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.