Development, Economics and finance, Social policy | Asia, Southeast Asia, The World

21 September 2015

We need to understand the limitations of some of the statistical indicators included in the Sustainable Development Goals if we want to find ways to address inequality, writes Art Martinez.

The image of a drowned toddler washed up on Turkish shores after trying to escape war-stricken Syria paints a stark picture of how it is to be disadvantaged in the lottery of birth. It makes a compelling case to take action and address socio-economic inequalities that currently exist in our societies.

Later this month, global leaders will descend on the United Nations Headquarters in New York to renew their commitment to eliminate poverty, reduce inequalities in social inclusion and promote long-term economic development by launching the Sustainable Development Goals (SDGs). The SDGs are a set of 17 global targets that will succeed the Millennium Development Goals (MDGs).

The MDG scorecards are quite encouraging. According to the latest MDG Report published early this year, significant progress has been made in many areas particularly in reducing poverty, improving access to clean drinking water and improving the lives of more than 100 million people living in the slums, cutting the incidence of malaria and tuberculosis and eradicating gender disparities in school enrolment. While this is an impressive accomplishment, progress has been uneven across the globe.

Inequality is one of the critical development problems that the MDG targets have overlooked according to experts. Oxfam International estimates that the world’s richest 1 per cent own roughly 48 per cent of total global wealth in 2014. This upward trend is expected to increase in the coming years.

There are two mechanisms how wealth inequality can increase. It increases if either the total wealth available in the society increases but the amount of wealth of the poor remains the same, or the total wealth remains the same but the amount of wealth owned by the poor declines. In both instances, critics of inequality argue that this happens when the opportunity to accumulate wealth is monopolised by the rich. Extreme wealth is problematic, according to renowned economists such as Paul Krugman and Joseph Stiglitz, because it can undermine democracy and give unfair advantage to the ultra-rich.

Image by mSeattle on Flickr.

Image by mSeattle on Flickr.

Thomas Piketty’s recent book, Capital in the Twenty First Century, has sparked debate on how societies should feel about inequality.  In his work, Piketty argued that increasing returns to capital and wealth pushes inequality up, however, some liberal economists argue that wealth accumulation also fuels economic growth because it provides the rich with additional resources to invest and create more jobs. Based on this argument, inequality is not all bad.

The thesis that inequality is both good and bad is not new; both sociologists and economists have long argued that there are two sides to it. On one hand, people may be encouraged to work harder due to the higher incentives rewarded to those who exert more effort.  At the same time, inequality can also threaten social cohesion if specific segments of the population do not reap the fruits of their labour. This happens when economic success is predetermined by uncontrollable circumstances such as families’ socioeconomic status, gender or race. Economists refer to this unfair type of inequality as inequality of opportunities.

Since addressing inequalities is one of the main targets of the Sustainable Development Goals (SDGs), it is important for the statistical indicators used to assess the performance to be consistent with the type of inequality that we aim to reduce. However, most official statistics compiled by many countries only measure total inequality, or what economists refer to as inequality of outcomes. By itself, inequality of outcomes does not tell us anything about the level of inequality of opportunities. This could potentially undermine the usefulness of existing inequality measures for SDG monitoring.

To address this, conventional measures of inequality can be supplemented by indicators of socioeconomic mobility. Mobility can be likened to a ladder, where the ladder represents the socioeconomic hierarchy. Some individuals continuously climb up, others always slide down while the rest move up and down. People can also move from one rung to another at different rates. By examining the characteristics of people falling into different types of mobility regimes, we can have a better understanding of the changes in inequalities. For instance, policymakers may be more concerned by increasing inequality if it is accompanied by more poor people falling into stagnant or downward mobility regimes.

In the study How Income Segmentation Affects Income Mobility: Evidence from Panel Data in the Philippines published in Asia & the Pacific Policy Studies journal recently, researchers from the University of Queensland zeroed in on the relationship between income inequality and income mobility in the Philippines. There are several reasons why the Philippines provides an interesting case study. According to World Development Indicators database, the Philippines is one of the fastest growing economies within the Asia Pacific region with its gross domestic product (GDP) per capita growing at an annual rate of 4.3 per cent as of 2014. However, this is accompanied by stubbornly high levels of income inequality.

This indicates that the poor, middle and rich classes have experienced different income mobility regimes over the past decade. The poor were more likely to experience continuous episodes of upward income mobility. On the other hand, the rich were more likely to fall into consecutive episodes of downward mobility, followed by the middle class – at first glance, this is indicative that the poor are catching up with the rest. However, the average income of the poor had barely changed over the years. This means that although there are slightly more poor people who experienced positive income gains, many had volatile incomes which prevented them from permanently exiting poverty. This contributed to stagnant yet high level of income inequality in the country.

As we embrace the new development goals, this is an opportune time to take stock of what we have learned from the MDGs. For instance, the MDGs have 60 statistical indicators while the SDGs have five times more. Considering that developing Asian countries were able to collect less than three-quarters of the MDG indicators only, it will be a challenge for the national statistical systems of these countries to compile all the SDG indicators, unless relevant authorities provide technical guidance on how to prioritise targets.

It is also important that we understand the limitations of some of the statistical indicators included in the SDGs, and find ways to address these issues. To reduce inequalities, examining socioeconomic mobility is one of the many ways to distinguish between the good and bad components of inequality.

Back to Top
Join the APP Society

Comments are closed.

Press Ctrl+C to copy