442
Views
5
CrossRef citations to date
0
Altmetric
Articles

Guns for Butter? Empirical Evidence from China

, , &
Pages 809-820 | Received 27 Jun 2016, Accepted 03 Feb 2017, Published online: 22 Feb 2017
 

Abstract

This study examines the causal nexus between defence spending and education expenditure in China using the bootstrap Granger full-sample causality test and sub-sample rolling window estimation. The full-sample result indicates that there is no causality between defence spending and education expenditure. By adopting a time-varying rolling window approach to revisit the dynamic causal relationships, this article identifies a negative unidirectional causality running from education expenditure to defence spending. The finding suggests that it is the education expenditure crowds out defence spending in China rather than reverse. No causality is demonstrated from defence spending to education expenditure, indicating that an increase in military spending will not crowd out expenditure on education. The results could be partly explained by that the education expenditure in China is below the requirement of corresponding economic growth, urging for more financial budget. Whereas the findings support a negative trade-off between defence and education expenditures, they refute the theory of ‘guns for butter’.

JEL Codes:

Acknowledgments

The useful comments and constructive suggestions by anonymous referees are gratefully acknowledged. The usual disclaimer applies.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 417.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.