The first step towards raising agricultural income is understanding, on a State by State basis, the unique binding constraints in order of priority. Policy intervention should be a later concern. A lot has been said about the NDA government’s strategy towards doubling farmers’ income and the subsequent recommendations by a specially constituted committee on it. Unlike in the past, the core theme of this round of policy recommendations has been to consider farmers’ income as the fulcrum of strategy. The report has laid out multiple recommendations for achieving the goal of doubling farmers’ incomes by 2022. However, it must be noted that most of these recommendations are the outcome of a top-down approach at the Union level, even though much of these policy decisions need to be undertaken by State Governments. Moreover, only some of these recommendations pertain to particular States and these are to be identified after examination at the ground level, which was not undertaken in the committee’s deliberations. Out of the seven-year period set for doubling of farmers’ income, three full agricultural years have already gone. There is, therefore, a daunting task ahead. Finally, even though committee reports provide estimates of the investment required to double farmers’ income, no attempt has been made to sequence investment needs. After all, given the fund constraints for investment and time limitation, the top priority should have been to identify the most binding constraints for increasing farmers’ income state-wise and allocate funds accordingly.
The binding constraints to farmers’ income or economic activity at the State level differ depending on the natural, political and institutional settings. A better understanding of these constraints helps to devise appropriate policy for efficient allocation of scarce financial resources. The methodology of growth diagnostics is conceptualised as a decision tree, which follows a top-down approach. This methodology developed by Hausmann et al (2008) considers the hierarchy of distortions, from the largest to the smallest. The strategy could be to start reducing the largest distortion to the level of the next largest and then proceed in a similar way in the subsequent round. This strategy is found to have welfare-improving effects. However, this requires a complete list of constraints, which is difficult to obtain and is unknown explicitly.
According to Hausmann et al (2008), the best strategy, therefore, is to focus on reforms that would alleviate the most binding constraint. The relaxation of the most binding constraint is guessed to have the largest direct effects on farmers’ income/ welfare. Since it is impractical to identify the full list of constraints, it is useful to start focussing on proximate determinants of economic growth (e.g. infrastructure). After identification of proximate determinants, one should search for their associated economic distortions (e.g. tax, corruption, finance), the removal of which would have the largest impact on farmers’ economic growth. Of course, it is not easy to identify these distortions.
The strategy is to start with aggregate outcome such as economic growth (agricultural income growth in case of agricultural sector) and its proximate determinants. In the context of a particular country, Hausmann et al (2008) began the diagnostic of economic growth through three proximate determinants — returns on accumulation, private appropriability and cost of financing accumulation. The first stage is to identify which of these three factors is the greatest obstacle to economic growth. In the next stage, distortions associated with most binding constraints or most severe of these constraints are to be identified. The most common distortions include inadequate infrastructure, poor property rights and corruption. In short, the growth diagnostic approach starts with determinants of economic growth and then role of distortions that underline the binding constraints.
A proper diagnosis of economic growth involves identification of the correct maladies (binding constraints). As discussed earlier, the idea of growth diagnostics is that not all the constraints affect economic growth equally and that an appropriate strategy should consist of identifying most serious constraints. Hence, success of growth diagnostics depends on identification of drivers of growth and then most binding constraints on growth drivers. Policy reforms can be prioritised for unleashing the most binding constraints on growth. Economic theory and evidence help in identification of growth drivers and binding constraints.
The discussion in the above sections provides insights into the details of growth diagnostics framework and possible analytical tools that can be used to identify the determinants of agricultural output growth. Since the profit-maximising objective function behind a producer is to equate marginal revenue to marginal cost, a producer would produce to the point where this condition holds. Of course, the producer as well as policy makers can make interventions to shift the producing point by removing constraints.
What are the binding constraints for raising agricultural income on the input and output side? Agricultural output growth depends on farm size, yield (technology), price and crop/enterprise diversification. Similarly input use depends on availability of seed, fertiliser, pesticide, labour, machinery, irrigation and credit. Suppose that the overarching problem is why has agricultural growth in states slowed down during the recent years? Application of growth diagnostics involves asking a series of questions about the binding constraints on growth determinants. For instance, if the problem seems to be a low scale of farming, is that due to poor soil quality, inadequate irrigation facility, expensive labour and government restriction on a particular cropping pattern? Is the low scale of farming also due to insecure land tenure, fragmented land holdings, higher rent or restrictions on land leasing? Yield is an important driver of output growth. If low crop yield appears to be a problem, is that due to lack of access to new technology, high cost of technology, failure of technology, poor training of farmers to use the technology, low agricultural research and development expenditure, high taxes or poor definition of property rights? Similarly, binding constraints on other determinants of output growth can be identified and then the remedies worked out.
On the input side, farmers could face a situation where they get lower returns from the modern inputs and hence low motivation, resulting in underinvestment on high pay-off inputs. If the problem is with non-availability of quality inputs, is that due to corruption, poor quality control, poor delivery system and high cost? If the problem is over the use of inputs affecting sustainability of production, is that due to subsidy, poor regulation or lack of awareness? Similarly, if high cost of financing is a problem, is that due to poor intermediation, low banking density or dominance of informal financing? In a similar way, binding constraints on specific inputs such as fertilisers, seed, labour, irrigation and machinery can be identified and suitable remedies designed to remove the constraints.
Understanding unique binding constraints in order of priority, State by State, is a first step towards raising agricultural income. The policy actions aiming at removing distortions or making investment form the next step.
(The authors are Associate Professor, Centre for the Study of Regional Development, School of Social Sciences, JNU and Professor, NCAER respectively. The views expressed are personal).
Writer: Elumalai Kannan and Sanjib Pohit
Courtesy: The Pioneer