This blog, meant for a general readership, is about my new paper Decomposing Poverty Change: Deciphering Change in Total Population and Beyond. This is published in The Review of Income and Wealth that is available under Early View and is also open access. A slide share explaining the method is also uploaded as Decomposing Poverty Change: Within- and Between-group Effects at my bepress page.
It is believed that growth in the economy would address poverty reduction through the trickle-down effect. At the same time, equitable distribution or lowering inequality will also help reduce poverty while also leading us towards a welfare state.
A question that assumes importance is that if in a society the incidence of poverty has reduced (say, from 50 per cent to 40 per cent) then then how much of this is on account of growth in the economy and how much is on account of reductions in inequality.
Conventionally, poverty reduction has tried to compute these two effects by holding the other constant. What is the growth effect, if inequality is held constant; and what is the inequality effect, if there is no growth.
While dealing with the changes in the proportion of poor, the population remains hidden. However, if the population consists of different subgroups (say, rural and urban) and the overall incidence of poverty is an weighted average then the changes in population shares between the subgroups could also have implications in our understanding of poverty reduction.
The literature refers to this change in population share as between-group effect (say, migration of people from rural to urban regions has helped reduced poverty in the rural regions, but it has increased it in urban regions while at an aggregate level it has helped reduce poverty). As against this, the growth and inequality effects are referred to as within-group effects.
Further, with the population being hidden, the conventional computations for delineating the effect of growth on poverty reduction have implicitly assumed that there is no change in total population. This is contrary to ground reality as also public policy concerns where increasing population has been an important aspect in designing appropriate poverty reduction strategies.
Keeping the change in total population in mind, I propose an alternative measure where growth, inequality and population can be considered as within-group effects and this would be independent of the between-group effect on account of changes in population shares across subgroups.
Using the method to Indian data for 2004-05 and 2009-10, one observes the following:
- At the aggregate all India level, poverty reduced from 37.14 per cent to 29.77 per cent (-7.37 percentage points).
- Growth effect led to a reduction in poverty by 187 per cent (-13.77 percentage points); from this, 69 per cent is from rural (-9.45 percentage points) and 31 per cent is from urban (-4.32 percentage points).
- Inequality effect led to an increase in poverty by 2 per cent (0.13 percentage points); from this there was a reduction in poverty by 308 per cent in rural India (-0.40 percentage points) and an an increase in poverty by 408 per cent in urban India (0.53 percentage points).
- Population effect (total change) led to an increase in poverty by 88 per cent (6.51 percentage points); from this, 63 per cent is from rural India (4.13 percentage points) and 37 per cent is from urban India (2.39 percentage points). The percentage point increase in rural and urban in this as also in some other instances may not add up to the aggregate level due to rounding off.
- Total within-group effects (growth + inequality + total population change) led to a reduction in poverty by 97 per cent (-7.13 percentage points); from this, 80 per cent is from rural India (-5.72 percentage points) and 20 per cent is from urban India (-1.41 percentage points).
- Between-group effect (change in population shares between rural and urban regions) led to a reduction of poverty by 3 per cent (-0.25 percentage points), from this there was a reduction of poverty in rural India by 263 per cent (-0.63 percentage points) and an increase in poverty in urban India by 163 per cent (0.39 percentage points). By definition, this will have a negative impact on one region and a positive impact on the other region. The results imply that at an aggregate level rural to urban migration is likely to have contributed to reductions in poverty.
- From the aggregate all India level reduction (-7.37 percentage points), the contribution of rural India was 86 per cent (-6.35 percentage points) and that of urban India was 14 per cent (-1.02 percentage points).
Getting back to the method, we mention that the computation of the three within-group effects will depend on the choice of the base period and the sequence of computations. Further, the three within group effects as also the between group effects, as shown in our results for India, can all be mutually exclusive. These are discussed in the paper.
The link to my open access paper Decomposing Poverty Change: Deciphering Change in Total Population and Beyond published in The Review of Income and Wealth. Also see the slide share explaining the method Decomposing Poverty Change: Within- and Between-group Effects that can be downloaded from my bepress page.
Some other recent blogs of mine on Poverty are: