Dear Editor, Many thanks for giving us the opportunity to resubmit our paper ‘Power or Wealth: Revisiting China’s Defence-Growth Nexus, 1960- 2014’. We have considered the referee’s comments very carefully and made a range of changes. In addition, we have change the paper tittle to “China’s first priority in post-war state building: a wealthy state and a strong army?” to discuss the defense-growth nexus under wealth-power dichotomy as two basic state policies. In addition we have updated the data to 2016 (the latest available data). It is we believe a much better paper now. The following are what we have done point by point regarding referee’s comments and our responses to report back to you. We hope that all the changes make you and the reviewer(s) satisfied. Cheng King and Jane Du Authors’ Report on Changes Made in ‘Power or Wealth: Revisiting China’s Defence-Growth Nexus’ Responses to the Referee 1. The trade-off growth-security is interesting: although we receive frequent submissions about this, few of the articles approach the matter the way you did. And for China, another priority, of course. This is good. Some of the Editors however feel that your study does not contain policy relevance. As one referee put it the empirical validation is more an exercise in determining, and then commenting on statistical parameters, rather than discussing them as a way of guiding policy. The Board offers you to recast the paper, making sure that the hypothesis evaluation is policy guided. Be aware that this involves a rewriting of parts of the paper, with a policy focus to start, a policy-based testing, and a policy discussion of the results. This is a policy journal, not only one that reports on nice models, or on fancy testing. Our response: on the use of ADL models and length of testing. Many thanks to reviewer’s comment on the use of ADL models. We chose ADL methods 1
Transcript
Dear Editor,
Many thanks for giving us the opportunity to resubmit our paper ‘Power or Wealth: Revisiting China’s Defence-Growth Nexus, 1960-2014’.
We have considered the referee’s comments very carefully and made a range of changes. In addition, we have change the paper tittle to “China’s first priority in post-war state building: a wealthy state and a strong army?” to discuss the defense-growth nexus under wealth-power dichotomy as two basic state policies. In addition we have updated the data to 2016 (the latest available data). It is we believe a much better paper now.
The following are what we have done point by point regarding referee’s comments and our responses to report back to you.
We hope that all the changes make you and the reviewer(s) satisfied.
Cheng King and Jane Du
Authors’ Report on Changes Made in ‘Power or Wealth: Revisiting China’s Defence-Growth Nexus’
Responses to the Referee
1. The trade-off growth-security is interesting: although we receive frequent submissions about this, few of the articles approach the matter the way you did. And for China, another priority, of course. This is good. Some of the Editors however feel that your study does not contain policy relevance. As one referee put it the empirical validation is more an exercise in determining, and then commenting on statistical parameters, rather than discussing them as a way of guiding policy. The Board offers you to recast the paper, making sure that the hypothesis evaluation is policy guided. Be aware that this involves a rewriting of parts of the paper, with a policy focus to start, a policy-based testing, and a policy discussion of the results. This is a policy journal, not only one that reports on nice models, or on fancy testing.
Our response: on the use of ADL models and length of testing. Many thanks to reviewer’s comment on the use of ADL models. We chose ADL methods because this method does not require all variables to be integrated of the same order and can be used in small sample sizes. These advantages make up for the limitation of China’s macro data and the relatively short observation period since 1960. In addition, we also put nonlinear relationship into consideration to improve the loss of power in the linear test. It supplies a direct answer to the question that which factor is more important in China’s post-war state building.
Due to use of two models, modelling and empirical testing were relatively long. We agree with reviewer’s suggestion and have cut section III short. Now this section has only four pages and a half. We moved some important empirical process into footnotes in order to make the main content consistent and policy-focused. Please see changes on pages 11, 12 and 13.
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Our response: on policy focus.To make the article policy-focused, in the section I the introduction, we
have cut some irrelevant content to make it precise to capture the argument of this paper. In Section II “historical background” we added two paragraphs on Deng’s policies, emphasizing on the international environment that Deng faced when he switched China’s basic state policy from defense- to growth-prioritized approach to rebuild the state. By doing this, we are going to show the situational conditions under which China made its basic state policies.
In the begging of section III we moved original figure 2 (now figure 4 on page 11) to this section as a part of data description. Figure 4 shows the threshold in defence and growth data used in empirical testing. This gives the paper a better flow as it is the main reason that we employed threshold ADL in addition to linear ADL model in this analysis. See changes on page 11.
In Section IV, empirical results have been revised following reviwers’ comment of a policy focused interpretation. We integrated defence growth nexus into the discussion of “power-wealth” dichotomy that China faced in its post-war state building. Within this framework, defence and growth are viewed as two basic state policies which the Chinese government chose according to its understanding of China’s economic level in regional order. Following the power-wealth framework, we added several paragraphs on China’s military plan in Cold-War tensions, and how the Sino-Soviet split influenced China’s military department in pre-reform era. Changes are made on page 21. We also discussed China’s re-integration in to Japan-led Asian industrialization after 1979, and the impact of such economic policies on revising military strategies. Please refer to the highlighted paragraphs on pages 21, 22 and 23.
A new section 5.2 on robustness checks are added to this paper. Considering that the statistical caliber of China’s economic ranking in Asia includes the Middle East which China has been loosely connected with in terms of economic cooperation, we replaced China’s per capita GDP as percentage of Asian average to that of Far East’s average to check China’s military response under its closely-connected Far East region. In addition, we also use China’s per capita GDP as World’s average to see if the results are any different. We employed two robustness checks to shows that Chinese government’s demand on military capacity has been consistently influenced by policy-maker’s understanding of the country’s economic status in surrounding regions. Its economic policies actually show a great impact on the country’s security plan. In addition, the robustness results also show that China’s military response are mostly sensitive to its status in the Far East, implying that until nowadays the country remains as a regional power.
But since the early 2010s, China’s globalization propaganda has accelerated the country’s involvement in international system, requiring a change in security plan accordingly. When China steps out of Asia and it Far East subregion, the country’s future security plan is largely expected from its re-calibration in the existing global order. Changes are made on pages 24 and 25.
With all changes above, we hope this paper has been more policy-oriented. Many thanks to reviewer’s comment on the focus of this paper.
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2. Make sure that the final length of the paper is max 30 pages, all inclusive (some of the large, yet detailed tables needs to be deleted). Be aware that this suggestion to revise the paper in no way implies that the submission will be eventually accepted: referees will judge the new submission),
Our response: length of the paper.Thanks for reviewer’s comments on this point. We have cut several pages from the modelling part and shortened the empirical results. Now the revised version is 30 pages, including all footnotes and bibliography.
3. Under these conditions, we would consider again your paper, in an expeditious way. As we have published in JPM a number of papers on related subjects, please cite them in your biblio: referees like to see their work recognized. Please resubmit your paper by uploading it into our JPM system as a word.doc. It would expedite matters is you send me privately a copy of the revised paper as an email attachment as a word.doc.
Our response: on bibliographyThank you for comments on reference and citation. Most papers on defence-growth nexus in JPM are not China-based, thus we used them as references to interpret general relations between defense and growth all over the world. For our purpose, we selected following nine articles. They have been inserted in sections I and II as general references. For details, please see change on pages 2, 3 and 8.
Abu-Bader, S. and Abu-Qarn, A. S. (2003). “Government Expenditure, Military Spending and Economic Growth: Causality Evidence from Egypt, Israel, and Syria”, Journal of Policy Modeling Vol. 25, pp.567–583.
Bayouni, T., Hewitt, D. and Symansky, S. (1998). “The Impact of Worldwide Military Spending Cuts on Developing Countries”, Journal of Policy Modeling Vol. 20, pp. 261–303.
Dakurah, A. H., Davies, S. P. and Sampath, R. K. (2001). “Defense Spending and Economic Growth in Developing Countries: A Causality Analysis”, Journal of Policy Modeling Vol. 23, pp.651–658.
Dritsakis, N. (2004). “Defense Spending and Economic Growth: An Empirical Investigation of Greece and Turkey”, Journal of Policy Modeling Vol. 26, pp.249–264.
Kollias, C., Manolas, G. and Paleologou, S. (2004). “Defence Expenditure and Economic Growth in the European Union: A Causality Analysis”, Journal of Policy Modeling Vol. 26, pp. 553–569.
Lipow, J. and Antinori, C. M. (1995). “External Security Threats, Defense 3
Expenditures, and the Economic Growth of Less-Developed Countries”, Journal of Policy Modeling Vol. 17(6), pp. 579–595.
Looney, R. E. (1997). “Excessive Defense Expenditures and Economic Stabilization: The Case of Pakistan”, Journal of Policy Modeling Vol. 19, pp. 381–406.
Manamperi, N. (2016). “Does Military Expenditure Hinder Economic Growth?: Evidence from Greece and Turkey”, Journal of Policy Modeling Vol. 38, pp. 1171–1193.
Yang, H., Hong, C., Jung, S. and Lee, J. (2015). “Arms or Butter: The Economic Effect of An Increase in Military Expenditure”, Journal of Policy Modeling Vol. 37, pp.596–615.
Finally, we have updated data used in testing to 2016. We thank reviewer and editor’s insightful comments and effort made in improving this paper.
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China’s First Priority in Post-War State Building:
China’s First Priority in Post-War State Building:
A Wealthy State, Or a Strong Army?
Abstract
This analysis examined causal links in China’s defence-growth nexus in 1960–2016. The
results show that better growth significantly reduces military-civilian ratio and propels
military reforms. The unidirectional threshold causality from growth to defence shows that
the military impact on a positive change in China’s growth is little in the long term.
Conversely, the growth impact of a positive change in defence has accelerated after it
reaches the threshold year in 1987. This finding explains why Chinese economy stagnated
when defence was prioritised and why China has risen dramatically in the Far East after
three decades of fast economic growth.
Keywords: Defence spending; economic growth; threshold ADL cointegration; China’s military
reform.
JEL Classification: F52; C22; N45; H30.
1. Introduction
This paper aims to empirically identify China’s first priority in its post-World War II
(henceforth post-war) state-building by causally assessing the defence-growth nexus which
is not constant over time for the China’s case. After being historically emphasised for
centuries, military defence was given less priority in the period requiring economic opening
up for China’s wealth accumulation. More recently, the Chinese government proposed
military reforms that necessitate an increase in military budget. Periods of high military
spending have sparked discussions in the literature on the possible causality between
defence and growth. Policy variation between defence and growth is however not a new
phenomenon: China’s pendulum swing between wealth and power for Chinese state
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building has been subject to external conditions since the late 19th century.
A strong army protects economic prosperity but by itself consumes national wealth
(Chang et al., 2001; Abu-Bader and Abu-Qarn, 2003; Manamperi, 2016). Analysing the
nexus of defence and growth – the causality between them and the consequential outcomes
of each – is important for an understanding of China’s quest for post-war state building.
This paper weighs the significance of both based on the traditional belief that “(a good state
should always be) a wealthy state, (with) a strong army” (fuguo qiangbing) (Shang, 4th
Century BC; Wei, 1842).
There are two general strands of thought pertaining to why defence-growth nexus
changes over time. First, a strong military defence safeguards the country’s boundary and
protects citizen’s production activities (Masih et al., 1997). It thus provides a stable
environment for the domestic economy to spur. In the 1950s, for example, military power
stabilised most domestic volatilities for post-war recovery. The second thought states that
economic growth enhances the country’s fiscal capacity to finance government expenditure
on creating a stronger defence (Dritsakis, 2004; Kollias et al., 2004; Chang et al., 2001).
Studies diverge at the point of economic returns to military expenditure: for the same
change in defence or growth, different studies show that the reaction (defence if growth is
changed and vice versa) varies. Such variation in fact represents different external
conditions that the state encountered. Reaction of military power is stronger when the
requirement of peace and stability is urgent; however, the sensitivity of safety to the
country may be reduced if military demand reacts less. Growth response is thus magnified
as there is less demand for military strengthening. As such, the changes in the speed and
level that the economy responds to the changes in military have made the cause and
consequence of the defence-growth nexus inconclusive in the long term ( Dakurah, et al.,
2001; Yang, et al., 2015).
It has been shown that the strengthening or weakening of each is reciprocal over time.
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For example, Masih et al. (1997), and Wolde-Rufael (2001) and Lai et al. (2005) have
demonstrated that a change in defence expenditure to build military power caused a
corresponding change in growth over the 1950s to 1990s. Since then, similar changes in
military spending had little effect on the Chinese economy; the causality alters when
observation has been extended to the 2010s (Chang et al., 2014; Dimitraki and Ali, 2015).
Seemingly, other factors are at play in this cause-and-effect of defence and growth, shaped
possibly by the period chosen for observation. In other words, different observation periods
provide different domestic and international environments for analysis. In some extreme
cases foreign powers completely dominated China’s external environment and exercised
tight control of China’s domestic affairs. The environment is likely the situational
conditions that move the country towards wealth (Lipow and Antinori, 1995), or the power.
For example, it has been stressed that without strong military power, it was impossible for
China to become rich as the terms of trade had been altered since the Opium War (Deng,
1999).
In this sense, the defence-growth dichotomy is largely shaped by China’s long search
for a way to build its state. When it is unable to simultaneously achieve both, “which
should have priority, the wealthy state or the strong army” remains a question for China.
This article will show that China’s economic ranking in Asia indeed significantly alters
the sensitivity of the country’s military demand. The turning point for China to walk out of
the defence-growth dichotomy was Deng Xiaoping’s low profile approach to accomplishing
China’s “peaceful rise”.
Methodologically, the investigation requires a time series dataset of China’s share of
(1) defence spending in (2) gross domestic product (GDP) and ratio of (3) China’s per
capita GDP relative to (4) Asian average. We use the share of military spending in GDP to
estimate military-civilian relation, which reveals China’s military capacity to protect the
population and their wealth; we also calculate the ratio of China’s per capita GDP relative
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to Asian average to gauge the country’s evolving economic status in regional order. Due to
data limitation,1 this article restricts its observation period to run from 1960 to 2016 to
reflect China’s progression from post-war recovery to an upper-middle-income economy.
Considering China’s long search for building its post-war state implying a regime
switch in policy-making between defence and growth, both linear and threshold auto-
regressive distributed lag (ADL) models are relied upon. The ADL method has econometric
advantages of avoiding a pre-testing of the underlying time series: it does not require all
variables must be integrated of the same order, and it allows small sample sizes. These
make up for the limitation of China’s macroeconomic data and the relatively short
observation period due to data unavailability. We use two ADL approaches because the
linear model may econometrically overlook the regime-switching effect in, which can be
empirically significant for identifying China’s long search for a balance in the defence-
growth dichotomy. The investigation first analyses China’s defence-growth nexus in a
linear framework with ADL bounds test (Pesaran et al, 2001) and its error correction model
(ECM) to detect the presence of linear causal links. The data are subsequently fitted to a
nonlinear framework using threshold ADL (Li and Lee, 2010) and corresponding ECMs.
The linear result shows no causal links between defence and growth in China, which is
similar to Chen’s finding (1993). The nonlinear result however clearly shows a
unidirectional causality from growth to defence. Conditional on being nonlinear, military
defence has an immediate but very tiny positive impact on China’s economic ranking. In
contrast, economic ranking in the short term has reduced the country’s military capacity,
while the economic impact of a positive change in military capacity increasingly
accelerates in the long term.
These empirical findings contribute to the existing literature on the nexus of defence
and growth in several realms. First, the findings prove that China’s defence-growth nexus is
not a simple linear relation; rather the two components reciprocally interacted in China
1 For example, the per capita GDP data in World Bank databases start from the year 1960.
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during 1960–2016. Second, the results have identified early to the year 1987 as a turning
point in the nexus in question when economic growth was prioritised over military
strengthening. As such, the results further indicate that defence-prioritised approach will
never make China a prosperous state. In China’s case, economic growth far outweighs
military defence in the country’s wealth-power dichotomy if they could not be attained
simultaneously.
The rest of the article is organised as follows: Section 2 introduces the historical
background against which defence-growth dichotomy matters for China. Section 3 and 4
explains the linear and threshold ADL models and their empirical results. Section 5
presents the transmission mechanism between defence and growth, robust checks and
policy implications. Section 6 concludes.
2. Historical background
The traditional belief in the defence-growth relation in China can be described as based on
the philosophy that war was of vital importance to the state (Guisso et al. 1989). The prosperity of
China in history highly correlated to the integrity of the country’s western and northern
borderlines. If China could conduct successful campaigns on its Central Asian frontier and defend
itself against northern nomadic monarchs, it would experience a period of prosperity at the same
time.
The long practice of such “military success-economic prosperity” mix made China adopt
passive approaches to its trade and foreign policies which did little to check the penetration of
western powers in the Age of Discovery. In the game of pre-modern competition with the western
power, China’s fate was destined to the beginning – the country simply had no means to fight
against Western and Asian modern powers. Since then, it is not surprising that China had aroused
rounds of reforms to rebuild the state with new wealth and power.
While relatively fair trade conditions prevailed when the West first embarked on modern
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growth, China had to accept lopsided terms of trade in favour of the West when it was forced to
open its economy by the end of the pre-industrial era, putting China in a “selling cheaper and
buying dearly” trap (Deng, 1999). In the following regimes, neither the Manchurian government
nor the Republican one could enjoy bona fide financial or military control of the whole of China.
All these changes downgraded China from its usual leading power in the Far East. Maoist China
thus reverted to strengthening its national defence in a closed economy and pinned hope on the
Soviet’s centrally planned methods of fast industrialisation. A large military sector became Mao’s
way of safeguarding peace and re-building the Chinese state. However, Soviet-styled harsh
dictatorship and seclusion did not bring China to the track of fast industrialisation.2 The re-
building of Chinese state after the mismanagement of the centrally-planned system necessitated
seeking a new trial for wealth and power.
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Fig. 1. Evolution of national defence spending.
(Source: Finance Yearbook of China, 1991–2017 Editions)
With Deng Xiaoping’s reforms in the early 1980s, China proactively re-opened itself to the
world. However, a large military presence developed during Mao’s regime consumed a significant
portion of national wealth (Figure 1). This wealth-power dichotomy resulted in a “switch” in the
2 The compounded annual growth rate of per capita GDP (constant at 2005 yuan) in China was a mere 3.33% over the 1952–1976 period.
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approach adopted for China’s post-war state building. It was up to the post-Mao reformist state to
gauge the cost of shelving plans for military strengthening in pursuit of a growth-prioritised way.
In contrast to wartime conditions, the low-profile military approach became preferable for China.
Thus Deng Xiaoping in 1981 proposed a large disarmament,3 which symbolised a switch in
China’s military-civilian relation (Figure 2) and a turning point in its long search for wealth and
power. Deng’s economic re-opening and low-profile diplomatic approach had relieved the
military tensions that China would have encountered with the Soviet Union and the United States,
hence reduced the country’s dependency on a large military presence. Such a switch from a
defence- to a growth-prioritised approach helped China concentrate on wealth accumulation and
integrated the country to the post-war world system at both senses of international relation and
domestic politics. The enhanced national wealth and technology level after three decades of
growth kicked start military modernisation. When the domestic politics in late 1990s turned in
favour of nationalism, the enhanced economic capacity financially backs China’s military
expansion. Deng’s growth-prioritised approach has strengthened the country’s position in the
international order, labelled “China’s peaceful rise”.
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Fig. 2. Changes in total armed forces and military-to-civilian ratio, China 1960–2016.
(Source: The Military Balance and China Statistical Yearbook)
3 In seven years, 2.45 million personnel were cut from the People’s Liberation Army (PLA). The 1981 disarmament halved China’s military-to-civilian ratio from 47 to 21 personnel per 10,000 population.
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Before Deng’s reforms, China was long trapped in wartime or quasi-wartime (e.g. Cold War)
conditions. Such wartime condition not only pushed up China’s defence spending, but also
misallocated large amount of manpower and crucial economic resources to the country’s defence
industries in Chinese interior (known as the Third Front). At one time, this Third Front consumed
about two-thirds of total investment on industry in China (Naughton, 1988). It was widely
believed that economic progress must be based on frontier security, relying on national defence. It
is true that defence was essential to externally safeguard state sovereignty and internally to
provide a stable environment within which the economy could prosper. However, a large military
sector does not equate to a strong international status. Rather, as shown in Figure 3, in the 1960–
1979 period, China’s economic ranking in Asia gradually slid to the bottom. This implies that
China’s position in the regional order was in jeopardy.
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Fig. 3. China’s changing wealth ranking in Asia.
Notes: Economic ranking: The ratio of China’s per capita GDP (current US$, 1960=100) relative to Asian average per
capita GDP level (excluding China, current US$, 1960=100). This figure presents the changing pattern of China’s
economic ranking in Asia which simulates statesmen’s perception of China’s position regionally.
(Source: World Development Indicators, 2017)
Unlike historical predecessors, the post-war fast growing economies can create positive
transboundary economic externalities that help strengthen a country’s security and hence reduce
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its need to safeguard the state through enhancing secluded military defence (Byoumi, et al.,
1998).4 In this sense, the need for military capacity is subject to the level of externalities that
economic growth can provide.5 However, when considering basic security requirements, a strong
national defence could be an extra help for building a wealthy China. Regressing China’s military
defence and economic ranking in Asia will help in the understanding of how China identifies a
balance between wealth and power and provides more empirical evidences to the analysis of
China’s defence-growth nexus.
3. Methodology and modelling
3.1. Basic setup and data description
As the relationship between defence and growth is an unknown a priori for the China
case, the analysis began by specifying two links at the core of the defence-growth nexus:
equation (1) presents the defence-to-growth link which depicts strong military defence
safeguarding production and supporting fast economic growth; and equation (2) illustrates the
growth-to-defence link as economic growth enabling the state to increase military expenditure to
have a strong national defence:
Gt=φ10+φ11 M t+ε1 t (1)
M t=φ20+φ21 Gt+ε 2t . (2)
The factors on the agenda are China’s military capabilities M t, estimated by military
spending as a percentage of GDP; and China’s evolving economic ranking in surrounding regions
Gt, estimated by China’s per capita GDP as a percentage of Asian average.6 Official databases,
such as the National Bureau of Statistics of China and the World Bank, are considered as good 4 For example, international trade, investment and regional cooperation can generate environmental externalities for both domestic and trade partner’s economic growth.5 See, Leeds, et al., 2006. 6 The percentage share of China’s per capita GDP in Asian average was used to indicate China’s economic status in the surrounding areas. Here average per capita GDP of Asia has excluded the part of China.
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sources of information to discern China’s concerns on defence and growth in real time. All data in
this paper are collected from China’s Statistical Yearbook, Finance Yearbook of China and
the World Development Indicators of the World Bank. In addition, the observation period is
restricted from 1960 to 2016 to cover the process of China’s post-war search for wealth and
power. Table 1 reports basic descriptive statistics of the main variables and their unit root
test results. For this analysis, the form which allows for a change in intercept in the
Military spending (% of GDP) (M t) 57 2.8561 1.8669 1.0173 6.8977Panel (b) Unit root tests
ADF test PP testI(0) I(1) I(0) I(1)[1] [2] [3] [4]
(i) –0.6848 –6.1412*** –0.8118 –6.1035***
M t (ii) –1.8085 –6.0841*** –0.8118 –6.0456***
(iii) –1.1119 –6.1176*** –1.0892 –6.1217***
(i) 3.3349 –1.5973 7.5621 –2.5943Gt (ii) 1.8041 –4.5443*** 1.6020 –4.6935***
(iii) 4.2873 –0.5704 10.2230 –1.2068Notes: Panel (a) of this table reports summary statistics for key variables used in the empirical study. Per capita GDP (% of Asian average) refers to China’s yearly per capita GDP as percentage of Asian average. Military spending (% of GDP) refers to Chinese government’s final expenditure on national defence as a percentage of GDP. Both are used as a percentage share in the testing procedure. Panel (b) provides the unit root test results of China’s military power and economic ranking in Asia. All three versions with (i) constant (columns 1 and 4), (ii) with constant and trend (columns 2 and 5) and (iii) with no constant or tend (columns 3 and 6) are included in the model specifications; the optimal lag lengths are chosen based on Schwartz Criterion (SC). * Indicates significance at the 10% level. ** Indicates significance at the 5% level.*** Indicates significance at the 1% level.(Source: China Statistical Yearbook, Finance Yearbook of China and World Development Indicators, 2017)
As highlighted in Figure 4, China’s defence-growth relation shows an asymmetric
adjustment in first difference during the period in question. To empirically ascertain
China’s optimal choice between wealth and power, a framework that allows for linear and 7 In order to formally validate preliminary evidence, the augmented Dickey-Fuller (Dickey and Fuller, 1981) (ADF) and Phillips-Perron (Phillips and Perron, 1988) (PP) models are applied to test the unit root hypothesis. Additional use of PP test is to ensure the robustness of serial correlation.
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nonlinear effects of one depending on changes of the other and a test on the causality types
of linear and nonlinear relations are needed. For this, the ADL method is selected for this
research. First, it enables us to identify both linear (Pesaran et al., 2001) and nonlinear (Li
and Lee, 2010) relations within the same econometric framework, a necessity as the
nonlinear relation that is possibly implied in China’s defence-growth nexus is an unknown
a priori in this case. Identifying relations with different linear and nonlinear frameworks
methodologically assume that results are comparable and would not be suitable. Second,
ADL framework does away with the necessity to integrate all data in the same order and is
well suited for small sample sizes.
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Fig. 4. Threshold in co-movement between defence and growth, China 1961–2016.
Notes: National defence spending: national defence expenditure as percentage of GDP; per capita GDP: per
capita GDP as percentage of Asian average in 2010 constant price.
(Source: China Statistical Yearbook; World Development Indicators, 2017.
3.2. ADL model
Following Pesaran et al (2001), we formally expand both links in equations (1) and (2)
to the linear ADL bounds model in the following forms: 8
8 We use the same lag lengths 19
61196
319
65196
719
6919
71197
319
7519
77197
919
81198
319
8519
87198
919
91199
319
9519
97199
920
01200
320
0520
07200
920
11201
320
15
-3 5
-2 5
-1 5
-5
5
15
25
35
Nat io na l Defe nc e Spe ndin g ( as % of GD P, China)Per Cap ita G DP ( China as % o f Asian Ave ra ge)
Year
-On-
Yea
r Cha
nge
Rat
e (%
)
for the ADL model in this study. The ADL method involves lag order selection. We use the Schwarz criterion (SC) to select the optimal lag length.
11
∆ Gt=c+α 11 Gt−1+α 12 M t−1+∑i=1
p
γ1 i ∆ Gt−i+∑i=0
q
δ1 i ∆ M t−i+e1 t (3)
∆ M t=c+α 21 M t−1+α 22Gt−1+∑i=1
p
γ2 i ∆ M t−i+∑i=0
q
δ 2 i ∆Gt−i+e2t.(4)
Here, α k 1 and α k 2 indicate the long-run coefficients; γki and δ ki are the short-run coefficients
and ekt is the residuals. The ADL bounds test uses F-test to detect long-run relations in equations
(3) and (4).9 If the estimated F-statistic surpasses the upper bound critical value provided by
Pesaran et al. (2001), cointegration is established. Next, we move to obtain the dynamic
parameters by estimating the underlying ECMs for the ADL bounds tests as follows:
∆ Gt=c+∑i=1
p
γ1 i ∆ W t−i +∑i=0
q
δ 1 i ∆ M t−i+ λ1 E t−1G +e1 t
(5)
∆ M t=c+∑i=1
p
γ2 i ∆ Mt−i+∑i=0
q
δ 2i ∆ Gt−i+ λ2 E t−1M +e2 t.
(6)
In equations (4) and (5), Et−1k is lagged error correction term obtained from equations (1)
and (2). Parameters δ ki represent short-run coefficients; λk indicates the adjustment speed to
equilibrium. Further, a Wald test for Granger causality to examine the presence and power
of causalities based on equations (5) and (6).10
3.3. Threshold ADL model
Due to a clear regime-switch effect between economic ranking and military capability
as shown in Figure 4, a test on whether the nexus in question is indeed nonlinear using
threshold ADL model (Li and Lee, 2010) of the following form was conducted:
∆ Gt=c+( α11 Gt−1+α 12 M t−1 ) I 1tG+ (α 13Gt−1+α 14 M t−1 ) I 2 t
G
9 The null hypothesis of no cointegration is tested as H 0 :α i1=αi 2=0. 10 Null hypotheses for Wald test was employed: (i) short-run causality δ i=0; (ii) long-run causality λ i=0; and (iii) the strong Granger causality tests δ i=λ i=0, respectively.
12
+∑i=1
p
γ1 i ∆ Gt−1+∑i=0
q
δ 1 i ∆ M t−i+e1 t (7)
∆ M t=c+(α 21 M t−1+α 22Gt−1) I 1 tM+( α23 M t−1+α24 Gt−1 ) I 1t
M
+∑i=1
p
γ2 i ∆ M t−1+∑i=0
q
δ 2 i∆ Gt−i+e2 t.(8)
Threshold ADL model depicts two indicators represented by I ¿k in equations (7) and (8):
I ¿k can either be I 1t
k =I ¿ for Indicator A; or I 2tk =I ¿ for Indicator B.11 Considering the power
for threshold ADL, the BO test (Boswijk, 1994) is used for the selection of the regime
indicator and to see which is more important in China’s post-war state building: defence or
growth.12
After establishing the nonlinear cointegration, the ECM for threshold ADL with the
following amended specification will be estimated:
∆ Gt=c+∑i=1
n
γ1 i ∆ Gt−i+∑i=1
n
δ 1 i ∆ M t−i+ λ11 Et−1G+¿+ λ12 E¿
G −¿+e ¿¿ (9)
∆ M t=c+∑i=1
n
γ2 i ∆ Mt−i+∑i=1
n
δ 2i ∆ Gt−i+ λ21 Et−1M+¿+ λ22 E¿
M −¿+e ¿¿.(10)
In the event that threshold cointegration is established under Indicator A, the lagged error
correction terms in equations (5) and (6) are set to be Et−1+¿=I1 t εt−1¿ and Et−1
−¿=I 2t ε t−1¿, given I=1 if
ε t−1<εt−1¿ ( τ ) otherwise I=0. In case cointegration is found under Indicator B, error
correction term will set based on ∆ εt−1<∆ εt−1¿ (τ ).13 Like the linear ECMs, Wald tests will be
applied to detect threshold causalities.14 11 For both indicators A and B we have I 1t
k =1−I 2 tk . The ε t
k are the residuals obtained from equations (1)
and (2). Threshold values are indicated by ε t−1k∗¿ ( τ )¿. As to the selection of the threshold indicators, the Akaike
information criterion (AIC) is followed. 12 Li and Lee (2010) proposed two tests for threshold cointegration: the BO test (Boswijk, 1994) and the BDM test (Banerjee et al., 1998). In terms of size and power, the BO test surpasses the BDM test, a reason why the BO test results were mainly adopted to conclude the presence of threshold ADL cointegration. 13 In case of Indicator B, ECT t−1
+¿=I1t εt−1¿ and ECT t−1−¿=I2 t εt−1¿, given I=1 if ∆ εt−1<∆ εt−1
¿ (τ ), otherwise I=0. ε t−1 is the lagged residual term obtained from long-run regression equations (1) and (2). 14 The threshold Granger causality can also be examined by Wald test in three ways: ( i) short-run causality
13
For both linear and nonlinear causality tests, if the Wald test results show bidirectional
causalities, the nexus in question inclines to be a reciprocal causation, implying that
defence and growth could be achieved simultaneously. However, if a unidirectional
causality is found, the conjecture of a mutually enforced co-movement between defence
and growth does not hold for China. The direction of causality is indicative of what China
should prioritise in its national policy: a wealthy state, or a strong army.
4. Causal analysis between wealth and power
4.1. Cointegration analysis
The cointegration test for ADL bounds model requires a comparison of the F-statistics
against the critical value provided in Pesaran et al. (2001).15 Using equations (3) and (4),
each link in the equation is estimated to be a dependent variable in the ADL bounds test.
The calculations of F- and Wald-statistics are reported in panel (a) of Table 2. With growth
as dependent variable, the FG=6.0482 (column 2 in Table 2a) is above the upper bound
critical value of 6.68 at 97.5% confidence. Nevertheless, when military power is the
dependent variable, F-statistic FM=1.5088 (column 4 in Table 2a) falls below the lower
bound critical value of 4.04 at 90% confidence. Accordingly, there exists a stable long-run
relation between China’s economic ranking and military power, but only when growth is
the dependent variable. In other words, linear cointegration could be established for the
defence-to-growth link (equation 3), but not for the vice versa situation.
However, as aforementioned the ignorance of nonlinear effect can affect the power of
the cointegration test. As such, threshold ADL model is tested for equations (7) and (8)
using the same data. The results are reported in panel (b) of Table 2. Columns (5) and (6)
by testing H 0 :δ ki=0; (ii) long-run causality by testing H 0 : λi 1=λ i 2=0; and (iii) strong causality by testing H 0 :δ ki=λ i 1=0 and H 0 :δ ki=λ i 2=0 (Yau and Nieh, 2009). 15 Given that the sample size is relatively small with 57 observations, a maximum lag lengths of eight (p=q=1,2, …,5) is allowed. Following the rule of SC, one lag length is selected.
14
present the results with economic ranking and military defence as dependent variable
respectively. Following AIC criteria, Indicator B is chosen for equation (7), and Indicator A
for equation (8). At 95% level, BO statistics have shown the presence of threshold
cointegration for both links in the nexus.16
These results confirm the consideration of nonlinearity between defence and growth in
China. Under linear hypothesis, cointegration is only present in the defence-to-growth link;
it suggests that military protection of economic growth has an immediate effect in China.
However, with regime-switching effect, the two variables interact with each other and
threshold cointegration was established for both links in China’s defence-growth nexus.
16 At 95% level, the result of BO statistic (BO=18.8432) surpasses 18.66 critical value, indicating the presence of threshold cointegration for the defence-to-growth link (column 5 in Table 3b). The result of BO statistic (BO=22.2354) surpasses the critical value of 19.04 at 95% confidence for the assumption of military defence as dependent variable (column 6 in Table 3b). Threshold cointegration of the growth-to-defence link is also established.
15
Table 2
Cointegration test results.
Panel (a) ADL bounds test for cointegration Panel (b) ADL test for threshold cointegration
D(G) D(M)D(G) D(M)Indicator B Indicator A
[1] [2] [3] [4] [5] [6]G(–1) 0.0232**
6.0482 **
M(–1) –0.0446
1.5088
(G(–1)) IG 0.0288*** (M(–1)) IM 0.0387(0.0089) (0.0406) (0.0090) (0.0468)
AIC 2.9070 1.0881 AIC 221.7957 110.1466Serial correlation a 0.4960 [0.6121] 1.0272 [0.3659] Serial correlation a 0.1907 [0.8271] 0.2212 [0.8025]Heteroscedasticity b 1.5551 [0.1904] 6.3704 [0.0001] Heteroscedasticity b 0.6072 [0.7470] 4.3970 [0.0009]Normality c 20.6530 [0.0000] 11.6121 [0.0030] Normality c 17.8160 [0.0001] 13.4987 [0.0012]Stability d Stable Stable Stability d Stable Not stable
Notes: a Breusch–Godfrey serial correlation LM test; b Harvey heteroscedasticity test; c Jacque-Bera normality test; d Cumulative sum of recursive residuals (CUSUM) test; Standard errors are reported in parentheses, while p-ratio in are reported in square brackets. The ADL bounds test critical values were obtained from Pesaran et al. (2001); critical values for ADL test for threshold cointegration were collected from Li and Lee (2010). * Indicates significance at the 10% level. ** Indicates significance at the 5% level. *** Indicates significance at the 1% level.
16
4.2. Causality analysis
Accordingly, the ECMs are estimated for causalities. Results are summarised in Table
3. In panel (a) , the positive coefficient of the lagged error correction term Et−1G (column 1)
for equation (5) shows that the response of growth to shocks in defence is ineffective. This
means that China’s post-war economic growth is indeed insensitive to changes in the
country’s military conditions. The estimation of the underlying ECM with Wald tests
confirm the non-causalities: (i) the result of the Wald test for the current and the lagged
terms of the first difference of defence indicates no short-run causation (column 1); ( ii) the
t-statistic pertaining to the error correction term Et −1G confirms non-causality in the long
run; and (iii) the joint Wald test of independent variables and error correction term again
suggests no strong causation from China’s defence to growth in the linear framework.
In panel (b), the situation of nonlinearity based on equations (9) and (10) is considered. The
results of growth-to-defence link show a significant negative coefficient of the threshold error
correction term Et−1M−¿¿. The adjustment speed of defence was strong (99% confidence level),
taking a value of –0.2525 (column 3 of Table 3b). This implies that China’s military defence can
effectively respond to a change in its economic ranking in surrounding areas. It adjusted back to
equilibrium at 25.25% speed. In contrast to military defence, the responding mechanism of
growth under threshold system was insignificant (column 2). Unlike the ECM for linear ADL
bounds model, results of ECM for threshold ADL show a unidirectional causality from China’s
economic ranking to military defence.
17
Table 3
The ECMs and Granger causality tests.
Panel (a) ECM for ADL bounds test Panel (b) ECM for threshold cointegration D(G) D(G) D(M)
Notes: a Breusch–Godfrey serial correlation LM test; b Harvey heteroscedasticity test; c Jacque-Bera normality test; d Cumulative sum of recursive residuals (CUSUM) test; Standard errors are reported in parentheses, while p-ratio in are reported in square brackets. * Indicates significance at the 10% level. ** Indicates significance at the 5% level. *** Indicates significance at the 1% level.
18
Based on the estimation of ECMs, three Wald testing are involved to show the nature of
causality for the growth-to-defence link (column 3 in Table 3b): ( i) the results of the
relation in the lagged terms of the first difference of independent variables indicate no
short-run causation; (ii) the F-statistics obtained from joint-coefficient Wald test on the
lagged error correction terms Et−1+¿ ¿ and Et−1
−¿¿ suggest a long-run causality; and ( iii) the joint
tests of independent variables and error correction terms confirm that strong causalities
exist in the growth-to-defence link. However, no threshold causality is found for the
defence-to-growth link (column 2).
The ECM results show that China’s regional economic ranking has strong impacts on
the country’s military defence in the long run. This causal relation is unidirectional and
only validates with structural breaks. The difference between linear and nonlinear results
arises from the enhanced power of threshold ADL model.
5. Discussion and policy implications
5.1. Transmission mechanism between wealth and power
In threshold ADL analysis China’s defence-growth dichotomy has been split into two
sub-links corresponding to defence- and growth-prioritised approaches of developing the
state. The estimated threshold causality results prove that defence and growth could not be
achieved simultaneously in the Chinese case. Conditional upon two links, impulse response
functions are estimated to throw light on the transmission mechanism in between: one for
the defence-to-growth link and one for the growth-to-defence link.
Figure 5 shows the estimated effects of the dependent variable in the vector
autoregressive regression (VAR) model to shocks from the independent variable. In order to
understand the long term sequential effects, the observation period is normalised to the
maximum length. The impulse responses are accumulated using Monte Carlo standard error
19
method. The real line in the left panel of Figure 5 represents the response of growth to
shocks from defence and the right panel shows the reversed link.
-20
-10
0
10
20Response of GRW to DEF
-0.5
-0.3
0.0
0.3
0.5Response of DEF to GRW
Fig. 5. Impulse response of defence-growth VAR.
Note: Monte Carlo standard error response is chosen for estimation.
The results in Figure 5 show that economic ranking is more sensitive to shocks in
national defence in the long run. In the 57th observation year, response of growth to
defence is –18.74, but defence only responded 0.40 to a unit change in growth. By
reinforcing the growth impact of defence shocks, enhanced military defence quickly
reduces growth level. In contrast, the defence effect of growth change is permanently
positive. In reality, the results in Figure 5 show that China’s enhanced economic ranking in
Asia has helped to strengthen its military power in the long term; however, the military-
prioritised approach will largely weaken China’s long term economic status in Asia.
Specifically, first, a unit increase in military defence can immediately increase China’s
economic ranking by 4.95% in two years’ time, albeit for a brief period. From the fourth
year, defence has a monotonically negative impact on growth throughout the observation
period. Second, by contrast, the right panel of Figure 5 shows that an increase in growth
does not necessarily enhance military defence in subsequent years. However, if the
economic ranking keeps increasing, it may quickly enhance China’s military capacity; and
after the 26th year, growth’s impact on defence will become positive.
20
These estimated results are also economically relevant. The higher the military
demands, the more spending the government has to pay for maintaining a large military
sector. Although the enhancement of the Chinese army will strengthen domestic economic
stability via increased demands on military facilities, equipment and other related goods
within a short period, this effect is not sustainable as increasingly high fiscal budget can be
a strain on government finance. For example, China’s defence industrialisation investment
from 1963 to 1965 took 38.2% of overall national investment (Naughton, 1988). Based on
empirical estimates, a unit increase in the share of defence spending in GDP caused a
maximum 4.95% increase in economic benefits in the second year; however, in the 12th
year the same increase will trigger a 101.40% decline in China’s economic status. This
conforms with the finding in Figure 3, which shows a continuous decrease of China’s
economic ranking in Asia during the 1960–1979 period. The negative response of growth to
defence implies that the defence-prioritised approach of state building is infeasible in the
Chinese case.
This in reality was determined by the situation conditions that China faced in the
1960s. To integrate China itself to the Soviet-led trade system (Council for Mutual
Economic Assistance), the country was required a strong military presence in the post-war
socialist camp to stabilise its position under the Cold War tensions. However, the Soviet-
style harsh dictatorship did not bring China to the track of fast industrialisation. After the
demise of Stalin, Mao split China away from the Soviet-dominated communist country
network (known as Sino-Soviet split) and made China a secluded economy, isolating from
either socialist- or capitalist-led world cooperation systems until Deng’s reform. China’s
opening-up since 1979 re-integrated the country to the global supply chain through the
Japan-led Asian industrialisation. China’s post-war defence-growth relationships was
largely a consequence of the country’s different trials to re-build the Chinese state under
Asia’s post-war geopolitical environments.
21
This finding also confirms that in the long-run resources have to be diverted to
production for both the goals of fast growth and strong defence to be achieved in the end.
When defence spending becomes excessive in the beginning of reform as shown in Figure
1, the Chinese government had to find a way to reallocate effort and funds from the
military department. The disarmament in the early 1980s signals that China’s first priority
in state policy-making had fundamentally switched from arming “everyone a soldier”
(quanmin jiebing) to making “economic construction as the focal point” (yi jingji jianshe
wei zhongxin). Although the 1980s disarmament had weakened China’s immediate military
power, forcing it to take a lower posture in foreign affairs, this approach produces better
economic growth for the country to accelerate military modernisation in the long term. This
is especially so when the response of defence to growth turned positive in the 27th year of
observation in 1987 (right panel of Figure 5). China’s growth-prioritised low-profile
approach eventually helped the country walk out of the wealth-power dichotomy.
As to the response frequency, the distribution of indicators identified by the ADL
threshold cointegration tests for equation (6) was plotted to show the tipping points of the
impacts posed by the economic ranking on military defence. Figure 6 demonstrates this
mechanism under a regime-switch framework. Apparently, China’s economic ranking has
affected military defence more frequently before 1979. Each tipping point in Figure 6
corresponds to a historical event in growth and stability, which more or less affected
Chinese government’s attitude towards defence or growth in its state policy-making: the
1961–1963 great famine, the 1965–1966 initial Third Front defence construction, 1968
economic turmoil of the Cultural Revolution, the 1975–1979 rehabilitation of Deng Xiaoping
after the fall of Lin Biao and the ongoing market reforms since 1980. The nonlinear causal
link from growth to defence also shows the structural changes in the impact of China’s
domestic economy to the country’s military modernisation. The pattern was switched to a
growth-first track and has stayed since then.
22
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
0
2
4
6
8
Threshold in economic ranking Defense spending / GDP ratio (%)
Def
ence
Spe
ndin
g in
GD
P
Fig. 6. Estimated threshold and identified periods of military structural change in China.
Notes: This figure plots the defence spending as percentage of GDP for the period 1960–2016. Shaded area
demonstrates the tipping points of China’s economic ranking in Asia which is detected by threshold ADL
tests.
In theory, the Chinese government has to consider both wealth accumulation and
military power in state building. Of course the absence of economic security can be, to
some extent, compensated for by military power, like what happened after Mao’s Sino-
Soviet split. However, this was very likely a short-term effect. Long-time economic
stagnation will certainly affect the basic living condition of the population and lowers the
country’s position in the region. It hence threatens the legitimacy of the ruling party.
China’s increased economic ranking among surrounding countries helps the country to
strengthen its position in the international order and hence reduce the needs of a relatively
oversized military. The country’s economic status affects government’s defence spending
and determines the scale and structure of the army. China’s fast economic growth and status
enhancement improved the quality of military manpower and accelerated the process of
PLA modernisation after 1980.
5.2. Robustness checks
23
Two robustness checks are further conducted to robust the findings. Considering the
statistical calibre of China’s economic ranking in Asia includes the Middle East which China has
been loosely connected with in terms of economic cooperation, we replace it with the Far East
(East and Southeast Asian countries) data to check China’s military response under its closely-
connected Far East regional order. In addition, we also use China’s per capita GDP as World’s
average to see if the results are any different. The reasons for keeping the share of defence
spending in GDP as the proxy for China’s military capacity are twofold. First, the limited data
availability has restricted our use of national defence spending. Second, we keep using defence
spending as percentage of GDP because the absolute level of defence spending cannot reflect the
country’s military-civilian ratio in the real time, hence it is unable to reveal government’s attitude
towards defence or growth in policy-making. Thus only relative defence spending in GDP-based
tests provide us with unbiased finding in China’s post-war defence-growth nexus. Results are
reported in Table 4.
The main results are consistent with the one using Asian data. Linear cointegration could be
only established from defence to growth using the Far East data (column 1 of Table 4a); no
cointegration for the World data (Table 4c). With consideration of nonlinearity China’s defence
and growth mutually cointegrates with each other for both Far East and world (columns 4, 5, 10
and 11). Based on cointegration results, the robustness causality tests are performed. Column 3 of
Table 4 shows the non-causality for the linear relationship using the Far East data. However, we
still find threshold causalities from growth to defence for both Far East and World data.
Interestingly, China’s military response to its rank in World economy is relative low (at 21.08% in
column 13). In contrast, the country’s response its status in the Far East is more efficient (column
7, 24.03% back to equilibrium). Empirically, after China moved its military focus away from
Central Asia frontiers, the country had maintained active in East and Southeast Asia. Since the
beginning of modern times, most of China’s closely-linked countries located in this region.
Consequently, compared with the whole world, China’s military responses to changes in Asia and
24
Far East’s regional order have been more sensitive.
The overall significance of two alternative tests remains the same to the results obtained from
our original tests. It thus seems unlikely that our finding in China’s post-war defence-growth
nexus could be influenced by different observations. Chinese government’s demand on military
capacity has been consistently influenced by policy-maker’s understanding of the country’s
economic status in surrounding regions. Even when China extended economic influence
internationally after its economic take-off, Asia and its Far East subregion have consistently
remained as the closest trade and investment partners to the country, making China a leading
power in regional order.
Since the early 2010s, Chinese government accelerated its “going-out” policy and encouraged
massive outward investments to foreign shores. This has made China one of the largest foreign
direct investment (FDI) originating countries in recent years. Alongside increasing FDI outside
Asia, China’s globalisation propaganda has made the country a rising power in the international
order. Accordingly, China’s security plan requires a change to adapt such new situations. When
China steps out of Asia and its Far East subregion, the country will inevitably face new
competitive forces outside Asia. As such, China’s future military plan is to largely expected from
its re-calibration in the existing global order.
25
Table 4Robustness of China’s defence spending and its economic ranking in the Far East and worldwide.Economic ranking in the Far East v.s defence spending Panel (a) ADL bounds test and ECM Panel (b) ADL test for threshold cointegration and ECMs
Notes: a The ADL bounds test critical values were obtained from Pesaran et al. (2001); b Critical values of ADL test for threshold cointegration were collected from Li and Lee (2010). Standard errors are reported in parentheses. * Indicates significance at the 10% level; ** Indicates significance at the 5% level; *** Indicates significance at the 1% level.
27
6. Concluding remarks
From a historical standpoint, military strength is crucial for the purpose of China attaining a
wealthy state in the modern times, as it is the key element to safeguard the country’s sovereignty.
In retrospect, a justifiable answer to why and how China was kinked in the wealth-power dilemma
in its development ultimately lies with the weakness of the country, and related to it, the absence
of a sound economic basis in China. After all it was western military superiority that had upset
China’s existing wealth-power balance at the end of the pre-industrial era, altered world market
conditions for China and further crippled its domestic order. Undoubtedly, overseas military
power was an external factor that had forced China to search for a new balance between wealth
and power. The internal factor was however the non-development in various areas of the Chinese
economy. The urgent need for military protection from the state made the defence-prioritised
approach legitimate while the pursuit of economic growth made the development of national
defence sustainable.
However, from the viewpoint of economic development after the establishment and
consolidation of the contemporary China, a better economic growth not only reduces the need for
a strong defence, but also provides the ultimate source of building the latter. China’s failed trials
resulted from first its fragile military capability and second its impotence in economic
development. In reality, after the founding of the People’s Republic of China, external shocks
from foreign powers were systematically eliminated from China’s development which gave China
the opportunity to fundamentally walk out of the dilemma. However, Mao’s erroneous assessment
of the post-war international environment had repeatedly entrapped China in army-first trials; it
was only after his demise and Deng Xiaoping’s advocacy of adopting a low profile to concentrate
on economic growth that changes could be discerned. This explains why the development of
Chinese state had failed when military defence was prioritised, and why China has risen
peacefully in the Far East after its own sphere of economic influence has strengthened in Asia.
28
To analyse China’s quest to become a wealthy state with strong power, the data for defence
spending as a percentage of GDP and China’s per capita GDP rank in Asia from 1960 to 2014 has
been used. By using the ADL tests for both linear and threshold cointegration, some long-run
stable ties could be detected in China’s defence-growth nexus. Under linear assumption,
cointegration was found from defence to power, but no causality in between. However, with
regime-switch consideration, the co-movement is bilateral. The causality only validates from
growth to defence. This proves that economic growth is a deep-rooted shaping force of post-war
Chinese state building.
Econometrically, the results compare favourably with traditional approaches because the
data take China’s position in the international order into consideration; meanwhile, the ADL
threshold method improves the answer to the power problem of cointegration tests. Empirically,
the test result proves a long-term determining co-movement from economic growth to military
strengthening. The indicator identified in ADL threshold cointegration also successfully detected
major historical events in China from 1960 to 2014. These results provide strong evidences for
China’s search for enriching the state and strengthening the army. Meanwhile, these findings
challenge traditional approach of China’s defence-growth nexus and provide empirical evidences
to the debate on “a wealthy state and a strong army” for post-war China.
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