Identifying and compiling data, standardisation, weightage assignment, computation and finally ranking were the steps followed
Agriculture was one of the four parameters on which CSE-DTE ranked 29 Indian states. Photo: iStock
Delhi-based Centre for Science and Environment (CSE) and Down To Earth (DTE) released their annual compendium of data, State of India’s Environment 2023: In Figures, on June 4 — a day before World Environment Day 2023.
A highlight of this year’s report is a ranking of 29 Indian states on parameters like environment, agriculture, public health and infrastructure.
But what exactly was the methodology used?
The report analysed a further 32 indicators under the four parameters. This presented problems as data for certain states was unavailable in certain indicators. These states were awarded the lowest score for the indicator.
In only net state value added by agriculture, forestry and fishing, one of the indicators used for agriculture, two assessment years have been considered, owing to data gaps.
In this indicator, 17 states have data for 2021-22 and 12 have data for 2020-21.
In one of the indicators used for health ranking, operationalisation of health and wellness centres against target, Delhi has been awarded the score for 100 per cent attainment even though the state is not part of the Central scheme of setting up Health and Wellness Centres which aims at reducing the time it takes for people to access public health services.
This has been done because Delhi has already implemented a similar scheme called mohalla clinics.
After identifying and compiling the necessary information, CSE-DTE standardised the numbers to make them comparable.
The raw numbers were normalised using the Dimensional Index Method. In this method, normalised value of each positive indicator (where a higher number is better) is obtained by subtracting the minimum value from the raw value and then dividing it by data range.
For negative values (where a lower number is better), the normalised value is arrived by subtracting the maximum value from the raw value and then dividing it by the data range.
CSE-DTE then assigned differential weightages to the indicators. Each of the four themes were given a total of 10 marks that were distributed among the indicators as per assigned weightages, arrived at on the basis of their importance.
While weightages introduce some level of subjectivity, care was taken to be rational and the weights are derived after extensive studying of government and non-government research in the sectors.
The final scores were then computed and ranked. After completing the data normalisation process, the normalised value of each indicator needed to be multiplied with weightage assigned to indicator in order to obtain the final indicator score.
These final individual indicator scores were aggregated to obtain the final score for the sector.
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