Crude Oil Price and Aggregate Economic Activity: Asymmetric or Symmetric Relationship: Evidence from Canada s Economy

Transcription

1 Crude Oil Price and Aggregate Economic Activity: Asymmetric or Symmetric Relationship: Evidence from Canada s Economy By Asgar Khademvatani And Frank J. Atkins Department of Economics The University of Calgary Calgary, Alberta Canada T2N 1N4

2 Abstract We represent an alternative time series technique to examine alternative asymmetry hypothesis based on the reliable vector Error Correction Model (ECM). In doing so, we add up negative and/or insert positive and negative changes of the crude oil price in a bivariate and multivariate ECM techniques among GDP, the crude oil price, the shortterm interest rate, and the aggregate implicit price deflator. This paper unlike most of the economic literature on the subject considers unit root and structural break tests for deciding whether cointegration and ECM technique or VAR techniques and innovation accounting tools would be used to explain the interaction of economic activities, oil price shocks, and other key economic variables. We employ this alternative empirical method for Canada s economy using quarterly data set over the period ( ). Our results suggest the longterm equilibrium relationship among GDP, the crude oil price, and other key economic variables. In contrast with the most literature, the results show that there is a significant portion of the symmetric and reversible response of Canada s economy to the crude oil price changes in both bivariate and multivariate context over the period under examination. We find that this symmetric response is due to the symmetric relationship of the crude oil price with the shortterm interest rate and the aggregate price Index in Canada s economy. 2

3 1. Introduction: A considerable body of economic research suggests that oil prices fluctuations have figured prominently in national economic activity since World War II. In fact, rising oil prices preceded eight of the nine postworld War II recessions. But an acceleration of U.S. economic activity did not seem to follow the oil price declines that occurred from the early 1980s to the late 1990s. In addition, rising oil prices seemed to have less of an effect on economic activity over the past fifteen years than they did in the 35 years following World War II. Beyond establishing a relationship between oil price movements and aggregate economic activity, research on the economic response to oil price shocks has gone in several directions. A number of studies have investigated why rising oil prices appear to retard aggregate economic activity by more than falling oil prices stimulate it. Other studies have investigated the channels through which oil price shocks are transmitted to economic activity, including, monetary policy, the adjustment costs, and so on. And several have examined the possibility of a weakening relationship between oil price fluctuations and aggregate economic activity. So, an oil price shock has preceded all but one postwar recession Hamilton (1983). Yet robust economic recovery did not follow the 1986 oil price collapse. Since the Canada has less productive capacity of crude oil than OPEC, NonOPEC and the United States, the importance of investigation of volatility of oil prices on Canada s economy is very interesting subject; Since Canadian economy in some provinces such as Alberta, British Columbia, Saskatchewan depends on oil price fluctuations and crude oil is as vital primary energy in supplyside of Canada s economy. So, explaining symmetric/or asymmetric relationship of the oil price changes 3

4 and aggregate economic activities could be a controversial debate. Meanwhile, there are many experimental working papers about the asymmetric or symmetric relationships between energy prices and aggregate economic activities in the United States (with similar economic structure). Also, doing some practices of applying main context of time series techniques is another objective of working paper. Since, the late 1980 s a number of studies Mark (1989), Hamilton and Herrera (1998), Davis and Haltiwanger (2001) and Nathan, Balk, Brown and Yucel (2002) that have investigated and confirmed an asymmetric relationships between oil prices and aggregate economic activity in the United States economy. An exception Huntington (1998) attributes some of the asymmetry to the relationship between crude oil and petroleum product prices but does not preclude other sources. In these studies, the source of asymmetric relationships some channels is addressed in following; The adjustment costs of shifting among economic sectors in response to changing oil prices. Falling oil prices stimulate economic activity, and rising oil prices decreases economic activity; but the cost of adjusting to changing oil prices has negative effects on economic activities. Combining these elements, we see that rising oil prices would present two negative effects for economic activity. Falling oil price would present both a negative and a positive effect that tend to be offsetting. Empirical work by Loungani (1986), Davis (1987), Lee et al. (1995), Davis and Haltiwanger (2001), and Hamilton and Herrera (1999) support, but do not directly test Hamilton s explanation. Monetary policy may account for the asymmetric response of aggregate economic activity. Bohi (1989), and Bernake Gertler and Watson (1997) argue that concretionary monetary policy addresses for declining of aggregate economic 4

5 activities following an oil price increase. Neither explores the asymmetry issue explicitly. Tatom (1988, 1993) argues that the apparent asymmetric response in U.S. economic activity to oil price shocks disappears when the stance of monetary policy or changes in the misery index (which combines unemployment and inflation rates) are taken into account. Uncertainty and financial stress that is offered by Ferderer (1996) who argues that changing oil prices could amplify the negative effects of rising oil prices and offset to some degree the positive effects of falling oil prices. These effects might be evident in the asymmetric response of interest rates to oil price shocks. The economy s short run response to energy price shocks is considerably more complicated than simple shifts along an aggregate production function for the nation. The mechanism for explaining oil shocks in most largescale macro econometrics models (as explained in Hickman (1987)) is essentially the aggregate supply and demand model found in many text books (e.g. see Dornbusch and Fischer (1994), and Hall and Taylor (1993) which emphasize the real balance effect through the interaction of the goods and money markets. This framework relies mostly on upward shifts in the aggregate price level that reduces real monetary balances, rather than relative price adjustment. Shifts in shortrun aggregate supply and demand curves push interest rates and prices upward while retarding economic growth. Energy price shocks in such a framework can have large macroeconomic effects and these effects do not need to be reversible. With energy price decreases, if wages and other prices in the economy are downward sticky. Most researchers focus exclusively on the relationships between crude oil 5

6 prices and aggregate economic output. However, oil price shocks have also had significant effects on wages, interest rate and prices throughout the explained framework. So, this paper reconsiders the relationship between crude oil shocks and economic activities within the context of the broader impact of oil prices on the aggregate price level and shortterm interest rate. Also, recent empirical studies to explain the economy s response to oil shocks have directly used vector autoregressive (VAR) or near VAR techniques, without consideration of the order of integration of the series. Nevertheless, this paper considers unit Root and structural break tests for deciding whether Bivariate and Multivariate Cointegration and error correction model or VAR techniques and innovation accounting tools to explain the interaction of economic activities, oil prices shocks and other key economic variables. The remainder of the paper proceeds as follows. Section 2 discusses some Basic theory and evidence on asymmetry in the economic literature. Section 3 explains methodological issues and data used in the empirical analysis. Section 4 reports on the empirical results. Section 5 presents the concluding remarks. 2. Asymmetry: The Basic Theory and Evidence The oil price shock of 1973 and the subsequent recession, gave rise to a plethora of studies analysing the effects of oil price increases on the economy. The 1973 recession was (at the time) the longest of the postworld WarII recessions, and it gave new gravity to the oilmacroeconomy relationship. The early studies included pierce and Enzler (1974), Rasche and Tatom (1977), Mork and Hall (1980), Darby (1982), Gisser 6

7 and Goodwin (1986) and the Energy Modeling Forum7 study documented in Hickman et al. (1987). They confirmed the inverse relationship between oil prices and aggregate economic activity for the United States. Darbey (1982), Burbidge and Harrison (1984), and Bruno and Sachs (1982, 1985) documented similar oilprice economy relationships for countries other than the United States. In an extensive survey of the empirical literature, Jones and Leiby (1996) find that the estimated oil price elasticity of GNP in the early studies ranged from 0.02 to 0.08, with the estimates consistently clustered around 0.05.During the 1980s and 1990s it became increasingly apparent that the U.S economic activity responded asymmetrically to oil price shocks. The seeming breakdown in the relationship between oil and the economy led researchers to explore different oilprice specifications in an attempt to reestablish the oiloutput relationship. When Mork (1989) did not find a significant relationship between oil and GDP, he separated out oil price changes into negative and positive oil price changes, and reestablished a significant relationship between oil prices and GDP. In follow up studies, Mory (1993) followed Mork and separated the oil price into negative and positive oil price changes and found that the positive oil price shocks Grangercaused key macroeconomic variables, but that negative shocks did not. Mork, Olsen and Mysen (1994) found asymmetry for seven industrialized countries. Lee, Ni and Ratti (1995) also found asymmetry between the effects of negative and positive oil price shocks, which they attributed to in part to price uncertainty. Ferderer (1996) found that increases in oil prices explained more than twice the variation of industrial production growth than did decreases. Hamilton (1996and 1999) proposed his now renowned net oil price, and found a statistically significant and stable negative relationship with output. Davis and 7

8 Haltiwanger (1998) constructed another oil price series that combines asymmetry and persistence. Several different channels have been proposed to account for the inverse relationship between oil price movements and aggregate economic activity. The most basic is the classic supply sideeffect in which rising oil prices are indicative of the reduced availability of a basic input to production. Other explanations include income transfers from the oil importing nations to the oil exporting nations, a real balance effect and monetary policy. Of these explanations, the classic supplyside effect clearly explains why rising oil prices slow GDP growth and stimulate inflation. Classic supplyside effects cannot explain asymmetry. Accordingly, a number of studies emphasize other channels through which oil prices may affect economic activity. Monetary policy, adjustment cost, and asymmetry in petroleum product price changes have been offered as possible explanations for the asymmetry Monetary Policy and Asymmetry Although the role of monetary policy was prominent in early explanations of how oil price shocks affect real economic activity, it was gradually supplanted by real business cycle theory. Nonetheless, an apparent breakdown in the relationship between oil and the economy during the 1980s and 1990s led researchers to question the pure supply shock models and to probe additional channels through which oil could affect the economy. Induced change in monetary policy was one such channel. Monetary policy is a possible explanation for the asymmetric response of the economy to oil price shocks. If wages are nominally sticky downward but not upward, monetary policy can have asymmetric effects. When oil prices rise, wages that are sticky downward will aggravate GDP losses 8

9 if the monetary authority fails to hold nominal GDP constant through unexpected inflation. When oil prices fall, however, real wages must rise to clear the markets. Because nominal wages can adjust upward freely, a monetary policy that fails to hold nominal GDP constant through the unexpected deflation need not be simulative. Tatom (1988, 1993) and BGW provide some evidence that monetary policy is a contributing factor to asymmetry. Tatom finds that the apparent asymmetric response of U.S. economic activity to oil price shocks disappears when the stance of monetary policy or changes in the misery index (which combines unemployment and inflation rates) are taken into account. In contrast, Ferderer (1996) shows that monetary policy cannot account for the asymmetry in his model. Bake, Brown, and Yucel (1999, 2002) also show that the Federal Reserve s response to oil price shocks is not the cause of asymmetry. They find that the asymmetry does not go awayand is in fact enhancedwhen the either the federalfunds rate is held constant or expectations of the federalfunds rate are held constant. Hence, monetary policy does not appear to be the sole cause of the asymmetry on the real side Adjustment Costs Adjustment costs could lead to an asymmetric response to changing oil prices, as first argued by Hamilton (1988). Rising oil price retards economic activity directly, and falling oil price stimulates economic activity directly, but the costs of adjusting to changing oil prices also retard economic activity. Falling oil prices would present both negative and positive effects, which would tend to be offsetting. Adjustment costs could arise either from sectoral imbalances, coordination problems between firms, or because the energytooutput ratio is embedded in the capital stock. Lilien (1982) and Hamilton 9

10 (1988) examine how changes in oil prices create sectoral imbalances by changing the equilibrium relationship between the sectors. Huntington (2000) examines how coordination problems associated with changing oil prices might affect economic activity. Atkeson and Kehoe (1999) examine how puttyclay technology (that is, technology in which the energytooutput, capitaltooutput, and labourtooutput ratios can be varied over the long run but cannot be changed in the short run because they are embedded in the capital stocks) affect on the economic response to changing oil prices. As explained by Ferderer (1996), uncertainty about future oil prices can also adversely affect economic activity by reducing investment demand. Bernake (1983) demonstrates that firms will find it increasingly desirable to postpone irreversible investment decisions when they are more uncertain about future oil prices. Although asymmetry is now fairly well accepted, relatively few studies have attempted to determine empirically through what channels (other than monetary policy) oil price shocks might yield an asymmetric response in aggregate economic activity. Work by Loungani (1986); Davis (1987); Lee et al (1996); Davis, Loungani and Mahidhara (1997); and Davis and Haltiwanger (1998) support but do not directly test Hamilton`s adjustment cost explanation. Balke, Brown and Yucel (1999, 2002) find significant asymmetric output and interest rate responses to oil price shocks, with transmission through market interest rate. They find strong asymmetry in the output response and, in particular, a strikingly similar negative response of output to both positive and negative oil price changes in the short run, which are similar to Mork (1994) and Davis and Haltiwanger (1998). Such findings are consistent with the explanation that oil price shocks necessitate costly adjustment (either intersectoral or intrasectoral as emphasized 10

11 by Davis and Haltiwanger), or sticky downward wages and/or prices (as emphasized by Mork) Petroleum Product Prices Petroleum product prices may also contribute to an asymmetric relationship between crude oil prices and economic activity. Public scrutiny of gasoline markets has led to the view that petroleum product prices respond asymmetrically to crude oil prices. Research provides econometric support for public claims that gasoline prices rise more quickly when crude oil prices are rising than they fall when crude oil prices are falling. Bacon (1991) finds asymmetry for the U.K. gasoline market. Karrenbock (1991); Borenstein, Cameron, and Gilbert (1997); and Balke, Brown, and Yucel (1998) all find some evidence for asymmetric response in U.S. gasoline markets. Huntington (1998) translated the findings of asymmetry in petroleum product prices into a possible explanation for the asymmetric relationship between crude oil prices and aggregate economic activity. He finds that the economy responds symmetrically to changes in petroleum product prices, but that petroleum product prices themselves respond asymmetrically to crude oil prices. The result is an asymmetric relationship between crude oil prices and aggregate economic activity. Huntington also finds that inflation responds symmetrically to crude oil prices. No followup studies have examined Huntington s findings Asymmetry and Transmission Mechanisms The most recent line of research on macroeconomic transmission mechanisms of oil price shocks is being developed in the literature on real business cycle models. These models first developed in the early 1970s, just prior to the first oil price shock of that decade. It was some time before oil price shocks were suspected to be the sort of recurrent, 11

12 anticipated shock that that class of models employs to obtain exogenous supplyside disturbances to macroeconomic equilibrium. David Lilien`s (1982) dispersion hypothesis has been a central focus of this research applied to oil price shocks. The dispersion hypothesis posits that a considerable amount of unemployment can be accounted for by sectoral shifts in demand, which require time for reallocation of labour. This mechanism involves exogenous allocative disturbances causing reallocation of specialized labour and capital. The speed of reallocation may be determined by the particular type of disturbance (Davis, 1987). The dispersion hypothesis modifies the conventional macroeconomic model specification that both the magnitude and direction of oil price shocks are important. Under the dispersion hypothesis, the direction of change is not important: both positive and negative changes increase the amount of labour reallocation required (Loungani, 1986,P.539). Mork, Olsen, and Mysen (1994) estimated regressions of GDP on contemporaneous and lagged oil prices as well as multivariate regressions which included also the inflation rate (measured by the GDP deflator), shortrun interest rates, the unemployment rate, and the growth rate of industrial production for the entire OECD as a proxy for exogenous export demand. The oil priceeffects were stronger and more frequently statistically significant in the multivariate analyses than in the bivariate. All countries except Norway experienced negative relationships between oil price increases and GDP growth. In the multivariate estimation, the U.S., Canada (both at the 2%level), Japan (at 3%), and Germany (at 10%) demonstrated significant evidence of asymmetry. The studies by Smyth (1993) and Jackson and Smyth (1986) suggest that some unknown biases maybe introduced by such a procedure (separating negative and positive oil prices shocks), particularly in longer time series that contain several price cycles. 12

13 A further businesscycle study on the subject of asymmetry and transmission mechanisms is the recent real business cycle model simulated by Kim and Loungani (1992). Their purpose is to distinguish the controversial role of stochastic shocks to technology from other real shocks. They specify an energy price shock as such an alternative and study what proportion of the variance in the volatility of output over the business cycle can be accounted for the two types of shock. Their results tend to reinforce suspicious which have emerged in the past decade regarding the importance of the allocative effects of oil price shocks in the labour market. Karras (1993) estimated a structural VAR of real GNP, the real federal deficit, the GDP deflator, the M2 money supply, the U.S dollarsdr exchange rate, and the price of oil over the period 1973:I1989:IV.Karras`s approach to identifying shocks relies on the error structure of the data series, and oil price shocks so defined account for small amount of variation in GNP; more direct methods of inferring the volatility of oil prices attribute a more prominent role to oil price shocks. Taking the asymmetry of the economic response to the 1986 oil price collapse as one of its departure points, Bohi`s (1989) monograph, and his article(1991) distilling that longer work, involve efforts to identify microeconomics mechanisms by which energy price shocks might propagate their effects throughout the economy. Bohi addresses the composition of demand as a possible route of effect of energy price shocks, but again maintains his pure pricetheoretic focus rather than incorporating business cycle considerations. As in his analysis of the labour market, he estimates zeroorder correlation coefficients between energy intensity and changes in industry output price indexes, between intermediate input cost shares and changes in output price indexes, and between energy intensity and changes in inventories. In Bohi`s analysis of the labour market and demand 13

14 decomposition, no formal models are constructed to guide expectations regarding statistical results or to facilitate interpretation of the results obtained. So, in the absence of formal modelling of business cycle transmission mechanisms, the simplicity of statistical methods employed, and the imprecision of implied hypothesis, the information content of Bohi`s results is unclear. Composition of demand as a transmission has been investigated by Beresnahan and Ramey (1992, pp.2427), who have found that when oil prices increase, plants that produce small cars operate at capacity and plants that produce large cars are idle. Addressing the issue of asymmetry has led to a more general search for transmission mechanisms by which oil price shocks may be propagated into economywide recessions. The empirically compelling shock that initiates the dispersion hypothesis` employment mechanism is oil price shocks. There is evidence at both the plant and aggregate levels that oil price shocks may operate through demand composition effects. Nonetheless, in the search for particular types of shocks that, via various transmission mechanisms, initiate business cycle in general, oil price shocks have not been shown to be principal causes of business cycles. 3. Methodological issues and data In this paper we examine alternative asymmetry hypothesis with a Bivarate and Multivariate time series models of Canada s economic activities. We show symmetry or asymmetry is transmitted via market interest rates to GDP and the aggregate implicit price deflator as well. This purpose is done in three steps. The first step is to verify of the order of integration of variables, through standard tests for the presence of a unit root 14

15 based on the work of Dicky and Fuller (1979, 1981) [ADF] and Kwiatkowski et al (1992) [KPSS] i. Also, we are testing for structural breaks via Perron (1997) tests. Since taking traditional VAR techniques or an error correction model (just the same as a near VAR model) is not valid without doing these standard tests ii. The second step involves testing for cointegration using the Engle Granger (1987), and the error correction method. Engle and Granger s (1987) method is a residual based co integration test, which has been criticized by Kremers et al. (1992) that it has reduced power because it imposes the common factor restriction. For this reason an unrestricted error correction model is employed to test directly for co integration among variables. Engle and Granger (1987) show that, in the presence of co integration, there always exists a corresponding errorcorrection representation, which implies that changes in the dependent variables are a function of the first lagged level of the cointegration vector, as well as changes in other explanatory variables. In the other words, an ErrorCorrection Model (ECM) is simply a VAR with the lagged cointegrating vector added. The aggregate case of this model is as follows; n Y = α + γε + δ Y + γ X + µ t 1 2 1t 1 i t i j t j 1t i= 1 j= 1 n X = α + γε + δ X + γ Y + µ t 1 2 2t 1 i t i j t j 2t i= 1 j= 1 m m Where; Yti and Xtj are the lagged value as Integrated of degree zero I (0), if we suppose the I(1) variables Xt and Yt are cointegrated and εit1 is the lagged co 15

16 integrating vector. The coefficient on the co integrating vector can be interpreted as the amount of adjustment in each period towards the longrun equilibrium. The analysis consists of estimating OLS equations that explain aggregate output, price levels and the shortrun interest rate as a function of crude oil prices and other key economic variables. The present empirical analysis has been carried out using Quarterly data for nominal gross domestic product (NGDP), the average unit valuecost of imported crude oil (NOIL), a short run interest rate (SIR) [Three months tbill], the aggregate implicit price deflator (IMP1997=100) and, the commodity price index (CPI) for the period for Canada s economy. Since the short run interest rate and price level are nominal variables, GDP and the imported cost of crude oil are measured as nominal values. In this paper the imported cost of crude oil is used as a proxy for crude oil prices. All of the variables except crude oil prices have been obtained via time series data produced by Statistic Canada (CANSIM). The imported cost of crude oil was obtained from the International Energy Agency quarterly document (Energy Prices and Indexes). Finally, to include the direct effects of imported oil to Canada, Heckman et al, (1987, pp 249) used the aggregate implicit price deflator instead of the personal consumption deflator. In order to account for monetary policy that targets interest rate (money Supply), so the short run interest rate and the implicit price deflator were added to variables. Tests for the symmetry null hypothesis consisted of adding a separate variable for crude oil price decreases that equalled the price change if negative and zero if positive. If this coefficient is significant; symmetry can be rejected. In these cases, we also estimate an equation with separate variables for price increases and decreases, While 16

17 these two equations are equivalent to each other, The coefficients in this second equation are easier to interpreted, particularly when the relationships involves lagged values. 4. Empirical Results 4.1. Conventional unit Root Tests As a starting point, Tables 1 and 2 present results of applying two standard unit Root Tests: the Augmented Dickey Fuller (ADF) test and the Kwitkowski, Philips, Shin, and Schimt (KPSS) test to all valuables: the Nominal Gross Domestic Product (NGDP), the nominal imported cost of crude oil (NOIL), the shortrun interest rate (SIR), the aggregate implicit price deflator (IMP), and the commodity price index (CPI). In Table 1, we present three versions of the ADF test, which differ by the inclusion of a constant or trend in the regression equation: no constant and no trend, τ ; constant, no trend, τ c ; and constant and trend, τ t. The null hypothesis is that the series are I (1). The ADF statistic suggests the all variables except the commodity price index are Integrated of order one, I (1), whereas the first differences are integrated of order zero, I (0). Therefore, there is no evidence to accept the hypothesis that the time series contain an autoregressive unit root. In Table 2, we present two versions of the KPSS test. The null hypothesis is that the series are I (0) around level ( η µ ), or I (0) around trend ( η τ ). These results are reported for only one lagtruncation parameters. Once again, most of the results are consistent with a unit root, i.e. they reject the null hypothesis of I (0). The exception is the commodity price index. The KPSS statistic do not reject the I (0) hypothesis 17

18 for the first differences of the series at different levels of significance. Therefore, the combined results from both standard unit root tests (ADF, KPSS) suggest that all the series except the commodity price index, appear to be I (1) processes The structural Break Alternative 1 In this section, we use the methodology developed by Perron (1997) of endogenously determined breaks. (3). That is, we undertake estimation without assuming any prior knowledge of any potential break dates. The model is estimated over all possible break dates in the data set, and the break date is chosen to maximize the probability of rejection of the unit root hypothesis. We estimate three models. Model (I) allows only a change in the intercept. A Test is performed using the tstatistics for the null hypothesis that ρ =1(an unit root) in the regression p (I) yt = α0 + α1dut + ddtbt + βt+ ρyt 1+ θi yt i + et i= 1 Where DU = 1( t > T ) and DTB = 1( t = T + 1); T is the endogenously determined t b t b b time of the break. The methodology searches over all possible breaks points and chooses the break point based on the value of the tstatistic. Under model (II), both a change in the intercept and the slope are allowed. p II) yt = α0 + α1dut + ddtbt + βt + γdtt + ρyt 1+ θi yt i + et i= 1 Where DT = t( t > T ). t b 1. This methodology is similar to that suggested by Zivot and Andrews (1992.) For details see Perron, Further evidence on breaking trend functions in macroeconomic variables, journal of Econometrics, 80(1997), page

19 Under model (III), only a change in the slope is allowed. p t i t i= 1 (III) yt = α0 + α1dut + βt+ γdtt + ρyt 1+ θi y + e The results of applying this procedure are presented in Table 3. As we see, at the 1% and 5% significance levels, all of the models fail to reject the null hypothesis underlying unit root for all series except the commodity price index. So we can say, these results are not consistent with the hypothesis that the series are best characterised as stationary around a breaking mean and/or trend function. In the other words, there is structural break in the endogenously given break dates except for the commodity price index. So these results confirm the pervious results of standard unit root tests Conventional Bivariate and Multivariate Co integration Tests Since, gross domestic product (NGPD), the proxy for average crude oil prices and the other key economic variables are integrated of the same order, it is appropriate to look for the relationship between the aggregate economic activity and the crude oil price, the shortrun interest rate, the aggregate implicit price deflator in bivariate and multivariate models.the commodity price index is taken a way since it is integrated of order zero, I (0). The Table 4 summarizes the results of cointegration analysis using the augmented Engle Granger method in Table 4, We present a two versions of the Engle Granger tests, which differ by the inclusion of a constant or trend in the regression equation: only a constant, no trend, τ cτ ; and constant and trend, τ cτ. The null hypothesis is no cointegration among variables in the involved models. The results of the bivariate regression model of aggregate 19

20 economic activity on the crude oil price shows that the hypothesis of no cointegration can be rejected in the both versions of Engle Granger method. Also, in regression model of the crude oil price on aggregate economic activity indicates evidence of cointegration in a both versions.the EngleGranger tests in the Bivariate regression model of the implicit price index and shortrun interest rate on the crude oil price and viceversa (i.e., in the regression models of the crude oil price on aggregate implicit price index and interest rate) suggest the null hypothesis of no cointegration could be rejected in both kind of regression models. As we can see, the Engle Granger tests on the bivariate models imply there is no evidence of weak exogeneity between the proxy for crude oil price and each of the mentioned key economic variables in Canada s economy. Since the influences of the changes of crude oil price is addressed by the changes in the aggregate price level and monetary policy (for instance; changing the interest rate) into the aggregate economic activities, the Bivariate cointegration tests are undertaken between the crude oil price and these key economic variables. So, in order to account for influences on the gross domestic product crude oil price of changes in the price level and monetary policy, the aggregate implicit price level and shortrun interest rate variables were added to the bivariate models for doing Multivariate cointegration tests. These tests are done in the three models as follows; In the regression model of GDP on the crude oil price, the interest rate and the implicit price index; in the model of regression GDP on the crude oil price and the shortrun interest rate; and the regression model of GDP on the implicit price index and interest rate. Since the movement trend of the crude oil price and the aggregate 20

21 implicit price index are similar to each other, these models are selected for multivariate cointegration tests. The results suggest that we cannot fail to reject the null hypothesis of no cointegration in these multivariate models in two versions of EngleGranger test. On the basis of results, we can support the proposition that a long run relationship exists among the aggregate economic activities, the imported the average unit value of imported cost of crude oil, the shortrun interest rate and the aggregate implicit price deflator in Canada s economy over the period under examination ( ) The Error Correction Models (ECM) As we stated in the previous section, most of the economic literature has used a simple shortrun dynamic VAR Model for asymmetry tests of a changing crude oil price. They have used either ordinary least square (OLS) as an efficient estimation of the VAR Model with similar structure for each of the equations, or the SURE Method for estimating equations of a near VAR Model with a different structure for each of the equations in the model. In some of these studies 2, an arbitrary Choleski Decomposition provides an extra equation necessary for identification of the structural model. Also, innovation techniques, like Impulse Response functions and variance decomposition, have been used to obtain information concerning the interactions among the variables Oil price shocks and US economy: where does the asymmetry originate, The Energy Journal, 2002, by N.S.Balke, S. P.A.Brown and Mine.k.Yucel. 3. Applied Econometrics TimeSeries, Iowa State University, 1992, by Walter Enders. 21

22 But, in other studies 4 asymmetry tests have been undertaken by adding up negative changing crude oil prices and / or entering the both of negative and positive changing crude oil prices in the aggregate economic activity model. As we discussed in the second section, these technique (adding up negative changing crude oil price and / or entering both negative and positive changing crude oil price) is used in this paper. By the way, there are the other methods in the economic literature that has been used to carry out asymmetry tests of changing energy price. For this reason, since in the bivariate and multivariate cointegration tests there are evidence of cointegration among involved variables.so as we know a principal feature of cointegrated variables is that their time paths are influenced by the extent of any deviations from long run equilibrium. After all, if the system is to return to the long run equilibrium, the movements of at least some of the variables most respond to the magnitude of the this equilibrium, so the shortrun dynamic Model must be influenced by the deviation from the long run relationship. So, we can apply Error Correction Model. Therefore according the feature of given reported cointegration test, error correction models have been undertaken as a Bivariate and Multivariate ones. The results of the estimated ECM model have been shown in Tables 510.We know the coefficients of the lagged cointegrated vector are the speed of adjustment coefficients, so one or both of these coefficients should be significantly different from zero, otherwise a long run relationship does not appear and the model is not one of error correction or cointegration. In these tables, only coefficients with tstatistics greater than one have been reported, and all of the variables are in first differences. Also, all of the estimated ECM results have been given in terms of drift and trend in 4. Crude oil prices and US economic performance, The Energy Journal, 1998., by Hillard G. Huntington. 22

23 the original cointegrated models. In Tables 5, 6 and 7, we present Bivariate ECM models between aggregate economic activity and the crude oil price, the implicit price deflator and the crude oil price and, the shortrun interest rate and the crude oil price respectively, and viceversa. The results based on ECM models with trend are more reliable than models with drift. Also, at least one of the coefficients of long run equilibrium term in two ways models is significantly differ from zero, so we can say, there are the long run equilibrium relationships between nominal GDP and the crude oil price, the aggregate implicit price deflator and the crude oil price, and the shortrun interest rate and the crude oil price. But, according the Schwartz Bayesian criteria (SBC), the best model has been selected with 4 lags and no significant coefficients have not been derived in the results.it seems the entering more key economic variables into the Bivariate long run equilibrium models would be useful.for this reason, multivariate error correction models have been estimated and reported in Tables 8, 9, and 10. Since, the multivariate cointegration tests show evidence of cointegration among involved variables. ECM models have been selected for estimating the long run equilibrium relationship of these variables. In Table 8, we present the long run equilibrium relationship among nominal GDP and the crude oil price, the implicit price deflator and the short run interest rate. The coefficient of the speed adjustment term (first lagged cointegrating vector) is not significantly different from zero, in both models with drift and trend. But, in some of the estimated ECM models, i.e., in the regression of the implicit price index on the other variables, these coefficients are not necessarily different from zero (That is not been reported here). Therefore, we cannot say there is not the long run equilibrium 23

24 relationship among these four key economic variables. Also, according SBC criteria model with four lags is the best model that the coefficient with tstatistics of more than one has been reported. Since, the movement trends of crude oil price and the aggregate implicit price index are similar to each other, in Table 9; we present the error correction model of the regression of nominal gross domestic product on the crude oil price and the short run interest rate. As we see, the ECM model with trend statistically has the most significant coefficient of the error correction term. So we can say, there would be a long run equilibrium relationship among GDP with the crude oil price and the shortrun interest rate, as a representative of monetary policy. Also, in Table10, are presented the error correction model of the regression GDP on the shortrun interest rate and the aggregate implicit price deflator with drift and trend separately. It seems this ECM model indicates a reliable long run equilibrium relationship among these variables Bivariate and Multivariate Asymmetry Tests of changing crude oil price Thus far, we showed that an error correction model could be used for studying the relationships amongst aggregate economic activity, the average unit value of imported cost of crude oil and other key economic variables in Canadian Economy. Some of the previous studies (Huntington 1998) used directly efficient OLS estimation of shortrun dynamic VAR models to allow asymmetry tests according to the aforementioned techniques (adding up negative changes of crude oil price and /or putting positive and negative changes of crude oil price in the estimated output equation of VAR model) without assessing cointegration tests and the long run relationships of the involved variables. In this paper, we used an efficient OLS 24

25 estimation of error correction models as Bivariate and multivariate to do asymmetry test with adding up negative changes of crude oil price and /or putting positive and negative changes of crude oil price in the estimated output equation of VAR model. These results have been shown throughout Tables 5 to 9. These tests are done to assess the symmetry relationship between crude oil price changes and GDP. Table 5 shows the asymmetry test only in the regression model of GDP on the crude oil price with drift and trend in the both equivalent techniques (adding up negative changes of crude oil price and /or putting positive and negative changes of crude oil price in the estimated output equation of VAR model. As we see, there is no evidence for rejecting the null hypothesis of a symmetrical relationship. Since, the changing crude oil price has effects on aggregate economic activity via changes in the aggregate price level and interest rate as symbol of monetary policy. This could make happen under affecting of dictated policy by government after oil price shocks for adjusting effects of the crude oil price shocks on the aggregate economic activity. So, in Tables 6 and 7 we are doing the source asymmetry tests with drift and trend under ECM models. The results indicate that there is not any reason for rejecting the symmetry null hypothesis. That means, the symmetry relationship between changing crude oil price and the aggregate economic activity is due to symmetric relationship of oil price changes with the changing aggregate implicit price index, and shortrun interest rate. The multivariate asymmetry tests have been reported in Tables 8 and 9 with drift and trend in the equivalent oil price changes techniques. In Table 8, we present asymmetry tests in the multivariate regression model of GDP regressed on the crude oil price, the implicit price deflator and the shortrun interest rate. In Table 9, this test 25

26 is reported for the multivariate model among GDP and the crude oil price, and the shortrun interest rate. All of the results indicate fail to reject the null hypothesis of a symmetric relationship between aggregate economic activities and changing of the crude oil price. Therefore, according to the results in Tables 8 and 9 (which are more reliable than the Bivariate asymmetry tests, because the some of the important key economic variables such as the aggregate price level and the interest rate are in the aggregate economic activity model), we can say that the imported crude oil price shocks to Canada (as reliable proxy of the crude oil price) has a symmetric effects on aggregate economic activity and this effect is yield via the monetary policy by the government and changes in the price level. This result contradicts most of the studies in economic literature about the effect of crude oil price shocks on the United States economy. In these models, the effects of changing energy price on aggregate economic activity is addressed via such indirect effects as redistribution of the real income between energyexporting and energyimporting countries (Termsoftrade), changes in the aggregate demand of a given country s trading partners (Foreign demand), uncertainty in both house hold and businesses, the impact on the production costs of non energy producers and the real income of households, and short and longterm effects on energy supply productions. So, it seems the asymmetric relationship in the United States economy due to the crude oil price shocks is created more via the uncertainty and in the Canada s economy complementary effects of these indirect factors towards a longrun equilibrium adjustment originates this symmetric effect. In other words the control on instruments of money markets by government s monetary policy (i.e., interest rate) 26

27 and the aggregate price level gives a longrun equilibrium adjustment into effects of oil price shocks on GDP under the framework of reliable ECM models. Therefore, it seems Canada government s monetary policy (i.e., interest rates) and the implicit price deflator seem to be as some sources of symmetric and reversible response of Canada s economy to the crude oil price shocks. 5. Conclusion The purpose of this paper was to examine the asymmetry between crude oil price shocks and aggregate economic activities in the frame work of developed various recently timeseries techniques in the Bivariate and the multivariate context for Canada s economy and finding out some of its affecting factors over period 1984 to In doing so, time series techniques such as UnitRoot testing, a structural break test, Bivariate and Multivariate cointegration and procedures in vector Error Correction Models were presented. This analysis supports several conclusions as follows: 1The all of the key economic variables including; the aggregate economic activities (NGDP), the average unit value of imported cost of crude oil (NOIL), the aggregate implicit price deflator (IMP), the shortrun interest rate (SIR), and the commodity price index (CPI) are integrated of order one, I(1). In the other words, these variables have a unit root. 2 The conventional structural alternative break test by Perron (1997) suggests no evidence of structural breaks, based on the endogenously taken break dates. This confirmed the results of unit root tests. 27

28 3 The conventional Bivariate and Multivariate cointegration tests by Engle and Granger support that there is cointegration between nominal GDP and the crude oil price and shows cointegration of nominal GDP with the crude oil price, the aggregate implicit price deflator and the shortrun interest rate in the frame work of different multivariate models. Also, evidence of cointegration is seen between the crude oil price and the implicit price index as well between the shortrun interest rate and the crude oil price. On the other hand, there is evidence of weak exogeneity between GDP and the crude oil price and, between each of the other key economic variables and the crude oil price. 4In this paper we showed that there are longrun equilibrium relationships between nominal GDP and the crude oil price, the aggregate implicit price deflator and the crude oil price, and the shortrun interest rate and the crude oil price in the framework of bivariate error correction models. Also, we see similar longterm and equilibrium relationships among nominal aggregate economic activity and the other mentioned key economic variables in different multivariate ECM models. By the way, the control on instruments of money markets by government s monetary policy (i.e., interest rate) and the aggregate price level gives a longrun equilibrium adjustment into effects of oil price shocks on GDP under the framework of reliable ECM models. 5The asymmetry test for crude oil price changes in both equivalent technique (adding up negative changes of crude oil price and/or adding the positive and negative changes in the crude oil price) are applied to explain effect of changes in the crude oil price on the aggregate economic activity by ErrorCorrection model 28

29 techniques in both Bivariate and Multivariate models. In contrast with a majority of economic literature, the results show a significant portion of the symmetry in the Canada s economy response to the crude oil price changes in bivariate model in both equivalent techniques. Also, this symmetry economy s response is obtained in the reliable Multivariable model with adding up the interest rate and the aggregate price level or only the interest rate. Since, government s monetary policy (i.e., interest rates) and the implicit price deflator seem to be as some sources of symmetry Canada s economy response to the crude oil price shocks. So, as source of this symmetric response, we did the equivalent asymmetry tests under the framework of bivariate model as the regression of the aggregate implicit price deflator and the interest rate on the crude oil price. The results indicate there is a symmetry relationship between the changes of crude oil price and these variables as sources of Canada economy s response to the oil price changes. In the other words, the mentioned symmetry response of aggregate economic activity has been originated from changes of the short run interest rate by monetary policy of the government and in the aggregate level of price index. 29

30 Variable τ k Table 1 Augmented DickeyFuller Tests τ c K τ t K Conclusion: The variable is: NOIL I (1) NGDP I (1) SIR I (1) IMP I (1) CPI I (0) Notes: 1) This table reports the ADF tests, for testing the unit root null hypothesis in the relevant variables. All of the variables are in nominal values. The τ, τ c and τ t statistics are described in the text. The k is the optimal number of lags that has been selected using the SchwartzBayesian criteria (SBC). 2) At the 1% significance level, the critical value for the τ, τ c and τ t statistics are 2.6, 3.51, and 3.18 respectively. Also, the critical values at the 5% significance level for the τ, τ c and τ t statistics are 1.95, 2.89 and 3.45 respectively. These critical values are reported from Hamilton (1994). 30