Analysis and Forecasting of India’s Defense Expenditure

DOI

10.2991/978-2-38476-309-2_100How to use a DOI?

Keywords

Defense Expenditure; ARIMA; GM(1, 1); Exponential Smoothing

Abstract

The analysis and forecasting of defense expenditure plays an instrumental role in the rational allocation of resources, ensuring the security and advancement of the nation. Furthermore, it has significant implications for the economic and social development of the country. This paper presents a comprehensive examination of the size of India’s defense expenditure, spanning from FY 2013–2014 to FY 2022–2023. It encompasses an in-depth analysis of the absolute size, share of GDP, share of government fiscal expenditure, per capita defense expenditure of citizens and per capita defense expenditure of military personnel. Subsequently, the structure of India’s defense expenditure is analyzed from FY 2017–2018 to FY 2022–2023, including the resource cost structure and the force group structure. Ultimately, in order to forecast India’s defense expenditure for the subsequent three fiscal years, ARIMA, the grey-system forecasting method GM(1, 1) and exponential smoothing are employed when considering defense expenditure as time series data.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhangqian Zhu
PY  - 2024
DA  - 2024/12/09
TI  - Analysis and Forecasting of India’s Defense Expenditure
BT  - Proceedings of the 2024 9th International Conference on Modern Management, Education and Social Sciences (MMET 2024)
PB  - Atlantis Press
SP  - 835
EP  - 843
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-309-2_100
DO  - 10.2991/978-2-38476-309-2_100
ID  - Zhu2024
ER  -