Forecasting Groundnut Area, Production and Productivity in Rajasthan, India using ARIMA Model

S. B. Bhusanar and Satyveer Singh Meena

Asian Journal of Agricultural Extension, Economics & Sociology, 2023, vol. 41, issue 5, 6

Abstract: This paper presents an analysis of the area, production and productivity of groundnut in Rajasthan over the last thirty years and a forecast of these variables using the auto regressing integrated moving average (ARIMA) model. Descriptive statistics show that there was a large fluctuation in the lowest and maximum values of area, production, and productivity of groundnut in Rajasthan over the period of last thirty years. The ARIMA model was used to forecast the area, production, and productivity of groundnut in Rajasthan. The parameter estimates of the ARIMA model were used to determine the model fit statistics, including the R-squared value, which indicates how well the model fits the data. The Ljung-Box Q Statistics and the corresponding Sig. indicate that there is no significant autocorrelation in the residuals of the model. Finally, forecasts for 2021, 2022, 2023, 2024, and 2025 are presented, along with their corresponding upper and lower confidence limits. The results indicate that there is a considerable upward trend in area, production, and productivity of groundnut in Rajasthan over the last thirty years. The ARIMA model was found to be successful in forecasting the area, production, and productivity of ground. The findings of this paper can help in the formulation of better policies for groundnut production in Rajasthan.

Keywords: Crop; Production/Industries (search for similar items in EconPapers)
Date: 2023
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