First I should clarify that in the context of our study, we have only looked at inequity in access to quality of life services for different socio-economic groups in the city. For this purpose we chose six service parameters, and identifying the minimum threshold for each service, as shown below:
|Quality of Life Service Parameters|
The sample survey data is used to assess what percentage of population in each income group has minimum or higher access to each of these six parameters. A well-being rank is defined on the following basis:
Rank 1: 0 to 10% households having minimum or more access
Rank 2: 11 to 20% households having minimum or more access
Rank 3: 21 to 30% households having minimum or more access
Rank 10: 91 to 100% households having minimum or more access
We also decided that we will take Rank 7 as the threshold. In other words, if the Rank is 7 or above, it means the access to that service for that income group is reasonably good. On the other hand, Rank below 7 is indicative of poor access.
On this basis, we define two indices:
- The number of Ranks less than 7 for any one income group is a Measure of Deprivation for that income group.
- The difference between the highest and lowest Ranks for a given parameter across income groups is a Measure of Inequity for that parameter.
Based on our own socio-economic data, we can generate the following table:
|Socio-Economic Inequity Indices|
For both the indices, lower value is better.
It is also possible to represent the indices and ranks graphically, as shown below.
|Graphical Representation of Socio-Economic Indices|
The above is just a conceptual idea. The six parameters were chosen on the basis of whether they refer to basic services, and whether there are quantifiable measures for these services, which are easily available and verifiable, through surveys and/or secondary data. The parameters can be changed, or their number can be reduced or increased, to further improve upon the approach.
We chose the threshold at 70% or more population from an income group having minimum or more access to a service. This is a rather arbitrary choice. The threshold may be increased or lowered.
Finally, the actual data used in this description is not representative of entire Pune city. So the picture that emerges from this data, based on surveys in just one municipal ward, may not be an accurate representation of the situation in Pune city.
We are now in the process of developing a survey questionnaire focused only on the chosen 6 parameters, which will allow us to not only get data required for calculation of the indices, but will also give us a more nuanced understanding of access to these quality of life services. We believe that this can be an effective tool for a quick and easy assessment of socio-economic equity from an urban planning perspective for any Indian city.
Comments and suggestions are most welcome!
Samuchit Enviro Tech