Content area
Abstract
This study uses yearly data from 1961 to 2018 to forecast milk production in South Asian countries (including China) using ARIMA/GARCH models and Holt’s Linear approach. It is revealed that not all the methods are equally effective in forecasting. Comparison of mean absolute percentage errors between ARIMA and Holt’s Linear model shows that Holt’s approach reveals higher errors.ARIMA forecasting results show that India will be the country with the highest milk production, followed by Pakistan and China while GARCH model fits better to Bangladesh. This paper has policy implications as it can be used for the proper planning of dairy products in the South-Asian counties to safeguard nutritional security.
Details
Title
Modeling and forecasting of milk production in the SAARC countries and China
Author
Mishra Pradeep 1
; Adelajda, Matuka 2 ; Abotaleb Mostafa Salaheldin Abdelsalam 3 ; Weerasinghe W P M C N 4 ; Karakaya Kadir 5 ; Das, S S 6
1 College of Agriculture, J.N.K.V.V., Powarkheda, India (GRID:grid.444466.0) (ISNI:0000 0001 0741 0174)
2 University of Macerata, Department of Economics and Law, Macerata, Italy (GRID:grid.8042.e) (ISNI:0000 0001 2188 0260)
3 South Ural State University, Department of Electrical Engineering and Computer Science, Chelyabinsk, Russia (GRID:grid.440724.1) (ISNI:0000 0000 9958 5862)
4 University of Kelaniya, Department of Statistics and Computer Science, Kelaniya, Sri Lanka (GRID:grid.45202.31) (ISNI:0000 0000 8631 5388)
5 Selçuk University, Faculty of Science, Department of Statistics, Konya, Turkey (GRID:grid.17242.32) (ISNI:0000 0001 2308 7215)
6 Birsa Agricultural University, Ranchi Agriculture College, Ranchi, India (GRID:grid.444698.3) (ISNI:0000 0001 0667 7168)
; Adelajda, Matuka 2 ; Abotaleb Mostafa Salaheldin Abdelsalam 3 ; Weerasinghe W P M C N 4 ; Karakaya Kadir 5 ; Das, S S 6 1 College of Agriculture, J.N.K.V.V., Powarkheda, India (GRID:grid.444466.0) (ISNI:0000 0001 0741 0174)
2 University of Macerata, Department of Economics and Law, Macerata, Italy (GRID:grid.8042.e) (ISNI:0000 0001 2188 0260)
3 South Ural State University, Department of Electrical Engineering and Computer Science, Chelyabinsk, Russia (GRID:grid.440724.1) (ISNI:0000 0000 9958 5862)
4 University of Kelaniya, Department of Statistics and Computer Science, Kelaniya, Sri Lanka (GRID:grid.45202.31) (ISNI:0000 0000 8631 5388)
5 Selçuk University, Faculty of Science, Department of Statistics, Konya, Turkey (GRID:grid.17242.32) (ISNI:0000 0001 2308 7215)
6 Birsa Agricultural University, Ranchi Agriculture College, Ranchi, India (GRID:grid.444698.3) (ISNI:0000 0001 0667 7168)
Pages
947-959
Publication year
2022
Publication date
Mar 2022
ISSN
23636203
e-ISSN
23636211
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2634670809
Copyright
© The Author(s), under exclusive licence to Springer Nature Switzerland AG part of Springer Nature 2021.