The need to have a performance-linked incentive model in education ecosystem

The National Education Policy (2020) has called for public expenditure on education to rise to 6% of India’s GDP. This is a reasonable target if India aspires to be a significant power. According to data from the World Bank, Australia (5.2%), Brazil (6.1%), and Canada (5.2%) are among the countries worldwide that have public expenditure in that range. We are currently far below that target. In 2021-2022, India’s public expenditure on education was 3.1% of the GDP. In 2022, the Finance Minister, Nirmala Sitharaman, announced an increase of 18% over the previous year. This was very welcome news after the slight decrease in the previous year. But the reality is that an increase in this range is insufficient to reach the targeted 6% in the near future. With the year-on-year increase of 15% in the education budget for the next decade, we will still be below that target. All the same, increasing well above that kind of increase in the national budget is unrealistic. As a percentage of our central government budget, education is already at 16%, the third highest item on the budget. This is roughly the same percentage of China’s budget during the 90s, the decade where they achieved transformational progress in developing a world-class public education ecosystem.

We could achieve a similar transformation by reimagining how we utilise budgeted expenditure on education. Our central budget on education expenditure is divided into two main areas: school education and literacy, and higher education, with a rough proportion of 60:40. We should innovate on disbursement models in each area separately. Let us consider some novel disbursement models for funding higher education.
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A potential game-changing scheme would be to use funds allocation to incentivise private giving to public and private colleges. Some large corporations have a scheme for matching charitable contributions made by their employees to the charity of their choice. An analogous scheme would be to set aside a portion of the budgeted amount to match donations made by alums and wealthy individuals to an educational institute. We do have schemes in place to give them tax relief. But this one serves a different purpose. The leverage of additional contributions would incentivise individuals to donate more to educational institutions. At the same time, the management of academic institutes would work harder to attract private funding sources. To safeguard against misuse, this matching of individual contributions can be restricted to the top 50 or 100 nationally ranked (NIRF-rated) colleges. Moreover, the government should only match donations that advance the key performance measures.

Another radical innovation to consider would be to allocate discretionary funds to an institute linked to its past track records on improvements. This model is quite different from what we have done recently. For instance, consider the scheme known as the Institute of Eminence (IoE). The scheme was introduced in the 2016 Budget by the Finance Minister of India, Arun Jaitley. According to this scheme, 10 public and 10 private universities in India were to be declared as IoE. In addition to allowing them autonomy over specific regulations, the scheme allocated Rs 1,000 crores to each public university designated as IoE. The intent was for them to utilise these funds to help become world-class teaching and research institutions. This is an example of what one would call a wishful-thinking funding model. We hoped these institutes would use the additional funds wisely to achieve the goal.

In comparison, a performance-linked incentive model is more likely to lead to having world-class educational institutions. The performance measures of an educational institute used in this context should be objectively observable. Aspirational goals such as becoming world-class do not qualify as that is broad and not an actionable goal. Specifying too many measures or being proscriptive should also be avoided. An ideal PLI model of funding scheme would define a few key performance indices (KPIs) and keep these relevant to how we envision our institutions to grow.

Some examples would clarify the intent. Many academics have suggested that our research institutes do incremental research rather than produce breakthrough research. If our objective is to do breakthrough research, then the appropriate KPI would be to use the aggregation of h-indices of research papers published by faculty members rather than the number of journal papers published by faculty. This (h-index) measures each research paper’s impact on the field. Similarly, many employers have indicated that our students are not well-prepared for the jobs they do and thus require additional training at their expense. Suppose our objective is that an institution imparts excellent education to students. In that case, relevant performance measures should be about placement data, including how many get jobs, the kinds of jobs offered, additional training needed to become effective upon graduation, etc.

In redesigning any models for disbursement that depends on performance measures, we need to look at key characteristics that make the redesign successful. More prominent and significant institutes would see disproportionate benefits if performance is measured in absolute numbers, such as the number of journal papers published in the past year. This, of course, perpetuates the status quo and will discourage continual improvements by institutions. A better design would measure the rate of progress in a performance metric. Similarly, a better plan would look at a metric averaged over the past 2 or 3 years, indicating a trend of improvement. Moreover, instead of earmarking separate funds to each desirable performance metric, discretionary funds should consider a mix of performance criteria and let funded institutes choose how to spend measures to improve metrics that play to their strength.
The above models are more relevant to the public funding of higher education. We should also seek similar models to disburse public funds in high school and literacy areas. Any such model must be based on observably objective measures and provide institutes clarity about steps to take to seek an increase in discretionary funding. This would be a radical and welcome departure from the current practice of allocating funds.

Recently in the city of Varanasi, during my travels, I came across a driver who earns close to Rs 16,000 per month and spends roughly Rs 9,000 out of that income on the education of his two daughters, one of whom he claimed, is a brilliant student aspiring to be a medical doctor. That level of personal sacrifice for their children’s future is relatively common among the poorer section of the Indian population. Given that kind of personal sacrifice by the ordinary person, the nation’s politicians and policymakers must learn to deploy our public expenditure on education effectively.

The writer is the Founder of Maker Bhavan Foundation.

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