State rankings 2025: A closer look at assumptions and indicators

The report ranks performance of states in terms of 7 pillars - namely, economic, fiscal, financial, infrastructural, social, governance, and environment - and works out composite index to rank states

The report on the performance ranking of states for 2025, prepared by Care Edge Ratings — a subsidiary of Care Ratings — has received wide media coverage since its recent release. Although the report was produced by a private rating agency, it was accorded a measure of official status through a foreword by the CEO of NITI Aayog.

 

The report ranks the performance of states in terms of seven pillars — namely, economic, fiscal, financial, infrastructural, social, governance, and environment — and works out a composite index to rank the states. This is the second edition of the report by the agency, the first having been released in 2023, though the report states that the two are not comparable. 

 

It is well known that development performance is multifaceted and no single variable can capture it in its entirety. Therefore, the performance measurement in terms of the seven pillars has a wider canvas. The exercise employs 50 indicators to represent them. It uses the standard method of normalisation and assigns different weights to the variables used in each of the seven pillars, based on judgements about their relative importance, and estimates indexes of the seven pillars. The composite index is prepared again by aggregating the indexes of the seven pillars, by assigning different weights based on judgements about their relative importance. 

 

The exercise is carried out separately for the large states (Group A) and the northeastern, hilly, and small states (Group B). Thus, we can observe the relative rankings of the states across each of the seven pillars, as well the overall performance. The composite ranking of the states shows Maharashtra, Gujarat and Karnataka occupying the top three positions in Group A, while Goa, Sikkim, and Himachal Pradesh lead in Group B. Madhya Pradesh, Jharkhand and Bihar are the worst three in Group A, while Arunachal Pradesh, Manipur and Nagaland are at the bottom in Group B. 

 

The subjectivity of the exercise comes out clearly when we consider the weights assigned to the different variables to measure the index of the seven pillars, as well as the varying weights assigned to the index of the seven pillars based on the judgements about their relative importance. Thus, economic and fiscal pillars are assigned weights of 25 and 20 per cent, financial and infrastructure pillars get a weight of 15 per cent each, social and governance pillars are given 10 per cent each, and environment gets a weight of 5 per cent.

 

Presumably, social infrastructure or human development is considered less important, and so is governance in the overall performance of a state. What is conspicuously missing in the analysis is the role of institutions that determine the structure of incentives and impact every one of the other pillars. Many economists, including the three who shared this year’s Nobel Prize — Daron Acemoglu, Simon Johnson, and James Robinson — have underlined the importance of the nature of institutions in impacting development through their effect on the structure of incentives.

 

In India’s case itself, Abhijit Banerjee and Lakshmi Iyer wrote extensively on the role of history and institutions in India’s economic development (“The Legacy of the Land Tenure System in India,” American Economic Review, 2005, pp. 1,190–1,213). This helps explain why many states, even though endowed with rich resources, have remained backward.

 

Even within the seven pillars, the subjectivity in assigning weights leads to curious results. The economic performance index, for example, shows that in Group A states, Telangana — despite having the highest per capita income — ranks sixth. Similarly, Bihar, which has the lowest per capita gross state domestic product (GSDP), ranks higher than Punjab, Kerala, and Andhra Pradesh, even though each of these states has a higher-than-average per capita GSDP. This is because, in addition to per capita income, the index includes the share of industry and services in gross state value added, GSDP growth, the share of foreign direct investment in GSDP, and the ratio of gross fixed capital formation to value added in industry.

 

Some of the indicators are outcome variables, such as per capita GSDP and its growth, while others — like the share of FDI in GSDP and the ratio of GFCF to value added in industry — are input variables. This creates considerable overlap.  Thus, both in the process of choosing the indicators and in assigning weights, questions arise about the legitimacy and objectivity of the exercise.

 

There are problems with the formulation of indicators as well. Unlike the Fiscal Health Index recently released by the NITI Aayog, which primarily considers deficits and debt, the fiscal pillar in this exercise also includes education and health spending — though the weights assigned to deficit and debt variables are much higher.

 

The problem is also with how the variables representing education and health services are formulated.  The indicators are taken as the share of spending on education and health and family welfare in total expenditure. A low-income state may allocate a higher share of its total expenditure on these services and yet its per capita spending — or spending per cohort in the relevant age group — could be much lower than that of other states. Therefore, the standards of education and health services could be lower despite a higher allocation share. This is because their tax base is lower, and they are allowed to borrow in per capita terms only 3 per cent of their low per capita GSDP due to the Fiscal Responsibility and Budget Management legislation. Hence, their total expenditure itself may be lower than their richer counterparts. 

 

In fact, it is observed that per capita expenditures in low-income states are much lower — even when they allocate a high share of their budgets to education and health care, the actual per capita spending on these services are much lower. Besides, expenditure on engineering, medical and agricultural colleges and universities are not included under the major head of education. Thus, it is also important to formulate the variables in a manner that represents what is intended.

 

Another issue relates to the use of this index. Unlike other credit ratings that help raise resources, this performance ranking will not impact the availability or cost of borrowings by the states, as the yield curves on their bonds carry a sovereign guarantee.

 

 According to the CEO of NITI Aayog, this is expected to play an active and complementary role in driving policy initiatives. Indeed, that can happen in a competitive federalism. However, unfortunately, there is little incentive or accountability to spur competition to drive elected governments in the states to improve their performance.  

  (The author is chairman, Karnataka Regional Imbalances Redressal Committee.  The views are personal)