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Understanding India’s Food Inflation: The Role of Demand and Supply Factors

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  • Rahul Anand
  • Naresh Kumar
  • Mr. Volodymyr Tulin

Abstract

Over the past decade, India has seen a prolonged period of high inflation, to a large extent driven by persistently-high food inflation. This paper investigates the demand and supply factors behind the contribution of relative food inflation to headline CPI inflation. It concludes that in the absence of a stronger food supply growth response, food inflation may exceed non-food inflation by 2½–3 percentage points per year. The sustainability of a long-term inflation target of 4 percent under India’s recently-adopted flexible inflation targeting framework will depend on enhancing food supply, agricultural market-based pricing, and reducing price distortions. A well-designed cereal buffer stock liquidation policy could also help mitigate food inflation volatility.

Suggested Citation

  • Rahul Anand & Naresh Kumar & Mr. Volodymyr Tulin, 2016. "Understanding India’s Food Inflation: The Role of Demand and Supply Factors," IMF Working Papers 2016/002, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2016/002
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    References listed on IDEAS

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    1. Kozicka, Marta & Kalkuhl, Matthias & Saini, Shweta & Brockhaus, Jan, 2014. "Modeling Indian Wheat and Rice Sector Policies," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169808, Agricultural and Applied Economics Association.
    2. Thangzason Sonna & Himanshu Joshi & Alice Sebastin & Upasana Sharma, 2014. "Analytics of Food Inflation in India," Working Papers id:6174, eSocialSciences.
    3. Timothy K.M. Beatty & Erling Røed Larsen, 2005. "Using Engel curves to estimate bias in the Canadian CPI as a cost of living index," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 38(2), pages 482-499, May.
    4. Richard Blundell & Alan Duncan & Krishna Pendakur, 1998. "Semiparametric estimation and consumer demand," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(5), pages 435-461.
    5. Rahul Anand & Ding Ding & Mr. Volodymyr Tulin, 2014. "Food Inflation in India: The Role for Monetary Policy," IMF Working Papers 2014/178, International Monetary Fund.
    6. Blanciforti, Laura & Green, Richard, 1983. "An Almost Ideal Demand System Incorporating Habits: An Analysis of Expenditures on Food and Aggregate Commodity Groups," The Review of Economics and Statistics, MIT Press, vol. 65(3), pages 511-515, August.
    7. Brian P. Poi, 2008. "Demand-system estimation: Update," Stata Journal, StataCorp LP, vol. 8(4), pages 554-556, December.
    8. Mr. James P Walsh, 2011. "Reconsidering the Role of Food Prices in Inflation," IMF Working Papers 2011/071, International Monetary Fund.
    9. Rakesh Mohan & Muneesh Kapur, 2015. "Pressing the Indian Growth Accelerator: Policy Imperatives," IMF Working Papers 2015/053, International Monetary Fund.
    10. Ganesh-Kumar, A. & Mehta, Rajesh & Pullabhotla, Hemant & Prasad, Sanjay K. & Ganguly, Kavery & Gulati, Ashok, 2012. "Demand and supply of cereals in India: 2010-2025:," IFPRI discussion papers 1158, International Food Policy Research Institute (IFPRI).
    11. Brian P. Poi, 2002. "From the help desk: Demand system estimation," Stata Journal, StataCorp LP, vol. 2(4), pages 403-410, November.
    12. Kumar, Praduman & Shinoj, P. & Raju, S.S. & Kumar, Anjani & Rich, Karl M. & Msangi, Siwa, 2010. "Factor Demand, Output Supply Elasticities and Supply Projections for Major Crops of India," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 23(1), January.
    13. Surabhi Mittal, 2010. "Application of the Quaids Model to the Food Sector in India," Journal of Quantitative Economics, The Indian Econometric Society, vol. 8(1), pages 42-54, January.
    14. Sen Gupta, Abhijit & Bhattacharya, Rudrani & Rao, Narhari, 2014. "Understanding Food Inflation in India," MPRA Paper 58319, University Library of Munich, Germany.
    15. Yatchew,Adonis, 2003. "Semiparametric Regression for the Applied Econometrician," Cambridge Books, Cambridge University Press, number 9780521812832, September.
    16. Deepankar Basu & Debarshi Das, 2014. "Social Hierarchies and Public Distribution of Food in Rural India," UMASS Amherst Economics Working Papers 2014-05, University of Massachusetts Amherst, Department of Economics.
    17. Blundell, Richard & Pashardes, Panos & Weber, Guglielmo, 1993. "What Do We Learn About Consumer Demand Patterns from Micro Data?," American Economic Review, American Economic Association, vol. 83(3), pages 570-597, June.
    18. Shweta Saini & Marta Kozicka, 2014. "Evolution and Critique of Buffer Stocking Policy of India," Working Papers id:6153, eSocialSciences.
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    Cited by:

    1. Sajjid Chinoy & Pankaj Kumar & Ms. Prachi Mishra, 2016. "What is Responsible for India’s Sharp Disinflation?," IMF Working Papers 2016/166, International Monetary Fund.
    2. Ginn, William & Pourroy, Marc, 2022. "The contribution of food subsidy policy to monetary policy in India," Economic Modelling, Elsevier, vol. 113(C).
    3. Chetan Ghate & Sargam Gupta & Debdulal Mallick, 2018. "Terms of Trade Shocks and Monetary Policy in India," Computational Economics, Springer;Society for Computational Economics, vol. 51(1), pages 75-121, January.
    4. Chandana Maitra & Sriram Shankar & D.S. Prasada Rao, 2016. "Income Poor or Calorie Poor? Who should get the Subsidy?," Discussion Papers Series 564, School of Economics, University of Queensland, Australia.
    5. Holtemöller, Oliver & Mallick, Sushanta, 2016. "Global food prices and monetary policy in an emerging market economy: The case of India," Journal of Asian Economics, Elsevier, vol. 46(C), pages 56-70.
    6. Akash Malhotra & Mayank Maloo, 2017. "Understanding food inflation in India: A Machine Learning approach," Papers 1701.08789, arXiv.org.

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