Modeling and forecasting of egg production in india using time series models

Abstract

Aim: Eating habits have changed in India and this change has also affected protein consumption habits. The change in eating habits of egg products is an indication of this. Considering the population growth rate and the resulting increase in egg demand, the countries should increase their production of protein poultry products. Aim of the study was to obtain results for both policymakers and suppliers to develop strategies with the forecast of egg consumption. Materials and Methods: In this study, the production of Eggs in India is considered and forecasts are made by the several time series model such as the ARIMA, BATS, TBATS, and Holt'slinear trend. The testing data for the production of the egg is considered from 2015-2019. Results: It is detected that Holt's Linear Trend Model is the best fit model for forecasting. The MAPE values are obtained as 2.137%, 5.378%, 4.681%, and 1.392% by the best-fitted models BATS, TBATS, ARIMA (1,2,2), and Holt?s Linear Trend respectively. According to Holt?s linear trend Model, the Eggs production continues its upward trend in India. The Eggs production in India would be increased from 111350.3 to 148696.9 during the period 2019-2020 to 2023-2024. Conclusion: This study might help policymakers in the Livestock sector to under standard making strategies for the future to invest in it. Furthermore, it is important to make a strategic plan for eggs export, eggs supply, eggs demand, and eggs prices by the Indian government.

Keywords

• bats
• tbats
• arima
• holt?s linear trend method
• forecasting