A key challenge for many developing countries is to promote growth by reducing the misallocation of factors of production — labour, capital, and land. Huge gains in growth can be made by reducing factor misallocation. Growth requires more efficient firms to produce more output and use more factors of production.
Which factor market is most distorted in India? There is mounting evidence that land misallocation is worse than labour misallocation. Low-productivity firms have better access to land and buildings than high-productivity firms. Indeed, land misallocation appears to be at the root of much of the misallocation of output in the manufacturing sector.
If land is misallocated, is capital also misallocated? There is an important reason to suspect that the two are connected. Most bank loans require some form of collateral to guarantee the loan. Land is simply the best form of collateral due to its immobility (i.e. the debtor can’t run off with land). This can be contrasted with a piece of specialised machinery, for example, where the borrower could seek to hide it from debt collectors or where its sale to other parties after repossession is weak. This difference is visible in terms of the amount of loan collateral possible against asset classes.
While borrowers can often pledge 80 per cent of land values against loans, for most other forms of fixed investment the loan-to-collateral value ratio is substantially lower (e.g. 25 per cent). So, if land markets are highly distorted, then it is likely that the bank loan allocation is also distorted, given the misplaced collateral channel. This can in turn lead to its own economic consequences. For example, rapidly growing firms in asset-intensive sectors require external finance due to their capital growth needs. If this is reduced due to land misallocation, this would help explain why India’s firms have trouble scaling up, or why the pace and scale of manufacturing trend has slowed down.
Illustration: Binay Sinha
Poorly functioning land markets may explain why there are so few start-ups in the manufacturing sector in India, given that that start-ups are often backed by bank loans for which land is used as collateral (see, D Gilles, E Ghani, A Goswami, and W Kerr. “Effects of land misallocation on capital allocations in India”, Policy Research Working Paper Series 7451, The World Bank).
Impact of financial misallocation
A detailed examination of millions of manufacturing enterprises in some 600 districts shows some striking trends in India’s financial misallocation:
First, a very low proportion of manufacturing establishments access financial loans in India (8 per cent).
Second, this low average masks huge spatial, sectoral, and gender differences. It is significantly higher in leading regions compared to lagging regions. Leading states such as Maharashtra show an important depth of financing for firms. At the other extreme are states such as Bihar where access to loan is very low.
Third, firms in the organised sector have much higher access to loans compared to firms in the unorganised sector. States like Gujarat, Punjab, Haryana, and Rajasthan have access to financial loans for over 95 per cent of the organised sector plants. Lagging states perform poorly in providing credit support for both the organised and unorganised sectors.
Fourth, irrespective of the urban/rural location, the share of plants accessing external loans in the organised sector has increased over time. By contrast, it has declined for the unorganised sector.
Fifth, there are urban-rural disparities in access to finance, with rural locations lagging their urban counterparts.
Sixth, and most importantly, there is significant disparity against women-owned enterprises. Although the gap between the access shares of female employee-dominated plants vis-à-vis male employee-dominated plants is closing in the organised sector, this gap is not shrinking in the unorganised sector.
Factor misallocation and productivity growth
It is widely recognised that growth can be enhanced by the reallocation of the factors of production from less-productive to more-productive firms. Thus, the ranking of firms by factor usage should reflect their relative productivity ranking and hence be perfectly correlated under optimum allocation. Conversely, a less-than-perfect correlation between productivity and factor usage indicates a misallocation of factors across firms. The lower this correlation between productivity and factor usage, the greater is the extent of misallocation of factors of production.
We computed an index of misallocation in all the districts in India for the organised and unorganised sectors separately. The indices of misallocation for output, value added, and factors of production were computed individually for factors such as labour and the extent of financial loans. These measures of misallocation were then used in various district-industry level regressions to examine both the determinants and the implications of misallocation, especially how the misallocation in access to finance is linked to the misallocations in land and buildings and labour. Empirical evidence provides substantial confirmation in the links between land misallocation and financial misallocation at the district level.
Looking to the future
Policy makers need to pay more attention to addressing the underlying causes of factor misallocation, especially land and financial misallocation to address the twin balance sheet challenge of India. Bank and corporate restructuring may not be enough to put growth on a higher trajectory. This would involve removing land market distortions, better land-use regulations, and more efficient taxation of properties. Faster growth requires marching ahead with even stronger policy reforms to promote competition, and enable more efficient firm to grow faster.
Making growth more inclusive also needs more attention. The unorganised sector accounts for nearly 80 per cent of employment and about half of the value of land and buildings held in the manufacturing sector. Yet, the value of financial loans reported in this sector is barely 2-6 per cent of the value of total loans reported in the manufacturing sector. Much more striking is the huge disparity against women-owned enterprises, where the gap is increasing. These gaps should also be addressed as an integral part of overcoming the twin balance sheet challenge.
The writer is lead economist, World Bank