Forecasting of milk production in Tamil Nadu: an application of Arima model

C. Balan; M. Thirunavukkarasu; G. Senthil Kumar; M. Boopathy Raja

doi:10.56093/ijvasr.v48i6.173215

Authors

C. Balan Assistant Professor, Department of Animal Husbandry Statistics and Computer Applications, Faculty of Basic Sciences, Madras Veterinary College Campus, Chennai - 600 007
M. Thirunavukkarasu Professor and Head, Department of Animal Husbandry Statistics and Computer Applications, Faculty of Basic Sciences, Madras Veterinary College Campus, Chennai - 600 007
G. Senthil Kumar Assistant Professor, Office of the Registrar, TANUVAS, Chennai - 600 051
M. Boopathy Raja Assistant Professor, Department of Veterinary and Animal Husbandry Extension Education, Veterinary College and Research Institute, Tirunelveli - 627 351

https://doi.org/10.56093/ijvasr.v48i6.173215

Keywords:

Milk Production, Tamil Nadu, Forecasting, ARIMA model

Abstract

A study was made to forecast the milk production in Tamil Nadu, using the milk production data of the State from 1978-79 to 2018-19 and the Auto Regressive Integrated Moving Average (ARIMA) model for estimating future milk production. The autoregressive (p) and moving average (q) parameters were identified based on the significant spikes in the correlogram plots of Partial Auto Correlation Function (PACF) and Auto Correlation Function (ACF) of time series data. The adequacy of the fitted model was verified by the test of significance of residuals using Box-Ljung statistic. The results indicated that ARIMA (0, 1, 0) model was found to be the good model, based on the minimum values of selection criteria, viz., Akaike Information criteria (AIC) and Bayesian Information Criteria (BIC). The results also indicated the non-significance of Box-Ljung statistic and that the residual was normally distributed. Based on the model, the predicted figures of milk production for the next five years will be viz., 2019-20, 2020-21, 2021-22, 2022-23 and 2023-24 are 8529, 8696, 8863, 9030 and 9197 thousand tons in the State, respectively.

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