CAPTURING DATA FOR MULTI-DIMENSIONAL RECOVERY RESPONSES — PART 2
Authored by Ms. Ayushka Nugaliyadda and Ms. Sarika Warusavitarana of Citra Social Innovation Lab
What progress was made with UNDP’s National Citizen Survey 2022–2023?
Following on from our last blog from February, the data from UNDP’s National Citizen Survey 2022–23 (NCS) is now officially live on the UNDP Sri Lanka website. In a first for UNDP Sri Lanka, and with technical support from the team at UNDP’s SURGE Data Hub, this data can be accessed both via an interactive dashboard, in addition to the dataset being freely available for download, for anyone who wishes to play around with the numbers.
Data collection for the NCS began back in November 2022, and concluded in March 2023. Through this process, we now have a rich dataset with a nationally representative sample of 25,042 households across all 25 districts, as per the Department of Census and Statistics’ (DCS) recommendations. Efforts were also made to ensure both urban and rural populations are proportionately represented in the sample. To supplement this analysis, a series of focus group discussions were conducted across the nine provinces.
So, how did that lead to a Multidimensional Vulnerability Index (MVI)?
Firstly, what is an MVI?
The MVI is an indicator that attempts to capture the intersecting and overlapping vulnerabilities households face. This measure aims to go beyond measures of financial vulnerability to also consider educational, health-related, and other kinds of vulnerabilities in order to provide a more comprehensive picture of the challenges being faced on the ground. The Oxford Poverty and Human Development Initiative (OPHI) is the global leader in developing both the MVI and the Multidimensional Poverty Index or MPI (having already supported the DCS on developing a national MPI for Sri Lanka).
In collaboration with OPHI, UNDP supported the calculation of an MVI for Sri Lanka using the data collected from the NCS.
The MVI assesses vulnerability in three critical dimensions: (1) Education; (2) Health and Disasters; and (3) Living Standards. The three dimensions are measured by 12 indicators, as illustrated in Figure 1 below.
MVI values range from 0 to 1, with 0 indicating that no one is vulnerable and 1 suggesting that everyone is vulnerable and deprived in all 12 indicators. The aim of the MVI is that, by combining the deprivations encountered by each household in each of these 12 indicators, we are able to get a snapshot of the vulnerabilities that were experienced by households in Sri Lanka during this timeframe.
Headcount ratios and censored headcount ratios
The MVI analysis was also able to provide us with information on the incidence of vulnerability (or the headcount ratio), which refers to the proportion of individuals identified as multidimensionally vulnerable — for instance, the national incidence was estimated to be 55.7%, based on the NCS data, indicating that it could be estimated that 55.7% of the Sri Lankan population could be said to be multidimensionally vulnerable.
It also provides us with what we call the censored headcount ratios, which represent the proportion of the population that is estimated to be multidimensionally vulnerable and is deprived in one specific indicator. To illustrate, we can take a look at the censored headcount ratios for Puttalam, which has the highest MVI value from all 25 districts:
This indicates that the highest deprivations in Puttalam are experienced in terms of adaptive capacity to disasters and water source, with 63.7% and 58.6% of the population being estimated to be multidimensionally vulnerable and deprived in those specific indicators, respectively.
It is therefore accurate to suggest that reducing any of the 12 censored headcount ratios (for each indicator) by addressing deprivations for vulnerable individuals will lead to a reduction in the overall MVI for the country.
For more information on the MVI, we launched a policy report titled ‘Understanding Multidimensional Vulnerabilities: Impact on People of Sri Lanka’ in September this year, which can be found here. In addition to the excellent work carried out by OPHI on this report, we are also grateful for the guidance provided by the Advisory Panel for this report, comprising Dr. Sonali Deraniyagala, Dr. Indrajit Coomaraswamy, and Dr. Ramani Gunatilaka, who provided valuable insights throughout the process.
What are some key policy recommendations, based on this analysis?
The report outlines some key recommendations in more detail than we will in this blog, focusing on thematic areas around evidence-based policymaking and national planning, social protection, support to Persons with Disabilities, household debt, climate and disaster resilience, and education. In addition to these critical areas, what we would like to highlight here is the need to establish systems and mechanisms to ensure the adoption of an official national MVI, and thereafter, use this MVI to inform long-term policy and programming.
An MVI with valid and reliable indicators can be a powerful and innovative tool for decision-makers. We must note here that while several potential dimensions and indicators emerged in expert consultations and FGDs as important for measuring vulnerability in Sri Lanka, the absence of these required indicators in the NCS prevented its inclusion in this particular MVI analysis. For instance, indicators on nutrition, job security, sanitation, food security, and social exclusion that were missing in the NCS should definitely be considered. Furthermore, improved versions of indicators relating to adaptive capacity to disasters, household debt burden, and employment status in the national measures must be designed. Finally, it is also vital that such exercises should ensure representative sampling across key demographics and sectors, to reflect the unique challenges experienced by different communities and locations — for instance, ensuring that the estate sector is sufficiently represented. This could provide a foundation for targeted policy interventions and effective poverty reduction strategies.
We therefore advocate for the calculation and adoption of an official National MVI by the DCS as part of their regular statistical exercises, in order to build on and complement Sri Lanka’s existing official National MPI. By combining these two indices, policymakers might find overlapping groups that are not just poor, but also extremely sensitive to external hazards. This synergy enables policymakers to design tailored initiatives that address the underlying causes of deprivation and vulnerability, ensuring that no one falls behind in the development process.
In the spirit of working out loud, we’ll continue to share updates on any follow-up work we do in this area. But, in the meantime, if you are interested in collaborating with us to analyse the data, unpack the findings and explore the different ways in which we might use this dataset, we would love to hear from you!
Citra is Sri Lanka’s pioneer Innovation Lab that offers human-centered design and systemic design thinking approaches to solve complex development problems. Together with the Prime Minister’s Office of Sri Lanka and the United Nations Development Programme (UNDP) in Sri Lanka, Citra Lab focuses on adopting innovative approaches and tools in its work to build solutions to the challenges faced by the country.
