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Supply response of Indian farmers: Pre and post reforms

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  • G. Mythili

    (Indira Gandhi Institute of Development Research)

Abstract

Supply response to price changes is likely to increase with the increasing liberalization of the agricultural sector. Past studies revealed weak supply response for Indian agriculture. There are no recent reliable estimates to see if the response has improved after the economic reforms introduced in early 90s in India. This study estimates supply response for major crops during pre and post reform periods using Nerlovian adjustment cum adaptive expectation model. Estimation is based on dynamic panel data approach with pooled cross section - time series data across states for India. The standard procedure is to use area as an indicator of supply due to the reason that area decision is totally under the control of farmers. Moreover using supply conceals some variations in area and yield if they move in the opposite directions. In this paper, it is hypothesized that acreage response underestimates supply response and farmers respond to price incentives partly through intensive application of other inputs given the same area, which is reflected in yield. Acreage and yield response functions were estimated and the supply response estimates were derived from these two responses. The significant feature of the specification used in the study is both main and substitutable crops are jointly estimated by a single equation by introducing varying slope coefficients to capture different responses. As expected, foodgrains reveal less response than non-foodgrains. The study found no significant difference in supply elasticities between pre and post reform periods for majority of crops. It raises questions such as whether the constraints are properly identified by the policies or if the impact of reform is yet to be felt in order to make a prominent impact on response parameters. In this study, infrastructural variables other than irrigation could not be introduced due to lack of information for a long time series. Results confirmed that farmers respond to price incentives equally by more intensive application of non-land inputs. Further analysis of the reasons for little impact of reforms on the responses is awaited.

Suggested Citation

  • G. Mythili, 2006. "Supply response of Indian farmers: Pre and post reforms," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2006-009, Indira Gandhi Institute of Development Research, Mumbai, India.
  • Handle: RePEc:ind:igiwpp:2006-009
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    File URL: http://www.igidr.ac.in/pdf/publication/WP-2006-009.pdf
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    References listed on IDEAS

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    1. Marc Nerlove, 1979. "The Dynamics of Supply: Retrospect and Prospect," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 61(5), pages 874-888.
    2. Pandey, L.M. & Kumar, Sant & Mruthyunjaya, 2005. "Instability, Supply Response and Insurance in Oilseeds Production in India," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 18(Conferenc).
    3. Nowshirvani, V F, 1971. "Land Allocation under Uncertainty in Subsistence Agriculture," Oxford Economic Papers, Oxford University Press, vol. 23(3), pages 445-455, November.
    4. Mittal, Surabhi & Kumar, Praduman, 2000. "Literacy, Technology Adoption, Factor Demand and Productivity: An Econometric Analysis," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 55(3), September.
    5. Eckstein, Zvi, 1984. "A Rational Expectations Model of Agricultural Supply," Journal of Political Economy, University of Chicago Press, vol. 92(1), pages 1-19, February.
    6. Unknown, 1962. "A Note on the Elasticity of the Marketable Surplus of a Subsistence Crop," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 17(3), pages 1-7.
    7. Nerlove, Marc, 1971. "Further Evidence on the Estimation of Dynamic Economic Relations from a Time Series of Cross Sections," Econometrica, Econometric Society, vol. 39(2), pages 359-382, March.
    8. Larry G. Epstein, 1981. "Duality Theory and Functional Forms for Dynamic Factor Demands," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 48(1), pages 81-95.
    9. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    10. Jere R. Behrman, 1966. "Price Elasticity of the Marketed Surplus of a Subsistence Crop," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 48(4_Part_I), pages 875-893.
    11. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
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    Cited by:

    1. Antony, Nyerere, 2016. "Determinants Of Rice Supply In Tanzania," Research Theses 276426, Collaborative Masters Program in Agricultural and Applied Economics.
    2. Parappurathu, Shinoj & Kumar, Anjani & Kumar, Shiv & Jain, Rajni, 2014. "Commodity Outlook on Major Cereals in India," Policy Papers 344972, ICAR National Institute of Agricultural Economics and Policy Research (NIAP).
    3. Tara Mitchell, 2014. "Is Knowledge Power? Competition and Information in Agricultural Markets," The Institute for International Integration Studies Discussion Paper Series iiisdp456, IIIS.
    4. Abu, O. & Okpe, A.E. & Abah, D.A., 2018. "Effects of Climate and Other Selected Variables on Rice Output Response in Nigeria," Nigerian Journal of Agricultural Economics, Nigerian Journal of Agricultural Economics, vol. 8(1), October.
    5. Shinoj Parappurathu & Anjani Kumar & Shiv Kumar & Rajni Jain, 2014. "A Partial Equilibrium Model for Future Outlooks on Major Cereals in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 8(2), pages 155-192, May.

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    More about this item

    Keywords

    Dynamic panel model; supply elasticity; acreage and yield response;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

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