Production status, market integration and the law of one price: An exploration of the major maize markets of India Bansal Surbhi1, Mohapatra Shruti2, Gohain Namami3,*, Das Arghyadeep4 1Assistant Professor, Khalsa College, Amritsar-143002 (Punjab) 2Assistant Professor, Sri Sri University, Cuttack-754006 (Odisha) 3Assistant Professor (Economics), Department of Economics and Sociology, Punjab Agricultural University, Ludhiana-141004 (Punjab) 4Asssistant Professor, Amar Singh (PG) College, Lakhaoti-203407 (Uttar Pradesh) *Corresponding author's email: namami@pau.edu
Online published on 4 February, 2023. Abstract The study looked at the area, production, and yield performance of the maize crop in India, as well as the market integration status of the country's key maize-producing states. The study included the years 1960 through 2019. Johansen co-integration, the Granger Causality Test, the compound annual growth rate (CAGR), and ARIMA, anAuto-regressive Integrated Moving Average, were used in the analysis. The findings showed that India experienced the highest growth in maize crop output and consistent increases in area, production, and yield. The ACF and PACF of the different series showed that the most appropriate models for forecasting based on the diagnostics, such as ACF, PACF, AIC, SBC, etc., were found to be ARIMA (0, 1, 0) for the area, ARIMA (2, 1, 3) for production, and ARIMA (2, 1, 1) for yield. In the next five years, from 2020 to 2025, the chosen ARIMA model anticipated a rise in maize area, production, and yield of 10.58 million ha, 35.65 MT, and 3390.50 kg/ha. The market integration status depicted a unidirectional causality from the Punjab market to the other two selected markets (Madhya Pradesh and Uttar Pradesh).At the same time, Madhya Pradesh and Uttar Pradesh showed no causality between them. Therefore, there is a need for policy involvement to develop market intelligence in every market as well as to enhance online marketing systems through networking and computerization. Top Keywords ARIMA, Forecasting, Granger causality, Integration. Top |