First Post – India: Regional Disparity in Growth (#1)
COMMENTS ON ECONOMIC LITERATURE
- Solow-Swan Model: (hereafter, SS model):
According to this, due to diminishing returns to capital, poorer regions which have short supply of capital, should exhibit higher marginal rates of return on investment than richer regions which have larger capital, and hence higher capital-output ratio. Hence, for any given rate of investment, the growth rate of a region with lower per capita output tends to grow faster than the region with a higher per capita output. This convergence is sometimes known as the “catch up” hypothesis.
However, this convergence was not found to take place in India. There is a positive, instead of negative (as suggested by SS model), correlation between initial per capita output and subsequent growth rate across states. Private investment is also found to be distributed disproportionately in favour of the richer states, thereby contradicting the expectation from SS model. Even within states, there is a tendency to concentrate industrial and infrastructural projects in more developed, urban and metropolitan areas.
Bakshi et al (2011) categorically state that ‘regional backwardness in India is a moving frontier with the most intense forms of poverty and deprivation getting increasingly concentrated within enclaves of backwardness’.
- Barro and Sala-i-Martin regression model:
These concepts relate to beta (β)-convergence and sigma (σ)-convergence. σ-convergence means that the per-capita income of poor regions become less disperse compared to that of richer regions. The concept of β-convergence suggests that poorer regions tend to grow faster than the richer ones and are hence able to catch up with them in the long run.
σ-convergence is elusive because we find that there is increasing polarisation between the rich and poor states over the decades. β-convergence is also unseen as the growth rate of per-capita income has also been high in richer states. Off late, however, some poor and slow states like Bihar, Uttar Pradesh and Assam have sped up considerably compared to their richer counterparts.H
- Harrod-Domar Model:
It explains economic growth in terms of savings rate and capital–output ratio. High level of individual savings are channelized into productive investments leading to greater output of goods and services. Similarly, with a decrease in capital–output ratio, more output is produced with fewer inputs.
This model seems to better explain the regional diversity in growth with both its variables being favourable for high per-capita income states. Capital output ratio has been skewed against backward regions as locational controls and programmes to promote industries in these areas have been gradually withdrawn to promote freer markets and global participation. Furthermore, capital is more mobile than labor, especially unskilled labor – which is more common in poor regions, which further exacerbates these differences. Since marginal propensity to save (MPS) is greater for relatively well-off states, they have higher savings rate – a determinant for private investment.
Williamson (1965) suggests the bias in favour of rich regions in licensing and tariff policy, the major instrument of planning and control, reverses once a threshold of national development is reached. However, it seems this threshold was never reached in India as the concentration of factories and PSUs in rich states suggest. Post-liberalization market forces reinforced this disparity in terms of investment. Hence, the spread effects of technical and social change and income multipliers have only slowly trickled down. Hence, widespread polarisation in terms of economic and social development has been observed.
- Myrdal’s Spread and Backwash Effect:
Backwash effect suggests that if an area in a country starts growing, it causes labor and capital (much more mobile than labor) from other parts of the country to gravitate towards this growing centre. Spread suggests the opposite that growth in one place, spreads to its suburbs and all the adjoining areas.
In India, it appears that backwash effects have largely predominated the spread effects. While satellite cities around centers like New Delhi, Kolkata, Mumbai, Bangalore, Hyderabad, Chandigarh, Ahmedabad etc. suggest spread effect has taken place. However, the gravitation of skilled labor migration and public as well as private investment in such narrow pockets show that agglomeration overshadows the positive spillovers. To begin with, the choice of these cities are affected by the distribution of natural resources, availability of health, education and transport facilities, access to major markets including foreign markets, distribution of inherited know-how and labor skills.
While distribution of natural resources is an important factor, access to market and capital seems to be much more significant as we find that the mineral-rich states like Jharkhand, Chhattisgarh, Orissa etc are still largely poor. On the other hand, coastal cities with access to ports and centers with access to financial capital have grown along with their neighbouring regions. It’s easy to see how this occurs. Capital rich industrial centers connect to their sources of cheap inputs and markets through roads, railways and ports. Subsidiary industries connected to the main industry also set up in the same region for ease of transportation, and thus a whole set of industries emerge in one hub. While the center spreads, this spread is limited to a small radius. In India, we also see a growth in the settlements of migrants from poor areas, dependent on daily wages, in and around these pockets.
The growth of manufacturing sector since the 1990s has been concentrated in a few developed states and large cities as the locational controls and programmes to promote industries in backward regions have been gradually withdrawn. This has accentuated the interstate and intrastate disparity in industrial development. (Gupta & Kundu, 1996)
An interesting new study (Chakravarty & Dahejia, 2016) correlates luminosity and state GDP. 380 of the 387 districts in the twelve most populous states (~ 85% population) are on average just one-fifth as bright as the metro cities of Mumbai and Bangalore at night. Even excluding the metros, 90% of all districts are just one-third as bright in the night as the top 10% of all districts. It also finds that this ratio is only worsening between 1992 and 2013.
A high initial share of agriculture seems to lead to relatively lower growth subsequently. The initially poor-and slow- growing states which had agriculture shares above the national average had, by 2004, significantly reduced their dependence on agriculture, to levels well below the previous average. In Bihar, in particular, the shift away from agriculture has continued in more recent years. (Ghate & Wright, 2013)
However, this may not necessarily be a positive development in terms of regional equity because this share has not gone to manufacturing sector either, while the growth has been significant. This growth may have concentrated in the capital cities and mainly in service sector, hence accentuating intra-state disparities.
Ironically, many economists, including in the Planning Commission (Second Five-Year Planning) felt that the objective of reducing inter-regional inequality can have an adverse bearing on the national output by curtailing efficiency and can even exacerbate the said inequality. Consequently, they suggested that goals of regional development and parity could be focused on when the national cake has grown sufficiently and when such an exercise will not significantly hamper economic progress.
Contrary to the aforesaid concerns, some economists felt that greater regional equity as a goal was essential for rapid growth. The logic of delayed profitability involving time-preference was central to these arguments. From the improvement and convergence in health and literacy figures across states, it seems that the logic of delayed profitability has indeed been realised in these sectors, disparity is still considerable.
While the rhetoric of ‘development of weaker states’ has been a constant feature of Indian politics, it has always been sacrificed at the altar of national growth focussed on growing the pie to divide it more equitably in a supposedly distant future. Planning for regional imbalance has been at best weak and at worst negligent and negligible (Bhagwati, 1970). Reduction of regional disparities had not been considered important enough as the recommendations of the successive Finance Commissions, except Fifth, are not in line with this objective (Reddy, 1972)
Changing Economy and Politics 