Jean-Pierre Allegret
email: jallegret@u-paris10.fr.

Valérie Mignon
email: valerie.mignon@u-paris10.fr

Audrey Sallenave
email: audrey@sallenave.fr

Oil price shocks and global imbalances: Lessons from a model with trade and financial interdependencies *

Keywords: JEL Classification: C32, F32, Q43 oil prices, global imbalances, global VAR

The aim of this paper is to investigate oil price shocks' effects and their associated transmission channels on global imbalances. To this end, we rely on a Global VAR approach that allows us to account for trade and financial interdependencies between countries. Considering a sample of 30 oil-exporting and importing economies over the 1980-2011 period, we show that the nature of the shock-demand-driven or supply-drivenmatters in understanding the effects of oil price shocks on global imbalances. In addition, we evidence that the main adjustment mechanism to oil shocks is based on the trade channel, the valuation channel being at play only on the short run.

Introduction

In a context of increasing scarcity of fossil fuels, and more particularly oil, the relationship between energy prices and current-account imbalances has become a key issue in the economic literature (IMF, 2011). Since the late 1990s, this theme has increasingly prevailed in the extensive study of global imbalances' persistence, as well as in the analysis of the recent financial crisis.1 Changes in energy prices impact worldwide current-account imbalances and, consequently, countries' net foreign asset positions, since an increase in energy prices can be considered as a transfer of wealth from importing to exporting countries. More specifically, considering the energy price-current account imbalances relationship, two main transmission channels can be highlighted. The first one refers to the trade channel that focuses on the dynamics of energy exports and imports for exporting and importing countries. Two related elements are of particular importance here: (i) the propensity of energy-importing countries to import due to increased revenues, and (ii) the geographical distribution of their international trade. The second channel is related to international capital flows linked to the increase in energy prices; these flows being important since many producing countries have a limited propensity to import. This channel can be apprehended by relying on intergenerational considerations: in a sustainable development perspective and with exhaustible energy resources, countries need to save part of their current earnings to shift resources toward future generations.

Within this context, the aim of this paper is to provide a detailed investigation of oil price shocks' effects and their associated transmission channels on global imbalances. Regarding previous literature, the IMF (2006) evidences that while oil price shocks have a short-lived impact on current accounts, they exert a significant effect on net foreign asset positions. In addition, oil importers suffer from slower growth and real exchange rate depreciation, while oil exporters experience higher growth and real appreciation. As equity prices fall in oil-importing countries, a significant valuation channel is identified. [START_REF] Kilian | Oil Shocks and External Balances[END_REF] investigate the effects of oil-supply driven and oil-demand driven shocks on external accounts of oil-importing and oil-exporting countries throughout the 1975-2006 period. By using a vector autoregressive (VAR) framework, they focus on the role of the non-oil trade balance in offsetting oil trade changes and on the effects of shocks (trade channel) on the value of gross foreign assets and liabilities (valuation channel). They show that (i) the source of the shocks matters insofar as oil-supply and oil-demand shocks have different effects on external accounts 2 , and (ii) trade and valuation channels exert a significant influence on the global adjustment process. Focusing on foreign trade as a key channel of transmission of oil shocks, [START_REF] Korhonen | Trade Linkages and Macroeconomic Effects of the Price of Oil[END_REF] estimate a system of simultaneous equations capturing the interlinkages among the GDP growth rates of different countries through the trade matrix. Their approach is based on the following intuition: (i) for net oil importers, higher oil prices constitute a negative supply shock that slowdowns growth, reducing the initial positive effect for net oil exporters, but (ii) at the same time, a higher growth in oil-exporting economies may lead to larger exports from oil importers. The specificity of their approach is that responses of growth rates are allowed to vary over time as the trading pattern changes. Considering the case of Russia from 1995 to 2006, [START_REF] Korhonen | Trade Linkages and Macroeconomic Effects of the Price of Oil[END_REF] find that the direct positive effect of higher oil prices is dampened by the negative indirect effect that rests on the slower growth in its main trading partners. [START_REF] Cashin | The Differential Effects of Oil Demand and Supply Shocks on the Global Economy[END_REF] analyze the macroeconomic consequences of oil price fluctuations across different countries over the 1979-2011 period, through the estimation of a global VAR model with a set of sign restrictions on the generalized impulse responses. They show that supply-and demand-driven shocks have specific impacts on macroeconomic variables, and that oil importers and exporters react differently.

This paper falls into this strand of the literature by focusing on the effects of oil price shocks on global imbalances, with particular attention paid to their transmission channels. To this end, we consider a panel of 30 countries over the 1980-2011 period. Our sample of countries accounts for more than 85 percent of the world GDP in 2011, and is composed by 18 oil importers (their share of world oil imports amounts to 75 percent throughout the studied period) and 12 oil exporters (covering 60 percent of world oil exports).3 Our main contributions are the following. First, from a methodological viewpoint, we rely on the global VAR (GVAR) approach introduced by [START_REF] Pesaran | Modelling Regional Interdependencies Using Global Error-Correcting Macroeconometric Model[END_REF] which allows us to account for trade and financial interdependencies between countries-which is a key condition to correctly analyze global imbalances. Second, while most of previous studies consider only oil-importing countries4 , we also include oil exporters in our sample of economies. Third, acknowledging that oil price shocks may have different effects over time5 , we consider various types of structural shocks following Kilian (2009)'s identification scheme:6 (i) supply shocks on crude oil, (ii) aggregate demand shocks, identified by demand shocks affecting all industrial commodity markets, and (iii) demand shocks specific to the oil market. Fourth, and compared to [START_REF] Cashin | The Differential Effects of Oil Demand and Supply Shocks on the Global Economy[END_REF] which is the closest study to ours, we pay particular attention to the adjustment channel, distinguishing between trade channel and valuation effects. Our findings show that the nature of the shock matters in understanding the effects of oil price shocks on global imbalances. In addition, we evidence that the main adjustment mechanism to oil shocks is based on the trade channel, the valuation channel being at play only on the short run.

The rest of this paper is organized as follows. Section 2 briefly describes the GVAR approach. Section 3 presents the data and outlines our estimation methodology. Results and related comments are reported in Section 4, while Section 5 concludes the paper.

The Global VAR framework

Consider a set of N +1 countries/regions indexed by i = 0, 1, 2, ..., N , with country 0 denoting the reference one. 7 The GVAR model consists in a collection of individual VARX models for each country that are linked together via a "linkage matrix". For the ease of exposition, and without loss of generality, consider V ARX(1, 1) specifications (see [START_REF] Pesaran | Modelling Regional Interdependencies Using Global Error-Correcting Macroeconometric Model[END_REF][START_REF] Dees | Exploring the International Linkages of the Euro Area: a Global VAR Analysis[END_REF] for a generalization).8 Those individual VARX models, that account for common global variables, are given by:

x i,t = a i,0 + a i,1 t + Φ i x i,t-1 + Σ 1 j=0 Ψ i,j x * i,t-j + Σ 1 j=0 τ i,j d t-j + ε i,t (1)
for t = 1, 2, ..., T and i = 0, 1, 2, ..., N . x i,t is a (k i × 1) vector containing country-specific domestic variables, x * i,t is a (k * i × 1) vector of country-specific foreign variables, and d t is a m-dimensional vector of observed common global variables assumed to be weakly exogenous to the global economy. Φ i , Ψ i,j , and τ i,j are of dimension (k i × k i ), (k i × k * i ) and (k i × m) respectively. The vectors of fixed intercepts and of deterministic time trend coefficients are both (k i × 1). ε i,t is a (k i × 1) vector of idiosyncratic country-specific shocks and is assumed to be serially uncorrelated with zero mean and non-singular covariance matrix:

ε i,t ∼ i.i.d(0, Σ ii ) (2)
The foreign variables specific to country i, x * i,t , are constructed as a weighted sum of the corresponding variables of the other countries. To this end, we use trade weights, reflecting the specific geographical trade composition of each economy.9 We thus have:

x * i,t = N j=1 w ij x j,t (3)
where w i,j stands for the share of country j in the total trade of country i (measured in U.S. dollars), i = j. We have:

N j=1 w ij = 1 (4)
for all i, j = 1, ..., N and w ii = 0 for all i = 1, ..., N . The weights we consider here rely on the average geographic distribution of imports and exports of goods and services over the 1980-2011 period. 10

Regarding the estimation strategy, we follow the procedure suggested by [START_REF] Pesaran | Modelling Regional Interdependencies Using Global Error-Correcting Macroeconometric Model[END_REF] and [START_REF] Dees | Exploring the International Linkages of the Euro Area: a Global VAR Analysis[END_REF]. We first check that foreign and common global variables are weakly exogenous to ensure that Equation (1) can be independently estimated on a country-bycountry basis. 11 We then stack the country-specific domestic and foreign variables, to study the dynamics for all the variables and all the considered countries simultaneously. More specifically, Equation ( 1) is rewritten as follows:

A i z i,t = a i,0 + a i,1 t + B i z i,t-1 + τ i,0 d t + τ i,1 d t-1 + ε i,t (5)
where

z i,t = (x i,t , x * i,t ) , A i = (I, -Ψ i,0 ) and B i = (Φ i , Ψ i,1 ). A i and B i are of dimension k i × (k i + k * i )
, and the rank of (A i -B i ) gives the number of long-run relationships that exist among x i,t and x * i,t .

In a last step, we combine the country-specific models into an overall representation. To this aim, we collect all country-specific variables in a (k × 1) vector x t = (x 0,t , x 1,t , ..., x N,t ) with k = Σ N i=0 k i . Country-specific variables in terms of x t are then given by:

z i,t = W i x t (6)
for i = 0, 1, 2, ..., N , where W i is a (k i + k * i ) × k matrix of fixed constants defined in terms of country-specific weights w ij . Then, stacking all country-specific equations, we get:

Γx t = a 0 + a 1 t + Cx t-1 + τ 0 d t + τ 1 d t-1 + t ( 7
)
where 11 This assumption is needed due to the high number of parameters that exceeds the number of available observations. Results are available upon request to the authors.

a 0 =       a 0,0 a 1,0 . . . a N,0       , a 1 =       a 0,1 a 1,1 . . . a N,1       , t =       0,t 1,t . . . N,t       , Γ =       A 0 W 0 A 1 W 1 . . . A N W N       , C =       B 0 W 0 B 1 W 1 . . . B N W N       , 10 See Section 3.
and τ 0 =       τ 0,0 τ 1,0 . . . τ N,0       , τ 1 =       τ 0,1 τ 1,1 . . . τ N,1       .
Assuming that the (k × k) matrix Γ is non-singular, we can deduce the GVAR model in its reduced form and solve it recursively so as to predict the future values of x t :

x t = Γ -1 (a 0 + a 1 t + Cx t-1 + τ 0 d t + τ 1 d t-1 + t ) (8)
3 Estimation methodology

Sample of countries

We consider quarterly data over the 1980Q1-2011Q1 period for the 30 following countries: Algeria, Argentina, Australia, Bahrain, Brazil, Canada, Chile, China, the Euro area, India, Indonesia, Japan, Korea, Kuwait, Malaysia, Mexico, New Zealand, Nigeria, Norway, Oman, the Philippines, Qatar, Saudi Arabia, Singapore, South Africa, Turkey, the United Arab Emirates, the United Kingdom, the United States, and Venezuela. To account for potentially different impacts of oil supply/demand shocks, we split our sample in two sub-groups of countries depending on whether they are oil importers or oil exporters. To make the empirical analysis more tractable, we also group our countries in four regions, namely Latin America, Emerging Asia, the Gulf region and Rest of the World 12 (see Table 1). The Euro area is considered as an economy as a whole, and is constructed as a weighted average of Germany, France, Italy, Spain and the Netherlands, using country-specific average purchasing power parity GDP weights 13 over the 2006-2008 period. A similar methodology is used for the construction of the four other regions, namely Latin America, Emerging Asia, the Gulf region, and ROW.

Individual country-specific models

We consider four country-specific variables, namely real GDP (y i,t ), real exchange rates (rer i,t ), equity prices (ep i,t ) and current accounts (ca i,t ). 14 The country-specific vector of domestic variables x i,t is thus given by:

x i,t = (y i,t , rer i,t , ep i,t , ca i,t ) (9)
y i,t is given by the ratio of nominal GDP to consumer price index (CPI), expressed in logarithm and in constant US dollars. rer i,t denotes the logarithm of the real effective exchange

12 Denoted ROW hereafter. 13 Country-specific weights are extracted from the World Development Indicators' database (World Bank).

14 Data sources are given in Appendix A. The foreign-specific variables are constructed from the domestic ones using average trade weights over the 1980-2011 period. Those weights are based on the sum of imports and exports, and are extracted from the Direction of Trade Statistics database. 16 Having defined four regions, the regional trade share is also constructed so that w ii = 0, where i denotes either a country or a region, the i th row summing to one for all i. The vector x * i,t of country-specific foreign variables is thus given by:

x * i,t = y * i,t , rer * i,t , ep * i,t , ca * i,t (10)
Finally, in addition to these four country-specific variables, our VARX models include two common global variables, namely the oil price and oil production. As previously mentioned, 15 Note that current-account series for Mexico, the Philippines, Argentina and Brazil have been seasonally

adjusted by the reg-ARIMA procedure (regression models with ARIMA errors, in which the mean function of the time series is described by a linear combination of regressors, and the covariance structure of the series is that of an ARIMA process). For the sake of completeness, we have also used the TRAMO-SEATS procedure, leading to similar results. 16 The weighting matrix is given in Appendix F.

we consider two reference countries/regions, the U.S. and the Gulf region. Following [START_REF] Pesaran | Modelling Regional Interdependencies Using Global Error-Correcting Macroeconometric Model[END_REF] and [START_REF] Dees | Exploring the International Linkages of the Euro Area: a Global VAR Analysis[END_REF] among others, we include the oil price as an endogenous variable in the U.S. model: where qoil denotes the world oil production (in logarithm).

x
The foreign counterparts of these vectors of variables for the U.S and Gulf region models are respectively given by:

x Table 2 summarizes the endogenous and foreign variables included in the country-specific models.

Oil supply/demand shock identification

To account for the different types of shocks, we need to discriminate between oil supply-driven and oil demand-driven shocks. To this aim, we impose sign restrictions on oil price, oil production and real GDP for both oil-exporting and oil-importing countries/regions. We rely on structural vector autoregressive (SVAR) models to identify oil-demand and oil-supply shocks (see among others [START_REF] Peersman | Oil and the Euro Area Economy[END_REF]Baumeister and Peersman, 2010;and Baumeister et al., 2010). The idea underlying sign restrictions is that structural shocks can be identified by checking whether the signs of the corresponding impulse responses are in line with economic theory.

According to [START_REF] Fry | Some Issues in Using Sign Restrictions for Identifying Structural VARs[END_REF], the sign restrictions' approach suffers from two drawbacks: it does not wedge a unique structural model, and any sign restriction identification procedure is likely to be imperfect. More precisely, the authors provide an analytical example based on a simple two equations-demand/supply model in which sign restrictions are not able to catch the correct sign of the impulse responses due to the very weak information embodied in the restrictions. On the contrary, [START_REF] Paustian | Assessing Sign Restrictions, The B.E[END_REF] argues that sign restrictions are able to pin down the correct sign of the impulse responses generated by a dynamic stochastic general equilibrium (DSGE) model provided that a fairly large number of sign restrictions is imposed.

Regarding the criticisms addressed to the sign restriction approach, our empirical analysis is in line with [START_REF] Chudik | Using the Global Dimension to Identify Shocks with Sign Restrictions[END_REF] who stress the benefits that can be derived from the global dimension of the GVAR for the identification of shocks, by adding a large number of sign restrictions. The global dimension indeed allows shifting from a weak information situation to a highly informative situation.17 More specifically, to distinguish between the different shocks' effects, we have to separate equations determining oil-demand and oil-supply shocks, justifying the need for an oil production equation and an oil price one for the identification of both disturbances.

Oil supply-driven shocks are then associated with a rise in oil prices, a fall in oil production, and no global economic activity expansion (see Table 3). Conversely, oil demand-driven shocks are associated with a positive co-movement between oil prices and oil production. The oildemand shock we consider here is a shock caused by an increase in global economic activity, leading us to expect the GDP growth of both oil importers and exporters to be positively associated to this shock.

Empirical results

Considering that the current balance is defined as the sum of merchandise trade balance, service trade balance and income balance, we successively analyze the responses of real GDP, real effective exchange rates, real equity prices, and current-account balances to oil price shocks.

The response of the current-account balance to oil shocks indeed results from the interaction of different transmission channels: (i) the trade channel proxied by economic activity in both net oil importers and exporters (real GDP); (ii) the inflation channel embodied by the real effective exchange rate; and (iii) the valuation effect represented by the equity price. As stressed above, two oil shocks-supply-driven and demand-driven shocks-are distinguished in order to investigate whether supply-driven (demand-driven) oil price shocks have a stronger influence than demand-driven (supply-driven) shocks on global imbalances. Impulse-response functions derived from the estimation of our GVAR model are reported in Appendices B and D for oil-exporting countries, and in Appendices C and E for oil importers.

Responses of real GDP

Consider first the case of oil-importing countries. As positive oil price shocks deteriorate terms of trade in those economies, they are accompanied by a transfer of wealth to oil-exporting countries. As a result, the domestic absorption in the former may contract over time. Overall, the two oil price shocks (supply-driven and demand-driven) do not have a strong and negative impact on real GDP (Appendices C and E). More specifically, except for the United States (supply-driven shock) and the Euro area (demand-driven shock), real GDP increases in the aftermath of the shocks. These results are in line with [START_REF] Rasmussen | Oil Shocks in a Global Perspective: Are they Really that Bad?[END_REF] who find that large oil price shocks 18 do not have a widespread negative effect on economic activity in net oil-importing countries. Similarly, using a multiregion dynamic general equilibrium model, the IMF (2011) suggests that a decline in the average growth rate of world oil production does not lead to severe long-term output effects.

Regarding specifically the U.S. case, the supply-driven oil price shock has a negative-but short-lived-influence on real GDP (Appendix C). Such a result is expected insofar as the identification of our GVAR model is based on negative relationships between the supplydriven shock and global economic activity (see the sign restrictions in Table 3). In addition, a negative response of real GDP may result from the heavily dependence of some oil importers on energy consumption [START_REF] Peersman | Cross-Country Differences in the Effects of Oil Shocks[END_REF]. However, the geographical composition of trade and the leading influence of oil prices on other commodity prices should also be accounted for, as trade links may indeed explain the positive response of real GDP to supply-driven shocks in China, Emerging Asia, and Japan. As stressed by the IMF ( 2011) and [START_REF] Cashin | The Differential Effects of Oil Demand and Supply Shocks on the Global Economy[END_REF], Asian economies benefit from the increased exports to net oil-exporting countries-as confirmed by the trade matrix (see Appendix F) showing that these economies have close trade relations with many net oil exporters. 19 This effect is strengthened by the positive impact of the driven-supply shock in the ROW and Latin American economies. Indeed, in these two sets of countries, the oil supply-driven shock leads to an increase in real GDP, and such a response rests on the positive co-movement of non-energy commodity prices with energy prices-agricultural products and/or fuel and mining products accounting for a significant share of total exports in countries belonging to these regions.20

Considering now the impact of the oil demand-driven shock-explained by an expansion in global economic activity-our findings show that, as expected, real GDP increases in the aftermath of the shock in all importing countries but the Euro area for which the effect lasts after one year (Appendices C and E). Interestingly, the time profile comparison of the two shocks evidences that the positive impact of the supply-driven shock is shorter than that of the demand-driven shock. This finding qualifies our overall result that the two shocks have a qualitatively similar influence on real GDP. Specifically, if these shocks tend to exert a positive impact on real GDP in a multilateral framework, the shorter-lived effects of the supply-driven shock support the view that the increase in oil prices explained by a contraction in oil production negatively affects global economic activity.

Turning now to oil exporters, the response of real GDP to oil price shocks in those countries depends on numerous factors. Some of them refer to supply conditions such as investment in the energy sector and the strategy of production diversification. Those supply conditions are closely related to the policies adopted by domestic authorities, but also to the development level of the financial system. While the former refers to the use of additional income from higher oil prices-mainly through fiscal policy-the latter concerns the ability to allocate savings efficiently. In addition, as stressed by the Dutch disease literature21 , an increase in oil prices may lead to real exchange rate appreciation, implying distortions in resource allocation. However, as suggested by [START_REF] Berument | The Impact of Oil Price Shocks on the Economic Growth of Selected MENA Countries[END_REF], a real appreciation decreases the prices of imported intermediary products that stimulates production. Finally, the response of real GDP to oil price shocks partly mirrors the reaction of net oil-importing countries.

As evidenced in Appendices B and D, the two oil shocks have different influences on real GDP in net oil exporters. While the supply-driven shock is not necessarily followed by a rise in real GDP, economic activity tends to increase in the aftermath of the demand-driven shock. More specifically, regarding supply-driven shocks, real GDP rises in Algeria and Mexicowith long-lasting effects observed in these countries-Nigeria, and to a lesser extent Canada. These countries share two common distinguishing features. First, throughout much of the studied period, their oil production rose. Second, they experience a common increase in their oil trade balance surplus over time. 22 Conversely, Appendix B displays a negative response of real GDP in the Gulf region, Indonesia, the United Kingdom, and Venezuela. Regarding the Gulf region, in addition to its high levels of macroeconomic volatility [START_REF] Arezki | Natural resources, Volatility, and Inclusive Growth: Perspective from the Middle East and North Africa[END_REF], our findings may be explained by the presence of productive inefficiencies in this area.

The negative response of the real GDP in Indonesia and the United Kingdom rests on two main factors: the declining trend in oil production (since 1990 and 1999, respectively), and a shifting position from net oil exporters to net oil importers (since 2003 and 2004, respectively). Venezuela has been experiencing a declining trend in its oil production since 1998, resulting from institutional deficiencies (corruption, fiscal greed...) and insufficient investment in the energy sector. In other words, Venezuela is affected by the resource curse.23

When significant, the oil demand-driven shock leads to an increase in real GDP in all countries except for Norway-the negative response is significant only at the impact-the United Kingdom after two years, and Indonesia after three years. Whatever the type of shock, Norway seems thus particularly immune from oil price changes. However, this country is the largest oil exporter in the world-the average ratio of oil exports to total exports amounting to 55.3 percent over the studied period-and oil and natural gas sectors provide the government with around 30 percent of its revenue. In fact, our results are in line with the literature that stresses the role of fiscal policy in this country. For instance, [START_REF] Pieschacón | The Value of Fiscal Discipline for Oil-Exporting Countries[END_REF], by using a VAR model to evaluate the effects of oil price changes in some macroeconomic variables in Mexico and Norway, shows that the lack of significant response for the latter contrary to the former is due to the transfer of the totality of its oil cash flow to the Government Pension Fund-Global. Indeed, such a framework allows Norway to conduct a countercyclical fiscal policy (see also [START_REF] Gylfason | Natural Resource Endowment: A Mixed Blessing?[END_REF].

Responses of real exchange rates

A rise in the real oil price represents negative (positive) terms of trade and income shocks for net oil importers (net exporters). As a result, since the real exchange rate adjustment ensures current-account sustainability, general equilibrium models predict the real exchange rate to depreciate (appreciate) in net importing (net exporting) countries. 24 For instance, in net oil importers, a real exchange rate depreciation allows the improvement of the nonoil trade balance that compensates for the degradation of the oil trade balance. Broadly speaking, our results contradict these theoretical predictions. On the one hand, we generally find that the real exchange rate in net oil importers tends to appreciate whatever the type of the underlying shock (Appendices C and E), emphasizing the inflationary consequences of the oil shock. 25 On the other hand, for net oil exporters, there is no clear link between oil price shocks and real exchange rate, whatever the exchange-rate regime adopted by those countries. It should be noticed that the demand-driven shock tends to be accompanied by more frequent real appreciation episodes while the opposite is observed for the supply-driven shock, suggesting that inflationary pressures are stronger when the oil price increase is due to a rise in global economic activity. The strongest appreciation is observed (i) on the short run for Venezuela, confirming that this country is faced with important difficulties to stabilize the economy in the aftermath of oil price shocks, and (ii) on the long run in the Gulf region, suggesting that the peg to the U.S. dollar constraints the ability of authorities to contain inflationary pressures due to oil shocks.

While [START_REF] Cashin | The Differential Effects of Oil Demand and Supply Shocks on the Global Economy[END_REF] find that real exchange rate appreciates in oil exporters, our results are in line with [START_REF] Buetzer | Global Exchange Rate Configurations. Do Oil Shocks Matter?[END_REF] and [START_REF] Dauvin | Energy Prices and the Real Exchange Rate of Commodity-Exporting Countries[END_REF]. Using a fixed effects pooled panel model for a sample of 12 advanced and 32 emerging economies over the 1980-2011 period, [START_REF] Buetzer | Global Exchange Rate Configurations. Do Oil Shocks Matter?[END_REF] show that there is no evidence of systematic appreciation of net oil exporters relative to net importers, emphasizing the role played by the accumulation of foreign exchange reserves. In a similar way, [START_REF] Dauvin | Energy Prices and the Real Exchange Rate of Commodity-Exporting Countries[END_REF] estimates panel smooth transition regression models for 10 energy-exporting and 23 commodity-exporting countries over the 1980-2011 period. She does not identify a clear relationship between positive terms of trade shocks and the real exchange rate appreciation for oil-exporting countries (except for Venezuela).

Responses of real equity prices

Changes in net foreign asset positions are part of the external adjustment in the aftermath of positive oil price shocks [START_REF] Kilian | Oil Shocks and External Balances[END_REF]. More specifically, the valuation channel rests on the following mechanism: as net oil exporters (importers) diversify their portfolio by holding assets from oil-importing (exporting) economies, a change in equity returns due to oil price shocks has an influence on the global adjustment process. Changes in asset values are an expected consequence of oil price shocks. Indeed, as oil price shocks are equivalent to a transfer of wealth from net oil importers to net oil exporters, we must observe a negative (positive) impact on equity returns in the former (the latter). As a result, lower (higher) equity prices in oil-importing (exporting) countries play as a wealth transfer in the opposite way. In other words, the valuation channel implies a transfer of some of the increased wealth that accompanies oil price shocks from net oil exporters to net importers. We analyze the valuation channel by considering the response of real equity prices in net oil importers and exporters to supply-driven and demand-driven shocks.26

Considering first the case of net oil importers (Appendices C and E), the short-term impact of the supply-driven shock is negative (except in Japan at the impact) while we find the opposite for demand shocks. Such a result supports our previous finding concerning the responses of real GDP. More specifically, as oil demand shocks are driven by an increase in global economic activity, we can expect a positive response of real equity prices. Turning to the case of oil exporters, oil supply-driven and demand-driven shocks exhibit similar responses of real equity prices (Appendices B and D).

On the whole, our findings qualify the previous literature on the role of the valuation effect in the global adjustment process.27 On the one hand, results suggest that responses of real equity prices in net oil importers differ according to the underlying oil shock. Clearly, in the case of a shock driven by a rise in global economic activity, there is no wealth transfer from net oil exporters to importers. On the other hand, real equity price responses are relatively short-lived.

Responses of current-account balances

As shown in Appendices C and E, both shocks tend to be followed by an increase in currentaccount deficits in net oil-importing economies, with however some interesting specificities. First, the sizes of the responses are larger for supply-driven shocks relative to demand-driven ones. Second, the former has a higher influence on current-account imbalances than the latter.

These two results suggest that oil-supply shocks contribute more to the increase in currentaccount imbalances than oil-demand shocks. Third, the supply-driven shocks' effects are closely related to the degree of energy dependence. More specifically, as shown in Appendix C, heavily dependent economies experiment especially strong responses of their current account to oil shocks (Japan, China, and the United States).28 This relationship is attenuated for oil-demand shocks, suggesting that the trade channel tends to smooth the reaction of the current account in those cases.

Regarding net oil exporters, both shocks increase current-account surpluses, as expected (Appendices B and D). In fact, current-account responses of net oil exporters mirror those of oil importers. Indeed, our results show that supply-driven shocks are accompanied by higher surplus than demand-driven disturbances.29 Interestingly, we find a similar result for net oil-importing countries, but in the direction of current-account deficits.

Conclusion

This paper investigates the respective effects of oil supply-driven and oil demand-driven shocks on global imbalances, as well as their transmission channels. To this end, we adopt a Global VAR approach that allows us to account for trade and financial interdependencies between countries. Three key findings emerge from our analysis. First, we evidence that the impact of oil shocks on global imbalances depends on the source of those shocks. Demand-driven shocks have a weak impact on current-account imbalances, a result that may be explained by the importance of the trade channel when the rise in oil price comes from an increase in global economic activity. Second, contrary to general equilibrium models, the real exchange rate does not play a key role in the global adjustment process. Third, while we identify a significant valuation channel, it is short-lived, and the trade channel-mostly explained by trade interdependencies between countries-represents the main adjustment mechanism to oil shocks.

Our findings have important implications since they show that the nature of the transmission of oil price shocks depends on the type of the shock. Furthermore, in addition to short-term valuation effects, the dynamics of energy exports and imports plays a key role in explaining global imbalances. On the whole, fully understanding the effects of oil shocks on global balances requires to consider both the trade channel and international capital flows. One promising extension would be to account for time-changing effects of oil price shocks using time-varying parameters GVAR models; this is left for future research.

Appendix A -Data sources

Table 1 :

 1 Countries and regions in the GVAR model country i at time t; real effective exchange rates being based on relative CPI. Equity price series ep i,t are calculated as the ratio of the nominal equity price index to CPI, and are expressed in logarithm. Current account data are expressed in US dollars and equal to 100 in 2005 base year.15

	Oil importers		Oil exporters
	Latin America		Algeria
	Emerging Asia		Canada
	China		Gulf region
	Euro area		Indonesia
	India		Mexico
	Japan		Nigeria
	Rest of the world		United Kingdom
	United States		Venezuela
			Norway
	Latin America	Emerging Asia Gulf region	Rest of the World
	Argentina	Korea	Bahrain	Australia
	Brazil	Malaysia	Kuwait	New Zealand
	Chile	Philippines	Oman	Turkey
		Singapore	Qatar	South Africa
			Saudi Arabia
			UAE
	rate of each

  us,t = (y us,t , rer us,t , ep us,t , ca us,t , poil t ) (11) where poil stands for the oil price index (in logarithm). Turning to the Gulf region model, oil production is included as an endogenous variable (see Cashin et al., 2013): x gulf,t = (y gulf,t , rer gulf,t , ep gulf,t , ca gulf,t , qoil t ) (12)

Table 2 :

 2 Domestic and foreign variables included in the country-specific models

		Emerging Asia	Gulf region	Latin America
	Variables	Endogenous Foreign Endogenous Foreign Endogenous Foreign
	Real GDP	y i,t	y * i,t	y gulf,t	y * gulf,t	y i,t	y * i,t
	Equity price	ep i,t	ep * i,t	-	ep * gulf,t	ep i,t	ep * i,t
	Current account ca i,t	ca * i,t	ca gulf,t	ca * gulf,t	ca i,t	ca * i,t
	Exchange rate	rer i,t	-	rer gulf,t	-	rer i,t	-
	Oil price	-	poil t	-	poil t	-	poil t
	Oil production	-	qoil t	qoil t	-	-	qoil t
		China		Euro area	United States
	Variables	Endogenous Foreign Endogenous Foreign Endogenous Foreign
	Real GDP	y i,t	y * i,t	y i,t	y * i,t	y us,t	y * us,t
	Equity price	-	ep * i,t	ep i,t	ep * i,t	ep us,t	ep * us,t
	Current account ca i,t	ca * i,t	ca i,t	ca * i,t	ca us,t	ca * us,t
	Exchange rate	rer i,t	-	rer i,t	-	rer us,t	-
	Oil price	-	poil t	-	poil t	poil t	-
	Oil production	-	qoil t	-	qoil t	-	qoil t

Table 3 :

 3 : Sign restrictions on impulse responses in the GVAR model

			Sign restrictions
		Oil-supply shock Oil-demand shock
	Oil price	+	+
	Oil production	-	+
	GDP oil∼importers -	+
	GDP oil∼exporters		+

  CountriesReal GDP CPI Real exchange rate Equity price Current account Oil price Oil production refers to the on line database available on the Pesaran's web page: https://sites.google.com/site/gvarmodelling/

	Algeria	IFS+WEO IFS	IFS	Bloomberg WEO	psw	Datastream
	Argentina	IFS	IFS	IFS	Bloomberg IFS	psw	Datastream
	Australia	IFS	IFS	IFS	Bloomberg IFS	psw	Datastream
	Bahrain	IFS+WEO IFS	IFS	Bloomberg WEO	psw	Datastream
	Brazil	IFS	IFS	IFS	Bloomberg IFS	psw	Datastream
	Canada	IFS	IFS	IFS	Bloomberg IFS+WDI	psw	Datastream
	Chile	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	China	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	Euro zone	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	India	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	Indonesia	IFS	IFS	IFS	Bloomberg WEO+IFS+WDI psw	Datastream
	Japan	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	Korea	IFS	IFS	IFS	Bloomberg IFS	psw	Datastream
	Kuwait	IFS+WEO IFS	IFS	Bloomberg WEO	psw	Datastream
	Malaysia	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	Mexico	IFS	IFS	IFS	Bloomberg IFS	psw	Datastream
	New Zealand	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	Nigeria	IFS+WEO IFS	IFS	Bloomberg WEO	psw	Datastream
	Norway	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	Oman	IFS+WEO WEO IFS	Bloomberg WEO	psw	Datastream
	Philippines	IFS	IFS	IFS	Bloomberg IFS	psw	Datastream
	Qatar	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	Saudi Arabia	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	Singapore	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	South Africa	IFS	IFS	IFS	Bloomberg IFS	psw	Datastream
	Turkey	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
	United Arab Emirates IFS	WEO IFS	Bloomberg WEO	psw	Datastream
	United Kingdom	IFS	IFS	IFS	Bloomberg IFS	psw	Datastream
	United States	IFS	IFS	IFS	Bloomberg IFS	psw	Datastream
	Venezuela	IFS	IFS	IFS	Bloomberg WEO	psw	Datastream
		Note: psw

See, among others, IMF (2006,

2011), and[START_REF] Caballero | Financial Crash, Commodity Prices and Global Imbalances[END_REF]. 2 For instance,[START_REF] Kilian | Oil Shocks and External Balances[END_REF] show that oil-supply shocks have a relatively small and short-lived impact on oil trade balance, while oil-demand shocks lead to large and persistent oil trade deficits in oil-importing countries.

Source: BP Statistical Review of World Energy.

See, for instance,[START_REF] Kilian | The Economic Effects of Energy Price Shocks[END_REF],[START_REF] Blanchard | The Macroeconomic Effects of Oil Shocks: Why are the 2000s so Different from the 1970s?[END_REF] and[START_REF] Peersman | Cross-Country Differences in the Effects of Oil Shocks[END_REF]; the main exceptions being[START_REF] Cashin | The Differential Effects of Oil Demand and Supply Shocks on the Global Economy[END_REF] and[START_REF] Esfahani | An empirical growth model for major oil exporters[END_REF].

See e.g.[START_REF] Hamilton | Oil and the macroeconomy[END_REF] and[START_REF] Kilian | The Economic Effects of Energy Price Shocks[END_REF].

Relying on a VAR specification,[START_REF] Kilian | Not all Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market[END_REF] shows that, unlike the two other types of shocks, pure supply shocks in the oil market have a short-term impact on crude oil prices, and therefore a limited effect on macroeconomic variables. See also[START_REF] Apergis | Do Structural Oil-Market Shocks Affect Stock Prices?[END_REF] and[START_REF] Hahn | The Role of Oil Prices in the Euro Area Economy since 1970s[END_REF].

The United States and the Gulf region are alternatively regarded as the reference country/region.

In our empirical analysis, we use the Akaike information criterion to select the lag orders corresponding to both domestic and foreign variables, allowing lags up to four. Tables for the selected lag orders, as well as the results regarding the number of cointegrating relationships based on the trace test are available upon request to the authors.

The choice of trade weights rests on the fact that bilateral trade has a strong influence on inter-country business cycle linkages (see, among others,[START_REF] Forbes | A Decomposition of Global Linkages in Financial Markets Over Time[END_REF][START_REF] Imbs | Trade, Finance, Specialization and Synchronization[END_REF][START_REF] Baxter | Determinants of Business Cycle Comovements: a Robust Analysis[END_REF].

See Chudik and Fidora (2011) for further details.

They define large oil price shocks as episodes in which oil prices have reached three-year rise.

Recall that Appendix F exhibits trade weights based on both exports and imports. However, our findings do not differ if we consider only weights based on exports. Results are available upon request to the authors.

And for Turkey, to a lesser extent.

See e.g.[START_REF] Corden | Booming sector and de-industrialisation in a small open economy[END_REF].

For Mexico, we can observe a reduction in the oil trade balance surplus since 2006.

On the resource curse, see[START_REF] Gylfason | Natural Resource Endowment: A Mixed Blessing?[END_REF] and van der Ploeg (2011).

See, among others, Elekdag et al. (2008),[START_REF] Bodenstein | Oil Shocks and External Adjustment[END_REF] IMF (2011).

Note that the supply-driven shock does not affect the real exchange rate in the Euro area, in line with[START_REF] Dees | Exploring the International Linkages of the Euro Area: a Global VAR Analysis[END_REF] and[START_REF] Cashin | The Differential Effects of Oil Demand and Supply Shocks on the Global Economy[END_REF].

Due to data availability constraints, the number of studied countries in the group of net oil exporters is limited.

Recall that related empirical studies report mixed results on this question. For instance, the study released by theIMF (2006) gives insignificant responses of real equity prices to oil shocks, while[START_REF] Kilian | Oil Shocks and External Balances[END_REF] find partially significant responses of net foreign asset positions in both net oil importers and exporters.

[START_REF] Peersman | Cross-Country Differences in the Effects of Oil Shocks[END_REF] find the same result for the responses of real GDP.

The Gulf region is an exception, as the demand-driven shock exhibits a stronger response at all horizons.Responses to demand-driven shock are statistically insignificant in Nigeria and Venezuela, a result that can be explained by the dramatic inefficiencies that characterized those countries, as stressed above.

* This research has been supported by the French Energy Council (Conseil Français de l'Energie), Paris,