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13
enero-junio ■ ISSN: 0121- 6805 ▪ e-ISSN: 1909 -7719 ■ pp. 13 -29
2023
Vol. 31(1)
Revista Facultad de
Ciencias Económicas
Economic Eects of Investment in Defense
Research and Development and its Impact
on Productivity in Developed Countries*
Guillermo Alfonso Giraldo Martineza ■ Jimmy Anderson Flórez Zuluagab
■ Diego Fernando Morante Granoblesc ■ Jhon Fredy Escobar Sotod
Abstract: This work is based on the hypothesis that a country’s technological development and innovation in the
security and defense sector is a critical factor for developing high-tech industries and thus promoting the coun-
try ’s competitiveness. This research seeks to establish a correlation between defense economics (), security
investments in research and development (R & R&D), and the generation of value-added produc ts in high-tech
industries from 2009 to 2018, based on models used in the United States, China, and Japan. Quantitative, des-
determining the connection between value-added productivity () indicators related to investments in R&D, the
Competitiveness Index, value-added industries, and high-technology exports creating a correlation between the
DE indicator and investments in research discovering positive relationships among these variables.
Keywords: defense industr y technology; research and development (R&D); value-added industries; high
technology: competitiveness.
Recibido: Aceptado: Disponible en línea: 23/10/2023
Cómo citar: Giraldo Mar tinez, G. A., Flórez Zuluaga, J. A., Morante Granobles, D. F., & Escobar Soto, J. F.(2023). Efec-
tos económicos de la inversión en investigación y desarrollo en defensa y su impacto en la productividad en países
desarrollados. Revista Facultad de Ciencias Económicas, 31(1), 13–29. https://doi.org/10.18359/rfce.6223
Código JEL: A12, C29, O31, O32, O33, F50, F52 , G18
* Artículo resultado de investigación.
a Ph.D. candidate in Technology Management and Innovation, Universidad de Queretaro, Master in Business Adminis-
tration, Universidad Sergio Arboleda, Technology and Innovation vice-principal For Colombian Air Force(FAC), Bogotá,
Colombia.
Correo electrónico: guillermo.giraldo@fac.mil.co: https://orcid.org/0000-0002-0788-9151
b -
list in securit y and national defense. Researcher of the Organizational World research group of the Remington Universi-
ty Corporation, Medellin, Colombia. Civil Aviation Advisor
: https://orcid.org/0000-0002-0426-1000
c Ph.D. in Technological Management and Innovation, Master in Industrial Engineering. Professor and researcher at the
Colombian Air Force Military Aviation School (EMAVI), Cali, Colombia.
Correo electrónico: diego.morante@emavi.edu.co: https://orcid.org/0000-0001-6543-1694
d
the Organizational World research group of the Remington University Corporation, Bogotá, Colombia.
Correo electrónico: jhon.escobar@uniremington.edu.co: https://orcid.org/0000-0002-6826-6222
DOI: https://doi.org/10.18359/rfce.6223
14
Efectos económicos de la inversión en investigación y
desarrollo en defensa y su impacto en la productividad
en países desarrollados
Resumen: este estudio se fundamenta en la hipótesis de que el avance tecnológico e innovación en
el ámbito de la seguridad y defensa de una nación son factores clave para fomentar industrias de
alta tecnología y, por ende, mejorar la competitividad del país. Esta investigación tiene como objetivo
establecer una correlación entre la economía de la defensa (DE), las inversiones en investigación y
de alta tecnología desde 2009 hasta 2018, basándose en modelos utilizados en los Estados Unidos,
China y Japón. Se emplearon metodologías de investigación cuantitativa, descriptiva y no experi-
mental para la validación estadística. Este enfoque ayudó a discernir la relación entre indicadores de
entre el indicador DE y las inversiones en investigación, descubriendo conexiones favorables entre
estas variables
Palabras clave: tecnología de la industria de defensa; Investigación y Desarrollo (I&D); industrias de
Efeitos econômicos do investimento em pesquisa e desenvolvimento
em defesa e seu impacto na produtividade em países desenvolvidos
Resumo: este estudo se baseia na hipótese de que o avanço tecnológico e a inovação no âmbito
da segurança e defesa de uma nação são fatores fundamentais para fomentar as indústrias de alta
tecnologia e, portanto, melhorar a competitividade do país. Esta pesquisa tem como objetivo esta-
belecer uma correlação entre a economia de defesa (ED), os investimentos em pesquisa e desenvol-
alta tecnologia de 2009 a 2018, com base em modelos usados nos Estados Unidos, China e Japão.
Metodologias de pesquisa quantitativa, descritiva e não experimental foram empregadas para vali-
dação estatística. Essa abordagem ajudou a discernir a relação entre indicadores de produtividade
-
trias de valor adicionado e exportações de alta tecnologia, revelando assim uma correlação positiva
entre o indicador de ED e os investimentos em pesquisa, descobrindo conexões favoráveis entre
essas variáveis.
Palavras-chave: Tecnologia na Indústria de Defesa, Pesquisa e Desenvolvimento (P&D), Indústrias
de Valor Adicionado, Alta Tecnologia, Competitividade.
15
Economic Eects of Investment in Defense Research and Development and its Impact
on Produc tivity in Developed Countries
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
Introduction
In the global environment, the knowledge eco-
nomy is the basis for the development and produc-
tivity of the leading countries through investment
in technology and innovation. However, these
countries also have highly technical and innova-
tive defense industries that promote economic dy-
namics. is study analyzes how the knowledge
produced by the security and defense sector (),
including its materialization and transfer through
inter-organizational relations by the moderniza-
tion, maintenance, and rationalization of defense,
could aect it. is strengthens the transfer of
know-how and the knowledge obtained from re-
search, development, and innovation (++i) pro-
cesses to society and dual-use industries through
knowledge-based economies. Information is pre-
sented through a knowledge and innovation de-
fense system comprising technological, social, and
economic characteristics to overcome future chal-
lenges and strengthen a nation’s competitiveness
based on this type of public spending (Peñalver,
2013).
Moreover, it is explored if there is a correla-
tion between some indicators that reect the
value-added productivity indicator or with
knowledge-based economies, including high-tech
exports, research and development () spending
with Gross Domestic Product (), the competi-
tiveness index, and value-added industries. ese
are associated with the defense economics concept
and the defense budget in in the total Govern-
ment Budget Allocations for R&D () (,
2019a). e analysis aims to determine whether in-
vestments in defense R&D contribute to develop-
ing high-value-added products based on three of
the strongest economies in the world concerning
their : the United States, China, and Japan. Ad-
ditionally, the data published by the World Trade
Organization for 2018, variables analyzed by the
World Bank () and the Organization for Eco-
nomic Cooperation and Development (), and
the Datosmacro website of the Spanish newspaper
Expansión were used as references for this study.
is document attempts to answer the follow-
ing questions: Are there relationships between
investments in research and development in de-
fense and value-added productivity indicators?
Are value-added productivity indicators associ-
ated with the budget allocated for defense purpos-
es in in the United States, China, and Japan?
ese questions seek to establish the eect these
investments generate in knowledge-based econo-
mies distinguished by the high value-added of
their productivity. is productivity is displayed
in product and service generation knowledge and
is reected in each country’s respective industries.
Furthermore, the existing relationship in defense-
focused investments in science, technology, and
innovation, with productive factors including
competitiveness, the development of high technol-
ogy, and the generation of high value-added in-
dustries in the strongest economies in the world,
is also analyzed. For this study, statistical analy-
sis tools, such as Pearson’s Correlation and simple
linear regression techniques, are used to establish
the correlation between value-added productivity
variables, representing the concept of the knowl-
edge economy, and the defense budget variable
in , representing defense economics. In addi-
tion, a review of the relevant theories that address
knowledge and defense economies was conducted
to establish how these two concepts are related by
analyzing the indicators of investment in and
how the literature review performed can be a stra-
tegic driver for generating knowledge.
Theoretical Framework
Economy Knowledge
During the 1970s in the United States, industries
based on microelectronics and technology experi-
enced signicant growth, generating new econom-
ic growth paradigms. ese integrated aspects,
such as technical progress, education, research,
experimental development, and innovation, in-
creased knowledge and placed economic capital in
the background (Dávila, 2008). Since then, the im-
portance of technological changes in the industry,
the economy, and new nancing methods in in-
novative markets has been demonstrated (Porter,
2012; Alam et al., 2017).
16 ■ G. A. Giraldo Martineza ■ J. A. Flórez Zuluaga ■ D. F. Morante Granobles ■ J. F. Escobar Soto
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
is is the basis of knowledge economies, de-
ned by the as those systems that demon-
strate dynamism, growt h, wealth, and employment
originating from the production and intensive use
of information, technology, and knowledge to gen-
erate high-value-added products to strengthen
the competitiveness of nations (Sánchez & Ríos,
2011); value-added productivity indica-
tors were used for this denition. In these econo-
mies, knowledge must be the center of the strategy,
based on four pillars: education and training; in-
frastructure for information access and telecom-
munications; innovation systems; and government
and business institutions (Sánchez & Ríos, 2011).
Defense Economy (DE)
Defense investments represent essential partici-
pation in creating innovation networks and tech-
nological infrastructures and promoting national
institutional policies to foster the allocation of re-
sources to generate highly technical knowledge.
An applied example is described in a case study
conducted by Florez Zuluaga et al. (2021) directed
to achieve technological sovereignty and the po-
tential savings of a country’s economy in applied
defense economics or .
consists of the ecient management and
administration of the human, material, and tech-
nological resources necessary to guarantee the
interests, security, and defense of all citizens, the
integrity of the territory, and national sovereignty
while contributing to the general economic well-
being of the country. It also seeks the articulation
of defense with the economic growth (Fernández,
2017), understanding transversality and dual-use
in markets other than a defense that have vari-
ous products developed in this industry. Further-
more, defense spending enables the formation of
new companies due to dual-use innovations and
establishes a valuable cycle of knowledge produc-
tion and the introduction of wealth creation pro-
cesses (Dávila, 2008). is is also a specialized
branch of economic knowledge applied to a state
activity that uses interdisciplinary approaches (Vi-
ñas, 1984), ranging from the economic eects of
defense spending and its relationship with the civil
sector to the administration, management, and
distribution of these resources. erefore, it can
be inferred that a connection between the of
knowledge-based economies and the defense
budget exists as they measure intensive activities
in knowledge creation. Consequently, analyzing
the indicators’ denition, form, and structure is
used as representative study variables. ese vari-
ables are listed below.
Value-added Productivity (VAP)
e indicator is that the additional economic
is the fundamental value obtained by goods and
services when transformed during production. In
other words, it is the monetary value that a given
production process adds to intermediate consump-
tion, such as the inputs used in the production
and distribution (Fuenzalida, 2002). Based on
this indicator, it can be assumed that developing
countries are characterized by a labor-intensive
industrial sector with low value-added, such as the
production of primary goods or their rst trans-
formation phase. In contrast, developed countries
have a knowledge-intensive economy generating
high value-addition; these concepts were created
by Adam Smith and David Ricardo, the founders
of the classical economic theory of international
trade (Fuenzalida, 2002). Consequently, the study
indicators used to measure productivity and the
capacity to generate value-added included
spending concerning the (annual %), the
competitiveness index, value-added industries (%
of ), and exports of high-tech products (% of
exports of manufactured products).
National indicators were also considered as
they refer to investments, the competitiveness
index, value-added industries, and high-tech ex-
ports to determine the correlation between the
indicator and the research defense () budget
included in the total government budget allocated
to (, s.f., 2019).
R&D Spending Concerning the GDP
On the other hand, R&D spending concerning the
(annual %), according to the World Bank,
shows that expenditures correspond to cur-
rent and capital expenditures on creative work,
17
Economic Eects of Investment in Defense Research and Development and its Impact
on Produc tivity in Developed Countries
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
systematically performed to increase knowledge
about humanity, culture, and society, and the use
of knowledge for new technological applications.
e department encompasses basic research,
applied research, and experimental development
(Banco Mundial, 2019b). is measurement makes
it possible to identify the investment capacity of
nations in knowledge generation. It is the
foundation for establishing perspectives regard-
ing sustainable development and strengthening
knowledge economies. is indicator enjoins gov-
ernments to promote sustainable industrializa-
tion and innovation through the rapid increase in
spending on and increment in the number of
researchers (Unesco, 2016). Innovation has become
necessary for transforming productive structures,
education, and other social requirements. e
highlights innovation as essential to increase
productivity, performance, and scientic and tech-
nological knowledge. (, 2015).
Global Competitiveness Index (GCI)
In terms of the Global Competitiveness Index ()
this instrument measures how a country uses its
available resources and its ability to provide its
inhabitants with a high level of economic prosper-
ity. In classifying countries according to competi-
tiveness, this indicator analyzes twelve variables,
among which the following stand out: infrastruc-
ture, macroeconomic environment, higher educa-
tion and training, market eciency, technological
preparation, and innovation. In this setting, com-
petitiveness is understood as a branch of economics
that analyzes the facts and policies that encourage
a nation’s capacity to create and maintain an en-
vironment that adds more value to its companies
and brings prosperity to its population (Álvarez et
al., 2012, p. 13). Moreover, competitiveness con-
tributes to factors that determine the growth of a
nation as a tool for formulating economic policies
and institutional reforms and making strategic
and investment decisions. erefore, the country’s
level of competitiveness is essential for its growth
and is supported by productivity and investments
(Schwab, 2016).
Value-added Industries, as a
GDP Percentage
In reference to the value of goods or services ac-
quired in the production chain; that is, the value
generated through each new participation in terms
of work or processing of a good and can be ana-
lyzed in monetary units based on the competitive-
ness of each economic agent of a country (Banco
Mundial, 2021). Value-added is the industry’s net
output aer adding all outputs and subtracting
intermediate inputs. Value-added is calculated
without deductions related to the depreciation of
manufactured goods or the depletion or degrada-
tion of natural resources (Banco Mundial, 2021).
Highly developed countries are those that can add
more value to their products. is value results in
higher life quality for their citizens. In this sense,
value-added is a core concept concerning knowl-
edge economies.
High-tech Product Exports
e indicator for high-tech product exports (as
a percentage of manufactured products exports)
measures high-tech products’ exports. ese prod-
ucts are highly intensive in , such as those of
the aerospace, computer, and pharmaceutical in-
dustries (Banco Mundial, 2019a). is technology
can provide numerous advantages for developing
an economy by creating and generating a criti-
cal mass of knowledge. As a result, the produc-
tion possibility frontiers of a country will improve
competitiveness indexes, thus creating participa-
tion in new technology-based markets, which, in
turn, will strengthen the .
The Defense Budget in R&D
of GBARD
Regarding the defense budget in of
(Government Budget Allocations for ), the bud-
get is based on analyzing three essential aspects of
economic activities: production, allocation, and
distribution. e rst aspect refers to the determi-
nation of goods produced, the second refers to the
use of limited resources in production lines, and
the third refers to the receivers and beneciaries
18 ■ G. A. Giraldo Martineza ■ J. A. Flórez Zuluaga ■ D. F. Morante Granobles ■ J. F. Escobar Soto
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
of production. When these traditional economic
perspectives are applied to defense matters, they
are related to the following specic issues (Martín,
1984): determination of security needs of the col-
lective good obtained in defense; allocation of re-
sources towards defense to the detriment of other
departments, and the resolution of defense spend-
ing beneciaries.
Defense Spending
It is important to stress that defense spending is a
signicant accelerator to scientic research, tech-
nological development, and innovation (R+D+i)
(Fernández, 2017), resulting in a key determining
factor for knowledge production. Furthermore,
this product can be transferred to other economic
sectors, generating value-added in dierent pro-
duction processes.
For example, transfers can occur through co-
operation agreements between government agen-
cies and industries (Leydesdor & Meyer, 2003), in
which cases based on are distinctive, exhibiting
interdependence between various organizations.
Another example is the United States, in which
technological developments for non-military pur-
poses are leveraged by investments in military and
defense research (Ruttan, 2006). Likewise, invest-
ments supported by the North Atlantic Treaty
Organization () in Europe have contributed
to economic and industrial developments in the
same sectors as the (Kluth, 2017). It can be
concluded that the defense sector and military ac-
quisitions contribute positively to the development
of multiple industries, such as aeronautics, energy,
information, and communication technologies
(), and are crucial for the world economy.
However, a possible obstacle to military spend-
ing investments (Viñas, 1984) is related to defense
programs using a signicant part of a country’s
technological and scientic talent and consum-
ing an actual amount of the goods and services
channeled to the nation’s public sector. is is due
to a high degree of productive and technological
specializations required, leading to a growth in
the activity. As a result, the Statistical Oce of
the European Communities and the dened
the index to identify the public budget al-
located to to determine the nancial potential
assigned by a public administration to strengthen
the national economic development (, 2019).
Methodology
e gathered information was taken from the Fra-
scati Manual guidelines to compare with other
countries’ results. (, 2015). is analysis was
conducted using descriptive quantitative tech-
niques under a non-experimental study model;
no changes in the researched variables related to
reactions, results, and consequences occurred.
Likewise, a simple linear correlation analysis was
conducted based on linear regression and the cor-
relation coecient to discover the relationship
between indicators and defense budget invest-
ments in related to the total budget for .
e correlation coecient is an index used to
measure the relationship between two quantitative
variables (Hernández Sampieri et al., 2014). e
coecient has a scale of –1 to 1, where 0 indicates
no relationship between the variables, while 1 or
–1 indicates a perfect positive or perfect negative
correlation between the two variables, respectively
(Camacho, 2008). Table 1 displays the correlation
ranges of this coecient.
Table 1. Pearson Coecient Rating Criteria
Ranges Score
0-0.3
(– 0.3)-0 Short
0.31-0.6
(– 0.31)-(– 0.6) Moderate
0.61-0.9
(– 0.61)-(– 0.9) High
0.91-1
(– 0.91)-(– 1) Very high
Source: Data crea ted by this study based on A lmaraz (2018).
On the other hand, linear regression establishes
the best equation representing the relationship
between the selected variables from the equation
Y=mx+b determined by the least-squares method,
19
Economic Eects of Investment in Defense Research and Development and its Impact
on Produc tivity in Developed Countries
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
quantifying the dierences between the observed
values and the predicted values of all possible lines
(Reding Bernal et al., 2011; Chavez Leandro, 2013).
For this, the coecient of determination (R2)
represents a quantitative measurement of the ad-
justment percentage of the model (Hernández
Sampieri et al., 2014). In addition, a direct or in-
verse linear relationship is established between the
variables X (independent) and Y (dependent) (Al-
maraz et al., 2018; Chavez Leandro, 2013).
For the development of the project, the follow-
ing hypotheses were stated:
◾Ho and Hi mean that the indicators have
and do not have a relationship with the de-
fense budget.
e following were alternative hypotheses (Ha):
◾Ha1: e defense budget is related to high
technology exports.
◾Ha2: e defense budget is related to spen-
ding in .
◾Ha3: e defense budget is related to the
competitiveness index.
◾Ha4: e defense budget is related to the
value-added industry.
e criteria for evaluating the study hypotheses
were: if a Pearson coecient of determination and
correlation equal to 0 existed, the Ho (null hypoth-
esis) was accepted. If Pearson’s coecient of deter-
mination and correlation diered from 0, Hi and
Ha were accepted.
Results
For the construction of the analyzed variables, data
were obtained from the World Bank, the , the
Spanish website Datosmacro, and the R&D defense
budget indicator related to the total in mil-
lions of . In China, this indicator is constructed
with data on military spending in millions of
from the World Bank, multiplied by the de-
fense budget, resulting in a percentage of the total
of Chinese Taipei. However, China does
not record these measurements in the as it
is considered a non-aligned country (Tables 2-4).
Table 2. Variables of the United States
Year
Expor ts of
Manufactured
Products (%)
Spending
(Annual % of )
Competitiveness
Index
Industry, Value-Added
(% of )
R&D Defense Budget -
(Millions of )
2009 25.01 2.82 82.06 19.32 57046000
2010 23.12 2.74 79.86 19.36 55765000
2011 21.07 2.77 77.59 19.42 51027000
2012 20.66 2.69 77.5 3 19.16 51662000
2013 20.65 2.72 78.11 19.26 46894000
2014 21.00 2.73 78.32 19.30 46109000
2015 21.95 2.73 79.2 18.52 47927000
2016 23.01 2.77 80.19 17.95 53782000
2017 19.69 2.80 83.57 18.21 55441000
2018 18.90 2.84 85.64 No information
registered 6749400
Source World Bank ()Datosmacro -current prices
Source: Study calculations.
20 ■ G. A. Giraldo Martineza ■ J. A. Flórez Zuluaga ■ D. F. Morante Granobles ■ J. F. Escobar Soto
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
Table 3. Variables of China
Year
Expor ts of
Manufactured
Products (%)
Spending
(Annual % of )
Competitiveness
Index
Industry, Value-Added
(% of )
Defense Budget -
(Millions of )
2009 31.95 1.93 67.12 45.96 7426790
2010 32.15 1.92 67.6 6 46.50 7921200
2011 30.50 1.97 69.08 46.53 7999240
2012 30.86 2.00 69.97 45.42 5216140
2013 31.58 2.02 68.97 4 4.18 5133580
2014 29.70 2.04 69.09 43.28 5148920
2015 30.43 2.04 69.87 41.11 5406280
2016 30.25 2.05 69.84 40.07 11338020
2017 30.89 2.06 71.43 40.54 14674650
2018 31.40 2.19 72.61 39.69 17390930
Source World Bank ()Datosmacro -current prices
Source: Study calculations.
Table 4. Variables of Japan
Year
Expor ts of
Manufactured
Products (%)
R&D Spending
(Annual % of )
Competitiveness
Index
Industry, Value-Added
(% of )
Defense Budget -
(Millions of )
2009 20.60 3.23 76.79 27.27 1144116000
2010 19.20 3.14 76.71 28.44 1534506000
2011 18.4 3.24 76.7 26.88 901006000
2012 18.30 3.21 77.0 9 26.75 1032194000
2013 17.8 0 3.31 77. 0 8 26.94 1647232000
2014 17. 8 0 3.40 7 7.11 27.69 1567557000
2015 18.10 3.28 78.18 29.02 1466848000
2016 17. 3 0 3.16 78.09 28.98 1004820000
2017 17.6 0 3.21 78.43 29.16 1160051000
2018 17. 3 0 3.26 82.47 29.07 995780000
Source World Bank ()Datosmacro -current prices
Source: Study calculations.
e studied variables are related to the con-
cepts of and being signicant factors in the
production process of a developed country; this
is a result of contributions to ++i as they create
dual-use products (military and civil), and these
become the primary assets of a nation by demon-
strating an ability to generate knowledge as a fun-
damental element of productivity (Schwab, 2016).
Once more, this exhibits the impact of defense
investments in dual-use projects, indicating how
defense investments can disruptively aect
markets and a population’s life quality (Yuan et al.,
2016).
e variables demonstrate vital indicators
to dene the behavior and impacts of knowledge
generation and how this is reected in the eco-
nomic development of a nation. e variables of
defense demonstrate how these investments
21
Economic Eects of Investment in Defense Research and Development and its Impact
on Produc tivity in Developed Countries
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
contribute to meeting security threats and, si-
multaneously, solving operational and logistical
situations that allow military advantages in the
territories of study. When the linear regression
and determination of correlation coecients were
performed, the results were obtained per country,
as exhibited in Tables 5-7 and Figures 1-3.
y = -0,00000039x + 0,23594724
R² = 0,01864266
y = 0,00000006x + 0,02458430
R² = 0,58939677
y = 0,0004x + 60,26
R² = 0,7394
y = -0,00000025x + 0,20245587
R² = 0,03352379
R&D Defense Budget (Millions of USD)
0%
5%
10%
15%
20%
25%
30%
0
10.000
20.000
30.000
40.000
50.000
60.000
70.000
80.000
Exports in High Technology
(%MP)
R&D Defense Budget (Millions of USD)
0
10.000
20.000
30.000
40.000
50.000
60.000
70.000
80.000
Expenditure on R&D (% GDP)
2,68%
2,70%
2,72%
2,74%
2,76%
2,78%
2,80%
2,82%
2,84%
2,86%
R&D Defense Budget (Millions of USD)
0
10.000
20.000
30.000
40.000
50.000
60.000
70.000
80.000
Competitiveness Index
R&D Defense Budget (Millions of USD)
0
10.000
20.000
30.000
40.000
50.000
60.000
70.000
80.000
Industry Value Added (% GDP)
77
78
79
80
81
82
83
84
85
86
87
17,8%
18,0%
18,2%
18,4%
18,6%
18,8%
19,0%
19,2%
19,4%
19,6%
Table 5. Results of the United States
Indicator Relationship Straight Line Equation
R²
Multiple
Correlation
Score
Pearson
Correlation
Relationship
Type
R&D Defense
Budget
related to
GBARD total
(Millions of
USD)
High-tech Exports (% Exports
of Manufactured Products) y = -0.00 000039x + 0.23594724 0.019 0.137 Short - 0.137 Inverse
Relationship
R&D Spending
(% GDP)y = 0.00000006x + 0.02458430 0.589 0.768 High 0.768 Direct
Relationship
Competitiveness Index y = 0.0004x + 60.26 0.739 0.860 High 0.860 Direct
Relationship
Value-added Industry
(% GDP)y = -0.000 00025x + 0.20245587 0.034 0.183 Short - 0.183 Inverse
Relationship
Source: Study calculations.
Figure 1. Graphs of the United States
Source: Study calculations.
22 ■ G. A. Giraldo Martineza ■ J. A. Flórez Zuluaga ■ D. F. Morante Granobles ■ J. F. Escobar Soto
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
Table 6. Results of China
Indicator Relationship Straight Line Equation
Multiple
Correlation
Score
Pearson
Correlation
Relationship
Type
R&D Defense
Budget
related to
GBARD total
(Millions of
USD)
High-tech Exports
(% Exports of Manufactured
Products)
y = 0.00000024x + 0.30763636 0.017 0.130 Short 0.130 Direct
Relationship
R&D Spending (% GDP)y = 0.0000001x + 0.0192054 0.437 0.661 High 0.661 Direct
Relationship
Competitiveness Index y = 0.0003x + 67.25 0.502 0.708 High 0.708 Direct
Relationship
Value-added Industry
(% GDP)y = -0.000 004x + 0.468 430 0.395 0.628 High -0.628 Inverse
Relationship
Source: Study calculations.
Figure 2. Graphs of China
Source: Study calculations.
y = 0,0003x + 67,25
R² = 0,5016
y = 0,00000024x + 0,30763636
R² = 0,01691837
y = 0,0000001x + 0,0192054
R² = 0,4369187
y = -0,000004x + 0,468430
R² = 0,394888
R&D Defense Budget (Millions of USD)
0
5.000
10.000
15.000
20.000
0
5.000
10.000
15.000
20.000
0
5.000
10.000
15.000
20.000
0
5.000
10.000
15.000
20.000
Competitiveness Index
R&D Defense Budget (Millions of USD)
Exports in High Technology
(%MP)
R&D Defense Budget (Millions of USD)
Expenditure on R&D (% GDP)
R&D Defense Budget (Millions of USD)
Industry Value Added (% GDP)
66
67
68
69
70
71
72
73
29,5%
30,0%
30,5%
31,0%
31,5%
32,0%
32,5%
39,0%
40,0%
41,0%
42,0%
43,0%
44,0%
45,0%
46,0%
47,0%
1,90%
1,95%
2,00%
2,05%
2,10%
2,15%
2,20%
23
Economic Eects of Investment in Defense Research and Development and its Impact
on Produc tivity in Developed Countries
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
Figure 3. Graphs of Japan
Source: Study calculations.
Table 7. Results of Japan
Indicator Relationship Straight Line Equation
Multiple
Correlation
Score
Pearson
Correlation
Relationship
Type
R&D Defense
Budget
related to
GBARD total
(Millions of
USD)
High-tech exports
(% Expor ts of
Manufactured
Products)
y = 0.000093x + 0.048772 0.003 0.054 Short 0.054 Direct
Relationship
R&D Spending
(% GDP)y = 0.00000120x + 0.03096250 0.18887301 0.436 Moderate 0.435 Direc t
Relationship
Competitiveness
Index y = -0.0020000x + 80.3558291 0.1024833 0.321 Moderate -0.319 Inverse
Relationship
Value-added
Industry (% GDP)y = -0.0000007x + 0.2810689 0.0003664 0.020 Short -0.019 Inverse
Relationship
Source: Study calculations.
y = -0,0020000x + 80,3558291
R² = 0,1024833
y = 0,00000120x + 0,03096250
R² = 0,18887301
y = 0,0000007x + 0,2810689
R² = 0,0003664
y = 0,000002x + 0,179971
R² = 0,002924
R&D Defense Budget (Millions of USD)
0
500
1.000
1.500
2.000
0
500
1.000
1.500
2.000
0
500
1.000
1.500
2.000
0
500
1.000
1.500
2.000
Competitiveness Index
R&D Defense Budget (Millions of USD)
Expenditure on R&D (% GDP)
R&D Defense Budget (Millions of USD)
Industry Value Added (% GDP)
R&D Defense Budget (Millions of USD)
Exports in High Technology
(%MP)
76,0
77,0
78,0
79,0
80,0
81,0
82,0
83,0
3,10%
3,15%
3,20%
3,25%
3,30%
3,35%
3,40%
3,45%
26,5%
27,0%
27,5%
28,0%
28,5%
29,0%
29,5%
17,0%
18,0%
19,0%
20,0%
21,0%
24 ■ G. A. Giraldo Martineza ■ J. A. Flórez Zuluaga ■ D. F. Morante Granobles ■ J. F. Escobar Soto
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
Discussion
e data obtained enabled us to answer the re-
search question regarding a relationship between
defense investments and Value-added produc-
tivity, indicating an agreement with the research
hypothesis (), as expressed by the multiple cor-
relation indicators and correlation coecients of
each country analyzed. Subsequently, the relation-
ship variables with each hypothesis proposed in
this research were explored. As a result, Ho was
discarded since the indicators studied re-
vealed correlations dierent than 0 related to the
defense budget indicators. Furthermore, a re-
lationship between and knowledge economies
was exhibited, validating the Hi. erefore, high-
lighting certain aspects, such as the collaboration
between military and civilian , is essential,
facilitating a country’s development and strength-
ening its economy, resulting in benecial eects
(Peñalver, 2013).
Regarding Ha1, the defense budget vari-
able aects high-tech exports with low ratings in
correlation coecients of 0.137, 0.130, and 0.04 for
the United States, China, and Japan, respectively.
In the case of the United States and China, this
situation should be studied further as it is highly
signicant to . Nonetheless, there is a correla-
tion regarding Ha1 in the three countries stud-
ied. Moreover, a direct relationship between the
variables analyzed in Ha1 for the United States
was absent. However, the country possesses the
leading companies in defense markets and re-
corded worldwide sales in 2018 of approximately
148040 000000 (, 2019b). is is dem-
onstrated by the decrease in the country’s exports
during the ten-year period analyzed (from 2009 to
2018), which experienced a decline from 25.01%
to 18.9 %. However, the defense budget in
increased from 57045000000 to 67494000000
. Since this indicator considers the exports of
high-tech products, deemed -intensive, the re-
lationship between these indicators contributes to
the ongoing worldwide demands concerning gen-
erating high-tech products and services in global
competitiveness.
Various research has been conducted in Japan,
another country analyzed in this study, demon-
strating the accelerating factors of the economy
following World War II. is is related to massive
production processes, the exchanging of monopo-
lies for “trade groups,” the inuence of education
on development, and the creation of the Agency for
Industrial Science and Technology. Japan’s success
is attributed to the importance given to human
capital in its evolution as a country. is implies
that Japan’s productive capacity was strongly in-
uenced by its developed capabilities due to World
War II’s war economy and its productive alliance
with the United States (Uribe Taborda & Mesa-
Palacio, 2019).
Regarding Ha2, the correlation coecient for
the United States, China, and Japan permits a di-
rect relationship to be established, showing a high
correlation in the cases of China and the United
States, with correlation coecient variables of
0.768 and 0.661, respectively. For Japan, the rela-
tionship is moderate, with a coecient of 0.425.
Likewise, there are various studies on the role that
has in a nation’s defense, in which dierent
perspectives have developed (Guellec & Van Pottel-
sberghe, 2003), demonstrating that in science
and technology (S&T) in defense has a “crowding
out” eect on civil and . Goel, Payne, and
Ram (Goel et al., 2008), discovered that the growth
impacts of public are more signicant than
that of private . e impact of public R&D
on defense is more important than that of non-
defense . For studies performed in Asian and
Latin American countries, Morales-Ramos (2002)
discovered that in national defense creates
a displacement eect on the country’s economic
growth due to its adverse impacts on investments.
By constructing a production function model con-
taining the stock of “knowledge capital,” Zeng and
Yunzhuang (2006) stated that defense pro-
duction signicantly contributes to the growth
of total defense productivity factors and creates
a positive spillover eect on national economic
growth. Yongzhi and Guangming (2010) dem-
onstrated that defense inputs in S&T have a
25
Economic Eects of Investment in Defense Research and Development and its Impact
on Produc tivity in Developed Countries
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
“crowding out” eect on civilian inputs. ere
is a reasonable proportion of defense with a
maximizing impact on national economic growth.
Lastly, Yonggang and Xiaofeng (2010) examined
the technological diusion of space technology
through a theoretical model based on three factors
(the technology return rate, the rate of technology
transfer, and industrial connections), combining
the idea of “eld,” concluding that technological
diusion revealed a state of decline and resembled
a “damped wave” with the extension of time, this
is also discussed in (Yuan et al., 2016).
In research studies regarding defense inno-
vations performed in China, data from both the
aviation and aerospace industries were considered
relevant and are primary participants within the
defense industry. While data from civil sector
operations were included, the inuence of ship-
building, electronics, and other adjacent sectors
within the defense industry was not considered
(Yu a n et al., 2016). Based on the previous studies,
a direct connection can be anticipated between
knowledge production in the defense sector, and
the allocation of public and private resources
in the countries researched. is connection is re-
ected in the size of defense industries, research
results, manufacturing patents, and the position-
ing of universities. As a result, articulating the
defense industry with various economic sectors
contributes to industrial, economic, and knowl-
edge development. However, the connection of
the defense industry with the economic and social
growth of a country has yet to be conclusive in
various theoretical models, empirical techniques,
and research samples in other eld studies (Hou &
Chen, 2013).
ere are ecient technology transfer pro-
grams in countries like the United States with
solid technological infrastructure. e Depart-
ment of Defense directly inuences the economy
through signicant investments, allocating over
40% of the defense research budget. As a result,
approximately one-third of the country’s scientists
and engineers work in the defense sector activi-
ties (Hernández Mosquera, 2011). A similar situa-
tion occurred in China. During the last ten years,
investments in defense research increased from
7426000000 in 2009 to 17390000000
in 2018, positioning its military industry among
the ve most important military sectors world-
wide. Lastly, while this trend has remained stable
in Japan, the country ultimately reduced its invest-
ments in defense research during the same period.
Ha3 is true in the case of the United States and
China. ese countries exhibit a high and direct
relationship with a correlation coecient of 0.86
and 0.708, respectively. However, in the case of Ja-
pan, the relationship is inverse and moderate, with
a correlation coecient of 0.319. e economic
model of the United States allows the military in-
dustry to inuence security and defense market
worldwide signicantly: the maintains 34 %
of the global arms market and supplies more than
one hundred countries. In contrast, China cur-
rently covers 6.2% of the world market and is the
h largest country in the global weapons exports
(, 2019b), thus impacting each China’s com-
petitiveness index factor.
In the case of China, this is reected in the ar-
ticulation of the arms industry development with
the State through joining the Chinese productive
defense system with the creation of the State Ad-
ministration for Science, Technology and Industry
for National Defense (). is entity de-
pends on the Chinese Ministry of Industry and In-
formation Technology, which coordinates with the
People’s Army of China to lead State entities and
the country’s defense industrial actors (Depart-
ment of Defense, 2018). Likewise, the government
relies on the National Natural Science Founda-
tion of China () and the Chinese Academy
of Sciences () to develop high technology for
defense. ese institutions work together to re-
solve conicts of interest in the university-com-
pany-State triad to eliminate adverse eects in
pursuing China’s industrial goals and geopoliti-
cal interests. Taking this into consideration, it is
essential to highlight that the United States has
programs, such as the Small Business Innovation
Research/Small Business Technology (/)
(, 2020), to integrate the development of in-
novative small business solutions and to provide
26 ■ G. A. Giraldo Martineza ■ J. A. Flórez Zuluaga ■ D. F. Morante Granobles ■ J. F. Escobar Soto
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
opportunities, guidance, and support in the trans-
fer or transition of technology in the war industry
or commercial markets. is is supported by a gov-
ernment policy issued in the Commerce and Trade
– Code, Chapter 15, Article 638: “Research and
Development” (Commerce and Trade - Code).
is demonstrates that the competitiveness index
in the countries analyzed is positively inuenced
by the defense budget. Furthermore, although
research is conducted in defense-related institu-
tions, knowledge returns escalate this industry,
strengthening the factors measured by this index,
such as infrastructure, local institutions, the mac-
roeconomic environment, technological readi-
ness, and innovation.
Regarding Ha4, in the United States, China,
and Japan, there is an inverse relationship with cor-
relation coecients of -0.183, -0.628, and -0.019,
respectively. is relationship can be explained
through industrial systems, which are reected
in the value-added variables of their industries.
erefore, these can be constructive strategic pro-
posals regarding Codes 10 to 45 of the (Inter-
national Standard Industrial Classication of All
Economic Activities) and include:
◾Section C for manufacturing industries (
Divisions 10 to 33)
◾Section D for the supply of electricity, gas,
steam, and air conditioning ( Division 35)
◾Section E for water supply, sewerage, waste
management, and remediation activities (
Divisions 36 to 39)
◾Construction Section F ( Divisions 41 to 43)
and
◾Section G for wholesale and retail trade and
repair of motor vehicles and motorcycles (
Division 45) (IndexMundi, s.f.).
is inverse relationship occurs as representa-
tive industries are included, such as automotive,
aeronautics, space, naval, information technol-
ogy, communications, machinery, and equip-
ment, and represent a signicant income for
economic development. is development relies
on large technology-based corporations, such as
Huawei™, Tencent™, and Sense Time™ in China,
where markets exist due to the signicant popu-
lation size and large manufacturing capacities
with a global scope through platforms such as
Alibaba™. e United States also has technology-
based companies with a worldwide impact, such
as Wal-Mart™, Amazon™, Apple™, ™, and the
Alphabet Group™, companies in the 2020 Fortune
500, ranking among the top ten globally. Japan
is listed in this ranking, with companies such as
Toyota™, Mitsubishi™, and Sony™, and has most
companies in the same ranking (Fortune, s. f.).
Table 8. Acceptance of Research Hypotheses (Study Calculations)
Hypothesis United States China Japan Hypothesis
Acceptance
Ho VAP indicators are not related
to the R&D defense budget Relationship Exists Relationship Exists Relationship Exists Hypothesis
Not Accepted
Hi VAP indicators are related to
the R&D defense budget Relationship Exists Relationship Exists Relationship Exists Hypothesis
Accepted
Ha1 R&D defense budget is related
to high-technology exports
There is a Low
Relationship
There is a Low
Relationship
There is a Low
Relationship
Partially Accepted
Hypothesis
Ha2 R&D defense budget is related
to R&D spending
There is a High
Relationship
There is a High
Relationship
There is a Moderate
Relationship
Hypothesis
Accepted
Ha3 R&D defense budget is related
to the competitiveness index
There is a High
Relationship
There is a High
Relationship
There is a Moderate
Relationship
Hypothesis
Accepted
Ha4 R&D defense budget is related
to the value-added industry
There is a Low
Relationship
There is a High
Relationship
There is a Low
Relationship
Partially Accepted
Hypothesis
27
Economic Eects of Investment in Defense Research and Development and its Impact
on Produc tivity in Developed Countries
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
Finally, it was demonstrated that contrib-
utes to in the United States, China, and Japan
through various relationships and correlation lev-
els in the variables analyzed. It also contributed to
the hypotheses validation, as listed in Table 8.
Conclusions and
Recommendations
e literature reviewed reveals that the R&D de-
fense budget impacts each VAP indicator studied.
erefore, for opportunities in the current eco-
nomic dynamics, knowledge is the primary asset
that will generate future wealth. For this reason,
the strength of knowledge economies will consist
of each nation’s ability to produce this new asset
systematically (Kaku, 2011).
Accordingly, social responsibility is placed on
those who create decisions on the economic eects
of allocating resources for defense activities. is
entails opportunity costs placed above other pub-
lic needs, thus increasing the stock of State capital
goods for the country’s economic growth (Viñas,
1984). However, suppose this defense spending is
focused on creating national production capacities.
In that case, it can become a generator of economic
assets, promoting development of high-value-add-
ed products and services based on knowledge.
In the context of the fourth industrial revolu-
tion, the world economy favors opportunities in-
volving the unsatised needs of millions of people
through technology and information, then public
policies are being designed to support this op-
portunity like ( 3975 - National Policy for
Digital Transformation and Articial Intelligence,
2019; 4069. National Science, Technol-
ogy and Innovation Policy, 2021), documents de-
scribing these policies for the case of Colombia. It
encourages additional demand for products and
services by empowering and connecting people
and communities worldwide (Schwab, 2016).
e three countries analyzed have implemented
and integrated national strategies. ey focus their
defense resources to generate a spillover eect
in various economic sectors, strengthening intel-
lectual capital and technological infrastructures
to develop sustainable competitive advantages.
Currently, the greatest asset of societies is knowl-
edge, and it is a valuable opportunity for both
R&D and defense spending to act as generators
and stimulators of new technologies in developing
countries. By acting as risk investors, the Nations
will allow the development of innovations for eco-
nomic growth and, at the same time, channel the
entry of foreign technologies toward eliminating
technological gaps.
e current economy and globalization create
ties of interdependence by establishing interna-
tional security and treaties, making a more
accessible transfer of knowledge and technologies
from developed countries to developing countries.
is reinforces the theory of military spending as
a value-added mechanism and generates a coun-
try’s economic and social development. From this
perspective, military spending can be a factor
in generating wealth and knowledge to transform
the concept of spending into the concept of invest-
ment; this can be reected in improvement,
institutionality, innovation, economic growth, and
the life quality of citizens, through strengthening
other social indicators and positively impacting
the economy.
Investments are also reected in the coun-
tries’ multidimensional security as it integrates
factors that can aect security in cultural, social,
personal, political, economic, and environmental
dimensions. erefore, a nation must plan com-
prehensive security policies reected in the Sus-
tainable Development Goals () programs. is
implies adopting approaches of multidimensional
security where the defense R&D signicantly con-
tributes to obtaining national capabilities in meet-
ing these goals (Barrero etal., 2018).
It can be concluded that the countries of the
United States, China, and Japan are submerged in
knowledge economies with high rates of competi-
tiveness and value-addition in their industries and
have close relationships with competitiveness indi-
cators, directly and indirectly, thus, revealing the
inuence of expenses on defense in their .
Based on these conclusions and by analyzing
the recent history of Colombia, it could also be
concluded that in the country, due to the inter-
nal conict, knowledge has been generated that
28 ■ G. A. Giraldo Martineza ■ J. A. Flórez Zuluaga ■ D. F. Morante Granobles ■ J. F. Escobar Soto
Revista Facultad de Ciencias Económicas ■ Vol. 31(1)
could be capitalized by the national industry as
the analyzed countries have done in a nascent in-
dustry of added value in the sector, which would
allow reverting the investment in defense into a
dynamic of the national economy, which could be
consumed both by the national industry and by
the regional industry.
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