1. Marvelous college of technology and Ateneo De Davao University, Philippines.

* Correspondence: bion11058914@gmail.com

Keywords: factors, military burden, economic growth

1. INTRODUCTION

The relationship between military expenditure and economic growth is highly debatable, whether in the nature of these expenditures and methods of financing or in the effect of military expenditure on economic growth. On the practical side, most of the research focused only on the relevance between the two variables which is military burden and economic growth. This does not include other economic factors that affect military burden and disregards the importance of interrelation between the civilian, education, health, tourism, prices, and other government sectors because opportunity cost is really significant. The maintenance of peace and security of a country is one of the most important functions of the government such that the government tries to ensure that the military is equipped and capable of defending the nation [1]. Military spending includes “all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects. It also includes military and civil personnel, including retirement pensions for military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid” [2]. Military spending is an important policy issue because security and economic development are important policy objectives of all nations worldwide.It has been observed by SIPRI, that there is a growing military expenditure around the world reaching an all-time high of $2.1 trillion in 2021. This was the seventh consecutive year that military spending increased. This massive military spending of some nations is justified as necessary. This includes countries like the USA, the People’s Republic of China, India, Russia, and the Kingdom of Saudi Arabia, accounting for around 60% of global military spending in 2019. For instance, the U.S. military expenditure is posted at $732 billion, an increase by almost 5.3% from the previous period. It increased by 59% because the USA engaged in defense operations in Afghanistan, and Iraq. More importantly, it also increased its ‘base’ defense budget [3].  In the Philippines, the assessment of military spending is important given that there is an increasing growth in military spending in recent years against the background of financial crisis from pandemic and excessive inflation. According to the International Monetary Fund, if a country maintains a 2% inflation rate, the country is considered to have a good inflation. The Philippines, however, experienced more than 2 percent inflation every year [4]. More importantly, the South China Sea issue presents a big “huge challenge” for the Philippines, and China is claiming much of this key waterway and in fact, has established military installations in the conflict area [5]. The conflict between China and the Philippines in the Western Philippine Sea is the result of several years of territorial dispute over the Spratly Islands wherein several countries have claimed it as their own territory. The People’s Republic of China is the most ambitious claimant, asserting almost 80 percent of the South China Sea is its sovereign territory which encompasses both the Paracel and Spratly islands, as well as Macclesfield Bank and Scarborough Shoal. This is because the South China Sea is one of the most important economic and strategic regions in the world and is undeniably essential to Southeast Asia’s way of life since it permits annual transfer of products worth trillions of dollars. These waters carry nearly one-third of all global trade, including essential energy supplies like oil and natural gas [6]. The basis for expanded military expenditure is the Revised Armed Forces Modernization Act, also known as Republic Act (RA) 10349, which was passed to improve the Armed Forces of the Philippines’ (AFP) capacity to handle domestic threats, maritime domain security, and counter terrorism.  It was created to safeguard defense modernization initiatives against changes in the nation’s political landscape. A 15-year modernization initiative for the Armed Forces of the Philippines (AFP) began in 2012 and will last through 2027. The program is focused on building military capability to address two threats − internal insurgency, primarily in the south of the country; and territorial disputes in the South China Sea. The planned budget for the third milestone or horizon era (2023–2027) is $4 billion, representing potential to buy weapons systems, unmanned aerial vehicles, communications, personal safety equipment, and intelligence and surveillance technologies. The Philippines procurement of Brahmos was the first ever export of the Indian missile system, marking a significant milestone for India’s defense export. [7]. The United States is the major provider of defensive equipment to the Philippines. However, Israel, South Korea, Turkey, Italy, Spain, France, Sweden, and Germany are fierce rivals [8]. The precursor to the AFP modernization occurred on December 13, 1990, when the Department of the Interior and Local Government (DILG) underwent reorganization by virtue of Republic Act No. 6975. The law also created the Philippine National Police (PNP) out of the Philippine Constabulary-Integrated National Police (PC-INP), which, together with the National Police Commission, was integrated under the new DILG, the Bureau of Fire Protection, Bureau of Jail Management and Penology, and the Philippine Public Safety College. It also absorbed the National Action Committee on Anti-Hijacking from the Department of National Defense (DND).The passage of RA 6975 paved the way for the union of the local governments and the police force after more than 40 years of separation [9]. Midway through the 1990s, a prior 15-year modernization plan that was supposed to have been implemented failed, leaving the Philippines with outdated equipment like World War II-era cruisers and American-made helicopters from the Vietnam War [10]. The Aquino administration spent around $1.7 billion on the military, the majority of which went into used ships and aircraft from 2010 to 2016. Compared to the administration of Duterte, the latter spent $5.6 billion over five years to upgrade the aging military [11]. In the past 30 years, the military expenditure in the Philippines expanded remarkably during the Duterte presidency. Under the Marcos Jr. administration, the Philippine government has proposed a PHP 240.29 billion ($4.28 billion) defense budget for 2023, an 8% increase over the PHP 221.60 billion allotted in 2022. The additional funds will be allocated to the new core defense budget broken down as follows: PHP 138.4 billion for personnel costs; PHP 58.6 billion for maintenance and other operating costs; and PHP 43.3 billion for capital expenditure outside the RAFPMP, according to documents released by the Department of Budget and Management (DBM). Some 46% of the core defense budget, or PHP 109.8 billion, would be allocated to the Philippine Army (PA); PHP 34.7 billion (14.4%) to the Philippine Navy; and PHP 35.4 billion (14.7%) to the Philippine Air Force (PAF). Most of the remaining funds will be allotted to the Government Arsenal, which supplies the AFP with weapons and ammunition, civilian defense, and veteran health care. Military expenditure has a huge opportunity cost and categorizes military expenditure as a sub-optimal means of increasing economic growth, given that other alternative uses of government spending, such as spending on infrastructure, education, health, tourism, and other social expenditures. Such high levels of spending frequently raise concerns as to the ‘opportunity cost’ involved in military spending—the potential civilian uses of such resources that are lost. One way to put this in perspective is to compare it to social spending. For example, do governments spend as much money on healthcare? We can also look at what else the money could achieve if it were put to other specific uses.  The boosting of economic growth through higher military expenditure is not the only efficient way to achieve economic growth. More importantly, the importance of private investment and foreign investment which may be crowded out by military expenditure. Empirical results revealed that resources used, such as productive capital formation, is four times more growth enhancing compared to the resources allocated for military expenditure. Therefore, as a result, there is a strong need for peace initiatives for boosting economic growth rate [12]. Moreover, under this theory, military spending creates high costs for consumption, investment, and other public spending creating a serious burden on the budget. Unfortunately, there is no consensus on the economic evidence that exists to date covering the economic impact of defense spending on economic growth. There is also the issue of whether military expenditure or military burden significantly and positively affect economic growth [13].The overarching goal of the study is to determine the factors affecting military burden and its relation to economic growth in the Philippine

2. MATERIALS & METHODS

Both descriptive statistics (comparison as to highest-lowest) and inferential statistics (OLS and 2SLS) study was used for this investigation because it allows the researcher to detect the presence and strength of a relationship between variables and to predict or forecast events from current data and knowledge. The researcher used independent variables including inflation, foreign direct investment, tax revenue, unemployment, percent share of tourism, percent share of education and percent share of health in testing the strength of the dependent variable which is military burden in the 1^st stage. In the 2^nd stage, the researcher used military burden as an independent variable to measure the strength of the dependent variable which is economic growth. The unit of analysis is the Philippine economy and government. These offer understanding about what are the predictors of military expenditure in the case of the Philippines and to understand if high military funding creates economic growth in the context of limited resources in the Philippine economy. In this investigation, secondary data was used. Data on the dependent variable, and independent, were obtained from the database of the World Bank from 2000 to 2021 because a rule of thumb for the sample size of regression analysis requires at least 20 cases per independent variable and with the exception of the new millennium, global tension and high levels of military expenditure across the world like the Middle East, Eastern Europe, South Asia, the East China Sea, and the South China Sea are detected. The Philippines is in the vortex of tension in Southeast Asia as 80 percent of the South China Sea is claimed by China.  Most of the islands claimed by China are within the 200-mile economic zone of the other countries including the Philippines. These include the Spratly’s, Machel filed Bank, Scaborashoal, and the Paracel islands. The study period covered 2000 to 2021 because these are the periods within which the Philippines is hotly embroiled in the conflict.  Equally important, it is within these periods where the other economic variables have complete data. The World Bank Data Portal provides access to global economic and development statistics. World Bank databases are comprehensive. They are formatted in a long time series and are following internationally accepted standards and norms resulting in a consistent, reliable source of information. The Philippine Statistics Authority (PSA) database is available online; however, the data are reported in short time periods. The World Bank databases yield essential tools that are important in supporting critical management decisions and providing key statistical information for various development operational activities. Data on GDP growth rate, inflation, foreign direct investment, tax revenue, unemployment, percent share of tourism, percent share of education and percent share of health were also obtained from the World Bank database and other relevant databases to complete the data of the variables.  Both the descriptive and inferential statistics were used to meet the objectives of the study. Descriptive statistics was used to determine the trends of the different variables over time, from 2000 to 2021. The inferential methods used were the multiple linear regression in the 1^st stage and two Stage Least Squares (2SLS) in the 2nd stage at the 5 percent level of significance to meet the objectives of the study. This analysis was used to determine the economic factors affecting military burden and its relationship to economic growth. This method led to an economic model that could explain the influence and relationship of explanatory variables and the dependent variable. This statistical technique determined the individual effect of the explanatory variables to the dependent variable, holding other variables constant, and provided estimates for unknown parameters of the model variable [14]. The F-test of the overall significance was used to indicate whether the linear regression model provides a better fit to the data than a model that contains no independent variables. F-tests can evaluate multiple model terms simultaneously, which allows them to compare the fits of different linear models. In contrast, t-tests can evaluate just one variable or term at a time. The Two Stage Least Squares is a method of extending regression to cover models which violate Ordinary Least Squares (OLS) regression assumption results of recursively. This is a single equation technique for estimating equations in a simultaneous equation model, each equation is estimated separately. The name 2-Stage Least Squares stems from the two regressions in the estimation procedure. Under this technique, instrumental variables that are uncorrelated with the error terms are used to compute the estimated values of the problematic predictor(s) (the first stage), and the (second stage) use values to estimate a linear regression model of the dependent variable. In this study, military burden was tested for its relation to economic growth.  Military burden, however, can influence economic growth and economic growth can also influence military burden.  Hence, the two-stage least squares was utilized which used other economic variables (Foreign Direct Investment, Health expenditure, Education expenditure, Tourism, Unemployment, Inflation, Tax revenue and Export) to proxy for military burden that are uncorrelated with the measurement errors in economic growth. These proxy variables were substituted for military burden itself in the originally specified model, which was then estimated. The Hausman Test (also called the Hausman specification test) was used to detect the endogenous regressors (predictor variables) in a regression model; that is, the economic variables which are thought to influence military burden. Endogenous variables have values that are determined by other variables in the system. Having endogenous regressors in a model will cause ordinary least squares estimators to fail, as one of the assumptions of OLS is that there is no correlation between an predictor variable and the error term. Instrumental variables estimators can be used as an alternative in this case. The Hausman test helps out if the predictor variables are endogenous. The econometric model of the study was expressed in the following equations:

Military Burden = β₀ + β₁FDI – β₂Health + β₃Educ – β₄Tour + β₅Unem – β₆ Inf + β₇Tax + β₈Export + i                              (1)

Where;

β₀ = the intercept/ the value of Y when all other explanatory variables are zero; constant

β₁= the parameter measuring the response of military burden, for every change in FDI, when all other variables remain the same.

β₂= the parameter measuring the response of military burden, for every change in health expenditure over GDP, when all other variables remain the same.

β₃= the parameter measuring the response of military burden, for every 1% change in education expenditure over GDP, when all other variables remain the same.

β₄= the parameter measuring the response of military burden, for every change in tourism expenditure over GDP, when all other variables remain the same.

β₅= the parameter measuring the response of military burden, for every 1% change in unemployment rate, when all other variables remain the same.

β₆ = the parameter measuring the response of military burden, for every 1% change in infrastructure expenditure over GDP, when all other variables remain the same.

β₇= the parameter measuring the response of military burden, for every 1% change in tax revenue over GDP, when all other variables remain the same.

β₈= the parameter measuring the response of military burden, for every 1% change in exports over GDPI, when all other variables remain the same.

_ἕ = Represents all the other factors that affect (Y) that are not captured in the model.

Economic Growth = β₀ + β₁Military Spending (Burden) + _I                                                                   (2)

Outputs generated were tested to find out if the variables/parameters are significant. The p-value was considered in testing the level of significance of the parameters. If the p-value is less than 0.05 level of significance, (p <0.05) the parameter is significant. The results of the 2SLS were compared with the results of the Multiple Regression to check if the 2SLS compared favorably with the Ordinary Least Squares. SPSS Version 27 was used to determine the estimates of the coefficients and the violations to the assumptions when using the Least Squares Method. There are two fundamental methods of estimation for simultaneous equations: least squares and maximum likelihood. The 2SLS uses the least-squares method and with small samples, 2SLS is appropriate. It is a single equation method, which means that over-identifying restrictions in other equations. The model was reviewed to see whether the model satisfied the assumptions of the OLS for the estimators to be Best Linear Unbiased Estimators (BLUE).

The assumptions to be satisfied are:

• E() = 0
• E(²) = Var()= σ²
• Cov (_i,_j) = 0; i≠j

One or more of these assumptions are often violated, thus a diagnostic test was conducted to examine whether the OLS derived from the equation satisfy the regression assumption, when one or more assumptions are violated, then the OLS estimators are no longer BLUE. If successive errors are correlated with each other, then we have a problem of autocorrelation. Thus, the last assumption is violated. In case of any violation, as of the problem of heteroscedasticity that violates the second assumption, existing when the variances for all observations are not the same, the assumption of Generalized Least Square (GLS) procedure was used to transform the model to eliminate the problem.

3. RESULTS & DISCUSSION

Table 01 shows the trend of the economic variables over time. To gain better appreciation of the data, however, the relationship between the economic variables and military burden is presented and discussed. Figure 01 presents the trends of the economic variables used in this study from 2000 to 2021. The highest and the lowest points of the dependent and independent variables were highlighted and offered main reasons for the contrasting movements over time. The connection between military burden and the independent variables were likewise discussed. Historically, the GDP annual growth rate in Philippines averaged 4.8 percent from 2000 until 2021, reaching an all-time high of 7.33 percent in 2010. This was attributed to the rising deployment of overseas workers that boosted remittances. Other important drivers for 2010 included the replenishment of depleted stocks by private companies and the strong short-term outlook for business process Outsourcing (BPO) sectors. A record low of -9.52 percent was registered in 2020 because of the global pandemic. The highest military burden value was 2000 (1.608%). From 2000 to 2021, however, the largest amount of money spent in the Philippines military was $4.10 billion, or 1.25% of GDP, in 2017 during Duterte’s administration to modernize the outdated military defense of the country. President Aquino Jr during his term, RA 10349 was enacted to revitalize our AFP modernization program. As a commander in chief, he recognized the importance of equipping our military to be a better response to the evolving domestic and regional security challenge. Estrada announced an all-out war against the MILF group because the group invaded the town of Kauswagan, Lanao del Norte and took hundreds of resident’s hostages. Military assault on camp Abubakar ordered by Estrada, the MILF largest and most important camp of the group [15]. However, President Gloria Macapagal Arroyo congratulated AFP and DND for slashing by half the strength of the communist new people’s army in the past 6 years and causing the disintegration of the Abu Sayyaf (Govt. Philippines). The International Monetary Fund (IMF) considers the inflation rate of 2% as good. The Philippines, however, experienced its high inflation rate in 2008 during Arroyo’s administration at 8.26% and recorded its lowest rate during the Aquino administration at 0.67%. The unprecedented inflation pressures in 2008 stemmed mainly from the higher international prices of oil and non-oil commodity products. The high food prices, particularly of rice, drove the trend of headline inflation. The prices of commodities were most stable in the Aquino years among the seven administrations in the sense that more energy policies were advocated, approved more power plants, and generated more electricity [16].  The average consumer price inflation in the Philippines, however, averaged 3.7 from 2000 to 2021. This was rated to be moderate inflation following the International Monetary Fund coefficients. Inflation reduces the purchasing power of the defense sector.

Table 01:  Economic Indicators of Economic Growth in the Philippines, 2000 to 2021.

Year	GDP Growth Rate	ME/GDP Military Burden	Education per GDP	Health per GDP	Inflation	Tax Revenue / GDP	Unemployment rate	FDI/GDP	Tourism Exp (% of GDP)	Export of good and services% of GDP
2000	4.38	1.608	15.21	3.60	3.98	12.440	3.65	1.777	5.6	43.30
2001	3.05	1.471	13.92	2.85	5.35	12.266	3.70	0.963	5.8	41.20
2002	3.72	1.474	14.07	2.64	2.72	11.668	3.63	2.098	5.6	40.00
2003	5.09	1.551	14.38	3.08	2.29	11.666	3.53	0.565	5.7	42.20
2004	6.57	1.361	12.75	3.05	4.83	11.364	3.55	0.623	5.9	41.80
2005	4.94	1.332	12.42	3.74	6.52	11.924	3.80	1.549	6.2	41.20
2006	5.32	1.315	13.27	3.78	5.49	13.127	4.05	2.121	6.3	41.20
2007	6.52	1.291	13.67	3.75	2.90	12.960	3.43	1.871	6.4	38.00
2008	4.34	1.250	14.44	3.86	8.26	13.034	3.72	0.738	5.7	33.40
2009	1.45	1.202	13.21	4.16	4.22	11.699	3.86	1.173	5.9	30.20
2010	7.33	1.170	15.77	4.13	3.79	11.635	3.61	0.514	6.2	32.90
2011	3.86	1.153	16.57	4.03	4.72	11.849	3.59	0.857	6.8	29.10
2012	6.90	1.107	16.07	4.18	3.03	12.306	3.50	1.228	7.7	27.50
2013	6.75	1.190	17.76	4.27	2.58	12.744	3.50	1.316	8.1	26.30
2014	6.35	1.043	16.05	3.70	3.60	13.016	3.60	1.929	8.9	27.40
2015	6.35	1.088	16.34	3.90	0.67	13.020	3.07	1.840	9.9	27.20
2016	7.15	1.046	17.11	3.95	1.25	13.087	2.70	2.599	10.4	26.70
2017	6.93	1.247	19.83	3.96	2.85	13.594	2.55	3.122	11.7	29.60
2018	6.34	0.820	18.74	3.95	5.31	14.048	2.34	2.868	12.3	30.20
2019	6.12	0.920	18.14	4.17	2.39	14.488	2.24	2.301	12.9	28.40
2020	-9.52	1.012	15.55	5.11	2.39	13.951	2.52	1.886	5.1	25.20
2021	5.70	1.000	16.62	5.61	3.93	14.100	2.41	3.000	5.2	25.80

Figure 01: Economic Indicators of Economic Growth in the Philippines, 2000 to 2021.

The FDI as a percent in GDP climbed, peaking at 3.12% in 2017 due to the structural reforms introduced. These enabled the Philippines to be more competitive with FDI inflow under the “Build” program and foreign investors were taking note of the progress (Dbm.gov). The lowest point was recorded in 2010 at the rate of 0.51% of GDP. This was attributed to the constitutional limits to foreign ownership and to threat of terrorism and the killings of journalists in relation to clan war between Mangudadatu and Ampatuan making the Philippines as one of the most dangerous countries in the world for journalists. To contain this threat, President Gloria Macapagal Arroyo officially placed Maguindanao Province under the state of martial law on December 4, 2009 through Proclamation No. 1959 [17]. The average of FDI percent in GDP in the Philippines, however, remained at 1.61 percent. Nevertheless, the foreign direct investment created new jobs and revenues that could enhance economic growth and create more spending like social programs and defense programs. The highest education expenditure percent in GDP was recorded in 2017 at a peak of 19.83% and the lowest percentage at 12.42% was recorded in 2005. The education departments increased their budget in 2017 to fund teachers’ salaries, improve basic educational facilities, purchase instructional materials, and to give financial assistance to students. In contrast, the lowest expenditure in education was observed under Arroyo’s administration because it focused on health and agriculture to finance the Greater Medicare Access Program Health Card and Agricultural funds for farm inputs. It was observed to be among the lowest in Asia in terms of education spending [18]. The average education expenditure percent of GDP in the Philippines during 2000 to 2021 was 15.54%. Education and military expenditure are competitors for economic resources as mentioned by [19] when he observed that a rise in military spending reduced the expenditure of education in France and the United Kingdom. One of the main reasons was intuitive in the sense that in the presence of dynamic spillovers from a given government budget, an increase in the military expenditure crowds out an equivalent amount of all other spending.  In terms of tax revenue generated, the Philippines experienced a direct relation of growth meaning to say as the years goes up the revenue also continue its growth for 8 consecutive years from 2011 to 2019 and peaked in 2019 at 14.5 %.The Philippines tax effort improved to 18% in 2019 because of tax reform or the train law (RA 10963).The bulk of Philippine tax revenue in 2019 came from taxes of goods and services (42.8%) followed by tax on income and profit at 35.6%. The lowest recorded tax revenue was in 2004 at 11.364% when there was a suspension of the implementation of withholding tax on income repayment made by suppliers of agricultural products issued March 12, 2004 [20]. The average tax revenue over GDP in the Philippines during the period of 2000 to 2021 was 12.72%. Tax is the prevalent source of finance for the governments and military expenditure is part of the government expenditure. The lowest health expenditure percent in GDP of the Philippines was recorded at a rate of 2.6 because the Philippines experienced a budget deficit hit record in 2002 [21] and the highest peak was in 2020 at 5.11% to GDP. The highest health expenditure in the Philippines was in 2020 as the country shifted its priority in public health for the Covid outbreak. This variable helps to understand if there was a tradeoff between health and military expenditure in the context of limited resources in the Philippines. A remarkable historical figure in Philippine tourism was recorded when for 11 consecutive years, the industry posted a positive or increasing growth rate from 2008 to 2019 due to travel services and the country’s external sector position. Before the pandemic, the tourism industry was one of the key contributors to the sustained growth of the Philippine economy. The significant improvements in tourism infrastructure, particularly airports, land transport and hotels during this period spurred this growth (bsp.gov). However, it experienced a slowdown in 2020 amid the pandemic at 5.1% growth. The highest unemployment rate was in 2006 at a rate of 4.05% because of the sluggish industry sector according to “Senate Economic Planning Office” and the lowest employment rate as reported by PSA was in 2019 2.34% as more Filipinos joined the workforce because of the Build Program of the Duterte administration, the lowest rate in the past two decades. The export of good and services share to GDP in the Philippines during the period of 2000 to 2021 recorded the highest peak in 2000 at 43.30 percent to GDP due to the country’s massive export of electronics and industrial materials to developed countries like the USA, Singapore, Japan, Netherland, and the lowest was in 2020 at 25.20% to GDP. This year was the lowest because of a pandemic resulting in export restrictions on internal movement and international movement or travel controls in partner countries. Table 02 shows the results of the analysis for the variables affecting military burden in the Philippines. Out of the eight (8) variables used in the study, four (4) variables were considered to be good predictors of military burden in the Philippines, where p-value is less than or alpha = 0.05. These variables are (1) total exports of goods and services (percent of GDP), (2) tourism expenditure (percent of GDP), (3) education expenditure (percent of GDP) and (4) inflation rate. Inflation rate and tourism expenditure over GDP have an inverse or negative relationship with military burden. This means that as inflation rate and tourism expenditure increase, military burden decreases because of the context of limited resources. On the other hand, education expenditure and export of goods and services have a direct or positive relationship with military burden. This implies that as these variables increase, military burden also increases. These results fail to reject the alternative hypothesis at alpha is less than 0.05, there is a significant positive relationship between military burden and education and export. Health expenditure (percent in GDP), unemployment, Foreign Direct Investment, and tax revenue were not significant predictors of military burden and therefore the study tends to accept the null hypothesis that these variables have no impact on military burden in the Philippines.

Table 02: Estimated Coefficients and Tests of Significance of Variables Affecting Military Burden Philippines, 2000 to 2021

Variable		Coefficient		Standard error		t value		p value
Constant		-0.014		0.782		-0.133		0.896
Education		0.051		0.013		2.838		0.014*
Export		0.023		0.018		3.834		0.002*
Inflation		-0.026		0.006		-2.099		0.056
Tourism		-0.045		0.015		-2.998		0.010*
FDI		.011		0.36		.311		.355
Health		-.060		0.59		-1.019		.327
Tax		.003		0.41		.079		.206
Unemployment		.117		0.65		1.804		.227
Note: *p-value significant at alpha = 0.05
Analysis of Variance
Source of Variation	Sum of Squares		Degrees of freedom		Mean Squares		F value		p value
Regression	0.794		8		0.099		15.798		0.000*
Residual	0.082		13		0.006
Total	0.876		21

Equation (3) below models the relationship between the regress and (military burden) and the regressors (total exports of goods and services (percent of GDP), tourism expenditure (percent of GDP), education expenditure (percent of GDP), in reference to the significant variables in Table 3 above.

Military Burden = Military Burden = -0.104+ 0.051Educ + 0.023Export– 0.026Inf –   0.045Tour+.355FDI+.327Health+.206Tax+.227Tax+ ἕ

The share of exports to GDP was directly related to military burden owing to their positive sign. This means that increasing exports increases military burden. It could be recalled that a nation’s “military burden” is the percentage of their gross domestic product that is spent on their military. This means that for every 1% increase in the exports over its GDP, there is an increase in the military burden by 0.023%, all other things being equal. This represents the effect exports have on military burden, provided all other variables remain the same. This study conforms to the findings of [22] in the period of 1987-1990 when he observed that Indian exports increased to fund high technological military systems from Europe and USA. During this period, most Indian military equipment was domestically manufactured and produced with licenses, and India exported acceptable technological military systems to many industrializing and developing countries. The result is also anchored [23] when he suggested that for India to boost its military exports, it should raise funds for importing high technological military equipment and systems and for improving its armed forces. During this period, India designed and produced military equipment and systems, based on collaboration with several American groups and companies specialized in military production, and exported military technologies to oil-rich West Asian nations. In the Philippine context, exports bring more revenue from foreign nations through goods and services that are exported. However, labor is the primary export of the Philippines, and the returns are enormous. The results of the study pointed to increasing exports so as to subsidize increases in military burden in the Philippines. Tourism expenditure as a percent to GDP, on the other hand, was significantly but negatively related to military burden. This means that an increase in tourism expenditure to GDP decreases military burden. The beta coefficient for tourism expenditure was negative 0.045. This implies that for every 1 percent increase in tourism expenditure percent in GDP, the military burden decreases by 0.045%, provided that all other variables remain the same.   This result confirms the findings of [23] when he observed that military spending had a significant opportunity cost and was classified as a less-than-ideal way to boost economic growth given other alternatives, such as spending on infrastructure. According to the study, increasing military spending was not the sole effective strategy for achieving economic growth. Additionally, it demonstrated the value of private investment, which may be suppressed by military spending. The empirical findings showed that the resources utilized, such as the production of productive capital, are four times more growth-enhancing when compared to the funds designated for military spending. Consequently, there is a critical need for peace measures to accelerate economic growth. These studies suggest that there is a significant trade-off between the utilization of productive economic resources and higher military spending. Increased military spending frequently has an impact on essential social services like health, education, and welfare. The education expenditure percent in GDP was also found to be significant and directly related to military burden owing to the positive sign in its beta coefficient. This implies that increasing expenditures in education also increases military burden. The contribution of education expenditure to military burden is 0.051, this means that the military burden increased by 0.051 percent for every 1 percent in education expenditure over GDP, holding all other variables constant. This result is related to the study of [24] when he examined the empirical analysis of the complex interrelationships between defense spending and public education expenditure in Nigeria. He suggested interrelationships between defense spending and public education expenditure in Nigeria. From this regression result, defense spending has a positive and significant relationship to education. As a result, both education and defense budgets benefit at the expense of socioeconomic activities that are free from organizational pressure. Also, the military can be an effective instrument in mobilizing human resources, disciplined work ethics and fostering basic work skills. Inflation rate, on the other hand, was significantly but negatively related to military burden. This means that a one percent increase in inflation decreases military burden by 0.026, while all other variables remain the same. This result was connected to the study of [25] that suggested that at the highest peak of inflation, the purchasing power for defense reduce in the evidence of comparative analysis budget assumption versus actual inflation. The results conform to the neoclassical economics theory because military burden in the Philippines creates opportunity cost to tourism over GDP and inflation rate with this result government or financial advisers act rationally when making decisions for the best of the economy. It describes how the government allocates defense spending versus social programs. A country’s budget includes military programs for national security or guns, and social programs, such as social security or family assistance, the butter. Politicians have evolved the phrase “guns and butter” for use in all areas of fiscal budgeting where there is a substantial trade-off between defense and social spending. In other words, governments make a difficult choice between the two options (defense versus social spending) based on their perception of which one is better for the country. Following the conceptual framework, military burden was then tested for its relation to economic growth after determining the factors affecting military burden. In the second regression model, the dependent variable was the GDP growth rate with military burden (military expenditure over GDP) as the independent variable.

Table 03: Estimated Coefficient of Military Burden Before Using Instrumental Variables and Tests of Significance of the Effect of Military Burden to Economic Growth, Philippines, 2000 to 2021, OLS

Variable		Unstandardized Coefficient				t ratio		p value
		B		Std. Error
(Constant)		4.412		4.753		-0.928		0.364
MEGDP		0.322		3.872		0.083		0.935
Analysis of Variance
Source of variation	Sum of Squares		Degrees of freedom		Mean Square		F ratio		p value
Regression	0.091		1		0.091		0.007		0.935b
Residual	262.562		20		13.128
Total	262.653		21

Equation (4) below models the relationship between regress and (economic growth) and the regressor (Military burden), in reference to Table 5.

Economic growth = 4.41+0.32Military Burden                                          (Eq.4)

                                       (p-value = 0.935)

Results of the tests are insignificant and so we fail to reject the hypothesis that military burden has no connection to economic growth in the Philippines during the said period. Results of the F test and the t test showed that military burden does not influence economic growth.

Table 04: Estimated Coefficient of Military Burden After Using Instrumental Variables and Tests of Significance of the Effect of Military Burden to Economic Growth, Philippines, 2000 to 2021, 2SLS.

Variable		Unstandardized Coefficient				t ratio		p value
		B		Std. Error
(Constant)		3.661		4.989		0.734		0.472
MEGDP		0.942		4.069		0.231		0.819
Analysis of Variance
Source of variation	Sum of Squares		Degrees of freedom		Mean Square		F ratio		p value
Regression	0.704		1		0.704		0.054		0.819
Residual	262.898		20		13.145
Total	263.603		21

Equation (5) below models the relationship between regress and (economic growth) and the regressor (military burden) after using instrumental variables, in reference to Table 4.

Economic growth = 3.661 +0.94Military Burden                                                 (Eq.5)

                                           (p-value = 0.819)

Results of the F test and the t test still showed that military burden does not influence economic growth. The p-value of 0.819 compared to the p-value of 0.94 (or 94) in the director OLS. Overall, the two approaches (before and after the use of instrumental variables) confirmed that during the period of study, military burden had no significant effect on economic growth. The findings are consistent with the result of the study by [26] which examined the relationship between military expenditure and economic growth in South Africa, during the period of 1964 to 1995. The result mentioned no significant impact of military expenditure to economic growth. This finding is associated with the result of [27] examining the case of military expenditure in India during the period of 1997 to 2007 using a causality test to see if military expenditure hinders or accelerates economic growth. The finding concluded that although the growth of military expenditure did not accelerate growth, it also did not hinder it. The study of [28] suggested that military burden is considered as a suboptimal means to economic growth because there are alternative uses of government spending, such as spending on infrastructure to be more effective to economic growth. The study indicated that in order to promote economic growth military spending is not the most efficient way to promote economic growth because productive capital formation is four times enhanced compared to the resources allocated for military expenditure.

Table 05: Result of the endogeneity test using Hausman test

The basic problem of endogeneity occurs when the explanans (x) may be influenced by the explanandum(y). Employing the Durbin-Wu-Hausman test for endogeneity (a statistical test in econometric used to test for endogeneity), Table 05 above shows a p-value of 0.39 indicating no endogeneity because a p-value less than 0.05 indicates endogeneity. The results suggested (in STATA) that these variables were exogenous. If the test indicates that those variables are exogenous, then a simultaneous equation model may not be necessary. Hence, we can estimate the given equation using (OLS) because they will give efficient and consistent results (spureconomics.com). In this study the variables used to test for endogeneity were export of goods and services as percent to GDP, tourism expenditure as percent to GDP, inflation rate and education expenditure as percent to GDP

4. CONCLUSION

The empirical evidence concerning the relationship between defense spending and economic growth in the Philippines is inconclusive as the result using the two (2) methodologies were not significant. This argument is built upon the belief that military spending usually takes an enormous resource away from other economic activities, such as private consumption and investment, public infrastructure investment, social security programs, etc., and hence deters economic growth. What is clear is that there is a strong relationship between military burden and expenditures in education and tourism, export, and inflation. The empirical evidence concerning the relationship between defense spending and economic growth in the Philippines, although positive in coefficient, is not significant enough to move the economy. This argument is built upon the belief that military spending usually takes enormous resources away from other economic activities, such as private consumption and investment, public infrastructure investment, social security programs, and hence deters economic growth.  What is clear is that there is a strong relationship between military burden and expenditures in education and tourism, export, and inflation. The most important result was the absence of relationship between military expenditure to economic growth in India. The results revealed that although the growth of military expenditure did not boost economic growth, it also did not hinder it. The results revealed that there was no significant impact of military expenditure on economic growth. The continuous regional tension forces the Philippines to adopt a military strategy and support military capabilities. Having a strong defense provides deterrence and security in a changing threat and risk environment. Sustaining a peaceful environment, however, requires a high level of military expenditure. The Philippines realized the importance of the strategic and economic dimension of military industries. Military expenditure is necessary to all other countries regardless because that is a justification of taxation to defend its nations, people, and resources.

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