oil price shocks and macroeconomic activities in … price shocks and macroeconomic activities in...

The Journal of World Economic Review; Vol. 6 • No. 2 • (July-December 2011) pp. 123-142

Oil Price Shocks and Macroeconomic Activities in MalaysiaMukhriz Izraf Azman Aziz* & Nor’Aznin Abu Bakar**

* Senior lecturer, College of Business. Universiti Utara Malaysia. 06010 Sintok, Kedah,Malaysia. E-mail: [email protected].

** Associate Professor, College of Business, Universiti Utara Malaysia. 06010 Sintok, Kedah,Malaysia. E-mail: [email protected]

ABSTRACT

This paper investigates the asymmetric effects of oil price shocks on real economic activities in Malaysiafrom 1991 to 2007. Using an unrestricted Vector Auto Regressive (VAR) method, mixed results areobtained. Evidence of a symmetric relationship between oil prices and economic activities is obtainedfrom the impulse response function (IRFs). However, the variance decomposition analyses VAR suggestthat oil prices have different impacts on economic activities when they increase than when they fall.

JEL Codes: F11, N50, C32.

Keywords: Oil price shocks, International trade, Unit root test, GDP growth, Export.

1. INTRODUCTION

Among the non-OPEC countries, Malaysia is a net oil exporter. While manufacturing productscurrently account for 75% of total Malaysian exports (and 30% of nominal GDP),1 crude oilexports contributed 43 billion Malaysian ringgits (RM) of export revenue in 2008, or 6% ofMalaysian total exports, and on average 40% of government revenues in annual budgets (CentralBank of Malaysia, 2008). The rise in crude oil prices in recent years has contributed significantlyto the increase in revenue for the Malaysian government. The oil revenue to the governmentpaid by PETRONAS2 increased from RM13.6 billion in 2000 to RM51.2 billion in 2007 (BankNegara Malaysia Report, 2008). This higher oil-based revenue has allowed the government toundertake development spending on infrastructure, education, and healthcare, thus enhancingthe country’s long-term productive capacity.

As a net exporter of oil, Malaysia benefits from higher crude oil prices in the short termbecause of better terms of trade. However, high oil prices are also a double-edged sword forMalaysia. Rising oil prices will impact on world growth, which will affect world consumptionand income. Thus, oil price shocks may impede the growth of trade between Malaysia and itstrading partners, especially for oil importers such as the US, China, Japan, and Europe. Beingan open economy, Malaysia is susceptible to adverse cyclic effects of this shock. Economicslowdown in these countries will limit internal consumer demand and thus affect Malaysia’sexports of goods and services. The recent global economic turmoil had resulted in lower GDPgrowth and rising inflation for Malaysia. In 2008, GDP growth was recorded at 4.6%, downfrom 6.7% in 2007, while the inflation rate surged to 8.5%, its highest level since 1982, wheninflation was 7.2% (Department of Statistics, Malaysia).

Studies on Malaysia have shown that high oil prices are not always beneficial to the economy.Abeysinghe (2001) concluded that, although the direct impact of high oil prices on Malaysia is

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124 THE JOURNAL OF WORLD ECONOMIC REVIEW

positive, it cannot escape the contractionary effect through its trading partners on growth, andin the long run Malaysia would also lose out. Cunado & de Gracia (2005) found that oil priceshocks have a significant effect on inflation, although the oil prices–macroeconomy relationshipseems to be less significant. Jaafar et al., (2008) examined the impacts of oil price shocks on theMalaysian economy using computable general equilibrium analysis. Results from the simulationshowed that a 5% increase in oil price reduces Malaysian real GDP (RGDP) by 0.35% and fixedcapital investment by 8%.

According to Abeysinghe (2001), the magnitude to which the volatility of oil prices affectsopen economies depends on whether the economy is a net importer or exporter of oil. Earlyliterature on oil price shocks on the oil-importing US economy found a statistically significantnegative linear relationship with output. These studies include Rasche and Tatom (1981), Darby(1982), Hamilton (1983), Burbidge and Harrison (1984), and Gisser and Goodwin (1986). Bythe mid-1980s, however, the estimated linear relationship between oil prices and real activitybegan to lose significance. In fact, the declines in oil prices that occurred over the second half ofthe 1980s had smaller positive effects on economic activity than predicted by linear models.Thus, Mork (1989), Lee et al., (1995), and Hamilton (1996) introduced non-linear transformationsof oil prices and established an asymmetric (non-linear) relationship between increases in oilprices and output growth. More recently, Hamilton (2003) and Jiménez-Rodríguez (2004) alsofound evidence of a non-linear relationship between the two variables for the US and severalOECD economies respectively.

Despite the non-linear (asymmetric) relationship found between oil price shocks andmacroeconomic variables in oil-importing economies, studies on oil-exporting countries haveshown that this relationship is in fact symmetric (linear). Eltony and Al-Awadi (2001) foundevidence that symmetric oil price shocks are important in explaining fluctuations inmacroeconomic variables in Kuwait. Their results showed the importance of oil price shocks ongovernment expenditures, which are the major determinant for the level of economic activity inKuwait. Berument et al., (2010) studied the effects of symmetric oil price shocks on output(proxied by industrial production) for a group of Middle East and North African countries.Their impulse response analyses suggest that the effects of world oil price on GDP of MiddleEastern countries are positive and statistically significant. In a recent study by Jbir and Zouari-Ghorbel (2009), no evidence was found of asymmetric effects of oil price shocks on the Tunisianeconomy, as no difference in terms of results was discovered between the linear and non-linearvector autoregressive (VAR) models.

This paper therefore aims to determine whether the macroeconomic volatility in Malaysiais due to fluctuations in oil prices. Specifically, the paper attempts to establish whether theimpact of oil price shocks on Malaysia’s macroeconomic variables are symmetric or asymmetric.This is achieved using a six-variable VAR model with quarterly data from 1991:1 to 2007:4.The paper will employ simulation techniques (impulse response functions) to determine whatimpacts an oil price shock would have on the variables in the model, how long such effectswould last, and when the maximum repercussions could be expected. In addition, an out-of-sample forecast is carried out to measure the accuracy of the VAR model for six quarters from2008:1 to 2009:2. To take into account the asymmetric effect of oil prices, the paper estimatesthe relationship between oil prices and macroeconomic variables using the standard linear and

OIL PRICE SHOCKS AND MACROECONOMIC ACTIVITIES IN MALAYSIA 125

three non-linear approaches. These are (1) quarterly oil price changes, (2) separate oil pricevariables for price increases and decreases, as in Mork (1989), (3) scaled oil price increases anddecreases, as in Lee at al., (1995), and (4) net specification as in Hamilton (1996), which considersthe amount by which oil prices have risen over the previous year.

The present study extends the existing empirical literature on the Malaysian economy intwo directions. First, it complements the methodologies employed in Abeysinghe (2001) andCunado & de Gracia (2005) on the use of VAR with different oil price shock specifications(both linear and non-linear). Although Abeysinghe employed a VAR model, he did not examinethe asymmetric effect of oil price shocks on the Malaysian economy. In contrast, Cunado & deGracia (2005) tested for asymmetric effects of oil prices, but the estimation was carried outusing an autoregressive distributed lag (ADL) model. Therefore, the present study combineselements of both papers to obtain a new set of results for the Malaysian economy. Second,unlike Abeysinghe (2001) and Cunado & de Gracia (2005), who specifically examined theeffects of oil price shocks on output growth and inflation, the present paper extends the analysisby investigating five macroeconomic variables, namely GDP growth, exchange rate, governmentexpenditure, export, and inflation. This should enable a better understanding of how oil priceshocks affect the Malaysian economy.

The remainder of this paper is organised as follows. Section 2 provides some backgroundto Malaysia as an oil-exporting country, while section 3 discusses the theoretical framework.Section 4 considers the methodology, followed by the results in section 5. Section 6 concludesthe paper.

2. BACKGROUND: MALAYSIA AS AN OIL EXPORTER

This section presents some background to Malaysia as a net oil exporter and recent developmentsin its production of oil and fuel prices. Over the last two decades, Malaysia as a non-OPECcountry has been a net exporter of natural gas and crude petroleum. Malaysia is important toworld energy markets because, Malaysia has the world’s 10th largest natural-gas reserves andthe 27th largest crude oil reserves (EIA, 2008). Malaysia has six oil refineries, with a totalcapacity of 753,700 barrels per day. Oil reserves in the country continued to increase in 2008,rising to 4 billion barrels, or 22 years of lifespan (EIA, 2008), following the discovery of severaldeepwater oil fields in offshore Sabah. These fields now account for about one-fourth of its oilreserves and have led to higher investments in the sector, particularly from multinational oilcompanies and domestic service providers related to oil and gas.

The recent rise in the oil price (of both crude oil and products) is one of a series of largeshifts in price that have occurred during the last 30 years. Since 1983, the Malaysian governmenthas been using the Automatic Pricing Mechanism to regulate and fix the domestic fuel prices.Its function is to stabilize the price of petrol and diesel in the country to a certain extent, via avariable amount sales tax and subsidy, so the retail price only has to be changed if the differencein price exceeds the threshold of the tax and subsidy, at the discretion of the government.

From 1990-1999, the price for research octane number (RON) 97 was fixed at RM1.10 perlitre. However, retail fuel prices were gradually increased from 1999 onwards following therapid increase in crude oil prices. From RM1.10 per litre in 1999 for RON 97, it escalated to


RM1.92 per litre in 2006. The domestic fuel price increased to a record high of RM2.70 per litrein June 2008 (RON97) when world oil price escalated to US$131 per barrel. Although Malaysiaproduces and exports oil, it is not a member of OPEC or a major oil-producing country. Thus,Malaysia has no influence on how the price of oil is determined internationally. If there is alarge increase in oil prices on the world market, this affects the price of petroleum productssuch as diesel, petrol, and cooking gas (LPG) in Malaysia.

3. THEORETICAL FRAMEWORK

3.1 Demand and Supply Sides’ Impacts of Oil Price Shocks

Fluctuations in oil prices have negative repercussions on the aggregate economy, as shown byeconomic literature. An oil price shock, as an example of an adverse supply shock, results in arise in price level and a reduction in output and employment (Dornbusch et al., 2001). On theother hand, aggregate demand decreases as higher commodity prices translate to lower demandfor goods and services, resulting in contraction in aggregate output and employment levels. Themacroeconomic effects of oil shocks are transmitted via supply and demand side channels andare potentially minimised by economic policy reactions.

Since oil is a factor of production in most sectors and industries, a rise in oil prices increasescompanies’ production costs and thus stimulates contraction in output (Jimenez-Rodriguez andSanchez, 2004). Given a firm’s resource constraints, the increase in the price of oil as an inputof production reduces the quantity it can produce. Hunt et al., (2001) add that an increase ininput costs can drive down non-oil potential output supplied in the short run given existingcapital stock and sticky wages. Moreover, workers and producers may respond to the decline intheir real wages and profit margins by putting upward pressure on unit labour costs and theprices of finished goods and services.

As discussed earlier, oil price increases translate to higher production costs, leading tocommodity price increases. Higher commodity prices then translate to lower demand for goodsand services, therefore shrinking aggregate output and employment. Furthermore, higher oil pricesaffect aggregate demand and consumption in the economy. The transfer of income and resourcesfrom oil-importing to oil-exporting economies is projected to reduce worldwide demand as demandin the former is likely to decline more than it will rise in the latter (Hunt et al., 2001). This isparticularly true when the marginal propensity for oil importers to consume is higher than that ofoil exporters. The resulting lower purchasing power of the oil-importing economy translates to alower demand for goods and services. In sum, an increase in oil prices causes a leftward shift inboth the demand and the supply curve, resulting in higher prices and lower output.

3.2 Why Does Asymmetry Effects of Oil Shock Arise?

The linearity or symmetric assumption between real oil prices and macroeconomic variables(for oil importing countries) implies that if oil price increases causes economic recession, thenoil price declines must cause an economic expansion with the same magnitude, although inreverse direction. On the other hand, the asymmetric effects of oil price shocks assume that anoil price decrease may actually lower future GDP growth through other channels. Hamilton(1988) suggests that asymmetry could be the result of adjustment costs to changing oil prices.


Falling oil prices stimulate economic activity, and rising oil prices impede economic activity,but the costs of adjusting to changing oil prices also impede economic activity. Combiningthese elements, it can be seen that rising oil prices would present two negative effects for economicactivity. Falling oil prices would present both a negative and a positive effect which would tendto be offsetting.

Another possibility is that monetary policy may account for the asymmetric response ofaggregate economic activity. The way monetary policy is conducted plays a significant role inhow the consequence of oil-price shocks play out in the economy. Bohi (1991), Bernanke et al.,(1997), Leduc and Sill (2004) and Jumah and Pastuszyn (2007) among others, argue thatcontractionary monetary policy following an oil price increase accounts for the decline inaggregate economic activity. Ferderer (1996) suggests a third possibility. Uncertainty and financialpressure brought on by changing oil prices could amplify the negative effects of rising oil pricesand offset to some degree the positive effects of falling oil prices.

4. DATA AND METHOD

4.1 The Data

This paper uses quarterly data for the period 1991:1 to 2007:4 for five macroeconomic variables(defined below) and four measures of oil price shocks. The four measures of oil price shocksare quarterly oil price changes (∆ROIL), Hamilton’s (1996) Net Oil Price Increase (NOPI), Leeet al.’s (1995) Scaled Oil Price Increase (SOPI), and Mork’s (1989) Oil Price Increase andDecrease. All macroeconomic variables and oil price variables are expressed in logs. The datasets were obtained from International Finance Statistics (IFS), the Economic Planning Unit(EPU), and the Statistics Department of Malaysia.

The six variables used in this paper are defined as follows:

i. Real gross domestic product (RGDP) is a measure of total output for the Malaysianeconomy. RGDP is expressed in RM.

ii. Real effective exchange rate (REER) index of the RM is the nominal effective exchangerate index (NEERI) of the RM adjusted for inflation rate differentials with countrieswhose currencies comprise the NEERI basket. REER is defined such that an increasemeans a real appreciation of the currency considered. An appreciation of the realexchange rate is expected to harm the country’s external competitiveness.

iii. Real government expenditure (GOVT) measures the total Malaysian government publicexpenditures (e.g. payments of governmental employees and subsidies). The GOVTvariable partly reflects the role of oil subsidy policy undertaken by the government toregulate fuel prices in Malaysia. GOVT is expressed in RM.

iv. Real exports (EXPORT) measure the importance of goods exports which includes oilexports in Malaysia. EXPORT is expressed in RM.

v. Inflation (CPI variable) is measured via the consumer price index in Malaysia.

vi. Oil price shock variables are divided into two specifications: linear and non-linear.

The choice of five macroeconomic variables is based on work by Farzanegan and Markwardt(2009). However, real imports and real industrial GDP variables as employed in Farzanegan


and Markwardt (2009) are substituted with real export and RGDP in this paper. The use ofRGDP is consistent with previous literature (see Lee et al., 1995, and Hamilton, 2003, forexamples), while the use of real exports instead of real imports reflects the significant contributionof the exports sector to Malaysian GDP.

4.2 Oil Price Shock Variables

An important question is how to incorporate oil prices into the model. A number of studies haveused different oil price variables to account for the effects of these shocks on economic activity.According to studies on the US (Hamilton, 1996; Mork, 1989; Lee et al., 1995), the effect of oilprices on growth is asymmetric. Thus, by defining the real oil price in time t as roil

t = log (O*E

t

/PPIt), where O is Dubai crude oil price in US$, E

t is the exchange rate of Malaysia against

US$, and PPIt is the producer price index of Malaysia, this paper estimates the effects of oil

price shocks using linear and non-linear specifications of a VAR model, which is discussed inthe next section. The linear specification of oil price is based on quarterly changes in real oilprices, that is, the conventional first difference transformation of oil price variables (in logs):

∆ roilt = roil

t – roil

t – 1 (1)

where roilt is the real oil price (in logs) in local currency, i.e. RM, as defined above.

On the basis of asymmetric oil effects, this paper also uses three non-linear specificationsof oil prices: (1) separate oil price variables for price increases and decreases, as in Mork (1989);(2) net specification (Hamilton, 1996 and 2003), where the relevant oil price variable is definedas the net amount by which these prices in quarter t exceed the maximum value reached in theprevious four quarters; and (3) scaled oil price increase and decrease, proposed by Lee et al.,(1995).

In Mork (1989), the asymmetric specification distinguishes between the positive rate ofchange in the oil price, +, and its negative rate of change, –, which are defined as follows:

roilt+ = max (0, (roli

t – roil

t – 1)), (2)

roilt– = min (0, (roli

t – roil

t – 1)). (3)

Hamilton (1996) proposed a different non-linear transformation, using an explanatoryvariable called net oil price increase (NOPI). This is defined as the amount by which oil pricesin quarter t, roil

t, exceed the maximum value over the previous four quarters, and zero otherwise.

That is:

NOPIt = max {0, roil

t – max {roil

t – 1 – roilt – 2, roil

t – 3, roilt – 4}}. (4)

Hamilton’s (1996) definition is also asymmetric in the specific sense that it captures oilprice increase-type shocks while neglecting the impact of oil price declines. This is inspired byearlier evidence that oil price decreases played a smaller role in the US business cycle.

Lee et al., (1995) argued that oil price shock is likely to have greater impact on real GNP inan environment where oil prices are stable than in one where oil price movements are frequentand erratic. The AR (4)-GARCH (1, 1) model is calculated as below:

∆ roilt = β0 + β1 ∆ roil

t – 1 + β2 ∆ roilt – 2 + β3 ∆ roil

t – 3 + β4 ∆ roilt – 4 + ε

t(5)

εt | I

t – 1 ~ N (0, ht) (6)


ht = γ0 + γ1 e2

t – 1 + γ2 ht – 1 (7)

ˆˆmax(0, / )t t tSOPI e h= (8)

ˆˆmin(0, / )t t tSOPD e h= (9)

where SOPI is scaled oil price increase, while SOPD denotes scaled oil price decreases. Thescaled model builds on the asymmetric model, where it employs a transformation of the oilprice that standardises the estimated residuals of the autoregressive model by its time-varying(conditional) variability. This transformation seems very plausible in light of the pattern of oilprice changes over time, with most changes being rather small and punctuated by occasionalsizeable shocks (Jiménez-Rodríguez and Sánchez, 2004).

4.3 The Vector Autoregression (VAR) Model

A number of the studies cited have made use of VAR models. This technique treats all variablesin the system as endogenous and regresses each current (non-lagged) variable in the model onall the variables in the model lagged a certain number of times. The VAR technique is appropriatein this case because of its ability to characterise the dynamic structure of the model as well as itsability to avoid imposing excessive identifying restrictions associated with various economictheories. The VAR model may be viewed as a system of reduced form equations in which eachof the endogenous variables is regressed on its own lagged values and the lagged values of allother variables in the system.

This paper employs the following unrestricted VAR model of order p (VAR (p)):

Yt = c + ΣA

iY

t – 1 + εt

(10)

where Yt is a (n × 1) vector of endogenous variables, c is the intercept vector of the VAR, A

i is the

i th matrix of autoregressive coefficients, and εtis the generalisation of a white noise process. A

separate VAR model is estimated for each measure of oil price shocks. Each VAR model includesRGDP, REER, GOVT, EXPORT, and CPI.

Yt = [Oil price variables, GOVT, RGDP, CPI, REER, EXPORT] (11)

The VAR system can be transformed into its moving average (MA) representation in orderto analyse the system’s response to a real oil price shock, that is:

0t i t iiY

∞−== ε + γ µ∑ (12)

where γ0 is the identity matrix, ε is the mean of the process. The MA representation is used toobtain the forecast error variance decomposition (FEVD) and the impulse response function(IRF).

5. ESTIMATION RESULTS

5.1 Test of Stationarity

Ohanian (1988), among other researchers, cautions against interpreting results derived from VARmodels estimated with potentially integrated regressors. Because of this, the ADF test for first-order


unit roots is used to determine the proper transformation for each variable. Table 1 provides theunit root regression results in levels and first differences of the five macroeconomic variablesentered in the model and the corresponding critical value of 10%, 5%, or 1% to reject the nullhypothesis of the presence of a unit root. The ADF statistics in the table suggest that all fivemacroeconomic variables are integrated of order one I(1), whereas the first differences are integratedof order zero I(0). These non-stationary variables were transformed by taking their first differencesin order to exhibit stationarity. As for the oil price variables, they are by definition stationary atlevels or I (0) because of the construction of the variables themselves. Each oil price measure isderived from taking the first difference (or the change) between the present value and the pastvalue of the price of oil according to the oil price variable definition. Besides, the graphical plotsof each oil price measures reveal the no trend pattern which satisfies the stationarity at levelscriterion. Thus, given the different orders of integration for the variables involved in the analysis,the paper needs to carry out an unrestricted VAR exercise for these variables with four lags, asfound to be optimal by Hannan–Quinn information criterion (HQIC) (refer Table 2).

Table 1Unit Root Tests

Level First difference

t-Statistics Probability t-Statistics Probability

GOVT (log) – 2.57684 0.2921 – 4.31009 0.00583 ***RGDP (log) – 2.29774 0.4288 – 4.10499 0.0102 **CPI (log) – 1.95557 0.6143 – 6.9044 0.0000 ***REER (log) – 2.60845 0.2781 – 5.75454 0.0001 ***EXPORT (log) – 2.34454 0.4047 – 7.57397 0.000 ***

Note: One/two/three asterisks respectively denote rejection of the null hypothesis of the presence of unit root ata 10%/5%/1% critical level.

Table 2Optimal Lag Length Using the Hannan-Quinn Information Criterion

Log linear Hamilton net Mork oil Mork oilVAR real oil oil price price price Lee et al. Lee et al.order p price increase increase decrease SOPI SOPD

0 -10.1378 – 12.1764 – 11.6963 – 11.9479 – 8.2822 – 8.277121 -20.138 – 21.257 – 21.1562 – 22.419 – 18.2802 – 18.32592 -20.405 – 21.4501 – 21.1626 – 22.7997 – 18.0344 – 18.53153 -20.3071 – 21.2929 – 21.0661 – 22.2804 – 17.7178 – 18.02074* -20.7585* – 21.7105* – 21.5434* – 23.0827* – 18.4522* – 18.7177*5 -20.5883 – 20.9996 – 20.8298 – 22.7192 – 18.3578 – 18.6848

* Optimal lag length.Significant coefficients in bold.

5.2 Impulse Response Function: Theory

The next step is to estimate the VAR. The estimates along with their standard deviation valuesare available from the authors upon request. Since the estimates of individual coefficients inVAR do not have a straightforward interpretation, this paper will focus the VAR results in terms


of IRFs and variance decomposition. IRFs trace the effect of one standard deviation shock toone of the innovations on current and future values of each of the endogenous variables in thesystem. If the innovations ε

t are contemporaneously uncorrelated, the interpretation of the impulse

response is straightforward. The i th innovation εtis simply a shock to the i th endogenous variable

yt. According to Runkle (1987), reporting IRFs without standard error bars is equivalent to

reporting regression coefficients without t-statistics. Accordingly, this paper estimates 90%confidence intervals for the IRFs. The middle lines in the IRF figures represent the IRF, whilethe bars represent confidence intervals. In this regard, when the horizontal line falls into theconfidence interval, the null hypothesis – that there is no effect of oil price shocks on othermacroeconomic variables – cannot be rejected.

This paper classifies the variables from the most exogenous to the less exogenous. Thefollowing ordering of variables is applied for linear and three non-linear oil price specifications:real oil price variables, real government expenditure (GOVT), real GDP, inflation (CPI), REER,and EXPORT. The baseline ordering assumes that goods market prices adjust slowly todisturbances in the oil market. The ordering also assumes that GOVT contemporaneously affectsRGDP following an oil price shock. This is plausible if GOVT is dependent upon the anticipatedrevenue that the government receives from oil exports. Other plausible orderings could also beconstructed using the Cholesky decomposition. These alternative orderings may yield differentoutcomes and interpretations of the IRFs.

In the baseline ordering, the real oil price variables are ranked as largely exogenous variables.This is because Malaysia’s oil production and exports account for less than 1% of total worldoil output; hence Malaysia is incapable of influencing global oil prices. Furthermore, demandfor crude oil is largely determined by global economic growth, speculator operations in oilmarkets, and the policies of key oil consumers on strategic petroleum reserves. The secondvariable in the ordering is government expenditure (GOVT). Oil revenue contributes up to 40%of Malaysian government income and is used for paying governmental employees, subsidies,and so on. Thus, it is a plausible assumption that changes in oil price will have an immediateeffect on government expenditures. The latter is then allowed to feed into changes in real GDP(RGDP). RGDP is also affected instantly by the level of government demand. The government,as a main recipient of oil rents, attempts to distribute some of these through various types ofexpenditures. Positive development in oil prices, which results in higher levels of governmentexpenditures and raises income per capita, pushes the effective demand upward. In the shortrun, the limited capacity of domestic supply and the rising cost of doing business may pushgeneral consumer prices upward, fuelling inflation.

Increasing inflation due to oil price increase appreciates the REER. This measures therelative price of non-tradable goods to tradable ones and gauges the competitiveness of aneconomy. The REER is a weighted real exchange rate index, with the weights assigned totrading partners of the local economy. If domestic prices increase while prices abroad remainunchanged, this would increase the relative prices of tradables, and the competitiveness of theeconomy will fall. Finally, a shock in REER contemporaneously affects real exports in Malaysia.Any significant developments in exchange rate markets may also affect the competitiveness ofMalaysian products and foreign trade.


5.3 IRF: Results

Figure 1 shows IRFs for one standard innovation shock in real oil price growth (∆ ROIL) (inlinear definition) for 1990:1–2007:4. Generally, most of the variables show an increase duringthe first few quarters, with the exception of REER. The IRFs generated from the VAR modelusing the linear specification of crude oil prices shows that a positive oil price shock leads to anincrease in GOVT, persisting for two quarters, after which government expenditures decreases.However, this effect is not statistically significant. The shocks in real oil price increase RGDPand EXPORT in the first and second quarters after the initial shock. However, such increasedoes not last long (i.e. RGDP and real exports decline after the second quarter).

Figure 1: IRFs for Linear Oil Price Specification (ROIL)Shock to ROIL

The impulse response of the REER suggests that, in the long run, this variable reacts to asymmetric shock in real oil price by appreciating. The significant real effective depreciation(i.e., decrease in REER value) in the short run between first and second quarters could bebecause rising oil prices lead directly to higher inflation for the major trading partners of Malaysiavia higher import prices, while domestic prices of energy products are subsidised in Malaysiaand are below global market prices. However, in the medium and long run, the second roundeffects of higher inflation in Malaysia through increasing nominal wages appear to surpass theinflation experienced by trading partners, leading to a real appreciation of the Malaysian ringgit.However, this is not statistically different from zero.

Figure 2 to Figure 4 illustrate the IRFs based on one standard deviation shock to the threenon-linear oil price increase measures for 1990:1 to 2007:4. Overall, the results are comparable.The response of GOVT to a positive oil price shock is not statistically significant for mostquarters, although the shock causes GOVT to decline significantly between the third and fourthquarters and between the sixth and seventh quarters. As an oil-exporting country, Malaysia’sRGDP is expected to improve at least in the short run consequent upon positive oil price shocks.Results from Figure 2 to Figure 4 show that RGDP increases for two quarters following a onestandard deviation shock to Hamilton’s NOPI, SOPI, and Mork’s Price Increase specifications.This confirms the stimulus effect of positive oil price shocks on domestic output. However, the


Figure 2: IRFs for Non-Linear Oil Price Specification (Hamilton’s NOPI)Shock to Hamilton’s NOPI

Figure 3: IRFs for Non-Linear Oil Price Specification (SOPI)Shock to Scaled Oil Price Increase (SOPI)

Figure 4: IRFs for Non-Linear Oil Price Specification (Mork’s +)Shock to Mork’s Oil Price Increase


increase in output does not last long. RGDP declines continuously after the second quarter tothe tenth quarter. This finding is consistent with those of Hamilton (1983) and Mork (1989),who found decreases in RGDP (or GNP) after an oil price shock. Furthermore, findings frompositive oil price shock models are in line with those of Abeysinghe (2001), who concludedthat, although the direct impact of high oil prices on Malaysia is positive, it cannot escape thecontractionary effect on growth coming through its trading partners, and in the long run Malaysiawould also lose out.

Inflation (CPI) reacts positively to oil price increases in both the short run and the long run.The inflationary effects of positive oil price shocks on the Malaysian economy can be explainedthrough the demand side and supply side. Increasing oil revenues lead to higher levels ofgovernment expenditures. Given the dominant role of the government in the domestic economy,current and capital expenditures of the government will rise as oil revenues increase. In addition,because of increased net foreign reserves of the Central Bank, the money supply will increase.The increased money supply and government expenditures will shift the aggregate demandcurve upward. On the supply side, oil price increases raise production costs as domestic fuelprice rises. Increased cost of doing business and lower profit margins would erode producers’profits and may cause them to cut back on output, shifting the supply curve upward.

Real export response to a shock on positive changes in real oil prices is positive and lastsuntil the end of the period. Real exports increase significantly for three quarters after the initialshock, and peak between the 2nd and 3rd quarters when measured using Hamilton’s NOPI, SOPI,and Mork’s Price Increase specifications. The medium- and long-term decreasing trend may bedue to weak consumer demand from Malaysia’s major trading partners, namely the US, Japan,Singapore, and China, consequent upon the positive oil price shocks. The adverse impacts of oilprice increase on these countries, especially the US, raise inflation and reduce the real disposableincome of consumers, thus limiting their demand for imports. In an oil-exporting economy, anoil price boom is expected to lead to a real appreciation of exchange rates and a decline in non-oil exports in the long term. This is often taken as the main symptom of Dutch disease. Thistrend (real appreciation of REER) however is not observed for the positive oil shock measures,as the real appreciation of REER is not statistically significant.

For Scaled Oil Price Decrease and Mork’s Oil Price Decrease specifications, Fig. 5 to Fig. 6show that the responses of CPI, real exports, and RGDP to a one standard deviation negativeshock are the opposites of those obtained from the increase specifications. Inflation declinescontinuously for five quarters, while real exports react negatively to negative oil price shockboth in the short and in the long term. Real exports decline in the first quarter after the initialshock but it moves back to its pre-shock level at the 10th quarter. Oil price decrease also has aprolonged negative impact on RGDP between the first and second quarters. The impact onRGDP is significantly negative for the first two quarters. However, the response on RGDP is notstatistically significant over the long term. This is in line with the findings of Mork (1989),whereby the impacts of negative oil price shocks on US output growth were not statisticallysignificant. For REER, negative oil price shocks lead to significant real appreciation betweenthe first and third quarters. This is expected because falling oil prices may reduce the inflationrates of trading partners by a larger proportion than in Malaysia, as many commodity prices inMalaysia, such as fuel, are state controlled. This then causes Malaysia’s REER to appreciate.


The response of real government expenditure to negative oil price changes is not significantlydifferent from zero. At first glance, this might seem counterintuitive. However, the Malaysianpolicy of reducing fuel subsidies during periods of low oil prices and using the oil revenues inpart to finance capital expenditures and the payment of external debts has been effective inmanaging oil wealth.

When comparing the results between the positive (increase) and negative (decrease)non-linear IRF simulations, the paper in general finds no significant difference between thesetwo approaches. In other words, there is no evidence of an asymmetric relation between oilprice and macroeconomic activities in Malaysia. In most cases, the IRF results of the negativenon-linear specifications are just the opposites of the results obtained from the positive non-linearmeasures. This is in line with the linear approach in which oil prices are assumed to havesymmetrical impacts on real activity. However, the paper does find some differences on theresponse of government expenditures (GOVT) to positive and negative oil price shocks. Positiveoil price shocks (as observed from SOPI and Mork ) causes GOVT to increase for two quarters

Figure 5: IRFs for Non-Linear Oil Price Specification (SOPD)Shock to Scaled Oil Price Decrease (SOPD)

Figure 6: IRFs for Non-Linear Oil Price Specification (Mork’s -)Shock to Mork’s Oil Price Decrease


but subsequently decline until the 4th quarter before returning to its pre-shock level in the 5th

quarter. This may reflect the typical spending habit of the Malaysian government during periodof high oil prices where its expenditure increases (in tandem with the increase in oil revenue)but declines when economic growth is low as evident from the decreasing RGDP from 3 rd

quarter onwards (see Fig. 2 to Fig. 4 for evidence) . In contrast, the response of GOVT to oilprice decreases does not exhibit any significant cyclical trends for the 10-quarter period. Onepossible reason could be the prudent oil wealth management by the Government during periodsof low oil prices in financing public expenditures.

The findings also show that positive oil price shocks may not necessarily lead to persistentpositive impacts on GDP growth for an oil-exporting country such as Malaysia, in contrast tothe findings of Berument et al., (2010) for Middle East countries. In other words, not alloil-exporting countries benefit from the hike in oil price, unless it is their major income earner.For countries such as Iraq, Kuwait, and the United Arab Emirates, oil accounts for more than75% of GDP. For Malaysia, oil contributes only 6% to export earnings and accounts for lessthan 9% of GDP. The relatively small share of oil to the economy makes Malaysia no lessvulnerable than some oil-importing countries to oil price shocks. Moreover, the Malaysianeconomy has been heavily dependent on continued growth in the US, China, and Japan as topexport destinations and key sources of foreign investment. While Malaysia has profited fromincreased world energy prices, its strong dependency on manufacturing exports makes itvulnerable to fluctuations in global demand and the performance of its trading partners. Theslowdown of the US economy in recent years and high crude oil prices are expected to impactexport growth adversely, especially the manufacturing sector, resulting in lower forecast GDPgrowth as simulated by the IRF analysis.

5.4 Robustness Checks

The IRFs obtained from the baseline ordering is based on the assumption that the Malaysiangovernment manages its spending (GOVT) in anticipation of the revenue it receives from oilexports. Thus, allowing shocks to GOVT to contemporaneously affect RGDP. However, if theimpacts of oil price shocks are allowed to transmit directly into price levels (CPI) or that thegovernment spending is dependent upon what it actually earned from oil exports, differentoutcome from IRFs may be obtained. Thus, for robustness checks, the paper performed IRFswith two alternative orderings for symmetric and asymmetric definition of oil prices shocks3.The first alternative ordering assumes prices are flexible – [Oil Price variable, CPI, REER,EXPORT, GOVT and RGDP]. This ordering allows the price level (CPI) to adjustcontemporaneously to shocks in oil prices. The second alternative ordering follows the pricerigidity assumption – [Oil Price variable, EXPORT, GOVT CPI, REER, and RGDP]. This orderingconsiders the contributions of oil export revenue to the GOVT. The IRFs obtained from the twoalternative orderings are comparable to the IRFs from the baseline ordering. In spite of thealternative orderings based on the price flexibility and price rigidity, responses of the fivemacroeconomic variables to an oil price shock however remains unchanged.

5.5 VAR Results: Variance Decomposition Analysis

Variance decomposition represents the VAR system dynamics by providing information aboutthe relative importance of each random innovation to the variables in the model. It shows how


many of the unanticipated changes or variations of the variables in the model can be explainedby various shocks. This sub-section presents variance decomposition analysis according to bothlinear and non-linear oil price specifications.

Table 3 shows the variance decomposition of the VAR model using linear and non-linear oilprice specifications. The columns in Table 3 are labelled alphabetically from A to E, each columnrepresents the impact of oil price shocks using a different oil price specification on the othervariables in the VAR system. The rows are numbered from 1 to 20. Each row represents thepercentage of the change in each variable that is the result of an oil price shock which is shown1, 4, 8 and 10 quarters in the future. For example, column A and row 5 is read as A5 andcorresponds to the value 47%. For linear specification (∆ ROIL), oil price shocks contribute arelatively large share to the variation of RGDP and EXPORT. The largest effect of an oil shockon a variable’s variation is through RGDP, accounting for approximately 47% (A5) in the firstperiod and 50% (A6) in the fourth period. Likewise, crude oil prices account for 25% to 52%(A17, A18) of real exports volatility between the first and fourth quarters. Meanwhile, crude oilprices are marginal sources of variation in government expenditure (GOVT). For inflation (CPI),the contribution of oil price shocks is about 28% (A10) in the fourth quarter, rising to 40%(A11) in the eighth quarter. Shocks to oil price account for up to 23% (A14) of shocks in REERin the second quarter, decreasing marginally to 17% (A15) in the eighth quarter.

For non-linear oil price measures, both oil price increases and decreases affect the volatilityof macroeconomic variables in the model to varying degrees. By and large, the contribution ofpositive oil price changes to each variable’s variation is greater than negative oil price changes,especially for inflation, GOVT and EXPORT. For inflation fluctuations, positive oil price shockshave a stronger short- and long-run role compared to negative oil price shocks. While negativeoil price shocks (MORK”) account for just 6% (E10) and 14% (E11) of variances in inflation inthe fourth and eighth quarters, respectively, positive oil price shocks (MORK+) explain about30-45% (C10, C11) of inflation fluctuations for the same period. This again confirms the highinflationary pressures observed during periods of high oil prices. The other important aspect ofasymmetric oil price shocks is in their effects on GOVT fluctuation. While negative oil priceshocks (MORK” and SOPD) play almost no role in variations in this variable, positive oil priceshocks (MORK+ and SOPI) have the largest effect in both the short and the long term. Positiveoil price shocks explain about 6-7% (C1, D1) of fluctuations in GOVT for the first quarter afterthe shock, increasing to about 23% (C3, D3) in the eighth quarter after the shock.

Again, positive compared to negative oil price shocks have larger explanatory effects onEXPORT fluctuations. This role increases gradually from 12% (C17) (when measured usingMORK+) in the first quarter after the shock to about 49% (C20) at the end of the period. Incontrast, the MORK” specification accounts for about 20% (E17 to E20) of variations in EXPORTover the ten-quarter period. Similarly, the contribution of Mork’s positive of oil price shocks toREER averaged around 18% (C9 to C12) during the ten-quarter period compared to just 9%(E9 to E12) when using Mork’s negative oil price shocks. For fluctuations of RGDP, Mork’snegative oil price shocks have a stronger short-run role compared to Mork’s positive oil priceshocks. While Mork’s positive oil price shocks account for 27% (C5) of variances of RGDP inthe first quarter, Mork’s negative oil price shocks explain about 46% (E5) of RGDP fluctuationsfor the same quarter.


The variance decomposition also suggests that positive oil price shocks account for aroundone-third of variability in real output. The contribution of oil innovations to output movementsin Malaysia is relatively lower when compared to major oil-producing countries such as Iranand Saudi Arabia. For example, Mehrara and Oskoui (2007) found that oil price shocks explainabout 54% of output fluctuations in Iran in the first year, increasing to more than 73% after twoyears. In Saudi Arabia, oil innovations explain about 65% of output movements in the short andlong run. The relatively lower influence of oil price changes on Malaysia’s RGDP can be attributedto the reasonably successful experience of Malaysia to diversify away from resource-basedproduction, including oil. Since oil accounts for only 6% of export earnings, the instability inthe world economy brought about by fluctuations in oil prices have relatively less influence onthe Malaysian economy.

When comparing the results obtained from the IRF, evidence of symmetric relationshipbetween oil prices and macroeconomic variables (as observed from the variance decomposition)cannot be supported. This is because, in most cases, the contributions of positive oil price

Table 3Variance Decomposition

SOURCES OF SHOCKS

COLUMN A B C D E F

∆ ROIL NOPI MORK+ SOPI MORK- SOPD

Real Govt1 1/QTR 1% 0% 6% 7% 0% 1%2 4/QTR 10% 4% 18% 14% 1% 5%3 8/QTR 14% 15% 23% 23% 1% 7%4 10QTR 14% 19% 25% 26% 1% 7%

Real GDP5 1/QTR 47% 37% 27% 20% 46% 34%6 4/QTR 50% 37% 38% 33% 40% 30%7 8/QTR 28% 24% 24% 24% 22% 16%8 10QTR 22% 21% 21% 23% 18% 13%

CPI9 1/QTR 2% 0% 2% 1% 0% 0%

10 4/QTR 28% 14% 30% 20% 6% 12%11 8/QTR 40% 27% 45% 31% 14% 13%12 10QTR 45% 33% 48% 36% 18% 14%

REER13 1/QTR 9% 7% 2% 3% 13% 11%14 4/QTR 23% 15% 27% 15% 12% 17%15 8/QTR 17% 14% 23% 22% 9% 12%16 10QTR 15% 12% 20% 18% 10% 10%

EXPORT17 1/QTR 25% 14% 12% 7% 16% 15%18 4/QTR 52% 36% 45% 29% 20% 25%19 8/QTR 56% 44% 51% 36% 22% 23%20 10QTR 55% 43% 49% 36% 22% 23%

RE

SPO

NSE

VA

RIA

BL

ES

RO

W


shocks on the macroeconomic variables are higher than the negative oil price shocks. In otherwords, there is a difference between the effects of positive and negative oil price shocks oneconomic activities, pointing to an asymmetric relationship between oil prices and themacroeconomic variables. Due to the mixed evidence obtained from the analyses, the studycannot conclude whether the impacts of oil price shocks on the Malaysian economy is symmetricor asymmetric. The mixed results could partly be attributed to the relatively short sample periodused in the study. The estimation results could be improved if the dataset could be extended upto the early 1980s, i.e. when the first two global oil shocks occurred. However, such dataset iscurrently unavailable for use.

6. CONCLUSION

This paper has studied the effects of oil price shocks on the real economic activity of Malaysia.It has focused on the relationship between oil prices and GDP growth, analysed in terms ofVAR using four specifications, namely a linear model and three leading non-linear specificationsproposed in the literature. IRFs and variance decomposition were estimated to assess how oilprice shocks move through major channels of the Malaysian economy and the contribution ofshocks to the variability of the variables in the system. Five macroeconomic variables weretaken into consideration: Real Government Expenditure (GOVT), Real Effective Exchange Rate(REER), Real Gross Domestic Product (RGDP), Real Export (EXPORT), and Inflation (CPI),together with four real oil price specifications.

Prior to estimation, a unit root test and cointegration test were conducted to determine thestructure of data to be used for each VAR model. While the paper found the variables to beintegrated of order one, it also found evidence of cointegration for each of the VAR modelsemployed. Therefore, the VAR models were estimated with data at levels instead of firstdifferenced. The IRF obtained from the linear oil price specification indicated that oil pricemovements lead to declines in RGDP in the long term after experiencing growth in the shortterm. However, only marginal impacts are seen in government expenditure (GOVT). Analysisfrom the non-linear oil price specifications produced comparable results. Hamilton’s (1996)NOPI, Lee et al.’s (1995) SOPI, and Mork’s (1989) positive oil price shock measure increaseaggregate output in the short term but negatively affect output growth in the long term. Fornon-linear oil price decrease specifications, real output responds negatively in the short termbefore recovering to its pre-shock level in the long term.

The insignificant difference between the effect of oil price increases and decreases (asobserved from IRF) suggest a symmetric relationship between aggregate economic activity andoil prices. Notwithstanding this, the variance decomposition estimated from the non-linear VARmodel shows that oil price increases contribute much higher to the variability of RGDP, realexports and inflation than that of oil price decreases. This on the contrary points to an asymmetricrelationship between oil prices and macroeconomic variables for the Malaysian economy. Themixed evidence found for this study may be attributed to the relatively short duration of datasetavailable in the study.

Results from the VAR estimation reveal that increases in oil prices have a larger impact onthe Malaysian economy compared to oil price decreases. The linear and non-linear oil pricespecifications show that RGDP responds negatively to oil price increase in the long term despite


experiencing growth in the short term. Though Malaysia produces and exports oil, the contributionto the economy is relatively small. Therefore, the economic stimulus provided by higher oil-exportearnings in Malaysia would be more than outweighed by the depressive effect of higher priceson economic activity in importing countries. In other words, the windfall revenue from the oilsector may not be sufficient to cushion the economy from slowdown experienced by neighbouringand major trading partners. This finding is consistent with those of Abeysinghe (2001) andMehrara and Oskoui (2007), who reached similar conclusions about the long-run effects of oilprice shocks on oil-exporting countries. Given these results, forthcoming fiscal policies mustnot assume that future effects of upcoming oil shocks will be the same as in the past. Nevertheless,analysing economic policy reactions amidst these shocks will show how effective the chosenmonetary or fiscal policies are in minimising adverse effects.

The recent hike in world crude oil prices has prompted the Malaysian government toencourage the use of alternative energy sources such as natural-gas vehicles (NGV). Since theimplementation of the 8th Malaysia Plan (2001-2005), renewable energy has been identified asthe fifth fuel alongside coal, gas, oil, and hydropower. This effort has minimized the dependenceof Malaysia’s power-generation sector on oil and gas as more coal-fired power plants areapproved. Its Small Renewable Energy Programme (SREP) also encourages the generation ofelectricity under 10 MW. Regarding its fuel subsidy policy, the government plans to reduce thegap between domestic retail and world prices gradually. This involves reducing the subsidiesfor consumers progressively, as has been done since June 2008. By increasing prices gradually,consumers should be able to adjust their expenditure, hence minimising the adverse effects offuture oil price shocks.

Acknowlwdgement

The author would like to thank Dr. Kwok Tong Soo for valuable comments on earlier drafts.

Notes

1. The manufacturing sector has consistently contributed between 29% and 30% to Malaysian GDPsince 2002 and accounts for 75% of gross export earnings (Malaysia Economic Report, 2008/2009).

2. PETRONAS (Petroliam Nasional Berhad) is Malaysia’s nationally owned petroleum company.

3. The results for other shocks are available upon request from the authors.

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