Interactional Impact of Defence Expenditure and Political Instability on Economic Growth in Nigeria: Revisited

ABSTRACT

Over the last decade empirical research has increasingly recognized the significance of understanding how defence spending and political stability jointly influence economic growth in developing nations. This paper revisits the complex interplay between defence expenditure, political instability, and economic growth in the context of Nigeria, and for the period 1960-2021. Leveraging the robust Smooth Transition Autoregressive (STAR) model proposed by Granger and Terasvirta, this study aims to provide a comprehensive analysis of the dynamic relationships among these critical factors. Our investigation employs the STAR model to capture potential nonlinearities and regime shifts in these interactions (confirmed by the diagnostic tests), shedding light on how political instability may impact the effectiveness of defence spending on economic growth. The findings further reveal how military spending can influence political stability and governance, particularly in contexts where military resources wield significant power and influence. They also show that low military spending negatively impacts economic growth due to inadequate resources for security and stability maintenance. These findings hold vital implications for policymakers striving to enhance economic development amidst the backdrop of geopolitical uncertainty and security challenges.

KEYWORDS:

• Nigeria
• economic growth
• military spending
• political instability, STAR

JEL CLASSIFICATION:

• C22
• H30
• O40

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

1. Strategies that will “reduce a country’s vulnerability to economic influence attempts as well as the more traditional forms of preparation for military defence “Friedberg (1991, 272).

2. According to the Keynesian type demand model, milex is part of the government consumption that promotes economic growth by boosting demand for goods and services (Azam 2020).

3. The Failed States Index (FSI) report (2021) ranked Nigeria as ‘Alert’. [The FSI releases yearly reports regarding risk factors for all countries, (e.g. security, external involvement, refugees, internally displaced populations, etc.). These reports categorize countries into four main groups: ‘Alert,’ ‘Warning,’ ‘Moderate,’ and ‘Sustainable,’ with ‘Alert’ representing the highest level of risk and ‘Sustainable’ the lowest].

4. Numerous economic variables often undergo regime shifts, indicating sudden and abrupt changes. However, for most economic variables, regime transitions occur gradually, with changes taking place over time (Kavkler et al. 2007).

5. For a comprehensive discussion as per political instability’s definitions and proxies used in economic studies see Jannils (2021).

6. We follow Samadi and Alipourian’s (2021) recommendations to measure the quality of institutions (specifically measures for political institutions).

7. Thus, and similarly to Londregan and Poole (1990), Blomberg (1996), and Alesina et al. (1996), political instability in this paper is equated with the propensity of observing changes in government and we measure it by using the variables of Political instability by Campos and Karanasos (2008). For a complete set of the used variables by the literature regarding institutions see: Samadi and Alipourian (2021) Table 1, pp. 146-149.

8. The mining sector, particularly petroleum production, saw remarkable growth during this period Crude oil production skyrocketed from 46,000 barrels per day (bpd) in 1961 to 600,000 bpd by 1967 (Falola 2004).

9. The decline in agriculture foreshadowed Nigeria’s long-term economic independence (Falola and Heaton 2008).

10. The Action Group (AG) was the dominant party in West Nigeria (Agi 1986).

11. For a comprehensive discussion see:Brooks (1997).

12. For a complete discussion on the Barro -type models see Dimitraki and Menla-Ali (2015).

13. Different approaches have been utilized to measure political instability within economic models. Some researchers incorporate specific variables as proxies for political instability, while others employ one-dimensional indices to condense its multifaceted nature into a single variable (see Alonso and Garcimartín 2013). Various techniques, such as logit analysis, mechanical aggregation, principal components analysis (PCA), and explanatory factor analysis (EFA), have been applied in constructing these indices (for a thorough discussion see Jannils (2021)).

14. The political instability indicators are: cc_t the number of basic alterations in a state’s constitutional structure, the extreme case being the adoption of a new constitution that significantly alters the prerogatives of the various branches of government; le_t are the number of elections for the lower house each year; str_t is the number of strikes of 1000 workers and above; ass_t are any politically motivated murder or attempted murder of a high government official or politician.

15. The estimated models are labelled as follows: Model 1 is the model with the variable ass_t, Model 2 the one with cc_t, while Models 3 and 4 are those including and respectively.

16. For a detailed discussion of the nonlinear optimization process see Hendry (1995).

17. There is also a ‘‘continuum” of regimes associated with different values of the transition function, that lie between 0 and 1 (Dijk, Teräsvirta, and Franses 2002).

18. After conducting the necessary preliminary testing, sse enters the model in first-differences and with zero lags.

19. See for example: Biswas and Ram (1986); Kalaitzidakis and Tzouvelekas (2011), to name but a few.