (poverty) therefore benefited not just average household incomes but had drastic impacts on life expectancies too.

Chart 1 – Example of a Preston Curve

Preston’s research also uncovered two more important findings. The first was that by periodically re-examining the relationship between national income and life expectancy, one could establish how the link between the two shifted as a result of new influences or scientific breakthroughs and how it impacted countries at different levels of economic development. The second was that by testing the relationship over time one could either prove or disprove the underlying relationship.

Chart 2 – Observing the relationship over time

Chart 2 illustrates three potential changes in relationship between life expectancy and income over time. In box A, life expectancy improves across all countries at a given level of income over time suggesting that any new influences or technological breakthroughs on life expectancy impact equally across all countries, regardless of their level of economic development. Box B shows a change in relationship where a new influence or technology proportionately benefits richer countries. Finally box C depicts a shift where poorer countries benefit more from exogenous changes to technology or other factors.

If data are indeed the new measure of income[2] as many have suggested, and given the pivotal importance ICT has been given in our ability to achieve the UN’s SDGs, I substituted the measure of GDP per capita with broadband subscriptions per 100 people. We observe some interesting initial findings (chart 3).

Chart 3 – Preston Curve: Broadband subscriptions per 100 people (X) vs life expectancy (Y)

Source: Huawei

Firstly, the relationship substituting broadband diffusion is very similar to that established by Preston using real income per capita. The curve is concave, suggesting rapid returns to increases in internet connectivity from the lowest levels of broadband diffusion but diminishing returns towards the highest ratios. But greater connectivity to the internet does still correlate to greater levels of life expectancy. Secondly, the concave relationship holds over the years 2005, 2010 and 2015 but changes slightly, while shifting upwards. Broadly the curve holds its shape, with rapid returns for less developed countries and less increases in life expectancy for more developed countries. As with income, increases in broadband diffusion have increased in lock-step with increases in life expectancy. Moreover, the fit to the curve also grows stronger statistically over time, showing less variance across countries as we move from 2005 to 2015.

Chart 4 – Preston Curve: Broadband subscriptions per 100 people vs SDG3 and SDG4

Source: Huawei

What does the current relationship look like if we substitute life expectancy for some measure of cross-country progress towards the SDGs?  In Huawei’s 2019 ICT Sustainable Development Goals Benchmark research report, we scored 55 countries across a range of SDGs by using a set of proxy quantitative metrics for each with a possible maximum available score of 50. I used these scores for our individual SDG Preston Curve analysis.

For SDG3 (Health) and SDG4 (Education) the results appear to be very similar to the previous findings – small improvements in broadband subscriptions from the lowest base ratios correlate to rapid improvements in national scores for health and education but with declining returns as we approach the highest levels of diffusion. Moreover, the fit to the curve is even stronger from our more holistic measure of health outcomes as covered in SDG3 of our ICT Sustainable Development Goals benchmark, than just life expectancy. The same is true with our broad SDG4 based measure of education outcomes.

Chart 5 – Preston Curve: Broadband subscriptions per 100 people vs SDG5 and SDG7

Source: Huawei

The relationship for the ratio of fixed broadband subscriptions per 100 people to SDG5 (gender equality) and SDG7 (affordable and clean energy) as plotted, do not exhibit the same clear concave curves as previously. The correlation is also weaker. On gender equality there are two distinctive groups weakening the overall fit to the curve. This possibly suggests that cultural and societal norms are more influential than just digital connectivity. The plot for SDG11 suggests only a very mild relationship of increasing returns to greater internet connectivity, which may be indicative of the very early stages we are at in terms of smart energy deployment through national infrastructures. Expect this to change with smart energy grid infrastructures.

In future iterations of Huawei’s ICT Sustainable Development Goals Benchmark assessment, we will continue to review shifts in our adapted Preston Curve analysis to better understand the underlying relationship between ICT and the SDGs and how the dynamics change over time as the benefits of greater connectivity are fully realised.

For more on Huawei’s commitment to sustainable development, see our 2019 Sustainability Report. And click the link find out more about our digital inclusion initiative TECH4ALL, which is aligned with the SDGs.

[1] Preston, S. H (1975). “The Changing Relation between Mortality and Level of Economic Development”. Population Studies. 29 (2): 231–248

[2] https://www.weforum.org/agenda/2015/08/is-data-the-new-currency/

Disclaimer: Any views and/or opinions expressed in this post by individual authors or contributors are their personal views and/or opinions and do not necessarily reflect the views and/or opinions of Huawei Technologies.

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Andrew Williamson

Vice President, Government Affairs and Economic Adviser, Huawei In this role, Andrew is a key aide on global macroeconomic, political and industry trends. His research also involves the contribution ICT makes to economic growth, and society.

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