govt spending, budget financing, and eco growth

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Government Spending, Budget Financing, and Economic Growth: The Tunisian ExperienceAuthor(s): Khalifa GhaliReviewed work(s):Source: The Journal of Developing Areas, Vol. 36, No. 2 (Spring, 2003), pp. 19-37Published by: College of Business, Tennessee State UniversityStable URL: http://www.jstor.org/stable/4192918 .Accessed: 24/09/2012 11:45

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The Journal of Developing Areas Volume 36 Number 2 Spring 2003

GOVERNMENT SPENDING, BUDGETFINANCING, AND ECONOMIC GROWTH:

THE TUNISIAN EXPERIENCE

Khalifa GhaliKuwait University

ABSTRACT

Many developing ountries dopted he IMF debt-stabilization rograms ithout having any clearevidence on whether public sector activities promote or depress economic growth. The existingliterature n the subject did not provide a consensus udgment n which a policy conclusion ansafely be made. In addition, he question f whether he impact f government ctivities n growthdepends n the source of financing he government udget s still open to debate. This paper aisesthese issues in the case of Tunisia, which is a small developing country mplementing ebt-stabilization rograms without having any clear guidance on how government ctivities nteractwith macroeconomic ariables n affecting ts growth process. In contrast o the conventionalprocedure f estimating single growth equation, his paper develops a vector error-correction

model and identifies both the direct as well as the indirect hannels hrough which governmentspending an affect economic rowth. These effects are hen analyzed epending n whether debtfinanced r a tax-financed iscal policy s followed. The empirical esults uggest hat governmentspending n Tunisia has an important ole in shaping he general efficiency of the economy,whereas government reliance on debt financing has adverse effects on economic growth.

INTRODUCTION

In the aftennath of the debt crisis, many developing countries adhered to the IMFsponsored debt-stabilization programs, which called for shrinking the size of the

government in order to control the debt and promote economic growth. However, formost of these countries, there is no evidence on the way government activities interactwith macroeconomic variables in affecting the growth process. Moreover, the existing


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literature produced conflicting results and raised doubts about the nature of therelationship between government spending and economic growth.

The economic literature on the subject witnessed the emergence of two conceptuallyopposite views about the impact of government pending on economic growth. One point ofview suggests that higher government spending is likely to be detimental to economicgrowth. One reason is that government operations are often conducted inefficiently. Forexample, state owned firms are often politicized and their main objective is to satisfyinterests of bureaucrats nd politicians. To maintain heir power and prevent social unrest,these groups favor excess employment, neffective locations, and under pricing of output. In

addition, public investment undertaken by heavily subsidized state-owned monopolies hasmore often reduced the possibilities for private nvestment and long-run economic growth.Another reason is that the financing of public expenditures hrough external and internalindebtedness imposes excessive burdens and costs on the economic system resulting inadverse effects on economic growth. At the other extreme, there are points of view thatattribute to the government a non-negligible role to play in the process of economicdevelopment and argue that a larger govenmment ize is likely to have a positive impact onlong-run economic growth. One argument is that government plays a critical role inharmonizing conflicts between the private and social interests and in providing a sociallyoptimal direction for growth. Moreover, in countries characterized by the existence ofmonopolies, the lack of fully developed markets of capital, insurance, and information,govemment can make factor and product markets work more efficiently and generatesubstantial pillover effects for the private sector.

On the empirical side, most investigations of the impact of government spending oneconomic growth were conducted using cross-country models. These studies attempted olink aggregate measures of fiscal policy with average growth rates of GDP using measures ofthe overall size of the govemment in the economy, disaggregate measures of governmentspending, or measures of the growth rate of government expenditures. The maincontributions o this literature were made by Rubinson 1977), Feder (1983), Landau 1983),

Kormendi and Meguire (1985, 1990), Ram (1986), Grier and Tullock (1989), Grossman(1988), Barro (1990, 1991), Romer (1989), Levine and Renelt (1992), and Barro and Sala-i-Martin 1995), among others.

However, as far as economic policy is concemed, the cross-country iterature did notprovide the basis on which a particular country can decide whether an expandinggovernment ize would accelerate or depress economic growth, and that for many reasons.

First, the cross-country iterature n the subject produced conflicting results and did notprovide any consensus judgment on the impact of government spending on economicgrowth. For example, Landau (1983), Grier and Tullock (1987), Grossman (1988), andBarro (1990) found a negative and significant relationship between the growth rate of real

GDP and the growth rate of the government hare n GDP, while Ram (1986) and Rubinson(1977) suggest that govenmment ize has a positive impact on economic growth. Kormendi


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Government pending 1

and Meguire (1985), however, found no significant relationship between the share ofgovernment onsumption n GDP and economic growth.

Second, since economic policies tend to be country-specific and their success dependslargely on the institutions mplementing hem, policy recommendations annot safely bemade by generalizing the results of cross-country models to individual countries. This isbecause the pooling process in cross-country regressions imposes strong parametricrestrictions across countries hat differ greatly in terms of their economic structure. Pooledestimates in these models are obtained by pulling the extreme values of the parameterstowards a common mean. This view seems to be consistent with the recent studies by

Maddala and Wu (2000) and Lee et al. (1996) who provided evidence on the problems ofheterogeneity, tability, and interpretation nherent o cross-country models. Moreover, it isfair to argue that, while a concept such as the long run is a dynamic one, cross-countrymodels do not include sufficient time and, hence, are not useful for analyzing the dynamicproperties of growth. Therefore, it is hazardous to draw policy conclusions from cross-country tudies and a better strategy would be to investigate he issue in a time-series settingwhere the particular characteristics of the country under consideration are taken intoaccount.

Finally, an important ssue that has often been neglected in the literature s the impact ofthe source of financing government expenditures on economic growth. In this respect, it isimportant o notice that cross-country tudies examine the impact of government pendingon economic growth by looking at the sign and significance of the relevant variable n thegrowth equation. In this context, government spending would have an accelerating or adepressing effect on growth depending on whether ts sign is positive or negative. Followingthis literature, a policy conclusion would be for the government to withdraw from anyactivity that has a significant negative impact on growth. However, one could argue that thenegative impact may be the result of the way this activity was financed and not the activityitself. For instance, a growing govenmment ize may affect economic growth n two oppositeways depending on whether a debt-financed r a tax-financed xpansionary iscal policy is

followed. Theoretically, here is a controversial debate on whether a tax- or adebt-financed

government budget has the same effects on growth. The two competing views known as theRicardian equivalence proposition and the traditional view are well documented in theliterature ut did not provide any consensus udgment on the issue. Examples are Leidermanand Blejer (1988), Kormendi and Meguire (1990), and Dalamagas (1992). Consequently,the question of whether the tax collection policy or the debt accumulation process isresponsible or the distortionary ffects of government xpenditures n economic growth nstill an open question n countries where the issue has not been addressed before.

The objective of this paper is to investigate whether changes in government pendingconstitute an effective policy for promoting economic growth in the small, developing

economy of Tunisia. The analysis ocuses on two main ssues of interest: i) investigating hecausal channels through which govenmment pending can affect economic growth; and (ii)investigating the impact of alternative sources of budget financing on the growthperformance. Upon recommendations by the IMF and the World Bank, Tunisia started


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22 Khalifa Ghali

large-scale programs of restructuring ts public sector in an attempt o reduce the size of thegovernment n the economy and, hence, accelerate conomic growth. However, here s noempirical evidence that provides policymakers with information concering the particularcausal patterns hat link public sector activities to economic growth. Although some of thepast studies have analyzed ssues related to growth, economic development, and economicpolicymaking n Tunisia, none of them has empirically assessed the impact of governmentactivities on economic growth.' Examples of these are: Nsouli et. Al. (1993), World Bank(1996), Ilker and Ghiath (1999) and Ghali (1999). The availability of such infonnationwould provide policymakers n this country with insightful ndications on the mechanisms

through which fiscal policy and macroeconomic variables nteract n affecting the growthprocess. Furthermore, he analysis would help the Tunisian iscal authorities o assess theimpact of altemative sources of financing the government budget on economic growth.

After reviewing some specification ssues raised by past empirical research we modelthe dynamic interactions between govermment pending and economic growth in a six-variable system consisting of real GDP, govemment spending, private nvestment, exports,imports, and labor. In particular, we use the Johansen 1988, 1991, 1992) and Johansen andJuselius 1990) cointegration echniques and develop a vector error-correction VEC) modeluseful for identifying all possible channels hrough which government pending may affecteconomic growth.

The results of the empirical analysis can be summarized as follows: (i) there is ameaningful, table long-run elationship hat ties the long-run behavior of real output o thatof governent spending, nvestment, xports, mports and labor; ii) there are four possiblechannels through which government spending can affect economic growth in Tunisia. Inaddition to its direct effects, government pending has also indirect effects on growth andthat through nvestment, mports and labor; iii) government ctivities designed to shape thegeneral efficiency of the economy, and to improve the productivity of labor and importsseem to have an accelerating effect on growth, whereas government nvolvement in theeconomy as a producer eems to crowd-out private nvestnent from profitable opportunities,resulting n a depressing effect on economic growth; and (iv) the government reliance ondebt to fmance its budget seems to induce adverse effects on economic growth. Theremainder of the paper is organized as follows. Section II presents the model and themethod, section III presents he empirical esults and section IV concludes.

THE MODEL AND THE METHOD

While the main focus of the paper s on the relationship etween government pendingand economic growth, we also consider some specification ssues raised by past empiricalresearch, especially those raised n cross-country rowth studies. The main reason for this isthe non-existence of a consensus theoretical ramework hat guides empirical research ongrowth. In addition, the existing literature using cross-country growthl models does notcompletely specify the variables that should be held constant when inferences are madeabout he relationship etween economic growth and the variables of interest. For example,


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Feder (1983) and Ram (1986) use an augmented neoclassical production imction o conducttheir empirical studies, while Romer (1989) and Barro (1990) use endogenous growthmodels. Kormendi and Meguire (1985) and Grier and Tullock (1989) use a variety ofmodels to justify an assortnent of variables hat they use in their empirical research. In ourempirical investigations of the causal links between govenmment pending and economicgrowth we will also consider variables such as international rade, investment, and labor.Apart rom their theoretical elevance, he inclusion of such variables would also avoid, or atleast minimize, the problem of non-causality due to omitted variables (Lutkepohl, 1982).

The theoretical ies between international rade and economic growth were formalizedby Romer (1986, 1990b), Grossman and Helpman (1990), and Rivera-Baptiz and Romer(1991), among others. Although theoretical discussions frequently consider the relationshipbetween international rade and economic growth, the empirical literature has typicallyexamined the relationship between exports and growhi.2 In our empirical investigations ofthe dynamic properties of growth in Tunisia we consider the effects of both imports andexports on the economic performance f the country.

Another ssue that we consider here is the interaction between growth, investment andtrade. Theoretically, the relationship between trade and growth is based on the improvedallocation of resources and not necessarily on enhanced resource accumulation. However,results from Levine and Renelt (1992) indicate that the relationship between growth andtrade becomes insignificant when investment s introduced n the growth equation, whereasthe relationship between investment and the trade variables s a significant one. Given thatinvestment was found positive and significant in the growth equation, they suggest theexistence of a two-link chain between trade and growth through nvestment and concludethat the relationship between trade and growth s based on enhanced resource accumulationand not the improved allocation of resources.

Given the importance of these issues, our investigation of the causal links betweengovernment spending and economic growth in Tunisia is made witiin a 6-variable systemcontaining real GDP, government spending, investment, exports, imports and labor.

The empirical analysis of causality s conducted witiin a framework based on unit roottesting and cointegration. n particular, we develop a vector error-correction model (VECM)of growth where all variables are allowed to be endogenous o the system. The advantage ofthis approach, as opposed to single growth equation estimation, s the possibility to captureboth the direct as well as the indirect effects of govemment spending on economic growth.Withiin this framework, we first investigate all the possible charmels through whichgovernment spending can affect economic growth, and then we investigate the impact ofalternative ources of financing he govemment budget on economic growth.

A VECTOR ERROR-CORRECTION MODEL OF GROWTH

Consider he set of variables consisting of real GDP and the respective shares n GDP ofprivate nvestment, otal government expenditures, xports, imports and labor. All variablesare transformed nto their natural ogarithm. These variables will be denoted hereafter by Y,


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24 Khalifa Ghali

I, G, X, M and L, respectively. Now consider he vector autoregressive VAR) model

A- 1 t-I + 2 Zt-2 +- ...+ 4kt-k + + nt, t1,....,T (1)

where Zj is a 6 x 1 vector containing Y I, G, X, M and L. Suppose that these variables areI(O) after applying he differencing ilter once. If we exploit the idea that there may exist co-movements of these variables and possibilities that they will trend together owards a long-run equilibrium state then, by the Granger representation heorem, we may posit thefollowing testing relationships hat constitute a vector error-correction VEC) model of

growth

AZ = r A 1t-kI +sit, t l. ,T (2)

where AZ4 contains he growth rates of the variables. The F's are estimable parameters, Ais a difference operator, lit is a vector of impulses which represent the unanticipatedmovements in Z, with flt niid (0, 3) and r is the long-run parameter matrix. With rcointegrating ectors (1? r < 6), D has rank r and can be decomposed as rI = ap', with aand f3both 6 x r matrices. , are the parameters n the cointegrating elationships and aare the adjustment oefficients which measure he strength f the cointegrating ectors n theVEC model.

The Johansen (1988) approach estimates the long-run or cointegrating relationshipsbetween the non-stationary ariables using a maximum ikelihood procedure which tests forthe cointegrating ank r and estimates he parameters f3 nd a.On expanding out equation 2, the VEC model of growth can be expressed as follows:

r pAYt =pLi Jlx,,vkt_p Y (yi,sAYt_s y2,sAGt +y3,sAIt_sy4,sAXA-s 75sAMt-s y6,sAL_t)+11 ,t (3)

k=l s=l

r pAGt =p2 + Ya2,kvkt-p (O,sAYts+02,sAGt?s+O3 AIt-s+04AXt-s+05,sAMt-s+06,sAL-s)+i2,t4)

k=l s-l

r pAlt =p3 +EVtp + (8sAYt-s+62 sAGt-s+63 Its+4,Xt-s+66sAMt-s +66,sALts) +13,t (5)

k=l s-l


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r pAXt =W +Ea4.kvk,t-p +E (4LsAYt-s+4 2,sAGt-s 4 3,sAIt-s 44,sAXt-s 0s,sAMt-s+4 ,sALt-s) Tn4,t (6)

k=l s=l

r pAMt =ps +Ea5kVkt-p +E (l,sAYt-s+92,sAGt s+(p3,sAIt +94,sAXt-s+sp5sAMt-s+96,sAI-t-s)+Ss5t 7)

k=l s=l

r pAL =p6 + X,kVkt-p +E (ki,sAYt s+2,sAGt s+k3,sAIt-s+4.sAXt-s+X5,sAMt-s+h,s s) +fn6,t (8)

kl s=l

where aXi,k re the adjustment coefficients, vkt-p are the cointegrating vectors, and pt,..., tsare intercepts.

The advantage of modeling the relationship between government spending andeconomic growth n a system of equations as in (3) - (8), instead of a single growth equation,is the possibility to identify both the direct as well as the indirect inks between them. Thedirect effect of government pending on economic growth, which is conventionally ested ina single growth equation, can be detected from equation (3) through he distributed ags ingovernment pending. The additional quations 4) - (8) offer the possibility to identify hoseindirect effects that may result from the impact of govemment spending on any of theremaining variables that has, in turn, a direct link with economic growth. That is, theinteraction of government spending with investment, trade and labor may result in anindirect mpact on economic growth.

EMPIRICAL RESULTS

Data and Variable Definitions

Data used in the study are annual series for Tunisia and cover the period 1960-2000.The variables and their definitions where In denotes the natural ogarithm are as follows:Y = ln(real GDP),I = ln(the ratio of private nvestnent to GDP),G = ln(the ratio of total government pending o GDP),X = ln(the ratio of exports o GDP),M = ln(the ratio of imports o GDP),L = ln(labor force),

D = ln(the ratio of government debt to GDP), andT = In(the ratio of tax revenues o GDP).


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GDP is gross domestic product, real GDP is GDP deflated by the GDP deflator. Privateinvestment s measured by the total real gross private-business nvestment. Total governmentspending s measured by government urrent and capital expenditures. Exports and importsrefer to total exports and total imports. The labor force refers to the total labor forceemployed in the different sectors of the economy, including agricultural employment.Government debt refers to the budget deficit of the government, and tax revenues are thetotal taxes collected by the government.

The first difference of Y is taken to be a proxy for economic growth. Data on GDP,exports, and imports are gathered rom various ssues of the IMF publication nternational

Financial Statistics (IFS). Data on private investment, labor, government debt, and taxrevenues were obtained rom the Tunisian Ministry of Economy.

TEST RESULTS FOR UNIT ROOTS

Since the VAR specification n (1) requires hat some or all variables are integrated forder one, I(1), we herein investigate he stationarity tatus of all the series defined aboveusing the augmented Dickey-Fuller ADF) and the Phillips-Perron P-P) tests of stationarity.These tests are performed both on the level as well as on the first difference of the variablesallowing for a time trend whenever s its significant. In each case the lag-length s chosenusing the Akaike Information Criterion AIC) after testing for first and higher order serialcorrelation n the residuals.

Table 1 reports he results of the unit root tests. The first half of the table contains theresults of testing for unit roots in the level variables. These results suggest that each of thetime-series has a unit root. The second half of the table reports tests for unit roots afterdifferencing the data once. In this case both tests reject the null hypothesis of unit root.Because the data appear o be stationary n first differences, no firther tests are performed.Therefore, we maintain the hypothesis that each of the series is integrated f order one.

Table 1. Test Results for Unit Roots

Variable Y I G X M L D TADF -1.182 -1.714 -1.942 -1.642 -1.390 -1.563 -1.992 -1.565P-P -1.212 -1.699 -1.640 -2.300 -1.558 -1.436 -1.966 -1.601Variable AY Al AG aX AM AL AD ATADF -4.562 -3.829 -3.864 -4.605 -3.752 -3.296 4.514 -3.692P-P -6.691 4.718 4.628 -5.176 -5.031 -4.672 -6.754 4.930

NOTES: Variables are as defined in the text. The above tests are performed using the followingregression

p

Ayt= po+ plYt-I p2T dsAYt,s+vt,s=I


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Govenment Spending 27

where yt is the relevant ime series, T is a time trend, and vt is a residual erm. The time tend in thisregression is allowed only when found to be significant. The lag-length p is chosen using the AIC

criterion after esting for first and higher order serial correlation n the residuals. The critical values for

ADF and P-P are -2.967 and -2.970, respectively.

TEST RESULTS FOR COINTEGRATION

Before applying he Johansen rocedure o estimate a and f3, it is5necessary odetermine he lag length, k, of the VAR, equation 1), which should be high enough o

ensure that the errors are approximately white noise, but small enough to alIow estimation.Since the Johansen procedure s sensitive to the choice of the lag length, we based ourdecision on the Akaike' s Final Prediction Error FPE) criterion and selected k-=3. Using thislag length, we conducted diagnostic checking tests for normality and serial correlation n theresiduals or each of the 6 equations n VAR. The results f these ests, not reported ere,indicate that with k--3 the residuals are approximately ndependently dentically normallydistributed niid) for all the equations.

The results of testing for the number of cointegrating vectors are reported n table 2,which presents both the maximum eigenvalue (X.,) and the trace statistics, he 10 percentcritical values as well as the corresponding X values. This test is performed using anunrestricted ntercept erm in VAR, which assumes the existence of a deterministic imetrend n the data. The results of the test indicate he existence f one cointegrating ectordriving the data. The check the robustness of this result, we jointly test the hypotheses thatthe rank s equal o one and hat he data ontain time rend.We do this using he Johansen(1992) ikelihood atio est. The results f this test, not reported ere, confirm hat he rankof D is equal o one and hat he data do contain time rend omponent. onsequently, heintercept erm will be associated o the VEC equations ndnot to the cointegration pace.

The estimates f the P and a and, vectors re presented n table 3. From he a vectorwe can see that he adjustment oefficient f labor s small and nsignificant. esting hat his

coefficient s zero s a test hat abor s weakly xogenous ndyields a likelihood atio est=1.64, which compared o the 5% critical alue x2(1) = 3.84 enables us to easily accept henull hypothesis. stimates f a and p after mposing he weak exogeneity estriction n Lare presented n table 4. The results f this table ndicate hat he model s now completelyidentified.

The results of cointegration ndicate the existence of a meaningful, stable long-runequilibrium elationship hat ties together he long-run ehavior f re4 output o that ofinvestment, overnment pending, xports, mports, and labor. With this, the short-rundynamics f output an be seen as an adjustment o this ong-run quilibrium tate. n eachshort-term eriod, deviations f output rom his equilibrium ill feed back on its changes n

order o force ts movement owards ts long-run quilibrium. rom he a vector n table 4we can see that real output n Tunisia has a high speed of adjustment o its long-run


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equilibrium tate. The short-mn behavior of output s being corrected by about 62% of theimbalance occuring in the previous period between output and its long-rn equilibriumvalue.

Table 2. Testing the Rank of n

Trace a

-HO HI Stat. 90% HO HI Stat. 90%

r=0 r> 1 93.99 89.37 r 0 r= 1 35.75 24.63 0.355r2 42.24 64.74 r 3 25.03 43.84 r? 2 r = 3 9.03 17.15 0.178r < 3 r > 4 15.03 26.70 rc3 r = 4 3.98 13.39 0.125r < 4 r > 5 8.03 13.31 r < 4 r 5 2.05 10.60 0.088r 6 1.03 2.71 r


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Govemment pending 9

Table 5. Estimates of the VEC Model

Variable AYt Alt AGt AXt AMt ALt

Intercept 1.4003 2.601 -0.455 0.104 1.277 0.563(3.116) (2.891) (-2.083) (1.998) (2.441) (3.119)

Vt I -0.620 0.528 0.357 0.441 -0.558

(-4.320 (3.970) (4.024) (3.229) (-2.633)

AYt i -0.315 0.110 0.522 -0.344 0.237 2.916(-2.788) (2.661) (2.662) (-0.081) (2.670) (3.530)

AYt 2 0.517 0.088 0.407 0.453 0.102 1.881(3.116) (1.177) (2.011) (2.013) (2.455) (3.016)

Alt i -0.027 0.322 0.202 0.219 0.417 -0.082(-0.770) (2.801) (1.708) (2.337) (3.058) (-1.456)

AIt-2 0.319 0.221 0.223 0.045 0.214 1.557(3.001) (1.701) (1.421) (1.116) (2.309) (1.490)

AGti 0.261 -0.231 0.233 -0.241 0.216 2.056(2.702) (-3.005) (1.094) (-1.443) (2.913) (5.733)

AGt-2 0.075 -0.066 0.118 -0.070 0.083 1.408(2.290) (-2.183) (1.002) (-0.844) (1.054) (3.339)

AXt i -0.007 0.338 -0.127 -0.031 -0.040 -0.976(-0.113) (2.529) (-0.728) (-0.112) (-0.836) (-1.002)

AXt-2 0.216 0.018 -0.032 -0.012 -0.019 -0.620(2.768) (1.327) (-0.401) (-0.304) (-0.026) (-0.839)

AMti 0.026 0.671 -0.004 -0.108 -0.412 -0.540(1.009) (3.593) (-1.201) (-0.313) (-1.225) (-1.036)

AMt 2 0.418 0.212 -0.013 -0.033 -0.327 -0.033(3.811) (2.642) (-0.801) (-0.019) (-0.981) (-0.025)

ALT-i -0.075 0.311 0.381 0.015 -0.028 -0.753

(-1.103) (2.818) (2.552) (1.002) (-0.985) (-2.566)ALt-2 0.251 0.115 0.227 0.012 -0.016 -0.216

(3.716) (2.091) (2.016) (0.974) (-0.335) (-1.499)R2 0.78 0.69 0.42 0.26 0.21 0.36

a 0.0164 0.0428 0.0477 0.0772 0.0981 0.0544TSC(10) 6.12 2.701 8.802 6.551 7.733 4.102

N(2) 1.041 0.415 0.453 1.399 1.520 0.836RESET(1) 0.236 0.813 2.487 0.562 1.644 0.721

NOTES: T-ratios are in parentheses. TSC(10) is a test for up to the tenth-order erial correlation, N(2)

is the Jarque and Bera test for normality, and RESET(1) s a test for parameter nstability.

Table 5 reports the OLS estimates of the vector error-correction model using thecointegration vector in Table 4. Since these estimates are sensitive to departures rom the


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30 Khalifa Ghali

standard ssumptions, we subjected he estimated residuals n each equation o a battery ofdiagnostic ests. The first test, TSC(10) is a test for up to the tenth order serial correlation nthe residuals, which is distributed X2(10). The second test, N(2), is the Jarque & Beranormality test whichis asymptotically distributed Z2(2). The third est, RESET(l), is theRESET test for parameter nstability which is asymptotically istributed X2(1). The resultsin table 5 suggest that residuals rom the 6 equations pass the tests at the 95% significancelevels and, hence, there is no significant departure from the standard assumptions.

TESTING FOR GRANGER NON-CAUSALITY

The recent literature as shown that the conventional esting procedure or granger non-causality using the F-statistic has size and power problems due to its, dependence on thepretesting for cointegration Zapata and Rambaldi, 1997). A much accurate and simplerprocedure was proposed independently by Dolado and Lutkepohl (1996) and Toda andYamamoto 1995) and is known as the augmented VAR approach. As shown by Zapata andRambaldi 1997) and Giles and Mirza (1999), the augmented VAR testing procedure s verysimple to compute and is independent of the cointegration properties of the data. For thepurposes of this paper, his procedure oes as follows:

1. Since the VAR model contains 3 lags and since the highest order of integrationin the data s one, we first estimate a VAR in levels with 4 lags, then2. We test jointly that the first 3 lags of the relevant variable are zero using a Wald-test which has a chi-squared istribution.

Table 6. Test results for Granger non-causality

Variable AY Al AG AX AM ALAY 24.68* 18.30* 15.67* 17.45* 11.21*

Al 18.45* 2.01 13.87* 14.11* 3.17

AG 16.55* 15.67* 2.05 13.81* 11.77*

AX 21.36* 13.07* 1.19 2.01 2.66

AM 16.47* 10.33* 1.56 0.88 -- 1.16

AL 12.22* 15.09* 13.61* 1.30 2.47

NOTES. The flow of causality n the table is from the variables n the first column to the variables nthe first row. A star * indicates that the null hypothesis of non-causality s rejected at the 5%significance evel.


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Table 6 reports he results of testing for Granger non-causality between the 6 variablesin the system. The flow of causality n the table is from the variables n the first column to

the variables in the first row. In this setting, table 6 identifies all the possible channelsthrough which government pending affects economic growth. The main conclusions fromtable 6 can be summarized s follows:

1. There are four possible channels through which government spending can affectthe growth process in Tunisia. From table 6, we can see that government pendingaffects economic growth directly through the growth equation and indirectlythrough its impact on investment, mports, and labor. Since government pending

Granger- auses investment, imports and labor, which in turn Granger-causeeconomic growth, then government spending has an indirect causal impact oneconomic growth through its effects on these variables. The advantage of

identifying these indirect causal links is the result of modeling growth dynamicswithin a system of equation rather han a single growth equation.

2. Looking at the results of tables 5 and 6 together, we can identify three causalchannels through which an expanding government size has an accelerating effecton economic growth in Tunisia. These are promotion of economic growth,imports, and labor. This result seems to be consistent with the Tunisian reality.The Tunisian government's ntervention n economic activity has for long playeda critical role in promoting the country's economic growth and development. Inparticular, he government was heavily involved in promoting social policies andeconomic infrastructure. Government spending on social policies played a

critical role in promoting the standard of living. The provision of free basichealth care, education, and training were necessary for the development of the

country's human capital. Given the relatively low contribution of the privatesector, the government remains the main importer of technology. In addition, the

provision of an adequate nfrastructure long with political stability has attracted

foreign direct investment n many key sectors of the economy.

However, government pending s having an indirect negativeeffect on economic

growth and that through ts negative impact on private investment. This could be

the result of the heavy involvement of the Tunisian government n many productivesectors of the economy, which crowded-out the private sector from profitableopportunities such as in banking, agriculture, energy, telecommunications, and

transport.3. As to the relationship etween growth, nvestment and trade, our time-series results

do not support the results of Levine and Renelt (1992). In our case, trade andinvestment are both significant in the growth equation. In addition both tradevariables are significant in the investment equation. Hence, the relationship

between trade and growth in the case of Tunisia seems to be based on both theenhanced resource accumulation as well as on the improved allocation ofresources.


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32 Khalifa Ghali

4. Finally, regarding the relationship between economic growth and labor, ourresults suggest that labor is an important nput into production in the case ofTunisia. Labor is highly significant n both the long-run relationship as well as inthe growth equation. This result contrasts with the results of the panel-data tudiesinvestigating growth convergence. In reference to the study by Islam (1995) as atypical example of the available panel data studies, one of his main conclusions isthat there s no room for labor accumulation n a growth equation.3 This isbecause labor appears to be always insignificant after controlling for the fixedeffects. However, our result seems to be rather supportive of the arguments

advanced by Maddala and Wu (2000) against the assumption that the theoryimplicit in Islam's model applies to all countries.

In light of these results, the recommendation by the IMF and the World Bank thatTunisia should reduce the size of its government n order to promote economic growth doesnot seem to be the appropriate ne.4 An appropriate olicy recommendation would be for theTunisian government to enhance its involvement in those activities that shape the generalproductive efficiency of the economy and to withdraw rom those activities hat are hamful toprivate investment and economic growth. In particular, Tunisia can build on its relativestrengths n terms of the young profile of its population, ts stability, prosperity, nd its closerintegration with Europe to further acilitate he country's absorption of new technologies andnew ways of doing business. The government should, however, reorient its developmentstrategy rom one that heavily depends on state-owned monopolies to one that encourages agreater participation of the private sector in most aspects of economic activities. Theprivatization nd deregulation f public enterprises long with the enforcement f regulationsencouraging profitable opportunities are the sorts of measures that would stimulate privateinvestment and allow the economy compete n a global environment.

BUDGET FINANCING AND ECONOMIC GROWTH

We have so far focused on assessing the impact of changes in government ize on thegrowth performance n Tunisia. In this respect, we clearly identified the channels throughwhich government activities can promote economic growth. However, given the burden of thegovemment budget constraint as being a binding factor n formulating overnment behavior,a required additional nformation s for policymakers o know whether his outcome would bethe same irrespective of the method used to finance government expenditures. For this, wenow turn to investigating the impact of the different sources of financing the governmentbudget on economic growth.

Given the flow budget constraint f the govemment, G = T + D, we now decompose totalgovernment expenditures, G, in our VEC model into two components; the ratio of tax

revenues o GDP (T) and the ratio of govemment debt to GDP (D). With this, we now have a7-variable ystem. Using the same methodology, we first tested for cointegration etween the


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variables and then estimated a VEC model in order to assess the separate effects of taxrevenues and government debt on economic growth.

Table 7 reports he growth equation rom the estimated VEC model and table 8 reportsthe results of testing for Granger-causality etween economic growth, tax revenues, andgovernment debt. As shown in these tables, while tax-revenues nd debt both Granger-causeeconomic growth, they have opposite sign effects in the growth equation. Both coefficientsof the debt ratio are negative and statistically ignificant. In contrast, he coefficients of thetax ratio are both positive but only the first coefficient s statistically ignificant.

Table 7. Effects of Debt and Tax Revenues on Economic Growth

Variable AYt t-statisticIntercept 1.238 (2.011)vt, -0.346 (4.706)AYt- -0.329 (-1.206)Yt-2 0.436 (3.078)Alt-i -0.038 (-0.524)AIt-2 0.326 (3.886)

ADt- -0.205 (-3.541)ADt-, -0.134 (-2.007)ATt-I 0.688 (2.364)ATt-2 0.256 (0.129)AXt-i -0.037 (-0.155)AXt-2 0.016 (3.001)AMt- 0.103 (1.272)AMt-2 0.228 (2.344)ALt- -0. 103 (- 1.105)Al-t2 0.306 (2.776)R 0.86a 0.015TSC(10) 5.32N(2) 1.778RESET(1) 0.452

NOTES: T-ratios are in parentheses. TSC(10) is a test for up to the tenth-order erial correlation, N(2)

is the Jarque and Bera test for normality, and RESET(1) s a test for parameter nstability.


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34 Khalifa Ghali

Table 8. Testing The Causal Impact of Tax Revenues and Debt on Economic Growth

Null Hypothesis Test Statistic x2(3)

Debt does not Granger-cause economic 19.45 7.81growth

Tax revenues do not Granger-cause 14.13 7.81economic growth

In light of these results, it seems that the method of financing he government budget isnot inconsequential on the growth performance n the case of Tunisia. The govemmentreliance on debt seems to induce adverse effects on economic growth, while tax-financedgovernment expenditures seem to have an accelerating effect on growth. With this, thepositive effects of government pending on economic growth that we found previously (table5) should be the outcome of tax-revenue ffects offsetting he negative effects of government-debt on growth. Hence, an additional useful policy recommendation s for the Tunisian iscalauthorities o adopt a strategy of fiancing public outlays by relying more on tax-revenuesthan on debt-accumulation.

CONCLUSION

Following the debt crisis, Tunisia was among many developing countries hat adopted heIMF debt-stabilization rograms without having any indication on how government pendinginteracts with macroeconomic variables in affecting its growth process. In addition, theexisting literature did not provide a consensus judgment on which a policy can be safelyformulated. Consequently, his paper attempted o empirically nvestigate he causal channels

through which government pending can affect economic growth n Tunisia and the extent towhich govemment activities can have an accelerating or a depressing effect on the growthperformance n this.country. An additional ssue that we investigate, but which was neglectedin the relevant empirical iterature, s whether he impact of government pending on growthis independent f the source of financing he government budget.

In an attempt o improve upon the conventional procedure of estimating a single growthequation, he paper developed a vector error-correction VEC) model that allows to identifynot only the direct effects of government pending on growth but also the indirectly nducedeffects resulting rom the interaction f government pending with other macro-variables uchas investment, trade and labor. With this, we were able to identify- hree channels through

which govenmment pending may have an accelerating effect on economic growth and onechannel through which govemment spending may have a depressing effect on economicgrowth.


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Government Spending 35

The main conclusions useful for the conduct of economic policy in Tunisia are thatgovernment pending aimed at shaping he general efficiency of the economy and promotingthe productivity f labor and imports have accelerating ffects on economic growth. Whereasgovernment nvolvement n the productive ectors of the economy has a crowding-out ffecton private nvestment and, hence, depresses economic growth. In addition, given the adverseeffects of debt-accumulation on growth performance, it is recommended that fiscalauthorities n Tunisia adopt a strategy of financing public activities by relying more on tax-revenues han on government debt.

ENDNOTES

IFor detailed background descriptions of the Tunisian economy, interested readers may referto World Bank (1996).2Several studies of fiscal policy have excluded trade indicators from their analysis. Theseinclude Landau (1983), Ram (1986), Grier and Tullock (1989), and Barro (1990, 1991).Other studies have ignored fiscal policy when studying trade policy. These include Feder(1983) and Edwards (1989). Studies that included both exports and imports includeKormendi and Meguire (1985), Romer (1990a), and Levine and Renelt (1991, 1992).3See also Knight et al. (1993), Easterly et al. (1993), and Cashin and Loayza (1995).4The World Bank (1996) Progress Report referred o the results of cross-country growthstudies and recommended hat Tunisia should reduce the size of its govermment.

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govt spending, budget financing, and eco growth

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