In their recent book The Paradox of India’s North–South Divide, Samuel Paul and Kala Sridhar discuss how and why Tamil Nadu and Uttar Pradesh have diverged quite significantly over the past 30 years. While their aim was to establish factors that primarily improve per capita incomes of the southern states, the book is limited to those two states largely. And was almost asking the reader to do a wider analysis for oneself. So, let’s look at a wider set of states. Let’s also include what one thought was an important factor that was missed in the analysis: population growth of each state.
Let’s consider 16 large states and their per capita incomes in 1961 and 2012.
|State||Per Capita Income (1960)||Relative Rank in 1960||Per Capita Income (2012)||Relative Rank in 2012||Movement in Relative Ranking|
|Jammu & Kashmir||267||13||52250||11||+2|
50 years is a reasonable time frame. And the data is quite remarkable. Kerala and Tamil Nadu had per capita incomes that were almost the same as that of Madhya Pradesh and Assam respectively in 1960. In 2012, Kerala had a per capita income that’s about twice that of Madhya Pradesh; Tamil Nadu had a per capita income that was well over twice that of Assam in 2012. Maharashtra and Gujarat have held on to their relative wealth. Andhra Pradesh (including Telangana for the purpose of this analysis) and Karnataka continue to be stuck in the middle. While West Bengal, apart from Assam, has seen a collapse in its relative wealth; Punjab, still wealthy, has lost its position a bit.
The relative movement, interesting in terms of challenging our political conceptions, does not tell us much. A far more interesting comparison is to look at growth rates of per capita income and compare it to actual NSDP growth.
|State||Per Capita Income CAGR||NSDP CAGR||Population Growth Rate(1961 – 2011)|
|Jammu & Kashmir||10.68%||13.71%||1.43%|
The two data tables taken together for the states of Tamil Nadu and Gujarat tell a very important story: while Gujarat’s NSDP was growing slightly faster than Tamil Nadu’s, the latter had a faster growth of per capita income. Simply because it had a lower rate of population growth. So, in 1960, Gujarat had a higher per capita income compared to Tamil Nadu. And in absolute terms, its economy grew slightly faster than Tamil Nadu in the past 50 years. Yet, at the end of those 50 years, the average Tamil is richer by about 1,652 rupees.
Kerala and Tamil Nadu, thus, aren’t growing faster than others. Just that they are growing just as well as others with fewer babies. Tamil Nadu has a TFR of 1.7 and Kerala’s is 1.8; Gujarat’s TFR was 2.5 in 2010. This story repeats itself with a far greater growth dampening effect in the case of Madhya Pradesh and Bihar. Both states had TFRs greater than 3 in 2010.
On the other hand, fewer babies isn’t a sufficient condition for doing well. West Bengal with a TFR of 1.7 sadly explains that. If we treat per capita income as an independent variable, the relative weights between NSDP growth and population growth is still skewed towards the former as shown the chart. But among relatively well governed states, the difference in growth is negligible while that in TFR isn’t.
The other factor that’s implied by Paul and Sridhar is that States with a greater share of services in their NSDP tend to break out compared to states that have a higher contribution of agriculture or manufacturing. This combined with low fertility is likely to open the advantage of states with high literacy and low TFR even further. Whether this adds a cleavage towards secession in the future will be worth watching.
 – The data for 1961 per capita income, NSDP figures was from these statistical tables. The data for 2012 NSDP Figures were found here; and the Per Capita Income was from Planning Commission. None of the figures have been adjusted for inflation. I assume because they are compared and relative movement is what’s used for analyses, that’s reasonable. If you think otherwise, please let me know. Madhya Pradesh, Bihar and Andhra Pradesh have been treated as undivided states. I calculated Population Growth Rates using Census Data of 1961 and 2011.
 – The details of regression and relative weights from R are as follows,