Judging development progress is easier said than done
Bibek Debroy Bibek Debroy | 26 Jul, 2019
Measures for Measurement (Illustration: Saurabh Singh)
BY NOW, MOST people have some idea about sustainable development goals (SDGs). SDGs were adopted in 2015 (they came into force in January 2016) and are to be attained by 2030. Earlier, for 2000 to 2015, there were millennium development goals (MDGs). If the world as a whole has progressed towards MDGs, that’s largely because of China. If the world as a whole is to make substantial progress towards SDGs, that will happen largely because of India. Most people also know SDGs have a nested structure. There are goals, targets and indicators. Goals are general statements, while targets make them precise. Indicators are specific variables one can track. Let’s take an example to illustrate what this means. SDG Goal 1 states, ‘End poverty in all its forms everywhere.’ Under Goal 1, we now have several targets: 1.1—‘By 2030, eradicate extreme poverty for all people everywhere, currently measured as people living on less than $1.25 a day’; 1.2—‘By 2030, reduce at least half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions’; 1.3—‘Implement nationally appropriate social protection systems and measures for all, including floors, and by 2030 achieve substantial coverage of the poor and the vulnerable’; 1.4—‘By 2030, ensure that all men and women, in particular the poor and the vulnerable, have equal rights to economic resources, as well as access to basic services, ownership and control over land and other forms of property, inheritance, natural resources, appropriate new technology and financial services, including microfinance’; 1.5—‘By 2030, build the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and other economic, social and environmental shocks and disasters’; 1.1a—‘Ensure significant mobilization of resources from a variety of sources, including through enhanced development cooperation, in order to provide adequate and predictable means for developing countries, in particular least developed countries, to implement programmes and policies to end poverty in all its dimensions’; 1.1b—‘Create sound policy frameworks at the national regional and international levels, based on pro-poor and gender-sensitive development strategies, to support accelerated investment in poverty eradication actions.’
This gives the general idea. The targets have made the goals more precise. But we still don’t know how to measure them and track progress. The indicators do that. Moreover, this was only for the first goal of SDGs. There are 17 such goals. Each country has to develop its own set of indicators, reflecting national priorities and data availability. In September 2016, the Ministry of Statistics and Programme Implementation developed a set of possible indicators for India. This was discussed and refined and we now have a list of 306 indicators, spanning all 17 goals (actually 16 since the 17th belongs to a different category). This is known as the National Indicator Framework (NIF). The NIF isn’t cast in stone. It can be tweaked. Indicators can be added or removed. However, the NIF is fundamentally how we will track India’s progress towards SDGs. Improvement on what base? We need a baseline report and the base-year is 2015-2016. India’s baseline report was recently released on June 29th. Measurement requires data availability at frequent intervals. While SDGs are desirable goals, tracking progress towards them is not that easy.
Since poverty is easily understood, let me stick to that first SDG goal to illustrate the kind of problem that occurs. I have already stated Target 1.1. Under Target 1.1, we have two indicators, 1.1.1 and 1.1.2. Indicator 1.1.1 is the ‘proportion of population living below the national poverty line’ and 1.1.2 is the ‘poverty gap ratio’. The baseline report gives us 21.92 per cent for 1.1.1 and 5.05 per cent (rural) and 2.7 per cent (urban) for 1.1.2. These numbers are for 2011-2012. Why 2011-2012? Because that’s when a National Sample Survey (NSS) was undertaken and when the then Planning Commission last computed such numbers. The NITI Aayog now has the responsibility of generating subsequent numbers for 1.1.1 and 1.1.2, every five years. However, we need an NSS round comparable to 2011-2012, a big if. And we also need a notion of the poverty line. In government programmes, Union and state, notions of deprivation are now based on the socio- economic caste census (SECC) and there is no longer any notion of a poverty line. Who is going to develop this poverty line and how? Add to that indicators for Target 1.2. If you re- read Target 1.1, you will see that this is nothing but a multi- dimensional poverty index. There is no consensus about what such a multi-dimensional poverty index should look like. Constructing one for the purpose of writing an academic paper is easy. Constructing one for the purpose of tracking the impact of policy is easier said than done.
Let’s move on to Target 1.3, which is far more tractable. The indicators for Target 1.3 are discussed below. Indicator 1.3.1 is ‘percentage of households with any usual member covered by a health scheme or health insurance’. For 2015- 2016, the baseline number is 28.7 per cent. Indicator 1.3.2 is ‘number of beneficiaries under Integrated Child Development Scheme’. The 2015-2016 baseline number is 102.1 million. Indicator 1.3.3 is ‘proportion of the population (out of total eligible population) receiving social protection benefits under Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA)’. We don’t yet have a baseline number for this. (I have a problem with an indicator like this. Whether we explicitly admit it or not, every indicator has an implied value judgement. If the MGNREGA numbers decline, is that good or bad? I don’t think the answer is clear.) Indicator 1.3.4 is ‘number of Self Help Groups (SHGs) formed and provided bank credit linkage’. The baseline figure for 2015-2016 is 1.83 million. Indicator 1.3.5 is ‘proportion of the population (out of total eligible population) receiving social protection benefits under Maternity Benefit’. This figure is also not ready yet. Indicator 1.3.6 is ‘number of senior citizens provided institutional assistance through Old Age Homes/ Day Care Centers funded by the Government’. The baseline number for 2016-2017 is 22,050. Notice that in two instances the denominator is total eligible population, not total population. The indicators for Target 1.3 are much more tractable. Data are almost always annual, obtained through the Ministries of Health and Family Welfare, Women and Child Development, Rural Development and Social Justice and Empowerment. Yes, data often come up from below, from states. And yes, there are time-lag issues. But otherwise, no serious monitoring issues.
That’s not true of Target 1.4. Here are the indicators: 1.4.1—‘percentage of population (rural) living in households with access to safe drinking water and sanitation (toilets)’; 1.4.2—‘proportion of population (urban) living in households with access to safe drinking water and sanitation (toilets)’; 1.4.3—‘proportion of population (urban/rural) living in households with access to electricity’; 1.4.4—‘proportion of homeless population to total population’; 1.4.5—‘proportion of population having bank accounts’; 1.4.6—‘number of mobile telephones as percentage of total population’. A few of the baseline numbers haven’t yet been compiled. For 1.4.4, the 2011 figure is 0.15 per cent. For 1.4.5 and 1.4.6, we have data for modified indicators. In 2015-2016, the number of accounts (including deposit and credit accounts) of scheduled commercial banks per 1,000 people was 1,425. In 2015- 2016, the number of telephone subscriptions as a percentage of the total population was 83.4 per cent. Indicators 1.4.5 and 1.4.6 will always be reasonably easy and reasonably current. But think of 1.4.1-1.4.4. Such numbers usually come through the Census. We can get 1.4.1 through the Ministry of Drinking Water and Sanitation, 1.4.2 through the Ministry of Housing and Urban Affairs and 1.4.3 through the Ministry of Power. But there is no guarantee that these will be consistent with Census numbers. That apart, 1.4.4 will only be available through the Census, and such numbers are only available once every 10 years. Not quite good enough. I will skip Targets 1.5, 1.a and 1.b, because they won’t add much to what I have already said.
If you think of the 17 SDG goals, several of them, understandably, are about social sectors, health and education, especially the former. Are our data good enough for either? Yes, there are surveys. How reliable are those surveys? Why don’t different findings tally with one another? What is the process of vetting data? The National Statistical Commission (NSC) has often got involved in controversies over national income data. For national income and the Central Statistics Office-data, the NSC is indeed the vetting authority. But for other sources, it is the NSC’s mandate to examine generation of data. Now that we have a newly constituted NSC, perhaps this is what the NSC will look at. Indeed, the 2001 Rangarajan report on India’s statistical system highlighted blemishes in the data-generation system and that is why the NSC was set up. Without better social-sector data, monitoring progress towards SDGs will be close to impossible.
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