Defense Spending Under Pressure: An ARDL Study of Indonesia’s Economic and Strategic Realities

1 Introduction

In an increasingly complex geopolitical environment, defense expenditure has emerged as a critical element of national security and policy planning. As a maritime and archipelagic state, Indonesia faces strategic challenges in safeguarding sovereignty while balancing developmental priorities. Historically, Indonesia’s defense spending has remained below 1 % of GDP, highlighting significant constraints in addressing its security requirements amid evolving regional and global dynamics (Stockholm International Peace Research Institute [SIPRI], 2023).

Unlike many nations where military expenditure is consolidated under a single defense ministry, Indonesia adopts the Total People’s Defense and Security System (Sistem Pertahanan dan Keamanan Rakyat Semesta or SISHANKAMRATA), which distributes defense-related funding across multiple ministries. This unique structure implies that the frequently cited 0.7 % of GDP figure does not fully capture the true scale of defense-related spending, as significant portions of military-related expenditures are managed by non-defense institutions. Simulations suggest that the effective defense spending under SISHANKAMRATA could be closer to 6.3–7.8 % of GDP, incorporating both military (Kemenhan) and non-military (other ministries) components. These figures are indicative estimates based on aggregating budget components from the Ministry of Defense and selected non-defense ministries believed to contribute to national defense under the SISHANKAMRATA framework (e.g., ministries of transportation, state-owned enterprises, and maritime affairs). Due to the absence of a unified dataset and the lack of publicly disaggregated data by function, these estimates remain approximations and are not used in formal model estimation.

However, due to the absence of consolidated time-series data that fully captures multi-ministerial defense allocations under the SISHANKAMRATA framework, this study utilizes conventional military expenditure data (% of GDP) as reported by SIPRI and the World Bank. While this indicator may underestimate actual defense commitments, it remains the most consistent and internationally comparable metric currently available. This limitation is acknowledged explicitly in our analysis and is further discussed in the methodology and conclusion sections as an avenue for future research.

Defense expenditure is influenced by a variety of economic and geopolitical factors, including GDP growth, inflation, foreign debt, and regional security threats (Fordham and Walker 2005). The trade-offs between defense and civilian priorities are particularly pronounced in developing economies, where budgetary constraints often limit military modernization and operational readiness (Kennedy 2017). The “Guns and Butter” model illustrates this fundamental dilemma, highlighting the need for strategic allocation between security and socioeconomic development. Under this framework, governments must decide how to allocate limited fiscal resources between military spending (“guns”) and social investments such as healthcare, education, and infrastructure (“butter”). Indonesia’s SISHANKAMRATA framework serves as an adaptive mechanism within this trade-off, ensuring that national security remains a shared responsibility across different government sectors while enabling fiscal efficiency. While this framework remains institutionally important, this study does not claim to empirically capture SISHANKAMRATA’s internal budget mechanics. Instead, it provides macro-level estimates using conventional data, with SISHANKAMRATA serving as a background for interpreting fiscal fragmentation.

Prior studies suggest that defense spending in developing nations can enhance economic stability if aligned with broader fiscal and security strategies (Deger and Sen 1995). However, existing research lacks a comprehensive econometric model that captures the unique interplay of Indonesia’s economic structure, its SISHANKAMRATA framework, and evolving geopolitical challenges in shaping defense expenditure. To bridge this gap, this study employs the Autoregressive Distributed Lag (ARDL) model to analyze both short-term and long-term relationships between economic variables and military spending. The ARDL approach is particularly suitable for this study as it accommodates mixed orders of integration (I(0) and I(1)), providing robust insights into dynamic fiscal relationships (Pesaran and Smith 2016).

Despite Indonesia’s strategic geographical position and increasing security challenges, its defense budget has remained relatively low compared to its regional counterparts. Figure 1 presents the military expenditure of the world’s leading military powers, showing that major economies allocate a substantial percentage of their GDP to defense. In contrast, Indonesia’s spending as a percentage of GDP is notably lower than regional counterparts such as Singapore, Brunei Darussalam, Australia, and Malaysia, as illustrated in Figure 1.

Figure 1:

ASEAN Military spending allocation. Source: World Bank (2025a, 2025b, 2025c, 2025d, 2025e, 2025f, 2025g, 2025h, 2025i, 2025j).

While Singapore and Australia consistently allocate between 3 and 6% of their GDP to defense, Indonesia’s military expenditure has remained below 1 % of GDP for decades. Brunei and Malaysia also tend to outspend Indonesia in relative terms, reflecting different strategic priorities and fiscal policies. This persistent gap in military expenditure raises concerns about Indonesia’s defense readiness in the face of regional security threats, maritime disputes, and military modernization efforts by neighboring countries. However, given the SISHANKAMRATA framework, it is important to reassess whether Indonesia’s defense budget is as limited as commonly perceived or if its unique security structure ensures a broader distribution of military-related spending across government institutions. Furthermore, historical trends in Indonesia’s defense budget (Figure 2) indicate a steady but relatively slow increase in absolute spending since 2000. However, this increase does not significantly alter the country’s standing in the regional defense hierarchy, as the allocation remains relatively stagnant in percentage terms. Unlike some neighboring countries that implement sharp increases in military spending in response to security concerns, Indonesia’s defense budget shows continuity rather than adaptation to evolving geopolitical dynamics.

Figure 2:

Indonesia military spending trends (% to GDP). Source: World Bank (2025a, 2025b, 2025c, 2025d, 2025e, 2025f, 2025g, 2025h, 2025i, 2025j).

The stagnation of Indonesia’s defense expenditure presents a critical economic and policy dilemma. Policymakers must balance military preparedness with fiscal responsibility, ensuring that defense spending remains efficient, sustainable, and strategically aligned. The SISHANKAMRATA model, while comprehensive, requires enhanced coordination to optimize the effectiveness of both military and non-military defense components.

Economic theories such as the “Guns and Butter” model underscore the inherent trade-offs in budget allocation between military and civilian priorities (Kennedy 2017). Developing nations, including Indonesia, often face budgetary constraints, making it difficult to modernize defense capabilities while simultaneously funding healthcare, education, and infrastructure development. While SISHANKAMRATA seeks to mitigate these challenges by embedding national defense across multiple institutions, the efficiency of its implementation and the clarity of its financial structure remain key concerns.

Research by Deger and Sen (1995) suggests that defense spending, if strategically aligned, can contribute positively to economic stability. However, Indonesia’s stagnant military expenditure despite its complex security needs raises concerns about its ability to address emerging security challenges while ensuring fiscal sustainability. Unlike major military powers that treat defense spending as an economic multiplier, Indonesia has prioritized developmental goals over military expansion, which raises questions about the long-term sustainability of its defense posture within an increasingly complex regional security environment. This study seeks to clarify these concerns by providing an econometric analysis of Indonesia’s defense spending within the dual constraints of economic management and security strategy, incorporating the nuances of SISHANKAMRATA into the broader policy discourse.

While the SISHANKAMRATA doctrine provides important context for understanding Indonesia’s defense structure, this study does not attempt to quantify its financial structure. Instead, the paper focuses on macroeconomic and geopolitical determinants of defense spending using conventional ARDL methods.

By applying the ARDL approach to macroeconomic and geopolitical drivers while contextualizing results within Indonesia’s institutional environment, we provide a replicable and expandable model for future studies that aim to integrate more detailed institutional data.

2 Literature Review

Research on military expenditure has grown considerably over the past two decades, reflecting increasing concern over how defense spending interacts with economic, political, and strategic variables. Seminal works such as those by Deger and Sen (1995) emphasized the dual role of defense budgets in promoting national security while potentially crowding out social investments in developing economies. More recently, Dunne and Tian (2017)offered a comprehensive overview of global military spending patterns, highlighting macroeconomic conditions, fiscal space, and external threats as key determinants.

Autoregressive Distributed Lag (ARDL) models have become popular for analyzing the short- and long-run dynamics of military expenditure. Aiyedogbon et al. (2012) applied ARDL to assess the impact of inflation on defense spending in Nigeria, finding a negative long-run relationship due to real-term erosion of budget value. Azam and Feng (2017) explored the link between military expenditure and external debt in Asian economies, indicating that higher debt ratios often accompany increased defense burdens. Pacific et al. (2017) investigated how military expenditure affects foreign direct investment and trade performance in Cameroon, again using time-series econometrics to account for dynamic interactions.

In the context of regional and geopolitical influences, Yalta and Yalta (2022) examined the Gulf region using ARDL and panel techniques, finding strong correlations between neighboring states’ military investments. Yesilyurt and Elhorst (2017) employed a dynamic spatial panel model to show that a country’s military budget is influenced by regional arms races, especially when border tensions are present. Christie (2019) focused on Europe, exploring the role of fiscal flexibility and NATO obligations in shaping military spending levels.

Despite this growing literature, few studies have incorporated institutional complexity into quantitative defense models. Most rely on unified budgeting systems, whereas Indonesia’s Total People’s Defense and Security System (Sistem Pertahanan dan Keamanan Rakyat Semesta, or SISHANKAMRATA) creates a fragmented spending structure in which multiple ministries share responsibility for defense-related expenditures. This institutional distinction has rarely been explored empirically, largely due to the lack of integrated, longitudinal data.

Moreover, while ASEAN countries like Singapore and Malaysia are often featured in defense economics literature for their relatively high defense-to-GDP ratios, Indonesia’s strategic budgeting behavior remains underexamined. The country’s relatively low official military expenditure under 1 % of GDP according to SIPRI and the World Bank – masks a broader network of defense activities funded through non-defense ministries. This study addresses this gap by using a macro-fiscal and geopolitical framework while acknowledging the institutional constraints inherent in Indonesia’s budgeting system.

In addition, studies such as Wang and Su (2021) have explored how resource wealth (e.g., oil) impacts military financing. However, these studies often assume that higher oil production correlates with higher military investment, an assumption that may not hold in countries like Indonesia, where oil revenues may be diverted toward non-defense subsidies or populist programs.

Therefore, this paper contributes to the literature by applying an ARDL model tailored to Indonesia’s macroeconomic and strategic environment, while explicitly discussing the implications of institutional fragmentation in defense spending. It also highlights the need for further research that combines econometric rigor with institutional realism, particularly in the context of emerging economies.

3 Data and Method

4 Results

To provide an initial understanding of the data structure, Table 2 result of all variables used in the analysis. The dataset used in this study spans the period 1984–2022, covering nearly four decades of Indonesia’s defense spending and its relationship with key macroeconomic and geopolitical variables. The data are sourced from authoritative institutions, including the World Bank, Indonesia’s Ministry of Finance, and BPS – Statistics Indonesia, ensuring high credibility and consistency. The selection of variables is based on theoretical and empirical justifications from previous literature, focusing on factors such as debt, exchange rate, FDI, inflation, trade openness, neighboring military expenditure, regional military expenditure, US military expenditure, oil, and population, all of which are expected to influence Indonesia’s defense budget allocation.

The elimination process in this study follows a systematic approach to ensure that only relevant and statistically valid variables are included in the ARDL estimation model. Initially, 23 research variables were identified, encompassing macroeconomic and geopolitical factors. However, due to data unavailability or insufficient observations, some variables were excluded, reducing the dataset to 10 variables. Next, a stationarity test (Unit Root Test) was conducted using the Augmented Dickey-Fuller (ADF) method to determine whether the remaining variables met the integration requirements for ARDL modeling. The results indicate that the dependent variable C_MILPER is stationary at level (I(0)) with a probability of 0.0321, while most independent variables, such as Debt, EXC, NEIGH, OIL, REG, and USMIL, are non-stationary at level but become stationary after first differencing (I(1)). Additionally, ECG and INF are found to be stationary at level (I(0)), while POP fails to achieve stationarity at both levels (p = 0.3204 at level, p = 0.9937 at first difference), making it unsuitable for inclusion in the ARDL model. Based on these findings, POP is excluded to ensure that all variables satisfy the stationarity requirements necessary for ARDL modelling.

To ensure the validity and robustness of the ARDL model, classical assumption tests were performed. The F-Bounds Test for cointegration confirms the presence of a long-term relationship among the variables, with an F-statistic value of 35.21413, which significantly exceeds the upper bound at all significance levels, justifying the application of the ARDL approach. The Jarque-Bera normality test confirms that the residuals are normally distributed (p-value = 0.119832), ensuring the validity of statistical inference. The Breusch-Godfrey serial correlation test reveals no autocorrelation in the residuals (p-value = 0.9227), ensuring that the model does not suffer from biased regression estimates. Furthermore, the Breusch-Pagan-Godfrey heteroscedasticity test confirms that residual variance remains constant (p-value = 0.9991), indicating the absence of heteroscedasticity, which ensures efficiency in parameter estimation. Table 2 presents the short-run estimation results of the ARDL model.

The short-run results in Table 2 show that several macroeconomic and geopolitical variables significantly influence Indonesia’s defense expenditure. Inflation (D(INF)) exhibits a strong negative effect, confirming that price increases erode the real value of military allocations in a system where defense budgets are determined in nominal terms. This finding is consistent with the literature on inflationary constraints in emerging economies’ defense spending.

Exchange rate (D(EXC(-1))) also shows a negative and significant coefficient, indicating that rupiah depreciation raises the cost of imported defense equipment and technology, thereby suppressing effective defense spending in the short run. Similarly, foreign direct investment (D(FDI)) exerts a negative influence, which may suggest that during periods of higher FDI inflows, the government prioritizes policies that maintain macroeconomic attractiveness rather than expanding military expenditure.

On the other hand, several variables demonstrate positive short-run effects. Debt (D(DEBT) and D(DEBT(-1))) is positively associated with defense expenditure, implying that borrowing may temporarily ease fiscal constraints and allow higher allocations to defense. Regional average military spending (D(REG_AVE)) and trade openness (D(TO(-1))) also show significant positive effects, suggesting that Indonesia reacts promptly to regional defense competition and international trade dynamics by adjusting its military budget.

Furthermore, U.S. military expenditure (D(USMIL) and D(USMIL(-1))) displays a negative short-run effect, indicating that a stronger U.S. presence in the Indo-Pacific may temporarily reduce Indonesia’s perceived need to increase its defense spending. This aligns with the concept of a security substitution effect in the short run. To capture Indonesia’s structural defense spending behavior, it is essential to examine the long-run estimation results presented in Table 3.

The long-run estimation results in Table 3 indicate that several macroeconomic and regional variables exert a statistically significant influence on Indonesia’s defense expenditure. Debt (DEBT), economic growth (ECG), exchange rate (EXC), foreign direct investment (FDI), inflation (INF), neighboring countries’ military expenditure (NEIGH_AVE), regional average military expenditure (REG_AVE), and trade openness (TO) are all significant determinants in the long run, though the direction of their effects varies.

Specifically, FDI, inflation, and economic growth have positive long-run effects, suggesting that improvements in macroeconomic fundamentals tend to expand fiscal space and allow greater allocation to defense. Similarly, neighboring countries’ defense spending (NEIGH_AVE) shows a strong positive impact, reinforcing the hypothesis that Indonesia responds to regional military dynamics. In contrast, trade openness (TO) and regional average expenditure (REG_AVE) exert negative effects, which may reflect fiscal trade-offs or regional burden-sharing dynamics. Exchange rate (EXC) also shows a negative relationship, consistent with the idea that depreciation increases procurement costs, thereby constraining defense spending.

Meanwhile, U.S. military expenditure (USMIL) does not appear significant in the long run, diverging from earlier short-run results. This finding suggests that Indonesia’s long-term defense allocation is shaped more by domestic macroeconomic conditions and regional security competition than by U.S. defense posture in the Indo-Pacific.

To ensure the validity and reliability of the ARDL estimations, robustness checks were performed. Table 4 presents the diagnostic test results, including normality of residuals, autocorrelation tests, and heteroscedasticity tests. The Error Correction Term (ECT) coefficient is −0.2285 and statistically significant at the 5 % level (p < 0.05), indicating that approximately 22.85 % of any deviation from the long-run equilibrium is corrected annually.

The findings of this study demonstrate that variables such as exchange rate (EXC) and inflation (INF) influence military expenditure in the short run, whereas external factors like US military expenditure (USMIL) have a sustained long-term impact. The presence of a significant and negative Error Correction Term (ECT) confirms the existence of a long-run equilibrium relationship. Additionally, robustness tests confirm that the model satisfies classical assumptions, ensuring the reliability of the results. These findings emphasize the importance of considering both short-term economic fluctuations and long-term strategic factors when formulating defense budget policies.

5 Discussion

6 Conclusions

This study offers a macroeconomic ARDL analysis of Indonesia’s defense expenditure using official data. While the SISHANKAMRATA system adds institutional complexity, it is not modeled empirically in this paper. The findings indicate that macroeconomic variables such as inflation, exchange rate fluctuations, and foreign direct investment significantly influence short-term defense budgeting, while geopolitical factors such as regional military spending and US military expenditure shape long-term allocation decisions. The presence of a significant and negative Error Correction Term (ECT) confirms the existence of a long-run equilibrium relationship, demonstrating that deviations in military spending adjust toward equilibrium over time.

Given Indonesia’s fragmented defense financing system under the SISHANKAMRATA doctrine, policy formulation should recognize the hidden fiscal burden that arises when multiple ministries contribute to defense functions without consolidated oversight. Policymakers are encouraged to develop an integrated budgeting framework that transparently accounts for defense-related expenditures across all relevant institutions.

Furthermore, the ARDL model used in this study, while effective in capturing macroeconomic and geopolitical influences, may not fully reflect the institutional complexity of Indonesia’s defense posture. As such, future modeling efforts could benefit from structural or systems-based approaches, including hybrid models or qualitative-comparative analysis, to better incorporate institutional fragmentation and inter-agency dynamics.

To enhance the strategic alignment of defense budgeting, Indonesia could explore innovative financing mechanisms such as a Defense Sovereign Wealth Fund (D-SWF) or targeted public-private partnerships (PPP) for infrastructure and logistics. These mechanisms would allow the state to maintain fiscal discipline while ensuring sustained military readiness.

In this light, the study serves not only as an empirical exploration of defense spending but also as a methodological bridge between traditional macroeconomic modeling and the realities of fragmented institutional environments. The framework developed here lays the groundwork for more integrated defense economic studies in the future, particularly for countries adopting non-centralized defense doctrines.

7 Future Research Direction

Despite the robustness of the findings, this study has several limitations. One major constraint is the availability of data, as some geopolitical variables, such as military alliances and conflict intensity, were excluded due to data unavailability. Future studies could integrate geopolitical risk indices to refine military expenditure modeling. Additionally, the model does not explicitly account for military technological advancements or defense procurement cycles, both of which are crucial in long-term defense budgeting. Expanding future research to include the role of defense innovation and arms trade dependencies could provide further insights into military financing.

An important future direction is the reconstruction of a defense spending index based on SISHANKAMRATA’s structure. This could involve aggregating actual budget data from multiple defense-relevant ministries (e.g., Ministry of Defense, Ministry of Transportation, Ministry of State-Owned Enterprises, etc.) to generate a more realistic measure of Indonesia’s total defense effort. Such an index would improve empirical alignment with the conceptual framework and offer a stronger basis for model estimation.

Another limitation is the scope of this study, which focuses solely on Indonesia, limiting the generalizability of the results. Future research should conduct panel data analysis across ASEAN countries to identify broader regional trends in military expenditure. A comparative study of defense budgeting strategies across developing nations would further enhance understanding of military expenditure dynamics in resource-constrained economies.