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COVID-19 and prices of pulses in Major markets of India: Impact of nationwide lockdown

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  • Ranjit Kumar Paul
  • Md Yeasin

Abstract

The COVID-19 pandemic has impacted almost all the sectors including agriculture in the country. The present paper investigates the impact of COVID-19 induced lockdown on both wholesale and retail prices of major pulses in India. The daily wholesale and retail price data on five major pulses namely Lentil, Moong, Arhar, Urad and Gram are collected for five major markets in India namely Delhi, Mumbai, Kolkata, Chennai and Hyderabad during the period January, 2019 to September, 2020 from Ministry of Consumer Affairs, Food & Public Distribution, Government of India. The Government of India declared nationwide lockdown since March, 24, to May, 31, 2020 in different phases in order to restrict the spread of the infection due to COVID-19. To see the impact of lockdown on price and price volatility, time series model namely Autoregressive integrated moving average (ARIMA) model with error following Generalized autoregressive conditional heteroscedastic (GARCH) model incorporating exogenous variable as lockdown dummy in both mean as well variance equations. It is observed that in almost all the markets, lockdown has significant impact on price of the pulses whereas in few cases, it has significant impact on price volatility.

Suggested Citation

  • Ranjit Kumar Paul & Md Yeasin, 2022. "COVID-19 and prices of pulses in Major markets of India: Impact of nationwide lockdown," PLOS ONE, Public Library of Science, vol. 17(8), pages 1-16, August.
    • Handle: RePEc:plo:pone00:0272999
    DOI: 10.1371/journal.pone.0272999
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    References listed on IDEAS

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    1. Jody Harris & Lutz Depenbusch & Arshad Ahmad Pal & Ramakrishnan Madhavan Nair & Srinivasan Ramasamy, 2020. "Food system disruption: initial livelihood and dietary effects of COVID-19 on vegetable producers in India," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(4), pages 841-851, August.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
    4. Paul, R.K. & Saxena, R. & Bhat, S.A., 2016. "How Price Signals in Pulses are Transmitted across Regions and Value Chain? Examining Horizontal and Vertical Market Price Integration for Major Pulses in India," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 29(Conferenc).
    5. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Ankit Kumar Singh & Md Yeasin & Ranjit Kumar Paul & Anita Sarkar & A. K. Paul, 2026. "P‐WEV: PSO Based Weighted Ensemble Technique for Agricultural Food Price Volatility Modeling," Agribusiness, John Wiley & Sons, Ltd., vol. 42(3), pages 1482-1498, July.

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