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Public Investment in Agricultural Research and Extension in India


Earlier studies have empirically illustrated the significant role that investment in agricultural research and extension (R&E) plays in enhancing productivity, accelerating agricultural growth and reducing poverty in India. This article adds to the existing literature on the spatial and temporal dimensions of agricultural R&E investments with special emphasis on returns to investment in major states of India. The study reveals that significant structural changes have occurred in the pattern of agricultural R&E investments across sectors and states over the past five decades. R&E investments on the crop and fishery sectors improved over time at the expense of the livestock sector. Similarly, the states’ share in aggregate R&E investments declined over the years, while the centre's improved proportionately. Returns to investments differed significantly according to geography, with the states that had a higher share of total factor productivity growth in their output growth faring better than the rest in relative terms. The R&E investment in the crop sub-sector in India has been especially rewarding, generating returns that are close to 50 per cent. In general, the findings of the study suggest the engineering of a deliberate shift in focus from alternative types of investment to agricultural R&E to meet the future growth challenges in India's agriculture sector.


D’autres études précédents ont illustré de façon empirique le rôle que les investissements en recherche et extension agriculturale (en anglais: R&E) en Inde ont eu sur l’amélioration de la productivité, sur la croissance agricole, et sur la réduction de la pauvreté. Cette étude complémente la littérature existante en étudiant les dimensions spatiales et temporelles des investissements R&E, en particulier le retour sur investissements, dans le secteur agricultural en Inde. Cette étude révèle que, dans les cinq dernières décades, des changements structurels importants ont eu lieu dans le modèle des investissements en R&E agricultural dans plusieurs secteurs et régions Indiens. Les investissements R&E dans les secteurs des récoltes et pécheur ont augmenté au long du temps, au détriment du secteur du bétail. La proportion des investissements fait par le centre a augmenté, tandis que la proportion des investissements faits dans l’ensemble par les états a chuté. Le retour sur investissement est assez différent parmi les régions géographiques: les états indiens ou il y a une proportion plus grande de la croissance de la production du a une croissance de la productivité totale des facteurs, ont bénéficié relativement plus que d’autres états. L’investissement R&E dans le secteur des récoltes a été particulièrement intéressant, avec des rendements de presque 50%. En général, les résultats de cette étude suggèrent que, pour faire face aux défis de croissance agricole en Inde, il faudrait réaliser un changement dans le secteur de l’investissement, se focalisant sur l‘investissement en R&E agricultural, plutôt que sur d’autres alternatives.

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Figure 1
Figure 2


  1. 1.

    Refers to the index used to deflate current price estimates of GDP to constant prices. This is a better index compared to the wholesale price index to deflate macro variables at the country/state level.

  2. 2.

    Research and extension stock were constructed from this expenditure data using 5-year lag structure for research and three years for extension. The research and extension stock variable was constructed by summing up research investment of 5 years and extension investment of 3 years. The stock was defined as one-fifth of the spending in the previous year, plus two-fifths of the spending 2 years before, before plus three-fifths of the spending 3 years before, plus four-fifths of the spending 4 years before, plus the sum of all spending 5 years before and earlier. These weights are admittedly arbitrary and chosen to reflect the lower impact of research activity in the earlier stages. The extension stock variable was constructed by summing up 3 years’ extension investment by assigning weights as 1.0 in the year t−1, 0.8 in the year t−2 and 0.4 in the year t−3. These weights were chosen to reflect the higher impact of extension activity in the earlier stages (Evenson et al, 1999).

  3. 3.

    Only a single country-level elasticity of TFP with respect to R&E stock (estimated by Fan et al, 1999) was used in the analysis as state-specific elasticities were not available in the literature. This may be a limitation of the study as the underlying assumption is identical production functions across states.

  4. 4.

    We followed the ‘inverted V’ scheme for constructing the time weights. This scheme has three regions. The first, sloping upward, refers to the number of years between the first appearance of a research benefit and its full effect. During this time, the research outcome has an increasing impact. In this region of the V, research output (VMP) is multiplied by smaller fractions, while more distant results are multiplied by larger fractions, until at the top of the upward-sloping region, the weights become one. The second region, a horizontal plateau, refers to the number of years the research output can continue to make its full contribution. The weights remain equal to one here. The third region, sloping downward, represents a sort of decay of the contribution of the research. In this region, earlier research contributions are multiplied by weights that become successively smaller as time passes.

  5. 5.

    From here on, the results pertaining to Bihar, Madhya Pradesh and Uttar Pradesh correspond to the status before their bifurcations.


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Correspondence to Pramod Kumar Joshi or Praduman Kumar.


Appendix A

Table A1

Table A1 Share of investment in research and extension to agricultural GDP by state, India

Appendix B

Divisia-Tornqvist index for computing TFP

TFP measures the amount of increase in the total output, which is not accounted for by increases in the total inputs. It is defined as the ratio of an index of aggregate output to an index of aggregate input. One of the most defensible methods of aggregation in productivity measurement is Divisia aggregation. The Divisia Tornqvist index has been used in this study for computing the total output, total input, and TFP indices for different states of India for major crops, which included cereals, pulses, edible oilseeds, sugarcane, cotton, jute, onion, and potato, using the farm-level data. The output index includes the main products as well as by-products. Farm harvest prices have been used to aggregate the output. The input index includes seed, manure, fertilizer, pesticide/herbicide, human labour, animal labour, machine labour, irrigation and land (rental value of land). The following formulae were used for constructing the indices:

Total output index (TOI)

Total input index (TII)


R jt :

is the share of jth crop output in total revenue in year t,

Q jt :

is the output of jth crop in year t,

S it :

is the share of input i in the total input cost in year t, and

X it :

is the quantity of input i in year t.

For the productivity measurement over a long period of time, chaining indexes for successive time periods is preferable. With Chain-linking, an index is calculated for two successive periods t and t-1, over the whole period t0 to T, (sample from time t=0 to t=T) and the separate indexes are then multiplied together:

Total factor productivity index (TFP)

Chain-linking index takes into account the changes in relative values/costs throughout the period of the study. This procedure has the advantage that no single period plays a dominant role in determining share weights and biases are likely to be reduced. The above equations provide the indices of total output, total input, and TFP indices for the specified time ‘t’.

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Joshi, P., Kumar, P. & Parappurathu, S. Public Investment in Agricultural Research and Extension in India. Eur J Dev Res 27, 438–451 (2015).

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  • public investment
  • government expenditure
  • returns to investment
  • total factor productivity