DEFENCE SPENDING AND THE MACROECONOMY THE CASE OF TURKEY

7/29/2019 DEFENCE SPENDING AND THE MACROECONOMY THE CASE OF TURKEY

1/15

PLEASE SCROLL DOWN FOR ARTICLE

This article was downloaded by: [Naval Postgradute School]On: 29 May 2009Access details: Access Details: [subscription number 790889519]Publisher RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK

Publication details, including instructions for authors and subscription information:http://www.informaworld.com/smpp/title~content=t713640174

Onur zsoy aa Department of Economics, Faculty of Political Sciences, Ankara University, Cebeci-Ankara-Turkey 06590

Online Publication Date: 01 June 2008

zsoy, Onur(2008)'DEFENCE SPENDING AND THE MACROECONOMY: THE CASE OF TURKEY',Defence andPeace Economics,19:3,195 208

10.1080/10242690801972139

http://dx.doi.org/10.1080/10242690801972139

Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf

This article may be used for research, teaching and private study purposes. Any substantial orsystematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply ordistribution in any form to anyone is expressly forbidden.

The publisher does not give any warranty express or implied or make any representation that the contentswill be complete or accurate or up to date. The accuracy of any instructions, formulae and drug dosesshould be independently verified with primary sources. The publisher shall not be liable for any loss,actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directlyor indirectly in connection with or arising out of the use of this material.
http://www.informaworld.com/smpp/title~content=t713640174http://dx.doi.org/10.1080/10242690801972139http://www.informaworld.com/terms-and-conditions-of-access.pdfhttp://www.informaworld.com/terms-and-conditions-of-access.pdfhttp://dx.doi.org/10.1080/10242690801972139http://www.informaworld.com/smpp/title~content=t713640174


2/15

Defence and Peace Economics, 2008,Vol. 19(3), June, pp. 195208

ISSN 1024-2694 print: ISSN 1476-8267 online 2008 Taylor & FrancisDOI: 10.1080/10242690801972139

DEFENCE SPENDING AND THE MACROECONOMY:

THE CASE OF TURKEY

ONUR ZSOY*

Department of Economics, Faculty of Political Sciences, Ankara University, Cemal Grsel Caddesi,Cebeci-Ankara-Turkey 06590

TaylorandFrancisGDPE_A_297379.sgm

(Received 1 December 2007; in final form 13 January 2008)

10.1080/10242690801972139DefenceandPeaceEconomics1024-2694 (print)/1476-8267 (online)OriginalArticle2008Taylor&[email protected] study uses a six-variable vector autoregressive (VAR) model and analyses the relationship between defencespending as a percentage of GNP, government budget as a percentage of GNP, total deficit as a percentage of GNP,the GNP growth rates, inflation rates, and government budget deficit as a percentage of GNP for the case of Turkeyfrom 1933 to 2004. The impulse response functions (IRFs) are also derived and Granger causalities among thevariables estimated. The results support the short-run causality between defence spending and economic growth.

Keywords: Defence expenditure; Macroeconomics; Government budget; VAR; Granger Causality; ImpulseResponse Functions; Turkey

JEL Codes: C22, C32, E10

INTRODUCTION

This study attempts to investigate empirically the relationship between defence spending asa percentage of GNP, government budget as a percentage of GNP, total deficit as a percent-age of GNP, the GNP growth rates, inflation rates, and government budget deficit as apercentage of GNP for the case of Turkey from 1933 to 2004. The analysis is conductedemploying a six-variable vector autoregressive (VAR) model. The VAR model is used toderive impulse response functions (IRFs) to examine the response of one variable to ashock in other variables. Additionally, Granger causalities among the variables are esti-

mated and analysed.Turkey is situated in a high-turmoil region in the world. Many of Turkeys neighbouring

countries have long been faced with internal and external economic, social, political, andmilitary problems. For example, Turkeys primary neighbours, Iran and Iraq, were involvedin a war resulting from a border dispute between these two countries, which lasted eight years.Not only did this war influence the countries involved in it, but it also affected neighbouringcountries, including Turkey. Turkey has also been dealing with terrorist activities since the1970s. The problems in neighbouring countries, together with internal terrorist activities, have

*Email: [email protected]


3/15

196 O. ZSOY

caused many direct and indirect negative impacts on the Turkish economy. The immediatedirect negative effects are reduced border security, external military-terrorist treats fromneighbouring countries and internal terrorist threats. On the other hand, the indirect negativeeffects involved the devotion of a large portion of limited resources to defence and security-related issues, reduced external inflow of capital and investment, and the availability of fewer

resources for other social types of spending, such as education, health, public housing, andpublic services. Due to these problems Turkey annually devoted approximately 3.4% of itsGNP to national defence and security between 1933 and 2004. This figure is quite highcompared with other NATO and European Union (EU)1 member countries. Therefore, theexamination of the subject matter is crucial and requires special attention. Since the data setemployed in this study covers a relatively long time span, the likelihood of drawing a clearpicture on the topic is very high. The current study covers a long time period and uses moremacroeconomic variables to better investigate and reach more robust results than previousstudies conducted to analyse the defence-macroeconomy nexus. The results of this studyshould help shed new light on defence and security-related issues, both in Turkey and in coun-tries having similar macroeconomic characteristics. The results of the current study shouldalso help policy-makers understand better the subject matter and so design effective andoptimal defence-macroeconomics related government policies.

This paper is organized as follows. The next section explains the relationship betweendefence spending and the macroeconomy. The third section contains a brief survey of previ-ous studies conducted on the topic. The fourth section includes an overall Turkish macro-economic analysis for the period 19332004. The fifth section focuses on modeldevelopment and presents the estimable form of a VAR system. This section also describesthe variables, defines the data sources, computes time series characteristics of the series, anddiscusses and interprets the empirical results. The final section concludes with main thefindings of this study.

The Relationship between Defence Spending and the Macroeconomy

Military expenditures are expected to positively and negatively influence the macroecon-omy in less developed countries (LDCs) as well as in developed countries (DCs) that allo-cate a significant portion of their limited resources to purchasing or producing defenceequipment or related goods, or to developing military industrial technology. These expendi-tures may affect an economy through several channels, which are categorized into aggre-gate demand and supply channels. It is argued that defence spending, as part of governmentexpenditure, increases aggregate demand through its stimulating effect on unemployed and

unutilized military and non-military industrial capacity, and that this leads to a higher short-run level of output, causing employment and economic growth to rise (zsoy, 1996;Dunne, 1996, Brauer, 2002, and Dunne et al., 2005). For these reasons, Keynesians widelybelieve that idle resources always exist in all types of economies and that military expendi-tures should be used as a tool to increase underutilized capacity and resources, and toexpand output.

As explicitly indicated by Dunne et al. (2005), aggregate supply channels are consideredto be spill-over and crowding-out effects. Spill-over effects occur when one sector of aneconomic system has an impact on the output of other sectors, and this interdependency issupported by market activities. Spill-over effects can be positive or negative. Examples of

1 Turkey is geo-strategically one of the most important members of NATO. However, Turkey is not a full memberof the EU. Negotiations between Turkey and the EU towards full membership started in September of 2005 andhopefully will end around 2015.


4/15

DEFENCE AND THE MACROECONOMY 197

positive spill-over effects include technology spill-over, human capital spill-over, employ-ment spill-over, security spill-over, etc, from the military to the civilian sector. It is believedthat military research and development (MIR&D) produce new ideas, new production tech-niques, and new technologies, which may have direct or indirect civilian applications anduse. This situation may reduce the unit costs of production and thus increase productivity

and economic growth. Contrary to the positive spill-over effects of MIR&D spending, muchMIR&D does not have either civilian applications or civilian use, and defence outlaysreduce the available resources for more productive areas and retard economic growth(zsoy, 1996). For example, production of tanks, nuclear missiles, or other armaments isnot used to increase civilian productivity or to reduce the unit costs of civilian production.Additionally, imports of military goods reduce the limited amount of foreign exchange thatis needed, mainly for imports of intermediate goods, which are necessary for main produc-tion. This worsens the balance of payments and retards economic growth in the LDCs.However, it is widely accepted that arms imports by the LDCs from DCs is a way of trans-ferring technology. It should also be realized that DCs transfer technologies to the LDCsand make LDCs technologically dependent on them. In addition to this, military educationand personnel training might have spill-over effects on the civilian sector. Military person-nel can be employed to increase productivity in the civilian sector after they retire. Militaryeducation and training decrease illiteracy and increase modernization of the LDCs. Thiscontributes positively to economic efficiency and growth. Nevertheless, according to someresearchers, higher wages in the military sector attract and divert more productive andskilled labour from civilian usage. This may be considered a loss for the national economyas a whole.

PREVIOUS STUDIES

Since the influential work of Benoit (1973), there have been many empirical studies conductedto analyse and test the relationship between defence spending and economic growtheconomic performance of both developed and developing countries. However, the studieshave produced different results namely, negative, positive and neutral. The main reasons forthese conflicting results are the different methods and different time periods used by differentresearchers (Dunne et al., 2005).

Kinsella (1990) studied and explored the macroeconomic effects of defence spending in theUS using time-series data for the period 19391989. Kinsella (1990) indicated that there wasno relationship between defence spending and the price level, unemployment rate, or interest

rate. He also found that there was no lagged relationship between defence spending and aggre-gate output. Moreover, Kinsella stated that analysing sub-annual data might attain the causalrelationship between defence spending and macroeconomic variables. On the other hand,Baek (1991) extended Kinsellas study by using a structural VAR model. Baek used Kinsellasdata and found out that the price level has a considerable impact on defence spending in thepost-Second World War period of 19461989 for the USA.

Payne and Ross (1992) extended Kinsellas and Baeks works by using quarterly data forthe time period 1960:11988:1 for the US. The findings of Payne and Ross paralleled the find-ings of Kinsella. Using an unrestricted VAR model, Payne and Ross found that there was norelationship between defence spending and economic performance in the case of the US for

the time period examined.Atesoglu (2002) used the new macroeconomic theory, proposed by Romer (2000) andTaylor (2000), and cointegration methodology, and investigated the defence spending andaggregate output nexus for the US between 1947:2 and 2000:2. He found that there was a


5/15

198 O. ZSOY

positive and statistically significant relationship between defence spending and aggregateoutput for the US. Halco[gbreve] lu (2004) adapted Atesoglus (2002) approach and empiricallyevaluated the relationship between the level of economic growth and defence spending forTurkey for 19502002. She found a positive long-run relationship between aggregate defencespending and aggregate output for Turkey for the sample period.

Kollias et al. (2004) analysed the defence spendinggrowth relation for 15 members of theEuropean Union using cointegration and causality tests for the period 19612000. The resultsof this study did not reveal a uniformity among the sample countries but it showed that growthGranger-caused defence spending. Dakurah et al. (2001) employed the Granger causality testtechnique to establish a relationship between defence spending and economic growth for 62developing countries. They found that there existed unidirectional causality for 23 countriesfrom either defence spending to economic growth or vice versa, bidirectional causality forseven countries, no causality for 18 countries, and the data were integrated of different ordersfor 14 countries.

Dritsakis (2004) investigated the relationship between defence spending and economicgrowth using the Johansen (1988, 1991) cointegration test and vector error correction modelfor Greece and Turkey for 19602001. He found no cointegrating relationship betweendefence spending and economic growth. However, he showed that a unidirectional causalrelationship existed between defence spending and economic growth for both countries.

As the literature review has demonstrated, the relationship between defence spending andvarious macroeconomic variables has been empirically investigated using different methodsand different time periods for different countries. The results of the previous studies foundpositive, negative and no impact of defence spending on the macroeconomic variables. Thus,there has not been any consensus over the topic among researchers. To the best of the authorsknowledge, there have only been a few studies that covered defence spending and more thanone macroeconomic variable at the same time for the case of Turkey. Therefore, this study is

an attempt to fill this gap by using an unrestricted VAR, IRFs, and Granger causality toempirically investigate the relationship between defence spending as a percentage of GNP,government budget as a percentage of GNP, total deficit as a percentage of GNP, the GNPgrowth rates, inflation rates, and government budget deficit as a percentage of GNP forTurkey from 1933 to 2004.

A BRIEF ANALYSIS OF THE TURKISH ECONOMY

After the foundation of the new Turkish state in 1923, Turkey launched new economic policies

to overcome its main economic problems, most of which were inherited from the OttomanEmpire. Until 1929, Turkey followed liberal economic policies to strengthen the privatesector. However, Turkey was negatively affected by the Great Depression of 1929, andchanged its macroeconomic policies. The Turkish economy was then shaped by state-ledeconomic policies until 1980.

Throughout the 1960s and 1970s, Turkey followed an import-substitution basedeconomic growth and development policies. During this period, international trade wascontrolled by the Turkish governments through the implementation of high customs andfixed exchange rate regimes. As a result of these economic policies, during this period, thegovernment played a very important and dominant role in Turkeys overall economic activ-

ities. Turkish private sector investment suffered due to a lack of capital stock. Therefore,large-scale investments were made by the Turkish governments. The main purpose of thiswas to accelerate the formation of capital to boost economic growth. Import substitutioneconomic growth policies were primarily based on importing intermediate goods and raw

g


6/15


materials in order to use them as inputs in producing the most important final goods that thecountry needed. However, the terms of trade deteriorated due to the oil crises of 1974 and1979. These oil crises led the share of intermediate goods imported in total imported goodsto rise from 48% in the early part of the 1970s to 78% in the late 1970s. As a result, thebalance of trade produced huge deficits. In order to overcome these balance of trade

deficits, the Turkish government borrowed short-term credits from international financialinstitutions, including the International Monetary Fund and the World Bank. This situationfurther worsened the macroeconomic condition of the country. Moreover, the conditionsmentioned above had adverse impacts both on the demand and on the supply sides of theeconomy. As a result, inflation, unemployment, interest rates, and international trade deficitstarted increasing.

The year 1980 was a benchmark for the Turkish economy. To overcome the macroeco-nomic problems faced in the 1960s and 1970s, the authorities in Turkey in 1980 made radicalchanges to macroeconomic policies and changed legislations accordingly.

Turkey switched its macroeconomic policies from import-substitution economic growth toan export-led economic growth model on 24 January 1980. The main aims of the macroeco-nomic policies implemented in 1980 can be summarized as follows: to promote free interna-tional trade, to reduce balance of trade deficits through stimulating foreign capital inflows, andto give incentives for domestic and foreign entrepreneurs to make investments to enhance themacroeconomic condition of the country. To achieve the targeted economic polices, theTurkish government reduced customs and taxes, paid trade incentives to export companies,and adopted a flexible exchange rate regime to improve the terms of trade. Moreover, duringthis new era, the Turkish currency was systematically devalued to increase competitivenessand improve the balance of trade. After implementation of the new macroeconomic policies,the overall macroeconomic conditions started improving. The major macroeconomic variablesare descriptively analysed below.

The descriptive data analysis of macroeconomic variables indicates that GNP growth rateswere hardly influenced by changing macroeconomic policies in Turkey. The average GNPgrowth rate was approximately 4.2% for the period 19702004. Between 1970 and 1980,which was before the radical change in macroeconomic policies, average the GNP growth ratewas 4.07%. Between 1981 and 2004, which was after the change in macroeconomic policies,the average GNP growth rate was 4.29%.

The rapid increase in government expenditure caused inflation to rise from an average of32.7% in the 19701980 period to approximately 55.3% in the 19812004 period. This wasmost likely due to the expansionary monetary and fiscal policies adopted after the 1980s.

Unemployment has always been a series problem for Turkey, even during the rapid

economic growth periods. The Turkish economy witnessed an average unemployment rateof 8.2% for the 19702004 period. The unemployment rate was 7.2% for the 19701980period. During the 19812004 period, the unemployment rate remained almost unaffectedat 8.9%.

Interest rates were determined and controlled by the government before the 1980s. As aresult, interest rates did not fluctuate and remained between 9% and 12%. On the other hand,the interest rates were partially determined by the government and by market forces during the19812004 period.

The complete change of macroeconomic policies, the complete or in some cases grad-ual and partial removal of barriers on international trade and the rise of private income

led imports to increase. Export receipts were high enough to remove the impact of highimports on the current account deficit. As a result, the current account deficit decreasedfrom an average deficit of 2.05% in the 19701980 period to 1.3% in the 19812004period.


7/15

200 O. ZSOY

As illustrated in Figure 1, almost all macroeconomic variables drift in the same direction.During the import substitution economic growth policy period, which covered the yearsbetween 1970 and 1980, movements in macroeconomic variables were smooth. Neverthelessin the post-1980 period, expansionary fiscal and monetary policies, the switching of economic

policies from import substitution economic growth models to export-led models, and the dete-rioration of terms of trade, led the major macroeconomic indicators to increase sharply. Inparticular, inflation, interest rates, and the share of the government budget in GNP showed asharp increase.FIGURE1 Majormacroeconomicindicators,19702004

Summary statistics for the major macroeconomic variables are also presented in Table I.When the correlation coefficients matrix is examined, it can be clearly seen that there is a

positive correlation between defence expenditure as a percentage of GNP and share of govern-ment budget in GNP, inflation, government budget deficit as a percentage in GNP, total debt(internal and external debt) as a percentage of GNP, interest rates, and unemployment rates.However, defence expenditure as a percentage of GNP is negatively correlated with GNP

growth rates and the current account deficit as a percentage of GNP (see Table II). The resultof preliminary data analysis is consistent with our theoretical expectations, which will bediscussed in the next section.

-20,00

0,00

20,00

40,00

60,0080,00

100,00

120,00

140,00

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

Year

%

Share of Defense Expenditure in GNP Share of Goverment Budget in GNP

Inflation GNP Growth rates

Government Budget Deficit/ GNP Total Debt/GNP

Interest Rates Unemployment

Current Account Deficit/GNP

FIGURE 1 Major macroeconomic indicators, 19702004

TABLE I Summary Statistics of Selected Macroeconomic Variables

Share ofDefence Ex-

penditure inGNP

Share ofGovernment

Budget inGNP Inflation

GNP

Growthrates

GovernmentBudget

Deficit/GNP

Total

Debt/GNP

InterestRates Unemployment

CurrentAccount

Deficit /GNP

Mean 3.67 23.42 48.25 4.19 4.73 61.55 46.32 8.14 1.54

Median 3.5 20.9 48.54 4.90 3.9 63.4 46.7 8 1.48StandardDeviation

0.70 8.13 26.13 4.71 4.43 28.58 29.98 1.18 2.05

Variance 0.49 66.19 682.97 22.23 19.68 817.22 898.94 1.41 4.20


8/15


TABLEII

CorrelationMatrixofSelectedMacroe

conomicVariables

ShareofDefence

Expenditurein

GNP

ShareofGovernment

BudgetinGNP

Inflation

GNPGrowth

rates

Government

BudgetDeficit/

GNP

TotalDebt/

GNP

Interest

Rates

Unemployment

CurrentAccount

Deficit/GNP

ShareofDefenceExpenditureinGNP

1

ShareofGov

ernmentBudgetinGNP

0.88

5

1

Inflation

0.04

6

0.1

308

1

GNPGrowth

rates

0.13

2

0.2

81

0.4

1

Government

BudgetDeficit/GNP

0.72

7

0.8

979

0.2

85

0.2

59

1

TotalDebt/G

NP

0.47

4

0.7

117

0.2

51

0.1

23

0.7

928

1

InterestRates

0.04

0.1

951

0.7

76

0.1

03

0.3

911

0.5

212

1

Unemployment

0.25

8

0.3

621

0.0

67

0.1

02

0.3

914

0.3

347

0.0

3

1

CurrentAcco

untDeficit/GNP

0.26

0.0

42

0.3

03

0.3

85

0.0

495

0.1

71

0.3

954

0.2

15

1


9/15

202 O. ZSOY

DATA AND EMPIRICAL MODEL

Data

The study uses annual time series data for the period 19702004. The data sources and thevariables are outlined and described below.

SDGNP: Defence expenditure as a percentage of GNP, obtained from the Stockholm Interna-tional Peace Research Institute Yearbooks (SIPRI).SGBGNP: Share of government budget as a percentage of GNP, taken from the TurkishStatistics Organization (TSO).TDGNP: Total deficit as a percentage of GNP, obtained from the TSO.GNPGR: Annual growth rate of GNP, gathered from the TSO.

INF: Inflation series collected from the TSO.GBDGNP: Share of government budget deficit as a percentage of GNP, taken from the TSO.

The procedure starts with the test of determining the order of integration of each of the seriescovered in this study employing the Augmented DickeyFuller (ADF) (Dickey and Fuller,1979) unit root test. The unit root test is crucial in determining the existence of stationarity oftime-series data, because if the stationarity of the time-series is violated, this could lead to aspurious regression (Granger and Newbold, 1974) and thus the estimated regressors could beinvalid for interpretations. In general, a non-stationary time series is said to be integrated oforder d, if it becomes stationary after differencing dtimes, and it is denoted as I(d). The follow-ing ADF unit root test is performed to determine the order of integration for each of the series.

In the equation, is the first difference operator,Xtis the variable to be tested for unit root intime t, is the stationary random error, tis time, and n is the lag length.

The null hypothesis of the existence of a unit root, in variableXt, H0 :1 =0 is tested againstthe alternative hypothesis of the non-existence of a unit root, Ha :1


10/15


were found to be non-stationary. These results indicate that all the series included in this studyare integrated in the first order.

Estimation of VAR models with differenced data may be misleading if the cointegratingrelations among the variables are disregarded (Engle and Granger, 1987). As a result, beforethe estimation of the proposed VAR model, cointegration among the variables needs to bechecked. For this reason, Johansens (1988) cointegration tests were conducted. The resultsindicate no cointegration between any of the series at the 5% significance level (see Table IV).

Since the series are integrated of order one and there is no cointegrating relationship amongthem, an appropriate vector autoregressive (VAR) model can be developed to be estimated.This study makes use of a six-equation VAR model to test and analyse the relationshipbetween defence spending, government budget, total deficits, gross national product, inflation,and government budget deficits for Turkey between 1933 and 2004.

Empirical Model

The unrestricted VAR model can be described in the matrix form as follows:

where 1,tare mutually independent error terms. TheXvariables are fixed and integratedof same order,I(1). The estimable form of the VAR system includes six equations. They aredefined in a matrix form as follows:

X

X

X

X

X

X

X

Xn n

t

t

t

nt

n

nn

n

n n n nn

t

t

t

nt

SDGNP

SGBGNP

TDGNP

GNPGRINF

GBDGNP

SDGNP

SGBGNP

TDGNP

GNPGRINF

GBDGNP

t

t

t

t

t

t

t

t

t

t

t

t

t

t

t

t

t

t

TABLE IV Johansen Tests for the Rank of Cointegration

Trace Test Maximal Eigenvalue Test

H0 Ha TS CV (5%) Prob.** H 0 Ha MES CV (5%) Prob.**

r= 0 r= 1 24.74 83.93 0.40 r= 0 r> 1 24.74 36.63 0.58r 1 r= 2 17.91 60.06 0.55 r 1 r> 2 17.91 30.43 0.70

r 2 r= 3 13.57 40.17 0.63 r 2 r> 3 13.57 24.15 0.64

r 3 r= 4 8.78 24.27 0.73 r 3 r> 4 8.78 17.79 0.61

r 4 r= 5 2.82 12.32 0.85 r 4 r> 5 2.82 11.22 0.81

r 5 r= 6 0.07 4.12 0.82 r 5 r> 6 0.07 4.12 0.82

Note: r is the number of cointegrating vectors. Trace test indicates no cointegration at the 0.05 level. ** denotes MacKinnon-Haug-Michelis (1999) p-values. t-statistics are in parentheses. TS: Trace statistic; MES: Maximal eigenvalue statistic; CV: Critical value.


11/15

204 O. ZSOY

The equations defined in the above matrix represent a standard VAR model. The VARmodel is used to derive impulse response functions. Impulse response functions show thepredictable response of each variable in the system to a shock to one of the variables includedin the system.

Diagnostic Tests on Residuals

Before going further, diagnostic tests should be conducted to ensure that the model is freefrom problems and is estimable. Results of diagnostic tests indicate that the model does nothave problems of serial correlation and heteroscedasticity (see Table V). Although residualtest results confirm that the normality assumption is violated mainly due to the kurtosis prob-lem, Gonzalo (1994) suggests that violation of normality in a VAR model is not a crucialproblem. The inverse roots graph proves the stability of the system (see Figure 2). Therefore,the system is free from problems and can be used to draw conclusions.

FIGURE2 ImpulseResponseFunctions

Pairwise Granger Causality results are shown in Table VI. The results indicate that there isno Granger causality either from SDGNP to SGBGNP, TDGNP,INF, and GBDGNP, or fromSGBGNP, TDGNP, INF, and GBDGNP to SDGNP. However, there is a unidirectionalGranger causality between SDGNP and GNPGR but not vice versa.

These findings are in line with the results of Kinsella (1990), Atesoglu (2002), Dakurahet al. (2001), and Dritsakis (2004) studies. On the other hand, the results of this study contra-dicts the findings of Baek (1991), Payne and Ross (1992), and Halco[gbreve] lu (2004).

In impulse response analysis, the ordering of the variables is important to analyse the effectof the shocks. The residual correlation matrix (see Table VII) suggests the correct ordering

based on the magnitude of the correlation matrix; however, low correlation in our estimationresults indicate that the different ordering of the variable would not produce significantlydifferent results.

The share of defence expenditures as a percentage of GNP continuously decreases for aboutten periods as a result of a shock to SDGNP. SDGNP initially decreases for about two and aquarter periods as a response to a shock to the share of the government budget as a percentageof GNP. The response ofSDGNP to a shock to total deficit as a percentage of GNP is ignorablefor about two and a quarter periods. However, this impact becomes negative thereafter.SDGNP increases for about four periods, then decreases for about two periods and thenreaches its equilibrium due to a shock to GNPGR. A shock toINFhas no impact on SDGNPfor three and a quarter periods; thereafter, a negative impact is present. SDGNP remainsconstant for two periods as a result of a shock to the government budget deficit as a percentageof GNP and then becomes negative for about three periods; after the fifth period this effectdies out.

g

TABLE V Diagnostic Tests Results

Hypothesis

Test statistics

(p values)

H0: No Var Residual Serial Correlation LM Stat 31.55(0.68)

H0: No Var Residual Heteroscedasticity Chi. Sq 524.82(0.25)

H0: Residuals are Multivariate Normal [Cholesky-(Lutkepohl)] Jarque-Bera 2.024(0.36)

H0: Residuals are Multivariate Normal (Urzua) Jarque-Bera 4.95(0.084)


12/15


FIGURE 2 Impulse Response Functions


13/15

206 O. ZSOY

TABLE VI Pairwise Granger Causality Tests

Sample: 19332004

Lags: 2

Null Hypothesis: Obs F-Statistic Probability

SGBGNP does not Granger Cause SDGNP 72 0.38372 0.68281

SDGNP does not Granger Cause SGBGNP 2.10387 0.12997

TDGNP does not Granger Cause SDGNP 70 0.08543 0.91822

SDGNP does not Granger Cause TDGNP 0.91644 0.40504

GNPGR does not Granger Cause SDGNP 72 0.61715 0.54252

SDGNP does not Granger Cause GNPGR 9.72951 0.00020

INFdoes not Granger Cause SDGNP 72 0.37124 0.69129

SDGNP does not Granger CauseINF 2.17584 0.12147

GBDGNP does not Granger Cause SDGNP 72 0.09131 0.91285

SDGNP does not Granger Cause GBDGNP 0.16351 0.84949

TDGNP does not Granger Cause SGBGNP 70 0.10203 0.90315SGBGNP does not Granger Cause TDGNP 2.47827 0.09178

GNPGR does not Granger Cause SGBGNP 72 1.48931 0.23290

SGBGNP does not Granger Cause GNPGR 0.89791 0.41227

INFdoes not Granger Cause SGBGNP 72 1.26410 0.28914

SGBGNP does not Granger CauseINF 4.20732 0.01900

GBDGNP does not Granger Cause SGBGNP 72 1.56567 0.21650

SGBGNP does not Granger Cause GBDGNP 2.13394 0.12635

GNPGR does not Granger Cause TDGNP 70 0.38380 0.68280

TDGNP does not Granger Cause GNPGR 0.05355 0.94790

INFdoes not Granger Cause TDGNP 70 3.20617 0.04700

TDGNP does not Granger CauseINF 3.06582 0.05341GBDGNP does not Granger Cause TDGNP 70 3.84807 0.02634

TDGNP does not Granger Cause GBDGNP 4.07816 0.02145

INFdoes not Granger Cause GNPGR 72 3.45114 0.03745

GNPGR does not Granger CauseINF 0.53516 0.58806

GBDGNP does not Granger Cause GNPGR 72 0.45132 0.63871

GNPGR does not Granger Cause GBDGNP 0.16294 0.84998

GBDGNP does not Granger CauseINF 72 0.39905 0.67254

INFdoes not Granger Cause GBDGNP 4.03937 0.02206

TABLE VII Residual Correlation Matrix

SDGNP SGBGNP TDGNP GNPGR INF GBDGNP

SDGNP 1.000000 0.353422 0.130031 0.007971 0.008328 0.318264

SGBGNP 0.353422 1.000000 0.419157 0.339429 0.124186 0.708427

TDGNP 0.130031 0.419157 1.000000 0.423422 0.263503 0.253333

GNPGR 0.007971 0.339429 0.423422 1.000000 0.359672 0.352892

INF 0.008328 0.124186 0.263503 0.359672 1.000000 0.208615

GBDGNP 0.318264 0.708427 0.253333 0.352892 0.208615 1.000000


14/15


CONCLUSIONS

This study used a six-variate VAR model and examined the relationship between share ofdefence spending in GNP, share of government budget in GNP, total deficit in GNP, GNPgrowth rate, inflation and government budget deficit in GNP for Turkey from 1933 to 1924.

IRF results are derived from the VAR model and examined. The results indicated that there isa unidirectional Granger causality between SDGNP and GNPGR and not vice versa. However,there is no causal relationship between SDGNP and all the other series included in this study.Moreover, IRF results show that a shock to GNP has no impact on SDGNP for about twoperiods, it increases SDGNP for about two periods and then reaches equilibrium after the sixthperiod. SDGDP decreases for about two periods as a result of a shock to SDGNP and thengradually increases until the eighth period and eventually returns to equilibrium. SDGNPremains constant for two periods, decreases for two and a half periods, increases for fourperiods and comes to the equilibrium due to a shock to TDGNP. The response ofSDGNP to ashock toINFis unnoticeable for about three and a quarter periods, decreases for one and a halfperiods and then increases and returns to equilibrium. Furthermore, a shock to GBDGNP hasno impact on SDGNP for about two and a quarter periods; it negatively affects SDGNP forabout one and a half periods and then reaches equilibrium at about the fifth period.

The major conclusions to be derived from this study are that defence expenditure Granger-causes economic growth and a shock to GNPGR leads SDGNP to increase.

References

Atesoglu, H.S. (2002) Defense spending promotes aggregate output in the United States evidence from cointegrationanalysis. Defence and Peace Economics 13(1) 5560.

Baek, E.G. (1991) Defense spending and economic performance in the United States: some structural VAR evidence.Defence and Peace Economic 2 251264.

Benoit, E. (1973) Defence and Economic Growth in Developing Countries. Boston: Heath DC.Brauer, J. (2002) Survey and review of the defence economics literature on Greece and Turkey: what have we

learned? Defence and Peace Economics 13(2) 85107.Dakurah, H., Davies, S. and Sampath, R. (2001) Defense spending and economic growth in developing countries.

A causality analysis. Journal of Policy Modeling 23 651658.Davidson, R. and MacKinnon, J. (1993) Estimation and Inference in Econometrics.London: Oxford University Press,

p. 708, Table 20.1.Dickey, D.A. and Fuller, W.A. (1979) Distribution of the estimators for autoregressive time series with a unit root.

Journal of the American Statistical Association74 427431.Dritsakis, N. (2004) Defense spending and economic growth: an empirical investigation for Greece and Turkey.

Journal of Policy Modeling26(2) 249264.Dunne, P. (1996) Economic effects of military expenditure in developing countries: a survey. In The Peace

Dividend, edited by N.P. Gleditsh, O. Bjerkholt, A. Cappelen, R. Smith and P. Dunne. Amsterdam: NorthHolland, 439464.

Dunne, J.P., Smith, R.P. and Willenbockell, D. (2005) Models of military expenditure and growth: a critical review.Defence and Peace Economics 16(6) 449461.

Engle, R.F. (1984) Wald, likelihood ratio, and Lagrange multiplier tests in econometrics. In Handbook of Econo-metrics, Volume 2, edited by Z. Griliches and M. D. Intriligator. North-Holland: Elsevier, Chapter 13.

Engle, R.F. and Granger, C.W.J. (1987) Co-integration and error correction: representation, estimation, and testing.Econometrica 55 251276.

Gonzalo, J. (1994) Five alternative methods of estimating long-run equilibrium relationships. Journal of Economet-rics 60(12) 203233.

Granger, C.W.J. and Newbold P. (1974) Spurious regressions in econometrics. Journal of Econometrics 2 111120.Halco [gbreve] lu, F. (2004) Defense spending and economic growth in Turkey: an empirical application of new macro-

economic theory. Review of Middle East Economics and Finance 2(3) 193201.Johansen, S. (1988) Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control 12

231254.

Johansen, S. (1991) Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressivemodels. Econometrica 59 15511580.Kinsella, D. (1990) Defense spending and economic performance in the United States: a causal analysis. Defence

Economics 1(4) 295309.

g


15/15

208 O. ZSOY

Kollias, C., George M. and Suzanna-Maria, P. (2004) Defence expenditure and economic growth in the EuropeanUnion a causality analysis. Journal of Policy Modeling 26 553569.

Ozsoy, O. (1996) Military expenditures and their impact on the economic growth of Turkey and Greece. UnpublishedPhD Dissertation. Binghamton, NY: State University of New York at Binghamton-USA.

Payne, J.E. and Ross, K.L. (1992) Defense spending and the macroeconomy. Defense Economics 3 161168.Romer, D. (2000) Keynesian macroeconomics without the LM curve. The Journal of Economic Perspectives 14(2)

149169.

Taylor, J.B. (2000) Teaching modern macroeconomics at the principles level. American Economic Review 90(2)9094.

Date post:	04-Apr-2018
Category:	Documents
Upload:	kostas-tourkantonis
View:	220 times
Download:	0 times

DEFENCE SPENDING AND THE MACROECONOMY THE CASE OF TURKEY

Documents