Inclusive Growth vs Marginalisation: Concept, Measurement, Issues (A Public Policy Perceptive)

The eleventh five-year plan laid great emphasis on faster and more

inclusive growth. Yet, nowhere in its three volumes is the term inclusive growth

explicitly defined. This is unfortunately a common sight in the realm of public

policy. Policies are often formulated without a clear sight on what exactly it

hopes to achieve. Preconceived notions might blur the line on how one goes

about defining who form the marginalised. It is therefore vital, that one remains

objective when making such definitions.

However, defining the problem is just the first step in public policy. Data

and statistics also play a crucial role. Often, policy formulations rely on back of

the envelope calculations. Hence, policies formed may be grand, but they also

must have the tools and the statistics to hold them up. These policies must be

supplemented by alternatives, monitoring and evaluation, which completes the

policy cycle.

Coming back to the problem of defining inclusive growth, one only needs

to work backwards to understand it. The 1 st dimension of growth is the provision

of employment and participation in economic activity. This is followed by

income earned for effort and households experiencing an improvement in

welfare. The question which follows is how do you measure it?

One such macro measure is the elasticity of mean consumption with

reference to mean income. The impetus behind this measure is that an economy

which witnesses a fluctuating consumption pattern as a consequence of varying

income levels is likely to tread on the path of inclusive-growth. Moreover, this

measure can be supplemented by analysing the responsiveness of mean

consumption at different levels of median consumption. Elasticity of mean

consumption greater than one implies that the economy is approaching a broad-

based growth. A micro measure of inclusive growth is the inclusion coefficient

for consumption distribution.

One real life application of such analysis is done in Maharashtra. If one

considers the per capita income of the state of Maharashtra, it is one of the

riches states in the country. However, if you consider the per capita

consumption, it is one of the poorest states of the nation. In such a case, it is

crucial that one uses statistics like median over mean, to measure

marginalisation.

The problem in Maharashtra was pinpointed to be the high segmentation of the market due to differences in citizen’s access to public services. Having

identified this heterogeneity, the next question is the magnitude. An Engle

relations curve of rural Maharashtra, which depicts the multivalued function of

expenditure, draws a good picture of the problem. The segmentation highlights

how direct cash transfer is not an apt solution. Rather for sustainable inclusive

growth, one must turn towards measures such as public distribution system.

Doing so would make the policy decision-centric and goal-driven and succeed

in tackling the root of the problem.