Hindawi Publishing CorporationThe Scientific World JournalVolume 2013 Article ID 171868 9 pageshttpdxdoiorg1011552013171868
Research ArticleRelationships among Energy Price Shocks Stock Market andthe Macroeconomy Evidence from China
Rong-Gang Cong12 and Shaochuan Shen3
1 School of Economics and Management North China Electric Power University Beijing 102206 China2 Centre for Environmental and Climate Research (CEC) Lund University 223 62 Lund Sweden3 State Key Laboratory Breeding Base of Green Chemistry Synthesis Technology College of Chemical Engineering andMaterials ScienceZhejiang University of Technology Hangzhou 310014 China
Correspondence should be addressed to Rong-Gang Cong ronggangcongcecluse
Received 18 February 2013 Accepted 17 March 2013
Academic Editors K J Chua and A Piacentino
Copyright copy 2013 R-G Cong and S Shen This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited
This paper investigates the interactive relationships among China energy price shocks stock market and the macroeconomy usingmultivariate vector autoregressionThe results indicate that there is a long cointegration among them A 1 rise in the energy priceindex can depress the stock market index by 054 and the industrial value-adding growth by 0037 Energy price shocks alsocause inflation and have a 5-month lag effect on stock market which may result in the stock market ldquounderreactingrdquo The energyprice can explain stock market fluctuations better than the interest rate over a longer time period Consequently investors shouldpay greater attention to the long-term effect of energy on the stock market
1 Introduction
Since 2002 the global crude oil price has risen rapidly In July2008 price of both WTI crude oil and Brent crude oil wentbeyond $140 per barrelThis results in fluctuation in the inter-national market causing the domestic oil price to increasewhich in turn pushes the energy price up for coal and elec-tricity [1] As a result the nationwide retail commodity priceindex also raises to some extent All of these factors have aprofound effect on Chinarsquos macroeconomy In the meantimeowing to appreciation of the China currency (RMB) and inanticipation of expansion in the Chinese economy duringthe Olympics Games the Chinese stock market has steadilyincreased since 2006 which as a consequence has attractedinvestors world wide As a result observing whether theshocks in energy price are transmitted to the stock marketwill receive considerable attention from investors It mightbe argued that this relationship reflects the efficiency of theChinese stock market
Extant research includes analyses of relationships be-tween energy price a countryrsquos macroeconomics and itsstock market Research on the relationship between energy
price and the macroeconomy is mainly focused on therelationship between crude oil price and GDPGNP andthe channels through which crude oil price influences themacroeconomy In the former the majority of scholars havefound a reverse relationship between oil price and GDPGNPwhich meant that rising oil price would depress GDPGNP[2ndash4] In the mid-1980s however the linear reverse rela-tionship became not so evident Various scholars studied theasymmetric relationship between oil price and macroeco-nomic activities [5ndash7] Lardic and Mignon [8] found thatwhile standard cointegration is rejected there is evidence forasymmetric cointegration between oil prices and GDP in themajor European countries In recent years scholarsmeasuredthe elasticity ofGNP to oil price [9] In the latter it is generallyassumed that oil price influenced the macroeconomy at thedemand and supply levels As to the demand level on theone hand the rise of oil price can cause inflation [10] andsuppress consumption [11 12] and investment [13 14] Ifthe Central Bank cannot increase the currency supply theinterest rate may tend to rise which may influence theaggregate demand [15 16] On the other hand the rise inoil price may transfer wealth from oil-importing countries to
2 The Scientific World Journal
those exporting This may deteriorate the purchasing powerof oil-importing countries and affect their international trade[17] As regards to the supply level as oil is a major materialfor production price increases will raise production costsand cause industries to scale-down or transfer to low energy-intensive industries [18]This in-turn may affect productionand increase unemployment [14 19] Meanwhile the riseof production costs may result in cost-driven inflation Ifthe cost increase is transferred to industries downstreamtheir production cost will increase So any rise in oil priceinfluences various industries in different ways Fan et al [20]researched the impact of rising international crude oil priceon Chinarsquos GDP investments consumptions import exportand so on
As shownpreviously scholars have extensively researchedthe relationship between oil price shocks and a countryrsquosmacroeconomy But there is relatively little research onthe relationship between oil price shocks and the financialmarketsmdashthe exception being those that focused on devel-oped countries For example Jones and Kaul [21] based ona standard cash flowsdividends valuation model researchedthe stock market of US Canada Japan and England Theyfound that the change of oil price had a decisive effect onthe four countriesrsquo real stock returns Sadorsky [22] identifiedthat oil price and its volatility played an important partin explaining the real stock returns The movement of oilprice explained more than interest rates for the forecast-ing variances Papapetrou [23] researched the Greek stockmarket Likewise he also found that oil price played animportant component in explaining stock price movementsand positive oil price shocks suppressed real stock returnsEwing and Thompson [24] also examined the cyclical rela-tionships among industrial production consumer pricesunemployment and stock prices using time series filteringmethods
Several scholars showed that oil price and its shocks influ-enced various industries differently [25] A common heldview is that shocks are beneficial for oil companies upstreamyet has an adverse effect on companies downstream andother industries For example Huangrsquos research [26] basedon correlative coefficient method and a VARmodel used theS amp P 500 index twelve industriesrsquo stock price indices andthree oil company stock prices He found that crude oil futurereturns had significant abilities to explain oil companiesrsquostock returns which could be seen as their lead index buthad little effect on the total market Faff and Brailsford [27]used an enlarged market model to research several industriesreturns in the Australian stock market They found that oilprice had an effect on stock prices They also found thatthe oil and gas industry and diverse resources industry hadpositive sensitivities while papermaking packing and trans-portation industry had negative sensitivities Using Johansencointegration test Hammoudeh et al [28] found that one-month to four-month WTI oil future price shocks explainedoil extracting refining andmarketing companiesrsquo stock pricemovement Sadorsky [29] took Canadian companies as anexample Using the stock market index energy price interestrates and exchange rates as explanatory variables he foundthat the rise of the stock market index and oil price had
a positive effect on oil companiesrsquo returns while the riseof interest rates and exchange rates had a negative effectLanza et al [30] used VARVECM models to research therelationships among six large oil companies various stockmarkets and the spread of crude oil future and spot priceThey found that the greater the spread the higher the oilcompaniesrsquo stock prices
In summary it can be stated that there are relationshipsamong oil price macroeconomy and the stockmarket whichhave been tested in several developed countries Whetherthese relationships exist in China is the focus of this paperAs the Chinese economic dependency on energy increasesany rise in energy price has a significant effect on themacroe-conomy In essence the stock market is a virtual economy Toknow whether it is affected by energy price this paper hasfocused on the Chinese Shanghai stock market using a VARmodel Based on impulse response functions and forecastingvariance decomposition it analyzes the interactive responsesamong several economic variables and energy price
The paper is structured as follows We begin with abrief introduction of the VAR model and then describe thedata in Section 2 Section 3 presents the empirical resultsIn Section 4 we discuss the results within the context ofthe Chinese situation Next we conclude with a summaryand propose suggestions in Section 5 Finally possible futurework is presented
2 Methodology and Data
21 Methodology of VAR Model We have selected to usea vector autoregression (VAR) method [31] Since VARmodel requires all variables in the system to be stationarya unit root test is initially completed Here we choose ADF(augmented Dickey-Fuller test) method Take oil price seriesas an example The fundamental principle of ADF test is
ΔOIL119905= 120574OIL
119905minus1+
119901
sum
119894=1
120573119894ΔOIL
119905minus119894+ 119906119905
119905 = 1 2 119879 no constant or linear time trends
ΔOIL119905= 120574OIL
119905minus1+ 119886 +
119901
sum
119894=1
120573119894ΔOIL
119905minus119894+ 119906119905
119905 = 1 2 119879 constant
ΔOIL119905= 120574OIL
119905minus1+ 119886 + 120575119905 +
119901
sum
119894=1
120573119894ΔOIL
119905minus119894+ 119906119905
119905 = 1 2 119879 constant and linear time trends
(1)
The letter ldquo119886rdquo is a constant 120575119905 is a linear trend functionΔ represents differentiation 119906
119905sim iid 119873(0 120590
2)which form is
chosen depends on a series graph119901 is the optimum lag orderwhich depends on AIC (Akaike Information Criterion) The
The Scientific World Journal 3
original hypothesis and the alternative hypothesis can bewritten as
1198670 120574 = 0
1198671 120574 lt 0
(2)
The original hypothesis for oil price time series has aunit root which is a nonstationary series The alternativehypothesis is the oil price time series that does not have unitroots which is a stationary series As to nonstationary timeseries another stationary test is needed If the test shows thatthe first-order differentiation is stationary the series is namedas I (1) otherwise the second differentiation should be tested
IP119905 OIL119905 119903119905 and STOCK
119905stand for industry production
oil price nominal interest rates and stock market indexrespectively 119910
where 119901 is lag orders which is determined by AIC andSC information criterion 119879 is the size of the sample1198601 1198602 119860
119901and B are parameter matrices 120576
119905are random
disturbances which can correlate in the same time but cannotcorrelate with their lag variables and the variables on the rightof the functions
If IP119905 OIL119905 119877119905 and STOCK
119905can be tested as the same
number of the unit roots which can be assumed as I (1)we can use JJ method to test whether there are cointegrationamong the series In otherwords whether there are long-termstable relationships among nonstationary variables
Based on VAR model we can also use impulse responsefunctions and forecasting variance decomposition to explainthe model established Impulse response functions can beused to test the effect of a standard variance shock on theendogenous variables and their future values Its fundamentalrationale is as follows
If 119871 is defined as a lag operator 119871119909119905= 119909119905minus1
it can bederived from (3) as follows
(119868119896minus 1198601119871 minus sdot sdot sdot minus 119860
119901119871119901) 119910119905= 120576119905
119910119905= (119868119896minus 1198601119871 minus sdot sdot sdot minus 119860
119901119871119901)minus1
120576119905
= (119868119896+ 1198621119871 + 119862
21198712+ sdot sdot sdot) 120576
119905
(4)
The first variable of 119910119905(industry production) can be writ-
ten as
IP119905= 1199101119905
=
4
sum
119895=1
(119888(0)
1119895120576119895119905+ 119888(1)
1119895120576119895119905minus1
+ sdot sdot sdot) 119905 = 1 2 119879
(5)
where 119888(119902)
1119895is the first row and first line element of 119862
119902 which
can be represented as 119888(119902)1119895
= 120597IP119905+119902
120597120576119895119905 It shows at period
IP119905+119902
rsquos response to a shock of 119910119895119905(IP119905 OIL119905 119903119905 or STOCK
119905)
at the condition that other variables keep constant We refer
to it as the impulse-response function which is similar to theshock multiplier effect analysis As there are correlations inthe same period among various functionsrsquo random variancesin VAR model it needs to construct an orthogonal matrixto transform shocks from correlation in the same period tononcorrelation There are many methods to accomplish thisgoal Here we used general impulse method [32] which doesnot depend on the variablesrsquo orders in VAR model
Variance decomposition decomposes the forecasting var-iances by various variables shocks We can use it to estimatethe importance of various structural shocks Its fundamentallogic is as follows take industrial production as an example Itcan be known from (5) that what is in the brackets is the total120576119895rsquos effect on IP
119905up to now If it can be assumed that there are
not series correlations among 120576119895 the variances are
119864 [(119888(0)
1119895120576119895119905+ 119888(1)
1119895120576119895119905minus1
+ 119888(2)
1119895120576119895119905minus2
+ sdot sdot sdot)2
]
=
infin
sum
119902=0
(119888(119902)
1119895)2
120590119895119895
119895 = 1 2 4
(6)
Additionally if there are no correlations among distur-bances in the same period the variance of IP
119905is the sum of
four variances above mentioned as follows
var (IP119905) =
4
sum
119895=1
infin
sum
119902=0
(119888(119902)
1119895)2
120590119895119895 119905 = 1 2 119879 (7)
Because the variance of IP119905can be decomposed into
four irrelative effect we can define the criterion as followsto measure the contribution of various disturbance to thevariance of IP
119905
RVC119895rarr1
(infin) =
suminfin
119902=0(119888(119902)
1119895)2
120590119895119895
var (IP119905)
=
suminfin
119902=0(119888(119902)
1119895)2
120590119895119895
sum4
119895=1suminfin
119902=0(119888(119902)
1119895)2
120590119895119895
119895 = 1 2 4
(8)
The relative variance contribution (RVC) measures theeffect of the 119895th variable on IP
119905 This paper decomposes each
endogenous variablersquos shock to four parts related to everyfunctionrsquos disturbance which can be used to know the relativeimportance of various shocks to endogenous variables in themodel Comparing the importance varyingwith time we alsoestimate the lag of the variablersquos effect
22 Data Sources In this paper we do not choose oil pricedata Drawing upon lessons from Papapetrou [23] we choosedomestic energy price index Different from commoditiesprice index for fuel that he chose in his paper we choosepurchase price index for fuel power Since Chinese oil pricesare not in accordance with international markets we do notchoose oil spot price or future price in international marketsInterestingly though since June 2006 the home refined oilprice started to adjust in accordance with the movement
4 The Scientific World Journal
Table 1 The test result of unit root
Variables ADF test Test type (119888 119905 119901) Critical valueIP minus2003340 (119888 119905 2) minus3160198lowast
Note 1The meanings of various variables in the table are as follows IP isindustry value added discounted by price index OIL is discounted purchaseprice index for fuel power 119877 stands for real interest rates and STOCK ismonthly price index of Shanghai stock market2119888 119905 and119901 in test type stand for constant trend and lag orders respectively
3At three remarkable levels when ADF value is greater than critical valuecorresponding series has unit root4 lowastlowastlowast lowastlowast and lowast stand for 1 5 and 10 critical levels respectively5119889 stands for the first differential of the variables and1198892 stands for the seconddifferential of the variables
of oil price in international market Based on Jiao et alrsquos[33] research the domestic oil price responded 784 to thechange of crude oil cost and it had a four-month lag Someof the international oil price shocks were absorbed by oilcompanies The purchase energy price index can accuratelyreflect the domestic oil price in a timely manner
Considering that the energy price has a close relationshipto industry we chose industry value adding as a proxy forthe macroeconomy As for the stock market we selected themonthly Chinese Shanghai stock market index and consid-ered the bonus and stock dividend According to traditionalfinancial theory it is generally assumed that the stock priceis equal to the discount of stockrsquos future cash So interestrates are important to stock price Following Sadorsky [22]and Papapetrou [23] we introduce interest rates to dynamicanalysis Interest rates can be divided into nominal interestrates and real interest rates This paper chooses the latter Wehave selected one year to mature a lump deposit for totalwithdrawal as a representative and eliminate the interest taxWith exception of the interest rate data sourced from thewebsite of Bank of China all the data is from the NationalBureau of Statistic of China With due consideration ofavailability of information we selectedmonthly data betweenJanuary 2000 and December 2010 The industry value-addeddata and the energy price data are both adjusted by CensusX12 method and discounted by consumer price index Allthe variables are in logarithmic form As interest rates are inpercentages we define the logarithm of it as log(1 + 119903100)
3 Results and Analysis
31 The Stationary Test of Data In Table 1 ADF test showsthat industrial value added has two unit roots and other vari-ables have a unit root
32 The Determination of Lag Orders Through testing on 1lag order to 5 lag orders AIC and SC can be obtained fromTable 2
Table 2 The choose of lag orders in the model
Lag AIC SC Log 1198710 minus1109981 minus109762 42024271 minus2011605 minus1949806lowast 77435202 minus2036989 minus192575 79987103 minus2037243lowast minus187656 81596624 minus2016755 minus180664 82428315 minus2030166 minus177061 8453124Note lowast above stand for the minimum values in the columns of AIC and SC
Through test iterations we find when the largest lag orderequals to three the AIC reaches the minimum SC reachesthe minimum when the lag order equals to one So LR test ischosen as tradeoff The original hypothesis test is the largestlag order equals to one The testing statistic is as follows
LR = minus2 lowast (1198971minus 1198973) = minus2 lowast (774352 minus 8159662) = 832284
(9)
where 1198971and 1198973are the whole log likelihood function values
when 119901 equals to one and three respectively In the originalhypothesis the statistic has gradually conformed to 120594
2
distribution whose degrees of freedom are thirty-two Theaccompanied probability is 19lowast10
minus6 So we chose a three lagorder VARmodel because the original hypothesis is rejected
33 The Estimation and Test of the Model To give the vari-ables the same integration order we choose the first lag orderto the third lag order values of OIL 119877 STOCK and 119889IP asan alternative of IP as endogenous variables and ordinaryleast squares method to estimate the model The results areas follows
(
119889IP119905
OIL119905
119877119905
STOCK119905
)
= (
minus092lowast
minus0175 073 012lowast
minus0056 127lowast
minus0223 00048
minus011lowast
0118lowast
117lowast
0017
036 minus026 minus148 1056
)(
119889IP119905minus1
OIL119905minus1
119877119905minus1
STOCK119905minus1
)
+(
minus069lowast
019 175 0006
minus002 minus035lowast
minus0163 0008
minus0079lowast
minus014 minus0067 minus0005
minus003 023 182 minus009
)(
119889IP119905minus2
OIL119905minus2
119877119905minus2
STOCK119905minus2
)
+(
minus015 minus0122 minus28lowast
minus02lowast
minus002 004 029 minus0045
minus001 0017 minus019 minus0015
028 018 047 003
)(
119889IP119905minus3
OIL119905minus3
119877119905minus3
STOCK119905minus3
)
+(
105lowast
043lowast
006
minus067
)
(10)
where lowast stands for coefficients that are significant
The Scientific World Journal 5
Table 3 The series cointegration test result
The original hypothesis Eigenvalue Trace statistic (119875 value) 120582-max statistic (119875 value)No cointegration vector 0606545 9620150 (00000)lowast 7369024 (00000)lowast
More than one cointegration vector 0154912 2251127 (02709) 1329684 (04253)More than two cointegration vector 0089195 9214422 (03459) 7380688 (04451)More than three cointegration vector 0022945 1833735 (01757) 1833735 (01757)Note lowast above means that the original hypothesis is significantly rejected
Table 4 The model test results
Stability testThe coefficients of all roots areless than oneSo the model estimated is stable
Autocorrelation LMtest
LM = 1888 (02749)No series autocorrelation
Heteroskedasticitytest
1205942(240) = 2312206 (06462)
No heteroskedasticity
Jarque-Bera normaltest
JB (8) = 711161 (05246)The residual series conform tonormal distribution
As four series in the model are I (1) series the conditionfor cointegration is satisfied The lag order is determinedto 2 Johansen cointegration test result shows that there isa cointegration relationship among four series above whichdemonstrates that there is a prolonged stationary relationshipamong macroeconomy energy price and the stock market(Table 3)
The cointegration can be expressed as
119889IP = minus0037lowastOIL minus 014119877 minus 002
lowastSTOCK + 036 (11)
We can see from the previous equation that in the longerterm the 1 rise in energy price will have an adverse effectof 0037 on industrial value adding and an adverse effect of054 on the stock market
Testing using VAR model obtains the following results(Table 4)
Generally it is difficult to analyze the dynamic relation-ships among variables based on the estimated parametersin the VAR model Consequently we use impulse-responsefunction and variance decomposition to analyze the interac-tive relationships among them
34 Impulse-Response Function and Variance DecompositionFigure 1 shows the impulse-response function curves simu-lated by analytic method based on VAR model
We consider the response of four variables to one SD(standard deviation) innovation of energy price
For one standard deviation innovation of energy price(11 of energy price) interest rate apparently respond In 3months it rises to the peak (02) In 5 months the effectkeeps stable which represents the level of interest rate with a1 stable increase
One standard deviation innovation of energy price to thegrowth rate of industrial value adding has the greatest adverse
effect (02) in 2months Also there is a shock following Butit has a negative convergence trend in the long term
As for one standard deviation innovation of energy pricethe stock price responds adversely to its peak in 3 months(1) But in 6 months the adverse effect disappears
Next we consider the effect of four variablesrsquo shocks onthe energy price index (Figure 2)
One standard deviation shock for interest rate shows thatenergy price is affected most adversely in four months andremains so for a long timeThe residual variances are still halfof its peak in a year
Energy price has little response to one standard deviationshock of industrial value adding
The stock price rises 5 In threemonths the energy pricehas a downward trend Twentymonths later the adverse effecthas reached its minimum value (2)
We decompose the variance to stock market price basedon VAR model and analytic method (above mentioned) Theresults are as follows
In Table 5 the first and seventh columns are the periodsthat are set to a maximum of twenty due to limited spaceThedata in the SE (standard error) column are the forecastingvariance of STOCK in various periods which are caused bythe change of the present or future value 119889IP OIL 119877 andSTOCK are the contribution of the innovations to forecastingvariance respectively which sum to 100 Figure 3 is thevariance decomposition where the periods are prolonged tothirty
It can be seen from Figure 3 that at the first month thestock price can only explain 94 of its forecasting varianceThe energy price can explain 014 the industrial value-added can explain 04 and the change rate of interest ratecan only explain 503 In fifteen months the importance ofenergy price exceeds interest rates At the twentieth monththe interest rates and energy price can explain 77 and 956respectively while the industrial value added can only explain024
4 Discussion
41 There Is a Cointegration among Stock Market Macroecon-omy and Energy Price In this paper we find that there is along-term stable correlation among the stock market macro-economy and energy price Stock market is often said to bethe barometer of onersquosmacroeconomy whichmeans that theyshould have a close relationship But it is a controversial issuein China Chinese scholars generally have two views One isthat the stock market has a weak positive correlation with themacroeconomy The other perspective is that the correlation
6 The Scientific World Journal
00004000800120016
1 2 3 4 5 6 7 8 9 10 11 12
000040008001200160020
1 2 3 4 5 6 7 8 9 10 11 12
000010002000300040005
1 2 3 4 5 6 7 8 9 10 11 12
0001002003004005
1 2 3 4 5 6 7 8 9 10 11 12
Response to cholesky one SD innovations
Response of OIL to OIL
Response of STOCK to OIL
Impulse-response function Impulse-response function
minus0004
minus0004
minus0001
minus0002
minus001
minus002
minus003
minus004
minus0008
minus0012
plusmn2 SEplusmn2 SE
plusmn2 SE
Response of 119889IP to OIL
Response of 119877 to OIL
Figure 1 Generalized impulse responses to one SD shock for energy price changes Note that the horizontal axis is the period The verticalaxis is the explanation level of dependent variables to independent variables In the model we fix the periods at 12 months
Figure 2 Generalized impulse responses of energy price to one SD shock for other variables changes Note that the horizontal axis is theperiodThe vertical axis is the explanation level of dependent variables to independent variables In themodel we fix the periods at 12months
is not significant or is negative Scholars holding this latterview believe that the Chinese stock market aims at financingbut not investingThe stockmarket can not evaluate the valueof companies correctly Therefore the stock market is notthe barometer of the Chinese macroeconomy Based on acapital asset pricing model the real value of stock equals tothe discount of its future cash flows As a result the value
of stock relates to future economy and also is affected bydiscount rates (interest rate) The rising energy price affectsthe Chinese macroeconomy and pushes up the inflation rateThe cointegration obtained in this paper demonstrates thatenergy price has a significant effect on the stock marketwhich is an extension of existing literature In equation (11)we find that in the long-term energy price has a negative
The Scientific World Journal 7
Table 5 Generalized variance decomposition of STOCK
relationship with industrial value adding and the stockmarket The rise in energy price affects the macroeconomyon the one hand and depresses the stock market on the otherhand
42 The Positive Shock of Energy Price Can Push up the RealInterest Rate Affect Industry Productions and Depress theStock Market Price On the basis of realizing the long-termrelationship among them we want to know the response ofstock prices and the macroeconomy to the short-term shockof the energy price Based on impulse response function wehave seen that the positive shock of energy price can push-up the real interest rate affect industry and depress the stockmarket
The shock of energy price can affect real interest rates tosome extent In China since 2002 the international crude oilprice has risen from $20 per barrel to nearly $100 per barrelIn turn this drives up oil related energy products and totalprices Therefore China has the risk of cost-push inflationThe rise of international crude oil price will increase the
domestic price of the refined oil and related chemical engi-neering products The rise of the refined oil price can furtherincrease the price of transportation industrial productionand residential gas Moreover the rise in price of relatedchemical engineering products will increase the cost ofplastic rubber chemical fiber and other inputs Finally thetotal social price level rises Inflation makes the supply ofcurrency relatively insufficientThe controllable real currencyon the whole will decrease Consequently the rise of energyprice will drive up the total interest rate level
As a major input to industry the rise in energy price canaffect economic growth In the Chinese industry chemicalengineering metallurgy and some other energy-intensiveindustries are seriously affected by the rise in oil price How-ever following advances in technology and the upgrading ofindustrial infrastructure the effect becomes less and less inthe long term
The stockmarket is not completely efficient with regard torecognizing energy price There is a phenomenon of under-reaction As a collection of energy-input companies the riseof energy price will increase their cost and decrease theirprofit If the stock market is efficient the rise in energyprice will depress the stock market immediately But in thispaper we find that the rise in energy price will depress thestock market during a five-month lag As the energy pricein the public domain it means there is conservatism in mostinvestorsrsquo decisions as acknowledged by Barberis et al [34]In other words investors find it difficult to renew their viewsand have an underreaction to the importance of the price ofenergy As a limitation in cognitive abilities they find it hardto evaluate the importance of energy price to stock valueThis conforms to the hypothesis that ldquoinformation diffusesgraduallyrdquo suggested by Hong and Stein [35]
43 The Effect on Energy Price of the Industrial Demand In-creasing Interest Rates and the Stock Market We have dis-cussed earlier that the energy price will have a significanteffect on industrial production real interest rates and thestock market But we still want to know the effect of threeshocks on energy price
To control the inflation caused by the rise of energyprice increasing the real interest rate is very efficient It is
8 The Scientific World Journal
because on the one hand high interest rates change peoplersquoscontrollable income by increasing savings and decreasingconsumption on energy relating products and on the otherhand high interest rates will cause the capital to depreciateand reduce peoplersquos wealth which reduces their consump-tion As to industries high interest rates increase their capitalcost and depresse their investment which reduces theirenergy use for relating products Since 2007 the PeoplersquosBank of China has increased the interest rates five times anddecreased the interest rate tax Currently a sixth increase ininterest rates is being considered It can be forecasted that thePeoplersquos Bank of Chinawill still control inflation by increasinginterest rates as price increase further
The shock of industrial growth has a small but long effecton energy price So the demand from industry on energy isone of the reasons that cause a rise in the energy price Butthe effect is slight
The bull stock market can attract a good deal of moneywhich reduces the currency The Chinese stock market hasrisen from 1000 points to 6000 points since 2005 It hasattracted a large amount of money So after the 2008 Olymp-ics or when the appreciated RMB has been realized a lot ofmoney will be taken back from stock market Additionallythere is risk of inflation in the near future Consequently therise in energy price will be severe
44 Energy Price over the Longer Term Has Better Abilityto Explain the Stock Market than Interest Rates From theresults of forecasting decomposition we find that over thelonger term the greatest effect of three factors on stock priceis energy price interest rates and industrial value adding Inthe short term the increase in interest rates is a bad newsand can be perceived easily by all investors So in the shortterm the interest rates are more important than the othertwo factors But in the long term the rise in energy price willbecome gradually apparent to people and have an effect onpeoplersquos anticipation So it will be the more important factorin the longer term As industries are only a part of stockmarket the effects from them on the total market are limitedThere is separation between the real economy and the virtualeconomy in China Consequently it has a poor explanationin explaining fluctuations in the stock market
5 Conclusions and Future Work
Through the analysis of results and discussion we can drawthe following conclusions
(1) There is a stable long-term relationship among energyprice industrial value adding real interest rates andstock price In the longer term the rise in energy pricewill drive up the real interest rates and have an adverseeffect on industrial value adding and the stockmarket
(2) The shocks in energy price have a lasting effect on realinterest rates which to some extent causes long-terminflation The shocks in energy price have a notableeffect on industrial value adding But the effect tendsto be weaker in the long term In the short time the
shocks in energy price have an effect on the stockmarket
(3) To control the rise in energy price we should considerthe macroeconomy and stock market in addition tothe international and domestic energy market Therising industrial value adding increases the energydemand which to some extent increases the energyprice But the rise of interest rates is favorable for con-trolling the energy price
(4) The effect of energy on the stock market is hard toignore Through forecasting the decomposition ofstock prices we can identify that the stock price ischiefly affected by itself What is a contradiction tothe general view is that energy price and interestrates have greater effect on the stock market thanindustrial value adding In the long term energy priceis evenmore important than interest rates It indicatesto investors that they should not only consider theinterest rates but also consider the energy price fortheir investment
This paper discusses the relationship between energyprice and stock market at the macrolevel The relationshipsbetween the shocks of energy price and the stock prices ofvarious industries and oil companies remain to be researchedMeanwhile opportunities for future research include the sim-ulation and analysis of China economic transition and sus-tainable development at various levels of energy price andthe optimal design of subsidy policy for rising oil price [36]
Conflict of Interests
Theauthors of the paper do not have a direct financial relationwith the commercial identity mentioned in this paper thatmight lead to a conflict of interests for any of the authors
Acknowledgments
The authors gratefully acknowledge the good research envi-ronments provided by the Centre for Environmental andClimate Research (CEC) LundUniversityThe authors thankthe anonymous referees for their helpful suggestions and cor-rections on the earlier draft of the paper which improved thecontentsThis research is funded by ldquoBiodiversity and Ecosys-tem services in a Changing Climate (BECC) and SAPESrdquoThe funders had no role in study design data collection andanalysis decision to publish or preparation of the paperThe contents are the responsibility of the authors and do notnecessarily reflect the views of Centre for Environmental andClimate Research (CEC) Lund University
References
[1] K Hanabusa ldquoThe effect of 107th OPEC ordinary meeting onoil prices and economic performances in Japanrdquo Renewable andSustainable Energy Reviews vol 16 pp 1666ndash1672 2012
[2] M RDarby ldquoTheprice of oil andworld inflation and recessionrdquoAmerican Economic Review vol 72 no 4 pp 738ndash751 1982
The Scientific World Journal 9
[3] J D Hamilton ldquoOil and the macroeconomy since World WarIIrdquo Journal of Political Economy vol 91 pp 228ndash248 1983
[4] A F Darrat OW Gilley and D J Meyer ldquoUS oil consumptionoil prices and themacroeconomyrdquo Empirical Economics vol 21no 3 pp 317ndash334 1996
[5] M K Anton ldquoOil and the macroeconomy when prices go upand down an extension of Hamiltonrsquos resultsrdquo Journal of Polit-ical Economy vol 97 pp 740ndash744 1989
[6] S P A Brown and M K Yucel ldquoEnergy prices and aggregateeconomic activity an interpretative surveyrdquo Quarterly Reviewof Economics and Finance vol 42 no 2 pp 193ndash208 2002
[7] M P Clements and H M Krolzig ldquoCan oil shocks explainasymmetries in the US business cyclerdquo Empirical Economicsvol 27 no 2 pp 185ndash204 2002
[8] S Lardic and V Mignon ldquoThe impact of oil prices on GDP inEuropean countries an empirical investigation based on asym-metric cointegrationrdquo Energy Policy vol 34 no 18 pp 3910ndash3915 2006
[9] A Fayyad and K Daly ldquoThe impact of oil price shocks on stockmarket returns comparing GCC countries with the UK andUSArdquo Emerging Markets Review vol 12 no 1 pp 61ndash78 2011
[10] L J Alvarez S Hurtado I Sanchez and C Thomas ldquoTheimpact of oil price changes on Spanish and euro area consumerprice inflationrdquo Economic Modelling vol 28 no 1-2 pp 422ndash431 2011
[11] J B Taylor ldquoThe lack of an empirical rationale for a revival ofdiscretionary fiscal policyrdquo American Economic Review vol 99no 2 pp 550ndash555 2009
[12] J Elder and A Serletis ldquoOil price uncertainty in CanadardquoEnergy Economics vol 31 no 6 pp 852ndash856 2009
[13] S van Wijnbergen ldquoOil price shocks unemployment invest-ment and the current account an intertemporal disequilibriumanalysisrdquo The Review of Economic Studies vol 52 pp 627ndash6451985
[14] N D Uri and R Boyd ldquoEconomic impact of the energy priceincrease in Mexicordquo Environmental and Resource Economicsvol 10 no 1 pp 101ndash107 1997
[15] J L Pierce J J Enzler D I Fand and R J Gordon ldquoThe effectsof external inflationary shocksrdquo Brookings Papers on EconomicActivity vol 5 no 1 pp 13ndash61 1974
[16] K A Mork O Olsen and H T Mysen ldquoMacroeconomic re-sponses to oil price increases and decreases in seven OECDcountriesrdquo Energy Journal vol 15 no 4 pp 19ndash35 1994
[17] J D Sachs R N Cooper and S Fischer ldquoThe current accountand macroeconomic adjustment in the 1970srdquo Brookings Paperson Economic Activity vol 12 no 1 pp 201ndash282 1981
[18] M Erturk ldquoEconomic analysis of unconventional liquid fuelsourcesrdquo Renewable and Sustainable Energy Reviews vol 15 no6 pp 2766ndash2771 2011
[19] N D Uri ldquoCrude oil price volatility and unemployment in theUnited Statesrdquo Energy vol 21 no 1 pp 29ndash38 1996
[20] Y Fan J L Jiao Q M Liang Z Y Han and Y M Wei ldquoTheimpact of rising international crude oil price on Chinarsquos econ-omy an empirical analysiswithCGEmodelrdquo International Jour-nal of Global Energy Issues vol 27 no 4 pp 402ndash424 2007
[21] C M Jones and G Kaul ldquoOil and the stock marketsrdquo Journal ofFinance vol 51 no 2 pp 463ndash491 1996
[22] P Sadorsky ldquoOil price shocks and stock market activityrdquo EnergyEconomics vol 21 no 5 pp 449ndash469 1999
[23] E Papapetrou ldquoOil price shocks stock market economic activ-ity and employment in Greecerdquo Energy Economics vol 23 no5 pp 511ndash532 2001
[24] B T Ewing and M A Thompson ldquoDynamic cyclical comove-ments of oil prices with industrial production consumer pricesunemployment and stock pricesrdquo Energy Policy vol 35 no 11pp 5535ndash5540 2007
[25] R G Cong Y M Wei J L Jiao and Y Fan ldquoRelationships be-tween oil price shocks and stock market an empirical analysisfrom Chinardquo Energy Policy vol 36 no 9 pp 3544ndash3553 2008
[26] R D Huang RWMasulis andH R Stoll ldquoEnergy shocks andfinancial marketsrdquo Journal of Futures Markets vol 16 no 1 pp1ndash27 1996
[27] R W Faff and T J Brailsford ldquoOil price risk and the Australianstock marketrdquo Journal of Energy Finance and Development vol4 pp 69ndash87 1999
[28] S Hammoudeh S Dibooglu and E Aleisa ldquoRelationshipsamong US oil prices and oil industry equity indicesrdquo Interna-tional Review of Economics and Finance vol 13 no 4 pp 427ndash453 2004
[29] P Sadorsky ldquoRisk factors in stock returns of Canadian oil andgas companiesrdquo Energy Economics vol 23 no 1 pp 17ndash28 2001
[30] A Lanza M Manera M Grasso and M Giovannini ldquoLong-run models of oil stock pricesrdquo Environmental Modelling andSoftware vol 20 no 11 pp 1423ndash1430 2005
[31] C A Sims ldquoMacroeconomics and realityrdquo Econometrica vol48 pp 1ndash48 1980
[32] H H Pesaran and Y Shin ldquoGeneralized impulse response anal-ysis in linear multivariate modelsrdquo Economics Letters vol 58no 1 pp 17ndash29 1998
[33] J L Jiao Y Fan and Y M Wei ldquoVECM based analysis ofgasolinediesel prices anti-symmetryrdquo Chinese Journal of Man-agement Science vol 14 pp 97ndash102 2006
[34] N Barberis A Shleifer and R Vishny ldquoA model of investorsentimentrdquo Journal of Financial Economics vol 49 no 3 pp307ndash343 1998
[35] H Hong and J C Stein ldquoA unified theory of underreactionmomentum trading and overreaction in asset marketsrdquo Journalof Finance vol 54 no 6 pp 2143ndash2184 1999
[36] R-G Cong and M Brady ldquoHow to design a targeted agricul-tural subsidy system efficiency or equityrdquo PLoS ONE vol 7Article ID e41225 2012
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
2 The Scientific World Journal
those exporting This may deteriorate the purchasing powerof oil-importing countries and affect their international trade[17] As regards to the supply level as oil is a major materialfor production price increases will raise production costsand cause industries to scale-down or transfer to low energy-intensive industries [18]This in-turn may affect productionand increase unemployment [14 19] Meanwhile the riseof production costs may result in cost-driven inflation Ifthe cost increase is transferred to industries downstreamtheir production cost will increase So any rise in oil priceinfluences various industries in different ways Fan et al [20]researched the impact of rising international crude oil priceon Chinarsquos GDP investments consumptions import exportand so on
As shownpreviously scholars have extensively researchedthe relationship between oil price shocks and a countryrsquosmacroeconomy But there is relatively little research onthe relationship between oil price shocks and the financialmarketsmdashthe exception being those that focused on devel-oped countries For example Jones and Kaul [21] based ona standard cash flowsdividends valuation model researchedthe stock market of US Canada Japan and England Theyfound that the change of oil price had a decisive effect onthe four countriesrsquo real stock returns Sadorsky [22] identifiedthat oil price and its volatility played an important partin explaining the real stock returns The movement of oilprice explained more than interest rates for the forecast-ing variances Papapetrou [23] researched the Greek stockmarket Likewise he also found that oil price played animportant component in explaining stock price movementsand positive oil price shocks suppressed real stock returnsEwing and Thompson [24] also examined the cyclical rela-tionships among industrial production consumer pricesunemployment and stock prices using time series filteringmethods
Several scholars showed that oil price and its shocks influ-enced various industries differently [25] A common heldview is that shocks are beneficial for oil companies upstreamyet has an adverse effect on companies downstream andother industries For example Huangrsquos research [26] basedon correlative coefficient method and a VARmodel used theS amp P 500 index twelve industriesrsquo stock price indices andthree oil company stock prices He found that crude oil futurereturns had significant abilities to explain oil companiesrsquostock returns which could be seen as their lead index buthad little effect on the total market Faff and Brailsford [27]used an enlarged market model to research several industriesreturns in the Australian stock market They found that oilprice had an effect on stock prices They also found thatthe oil and gas industry and diverse resources industry hadpositive sensitivities while papermaking packing and trans-portation industry had negative sensitivities Using Johansencointegration test Hammoudeh et al [28] found that one-month to four-month WTI oil future price shocks explainedoil extracting refining andmarketing companiesrsquo stock pricemovement Sadorsky [29] took Canadian companies as anexample Using the stock market index energy price interestrates and exchange rates as explanatory variables he foundthat the rise of the stock market index and oil price had
a positive effect on oil companiesrsquo returns while the riseof interest rates and exchange rates had a negative effectLanza et al [30] used VARVECM models to research therelationships among six large oil companies various stockmarkets and the spread of crude oil future and spot priceThey found that the greater the spread the higher the oilcompaniesrsquo stock prices
In summary it can be stated that there are relationshipsamong oil price macroeconomy and the stockmarket whichhave been tested in several developed countries Whetherthese relationships exist in China is the focus of this paperAs the Chinese economic dependency on energy increasesany rise in energy price has a significant effect on themacroe-conomy In essence the stock market is a virtual economy Toknow whether it is affected by energy price this paper hasfocused on the Chinese Shanghai stock market using a VARmodel Based on impulse response functions and forecastingvariance decomposition it analyzes the interactive responsesamong several economic variables and energy price
The paper is structured as follows We begin with abrief introduction of the VAR model and then describe thedata in Section 2 Section 3 presents the empirical resultsIn Section 4 we discuss the results within the context ofthe Chinese situation Next we conclude with a summaryand propose suggestions in Section 5 Finally possible futurework is presented
2 Methodology and Data
21 Methodology of VAR Model We have selected to usea vector autoregression (VAR) method [31] Since VARmodel requires all variables in the system to be stationarya unit root test is initially completed Here we choose ADF(augmented Dickey-Fuller test) method Take oil price seriesas an example The fundamental principle of ADF test is
ΔOIL119905= 120574OIL
119905minus1+
119901
sum
119894=1
120573119894ΔOIL
119905minus119894+ 119906119905
119905 = 1 2 119879 no constant or linear time trends
ΔOIL119905= 120574OIL
119905minus1+ 119886 +
119901
sum
119894=1
120573119894ΔOIL
119905minus119894+ 119906119905
119905 = 1 2 119879 constant
ΔOIL119905= 120574OIL
119905minus1+ 119886 + 120575119905 +
119901
sum
119894=1
120573119894ΔOIL
119905minus119894+ 119906119905
119905 = 1 2 119879 constant and linear time trends
(1)
The letter ldquo119886rdquo is a constant 120575119905 is a linear trend functionΔ represents differentiation 119906
119905sim iid 119873(0 120590
2)which form is
chosen depends on a series graph119901 is the optimum lag orderwhich depends on AIC (Akaike Information Criterion) The
The Scientific World Journal 3
original hypothesis and the alternative hypothesis can bewritten as
1198670 120574 = 0
1198671 120574 lt 0
(2)
The original hypothesis for oil price time series has aunit root which is a nonstationary series The alternativehypothesis is the oil price time series that does not have unitroots which is a stationary series As to nonstationary timeseries another stationary test is needed If the test shows thatthe first-order differentiation is stationary the series is namedas I (1) otherwise the second differentiation should be tested
IP119905 OIL119905 119903119905 and STOCK
119905stand for industry production
oil price nominal interest rates and stock market indexrespectively 119910
where 119901 is lag orders which is determined by AIC andSC information criterion 119879 is the size of the sample1198601 1198602 119860
119901and B are parameter matrices 120576
119905are random
disturbances which can correlate in the same time but cannotcorrelate with their lag variables and the variables on the rightof the functions
If IP119905 OIL119905 119877119905 and STOCK
119905can be tested as the same
number of the unit roots which can be assumed as I (1)we can use JJ method to test whether there are cointegrationamong the series In otherwords whether there are long-termstable relationships among nonstationary variables
Based on VAR model we can also use impulse responsefunctions and forecasting variance decomposition to explainthe model established Impulse response functions can beused to test the effect of a standard variance shock on theendogenous variables and their future values Its fundamentalrationale is as follows
If 119871 is defined as a lag operator 119871119909119905= 119909119905minus1
it can bederived from (3) as follows
(119868119896minus 1198601119871 minus sdot sdot sdot minus 119860
119901119871119901) 119910119905= 120576119905
119910119905= (119868119896minus 1198601119871 minus sdot sdot sdot minus 119860
119901119871119901)minus1
120576119905
= (119868119896+ 1198621119871 + 119862
21198712+ sdot sdot sdot) 120576
119905
(4)
The first variable of 119910119905(industry production) can be writ-
ten as
IP119905= 1199101119905
=
4
sum
119895=1
(119888(0)
1119895120576119895119905+ 119888(1)
1119895120576119895119905minus1
+ sdot sdot sdot) 119905 = 1 2 119879
(5)
where 119888(119902)
1119895is the first row and first line element of 119862
119902 which
can be represented as 119888(119902)1119895
= 120597IP119905+119902
120597120576119895119905 It shows at period
IP119905+119902
rsquos response to a shock of 119910119895119905(IP119905 OIL119905 119903119905 or STOCK
119905)
at the condition that other variables keep constant We refer
to it as the impulse-response function which is similar to theshock multiplier effect analysis As there are correlations inthe same period among various functionsrsquo random variancesin VAR model it needs to construct an orthogonal matrixto transform shocks from correlation in the same period tononcorrelation There are many methods to accomplish thisgoal Here we used general impulse method [32] which doesnot depend on the variablesrsquo orders in VAR model
Variance decomposition decomposes the forecasting var-iances by various variables shocks We can use it to estimatethe importance of various structural shocks Its fundamentallogic is as follows take industrial production as an example Itcan be known from (5) that what is in the brackets is the total120576119895rsquos effect on IP
119905up to now If it can be assumed that there are
not series correlations among 120576119895 the variances are
119864 [(119888(0)
1119895120576119895119905+ 119888(1)
1119895120576119895119905minus1
+ 119888(2)
1119895120576119895119905minus2
+ sdot sdot sdot)2
]
=
infin
sum
119902=0
(119888(119902)
1119895)2
120590119895119895
119895 = 1 2 4
(6)
Additionally if there are no correlations among distur-bances in the same period the variance of IP
119905is the sum of
four variances above mentioned as follows
var (IP119905) =
4
sum
119895=1
infin
sum
119902=0
(119888(119902)
1119895)2
120590119895119895 119905 = 1 2 119879 (7)
Because the variance of IP119905can be decomposed into
four irrelative effect we can define the criterion as followsto measure the contribution of various disturbance to thevariance of IP
119905
RVC119895rarr1
(infin) =
suminfin
119902=0(119888(119902)
1119895)2
120590119895119895
var (IP119905)
=
suminfin
119902=0(119888(119902)
1119895)2
120590119895119895
sum4
119895=1suminfin
119902=0(119888(119902)
1119895)2
120590119895119895
119895 = 1 2 4
(8)
The relative variance contribution (RVC) measures theeffect of the 119895th variable on IP
119905 This paper decomposes each
endogenous variablersquos shock to four parts related to everyfunctionrsquos disturbance which can be used to know the relativeimportance of various shocks to endogenous variables in themodel Comparing the importance varyingwith time we alsoestimate the lag of the variablersquos effect
22 Data Sources In this paper we do not choose oil pricedata Drawing upon lessons from Papapetrou [23] we choosedomestic energy price index Different from commoditiesprice index for fuel that he chose in his paper we choosepurchase price index for fuel power Since Chinese oil pricesare not in accordance with international markets we do notchoose oil spot price or future price in international marketsInterestingly though since June 2006 the home refined oilprice started to adjust in accordance with the movement
4 The Scientific World Journal
Table 1 The test result of unit root
Variables ADF test Test type (119888 119905 119901) Critical valueIP minus2003340 (119888 119905 2) minus3160198lowast
Note 1The meanings of various variables in the table are as follows IP isindustry value added discounted by price index OIL is discounted purchaseprice index for fuel power 119877 stands for real interest rates and STOCK ismonthly price index of Shanghai stock market2119888 119905 and119901 in test type stand for constant trend and lag orders respectively
3At three remarkable levels when ADF value is greater than critical valuecorresponding series has unit root4 lowastlowastlowast lowastlowast and lowast stand for 1 5 and 10 critical levels respectively5119889 stands for the first differential of the variables and1198892 stands for the seconddifferential of the variables
of oil price in international market Based on Jiao et alrsquos[33] research the domestic oil price responded 784 to thechange of crude oil cost and it had a four-month lag Someof the international oil price shocks were absorbed by oilcompanies The purchase energy price index can accuratelyreflect the domestic oil price in a timely manner
Considering that the energy price has a close relationshipto industry we chose industry value adding as a proxy forthe macroeconomy As for the stock market we selected themonthly Chinese Shanghai stock market index and consid-ered the bonus and stock dividend According to traditionalfinancial theory it is generally assumed that the stock priceis equal to the discount of stockrsquos future cash So interestrates are important to stock price Following Sadorsky [22]and Papapetrou [23] we introduce interest rates to dynamicanalysis Interest rates can be divided into nominal interestrates and real interest rates This paper chooses the latter Wehave selected one year to mature a lump deposit for totalwithdrawal as a representative and eliminate the interest taxWith exception of the interest rate data sourced from thewebsite of Bank of China all the data is from the NationalBureau of Statistic of China With due consideration ofavailability of information we selectedmonthly data betweenJanuary 2000 and December 2010 The industry value-addeddata and the energy price data are both adjusted by CensusX12 method and discounted by consumer price index Allthe variables are in logarithmic form As interest rates are inpercentages we define the logarithm of it as log(1 + 119903100)
3 Results and Analysis
31 The Stationary Test of Data In Table 1 ADF test showsthat industrial value added has two unit roots and other vari-ables have a unit root
32 The Determination of Lag Orders Through testing on 1lag order to 5 lag orders AIC and SC can be obtained fromTable 2
Table 2 The choose of lag orders in the model
Lag AIC SC Log 1198710 minus1109981 minus109762 42024271 minus2011605 minus1949806lowast 77435202 minus2036989 minus192575 79987103 minus2037243lowast minus187656 81596624 minus2016755 minus180664 82428315 minus2030166 minus177061 8453124Note lowast above stand for the minimum values in the columns of AIC and SC
Through test iterations we find when the largest lag orderequals to three the AIC reaches the minimum SC reachesthe minimum when the lag order equals to one So LR test ischosen as tradeoff The original hypothesis test is the largestlag order equals to one The testing statistic is as follows
LR = minus2 lowast (1198971minus 1198973) = minus2 lowast (774352 minus 8159662) = 832284
(9)
where 1198971and 1198973are the whole log likelihood function values
when 119901 equals to one and three respectively In the originalhypothesis the statistic has gradually conformed to 120594
2
distribution whose degrees of freedom are thirty-two Theaccompanied probability is 19lowast10
minus6 So we chose a three lagorder VARmodel because the original hypothesis is rejected
33 The Estimation and Test of the Model To give the vari-ables the same integration order we choose the first lag orderto the third lag order values of OIL 119877 STOCK and 119889IP asan alternative of IP as endogenous variables and ordinaryleast squares method to estimate the model The results areas follows
(
119889IP119905
OIL119905
119877119905
STOCK119905
)
= (
minus092lowast
minus0175 073 012lowast
minus0056 127lowast
minus0223 00048
minus011lowast
0118lowast
117lowast
0017
036 minus026 minus148 1056
)(
119889IP119905minus1
OIL119905minus1
119877119905minus1
STOCK119905minus1
)
+(
minus069lowast
019 175 0006
minus002 minus035lowast
minus0163 0008
minus0079lowast
minus014 minus0067 minus0005
minus003 023 182 minus009
)(
119889IP119905minus2
OIL119905minus2
119877119905minus2
STOCK119905minus2
)
+(
minus015 minus0122 minus28lowast
minus02lowast
minus002 004 029 minus0045
minus001 0017 minus019 minus0015
028 018 047 003
)(
119889IP119905minus3
OIL119905minus3
119877119905minus3
STOCK119905minus3
)
+(
105lowast
043lowast
006
minus067
)
(10)
where lowast stands for coefficients that are significant
The Scientific World Journal 5
Table 3 The series cointegration test result
The original hypothesis Eigenvalue Trace statistic (119875 value) 120582-max statistic (119875 value)No cointegration vector 0606545 9620150 (00000)lowast 7369024 (00000)lowast
More than one cointegration vector 0154912 2251127 (02709) 1329684 (04253)More than two cointegration vector 0089195 9214422 (03459) 7380688 (04451)More than three cointegration vector 0022945 1833735 (01757) 1833735 (01757)Note lowast above means that the original hypothesis is significantly rejected
Table 4 The model test results
Stability testThe coefficients of all roots areless than oneSo the model estimated is stable
Autocorrelation LMtest
LM = 1888 (02749)No series autocorrelation
Heteroskedasticitytest
1205942(240) = 2312206 (06462)
No heteroskedasticity
Jarque-Bera normaltest
JB (8) = 711161 (05246)The residual series conform tonormal distribution
As four series in the model are I (1) series the conditionfor cointegration is satisfied The lag order is determinedto 2 Johansen cointegration test result shows that there isa cointegration relationship among four series above whichdemonstrates that there is a prolonged stationary relationshipamong macroeconomy energy price and the stock market(Table 3)
The cointegration can be expressed as
119889IP = minus0037lowastOIL minus 014119877 minus 002
lowastSTOCK + 036 (11)
We can see from the previous equation that in the longerterm the 1 rise in energy price will have an adverse effectof 0037 on industrial value adding and an adverse effect of054 on the stock market
Testing using VAR model obtains the following results(Table 4)
Generally it is difficult to analyze the dynamic relation-ships among variables based on the estimated parametersin the VAR model Consequently we use impulse-responsefunction and variance decomposition to analyze the interac-tive relationships among them
34 Impulse-Response Function and Variance DecompositionFigure 1 shows the impulse-response function curves simu-lated by analytic method based on VAR model
We consider the response of four variables to one SD(standard deviation) innovation of energy price
For one standard deviation innovation of energy price(11 of energy price) interest rate apparently respond In 3months it rises to the peak (02) In 5 months the effectkeeps stable which represents the level of interest rate with a1 stable increase
One standard deviation innovation of energy price to thegrowth rate of industrial value adding has the greatest adverse
effect (02) in 2months Also there is a shock following Butit has a negative convergence trend in the long term
As for one standard deviation innovation of energy pricethe stock price responds adversely to its peak in 3 months(1) But in 6 months the adverse effect disappears
Next we consider the effect of four variablesrsquo shocks onthe energy price index (Figure 2)
One standard deviation shock for interest rate shows thatenergy price is affected most adversely in four months andremains so for a long timeThe residual variances are still halfof its peak in a year
Energy price has little response to one standard deviationshock of industrial value adding
The stock price rises 5 In threemonths the energy pricehas a downward trend Twentymonths later the adverse effecthas reached its minimum value (2)
We decompose the variance to stock market price basedon VAR model and analytic method (above mentioned) Theresults are as follows
In Table 5 the first and seventh columns are the periodsthat are set to a maximum of twenty due to limited spaceThedata in the SE (standard error) column are the forecastingvariance of STOCK in various periods which are caused bythe change of the present or future value 119889IP OIL 119877 andSTOCK are the contribution of the innovations to forecastingvariance respectively which sum to 100 Figure 3 is thevariance decomposition where the periods are prolonged tothirty
It can be seen from Figure 3 that at the first month thestock price can only explain 94 of its forecasting varianceThe energy price can explain 014 the industrial value-added can explain 04 and the change rate of interest ratecan only explain 503 In fifteen months the importance ofenergy price exceeds interest rates At the twentieth monththe interest rates and energy price can explain 77 and 956respectively while the industrial value added can only explain024
4 Discussion
41 There Is a Cointegration among Stock Market Macroecon-omy and Energy Price In this paper we find that there is along-term stable correlation among the stock market macro-economy and energy price Stock market is often said to bethe barometer of onersquosmacroeconomy whichmeans that theyshould have a close relationship But it is a controversial issuein China Chinese scholars generally have two views One isthat the stock market has a weak positive correlation with themacroeconomy The other perspective is that the correlation
6 The Scientific World Journal
00004000800120016
1 2 3 4 5 6 7 8 9 10 11 12
000040008001200160020
1 2 3 4 5 6 7 8 9 10 11 12
000010002000300040005
1 2 3 4 5 6 7 8 9 10 11 12
0001002003004005
1 2 3 4 5 6 7 8 9 10 11 12
Response to cholesky one SD innovations
Response of OIL to OIL
Response of STOCK to OIL
Impulse-response function Impulse-response function
minus0004
minus0004
minus0001
minus0002
minus001
minus002
minus003
minus004
minus0008
minus0012
plusmn2 SEplusmn2 SE
plusmn2 SE
Response of 119889IP to OIL
Response of 119877 to OIL
Figure 1 Generalized impulse responses to one SD shock for energy price changes Note that the horizontal axis is the period The verticalaxis is the explanation level of dependent variables to independent variables In the model we fix the periods at 12 months
Figure 2 Generalized impulse responses of energy price to one SD shock for other variables changes Note that the horizontal axis is theperiodThe vertical axis is the explanation level of dependent variables to independent variables In themodel we fix the periods at 12months
is not significant or is negative Scholars holding this latterview believe that the Chinese stock market aims at financingbut not investingThe stockmarket can not evaluate the valueof companies correctly Therefore the stock market is notthe barometer of the Chinese macroeconomy Based on acapital asset pricing model the real value of stock equals tothe discount of its future cash flows As a result the value
of stock relates to future economy and also is affected bydiscount rates (interest rate) The rising energy price affectsthe Chinese macroeconomy and pushes up the inflation rateThe cointegration obtained in this paper demonstrates thatenergy price has a significant effect on the stock marketwhich is an extension of existing literature In equation (11)we find that in the long-term energy price has a negative
The Scientific World Journal 7
Table 5 Generalized variance decomposition of STOCK
relationship with industrial value adding and the stockmarket The rise in energy price affects the macroeconomyon the one hand and depresses the stock market on the otherhand
42 The Positive Shock of Energy Price Can Push up the RealInterest Rate Affect Industry Productions and Depress theStock Market Price On the basis of realizing the long-termrelationship among them we want to know the response ofstock prices and the macroeconomy to the short-term shockof the energy price Based on impulse response function wehave seen that the positive shock of energy price can push-up the real interest rate affect industry and depress the stockmarket
The shock of energy price can affect real interest rates tosome extent In China since 2002 the international crude oilprice has risen from $20 per barrel to nearly $100 per barrelIn turn this drives up oil related energy products and totalprices Therefore China has the risk of cost-push inflationThe rise of international crude oil price will increase the
domestic price of the refined oil and related chemical engi-neering products The rise of the refined oil price can furtherincrease the price of transportation industrial productionand residential gas Moreover the rise in price of relatedchemical engineering products will increase the cost ofplastic rubber chemical fiber and other inputs Finally thetotal social price level rises Inflation makes the supply ofcurrency relatively insufficientThe controllable real currencyon the whole will decrease Consequently the rise of energyprice will drive up the total interest rate level
As a major input to industry the rise in energy price canaffect economic growth In the Chinese industry chemicalengineering metallurgy and some other energy-intensiveindustries are seriously affected by the rise in oil price How-ever following advances in technology and the upgrading ofindustrial infrastructure the effect becomes less and less inthe long term
The stockmarket is not completely efficient with regard torecognizing energy price There is a phenomenon of under-reaction As a collection of energy-input companies the riseof energy price will increase their cost and decrease theirprofit If the stock market is efficient the rise in energyprice will depress the stock market immediately But in thispaper we find that the rise in energy price will depress thestock market during a five-month lag As the energy pricein the public domain it means there is conservatism in mostinvestorsrsquo decisions as acknowledged by Barberis et al [34]In other words investors find it difficult to renew their viewsand have an underreaction to the importance of the price ofenergy As a limitation in cognitive abilities they find it hardto evaluate the importance of energy price to stock valueThis conforms to the hypothesis that ldquoinformation diffusesgraduallyrdquo suggested by Hong and Stein [35]
43 The Effect on Energy Price of the Industrial Demand In-creasing Interest Rates and the Stock Market We have dis-cussed earlier that the energy price will have a significanteffect on industrial production real interest rates and thestock market But we still want to know the effect of threeshocks on energy price
To control the inflation caused by the rise of energyprice increasing the real interest rate is very efficient It is
8 The Scientific World Journal
because on the one hand high interest rates change peoplersquoscontrollable income by increasing savings and decreasingconsumption on energy relating products and on the otherhand high interest rates will cause the capital to depreciateand reduce peoplersquos wealth which reduces their consump-tion As to industries high interest rates increase their capitalcost and depresse their investment which reduces theirenergy use for relating products Since 2007 the PeoplersquosBank of China has increased the interest rates five times anddecreased the interest rate tax Currently a sixth increase ininterest rates is being considered It can be forecasted that thePeoplersquos Bank of Chinawill still control inflation by increasinginterest rates as price increase further
The shock of industrial growth has a small but long effecton energy price So the demand from industry on energy isone of the reasons that cause a rise in the energy price Butthe effect is slight
The bull stock market can attract a good deal of moneywhich reduces the currency The Chinese stock market hasrisen from 1000 points to 6000 points since 2005 It hasattracted a large amount of money So after the 2008 Olymp-ics or when the appreciated RMB has been realized a lot ofmoney will be taken back from stock market Additionallythere is risk of inflation in the near future Consequently therise in energy price will be severe
44 Energy Price over the Longer Term Has Better Abilityto Explain the Stock Market than Interest Rates From theresults of forecasting decomposition we find that over thelonger term the greatest effect of three factors on stock priceis energy price interest rates and industrial value adding Inthe short term the increase in interest rates is a bad newsand can be perceived easily by all investors So in the shortterm the interest rates are more important than the othertwo factors But in the long term the rise in energy price willbecome gradually apparent to people and have an effect onpeoplersquos anticipation So it will be the more important factorin the longer term As industries are only a part of stockmarket the effects from them on the total market are limitedThere is separation between the real economy and the virtualeconomy in China Consequently it has a poor explanationin explaining fluctuations in the stock market
5 Conclusions and Future Work
Through the analysis of results and discussion we can drawthe following conclusions
(1) There is a stable long-term relationship among energyprice industrial value adding real interest rates andstock price In the longer term the rise in energy pricewill drive up the real interest rates and have an adverseeffect on industrial value adding and the stockmarket
(2) The shocks in energy price have a lasting effect on realinterest rates which to some extent causes long-terminflation The shocks in energy price have a notableeffect on industrial value adding But the effect tendsto be weaker in the long term In the short time the
shocks in energy price have an effect on the stockmarket
(3) To control the rise in energy price we should considerthe macroeconomy and stock market in addition tothe international and domestic energy market Therising industrial value adding increases the energydemand which to some extent increases the energyprice But the rise of interest rates is favorable for con-trolling the energy price
(4) The effect of energy on the stock market is hard toignore Through forecasting the decomposition ofstock prices we can identify that the stock price ischiefly affected by itself What is a contradiction tothe general view is that energy price and interestrates have greater effect on the stock market thanindustrial value adding In the long term energy priceis evenmore important than interest rates It indicatesto investors that they should not only consider theinterest rates but also consider the energy price fortheir investment
This paper discusses the relationship between energyprice and stock market at the macrolevel The relationshipsbetween the shocks of energy price and the stock prices ofvarious industries and oil companies remain to be researchedMeanwhile opportunities for future research include the sim-ulation and analysis of China economic transition and sus-tainable development at various levels of energy price andthe optimal design of subsidy policy for rising oil price [36]
Conflict of Interests
Theauthors of the paper do not have a direct financial relationwith the commercial identity mentioned in this paper thatmight lead to a conflict of interests for any of the authors
Acknowledgments
The authors gratefully acknowledge the good research envi-ronments provided by the Centre for Environmental andClimate Research (CEC) LundUniversityThe authors thankthe anonymous referees for their helpful suggestions and cor-rections on the earlier draft of the paper which improved thecontentsThis research is funded by ldquoBiodiversity and Ecosys-tem services in a Changing Climate (BECC) and SAPESrdquoThe funders had no role in study design data collection andanalysis decision to publish or preparation of the paperThe contents are the responsibility of the authors and do notnecessarily reflect the views of Centre for Environmental andClimate Research (CEC) Lund University
References
[1] K Hanabusa ldquoThe effect of 107th OPEC ordinary meeting onoil prices and economic performances in Japanrdquo Renewable andSustainable Energy Reviews vol 16 pp 1666ndash1672 2012
[2] M RDarby ldquoTheprice of oil andworld inflation and recessionrdquoAmerican Economic Review vol 72 no 4 pp 738ndash751 1982
The Scientific World Journal 9
[3] J D Hamilton ldquoOil and the macroeconomy since World WarIIrdquo Journal of Political Economy vol 91 pp 228ndash248 1983
[4] A F Darrat OW Gilley and D J Meyer ldquoUS oil consumptionoil prices and themacroeconomyrdquo Empirical Economics vol 21no 3 pp 317ndash334 1996
[5] M K Anton ldquoOil and the macroeconomy when prices go upand down an extension of Hamiltonrsquos resultsrdquo Journal of Polit-ical Economy vol 97 pp 740ndash744 1989
[6] S P A Brown and M K Yucel ldquoEnergy prices and aggregateeconomic activity an interpretative surveyrdquo Quarterly Reviewof Economics and Finance vol 42 no 2 pp 193ndash208 2002
[7] M P Clements and H M Krolzig ldquoCan oil shocks explainasymmetries in the US business cyclerdquo Empirical Economicsvol 27 no 2 pp 185ndash204 2002
[8] S Lardic and V Mignon ldquoThe impact of oil prices on GDP inEuropean countries an empirical investigation based on asym-metric cointegrationrdquo Energy Policy vol 34 no 18 pp 3910ndash3915 2006
[9] A Fayyad and K Daly ldquoThe impact of oil price shocks on stockmarket returns comparing GCC countries with the UK andUSArdquo Emerging Markets Review vol 12 no 1 pp 61ndash78 2011
[10] L J Alvarez S Hurtado I Sanchez and C Thomas ldquoTheimpact of oil price changes on Spanish and euro area consumerprice inflationrdquo Economic Modelling vol 28 no 1-2 pp 422ndash431 2011
[11] J B Taylor ldquoThe lack of an empirical rationale for a revival ofdiscretionary fiscal policyrdquo American Economic Review vol 99no 2 pp 550ndash555 2009
[12] J Elder and A Serletis ldquoOil price uncertainty in CanadardquoEnergy Economics vol 31 no 6 pp 852ndash856 2009
[13] S van Wijnbergen ldquoOil price shocks unemployment invest-ment and the current account an intertemporal disequilibriumanalysisrdquo The Review of Economic Studies vol 52 pp 627ndash6451985
[14] N D Uri and R Boyd ldquoEconomic impact of the energy priceincrease in Mexicordquo Environmental and Resource Economicsvol 10 no 1 pp 101ndash107 1997
[15] J L Pierce J J Enzler D I Fand and R J Gordon ldquoThe effectsof external inflationary shocksrdquo Brookings Papers on EconomicActivity vol 5 no 1 pp 13ndash61 1974
[16] K A Mork O Olsen and H T Mysen ldquoMacroeconomic re-sponses to oil price increases and decreases in seven OECDcountriesrdquo Energy Journal vol 15 no 4 pp 19ndash35 1994
[17] J D Sachs R N Cooper and S Fischer ldquoThe current accountand macroeconomic adjustment in the 1970srdquo Brookings Paperson Economic Activity vol 12 no 1 pp 201ndash282 1981
[18] M Erturk ldquoEconomic analysis of unconventional liquid fuelsourcesrdquo Renewable and Sustainable Energy Reviews vol 15 no6 pp 2766ndash2771 2011
[19] N D Uri ldquoCrude oil price volatility and unemployment in theUnited Statesrdquo Energy vol 21 no 1 pp 29ndash38 1996
[20] Y Fan J L Jiao Q M Liang Z Y Han and Y M Wei ldquoTheimpact of rising international crude oil price on Chinarsquos econ-omy an empirical analysiswithCGEmodelrdquo International Jour-nal of Global Energy Issues vol 27 no 4 pp 402ndash424 2007
[21] C M Jones and G Kaul ldquoOil and the stock marketsrdquo Journal ofFinance vol 51 no 2 pp 463ndash491 1996
[22] P Sadorsky ldquoOil price shocks and stock market activityrdquo EnergyEconomics vol 21 no 5 pp 449ndash469 1999
[23] E Papapetrou ldquoOil price shocks stock market economic activ-ity and employment in Greecerdquo Energy Economics vol 23 no5 pp 511ndash532 2001
[24] B T Ewing and M A Thompson ldquoDynamic cyclical comove-ments of oil prices with industrial production consumer pricesunemployment and stock pricesrdquo Energy Policy vol 35 no 11pp 5535ndash5540 2007
[25] R G Cong Y M Wei J L Jiao and Y Fan ldquoRelationships be-tween oil price shocks and stock market an empirical analysisfrom Chinardquo Energy Policy vol 36 no 9 pp 3544ndash3553 2008
[26] R D Huang RWMasulis andH R Stoll ldquoEnergy shocks andfinancial marketsrdquo Journal of Futures Markets vol 16 no 1 pp1ndash27 1996
[27] R W Faff and T J Brailsford ldquoOil price risk and the Australianstock marketrdquo Journal of Energy Finance and Development vol4 pp 69ndash87 1999
[28] S Hammoudeh S Dibooglu and E Aleisa ldquoRelationshipsamong US oil prices and oil industry equity indicesrdquo Interna-tional Review of Economics and Finance vol 13 no 4 pp 427ndash453 2004
[29] P Sadorsky ldquoRisk factors in stock returns of Canadian oil andgas companiesrdquo Energy Economics vol 23 no 1 pp 17ndash28 2001
[30] A Lanza M Manera M Grasso and M Giovannini ldquoLong-run models of oil stock pricesrdquo Environmental Modelling andSoftware vol 20 no 11 pp 1423ndash1430 2005
[31] C A Sims ldquoMacroeconomics and realityrdquo Econometrica vol48 pp 1ndash48 1980
[32] H H Pesaran and Y Shin ldquoGeneralized impulse response anal-ysis in linear multivariate modelsrdquo Economics Letters vol 58no 1 pp 17ndash29 1998
[33] J L Jiao Y Fan and Y M Wei ldquoVECM based analysis ofgasolinediesel prices anti-symmetryrdquo Chinese Journal of Man-agement Science vol 14 pp 97ndash102 2006
[34] N Barberis A Shleifer and R Vishny ldquoA model of investorsentimentrdquo Journal of Financial Economics vol 49 no 3 pp307ndash343 1998
[35] H Hong and J C Stein ldquoA unified theory of underreactionmomentum trading and overreaction in asset marketsrdquo Journalof Finance vol 54 no 6 pp 2143ndash2184 1999
[36] R-G Cong and M Brady ldquoHow to design a targeted agricul-tural subsidy system efficiency or equityrdquo PLoS ONE vol 7Article ID e41225 2012
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
The Scientific World Journal 3
original hypothesis and the alternative hypothesis can bewritten as
1198670 120574 = 0
1198671 120574 lt 0
(2)
The original hypothesis for oil price time series has aunit root which is a nonstationary series The alternativehypothesis is the oil price time series that does not have unitroots which is a stationary series As to nonstationary timeseries another stationary test is needed If the test shows thatthe first-order differentiation is stationary the series is namedas I (1) otherwise the second differentiation should be tested
IP119905 OIL119905 119903119905 and STOCK
119905stand for industry production
oil price nominal interest rates and stock market indexrespectively 119910
where 119901 is lag orders which is determined by AIC andSC information criterion 119879 is the size of the sample1198601 1198602 119860
119901and B are parameter matrices 120576
119905are random
disturbances which can correlate in the same time but cannotcorrelate with their lag variables and the variables on the rightof the functions
If IP119905 OIL119905 119877119905 and STOCK
119905can be tested as the same
number of the unit roots which can be assumed as I (1)we can use JJ method to test whether there are cointegrationamong the series In otherwords whether there are long-termstable relationships among nonstationary variables
Based on VAR model we can also use impulse responsefunctions and forecasting variance decomposition to explainthe model established Impulse response functions can beused to test the effect of a standard variance shock on theendogenous variables and their future values Its fundamentalrationale is as follows
If 119871 is defined as a lag operator 119871119909119905= 119909119905minus1
it can bederived from (3) as follows
(119868119896minus 1198601119871 minus sdot sdot sdot minus 119860
119901119871119901) 119910119905= 120576119905
119910119905= (119868119896minus 1198601119871 minus sdot sdot sdot minus 119860
119901119871119901)minus1
120576119905
= (119868119896+ 1198621119871 + 119862
21198712+ sdot sdot sdot) 120576
119905
(4)
The first variable of 119910119905(industry production) can be writ-
ten as
IP119905= 1199101119905
=
4
sum
119895=1
(119888(0)
1119895120576119895119905+ 119888(1)
1119895120576119895119905minus1
+ sdot sdot sdot) 119905 = 1 2 119879
(5)
where 119888(119902)
1119895is the first row and first line element of 119862
119902 which
can be represented as 119888(119902)1119895
= 120597IP119905+119902
120597120576119895119905 It shows at period
IP119905+119902
rsquos response to a shock of 119910119895119905(IP119905 OIL119905 119903119905 or STOCK
119905)
at the condition that other variables keep constant We refer
to it as the impulse-response function which is similar to theshock multiplier effect analysis As there are correlations inthe same period among various functionsrsquo random variancesin VAR model it needs to construct an orthogonal matrixto transform shocks from correlation in the same period tononcorrelation There are many methods to accomplish thisgoal Here we used general impulse method [32] which doesnot depend on the variablesrsquo orders in VAR model
Variance decomposition decomposes the forecasting var-iances by various variables shocks We can use it to estimatethe importance of various structural shocks Its fundamentallogic is as follows take industrial production as an example Itcan be known from (5) that what is in the brackets is the total120576119895rsquos effect on IP
119905up to now If it can be assumed that there are
not series correlations among 120576119895 the variances are
119864 [(119888(0)
1119895120576119895119905+ 119888(1)
1119895120576119895119905minus1
+ 119888(2)
1119895120576119895119905minus2
+ sdot sdot sdot)2
]
=
infin
sum
119902=0
(119888(119902)
1119895)2
120590119895119895
119895 = 1 2 4
(6)
Additionally if there are no correlations among distur-bances in the same period the variance of IP
119905is the sum of
four variances above mentioned as follows
var (IP119905) =
4
sum
119895=1
infin
sum
119902=0
(119888(119902)
1119895)2
120590119895119895 119905 = 1 2 119879 (7)
Because the variance of IP119905can be decomposed into
four irrelative effect we can define the criterion as followsto measure the contribution of various disturbance to thevariance of IP
119905
RVC119895rarr1
(infin) =
suminfin
119902=0(119888(119902)
1119895)2
120590119895119895
var (IP119905)
=
suminfin
119902=0(119888(119902)
1119895)2
120590119895119895
sum4
119895=1suminfin
119902=0(119888(119902)
1119895)2
120590119895119895
119895 = 1 2 4
(8)
The relative variance contribution (RVC) measures theeffect of the 119895th variable on IP
119905 This paper decomposes each
endogenous variablersquos shock to four parts related to everyfunctionrsquos disturbance which can be used to know the relativeimportance of various shocks to endogenous variables in themodel Comparing the importance varyingwith time we alsoestimate the lag of the variablersquos effect
22 Data Sources In this paper we do not choose oil pricedata Drawing upon lessons from Papapetrou [23] we choosedomestic energy price index Different from commoditiesprice index for fuel that he chose in his paper we choosepurchase price index for fuel power Since Chinese oil pricesare not in accordance with international markets we do notchoose oil spot price or future price in international marketsInterestingly though since June 2006 the home refined oilprice started to adjust in accordance with the movement
4 The Scientific World Journal
Table 1 The test result of unit root
Variables ADF test Test type (119888 119905 119901) Critical valueIP minus2003340 (119888 119905 2) minus3160198lowast
Note 1The meanings of various variables in the table are as follows IP isindustry value added discounted by price index OIL is discounted purchaseprice index for fuel power 119877 stands for real interest rates and STOCK ismonthly price index of Shanghai stock market2119888 119905 and119901 in test type stand for constant trend and lag orders respectively
3At three remarkable levels when ADF value is greater than critical valuecorresponding series has unit root4 lowastlowastlowast lowastlowast and lowast stand for 1 5 and 10 critical levels respectively5119889 stands for the first differential of the variables and1198892 stands for the seconddifferential of the variables
of oil price in international market Based on Jiao et alrsquos[33] research the domestic oil price responded 784 to thechange of crude oil cost and it had a four-month lag Someof the international oil price shocks were absorbed by oilcompanies The purchase energy price index can accuratelyreflect the domestic oil price in a timely manner
Considering that the energy price has a close relationshipto industry we chose industry value adding as a proxy forthe macroeconomy As for the stock market we selected themonthly Chinese Shanghai stock market index and consid-ered the bonus and stock dividend According to traditionalfinancial theory it is generally assumed that the stock priceis equal to the discount of stockrsquos future cash So interestrates are important to stock price Following Sadorsky [22]and Papapetrou [23] we introduce interest rates to dynamicanalysis Interest rates can be divided into nominal interestrates and real interest rates This paper chooses the latter Wehave selected one year to mature a lump deposit for totalwithdrawal as a representative and eliminate the interest taxWith exception of the interest rate data sourced from thewebsite of Bank of China all the data is from the NationalBureau of Statistic of China With due consideration ofavailability of information we selectedmonthly data betweenJanuary 2000 and December 2010 The industry value-addeddata and the energy price data are both adjusted by CensusX12 method and discounted by consumer price index Allthe variables are in logarithmic form As interest rates are inpercentages we define the logarithm of it as log(1 + 119903100)
3 Results and Analysis
31 The Stationary Test of Data In Table 1 ADF test showsthat industrial value added has two unit roots and other vari-ables have a unit root
32 The Determination of Lag Orders Through testing on 1lag order to 5 lag orders AIC and SC can be obtained fromTable 2
Table 2 The choose of lag orders in the model
Lag AIC SC Log 1198710 minus1109981 minus109762 42024271 minus2011605 minus1949806lowast 77435202 minus2036989 minus192575 79987103 minus2037243lowast minus187656 81596624 minus2016755 minus180664 82428315 minus2030166 minus177061 8453124Note lowast above stand for the minimum values in the columns of AIC and SC
Through test iterations we find when the largest lag orderequals to three the AIC reaches the minimum SC reachesthe minimum when the lag order equals to one So LR test ischosen as tradeoff The original hypothesis test is the largestlag order equals to one The testing statistic is as follows
LR = minus2 lowast (1198971minus 1198973) = minus2 lowast (774352 minus 8159662) = 832284
(9)
where 1198971and 1198973are the whole log likelihood function values
when 119901 equals to one and three respectively In the originalhypothesis the statistic has gradually conformed to 120594
2
distribution whose degrees of freedom are thirty-two Theaccompanied probability is 19lowast10
minus6 So we chose a three lagorder VARmodel because the original hypothesis is rejected
33 The Estimation and Test of the Model To give the vari-ables the same integration order we choose the first lag orderto the third lag order values of OIL 119877 STOCK and 119889IP asan alternative of IP as endogenous variables and ordinaryleast squares method to estimate the model The results areas follows
(
119889IP119905
OIL119905
119877119905
STOCK119905
)
= (
minus092lowast
minus0175 073 012lowast
minus0056 127lowast
minus0223 00048
minus011lowast
0118lowast
117lowast
0017
036 minus026 minus148 1056
)(
119889IP119905minus1
OIL119905minus1
119877119905minus1
STOCK119905minus1
)
+(
minus069lowast
019 175 0006
minus002 minus035lowast
minus0163 0008
minus0079lowast
minus014 minus0067 minus0005
minus003 023 182 minus009
)(
119889IP119905minus2
OIL119905minus2
119877119905minus2
STOCK119905minus2
)
+(
minus015 minus0122 minus28lowast
minus02lowast
minus002 004 029 minus0045
minus001 0017 minus019 minus0015
028 018 047 003
)(
119889IP119905minus3
OIL119905minus3
119877119905minus3
STOCK119905minus3
)
+(
105lowast
043lowast
006
minus067
)
(10)
where lowast stands for coefficients that are significant
The Scientific World Journal 5
Table 3 The series cointegration test result
The original hypothesis Eigenvalue Trace statistic (119875 value) 120582-max statistic (119875 value)No cointegration vector 0606545 9620150 (00000)lowast 7369024 (00000)lowast
More than one cointegration vector 0154912 2251127 (02709) 1329684 (04253)More than two cointegration vector 0089195 9214422 (03459) 7380688 (04451)More than three cointegration vector 0022945 1833735 (01757) 1833735 (01757)Note lowast above means that the original hypothesis is significantly rejected
Table 4 The model test results
Stability testThe coefficients of all roots areless than oneSo the model estimated is stable
Autocorrelation LMtest
LM = 1888 (02749)No series autocorrelation
Heteroskedasticitytest
1205942(240) = 2312206 (06462)
No heteroskedasticity
Jarque-Bera normaltest
JB (8) = 711161 (05246)The residual series conform tonormal distribution
As four series in the model are I (1) series the conditionfor cointegration is satisfied The lag order is determinedto 2 Johansen cointegration test result shows that there isa cointegration relationship among four series above whichdemonstrates that there is a prolonged stationary relationshipamong macroeconomy energy price and the stock market(Table 3)
The cointegration can be expressed as
119889IP = minus0037lowastOIL minus 014119877 minus 002
lowastSTOCK + 036 (11)
We can see from the previous equation that in the longerterm the 1 rise in energy price will have an adverse effectof 0037 on industrial value adding and an adverse effect of054 on the stock market
Testing using VAR model obtains the following results(Table 4)
Generally it is difficult to analyze the dynamic relation-ships among variables based on the estimated parametersin the VAR model Consequently we use impulse-responsefunction and variance decomposition to analyze the interac-tive relationships among them
34 Impulse-Response Function and Variance DecompositionFigure 1 shows the impulse-response function curves simu-lated by analytic method based on VAR model
We consider the response of four variables to one SD(standard deviation) innovation of energy price
For one standard deviation innovation of energy price(11 of energy price) interest rate apparently respond In 3months it rises to the peak (02) In 5 months the effectkeeps stable which represents the level of interest rate with a1 stable increase
One standard deviation innovation of energy price to thegrowth rate of industrial value adding has the greatest adverse
effect (02) in 2months Also there is a shock following Butit has a negative convergence trend in the long term
As for one standard deviation innovation of energy pricethe stock price responds adversely to its peak in 3 months(1) But in 6 months the adverse effect disappears
Next we consider the effect of four variablesrsquo shocks onthe energy price index (Figure 2)
One standard deviation shock for interest rate shows thatenergy price is affected most adversely in four months andremains so for a long timeThe residual variances are still halfof its peak in a year
Energy price has little response to one standard deviationshock of industrial value adding
The stock price rises 5 In threemonths the energy pricehas a downward trend Twentymonths later the adverse effecthas reached its minimum value (2)
We decompose the variance to stock market price basedon VAR model and analytic method (above mentioned) Theresults are as follows
In Table 5 the first and seventh columns are the periodsthat are set to a maximum of twenty due to limited spaceThedata in the SE (standard error) column are the forecastingvariance of STOCK in various periods which are caused bythe change of the present or future value 119889IP OIL 119877 andSTOCK are the contribution of the innovations to forecastingvariance respectively which sum to 100 Figure 3 is thevariance decomposition where the periods are prolonged tothirty
It can be seen from Figure 3 that at the first month thestock price can only explain 94 of its forecasting varianceThe energy price can explain 014 the industrial value-added can explain 04 and the change rate of interest ratecan only explain 503 In fifteen months the importance ofenergy price exceeds interest rates At the twentieth monththe interest rates and energy price can explain 77 and 956respectively while the industrial value added can only explain024
4 Discussion
41 There Is a Cointegration among Stock Market Macroecon-omy and Energy Price In this paper we find that there is along-term stable correlation among the stock market macro-economy and energy price Stock market is often said to bethe barometer of onersquosmacroeconomy whichmeans that theyshould have a close relationship But it is a controversial issuein China Chinese scholars generally have two views One isthat the stock market has a weak positive correlation with themacroeconomy The other perspective is that the correlation
6 The Scientific World Journal
00004000800120016
1 2 3 4 5 6 7 8 9 10 11 12
000040008001200160020
1 2 3 4 5 6 7 8 9 10 11 12
000010002000300040005
1 2 3 4 5 6 7 8 9 10 11 12
0001002003004005
1 2 3 4 5 6 7 8 9 10 11 12
Response to cholesky one SD innovations
Response of OIL to OIL
Response of STOCK to OIL
Impulse-response function Impulse-response function
minus0004
minus0004
minus0001
minus0002
minus001
minus002
minus003
minus004
minus0008
minus0012
plusmn2 SEplusmn2 SE
plusmn2 SE
Response of 119889IP to OIL
Response of 119877 to OIL
Figure 1 Generalized impulse responses to one SD shock for energy price changes Note that the horizontal axis is the period The verticalaxis is the explanation level of dependent variables to independent variables In the model we fix the periods at 12 months
Figure 2 Generalized impulse responses of energy price to one SD shock for other variables changes Note that the horizontal axis is theperiodThe vertical axis is the explanation level of dependent variables to independent variables In themodel we fix the periods at 12months
is not significant or is negative Scholars holding this latterview believe that the Chinese stock market aims at financingbut not investingThe stockmarket can not evaluate the valueof companies correctly Therefore the stock market is notthe barometer of the Chinese macroeconomy Based on acapital asset pricing model the real value of stock equals tothe discount of its future cash flows As a result the value
of stock relates to future economy and also is affected bydiscount rates (interest rate) The rising energy price affectsthe Chinese macroeconomy and pushes up the inflation rateThe cointegration obtained in this paper demonstrates thatenergy price has a significant effect on the stock marketwhich is an extension of existing literature In equation (11)we find that in the long-term energy price has a negative
The Scientific World Journal 7
Table 5 Generalized variance decomposition of STOCK
relationship with industrial value adding and the stockmarket The rise in energy price affects the macroeconomyon the one hand and depresses the stock market on the otherhand
42 The Positive Shock of Energy Price Can Push up the RealInterest Rate Affect Industry Productions and Depress theStock Market Price On the basis of realizing the long-termrelationship among them we want to know the response ofstock prices and the macroeconomy to the short-term shockof the energy price Based on impulse response function wehave seen that the positive shock of energy price can push-up the real interest rate affect industry and depress the stockmarket
The shock of energy price can affect real interest rates tosome extent In China since 2002 the international crude oilprice has risen from $20 per barrel to nearly $100 per barrelIn turn this drives up oil related energy products and totalprices Therefore China has the risk of cost-push inflationThe rise of international crude oil price will increase the
domestic price of the refined oil and related chemical engi-neering products The rise of the refined oil price can furtherincrease the price of transportation industrial productionand residential gas Moreover the rise in price of relatedchemical engineering products will increase the cost ofplastic rubber chemical fiber and other inputs Finally thetotal social price level rises Inflation makes the supply ofcurrency relatively insufficientThe controllable real currencyon the whole will decrease Consequently the rise of energyprice will drive up the total interest rate level
As a major input to industry the rise in energy price canaffect economic growth In the Chinese industry chemicalengineering metallurgy and some other energy-intensiveindustries are seriously affected by the rise in oil price How-ever following advances in technology and the upgrading ofindustrial infrastructure the effect becomes less and less inthe long term
The stockmarket is not completely efficient with regard torecognizing energy price There is a phenomenon of under-reaction As a collection of energy-input companies the riseof energy price will increase their cost and decrease theirprofit If the stock market is efficient the rise in energyprice will depress the stock market immediately But in thispaper we find that the rise in energy price will depress thestock market during a five-month lag As the energy pricein the public domain it means there is conservatism in mostinvestorsrsquo decisions as acknowledged by Barberis et al [34]In other words investors find it difficult to renew their viewsand have an underreaction to the importance of the price ofenergy As a limitation in cognitive abilities they find it hardto evaluate the importance of energy price to stock valueThis conforms to the hypothesis that ldquoinformation diffusesgraduallyrdquo suggested by Hong and Stein [35]
43 The Effect on Energy Price of the Industrial Demand In-creasing Interest Rates and the Stock Market We have dis-cussed earlier that the energy price will have a significanteffect on industrial production real interest rates and thestock market But we still want to know the effect of threeshocks on energy price
To control the inflation caused by the rise of energyprice increasing the real interest rate is very efficient It is
8 The Scientific World Journal
because on the one hand high interest rates change peoplersquoscontrollable income by increasing savings and decreasingconsumption on energy relating products and on the otherhand high interest rates will cause the capital to depreciateand reduce peoplersquos wealth which reduces their consump-tion As to industries high interest rates increase their capitalcost and depresse their investment which reduces theirenergy use for relating products Since 2007 the PeoplersquosBank of China has increased the interest rates five times anddecreased the interest rate tax Currently a sixth increase ininterest rates is being considered It can be forecasted that thePeoplersquos Bank of Chinawill still control inflation by increasinginterest rates as price increase further
The shock of industrial growth has a small but long effecton energy price So the demand from industry on energy isone of the reasons that cause a rise in the energy price Butthe effect is slight
The bull stock market can attract a good deal of moneywhich reduces the currency The Chinese stock market hasrisen from 1000 points to 6000 points since 2005 It hasattracted a large amount of money So after the 2008 Olymp-ics or when the appreciated RMB has been realized a lot ofmoney will be taken back from stock market Additionallythere is risk of inflation in the near future Consequently therise in energy price will be severe
44 Energy Price over the Longer Term Has Better Abilityto Explain the Stock Market than Interest Rates From theresults of forecasting decomposition we find that over thelonger term the greatest effect of three factors on stock priceis energy price interest rates and industrial value adding Inthe short term the increase in interest rates is a bad newsand can be perceived easily by all investors So in the shortterm the interest rates are more important than the othertwo factors But in the long term the rise in energy price willbecome gradually apparent to people and have an effect onpeoplersquos anticipation So it will be the more important factorin the longer term As industries are only a part of stockmarket the effects from them on the total market are limitedThere is separation between the real economy and the virtualeconomy in China Consequently it has a poor explanationin explaining fluctuations in the stock market
5 Conclusions and Future Work
Through the analysis of results and discussion we can drawthe following conclusions
(1) There is a stable long-term relationship among energyprice industrial value adding real interest rates andstock price In the longer term the rise in energy pricewill drive up the real interest rates and have an adverseeffect on industrial value adding and the stockmarket
(2) The shocks in energy price have a lasting effect on realinterest rates which to some extent causes long-terminflation The shocks in energy price have a notableeffect on industrial value adding But the effect tendsto be weaker in the long term In the short time the
shocks in energy price have an effect on the stockmarket
(3) To control the rise in energy price we should considerthe macroeconomy and stock market in addition tothe international and domestic energy market Therising industrial value adding increases the energydemand which to some extent increases the energyprice But the rise of interest rates is favorable for con-trolling the energy price
(4) The effect of energy on the stock market is hard toignore Through forecasting the decomposition ofstock prices we can identify that the stock price ischiefly affected by itself What is a contradiction tothe general view is that energy price and interestrates have greater effect on the stock market thanindustrial value adding In the long term energy priceis evenmore important than interest rates It indicatesto investors that they should not only consider theinterest rates but also consider the energy price fortheir investment
This paper discusses the relationship between energyprice and stock market at the macrolevel The relationshipsbetween the shocks of energy price and the stock prices ofvarious industries and oil companies remain to be researchedMeanwhile opportunities for future research include the sim-ulation and analysis of China economic transition and sus-tainable development at various levels of energy price andthe optimal design of subsidy policy for rising oil price [36]
Conflict of Interests
Theauthors of the paper do not have a direct financial relationwith the commercial identity mentioned in this paper thatmight lead to a conflict of interests for any of the authors
Acknowledgments
The authors gratefully acknowledge the good research envi-ronments provided by the Centre for Environmental andClimate Research (CEC) LundUniversityThe authors thankthe anonymous referees for their helpful suggestions and cor-rections on the earlier draft of the paper which improved thecontentsThis research is funded by ldquoBiodiversity and Ecosys-tem services in a Changing Climate (BECC) and SAPESrdquoThe funders had no role in study design data collection andanalysis decision to publish or preparation of the paperThe contents are the responsibility of the authors and do notnecessarily reflect the views of Centre for Environmental andClimate Research (CEC) Lund University
References
[1] K Hanabusa ldquoThe effect of 107th OPEC ordinary meeting onoil prices and economic performances in Japanrdquo Renewable andSustainable Energy Reviews vol 16 pp 1666ndash1672 2012
[2] M RDarby ldquoTheprice of oil andworld inflation and recessionrdquoAmerican Economic Review vol 72 no 4 pp 738ndash751 1982
The Scientific World Journal 9
[3] J D Hamilton ldquoOil and the macroeconomy since World WarIIrdquo Journal of Political Economy vol 91 pp 228ndash248 1983
[4] A F Darrat OW Gilley and D J Meyer ldquoUS oil consumptionoil prices and themacroeconomyrdquo Empirical Economics vol 21no 3 pp 317ndash334 1996
[5] M K Anton ldquoOil and the macroeconomy when prices go upand down an extension of Hamiltonrsquos resultsrdquo Journal of Polit-ical Economy vol 97 pp 740ndash744 1989
[6] S P A Brown and M K Yucel ldquoEnergy prices and aggregateeconomic activity an interpretative surveyrdquo Quarterly Reviewof Economics and Finance vol 42 no 2 pp 193ndash208 2002
[7] M P Clements and H M Krolzig ldquoCan oil shocks explainasymmetries in the US business cyclerdquo Empirical Economicsvol 27 no 2 pp 185ndash204 2002
[8] S Lardic and V Mignon ldquoThe impact of oil prices on GDP inEuropean countries an empirical investigation based on asym-metric cointegrationrdquo Energy Policy vol 34 no 18 pp 3910ndash3915 2006
[9] A Fayyad and K Daly ldquoThe impact of oil price shocks on stockmarket returns comparing GCC countries with the UK andUSArdquo Emerging Markets Review vol 12 no 1 pp 61ndash78 2011
[10] L J Alvarez S Hurtado I Sanchez and C Thomas ldquoTheimpact of oil price changes on Spanish and euro area consumerprice inflationrdquo Economic Modelling vol 28 no 1-2 pp 422ndash431 2011
[11] J B Taylor ldquoThe lack of an empirical rationale for a revival ofdiscretionary fiscal policyrdquo American Economic Review vol 99no 2 pp 550ndash555 2009
[12] J Elder and A Serletis ldquoOil price uncertainty in CanadardquoEnergy Economics vol 31 no 6 pp 852ndash856 2009
[13] S van Wijnbergen ldquoOil price shocks unemployment invest-ment and the current account an intertemporal disequilibriumanalysisrdquo The Review of Economic Studies vol 52 pp 627ndash6451985
[14] N D Uri and R Boyd ldquoEconomic impact of the energy priceincrease in Mexicordquo Environmental and Resource Economicsvol 10 no 1 pp 101ndash107 1997
[15] J L Pierce J J Enzler D I Fand and R J Gordon ldquoThe effectsof external inflationary shocksrdquo Brookings Papers on EconomicActivity vol 5 no 1 pp 13ndash61 1974
[16] K A Mork O Olsen and H T Mysen ldquoMacroeconomic re-sponses to oil price increases and decreases in seven OECDcountriesrdquo Energy Journal vol 15 no 4 pp 19ndash35 1994
[17] J D Sachs R N Cooper and S Fischer ldquoThe current accountand macroeconomic adjustment in the 1970srdquo Brookings Paperson Economic Activity vol 12 no 1 pp 201ndash282 1981
[18] M Erturk ldquoEconomic analysis of unconventional liquid fuelsourcesrdquo Renewable and Sustainable Energy Reviews vol 15 no6 pp 2766ndash2771 2011
[19] N D Uri ldquoCrude oil price volatility and unemployment in theUnited Statesrdquo Energy vol 21 no 1 pp 29ndash38 1996
[20] Y Fan J L Jiao Q M Liang Z Y Han and Y M Wei ldquoTheimpact of rising international crude oil price on Chinarsquos econ-omy an empirical analysiswithCGEmodelrdquo International Jour-nal of Global Energy Issues vol 27 no 4 pp 402ndash424 2007
[21] C M Jones and G Kaul ldquoOil and the stock marketsrdquo Journal ofFinance vol 51 no 2 pp 463ndash491 1996
[22] P Sadorsky ldquoOil price shocks and stock market activityrdquo EnergyEconomics vol 21 no 5 pp 449ndash469 1999
[23] E Papapetrou ldquoOil price shocks stock market economic activ-ity and employment in Greecerdquo Energy Economics vol 23 no5 pp 511ndash532 2001
[24] B T Ewing and M A Thompson ldquoDynamic cyclical comove-ments of oil prices with industrial production consumer pricesunemployment and stock pricesrdquo Energy Policy vol 35 no 11pp 5535ndash5540 2007
[25] R G Cong Y M Wei J L Jiao and Y Fan ldquoRelationships be-tween oil price shocks and stock market an empirical analysisfrom Chinardquo Energy Policy vol 36 no 9 pp 3544ndash3553 2008
[26] R D Huang RWMasulis andH R Stoll ldquoEnergy shocks andfinancial marketsrdquo Journal of Futures Markets vol 16 no 1 pp1ndash27 1996
[27] R W Faff and T J Brailsford ldquoOil price risk and the Australianstock marketrdquo Journal of Energy Finance and Development vol4 pp 69ndash87 1999
[28] S Hammoudeh S Dibooglu and E Aleisa ldquoRelationshipsamong US oil prices and oil industry equity indicesrdquo Interna-tional Review of Economics and Finance vol 13 no 4 pp 427ndash453 2004
[29] P Sadorsky ldquoRisk factors in stock returns of Canadian oil andgas companiesrdquo Energy Economics vol 23 no 1 pp 17ndash28 2001
[30] A Lanza M Manera M Grasso and M Giovannini ldquoLong-run models of oil stock pricesrdquo Environmental Modelling andSoftware vol 20 no 11 pp 1423ndash1430 2005
[31] C A Sims ldquoMacroeconomics and realityrdquo Econometrica vol48 pp 1ndash48 1980
[32] H H Pesaran and Y Shin ldquoGeneralized impulse response anal-ysis in linear multivariate modelsrdquo Economics Letters vol 58no 1 pp 17ndash29 1998
[33] J L Jiao Y Fan and Y M Wei ldquoVECM based analysis ofgasolinediesel prices anti-symmetryrdquo Chinese Journal of Man-agement Science vol 14 pp 97ndash102 2006
[34] N Barberis A Shleifer and R Vishny ldquoA model of investorsentimentrdquo Journal of Financial Economics vol 49 no 3 pp307ndash343 1998
[35] H Hong and J C Stein ldquoA unified theory of underreactionmomentum trading and overreaction in asset marketsrdquo Journalof Finance vol 54 no 6 pp 2143ndash2184 1999
[36] R-G Cong and M Brady ldquoHow to design a targeted agricul-tural subsidy system efficiency or equityrdquo PLoS ONE vol 7Article ID e41225 2012
Note 1The meanings of various variables in the table are as follows IP isindustry value added discounted by price index OIL is discounted purchaseprice index for fuel power 119877 stands for real interest rates and STOCK ismonthly price index of Shanghai stock market2119888 119905 and119901 in test type stand for constant trend and lag orders respectively
3At three remarkable levels when ADF value is greater than critical valuecorresponding series has unit root4 lowastlowastlowast lowastlowast and lowast stand for 1 5 and 10 critical levels respectively5119889 stands for the first differential of the variables and1198892 stands for the seconddifferential of the variables
of oil price in international market Based on Jiao et alrsquos[33] research the domestic oil price responded 784 to thechange of crude oil cost and it had a four-month lag Someof the international oil price shocks were absorbed by oilcompanies The purchase energy price index can accuratelyreflect the domestic oil price in a timely manner
Considering that the energy price has a close relationshipto industry we chose industry value adding as a proxy forthe macroeconomy As for the stock market we selected themonthly Chinese Shanghai stock market index and consid-ered the bonus and stock dividend According to traditionalfinancial theory it is generally assumed that the stock priceis equal to the discount of stockrsquos future cash So interestrates are important to stock price Following Sadorsky [22]and Papapetrou [23] we introduce interest rates to dynamicanalysis Interest rates can be divided into nominal interestrates and real interest rates This paper chooses the latter Wehave selected one year to mature a lump deposit for totalwithdrawal as a representative and eliminate the interest taxWith exception of the interest rate data sourced from thewebsite of Bank of China all the data is from the NationalBureau of Statistic of China With due consideration ofavailability of information we selectedmonthly data betweenJanuary 2000 and December 2010 The industry value-addeddata and the energy price data are both adjusted by CensusX12 method and discounted by consumer price index Allthe variables are in logarithmic form As interest rates are inpercentages we define the logarithm of it as log(1 + 119903100)
3 Results and Analysis
31 The Stationary Test of Data In Table 1 ADF test showsthat industrial value added has two unit roots and other vari-ables have a unit root
32 The Determination of Lag Orders Through testing on 1lag order to 5 lag orders AIC and SC can be obtained fromTable 2
Table 2 The choose of lag orders in the model
Lag AIC SC Log 1198710 minus1109981 minus109762 42024271 minus2011605 minus1949806lowast 77435202 minus2036989 minus192575 79987103 minus2037243lowast minus187656 81596624 minus2016755 minus180664 82428315 minus2030166 minus177061 8453124Note lowast above stand for the minimum values in the columns of AIC and SC
Through test iterations we find when the largest lag orderequals to three the AIC reaches the minimum SC reachesthe minimum when the lag order equals to one So LR test ischosen as tradeoff The original hypothesis test is the largestlag order equals to one The testing statistic is as follows
LR = minus2 lowast (1198971minus 1198973) = minus2 lowast (774352 minus 8159662) = 832284
(9)
where 1198971and 1198973are the whole log likelihood function values
when 119901 equals to one and three respectively In the originalhypothesis the statistic has gradually conformed to 120594
2
distribution whose degrees of freedom are thirty-two Theaccompanied probability is 19lowast10
minus6 So we chose a three lagorder VARmodel because the original hypothesis is rejected
33 The Estimation and Test of the Model To give the vari-ables the same integration order we choose the first lag orderto the third lag order values of OIL 119877 STOCK and 119889IP asan alternative of IP as endogenous variables and ordinaryleast squares method to estimate the model The results areas follows
(
119889IP119905
OIL119905
119877119905
STOCK119905
)
= (
minus092lowast
minus0175 073 012lowast
minus0056 127lowast
minus0223 00048
minus011lowast
0118lowast
117lowast
0017
036 minus026 minus148 1056
)(
119889IP119905minus1
OIL119905minus1
119877119905minus1
STOCK119905minus1
)
+(
minus069lowast
019 175 0006
minus002 minus035lowast
minus0163 0008
minus0079lowast
minus014 minus0067 minus0005
minus003 023 182 minus009
)(
119889IP119905minus2
OIL119905minus2
119877119905minus2
STOCK119905minus2
)
+(
minus015 minus0122 minus28lowast
minus02lowast
minus002 004 029 minus0045
minus001 0017 minus019 minus0015
028 018 047 003
)(
119889IP119905minus3
OIL119905minus3
119877119905minus3
STOCK119905minus3
)
+(
105lowast
043lowast
006
minus067
)
(10)
where lowast stands for coefficients that are significant
The Scientific World Journal 5
Table 3 The series cointegration test result
The original hypothesis Eigenvalue Trace statistic (119875 value) 120582-max statistic (119875 value)No cointegration vector 0606545 9620150 (00000)lowast 7369024 (00000)lowast
More than one cointegration vector 0154912 2251127 (02709) 1329684 (04253)More than two cointegration vector 0089195 9214422 (03459) 7380688 (04451)More than three cointegration vector 0022945 1833735 (01757) 1833735 (01757)Note lowast above means that the original hypothesis is significantly rejected
Table 4 The model test results
Stability testThe coefficients of all roots areless than oneSo the model estimated is stable
Autocorrelation LMtest
LM = 1888 (02749)No series autocorrelation
Heteroskedasticitytest
1205942(240) = 2312206 (06462)
No heteroskedasticity
Jarque-Bera normaltest
JB (8) = 711161 (05246)The residual series conform tonormal distribution
As four series in the model are I (1) series the conditionfor cointegration is satisfied The lag order is determinedto 2 Johansen cointegration test result shows that there isa cointegration relationship among four series above whichdemonstrates that there is a prolonged stationary relationshipamong macroeconomy energy price and the stock market(Table 3)
The cointegration can be expressed as
119889IP = minus0037lowastOIL minus 014119877 minus 002
lowastSTOCK + 036 (11)
We can see from the previous equation that in the longerterm the 1 rise in energy price will have an adverse effectof 0037 on industrial value adding and an adverse effect of054 on the stock market
Testing using VAR model obtains the following results(Table 4)
Generally it is difficult to analyze the dynamic relation-ships among variables based on the estimated parametersin the VAR model Consequently we use impulse-responsefunction and variance decomposition to analyze the interac-tive relationships among them
34 Impulse-Response Function and Variance DecompositionFigure 1 shows the impulse-response function curves simu-lated by analytic method based on VAR model
We consider the response of four variables to one SD(standard deviation) innovation of energy price
For one standard deviation innovation of energy price(11 of energy price) interest rate apparently respond In 3months it rises to the peak (02) In 5 months the effectkeeps stable which represents the level of interest rate with a1 stable increase
One standard deviation innovation of energy price to thegrowth rate of industrial value adding has the greatest adverse
effect (02) in 2months Also there is a shock following Butit has a negative convergence trend in the long term
As for one standard deviation innovation of energy pricethe stock price responds adversely to its peak in 3 months(1) But in 6 months the adverse effect disappears
Next we consider the effect of four variablesrsquo shocks onthe energy price index (Figure 2)
One standard deviation shock for interest rate shows thatenergy price is affected most adversely in four months andremains so for a long timeThe residual variances are still halfof its peak in a year
Energy price has little response to one standard deviationshock of industrial value adding
The stock price rises 5 In threemonths the energy pricehas a downward trend Twentymonths later the adverse effecthas reached its minimum value (2)
We decompose the variance to stock market price basedon VAR model and analytic method (above mentioned) Theresults are as follows
In Table 5 the first and seventh columns are the periodsthat are set to a maximum of twenty due to limited spaceThedata in the SE (standard error) column are the forecastingvariance of STOCK in various periods which are caused bythe change of the present or future value 119889IP OIL 119877 andSTOCK are the contribution of the innovations to forecastingvariance respectively which sum to 100 Figure 3 is thevariance decomposition where the periods are prolonged tothirty
It can be seen from Figure 3 that at the first month thestock price can only explain 94 of its forecasting varianceThe energy price can explain 014 the industrial value-added can explain 04 and the change rate of interest ratecan only explain 503 In fifteen months the importance ofenergy price exceeds interest rates At the twentieth monththe interest rates and energy price can explain 77 and 956respectively while the industrial value added can only explain024
4 Discussion
41 There Is a Cointegration among Stock Market Macroecon-omy and Energy Price In this paper we find that there is along-term stable correlation among the stock market macro-economy and energy price Stock market is often said to bethe barometer of onersquosmacroeconomy whichmeans that theyshould have a close relationship But it is a controversial issuein China Chinese scholars generally have two views One isthat the stock market has a weak positive correlation with themacroeconomy The other perspective is that the correlation
6 The Scientific World Journal
00004000800120016
1 2 3 4 5 6 7 8 9 10 11 12
000040008001200160020
1 2 3 4 5 6 7 8 9 10 11 12
000010002000300040005
1 2 3 4 5 6 7 8 9 10 11 12
0001002003004005
1 2 3 4 5 6 7 8 9 10 11 12
Response to cholesky one SD innovations
Response of OIL to OIL
Response of STOCK to OIL
Impulse-response function Impulse-response function
minus0004
minus0004
minus0001
minus0002
minus001
minus002
minus003
minus004
minus0008
minus0012
plusmn2 SEplusmn2 SE
plusmn2 SE
Response of 119889IP to OIL
Response of 119877 to OIL
Figure 1 Generalized impulse responses to one SD shock for energy price changes Note that the horizontal axis is the period The verticalaxis is the explanation level of dependent variables to independent variables In the model we fix the periods at 12 months
Figure 2 Generalized impulse responses of energy price to one SD shock for other variables changes Note that the horizontal axis is theperiodThe vertical axis is the explanation level of dependent variables to independent variables In themodel we fix the periods at 12months
is not significant or is negative Scholars holding this latterview believe that the Chinese stock market aims at financingbut not investingThe stockmarket can not evaluate the valueof companies correctly Therefore the stock market is notthe barometer of the Chinese macroeconomy Based on acapital asset pricing model the real value of stock equals tothe discount of its future cash flows As a result the value
of stock relates to future economy and also is affected bydiscount rates (interest rate) The rising energy price affectsthe Chinese macroeconomy and pushes up the inflation rateThe cointegration obtained in this paper demonstrates thatenergy price has a significant effect on the stock marketwhich is an extension of existing literature In equation (11)we find that in the long-term energy price has a negative
The Scientific World Journal 7
Table 5 Generalized variance decomposition of STOCK
relationship with industrial value adding and the stockmarket The rise in energy price affects the macroeconomyon the one hand and depresses the stock market on the otherhand
42 The Positive Shock of Energy Price Can Push up the RealInterest Rate Affect Industry Productions and Depress theStock Market Price On the basis of realizing the long-termrelationship among them we want to know the response ofstock prices and the macroeconomy to the short-term shockof the energy price Based on impulse response function wehave seen that the positive shock of energy price can push-up the real interest rate affect industry and depress the stockmarket
The shock of energy price can affect real interest rates tosome extent In China since 2002 the international crude oilprice has risen from $20 per barrel to nearly $100 per barrelIn turn this drives up oil related energy products and totalprices Therefore China has the risk of cost-push inflationThe rise of international crude oil price will increase the
domestic price of the refined oil and related chemical engi-neering products The rise of the refined oil price can furtherincrease the price of transportation industrial productionand residential gas Moreover the rise in price of relatedchemical engineering products will increase the cost ofplastic rubber chemical fiber and other inputs Finally thetotal social price level rises Inflation makes the supply ofcurrency relatively insufficientThe controllable real currencyon the whole will decrease Consequently the rise of energyprice will drive up the total interest rate level
As a major input to industry the rise in energy price canaffect economic growth In the Chinese industry chemicalengineering metallurgy and some other energy-intensiveindustries are seriously affected by the rise in oil price How-ever following advances in technology and the upgrading ofindustrial infrastructure the effect becomes less and less inthe long term
The stockmarket is not completely efficient with regard torecognizing energy price There is a phenomenon of under-reaction As a collection of energy-input companies the riseof energy price will increase their cost and decrease theirprofit If the stock market is efficient the rise in energyprice will depress the stock market immediately But in thispaper we find that the rise in energy price will depress thestock market during a five-month lag As the energy pricein the public domain it means there is conservatism in mostinvestorsrsquo decisions as acknowledged by Barberis et al [34]In other words investors find it difficult to renew their viewsand have an underreaction to the importance of the price ofenergy As a limitation in cognitive abilities they find it hardto evaluate the importance of energy price to stock valueThis conforms to the hypothesis that ldquoinformation diffusesgraduallyrdquo suggested by Hong and Stein [35]
43 The Effect on Energy Price of the Industrial Demand In-creasing Interest Rates and the Stock Market We have dis-cussed earlier that the energy price will have a significanteffect on industrial production real interest rates and thestock market But we still want to know the effect of threeshocks on energy price
To control the inflation caused by the rise of energyprice increasing the real interest rate is very efficient It is
8 The Scientific World Journal
because on the one hand high interest rates change peoplersquoscontrollable income by increasing savings and decreasingconsumption on energy relating products and on the otherhand high interest rates will cause the capital to depreciateand reduce peoplersquos wealth which reduces their consump-tion As to industries high interest rates increase their capitalcost and depresse their investment which reduces theirenergy use for relating products Since 2007 the PeoplersquosBank of China has increased the interest rates five times anddecreased the interest rate tax Currently a sixth increase ininterest rates is being considered It can be forecasted that thePeoplersquos Bank of Chinawill still control inflation by increasinginterest rates as price increase further
The shock of industrial growth has a small but long effecton energy price So the demand from industry on energy isone of the reasons that cause a rise in the energy price Butthe effect is slight
The bull stock market can attract a good deal of moneywhich reduces the currency The Chinese stock market hasrisen from 1000 points to 6000 points since 2005 It hasattracted a large amount of money So after the 2008 Olymp-ics or when the appreciated RMB has been realized a lot ofmoney will be taken back from stock market Additionallythere is risk of inflation in the near future Consequently therise in energy price will be severe
44 Energy Price over the Longer Term Has Better Abilityto Explain the Stock Market than Interest Rates From theresults of forecasting decomposition we find that over thelonger term the greatest effect of three factors on stock priceis energy price interest rates and industrial value adding Inthe short term the increase in interest rates is a bad newsand can be perceived easily by all investors So in the shortterm the interest rates are more important than the othertwo factors But in the long term the rise in energy price willbecome gradually apparent to people and have an effect onpeoplersquos anticipation So it will be the more important factorin the longer term As industries are only a part of stockmarket the effects from them on the total market are limitedThere is separation between the real economy and the virtualeconomy in China Consequently it has a poor explanationin explaining fluctuations in the stock market
5 Conclusions and Future Work
Through the analysis of results and discussion we can drawthe following conclusions
(1) There is a stable long-term relationship among energyprice industrial value adding real interest rates andstock price In the longer term the rise in energy pricewill drive up the real interest rates and have an adverseeffect on industrial value adding and the stockmarket
(2) The shocks in energy price have a lasting effect on realinterest rates which to some extent causes long-terminflation The shocks in energy price have a notableeffect on industrial value adding But the effect tendsto be weaker in the long term In the short time the
shocks in energy price have an effect on the stockmarket
(3) To control the rise in energy price we should considerthe macroeconomy and stock market in addition tothe international and domestic energy market Therising industrial value adding increases the energydemand which to some extent increases the energyprice But the rise of interest rates is favorable for con-trolling the energy price
(4) The effect of energy on the stock market is hard toignore Through forecasting the decomposition ofstock prices we can identify that the stock price ischiefly affected by itself What is a contradiction tothe general view is that energy price and interestrates have greater effect on the stock market thanindustrial value adding In the long term energy priceis evenmore important than interest rates It indicatesto investors that they should not only consider theinterest rates but also consider the energy price fortheir investment
This paper discusses the relationship between energyprice and stock market at the macrolevel The relationshipsbetween the shocks of energy price and the stock prices ofvarious industries and oil companies remain to be researchedMeanwhile opportunities for future research include the sim-ulation and analysis of China economic transition and sus-tainable development at various levels of energy price andthe optimal design of subsidy policy for rising oil price [36]
Conflict of Interests
Theauthors of the paper do not have a direct financial relationwith the commercial identity mentioned in this paper thatmight lead to a conflict of interests for any of the authors
Acknowledgments
The authors gratefully acknowledge the good research envi-ronments provided by the Centre for Environmental andClimate Research (CEC) LundUniversityThe authors thankthe anonymous referees for their helpful suggestions and cor-rections on the earlier draft of the paper which improved thecontentsThis research is funded by ldquoBiodiversity and Ecosys-tem services in a Changing Climate (BECC) and SAPESrdquoThe funders had no role in study design data collection andanalysis decision to publish or preparation of the paperThe contents are the responsibility of the authors and do notnecessarily reflect the views of Centre for Environmental andClimate Research (CEC) Lund University
References
[1] K Hanabusa ldquoThe effect of 107th OPEC ordinary meeting onoil prices and economic performances in Japanrdquo Renewable andSustainable Energy Reviews vol 16 pp 1666ndash1672 2012
[2] M RDarby ldquoTheprice of oil andworld inflation and recessionrdquoAmerican Economic Review vol 72 no 4 pp 738ndash751 1982
The Scientific World Journal 9
[3] J D Hamilton ldquoOil and the macroeconomy since World WarIIrdquo Journal of Political Economy vol 91 pp 228ndash248 1983
[4] A F Darrat OW Gilley and D J Meyer ldquoUS oil consumptionoil prices and themacroeconomyrdquo Empirical Economics vol 21no 3 pp 317ndash334 1996
[5] M K Anton ldquoOil and the macroeconomy when prices go upand down an extension of Hamiltonrsquos resultsrdquo Journal of Polit-ical Economy vol 97 pp 740ndash744 1989
[6] S P A Brown and M K Yucel ldquoEnergy prices and aggregateeconomic activity an interpretative surveyrdquo Quarterly Reviewof Economics and Finance vol 42 no 2 pp 193ndash208 2002
[7] M P Clements and H M Krolzig ldquoCan oil shocks explainasymmetries in the US business cyclerdquo Empirical Economicsvol 27 no 2 pp 185ndash204 2002
[8] S Lardic and V Mignon ldquoThe impact of oil prices on GDP inEuropean countries an empirical investigation based on asym-metric cointegrationrdquo Energy Policy vol 34 no 18 pp 3910ndash3915 2006
[9] A Fayyad and K Daly ldquoThe impact of oil price shocks on stockmarket returns comparing GCC countries with the UK andUSArdquo Emerging Markets Review vol 12 no 1 pp 61ndash78 2011
[10] L J Alvarez S Hurtado I Sanchez and C Thomas ldquoTheimpact of oil price changes on Spanish and euro area consumerprice inflationrdquo Economic Modelling vol 28 no 1-2 pp 422ndash431 2011
[11] J B Taylor ldquoThe lack of an empirical rationale for a revival ofdiscretionary fiscal policyrdquo American Economic Review vol 99no 2 pp 550ndash555 2009
[12] J Elder and A Serletis ldquoOil price uncertainty in CanadardquoEnergy Economics vol 31 no 6 pp 852ndash856 2009
[13] S van Wijnbergen ldquoOil price shocks unemployment invest-ment and the current account an intertemporal disequilibriumanalysisrdquo The Review of Economic Studies vol 52 pp 627ndash6451985
[14] N D Uri and R Boyd ldquoEconomic impact of the energy priceincrease in Mexicordquo Environmental and Resource Economicsvol 10 no 1 pp 101ndash107 1997
[15] J L Pierce J J Enzler D I Fand and R J Gordon ldquoThe effectsof external inflationary shocksrdquo Brookings Papers on EconomicActivity vol 5 no 1 pp 13ndash61 1974
[16] K A Mork O Olsen and H T Mysen ldquoMacroeconomic re-sponses to oil price increases and decreases in seven OECDcountriesrdquo Energy Journal vol 15 no 4 pp 19ndash35 1994
[17] J D Sachs R N Cooper and S Fischer ldquoThe current accountand macroeconomic adjustment in the 1970srdquo Brookings Paperson Economic Activity vol 12 no 1 pp 201ndash282 1981
[18] M Erturk ldquoEconomic analysis of unconventional liquid fuelsourcesrdquo Renewable and Sustainable Energy Reviews vol 15 no6 pp 2766ndash2771 2011
[19] N D Uri ldquoCrude oil price volatility and unemployment in theUnited Statesrdquo Energy vol 21 no 1 pp 29ndash38 1996
[20] Y Fan J L Jiao Q M Liang Z Y Han and Y M Wei ldquoTheimpact of rising international crude oil price on Chinarsquos econ-omy an empirical analysiswithCGEmodelrdquo International Jour-nal of Global Energy Issues vol 27 no 4 pp 402ndash424 2007
[21] C M Jones and G Kaul ldquoOil and the stock marketsrdquo Journal ofFinance vol 51 no 2 pp 463ndash491 1996
[22] P Sadorsky ldquoOil price shocks and stock market activityrdquo EnergyEconomics vol 21 no 5 pp 449ndash469 1999
[23] E Papapetrou ldquoOil price shocks stock market economic activ-ity and employment in Greecerdquo Energy Economics vol 23 no5 pp 511ndash532 2001
[24] B T Ewing and M A Thompson ldquoDynamic cyclical comove-ments of oil prices with industrial production consumer pricesunemployment and stock pricesrdquo Energy Policy vol 35 no 11pp 5535ndash5540 2007
[25] R G Cong Y M Wei J L Jiao and Y Fan ldquoRelationships be-tween oil price shocks and stock market an empirical analysisfrom Chinardquo Energy Policy vol 36 no 9 pp 3544ndash3553 2008
[26] R D Huang RWMasulis andH R Stoll ldquoEnergy shocks andfinancial marketsrdquo Journal of Futures Markets vol 16 no 1 pp1ndash27 1996
[27] R W Faff and T J Brailsford ldquoOil price risk and the Australianstock marketrdquo Journal of Energy Finance and Development vol4 pp 69ndash87 1999
[28] S Hammoudeh S Dibooglu and E Aleisa ldquoRelationshipsamong US oil prices and oil industry equity indicesrdquo Interna-tional Review of Economics and Finance vol 13 no 4 pp 427ndash453 2004
[29] P Sadorsky ldquoRisk factors in stock returns of Canadian oil andgas companiesrdquo Energy Economics vol 23 no 1 pp 17ndash28 2001
[30] A Lanza M Manera M Grasso and M Giovannini ldquoLong-run models of oil stock pricesrdquo Environmental Modelling andSoftware vol 20 no 11 pp 1423ndash1430 2005
[31] C A Sims ldquoMacroeconomics and realityrdquo Econometrica vol48 pp 1ndash48 1980
[32] H H Pesaran and Y Shin ldquoGeneralized impulse response anal-ysis in linear multivariate modelsrdquo Economics Letters vol 58no 1 pp 17ndash29 1998
[33] J L Jiao Y Fan and Y M Wei ldquoVECM based analysis ofgasolinediesel prices anti-symmetryrdquo Chinese Journal of Man-agement Science vol 14 pp 97ndash102 2006
[34] N Barberis A Shleifer and R Vishny ldquoA model of investorsentimentrdquo Journal of Financial Economics vol 49 no 3 pp307ndash343 1998
[35] H Hong and J C Stein ldquoA unified theory of underreactionmomentum trading and overreaction in asset marketsrdquo Journalof Finance vol 54 no 6 pp 2143ndash2184 1999
[36] R-G Cong and M Brady ldquoHow to design a targeted agricul-tural subsidy system efficiency or equityrdquo PLoS ONE vol 7Article ID e41225 2012
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
The Scientific World Journal 5
Table 3 The series cointegration test result
The original hypothesis Eigenvalue Trace statistic (119875 value) 120582-max statistic (119875 value)No cointegration vector 0606545 9620150 (00000)lowast 7369024 (00000)lowast
More than one cointegration vector 0154912 2251127 (02709) 1329684 (04253)More than two cointegration vector 0089195 9214422 (03459) 7380688 (04451)More than three cointegration vector 0022945 1833735 (01757) 1833735 (01757)Note lowast above means that the original hypothesis is significantly rejected
Table 4 The model test results
Stability testThe coefficients of all roots areless than oneSo the model estimated is stable
Autocorrelation LMtest
LM = 1888 (02749)No series autocorrelation
Heteroskedasticitytest
1205942(240) = 2312206 (06462)
No heteroskedasticity
Jarque-Bera normaltest
JB (8) = 711161 (05246)The residual series conform tonormal distribution
As four series in the model are I (1) series the conditionfor cointegration is satisfied The lag order is determinedto 2 Johansen cointegration test result shows that there isa cointegration relationship among four series above whichdemonstrates that there is a prolonged stationary relationshipamong macroeconomy energy price and the stock market(Table 3)
The cointegration can be expressed as
119889IP = minus0037lowastOIL minus 014119877 minus 002
lowastSTOCK + 036 (11)
We can see from the previous equation that in the longerterm the 1 rise in energy price will have an adverse effectof 0037 on industrial value adding and an adverse effect of054 on the stock market
Testing using VAR model obtains the following results(Table 4)
Generally it is difficult to analyze the dynamic relation-ships among variables based on the estimated parametersin the VAR model Consequently we use impulse-responsefunction and variance decomposition to analyze the interac-tive relationships among them
34 Impulse-Response Function and Variance DecompositionFigure 1 shows the impulse-response function curves simu-lated by analytic method based on VAR model
We consider the response of four variables to one SD(standard deviation) innovation of energy price
For one standard deviation innovation of energy price(11 of energy price) interest rate apparently respond In 3months it rises to the peak (02) In 5 months the effectkeeps stable which represents the level of interest rate with a1 stable increase
One standard deviation innovation of energy price to thegrowth rate of industrial value adding has the greatest adverse
effect (02) in 2months Also there is a shock following Butit has a negative convergence trend in the long term
As for one standard deviation innovation of energy pricethe stock price responds adversely to its peak in 3 months(1) But in 6 months the adverse effect disappears
Next we consider the effect of four variablesrsquo shocks onthe energy price index (Figure 2)
One standard deviation shock for interest rate shows thatenergy price is affected most adversely in four months andremains so for a long timeThe residual variances are still halfof its peak in a year
Energy price has little response to one standard deviationshock of industrial value adding
The stock price rises 5 In threemonths the energy pricehas a downward trend Twentymonths later the adverse effecthas reached its minimum value (2)
We decompose the variance to stock market price basedon VAR model and analytic method (above mentioned) Theresults are as follows
In Table 5 the first and seventh columns are the periodsthat are set to a maximum of twenty due to limited spaceThedata in the SE (standard error) column are the forecastingvariance of STOCK in various periods which are caused bythe change of the present or future value 119889IP OIL 119877 andSTOCK are the contribution of the innovations to forecastingvariance respectively which sum to 100 Figure 3 is thevariance decomposition where the periods are prolonged tothirty
It can be seen from Figure 3 that at the first month thestock price can only explain 94 of its forecasting varianceThe energy price can explain 014 the industrial value-added can explain 04 and the change rate of interest ratecan only explain 503 In fifteen months the importance ofenergy price exceeds interest rates At the twentieth monththe interest rates and energy price can explain 77 and 956respectively while the industrial value added can only explain024
4 Discussion
41 There Is a Cointegration among Stock Market Macroecon-omy and Energy Price In this paper we find that there is along-term stable correlation among the stock market macro-economy and energy price Stock market is often said to bethe barometer of onersquosmacroeconomy whichmeans that theyshould have a close relationship But it is a controversial issuein China Chinese scholars generally have two views One isthat the stock market has a weak positive correlation with themacroeconomy The other perspective is that the correlation
6 The Scientific World Journal
00004000800120016
1 2 3 4 5 6 7 8 9 10 11 12
000040008001200160020
1 2 3 4 5 6 7 8 9 10 11 12
000010002000300040005
1 2 3 4 5 6 7 8 9 10 11 12
0001002003004005
1 2 3 4 5 6 7 8 9 10 11 12
Response to cholesky one SD innovations
Response of OIL to OIL
Response of STOCK to OIL
Impulse-response function Impulse-response function
minus0004
minus0004
minus0001
minus0002
minus001
minus002
minus003
minus004
minus0008
minus0012
plusmn2 SEplusmn2 SE
plusmn2 SE
Response of 119889IP to OIL
Response of 119877 to OIL
Figure 1 Generalized impulse responses to one SD shock for energy price changes Note that the horizontal axis is the period The verticalaxis is the explanation level of dependent variables to independent variables In the model we fix the periods at 12 months
Figure 2 Generalized impulse responses of energy price to one SD shock for other variables changes Note that the horizontal axis is theperiodThe vertical axis is the explanation level of dependent variables to independent variables In themodel we fix the periods at 12months
is not significant or is negative Scholars holding this latterview believe that the Chinese stock market aims at financingbut not investingThe stockmarket can not evaluate the valueof companies correctly Therefore the stock market is notthe barometer of the Chinese macroeconomy Based on acapital asset pricing model the real value of stock equals tothe discount of its future cash flows As a result the value
of stock relates to future economy and also is affected bydiscount rates (interest rate) The rising energy price affectsthe Chinese macroeconomy and pushes up the inflation rateThe cointegration obtained in this paper demonstrates thatenergy price has a significant effect on the stock marketwhich is an extension of existing literature In equation (11)we find that in the long-term energy price has a negative
The Scientific World Journal 7
Table 5 Generalized variance decomposition of STOCK
relationship with industrial value adding and the stockmarket The rise in energy price affects the macroeconomyon the one hand and depresses the stock market on the otherhand
42 The Positive Shock of Energy Price Can Push up the RealInterest Rate Affect Industry Productions and Depress theStock Market Price On the basis of realizing the long-termrelationship among them we want to know the response ofstock prices and the macroeconomy to the short-term shockof the energy price Based on impulse response function wehave seen that the positive shock of energy price can push-up the real interest rate affect industry and depress the stockmarket
The shock of energy price can affect real interest rates tosome extent In China since 2002 the international crude oilprice has risen from $20 per barrel to nearly $100 per barrelIn turn this drives up oil related energy products and totalprices Therefore China has the risk of cost-push inflationThe rise of international crude oil price will increase the
domestic price of the refined oil and related chemical engi-neering products The rise of the refined oil price can furtherincrease the price of transportation industrial productionand residential gas Moreover the rise in price of relatedchemical engineering products will increase the cost ofplastic rubber chemical fiber and other inputs Finally thetotal social price level rises Inflation makes the supply ofcurrency relatively insufficientThe controllable real currencyon the whole will decrease Consequently the rise of energyprice will drive up the total interest rate level
As a major input to industry the rise in energy price canaffect economic growth In the Chinese industry chemicalengineering metallurgy and some other energy-intensiveindustries are seriously affected by the rise in oil price How-ever following advances in technology and the upgrading ofindustrial infrastructure the effect becomes less and less inthe long term
The stockmarket is not completely efficient with regard torecognizing energy price There is a phenomenon of under-reaction As a collection of energy-input companies the riseof energy price will increase their cost and decrease theirprofit If the stock market is efficient the rise in energyprice will depress the stock market immediately But in thispaper we find that the rise in energy price will depress thestock market during a five-month lag As the energy pricein the public domain it means there is conservatism in mostinvestorsrsquo decisions as acknowledged by Barberis et al [34]In other words investors find it difficult to renew their viewsand have an underreaction to the importance of the price ofenergy As a limitation in cognitive abilities they find it hardto evaluate the importance of energy price to stock valueThis conforms to the hypothesis that ldquoinformation diffusesgraduallyrdquo suggested by Hong and Stein [35]
43 The Effect on Energy Price of the Industrial Demand In-creasing Interest Rates and the Stock Market We have dis-cussed earlier that the energy price will have a significanteffect on industrial production real interest rates and thestock market But we still want to know the effect of threeshocks on energy price
To control the inflation caused by the rise of energyprice increasing the real interest rate is very efficient It is
8 The Scientific World Journal
because on the one hand high interest rates change peoplersquoscontrollable income by increasing savings and decreasingconsumption on energy relating products and on the otherhand high interest rates will cause the capital to depreciateand reduce peoplersquos wealth which reduces their consump-tion As to industries high interest rates increase their capitalcost and depresse their investment which reduces theirenergy use for relating products Since 2007 the PeoplersquosBank of China has increased the interest rates five times anddecreased the interest rate tax Currently a sixth increase ininterest rates is being considered It can be forecasted that thePeoplersquos Bank of Chinawill still control inflation by increasinginterest rates as price increase further
The shock of industrial growth has a small but long effecton energy price So the demand from industry on energy isone of the reasons that cause a rise in the energy price Butthe effect is slight
The bull stock market can attract a good deal of moneywhich reduces the currency The Chinese stock market hasrisen from 1000 points to 6000 points since 2005 It hasattracted a large amount of money So after the 2008 Olymp-ics or when the appreciated RMB has been realized a lot ofmoney will be taken back from stock market Additionallythere is risk of inflation in the near future Consequently therise in energy price will be severe
44 Energy Price over the Longer Term Has Better Abilityto Explain the Stock Market than Interest Rates From theresults of forecasting decomposition we find that over thelonger term the greatest effect of three factors on stock priceis energy price interest rates and industrial value adding Inthe short term the increase in interest rates is a bad newsand can be perceived easily by all investors So in the shortterm the interest rates are more important than the othertwo factors But in the long term the rise in energy price willbecome gradually apparent to people and have an effect onpeoplersquos anticipation So it will be the more important factorin the longer term As industries are only a part of stockmarket the effects from them on the total market are limitedThere is separation between the real economy and the virtualeconomy in China Consequently it has a poor explanationin explaining fluctuations in the stock market
5 Conclusions and Future Work
Through the analysis of results and discussion we can drawthe following conclusions
(1) There is a stable long-term relationship among energyprice industrial value adding real interest rates andstock price In the longer term the rise in energy pricewill drive up the real interest rates and have an adverseeffect on industrial value adding and the stockmarket
(2) The shocks in energy price have a lasting effect on realinterest rates which to some extent causes long-terminflation The shocks in energy price have a notableeffect on industrial value adding But the effect tendsto be weaker in the long term In the short time the
shocks in energy price have an effect on the stockmarket
(3) To control the rise in energy price we should considerthe macroeconomy and stock market in addition tothe international and domestic energy market Therising industrial value adding increases the energydemand which to some extent increases the energyprice But the rise of interest rates is favorable for con-trolling the energy price
(4) The effect of energy on the stock market is hard toignore Through forecasting the decomposition ofstock prices we can identify that the stock price ischiefly affected by itself What is a contradiction tothe general view is that energy price and interestrates have greater effect on the stock market thanindustrial value adding In the long term energy priceis evenmore important than interest rates It indicatesto investors that they should not only consider theinterest rates but also consider the energy price fortheir investment
This paper discusses the relationship between energyprice and stock market at the macrolevel The relationshipsbetween the shocks of energy price and the stock prices ofvarious industries and oil companies remain to be researchedMeanwhile opportunities for future research include the sim-ulation and analysis of China economic transition and sus-tainable development at various levels of energy price andthe optimal design of subsidy policy for rising oil price [36]
Conflict of Interests
Theauthors of the paper do not have a direct financial relationwith the commercial identity mentioned in this paper thatmight lead to a conflict of interests for any of the authors
Acknowledgments
The authors gratefully acknowledge the good research envi-ronments provided by the Centre for Environmental andClimate Research (CEC) LundUniversityThe authors thankthe anonymous referees for their helpful suggestions and cor-rections on the earlier draft of the paper which improved thecontentsThis research is funded by ldquoBiodiversity and Ecosys-tem services in a Changing Climate (BECC) and SAPESrdquoThe funders had no role in study design data collection andanalysis decision to publish or preparation of the paperThe contents are the responsibility of the authors and do notnecessarily reflect the views of Centre for Environmental andClimate Research (CEC) Lund University
References
[1] K Hanabusa ldquoThe effect of 107th OPEC ordinary meeting onoil prices and economic performances in Japanrdquo Renewable andSustainable Energy Reviews vol 16 pp 1666ndash1672 2012
[2] M RDarby ldquoTheprice of oil andworld inflation and recessionrdquoAmerican Economic Review vol 72 no 4 pp 738ndash751 1982
The Scientific World Journal 9
[3] J D Hamilton ldquoOil and the macroeconomy since World WarIIrdquo Journal of Political Economy vol 91 pp 228ndash248 1983
[4] A F Darrat OW Gilley and D J Meyer ldquoUS oil consumptionoil prices and themacroeconomyrdquo Empirical Economics vol 21no 3 pp 317ndash334 1996
[5] M K Anton ldquoOil and the macroeconomy when prices go upand down an extension of Hamiltonrsquos resultsrdquo Journal of Polit-ical Economy vol 97 pp 740ndash744 1989
[6] S P A Brown and M K Yucel ldquoEnergy prices and aggregateeconomic activity an interpretative surveyrdquo Quarterly Reviewof Economics and Finance vol 42 no 2 pp 193ndash208 2002
[7] M P Clements and H M Krolzig ldquoCan oil shocks explainasymmetries in the US business cyclerdquo Empirical Economicsvol 27 no 2 pp 185ndash204 2002
[8] S Lardic and V Mignon ldquoThe impact of oil prices on GDP inEuropean countries an empirical investigation based on asym-metric cointegrationrdquo Energy Policy vol 34 no 18 pp 3910ndash3915 2006
[9] A Fayyad and K Daly ldquoThe impact of oil price shocks on stockmarket returns comparing GCC countries with the UK andUSArdquo Emerging Markets Review vol 12 no 1 pp 61ndash78 2011
[10] L J Alvarez S Hurtado I Sanchez and C Thomas ldquoTheimpact of oil price changes on Spanish and euro area consumerprice inflationrdquo Economic Modelling vol 28 no 1-2 pp 422ndash431 2011
[11] J B Taylor ldquoThe lack of an empirical rationale for a revival ofdiscretionary fiscal policyrdquo American Economic Review vol 99no 2 pp 550ndash555 2009
[12] J Elder and A Serletis ldquoOil price uncertainty in CanadardquoEnergy Economics vol 31 no 6 pp 852ndash856 2009
[13] S van Wijnbergen ldquoOil price shocks unemployment invest-ment and the current account an intertemporal disequilibriumanalysisrdquo The Review of Economic Studies vol 52 pp 627ndash6451985
[14] N D Uri and R Boyd ldquoEconomic impact of the energy priceincrease in Mexicordquo Environmental and Resource Economicsvol 10 no 1 pp 101ndash107 1997
[15] J L Pierce J J Enzler D I Fand and R J Gordon ldquoThe effectsof external inflationary shocksrdquo Brookings Papers on EconomicActivity vol 5 no 1 pp 13ndash61 1974
[16] K A Mork O Olsen and H T Mysen ldquoMacroeconomic re-sponses to oil price increases and decreases in seven OECDcountriesrdquo Energy Journal vol 15 no 4 pp 19ndash35 1994
[17] J D Sachs R N Cooper and S Fischer ldquoThe current accountand macroeconomic adjustment in the 1970srdquo Brookings Paperson Economic Activity vol 12 no 1 pp 201ndash282 1981
[18] M Erturk ldquoEconomic analysis of unconventional liquid fuelsourcesrdquo Renewable and Sustainable Energy Reviews vol 15 no6 pp 2766ndash2771 2011
[19] N D Uri ldquoCrude oil price volatility and unemployment in theUnited Statesrdquo Energy vol 21 no 1 pp 29ndash38 1996
[20] Y Fan J L Jiao Q M Liang Z Y Han and Y M Wei ldquoTheimpact of rising international crude oil price on Chinarsquos econ-omy an empirical analysiswithCGEmodelrdquo International Jour-nal of Global Energy Issues vol 27 no 4 pp 402ndash424 2007
[21] C M Jones and G Kaul ldquoOil and the stock marketsrdquo Journal ofFinance vol 51 no 2 pp 463ndash491 1996
[22] P Sadorsky ldquoOil price shocks and stock market activityrdquo EnergyEconomics vol 21 no 5 pp 449ndash469 1999
[23] E Papapetrou ldquoOil price shocks stock market economic activ-ity and employment in Greecerdquo Energy Economics vol 23 no5 pp 511ndash532 2001
[24] B T Ewing and M A Thompson ldquoDynamic cyclical comove-ments of oil prices with industrial production consumer pricesunemployment and stock pricesrdquo Energy Policy vol 35 no 11pp 5535ndash5540 2007
[25] R G Cong Y M Wei J L Jiao and Y Fan ldquoRelationships be-tween oil price shocks and stock market an empirical analysisfrom Chinardquo Energy Policy vol 36 no 9 pp 3544ndash3553 2008
[26] R D Huang RWMasulis andH R Stoll ldquoEnergy shocks andfinancial marketsrdquo Journal of Futures Markets vol 16 no 1 pp1ndash27 1996
[27] R W Faff and T J Brailsford ldquoOil price risk and the Australianstock marketrdquo Journal of Energy Finance and Development vol4 pp 69ndash87 1999
[28] S Hammoudeh S Dibooglu and E Aleisa ldquoRelationshipsamong US oil prices and oil industry equity indicesrdquo Interna-tional Review of Economics and Finance vol 13 no 4 pp 427ndash453 2004
[29] P Sadorsky ldquoRisk factors in stock returns of Canadian oil andgas companiesrdquo Energy Economics vol 23 no 1 pp 17ndash28 2001
[30] A Lanza M Manera M Grasso and M Giovannini ldquoLong-run models of oil stock pricesrdquo Environmental Modelling andSoftware vol 20 no 11 pp 1423ndash1430 2005
[31] C A Sims ldquoMacroeconomics and realityrdquo Econometrica vol48 pp 1ndash48 1980
[32] H H Pesaran and Y Shin ldquoGeneralized impulse response anal-ysis in linear multivariate modelsrdquo Economics Letters vol 58no 1 pp 17ndash29 1998
[33] J L Jiao Y Fan and Y M Wei ldquoVECM based analysis ofgasolinediesel prices anti-symmetryrdquo Chinese Journal of Man-agement Science vol 14 pp 97ndash102 2006
[34] N Barberis A Shleifer and R Vishny ldquoA model of investorsentimentrdquo Journal of Financial Economics vol 49 no 3 pp307ndash343 1998
[35] H Hong and J C Stein ldquoA unified theory of underreactionmomentum trading and overreaction in asset marketsrdquo Journalof Finance vol 54 no 6 pp 2143ndash2184 1999
[36] R-G Cong and M Brady ldquoHow to design a targeted agricul-tural subsidy system efficiency or equityrdquo PLoS ONE vol 7Article ID e41225 2012
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
6 The Scientific World Journal
00004000800120016
1 2 3 4 5 6 7 8 9 10 11 12
000040008001200160020
1 2 3 4 5 6 7 8 9 10 11 12
000010002000300040005
1 2 3 4 5 6 7 8 9 10 11 12
0001002003004005
1 2 3 4 5 6 7 8 9 10 11 12
Response to cholesky one SD innovations
Response of OIL to OIL
Response of STOCK to OIL
Impulse-response function Impulse-response function
minus0004
minus0004
minus0001
minus0002
minus001
minus002
minus003
minus004
minus0008
minus0012
plusmn2 SEplusmn2 SE
plusmn2 SE
Response of 119889IP to OIL
Response of 119877 to OIL
Figure 1 Generalized impulse responses to one SD shock for energy price changes Note that the horizontal axis is the period The verticalaxis is the explanation level of dependent variables to independent variables In the model we fix the periods at 12 months
Figure 2 Generalized impulse responses of energy price to one SD shock for other variables changes Note that the horizontal axis is theperiodThe vertical axis is the explanation level of dependent variables to independent variables In themodel we fix the periods at 12months
is not significant or is negative Scholars holding this latterview believe that the Chinese stock market aims at financingbut not investingThe stockmarket can not evaluate the valueof companies correctly Therefore the stock market is notthe barometer of the Chinese macroeconomy Based on acapital asset pricing model the real value of stock equals tothe discount of its future cash flows As a result the value
of stock relates to future economy and also is affected bydiscount rates (interest rate) The rising energy price affectsthe Chinese macroeconomy and pushes up the inflation rateThe cointegration obtained in this paper demonstrates thatenergy price has a significant effect on the stock marketwhich is an extension of existing literature In equation (11)we find that in the long-term energy price has a negative
The Scientific World Journal 7
Table 5 Generalized variance decomposition of STOCK
relationship with industrial value adding and the stockmarket The rise in energy price affects the macroeconomyon the one hand and depresses the stock market on the otherhand
42 The Positive Shock of Energy Price Can Push up the RealInterest Rate Affect Industry Productions and Depress theStock Market Price On the basis of realizing the long-termrelationship among them we want to know the response ofstock prices and the macroeconomy to the short-term shockof the energy price Based on impulse response function wehave seen that the positive shock of energy price can push-up the real interest rate affect industry and depress the stockmarket
The shock of energy price can affect real interest rates tosome extent In China since 2002 the international crude oilprice has risen from $20 per barrel to nearly $100 per barrelIn turn this drives up oil related energy products and totalprices Therefore China has the risk of cost-push inflationThe rise of international crude oil price will increase the
domestic price of the refined oil and related chemical engi-neering products The rise of the refined oil price can furtherincrease the price of transportation industrial productionand residential gas Moreover the rise in price of relatedchemical engineering products will increase the cost ofplastic rubber chemical fiber and other inputs Finally thetotal social price level rises Inflation makes the supply ofcurrency relatively insufficientThe controllable real currencyon the whole will decrease Consequently the rise of energyprice will drive up the total interest rate level
As a major input to industry the rise in energy price canaffect economic growth In the Chinese industry chemicalengineering metallurgy and some other energy-intensiveindustries are seriously affected by the rise in oil price How-ever following advances in technology and the upgrading ofindustrial infrastructure the effect becomes less and less inthe long term
The stockmarket is not completely efficient with regard torecognizing energy price There is a phenomenon of under-reaction As a collection of energy-input companies the riseof energy price will increase their cost and decrease theirprofit If the stock market is efficient the rise in energyprice will depress the stock market immediately But in thispaper we find that the rise in energy price will depress thestock market during a five-month lag As the energy pricein the public domain it means there is conservatism in mostinvestorsrsquo decisions as acknowledged by Barberis et al [34]In other words investors find it difficult to renew their viewsand have an underreaction to the importance of the price ofenergy As a limitation in cognitive abilities they find it hardto evaluate the importance of energy price to stock valueThis conforms to the hypothesis that ldquoinformation diffusesgraduallyrdquo suggested by Hong and Stein [35]
43 The Effect on Energy Price of the Industrial Demand In-creasing Interest Rates and the Stock Market We have dis-cussed earlier that the energy price will have a significanteffect on industrial production real interest rates and thestock market But we still want to know the effect of threeshocks on energy price
To control the inflation caused by the rise of energyprice increasing the real interest rate is very efficient It is
8 The Scientific World Journal
because on the one hand high interest rates change peoplersquoscontrollable income by increasing savings and decreasingconsumption on energy relating products and on the otherhand high interest rates will cause the capital to depreciateand reduce peoplersquos wealth which reduces their consump-tion As to industries high interest rates increase their capitalcost and depresse their investment which reduces theirenergy use for relating products Since 2007 the PeoplersquosBank of China has increased the interest rates five times anddecreased the interest rate tax Currently a sixth increase ininterest rates is being considered It can be forecasted that thePeoplersquos Bank of Chinawill still control inflation by increasinginterest rates as price increase further
The shock of industrial growth has a small but long effecton energy price So the demand from industry on energy isone of the reasons that cause a rise in the energy price Butthe effect is slight
The bull stock market can attract a good deal of moneywhich reduces the currency The Chinese stock market hasrisen from 1000 points to 6000 points since 2005 It hasattracted a large amount of money So after the 2008 Olymp-ics or when the appreciated RMB has been realized a lot ofmoney will be taken back from stock market Additionallythere is risk of inflation in the near future Consequently therise in energy price will be severe
44 Energy Price over the Longer Term Has Better Abilityto Explain the Stock Market than Interest Rates From theresults of forecasting decomposition we find that over thelonger term the greatest effect of three factors on stock priceis energy price interest rates and industrial value adding Inthe short term the increase in interest rates is a bad newsand can be perceived easily by all investors So in the shortterm the interest rates are more important than the othertwo factors But in the long term the rise in energy price willbecome gradually apparent to people and have an effect onpeoplersquos anticipation So it will be the more important factorin the longer term As industries are only a part of stockmarket the effects from them on the total market are limitedThere is separation between the real economy and the virtualeconomy in China Consequently it has a poor explanationin explaining fluctuations in the stock market
5 Conclusions and Future Work
Through the analysis of results and discussion we can drawthe following conclusions
(1) There is a stable long-term relationship among energyprice industrial value adding real interest rates andstock price In the longer term the rise in energy pricewill drive up the real interest rates and have an adverseeffect on industrial value adding and the stockmarket
(2) The shocks in energy price have a lasting effect on realinterest rates which to some extent causes long-terminflation The shocks in energy price have a notableeffect on industrial value adding But the effect tendsto be weaker in the long term In the short time the
shocks in energy price have an effect on the stockmarket
(3) To control the rise in energy price we should considerthe macroeconomy and stock market in addition tothe international and domestic energy market Therising industrial value adding increases the energydemand which to some extent increases the energyprice But the rise of interest rates is favorable for con-trolling the energy price
(4) The effect of energy on the stock market is hard toignore Through forecasting the decomposition ofstock prices we can identify that the stock price ischiefly affected by itself What is a contradiction tothe general view is that energy price and interestrates have greater effect on the stock market thanindustrial value adding In the long term energy priceis evenmore important than interest rates It indicatesto investors that they should not only consider theinterest rates but also consider the energy price fortheir investment
This paper discusses the relationship between energyprice and stock market at the macrolevel The relationshipsbetween the shocks of energy price and the stock prices ofvarious industries and oil companies remain to be researchedMeanwhile opportunities for future research include the sim-ulation and analysis of China economic transition and sus-tainable development at various levels of energy price andthe optimal design of subsidy policy for rising oil price [36]
Conflict of Interests
Theauthors of the paper do not have a direct financial relationwith the commercial identity mentioned in this paper thatmight lead to a conflict of interests for any of the authors
Acknowledgments
The authors gratefully acknowledge the good research envi-ronments provided by the Centre for Environmental andClimate Research (CEC) LundUniversityThe authors thankthe anonymous referees for their helpful suggestions and cor-rections on the earlier draft of the paper which improved thecontentsThis research is funded by ldquoBiodiversity and Ecosys-tem services in a Changing Climate (BECC) and SAPESrdquoThe funders had no role in study design data collection andanalysis decision to publish or preparation of the paperThe contents are the responsibility of the authors and do notnecessarily reflect the views of Centre for Environmental andClimate Research (CEC) Lund University
References
[1] K Hanabusa ldquoThe effect of 107th OPEC ordinary meeting onoil prices and economic performances in Japanrdquo Renewable andSustainable Energy Reviews vol 16 pp 1666ndash1672 2012
[2] M RDarby ldquoTheprice of oil andworld inflation and recessionrdquoAmerican Economic Review vol 72 no 4 pp 738ndash751 1982
The Scientific World Journal 9
[3] J D Hamilton ldquoOil and the macroeconomy since World WarIIrdquo Journal of Political Economy vol 91 pp 228ndash248 1983
[4] A F Darrat OW Gilley and D J Meyer ldquoUS oil consumptionoil prices and themacroeconomyrdquo Empirical Economics vol 21no 3 pp 317ndash334 1996
[5] M K Anton ldquoOil and the macroeconomy when prices go upand down an extension of Hamiltonrsquos resultsrdquo Journal of Polit-ical Economy vol 97 pp 740ndash744 1989
[6] S P A Brown and M K Yucel ldquoEnergy prices and aggregateeconomic activity an interpretative surveyrdquo Quarterly Reviewof Economics and Finance vol 42 no 2 pp 193ndash208 2002
[7] M P Clements and H M Krolzig ldquoCan oil shocks explainasymmetries in the US business cyclerdquo Empirical Economicsvol 27 no 2 pp 185ndash204 2002
[8] S Lardic and V Mignon ldquoThe impact of oil prices on GDP inEuropean countries an empirical investigation based on asym-metric cointegrationrdquo Energy Policy vol 34 no 18 pp 3910ndash3915 2006
[9] A Fayyad and K Daly ldquoThe impact of oil price shocks on stockmarket returns comparing GCC countries with the UK andUSArdquo Emerging Markets Review vol 12 no 1 pp 61ndash78 2011
[10] L J Alvarez S Hurtado I Sanchez and C Thomas ldquoTheimpact of oil price changes on Spanish and euro area consumerprice inflationrdquo Economic Modelling vol 28 no 1-2 pp 422ndash431 2011
[11] J B Taylor ldquoThe lack of an empirical rationale for a revival ofdiscretionary fiscal policyrdquo American Economic Review vol 99no 2 pp 550ndash555 2009
[12] J Elder and A Serletis ldquoOil price uncertainty in CanadardquoEnergy Economics vol 31 no 6 pp 852ndash856 2009
[13] S van Wijnbergen ldquoOil price shocks unemployment invest-ment and the current account an intertemporal disequilibriumanalysisrdquo The Review of Economic Studies vol 52 pp 627ndash6451985
[14] N D Uri and R Boyd ldquoEconomic impact of the energy priceincrease in Mexicordquo Environmental and Resource Economicsvol 10 no 1 pp 101ndash107 1997
[15] J L Pierce J J Enzler D I Fand and R J Gordon ldquoThe effectsof external inflationary shocksrdquo Brookings Papers on EconomicActivity vol 5 no 1 pp 13ndash61 1974
[16] K A Mork O Olsen and H T Mysen ldquoMacroeconomic re-sponses to oil price increases and decreases in seven OECDcountriesrdquo Energy Journal vol 15 no 4 pp 19ndash35 1994
[17] J D Sachs R N Cooper and S Fischer ldquoThe current accountand macroeconomic adjustment in the 1970srdquo Brookings Paperson Economic Activity vol 12 no 1 pp 201ndash282 1981
[18] M Erturk ldquoEconomic analysis of unconventional liquid fuelsourcesrdquo Renewable and Sustainable Energy Reviews vol 15 no6 pp 2766ndash2771 2011
[19] N D Uri ldquoCrude oil price volatility and unemployment in theUnited Statesrdquo Energy vol 21 no 1 pp 29ndash38 1996
[20] Y Fan J L Jiao Q M Liang Z Y Han and Y M Wei ldquoTheimpact of rising international crude oil price on Chinarsquos econ-omy an empirical analysiswithCGEmodelrdquo International Jour-nal of Global Energy Issues vol 27 no 4 pp 402ndash424 2007
[21] C M Jones and G Kaul ldquoOil and the stock marketsrdquo Journal ofFinance vol 51 no 2 pp 463ndash491 1996
[22] P Sadorsky ldquoOil price shocks and stock market activityrdquo EnergyEconomics vol 21 no 5 pp 449ndash469 1999
[23] E Papapetrou ldquoOil price shocks stock market economic activ-ity and employment in Greecerdquo Energy Economics vol 23 no5 pp 511ndash532 2001
[24] B T Ewing and M A Thompson ldquoDynamic cyclical comove-ments of oil prices with industrial production consumer pricesunemployment and stock pricesrdquo Energy Policy vol 35 no 11pp 5535ndash5540 2007
[25] R G Cong Y M Wei J L Jiao and Y Fan ldquoRelationships be-tween oil price shocks and stock market an empirical analysisfrom Chinardquo Energy Policy vol 36 no 9 pp 3544ndash3553 2008
[26] R D Huang RWMasulis andH R Stoll ldquoEnergy shocks andfinancial marketsrdquo Journal of Futures Markets vol 16 no 1 pp1ndash27 1996
[27] R W Faff and T J Brailsford ldquoOil price risk and the Australianstock marketrdquo Journal of Energy Finance and Development vol4 pp 69ndash87 1999
[28] S Hammoudeh S Dibooglu and E Aleisa ldquoRelationshipsamong US oil prices and oil industry equity indicesrdquo Interna-tional Review of Economics and Finance vol 13 no 4 pp 427ndash453 2004
[29] P Sadorsky ldquoRisk factors in stock returns of Canadian oil andgas companiesrdquo Energy Economics vol 23 no 1 pp 17ndash28 2001
[30] A Lanza M Manera M Grasso and M Giovannini ldquoLong-run models of oil stock pricesrdquo Environmental Modelling andSoftware vol 20 no 11 pp 1423ndash1430 2005
[31] C A Sims ldquoMacroeconomics and realityrdquo Econometrica vol48 pp 1ndash48 1980
[32] H H Pesaran and Y Shin ldquoGeneralized impulse response anal-ysis in linear multivariate modelsrdquo Economics Letters vol 58no 1 pp 17ndash29 1998
[33] J L Jiao Y Fan and Y M Wei ldquoVECM based analysis ofgasolinediesel prices anti-symmetryrdquo Chinese Journal of Man-agement Science vol 14 pp 97ndash102 2006
[34] N Barberis A Shleifer and R Vishny ldquoA model of investorsentimentrdquo Journal of Financial Economics vol 49 no 3 pp307ndash343 1998
[35] H Hong and J C Stein ldquoA unified theory of underreactionmomentum trading and overreaction in asset marketsrdquo Journalof Finance vol 54 no 6 pp 2143ndash2184 1999
[36] R-G Cong and M Brady ldquoHow to design a targeted agricul-tural subsidy system efficiency or equityrdquo PLoS ONE vol 7Article ID e41225 2012
relationship with industrial value adding and the stockmarket The rise in energy price affects the macroeconomyon the one hand and depresses the stock market on the otherhand
42 The Positive Shock of Energy Price Can Push up the RealInterest Rate Affect Industry Productions and Depress theStock Market Price On the basis of realizing the long-termrelationship among them we want to know the response ofstock prices and the macroeconomy to the short-term shockof the energy price Based on impulse response function wehave seen that the positive shock of energy price can push-up the real interest rate affect industry and depress the stockmarket
The shock of energy price can affect real interest rates tosome extent In China since 2002 the international crude oilprice has risen from $20 per barrel to nearly $100 per barrelIn turn this drives up oil related energy products and totalprices Therefore China has the risk of cost-push inflationThe rise of international crude oil price will increase the
domestic price of the refined oil and related chemical engi-neering products The rise of the refined oil price can furtherincrease the price of transportation industrial productionand residential gas Moreover the rise in price of relatedchemical engineering products will increase the cost ofplastic rubber chemical fiber and other inputs Finally thetotal social price level rises Inflation makes the supply ofcurrency relatively insufficientThe controllable real currencyon the whole will decrease Consequently the rise of energyprice will drive up the total interest rate level
As a major input to industry the rise in energy price canaffect economic growth In the Chinese industry chemicalengineering metallurgy and some other energy-intensiveindustries are seriously affected by the rise in oil price How-ever following advances in technology and the upgrading ofindustrial infrastructure the effect becomes less and less inthe long term
The stockmarket is not completely efficient with regard torecognizing energy price There is a phenomenon of under-reaction As a collection of energy-input companies the riseof energy price will increase their cost and decrease theirprofit If the stock market is efficient the rise in energyprice will depress the stock market immediately But in thispaper we find that the rise in energy price will depress thestock market during a five-month lag As the energy pricein the public domain it means there is conservatism in mostinvestorsrsquo decisions as acknowledged by Barberis et al [34]In other words investors find it difficult to renew their viewsand have an underreaction to the importance of the price ofenergy As a limitation in cognitive abilities they find it hardto evaluate the importance of energy price to stock valueThis conforms to the hypothesis that ldquoinformation diffusesgraduallyrdquo suggested by Hong and Stein [35]
43 The Effect on Energy Price of the Industrial Demand In-creasing Interest Rates and the Stock Market We have dis-cussed earlier that the energy price will have a significanteffect on industrial production real interest rates and thestock market But we still want to know the effect of threeshocks on energy price
To control the inflation caused by the rise of energyprice increasing the real interest rate is very efficient It is
8 The Scientific World Journal
because on the one hand high interest rates change peoplersquoscontrollable income by increasing savings and decreasingconsumption on energy relating products and on the otherhand high interest rates will cause the capital to depreciateand reduce peoplersquos wealth which reduces their consump-tion As to industries high interest rates increase their capitalcost and depresse their investment which reduces theirenergy use for relating products Since 2007 the PeoplersquosBank of China has increased the interest rates five times anddecreased the interest rate tax Currently a sixth increase ininterest rates is being considered It can be forecasted that thePeoplersquos Bank of Chinawill still control inflation by increasinginterest rates as price increase further
The shock of industrial growth has a small but long effecton energy price So the demand from industry on energy isone of the reasons that cause a rise in the energy price Butthe effect is slight
The bull stock market can attract a good deal of moneywhich reduces the currency The Chinese stock market hasrisen from 1000 points to 6000 points since 2005 It hasattracted a large amount of money So after the 2008 Olymp-ics or when the appreciated RMB has been realized a lot ofmoney will be taken back from stock market Additionallythere is risk of inflation in the near future Consequently therise in energy price will be severe
44 Energy Price over the Longer Term Has Better Abilityto Explain the Stock Market than Interest Rates From theresults of forecasting decomposition we find that over thelonger term the greatest effect of three factors on stock priceis energy price interest rates and industrial value adding Inthe short term the increase in interest rates is a bad newsand can be perceived easily by all investors So in the shortterm the interest rates are more important than the othertwo factors But in the long term the rise in energy price willbecome gradually apparent to people and have an effect onpeoplersquos anticipation So it will be the more important factorin the longer term As industries are only a part of stockmarket the effects from them on the total market are limitedThere is separation between the real economy and the virtualeconomy in China Consequently it has a poor explanationin explaining fluctuations in the stock market
5 Conclusions and Future Work
Through the analysis of results and discussion we can drawthe following conclusions
(1) There is a stable long-term relationship among energyprice industrial value adding real interest rates andstock price In the longer term the rise in energy pricewill drive up the real interest rates and have an adverseeffect on industrial value adding and the stockmarket
(2) The shocks in energy price have a lasting effect on realinterest rates which to some extent causes long-terminflation The shocks in energy price have a notableeffect on industrial value adding But the effect tendsto be weaker in the long term In the short time the
shocks in energy price have an effect on the stockmarket
(3) To control the rise in energy price we should considerthe macroeconomy and stock market in addition tothe international and domestic energy market Therising industrial value adding increases the energydemand which to some extent increases the energyprice But the rise of interest rates is favorable for con-trolling the energy price
(4) The effect of energy on the stock market is hard toignore Through forecasting the decomposition ofstock prices we can identify that the stock price ischiefly affected by itself What is a contradiction tothe general view is that energy price and interestrates have greater effect on the stock market thanindustrial value adding In the long term energy priceis evenmore important than interest rates It indicatesto investors that they should not only consider theinterest rates but also consider the energy price fortheir investment
This paper discusses the relationship between energyprice and stock market at the macrolevel The relationshipsbetween the shocks of energy price and the stock prices ofvarious industries and oil companies remain to be researchedMeanwhile opportunities for future research include the sim-ulation and analysis of China economic transition and sus-tainable development at various levels of energy price andthe optimal design of subsidy policy for rising oil price [36]
Conflict of Interests
Theauthors of the paper do not have a direct financial relationwith the commercial identity mentioned in this paper thatmight lead to a conflict of interests for any of the authors
Acknowledgments
The authors gratefully acknowledge the good research envi-ronments provided by the Centre for Environmental andClimate Research (CEC) LundUniversityThe authors thankthe anonymous referees for their helpful suggestions and cor-rections on the earlier draft of the paper which improved thecontentsThis research is funded by ldquoBiodiversity and Ecosys-tem services in a Changing Climate (BECC) and SAPESrdquoThe funders had no role in study design data collection andanalysis decision to publish or preparation of the paperThe contents are the responsibility of the authors and do notnecessarily reflect the views of Centre for Environmental andClimate Research (CEC) Lund University
References
[1] K Hanabusa ldquoThe effect of 107th OPEC ordinary meeting onoil prices and economic performances in Japanrdquo Renewable andSustainable Energy Reviews vol 16 pp 1666ndash1672 2012
[2] M RDarby ldquoTheprice of oil andworld inflation and recessionrdquoAmerican Economic Review vol 72 no 4 pp 738ndash751 1982
The Scientific World Journal 9
[3] J D Hamilton ldquoOil and the macroeconomy since World WarIIrdquo Journal of Political Economy vol 91 pp 228ndash248 1983
[4] A F Darrat OW Gilley and D J Meyer ldquoUS oil consumptionoil prices and themacroeconomyrdquo Empirical Economics vol 21no 3 pp 317ndash334 1996
[5] M K Anton ldquoOil and the macroeconomy when prices go upand down an extension of Hamiltonrsquos resultsrdquo Journal of Polit-ical Economy vol 97 pp 740ndash744 1989
[6] S P A Brown and M K Yucel ldquoEnergy prices and aggregateeconomic activity an interpretative surveyrdquo Quarterly Reviewof Economics and Finance vol 42 no 2 pp 193ndash208 2002
[7] M P Clements and H M Krolzig ldquoCan oil shocks explainasymmetries in the US business cyclerdquo Empirical Economicsvol 27 no 2 pp 185ndash204 2002
[8] S Lardic and V Mignon ldquoThe impact of oil prices on GDP inEuropean countries an empirical investigation based on asym-metric cointegrationrdquo Energy Policy vol 34 no 18 pp 3910ndash3915 2006
[9] A Fayyad and K Daly ldquoThe impact of oil price shocks on stockmarket returns comparing GCC countries with the UK andUSArdquo Emerging Markets Review vol 12 no 1 pp 61ndash78 2011
[10] L J Alvarez S Hurtado I Sanchez and C Thomas ldquoTheimpact of oil price changes on Spanish and euro area consumerprice inflationrdquo Economic Modelling vol 28 no 1-2 pp 422ndash431 2011
[11] J B Taylor ldquoThe lack of an empirical rationale for a revival ofdiscretionary fiscal policyrdquo American Economic Review vol 99no 2 pp 550ndash555 2009
[12] J Elder and A Serletis ldquoOil price uncertainty in CanadardquoEnergy Economics vol 31 no 6 pp 852ndash856 2009
[13] S van Wijnbergen ldquoOil price shocks unemployment invest-ment and the current account an intertemporal disequilibriumanalysisrdquo The Review of Economic Studies vol 52 pp 627ndash6451985
[14] N D Uri and R Boyd ldquoEconomic impact of the energy priceincrease in Mexicordquo Environmental and Resource Economicsvol 10 no 1 pp 101ndash107 1997
[15] J L Pierce J J Enzler D I Fand and R J Gordon ldquoThe effectsof external inflationary shocksrdquo Brookings Papers on EconomicActivity vol 5 no 1 pp 13ndash61 1974
[16] K A Mork O Olsen and H T Mysen ldquoMacroeconomic re-sponses to oil price increases and decreases in seven OECDcountriesrdquo Energy Journal vol 15 no 4 pp 19ndash35 1994
[17] J D Sachs R N Cooper and S Fischer ldquoThe current accountand macroeconomic adjustment in the 1970srdquo Brookings Paperson Economic Activity vol 12 no 1 pp 201ndash282 1981
[18] M Erturk ldquoEconomic analysis of unconventional liquid fuelsourcesrdquo Renewable and Sustainable Energy Reviews vol 15 no6 pp 2766ndash2771 2011
[19] N D Uri ldquoCrude oil price volatility and unemployment in theUnited Statesrdquo Energy vol 21 no 1 pp 29ndash38 1996
[20] Y Fan J L Jiao Q M Liang Z Y Han and Y M Wei ldquoTheimpact of rising international crude oil price on Chinarsquos econ-omy an empirical analysiswithCGEmodelrdquo International Jour-nal of Global Energy Issues vol 27 no 4 pp 402ndash424 2007
[21] C M Jones and G Kaul ldquoOil and the stock marketsrdquo Journal ofFinance vol 51 no 2 pp 463ndash491 1996
[22] P Sadorsky ldquoOil price shocks and stock market activityrdquo EnergyEconomics vol 21 no 5 pp 449ndash469 1999
[23] E Papapetrou ldquoOil price shocks stock market economic activ-ity and employment in Greecerdquo Energy Economics vol 23 no5 pp 511ndash532 2001
[24] B T Ewing and M A Thompson ldquoDynamic cyclical comove-ments of oil prices with industrial production consumer pricesunemployment and stock pricesrdquo Energy Policy vol 35 no 11pp 5535ndash5540 2007
[25] R G Cong Y M Wei J L Jiao and Y Fan ldquoRelationships be-tween oil price shocks and stock market an empirical analysisfrom Chinardquo Energy Policy vol 36 no 9 pp 3544ndash3553 2008
[26] R D Huang RWMasulis andH R Stoll ldquoEnergy shocks andfinancial marketsrdquo Journal of Futures Markets vol 16 no 1 pp1ndash27 1996
[27] R W Faff and T J Brailsford ldquoOil price risk and the Australianstock marketrdquo Journal of Energy Finance and Development vol4 pp 69ndash87 1999
[28] S Hammoudeh S Dibooglu and E Aleisa ldquoRelationshipsamong US oil prices and oil industry equity indicesrdquo Interna-tional Review of Economics and Finance vol 13 no 4 pp 427ndash453 2004
[29] P Sadorsky ldquoRisk factors in stock returns of Canadian oil andgas companiesrdquo Energy Economics vol 23 no 1 pp 17ndash28 2001
[30] A Lanza M Manera M Grasso and M Giovannini ldquoLong-run models of oil stock pricesrdquo Environmental Modelling andSoftware vol 20 no 11 pp 1423ndash1430 2005
[31] C A Sims ldquoMacroeconomics and realityrdquo Econometrica vol48 pp 1ndash48 1980
[32] H H Pesaran and Y Shin ldquoGeneralized impulse response anal-ysis in linear multivariate modelsrdquo Economics Letters vol 58no 1 pp 17ndash29 1998
[33] J L Jiao Y Fan and Y M Wei ldquoVECM based analysis ofgasolinediesel prices anti-symmetryrdquo Chinese Journal of Man-agement Science vol 14 pp 97ndash102 2006
[34] N Barberis A Shleifer and R Vishny ldquoA model of investorsentimentrdquo Journal of Financial Economics vol 49 no 3 pp307ndash343 1998
[35] H Hong and J C Stein ldquoA unified theory of underreactionmomentum trading and overreaction in asset marketsrdquo Journalof Finance vol 54 no 6 pp 2143ndash2184 1999
[36] R-G Cong and M Brady ldquoHow to design a targeted agricul-tural subsidy system efficiency or equityrdquo PLoS ONE vol 7Article ID e41225 2012
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
8 The Scientific World Journal
because on the one hand high interest rates change peoplersquoscontrollable income by increasing savings and decreasingconsumption on energy relating products and on the otherhand high interest rates will cause the capital to depreciateand reduce peoplersquos wealth which reduces their consump-tion As to industries high interest rates increase their capitalcost and depresse their investment which reduces theirenergy use for relating products Since 2007 the PeoplersquosBank of China has increased the interest rates five times anddecreased the interest rate tax Currently a sixth increase ininterest rates is being considered It can be forecasted that thePeoplersquos Bank of Chinawill still control inflation by increasinginterest rates as price increase further
The shock of industrial growth has a small but long effecton energy price So the demand from industry on energy isone of the reasons that cause a rise in the energy price Butthe effect is slight
The bull stock market can attract a good deal of moneywhich reduces the currency The Chinese stock market hasrisen from 1000 points to 6000 points since 2005 It hasattracted a large amount of money So after the 2008 Olymp-ics or when the appreciated RMB has been realized a lot ofmoney will be taken back from stock market Additionallythere is risk of inflation in the near future Consequently therise in energy price will be severe
44 Energy Price over the Longer Term Has Better Abilityto Explain the Stock Market than Interest Rates From theresults of forecasting decomposition we find that over thelonger term the greatest effect of three factors on stock priceis energy price interest rates and industrial value adding Inthe short term the increase in interest rates is a bad newsand can be perceived easily by all investors So in the shortterm the interest rates are more important than the othertwo factors But in the long term the rise in energy price willbecome gradually apparent to people and have an effect onpeoplersquos anticipation So it will be the more important factorin the longer term As industries are only a part of stockmarket the effects from them on the total market are limitedThere is separation between the real economy and the virtualeconomy in China Consequently it has a poor explanationin explaining fluctuations in the stock market
5 Conclusions and Future Work
Through the analysis of results and discussion we can drawthe following conclusions
(1) There is a stable long-term relationship among energyprice industrial value adding real interest rates andstock price In the longer term the rise in energy pricewill drive up the real interest rates and have an adverseeffect on industrial value adding and the stockmarket
(2) The shocks in energy price have a lasting effect on realinterest rates which to some extent causes long-terminflation The shocks in energy price have a notableeffect on industrial value adding But the effect tendsto be weaker in the long term In the short time the
shocks in energy price have an effect on the stockmarket
(3) To control the rise in energy price we should considerthe macroeconomy and stock market in addition tothe international and domestic energy market Therising industrial value adding increases the energydemand which to some extent increases the energyprice But the rise of interest rates is favorable for con-trolling the energy price
(4) The effect of energy on the stock market is hard toignore Through forecasting the decomposition ofstock prices we can identify that the stock price ischiefly affected by itself What is a contradiction tothe general view is that energy price and interestrates have greater effect on the stock market thanindustrial value adding In the long term energy priceis evenmore important than interest rates It indicatesto investors that they should not only consider theinterest rates but also consider the energy price fortheir investment
This paper discusses the relationship between energyprice and stock market at the macrolevel The relationshipsbetween the shocks of energy price and the stock prices ofvarious industries and oil companies remain to be researchedMeanwhile opportunities for future research include the sim-ulation and analysis of China economic transition and sus-tainable development at various levels of energy price andthe optimal design of subsidy policy for rising oil price [36]
Conflict of Interests
Theauthors of the paper do not have a direct financial relationwith the commercial identity mentioned in this paper thatmight lead to a conflict of interests for any of the authors
Acknowledgments
The authors gratefully acknowledge the good research envi-ronments provided by the Centre for Environmental andClimate Research (CEC) LundUniversityThe authors thankthe anonymous referees for their helpful suggestions and cor-rections on the earlier draft of the paper which improved thecontentsThis research is funded by ldquoBiodiversity and Ecosys-tem services in a Changing Climate (BECC) and SAPESrdquoThe funders had no role in study design data collection andanalysis decision to publish or preparation of the paperThe contents are the responsibility of the authors and do notnecessarily reflect the views of Centre for Environmental andClimate Research (CEC) Lund University
References
[1] K Hanabusa ldquoThe effect of 107th OPEC ordinary meeting onoil prices and economic performances in Japanrdquo Renewable andSustainable Energy Reviews vol 16 pp 1666ndash1672 2012
[2] M RDarby ldquoTheprice of oil andworld inflation and recessionrdquoAmerican Economic Review vol 72 no 4 pp 738ndash751 1982
The Scientific World Journal 9
[3] J D Hamilton ldquoOil and the macroeconomy since World WarIIrdquo Journal of Political Economy vol 91 pp 228ndash248 1983
[4] A F Darrat OW Gilley and D J Meyer ldquoUS oil consumptionoil prices and themacroeconomyrdquo Empirical Economics vol 21no 3 pp 317ndash334 1996
[5] M K Anton ldquoOil and the macroeconomy when prices go upand down an extension of Hamiltonrsquos resultsrdquo Journal of Polit-ical Economy vol 97 pp 740ndash744 1989
[6] S P A Brown and M K Yucel ldquoEnergy prices and aggregateeconomic activity an interpretative surveyrdquo Quarterly Reviewof Economics and Finance vol 42 no 2 pp 193ndash208 2002
[7] M P Clements and H M Krolzig ldquoCan oil shocks explainasymmetries in the US business cyclerdquo Empirical Economicsvol 27 no 2 pp 185ndash204 2002
[8] S Lardic and V Mignon ldquoThe impact of oil prices on GDP inEuropean countries an empirical investigation based on asym-metric cointegrationrdquo Energy Policy vol 34 no 18 pp 3910ndash3915 2006
[9] A Fayyad and K Daly ldquoThe impact of oil price shocks on stockmarket returns comparing GCC countries with the UK andUSArdquo Emerging Markets Review vol 12 no 1 pp 61ndash78 2011
[10] L J Alvarez S Hurtado I Sanchez and C Thomas ldquoTheimpact of oil price changes on Spanish and euro area consumerprice inflationrdquo Economic Modelling vol 28 no 1-2 pp 422ndash431 2011
[11] J B Taylor ldquoThe lack of an empirical rationale for a revival ofdiscretionary fiscal policyrdquo American Economic Review vol 99no 2 pp 550ndash555 2009
[12] J Elder and A Serletis ldquoOil price uncertainty in CanadardquoEnergy Economics vol 31 no 6 pp 852ndash856 2009
[13] S van Wijnbergen ldquoOil price shocks unemployment invest-ment and the current account an intertemporal disequilibriumanalysisrdquo The Review of Economic Studies vol 52 pp 627ndash6451985
[14] N D Uri and R Boyd ldquoEconomic impact of the energy priceincrease in Mexicordquo Environmental and Resource Economicsvol 10 no 1 pp 101ndash107 1997
[15] J L Pierce J J Enzler D I Fand and R J Gordon ldquoThe effectsof external inflationary shocksrdquo Brookings Papers on EconomicActivity vol 5 no 1 pp 13ndash61 1974
[16] K A Mork O Olsen and H T Mysen ldquoMacroeconomic re-sponses to oil price increases and decreases in seven OECDcountriesrdquo Energy Journal vol 15 no 4 pp 19ndash35 1994
[17] J D Sachs R N Cooper and S Fischer ldquoThe current accountand macroeconomic adjustment in the 1970srdquo Brookings Paperson Economic Activity vol 12 no 1 pp 201ndash282 1981
[18] M Erturk ldquoEconomic analysis of unconventional liquid fuelsourcesrdquo Renewable and Sustainable Energy Reviews vol 15 no6 pp 2766ndash2771 2011
[19] N D Uri ldquoCrude oil price volatility and unemployment in theUnited Statesrdquo Energy vol 21 no 1 pp 29ndash38 1996
[20] Y Fan J L Jiao Q M Liang Z Y Han and Y M Wei ldquoTheimpact of rising international crude oil price on Chinarsquos econ-omy an empirical analysiswithCGEmodelrdquo International Jour-nal of Global Energy Issues vol 27 no 4 pp 402ndash424 2007
[21] C M Jones and G Kaul ldquoOil and the stock marketsrdquo Journal ofFinance vol 51 no 2 pp 463ndash491 1996
[22] P Sadorsky ldquoOil price shocks and stock market activityrdquo EnergyEconomics vol 21 no 5 pp 449ndash469 1999
[23] E Papapetrou ldquoOil price shocks stock market economic activ-ity and employment in Greecerdquo Energy Economics vol 23 no5 pp 511ndash532 2001
[24] B T Ewing and M A Thompson ldquoDynamic cyclical comove-ments of oil prices with industrial production consumer pricesunemployment and stock pricesrdquo Energy Policy vol 35 no 11pp 5535ndash5540 2007
[25] R G Cong Y M Wei J L Jiao and Y Fan ldquoRelationships be-tween oil price shocks and stock market an empirical analysisfrom Chinardquo Energy Policy vol 36 no 9 pp 3544ndash3553 2008
[26] R D Huang RWMasulis andH R Stoll ldquoEnergy shocks andfinancial marketsrdquo Journal of Futures Markets vol 16 no 1 pp1ndash27 1996
[27] R W Faff and T J Brailsford ldquoOil price risk and the Australianstock marketrdquo Journal of Energy Finance and Development vol4 pp 69ndash87 1999
[28] S Hammoudeh S Dibooglu and E Aleisa ldquoRelationshipsamong US oil prices and oil industry equity indicesrdquo Interna-tional Review of Economics and Finance vol 13 no 4 pp 427ndash453 2004
[29] P Sadorsky ldquoRisk factors in stock returns of Canadian oil andgas companiesrdquo Energy Economics vol 23 no 1 pp 17ndash28 2001
[30] A Lanza M Manera M Grasso and M Giovannini ldquoLong-run models of oil stock pricesrdquo Environmental Modelling andSoftware vol 20 no 11 pp 1423ndash1430 2005
[31] C A Sims ldquoMacroeconomics and realityrdquo Econometrica vol48 pp 1ndash48 1980
[32] H H Pesaran and Y Shin ldquoGeneralized impulse response anal-ysis in linear multivariate modelsrdquo Economics Letters vol 58no 1 pp 17ndash29 1998
[33] J L Jiao Y Fan and Y M Wei ldquoVECM based analysis ofgasolinediesel prices anti-symmetryrdquo Chinese Journal of Man-agement Science vol 14 pp 97ndash102 2006
[34] N Barberis A Shleifer and R Vishny ldquoA model of investorsentimentrdquo Journal of Financial Economics vol 49 no 3 pp307ndash343 1998
[35] H Hong and J C Stein ldquoA unified theory of underreactionmomentum trading and overreaction in asset marketsrdquo Journalof Finance vol 54 no 6 pp 2143ndash2184 1999
[36] R-G Cong and M Brady ldquoHow to design a targeted agricul-tural subsidy system efficiency or equityrdquo PLoS ONE vol 7Article ID e41225 2012
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
The Scientific World Journal 9
[3] J D Hamilton ldquoOil and the macroeconomy since World WarIIrdquo Journal of Political Economy vol 91 pp 228ndash248 1983
[4] A F Darrat OW Gilley and D J Meyer ldquoUS oil consumptionoil prices and themacroeconomyrdquo Empirical Economics vol 21no 3 pp 317ndash334 1996
[5] M K Anton ldquoOil and the macroeconomy when prices go upand down an extension of Hamiltonrsquos resultsrdquo Journal of Polit-ical Economy vol 97 pp 740ndash744 1989
[6] S P A Brown and M K Yucel ldquoEnergy prices and aggregateeconomic activity an interpretative surveyrdquo Quarterly Reviewof Economics and Finance vol 42 no 2 pp 193ndash208 2002
[7] M P Clements and H M Krolzig ldquoCan oil shocks explainasymmetries in the US business cyclerdquo Empirical Economicsvol 27 no 2 pp 185ndash204 2002
[8] S Lardic and V Mignon ldquoThe impact of oil prices on GDP inEuropean countries an empirical investigation based on asym-metric cointegrationrdquo Energy Policy vol 34 no 18 pp 3910ndash3915 2006
[9] A Fayyad and K Daly ldquoThe impact of oil price shocks on stockmarket returns comparing GCC countries with the UK andUSArdquo Emerging Markets Review vol 12 no 1 pp 61ndash78 2011
[10] L J Alvarez S Hurtado I Sanchez and C Thomas ldquoTheimpact of oil price changes on Spanish and euro area consumerprice inflationrdquo Economic Modelling vol 28 no 1-2 pp 422ndash431 2011
[11] J B Taylor ldquoThe lack of an empirical rationale for a revival ofdiscretionary fiscal policyrdquo American Economic Review vol 99no 2 pp 550ndash555 2009
[12] J Elder and A Serletis ldquoOil price uncertainty in CanadardquoEnergy Economics vol 31 no 6 pp 852ndash856 2009
[13] S van Wijnbergen ldquoOil price shocks unemployment invest-ment and the current account an intertemporal disequilibriumanalysisrdquo The Review of Economic Studies vol 52 pp 627ndash6451985
[14] N D Uri and R Boyd ldquoEconomic impact of the energy priceincrease in Mexicordquo Environmental and Resource Economicsvol 10 no 1 pp 101ndash107 1997
[15] J L Pierce J J Enzler D I Fand and R J Gordon ldquoThe effectsof external inflationary shocksrdquo Brookings Papers on EconomicActivity vol 5 no 1 pp 13ndash61 1974
[16] K A Mork O Olsen and H T Mysen ldquoMacroeconomic re-sponses to oil price increases and decreases in seven OECDcountriesrdquo Energy Journal vol 15 no 4 pp 19ndash35 1994
[17] J D Sachs R N Cooper and S Fischer ldquoThe current accountand macroeconomic adjustment in the 1970srdquo Brookings Paperson Economic Activity vol 12 no 1 pp 201ndash282 1981
[18] M Erturk ldquoEconomic analysis of unconventional liquid fuelsourcesrdquo Renewable and Sustainable Energy Reviews vol 15 no6 pp 2766ndash2771 2011
[19] N D Uri ldquoCrude oil price volatility and unemployment in theUnited Statesrdquo Energy vol 21 no 1 pp 29ndash38 1996
[20] Y Fan J L Jiao Q M Liang Z Y Han and Y M Wei ldquoTheimpact of rising international crude oil price on Chinarsquos econ-omy an empirical analysiswithCGEmodelrdquo International Jour-nal of Global Energy Issues vol 27 no 4 pp 402ndash424 2007
[21] C M Jones and G Kaul ldquoOil and the stock marketsrdquo Journal ofFinance vol 51 no 2 pp 463ndash491 1996
[22] P Sadorsky ldquoOil price shocks and stock market activityrdquo EnergyEconomics vol 21 no 5 pp 449ndash469 1999
[23] E Papapetrou ldquoOil price shocks stock market economic activ-ity and employment in Greecerdquo Energy Economics vol 23 no5 pp 511ndash532 2001
[24] B T Ewing and M A Thompson ldquoDynamic cyclical comove-ments of oil prices with industrial production consumer pricesunemployment and stock pricesrdquo Energy Policy vol 35 no 11pp 5535ndash5540 2007
[25] R G Cong Y M Wei J L Jiao and Y Fan ldquoRelationships be-tween oil price shocks and stock market an empirical analysisfrom Chinardquo Energy Policy vol 36 no 9 pp 3544ndash3553 2008
[26] R D Huang RWMasulis andH R Stoll ldquoEnergy shocks andfinancial marketsrdquo Journal of Futures Markets vol 16 no 1 pp1ndash27 1996
[27] R W Faff and T J Brailsford ldquoOil price risk and the Australianstock marketrdquo Journal of Energy Finance and Development vol4 pp 69ndash87 1999
[28] S Hammoudeh S Dibooglu and E Aleisa ldquoRelationshipsamong US oil prices and oil industry equity indicesrdquo Interna-tional Review of Economics and Finance vol 13 no 4 pp 427ndash453 2004
[29] P Sadorsky ldquoRisk factors in stock returns of Canadian oil andgas companiesrdquo Energy Economics vol 23 no 1 pp 17ndash28 2001
[30] A Lanza M Manera M Grasso and M Giovannini ldquoLong-run models of oil stock pricesrdquo Environmental Modelling andSoftware vol 20 no 11 pp 1423ndash1430 2005
[31] C A Sims ldquoMacroeconomics and realityrdquo Econometrica vol48 pp 1ndash48 1980
[32] H H Pesaran and Y Shin ldquoGeneralized impulse response anal-ysis in linear multivariate modelsrdquo Economics Letters vol 58no 1 pp 17ndash29 1998
[33] J L Jiao Y Fan and Y M Wei ldquoVECM based analysis ofgasolinediesel prices anti-symmetryrdquo Chinese Journal of Man-agement Science vol 14 pp 97ndash102 2006
[34] N Barberis A Shleifer and R Vishny ldquoA model of investorsentimentrdquo Journal of Financial Economics vol 49 no 3 pp307ndash343 1998
[35] H Hong and J C Stein ldquoA unified theory of underreactionmomentum trading and overreaction in asset marketsrdquo Journalof Finance vol 54 no 6 pp 2143ndash2184 1999
[36] R-G Cong and M Brady ldquoHow to design a targeted agricul-tural subsidy system efficiency or equityrdquo PLoS ONE vol 7Article ID e41225 2012
