investigating stock price dynamics in an oil-dependent economy: the case of kuwait

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Economic Analysis & Policy VoL32 No.2, September 2002 141

200303786

INVESTIGATING STOCK PRICE DYNAMICS IN ANOIL·DEPENDENT ECONOMY: THE CASE OF KUWAIT

Ali Arifa'Economics Department

College of Business AdministrationKuwait University

PO Box 5486 Safar-Code 13055, Kuwait.

Khalifa H. GhaliEconomics Department

College of Business AdministrationKuwait University

PO Box 5486 Safat-Code 13055, Kuwait.

Imed LimamThe Arab Planning Institute

PO Box 5834 Safat-Code 13059, Kuwait.

The recent literature on stock markets has used modem time series techniquessuch as cointegration and causality to identify macroeconomic variables thatcause stock index movements. But this type of investigation has to a large extentremained confmed to markets belonging to well developed and diversifiedeconomies. Motivated by the lack of set-ups involving stock markets fromeconomies with different profiles, this paper concentrates on the Kuwaiti stockmarket whose unique features as an oil-dependent economy render its investigationa useful exercise. Based on mutivariate time-series techniques and using monthlydata spanning the period September 1992 to December 1998, the investigationreveals three important factors that are believed to have long-term equilibriumeffects on stock market prices in Kuwait. Oil prices, U.S. interest rates and realestate prices are found to form a cointegrating relationship with stock prices. Theresults in this paper indicate clearly a sharp contrast in terms of stock marketdynamics between an oil-dependent economy like Kuwait's and those of highlydiversified economies. It is argued that the reported results are neverthelesslogical in light of the unique features of the oil-dependent Kuwaiti economy.

1. INTRODUCTION

The proposition that movements in stock prices are driven by a number of keyeconomic macroeconomic variables has for a long time been widely accepted in theliterature about the stock market. However, more sophisticated empirical elaborations

The authors are grateful to two anonymous referees for a most insightful review of anearlier version of this paper. The authors are alone responsible for any remaining errors.

142 Economic Analysis & Policy Vol.32 No.2. September 2002

aiming specifically at adequately capturing the dynamic effects of·such variableson stock markets performance is a relatively more recent development. The currentsurge in empirical work in this area is due in part to the devolopment ofnonstationarytime series techniques, especially cointegration analysis, which has made itpossible to adequately explore stock market dynamics and interactions with keymacroeconomic variables. In particular, the work by Granger (1986) has opened awindow to the prospects of using cointegration analysis in detecting the presenceof any long-term equilibrium relation of stock prices to pertinent variables. On thisground, it would be possible to design error correction models allowing for thetracking of long-term dynamics of stock prices. A survey of the literature revealsclearly that a number of studies have indeed adopted this approach. Mukherjee andNaka (1995) for example used a vector error correction model (VECM) to explorethe dynamic relations ofa number ofkey variables to the stock market in the contextof the highly developed Japanese economy. Likewise, Maysami and Koh (2000)adopted a similar methodology in investigating long-term relations of a number ofvariables and the stock index of one of the Asian tigers, Singapore. Also, in anattempt to investigate integration of three European stock markets (Frankfurt,London, and Paris) along with the New York market, Dickinson (2000) adopted anapproach that included the use of cointegration analysis to uncover the mostsignificant macroeconomic determinants of stock price movements.

Overall there is a significant literature using modern time series techniquesestablishing credible evidence that stock prices are affected by a number of keymacroeconomic variables. However, it is quite clear that the type ofempirical workoutlined above has to a large extent been confined in the relevant literature to setups involving wealthy economies with highly diversified productive sectors.Similar research about stock markets in economies that do not fit this profile isalmost non-existent. The purpose of this paper is to widen the scope of this courseof research by extending this type of analysis to an economy with a different profilethan that commonly investigated in the current literature. It is believed that a greatdeal of insights could be learned from such investigations. They would at leastallow for establishing bases for meaningful comparisons in terms of the disparitiesin the nature of economic forces and their impacts on stock markets acrosseconomies with different characteristics. In addition, they would inevitably propelan upsurge of improved forecasting frameworks potentially aHawing policymakers as well as stock market participants in the concerned economies to betterdetect what macroeconomic variables ought to be considered as "barometers" farfuture returns.

With this in mind, this paperpropases to explore some hypothesized relationshipsbetween stock prices in Kuwait and several variables. Clearly, the Kuwaiti stockmarket belongs to an economy whose general features are not in line with thestandard profile encountered in recent relevant literature employing cointegrationanalysis. This is to say that many of the variables used in previous studies wouldnot be suitable in this particular case. For example, standard variables such as theindustrial production which is commonly used as a proxy for real economic activitywould have little relevance in the determination of stock prices in Kuwait. The

Economic Analysis & Policy Vo1.32 No.2, September 2002 143

reality is that, although the country is boosting high per capita income levels, theeconomy is far from being diversified. In fact, the economy has traditionally beenalmost totally dependent on oil exports. The relative abundance of wealth alongwith the dominance of only one productive sector are interesting and quiteuncommon features that render the investigation of the dynamics of the Kuwaitistock prices a very insightful exercise. The large dependence of the productiveeconomy on the performance of the oil sector, and with the dearth of significantnon-oil productive sectors whose development could well be inhibited by thedominance of the oil sector, Kuwaitis might find it somehow difficult to encounterprofitable investment opportunities within the country. I So investors tum into rentseeking and speculative activities. Accordingly, it is no coincidence that thecommon domestic business activities among Kuwaitis evolve around real estate,trade and the stock market. Naturally, there is also the other significant investmentalternative represented by the overseas channel.

From this perspective, this paper proposes to analyze the dynamics of theKuwaiti stock market prices using a model whose specification reflects thoseunique features to the Kuwaiti economy. That is, we explore the dynamic relationsbetween stock prices and the main economic variables that are believed to impingeon the working of this market notably, oil prices and variables reflecting the rentseeking and speculative temperament of Kuwaiti investors. The proposedmethodology relies mainly on a VECM designed to identify those factors that havelong-run equilibrium effects on the Kuwaiti stock market. Monthly data coveringthe period 1992:9 - 1998:12 are used in this investigation.

The remainder of this paper is organized as follows. The second section of thepaper presents a short description of the Kuwaiti stock market and offers detailsabout its unique features. It also provides brief intuitive depictions of the variablesthat are believed to have bearings on stock prices and the nature of their impacts.The third section describes the econometric methodology in use in this paper. Theapplication of the proposed methodology and the results are presented in the fourthsection. The final section is devoted to some concluding remarks.

2. THE STOCK MARKET OF KUWAIT (KSE): DESCRIPTIVEBACKGROUND AND HYPOTHESIZED DYNAMICS

The KSE is one of the most significant markets in the Arab world in terms ofturnover and market capitalization. It is the most ·active among arab markets interms of monthly turnover. It was officially established in 1976, although over-thecounter share trading existed well before that. Looking at the developments of thelast ten years, and starting with the aftermath of the 1991 Gulf war, the volume oftrade and turnover rate were substantially lower than the pre-invasion period. Inorder to reactivate the market, the government then took several steps mainly,

The development of non-oil sectors could be inhibited by the dominance of the oil sectorin accordance with the so-called "Dutch Disea,e" syndrome. For detailed infonnation onthe "Dutch Disease" pehnomenon and its application to developing countries, refer toRoemer (1985).

144 Economic Analysis & Policy Vo1.32 No.2, September 2002

issuing public debt instruments and selling its shares in domestic companies. Since1994, the market has picked up under favorable conditions notably the establishmentof two investment funds, one to acquire assets in public companies targeted forprivatization and the other for real estate. The upward trend was consolidated upuntil 1997. By the end of 1998, the market was negatively affected by severalfactors notably the drop in oil prices and the ban by the monetary authorities onmargin trading.

Like the rest of the oil-producing Gulf states, the impetus for the creation of astock market in Kuwait originated from domestic investors being open to investmentopportunities as the oil industry was developing. It is well known that the oil boom,particularly since the 1970' s, has allowed the government of Kuwait to accumulatesubtantial financial wealth that has been passed on to different segments ofpopulation in the fonn of wages, subsidies, transfers, and a large number of otherl>enefits. As a result, Kuwait has currently one of the highest per capita incomelevels in the world. However, and despite many efforts to diversify. the Kuwaitieconomy remains overly dependent on oil. Around 80 per cent of budget revenuesare due to oil. Another important feature of the Kuwaiti economy is the relativeweakness of the private sector. In fact, however small it may be, the performanceof the private sector in the productive economy is undoubtedly over-estimated asit has traditionally benefited from government intervention in different forms suchas provisions of subsidized loans and input prices, equity injections, bail-outs, andpreferences in government procurements. This combination of limited business,diversity and excess liquidity has favored the surge of domestic investmentactivities mainly in real estate, trade and the stock market.

In this economic climate, and with the abundance of liquidity, it is only naturalthat the KSE would see much activity. In fact, given the lack of alternativeinvestment opportunities, even the lending by commercial banks is finding its wayto the KSE through margin trading and the like. It is these characteristics ofinvestment in Kuwait which are perhaps one of the principal causes for the manyspeculative bubble-cases recorded throughout the history of the KSE. The mostfamous resulted in what is referred to as the "Souk AI-Manakh" crash of 1982,caused by lax margins and forward trading regulations.' In this instance, thegovernment, whom many people blame for several unwarrantable stock marketspeculator bail-outs, has once again intervened to bail-out the system through whatis known as the "Difficult Debt Senlement Program".

The fact that there are so many factors that are atypical in the Kuwaiti case, asbriefly outlined above, renders the determination of stock prices in the KSEsignificantly different from those in other countries. Many of the standardmacroeconomic variables reflecting the well-being of the economy, (such asinflation, exports, and industrial exports), that are commonly hypothesized in therecent relevant time series literature to relate to the stock market have probably linlebearing on stock prices in Kuwait. Therefore, attempting to test for the existence

Loughani (2000, p.64) reports that the vaJue of the post-dated cheques used in forwardtrading registered after the crash was around $ 93 billion.


of a long-run stable relationship linking stock prices in the KSE to changes inrelevant variables, as well as exploring the nature of the causa] patterns amongthose variables and their potential causal effects on stock prices. would require aspecification which on the surface may not look familiar to people with financialtheory background. On the other hand, forcing a more "standard" specification tothe Kuwait case would in our view be unfitting.

On this ground, we hypothesize in this paper a relationship between the KSEprices and several variables that we view to be most pertinent to the Kuwaiti setting.Obviously some of them will be discarded upon completion of relevant time seriesanalyses. The first variable which is believed to impinge on the working ofthe stockprices in the KSE is the price of oil. This choice is easily justifiable on the groundthat the economy is simply oil-driven with the profitability of the business sectordetennined to a large extent by the perfonnance of oil in energy markets. It can alsobe viewed as a variable measuring the income or wealth effects.

Other variables include the net domestic credit in the economy. The rationalefor it is to have a factor reflecting the liquidity effect on the KSE stock prices. Thedomestic lending interest rate is another variable of interest because of its perceivedeffect, among other things, on future dividends. The T-bill rate in the United Statescomes into the specification as a proxy for long-term interest rates. The exchangerate is also included in the analysis. It is one of the more "standard" variablesadopted in this type of investigations as it affects the levels ofcash flows in and outof the country. It is in this case a variable affecting the arbitrage between domesticand foreign investment opportunities. Finally, to account for the real estate sectorwhich competes with the stock market for investment opportunities, we use the realestate price as a signal of the profitability level in the sector.

3, THE ECONOMETRIC METHODOLOGY

To investigate the dynamic interaction between stock prices and the variablesoutlined above, this section proposes a framework based on multivariatenonstationary time series techniques. In what follows, briefdescriptions ofthe toolsof analysis in use are presented.

3,1 Testing for Cointegration

Consider the vector autoregressive (VAR) model

MI = <1>1 M,_I + <1>, M,_, + ... + <1>, MI _, + ~ + 11" 1=1, ... , T, (1)

(2)

whereM, is a k x I vector containing the relevant variables in our analysis. Supposethat these variables are 1(0) after applying the difference filter once. If we exploitthe idea that there may exist co-movements of these variables and possibilities thatthey will trend together towards a long-run equilibrium state, then by the Grangerrepresentation theorem we may posit the following testing relationships thatconstitute a VECM Model

I1Mt ;;; f, I1Mt _ 1 + f 2 ~t-'2. + ... + r k _ 1~t-k+ 1 +flMl _, + ~+ 111. t = I,... ,T

146 Economic Analysis & Policy Vol.32 No.2, September 2002

where ~t is now the vector of the first differences of the variables, the r's areestimable parameters, ~ is a difference operator, T\t is a vector of impulses whichrepresent the unanticipated movements in M" with '11 - niid(O, Il) and is the longrun parameter matrix. With r cointegrating vectors (I ::; r::; k), Il has rank r and canbe decomposed as = Il = CL~', with CL and ~ both k x r matrices. ~ are the parametersin the cointegrating relationships and ex. are the adjustment coefficients whichmeasure the strength of the cointegrating vectors in the VECM. The Johansen(1988, 1992) andJohansenandJuselius (1990) multivariate cointegration techniquesallow us to estimate the long-run or cointegrating relationships between the nonstationary variables using a maximum likelihood procedure which tests for thecointegrating rank r and estimates the parameters ~ of these cointegratingrelationships. As proved by Johansen (1991, 1992), the interceptterms in the modelshould be associated with the existence of a deterministic linear time trend in thedata. If, however, the data do not contain a time trend, the model should include arestricted intercept term associated with the cointegrating vector.

3.2 Testing for Granger-Causality

As Granger (1986, 1988) pointed out, if two variables are cointegrated thenGranger-causality must exist in at least one direction. This result is a consequenceof the relationships described by the VECM. Since the variables share commontrends, then any variable in ~Mt, or a combination ofany ofthem must be Grangercaused by lagged values of the error-correction terms which themselves arefunctions of the lagged values of the level variables. Given this, the temporalGranger-causality between the variables can be investigated using a joint F-test ora Wald X2 test applied to the coefficients of each explanatory variable and thecoefficient of the cointegrating vector in the VECM.

3.3 Variance Decomposition

In order to have an idea about the relative importance of the variables in predictingthe future values of stock prices, we decompose the forecast error variance of stockprices into components accounted for by innovations in the different variables ofthe system.

4. EMPIRICAL RESULTS

In this section we apply the methodology described above to investigate the longrun and short-run dynamics of stock prices in Kuwait and their intertemporalinteraction with relevant economic variables that are believed to impinge on theworking of the stock prices in Kuwait. As described earlier, the proposed variablesin the analysis are: the net domestic credit distributed in the economy, the domesticlending interest rate, the T-bill rates in the United States, the exchange rate, the priceof oil, the real estate price, and naturally the index of stock prices.

The main focus of the analysis is on: (1') testing for the existence of a long-runstable relationship that ties the long-run movement of stock prices in Kuwait tochanges in the above variables, (ii) investigating the nature of the causal patternsamong the variables included in the model with particular attention given to


identifying the causal effects that these variables may have on stock prices inKuwait, and (iii) assessing the separate effects of the different variables on futurechanges in stock prices.

4.1 Data and Variable Definitions

Data used in the analysis are monthly and cover the period 1992:9 - 1998:12. Thechoice of the period was determined by the reopening ofKSE in September of 1992after two years of closure due to the invasion of Kuwait. The variables are definedas follows:

KSEP: value-weighted stock price indexPHOU: general price index for housingPOlL: crude oil priceTBUS: treasury bill rates in the U.S.OCR: net domestic credit distributed in the economy by the banking sectorEXR: official exchange rate of the Kuwaiti Dinar against the U.S. dollarLEN: domestic lending rate.KSEP is a value-weighted stock price index produced by a private consulting

company, AI-Shal, based in Kuwait; and PHOU is a general index for housingpublished by the Central Statistical Office of the Minstry of Planning in Kuwait.Data for the rest of the variables come from the International Monetary Fund'sInternational Financial Statistics.

All variables are transformed into their natural logarithm so that coefficientsof the cointegrating relationships could be interpreted as long-term elasticities.

The following plots show the time profile of selected variables over the sample

period.

KSEP: Stock Price Index in Kuwait5.4 .,.- --,

5.2

5.0

4.8

4.6_~ '--

4.4

9897969593

4.2 -hTrTTTTrrn"",'TTT'ITTTrrn""'TTTTTTrrn""''TTTTTTrrn'''''TTTTTTrrn'''''TTT-rrn1

94


PHOU: General Price Index for Housing

98

98

98

97

97

97

96

96

96

95

95

95

POlL: Oil Prices

TBUS: T-bills Rate in the U.S.

94

94

94

2.20

2.15

2.10

2.05

2.00

1.95

93

3.2

3.0

2.8

2.6

2.4

2.2

93

1.8

1.6

1.4

1.2

1.0

93

Economic Analysis & Policy Vol.32 No.2, September 2002 149

KSEP: Stock Price Index in KuwaitPHOU: General Price Index for HousingPOlL: Oil PricesTBUS: T-bills Rate in the U.S.The time profiles for the four variables show some similiraties in their trends,

possibily indicating cointegration, which is to be investigated later on.

4,2 Test Results for Unit Roots

As a preliminary data analysis, the different series are first checked for stationaritybecause, if the data are not stationary, standard econometric techniques can lead tomisleading results. The tests used to investigate the existence of unit roots in thelevel variables as well as in their first differences are the augmented Dickey-Fuller(ADF), Dickey and Fuller 1979, and the Phillips-Perron (P-P), Phillips and Perron1988, tests, These tests are performed on the level variables as well as on their firstdifferences. The null hypothesis tested is that the variable under investigation hasa unit root, against the alternative that it does not. ]n each case the lag-length ischosen by minimizing the final prediction error (FPE) due to Akaike (1969). Wealso tested for the existence ofup to the tenth order serial correlation in the residualsof each regression using the Ljung-Box Qstatistics. The results of these tests, notreported here, indicate absence of serial correlation.

The results ofthe unit roottests are reported in Table I. The null hypothesis thatthe level variables contain unit roots cannot be rejected by both tests. However,after differencing the data once, both tests reject the null hypothesis. Since the dataappear to be stationary in first differences, no further tests are performed,

TABLE 1

TEST RESULTS FOR UNIT ROOTS

Variable

KSEPPHOUPOlLTBUSt.KSEP&HOUM'OILt>TBUS5% Critical Values

ADF

-1.287-0.210-0.649-1.533-4.813-7.148-5.383-4.915-1.945

POP

-1.911-0.327-0.743-1.765-8.829

-16.261-6.765-7.384-1.944

4,3 Test Results for Cointegration

Before applying the Johansen procedure to estimate the parameters of thecointegrating relationships and the associated adjustment coefficients, r3 and a., itis necessary to detennine the lag length k to be included in the VAR equation (1).


This lag length should be high enough to ensure that the errors are approximatelywhite noise, but small enough to allow estimation. Since the Johansen procedureis sensitive to the choice of the lag length, we based our decision on the Akaike'sFinal Prediction Error (FPE) criterion. A ftrst round of tests was performed usingall the variables described above. However, we failed to find cointegratingrelationships in which KSEP, or the remaining variables, contributed significantly.Upon testing different subsets ofthe original variables, the subset including KSEP,PHOU, POlL and TBUS was chosen. Table 2 reports the diagnostic tests fornormality and serial correlation in the residuals for each of the four equations inVAR using a lag of order six (k=6). The results in this table indicate that this laglength left the residuals approximately independently identically normally distributed(niit!) for all the equations.

TABLE 2

RESIDUAL DIAGNOSTIC TESTS FOR THE VAR EQUATIONS, K=6

Variable TSC(10j N(2)

KSEP 10.483 2.514

PHOU 12.065 3.899

POlL 8.705 2.082

TBUS 13.414 3.716

Notes: TSC( 10) is a test for up to the tenth order serial correlation,TSC(IO) = T(L;'), i = I, ...• 10 - X'(10).N(2) is the Jacque and Bera (1980) test for normality which is asymptotically distributed 2(2).

The results of testing for the number of cointegrating vectors are reported inTable 3, which presents both the maximum eigenvalue ("-m,,) and the tracestatistics. the 10 per cent critical values as well as the corresponding A. values. Ascan be noticed both the "-m" and the trace tests suggest the existence of a uniquecointegrating vector.

TABLE 3

TESTING THE RANK OF nTrace ImaxHO HI Slat. 90% HO HI Stat. 90% A

critical value critical value

R=O r~l 48.43 43.84 r=O r= I 33.77 17.15 0.383

r$1 r~2 14.66 26.70 r$1 r = 2 7.68 13.39 0.104

r$2 r~3 6.99 13.31 r$2 r= 3 6.06 10.60 0.083

r$3 r=4 0.92 2.71 r$3 r=4 0.92 2.71 0.013

The estimates of ~ and (i are presented in Table 4. From the a vector one canquickly notice that the coefficients on the cointegrating vector in the PHOU andPOlL equations of the VECM are both insigniftcant. Testing thai these coefficienlsare equal to zero is actually a test that housing prices and oil prices are weakly

Economic Analysis & Policy Vo1.32 No.2. September 2002 151

exogenous, which enables the model to be re-specified as a two equation systemconditional on these variables.

TABLE 4

THE a AND pVECTORS

Variable a.

KSEP

PHOU

POlL

TBUS

Notes: T-ratios are in parentheses.

-6.483(-5.199)-1.292

(-6.558)0.278

(1.904)

-0.120(-5.662)

0.000(0.095)-0.031

(-0.588)-0.069

(-2.390)

Testing weak exogeneity of PHOU and POlL yields a likelihood ratio test =0.30. which compared to the 5 per cent critical value X,(2) = 5.99, enables us toeasily accept the null hypothesis. Estimates of a and p and their t-ratios afterimposing the weak. exogeneity restriction on these two variables are presented inTable 5. .

TABLES

THE IX AND ~ VECTORS FROM THE RESTRICTED MODEL

Variable

KSEP

PHOU

POlL

TBUS

Notes: T-ratios are in parentheses.

-6.950(-5.845)-1.269

(-6.750)0.311

(2.237)

a.

-0.123(-5.490)

0.073(-2.397)

To assess the model after imposing the weak exogeneity of PHOU and POlL,we check the eigenvalues of the companion matrix to make sure that none of theunrestricted roots have come close to unity as a result of imposing this restriction.The eigenvalues of the companion matrix, not reported here, confirm that therestricted system has three unit roots with the remaining roots being less than one.Given these results we can say that the model is now completely identified. The four


variables in the system have a unique and stable long-run relationship thatinfluences their behavior. In particular, the result that stock prices cointegrate withthe remaining variables in the model means that its movement towards a long-runequilibrium state defined by the cointegrating equation characterizes its long-runbehavior. In the short-run, any deviation of the stock prices from this long-runequilibrium will feed back on their changes in order to force their movementtowards the long-run equilibrium state. The coefficient of the cointegrating vectorin the stock prices equation (ex= -0.123) is the adjustment coefficient ofstock pricesand measures their speed of adjustment to the long-run equilibrium state. Thismeans that, in each short-term period, stock prices adjust by about 12.3 per cent ofthe imbalance that exists at time (t-I) between its current value and its long-runequilibrium value given by the long-run equilibrium relationship.

From the long-run relationship between the variables given by the cointegratingequation,

(KSEP), = 6.950(PHOU), + 1.269(POIL), - O.3II(TBUS)" (3)

the results reveal that stock prices contribute to the cointegrating relationship inwhich PHOU, POlL and TBUS are significant. In the long-run, both housing andoil prices have positive effects on stock prices. U.S. T-bills rates, however, have anegative effect on stock prices. The most significant effect on stock prices is thatof POlL. The price of oil affects profitability not only of the business activitiesdirectly linked to oil, but also other businesses through its impact on governmentand private sector's expenditures.

The real estate sector is looked at in Kuwait as an alternative investmentopportunity to the stock market. Therefore, at prima facie, the real estate and stockmarket prices are expected to move in different directions. However, "the businessgroup phenomenon" in Kuwait', whereby a group of wealthy investors have theupper hand over all business activities in the country, is such that the prices in thetwo markets do not necessarily move in opposite directions. Furthermore, thepositive link between the real estate and stock prices could be explained by the factthat more than 50 per cent of the domestic companies listed in KSE are eithercommercial banks, financial institutions and other companies involved, throughtheir respective activities and to different degrees, in the real estate sector. Hence,a higher profitability in the real estate sector affects positively profitability ofthesecompanies and subsequently their stock prices.

The negative link between stock prices and the interest rates is very evidentfrom the perspective of stock valuation models where these rates are considered asdiscount factors. The U.S. rates represent also the opportunity cost of holdingcapital domestically.

The results show a clear contrast between'the dynamics in the Kuwaiti Stockmarket and those of developed and emerging highly diversified economies. Forinstance, the domestic credit variable depicting the possible liquidity effect on the

See Loughani, op. cit.


(4)

stock market does not contribute significantly to the cointegrating relationship inthe case of Kuwait. In the case of developed economies like the U.S., money orcredit variables are believed to affect stock prices through direct injection ofliquidity into the market and by influencing corporate earnings. Fama (1981)argues that ihe significant relationship often found between money supply andstock prices in developed economies is only statistical and indirect and due to thelink between money variables and real activity. This relationship might be concealinga more direct relationship between stock prices and real activity. The insignificanceof the monetary variable, DCR, in the case of Kuwait may be due to the fact that oilprice is a better proxy for real activity than ihe fonner. The statistical significanceof oil price in the cointegrating relationship in this case lends support to thisargument.

The exchange rate variable is also found to be insignificant in the case ofKuwait. Unlike the cases of well developed or emerging diversified economies, theexchange rate in Kuwait is not believed to have a major effect on the competitivenessofexports dominated by the public sector and confined almost exc!usively to oil andoil-related products' In addition, demand for imports in the oil-rich Arabian Gulfcountries like Kuwait tends to be price-inelastic. Domestic demand is believed tobe the main detenninant of profitability for importing companies. These factorscoupled wiih ihe limited weight, in tenns of traded shares, of listed companiesdirectly involved in international trade, explain to a large extent why the exchangerate is not possibly an important determinant of stock price movements in Kuwait.Even from the perspective of arbitrage between domestic and overseas investmentopportunities, the exchange rate does not seem to affect stock prices. This may belinked to the nature of monetary policy followed in Kuwait which is traditionallycentered around maintaining a wedge between domestic and foreign interest ratesin order to stabilize exchange rate and stem shifts from domestic to foreign assets.It is this same policy that could possibly explain the reasons why domestic interestrates do not contribute in any significant way to the long-term behavior of stockprices. Given that domestic interest rates track world interest rates, the latter werefound in the case of Kuwait to be more significant in affecting the discount factorand the arbitrage between domestic and foreign assets.

4.4 Test Results for Granger-Causality

The unit root and cointegration test results presented above imply that the variableshave a vector error-correction representation of the form

5 5<.\(KSEP), 80 + I 8,., MKSEP) ,., + I 8,., <.\(PHOU),., +

s=1 ~l

5 5

I 83., <.\(POIL),., + I 84., <.\(THUS) ,., + U,V,·I + rl"

8"'1 8=1

Maysami and Koh (2000) found. for instance, thaI exchange rates affect significantlystock prices in the case of Singapore.


5 5

~(PHOUh = <1>0 + L <1>,., ~(KSEP) 1-' + L <1>2., ~(PHOU)I_' +s=1 s=l

5 5

L <1>3" ~(POIL),_, + L <1>4., ~(BUS) 1-' + £2.1s:l s=l

5 5

~(POIL), = 00 + L 01., ~(KSEP) 1-' + L 02., !>(PHOU) 1_' +5=1 s=!

5 5

L lh., ~(POIL)I_' + L 04., ~(BUS) 1-' + £3.1s:=l s=!

5 5

~(TBUS) I= 80 + L 61.' ~(KSEP) ... + L 62.' ~(PHOU),_, +s=l s=1

5 5

L 63., ~(POIL)I_' + L 64.' ~(BUS) 1-' + a4vI_' + £4.1i=l 8""1

(5)

(6)

(7)

where v t is the cointegrating vector and where 0.1 and CX4 are the adjustmentcoefficients of stock prices and U.S. T-bills rates. respectively.

Although the ex.. coefficient is statistically significant, we find no reason toargue that the T-bill rate in the USA is endogenous to the system. For this reason,the T-bill rate variable will be treated as weakly exogenous.

Now given that oil prices, housing prices, and T-bill rates are weakly exogenous,the system in (4) - (7) Can be reformulated into a one equation error-correctionmodel containing only equation (4), which we will use 10 test for Granger noncausality and variance decomposition.

Given that the analysis focuses on the short-run dynamics of stock prices inKuwait and how their short-run behavior is affected by the other variables in thesystem. we focus OUf attention on testing for the existence of Granger causality inonly one direction, from oil prices, housing prices, and U.S. T-bills rates to stockprices. The existence of such causality means that past information on oil prices,housing prices, and U.S. T-bills rates help predict future values of stock prices inKuwait. Consequently. we test the following hypotheses,

HOi: 6 i1 =0, 6", =0,. ", aiS =0 and al~i =0, (8)

where aij are the coefficients of housing prices, oil prices, and U.S. T-bills rates inthe stock prices equation (4) and al is the adjustment coefficient of stock prices.

However, this test involves not only a non-linear restriction which makes itcomplicated to compute. but also has been shown to have size and power problemsdue to its dependence on the pre-testing for cointegration (Zapata and Rambaldi,1997)_ A much simpler and accurate test was proposed independently by Doladoand Lutkepohl (1996) and Toda and Yamamoto (1995) and is known as the

Economic Analysis & Policy Vol.32 No.2, September 2002 155

"augmented VAR" test procedure. As shown by Zapata and Rambaldi (1997) andGiles and Mirza (1999), the augmented VAR approach is very simple to computeand is independent of the cointegration properties of the data.

Using this augmented VAR approach, the testing procedure for Granger noncausality is as follows:I. Given that our VAR in levels has 6 lags and the highest order of integration in the

data is one, we first estimate a VAR in levels with 7 lags. then2. We test jointly that the ftrst 6 lags of the relevant variable are zero using a Wald

test which has a chi-squared distribution:

HOi: <Pi! = 0, <Pi2 = 0, ... <Pi. = 0, i= 1,2,3 (9)

HOI tests the null hypothesis that housing prices do not Granger-cause stock prices,Ho' tests the null hypothesis that oil prices do not Granger-cause stock prices, andftnally H03 tests the null hypothesis that U.S. T-bills rates do not Granger-causestock prices.s

Before testing for Granger-causality, equation (4) is estimated using OLS.Since the results are sensitive to departures from the standard assumptions, wesubject the residuals ofthe estimated equation to a battery of diagnostic tests. Table6 presents diagnostic tests on the estimated residuals from equation (4). The ftrsttest, TSC( 10) is a test for up to the tenth order serial correlation in the residuals,which is distributed X'(10). The second test, N(2), is the Jarque & Bera (1980)normality test which is asymptotically distributed X'(2). The third test, RESET(I),is the RESET test for parameter instability which is asymptotically distributedX'(1). The results in Table 6 suggest that residuals from equation (4) pass the testsat the 95 per cent significance levels and, hence, there is no significant departurefrom the standard assumptions.

Table 7 reports the results of the Granger-causality tests. The results in thistable suggest that stock prices in Kuwait are being significantly Granger-caused byhousing prices. oil prices. and U.S. T-bills rates. This means that the short-rundynamics of stock prices is being affected by past infonnation on these variables.

4.5 Variance Decomposition

Table 8 decomposes the forecast error variance of average stock returns intoproportions attributable to each variable within a twenty-four period horizon. Themain observations from this table can be summarized as follows: i) Stock prices inKuwait are endogenous in the sense that they allow being explained by the othervariables in the model. Past infonnation on housing prices, oil prices, and U.S. Tbills rates explain together almost 40 per cent ofthe future changes in stock prices.The remaining proportion ofchange is due to past (historical) information on stockprices themselves. ii) Changes in oil are the main contributor to changes in stockprices in Kuwait. As indicated in Table 8, around 19 per cent of the twenty-fourthperiod forecast error variance of stock returns are explained by innovations to oil

The code to implement this test was obtained from Rambaldi, A.N. and H.E. Doran(1996).


prices. This, once again, points to the importance ofoil prices in detennining stockprices in an oil-dependent economy like Kuwait. Innovations in oil prices areseconded by U.S. interest rates and real estate prices to explain future variation ofstock returns.

TABLE 6

DIAGNOSTIC TESTS ON THE RESIDUALS OF EQUATION (4)

R2

0.589"

0.603

TSC(lO)

0.034

N(2)

1.822

RESET(I)

0.947

Null Hypothesis

TABLE 7

TEST RESULTS FOR GRANGER-CAUSALITY

Significance Level

HOI: Housing prices do nor

Granger·cause srock prices

HOI: Oil prices do notGranger.cause stock prices

HOI: U.S. T·bills rates do notGranger-cause srock prices

13.974

19.243

15.231

0.0299

0.00377

0.0185

TABLES

RESULTS OF VARIANCE DECOMPOSITIONS

Percentage of forecast variance of D(KSEP) explained byinnovations in

ForecastPeriod(months)

234569121824

ForecastError of

l>(KSEP)

0.0240.0270.02880.02970.0310.0320.0320.0320.032

l>(KSEP)

91.47473.83269.95266.59261.72959.84859.45959.34559.337

l>(PHOU)

0.7978.3637.9447.4946.9716.5836.9847.0047.008

l>(POIL)

3.42913.94314.97218.83418.83818.95919.09919.19919.202

l>(TBUS)

4.3003.8627.1307.080

12.46214.61214.45714.45114.452

Economic Analysis & Policy

5. CONCLUSION

Vo1.32 No.2, September 2002 157

Based on mutivariate time-series techniques and monthly data spanning the periodSeptember 1992 to December 1998, we have identified three important factors thathave long-term equilibrium effects on stock market prices in Kuwait. We found thatoil prices, U.S. interest rates and real estate prices form a cointegrating relationshipwith stock prices in Kuwait. We were also able to show through Granger causalityand exogeneity tests, that stock prices are endogenous with respect to these threevariables. Variance decomposition analysis revealed that almost 50 per cent oflong-run future changes in stock returns could be traced to innovations to oil prices,real estate prices and U.S. interest rates.

Our results show the contrast between the Kuwaiti stock market and those ofdeveloped and other developing economies. Many ofthe conventional variables usedin the literature to explain the long-term behavior of stock prices were found to beinsignificant in the case of Kuwait. The variables found to impinge on the long-termbehavior of stock prices and the dynamics of the stock market reflect characteristicsand features that are unique to an oil-dependent economy such as the Kuwaitieconomy. These findings could prove useful for portofolio managers in Kuwait andin economies with similar features in the region. A point that may provide groundsfor future research is related to the fact that given the common features between theKuwaiti economy and anumber ofeconomies in the region, there may be a correlationbetween stock markets of the region. An investigation of this nature would offer avaluable insight for regional policy makers on the extent of the effects of theincreasingly integrated nature of their economies on the stock index behavior.

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investigating stock price dynamics in an oil-dependent economy: the case of kuwait

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