Editorial 1 : Funding the Future: A chance at genuine innovation
Context:
- In 2017, eight-member committee was formed under the chairmanship of K Kasturirangan to draft a national education policy. The committee’s recommendations were published as National Education Policy 2020 (NEP-2020).
- The report highlighted the lacunae in the higher education system, the most prominent being the rigid boundaries of disciplines and fields, thousands of stand-alone institutions, absence of research at most universities and colleges, and the lack of a transparent and competitive peer-reviewed research funding system.
- One of the major recommendations of NEP-2020 was the establishment of a National Research Foundation (NRF) to manage a competitive grant system for R&D in universities and institutes involved with higher education.
Recent Set up of NRF will help in promoting research and development
- The Central government has finally given clearance to the establishment of NRF. A budget of Rs 50,000 crore for research has been envisaged for the next five years.
- The contribution of the Central government has been pegged at Rs 14,000 crore while the remaining 36,000 crore will be garnered from public sector enterprises, industry, foundations, and international research organisations.
- It also proposed to convert the Science Engineering Research Board (SERB) attached to DST into NRF.
Significance /Objective of National Research Foundation (NRF)
- NRF aims to “seed, grow and promote research and development (R&D) and foster a culture of innovation throughout Indian universities, colleges, institutions, and R&D laboratories”, and
- promoting need-based research and help support research in the fields of natural sciences, engineering and technology, environmental and earth sciences and social sciences
Current status of government’s funding for R&D:
- Currently, government funding for R&D is being spent in two modes core grants and extramural grants. Most of the expenditure is through core grants.
- In the financial year 2016-17 for which complete information is available from “Research and Development Statistics 2019-20 by DST” Rs 42,074 crore was spent by the Central government on R&D.
- The three major recipients of the funding — DRDO (31.8 per cent), DoS (19.1 per cent), and DAE (11.3 per cent) almost completely work with core grants
- In 2016-17, around Rs 2,454 crore (5.8 per cent of the total expenditure on R&D) was spent on extramural grants to fund around 4,711 projects.
- This small amount served the R&D aspirations of the central universities, state universities including agricultural universities, colleges, deemed universities, institutions of national importance like IISc and IITs, and even the national laboratories.
There is need to enhance funding for educational institution:
- India needs a strong competitive grant system as has been proposed by NEP-2020. As the number of institutes/universities/medical schools has increased significantly.
- However, the overall funding under extramural grants has remained static. This has led to poor doctoral-level training which has very grim consequences for the country.
- As for the big picture, India is spending too little on R&D — only 0.65 per cent of our GDP (0.41 per cent by the public and 0.24 per cent by private funding).
- These investments are much lower than those being made by the developed and newly emerged economies of East Asia (more than 2 per cent of the GDP).
- Therefore, a competitive grant system provides the necessary leeway to accelerate research in new and emerging areas where interdisciplinarity is critical and can be used for collaborative work among institutions, between institutions and industry, and collaborations across the countries.
Conclusion:
- NRG administration will implement a time-bound, ICT-based system for managing the projects and disbursing a grant of Rs 3,000 crore in the launch year and will seed, grow and promote research and development (R&D) and foster a culture of innovation throughout Indian universities, colleges, institutions, and R&D laboratories
- Therefore, set up of NRF is right step towards the direction of research and development in India.
Editorial 2 : The sample is wrong
Context:
- In India, estimates related to poverty, growth, employment, and unemployment are fiercely scrutinised and debated.
- Given the importance of these data in framing policies, it becomes imperative that the surveys that produce these estimates are conducted at regular intervals in a pre-determined timely manner and are of the highest quality
- As For data to inform policy, three issues merit consideration are important:
- One, availability of data
- two, transparent and robust statistical analysis, and
- three, data quality.
Over dependency on surveys of households
- In India, policymakers typically rely on the estimates of sample surveys of households to assess previous policies or to frame new policies.
- For example, the National Sample Survey (NSS) of households has been conducted to determine the household consumption expenditure, including services or durables, or
- to provide estimates of persons with disabilities, or
- to provide estimates of expenditure related to domestic tourism, or
- to provide estimates related to drinking water, hygiene, conditions of the house, etc.
- For health, policymakers rely on the National Family Health Survey (NFHS) and the Periodic Labour Force Survey (PLFS) for questions related to employment and unemployment.
- But there is concern over non-frequent nature of some of these surveys (in particular, the household consumption expenditure survey), and there is a constant demand for increasing frequency and size of surveys, there is practically a consensus on the robustness and the representativeness of the survey methodology. Along with it there have been virtually no concerns or studies on these surveys’ data quality.
Issues with current sampling methods:
- Data quality related to NSS, NFHS, and PLFS needs a major sampling overhaul to reflect the true status of India’s real economy.
- These surveys use outdated sampling frames and hence, are not representative. In fact, the survey mechanisms are archaic and not adapted for rapid changes.
- As a consequence, these surveys grossly and systematically underestimate India’s progress and development and the misleading estimates from these surveys impede policy-making.
- Framing policies based on these estimates are unlikely to yield the desired results and we will continue to see a gap between ground realities and survey estimates
- Using projected population estimates, It is found that nearly all major surveys in India that were conducted post-2011 and used the Census 2011 for the sampling frame have overestimated the proportion of the rural population significantly.
- This is one of the several problems with data quality, but it is a critical concern — and appropriately highlights the problem at hand.
How the data Differ:
- The graph below shows the projected rural population of India over the years 2011 to 2021 and compares these with the estimates of rural population from the major surveys during this period.
- As is evident, every survey (except NFHS-4 of 2015-16) underestimates the proportion of the urban population or overestimates the rural population significantly compared to the population projections based on the Census 2011.
- A key implication is that the differences in estimates are significant and indicate major concerns in sample design across all these surveys.
- Moreover, it is important to appreciate that the population projections themselves fall short of the rapid pace of change on the ground.
- It is well documented that the proportion of the urban population based on a projection from Census 2001 grossly underestimated the speed of urbanisation in India.
- And not correcting for such errors will most definitely lead to misleading estimates from the surveys, however large the sample size.
- Continue to raise sample size without correcting for such non-sampling errors then the estimates from such large surveys will be “very precisely wrong”.
- Given that rural and urban estimates are closely related to almost all variables of interest, such as health outcomes, wealth and asset ownership, poverty, employment and unemployment, growth etc,
- the resulting estimates from these surveys would over-represent the rural population and therefore systematically underestimate the improvements across the economy.
- the resulting estimates from these surveys would over-represent the rural population and therefore systematically underestimate the improvements across the economy.
Conclusion
- It is evident from the analysis is that the greater the improvement on the ground, the greater will be the bias in the survey estimates.
- The Indian economy has been incredibly dynamic in the last 30 years with significant policy reforms and subsequent major breaks in the long-term structural growth path.
- As India is urbanising at a rapid pace, and often defying the expectations and projections based on past trends.
- Therefore, a large part of statistical reforms should not merely focus on the availability, frequency and largeness of data, but greater emphasis should be placed on data quality.