قیمت نفت، نرخ ارز و بازار سهام در حال ظهور

While two different streams of literature exist investigating 1) the relationship between oil prices and emerging market stock prices and 2) the relationship between oil prices and exchange rates, relatively little is known about the dynamic relationship between oil prices, exchange rates and emerging market stock prices. This paper proposes and estimates a structural vector autoregression model to investigate the dynamic relationship between these variables. Impulse responses are calculated in two ways (standard and the recently developed projection based methods). The model supports stylized facts. In particular, positive shocks to oil prices tend to depress emerging market stock prices and US dollar exchange rates in the short run. The model also captures stylized facts regarding movements in oil prices. A positive oil production shock lowers oil prices while a positive shock to real economic activity increases oil prices. There is also evidence that increases in emerging market stock prices increase oil prices.

The recent surge in oil prices over the past 8 years has generated a lot of interest in the relationship between oil prices, financial markets and the economy (see, for example, Blanchard and Gali, 2007 and Herrera and Pesavento, 2009). Crude oil spot prices, measured using West Texas Intermediate crude oil, closed out the year 2002 at $29.42 per barrel.1 By June of 2008 spot oil prices had risen to $133.93 per barrel. Over this same time period, the US dollar fell against other major traded currencies and emerging market stock prices rose (Fig. 1). While there exists a literature on the relationship between oil prices and stock prices, and a separate literature on the relationship between oil prices and exchange rates, the relationship between these two streams has, however, not been that closely studied, especially within the context of emerging market stock prices. The purpose of this paper is to use a structural vector autoregression (SVAR) model to bring these two literatures together. Full-size image (91 K) Fig. 1. Global oil production, real economic activity, emerging market stock prices, the US treasury/Euro interest rate spread, exchange rates, and oil prices. Figure options Understanding the relationship between oil prices, exchange rates and emerging stock market prices is an important topic to study because as emerging economies continue to grow and prosper, they will exert a larger influence over the global economy. By some estimates, emerging economies will account for 50% of global GDP by 2050 (Cheng et al., 2007) and the majority of economic growth. Over the period 1990 to 2007 real GDP in China and India grew at average annual rates of 10.0% and 6.3% respectively.2 By comparison, OECD countries grew at an average annual rate of 2.5% over this same period. At these growth rates the Chinese economy will double every 7 years and the Indian economy will double every 11 years. Along with this economic growth comes a voracious demand for energy products such as oil. In 2009, the US was the largest consumer of oil in the world, accounting for 22% of the global oil demand. China, at 10% of the world total, had overtaken Japan to become the second largest oil consuming nation (Table 1). While the demand for oil in developed economies is holding steady or declining slightly, the demand for oil in emerging economies is rapidly growing. The International Energy Agency (IEA) (2009, p. 81) predicts that between 2008 and 2030, China and India will have average annual growth rates in oil consumption of 3.5% and 3.9% respectively (compared to the 1.0% average annual growth rate for the world). China alone will account for 42% of the global increase in oil demand between 2008 and 2030. Table 1. The top 10 countries with the largest increase in oil consumption over the past 10 years. Oil consumption ('000 barrels per day) 2008 2009 Growth past 5 years Growth past 10 years Change 2009 over 2008 2009 share of total Qatar 198 209 54.09% 140.41% 5.00% 0.21% China 8086 8625 24.19% 65.57% 6.69% 10.42% Kazakhstan 263 260 13.32% 57.15% − 3.34% 0.31% Algeria 311 331 32.00% 57.06% 6.49% 0.38% Kuwait 370 419 24.79% 54.33% 9.79% 0.49% Saudi Arabia 2390 2614 32.96% 52.71% 9.79% 3.14% United Arab Emirates 475 455 22.28% 51.81% − 4.95% 0.56% Ecuador 207 216 42.62% 49.90% 5.24% 0.25% Singapore 968 1002 29.23% 48.14% 3.49% 1.34% India 3071 3183 21.25% 39.99% 3.70% 3.83% USA (ranked 52) 19,498 18,686 − 10.39% − 4.36% − 4.87% 21.71% Source: BP Statistical Review of World Energy, 2010. Table options Some emerging economies, like China, are accumulating large reserves of foreign currency (mostly US dollars) and this will make them a bigger player in the world financial markets. Some estimates place China's reserves of foreign exchange and gold at $2.206 trillion as of December 2009.3 Managing this amount of money and protecting its store of value will mean that China will have not only a greater participation but also a greater influence over global financial capital markets. Shocks or unexpected price hikes originating from the oil market have been captured in different ways.4Hamilton (2003) defines an oil price shock as a net oil price increase, which is the log change in the nominal price of oil relative to its previous 3 year high if positive, or zero otherwise. However, Kilian (2008a) argues that this measure of oil price shocks does not necessarily filter out oil price changes due to exogenous political events or wars because oil price shocks may be demand-driven.5 Furthermore, nominal oil price shocks do not mean that there are corresponding real oil price shocks. In order to account for these problems, Kilian (2009) uses a vector autoregression (VAR) with three variables, the oil supply, the real price of oil and a proxy variable for global demand for industrial commodities measuring global real economic activity. He identifies, based on a recursive structure, three oil shocks: an oil supply shock, an oil-market specific shock and a global demand shock. Kilian (2009) treats these shocks as pre-determined in secondary ordinary least squares regressions analyzing their effects on the US economy.6 We model the oil market as in Kilian (2009), however, we use a much less restrictive set-up for the analysis of the effects of oil shocks that treats all variables as endogenous and allows for rich dynamics in the interrelations across markets.7 Killian's approach has recently been used by several authors to investigate the impact of oil price shocks on stock prices or oil prices. Kilian and Park (2009) use four variables (the percentage change in world crude oil production, global real economic activity, the real oil price, and return on US stocks) to investigate the relationship between US stock prices and oil price shocks within the same modeling framework as in Kilian (2009). They find that while oil demand shocks do depress stock prices oil supply shocks have much less impact on stock prices. Apergis and Miller (2009) use a SVAR approach to analyze the effect of structural oil market shocks on the stock prices in eight developed economies (Australia, Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States). They find that oil market shocks do not have a very large or significant impact on the stock prices in the countries studied. Killian's index of real economic activity has recently been used by He et al. (2010) to investigate the relationship between real economic activity and oil prices. They find that real oil future prices are cointegrated with the real economic activity index and a trade weighted US dollar index. They also find evidence of Granger causality running from the real economic activity index to real oil prices. The approach taken in this paper is to use a SVAR to model the dynamic relationship between real oil prices, an exchange rate index for major currencies, emerging market stock prices, interest rates, global real economic activity and oil supply. The empirical results show that the six-variable SVAR model fits the data well in supporting some stylized facts. Impulse responses are calculated in two alternative ways (standard and local projection based methods) in order to check their robustness. The results presented in this paper help to further deepen our understanding of the relationship between oil prices, exchange rates and emerging market equity prices. The rest of the paper is organized as follows. Section 2 discusses the theoretical and empirical relationship between oil prices, exchange rates and emerging stock prices. Section 3 describes the data and the identification of the structural VAR model. Section 4 presents the main results of the paper. It also includes the discussion of impulse responses based on the local projection methods and a discussion on the forecast error variance decomposition. Some concluding remarks appear in Section 5.

Recognizing the importance of the relationship between stock prices and oil prices and the relationship between oil prices and exchange rates, this paper combines these two streams of literature, discussed in Section 2 of our paper, together into one empirical structural vector autoregression model. This differentiates our paper from prior studies. In doing so, it is possible to gain a more complete understanding of the dynamic relationship between oil prices, emerging market stock prices and exchange rates. This is important because emerging economies have, over the past ten years, been accounting for a larger proportion of global GDP and this trend is expected to continue. Emerging economies are among the fastest growing economies (with GDP growth rates much higher than the growth rates observed in developed economies) and this combination of size and growth is likely to influence the dynamics between oil prices, emerging market stock prices and exchange rates. The short-term dynamics between oil prices, emerging market stock prices and exchange rates are analyzed using two sets of impulse response functions (standard and local projection based). In most cases the projection based IRFs provide similar results as the standard IRFs. Where the two approaches differ, the projection based approach tends to provide impulse responses that are more likely to adequately capture the cyclical response of a variable to an unexpected structural shock. Both approaches for example report that stock prices respond negatively to a positive oil price shock, and that oil prices respond positively to a positive emerging market shock. However, the first effect is only statistically significant for the projection based impulses for the first 2–3 months after the impact. The second effect is barely statistically significant in the period 2–8 months after the impact for standard impulses and is statistically significant in that period (4–13 months) for projection based responses with one standard error confidence bands. These results indicate that while increases in oil prices depress stock prices (a result widely supported by the literature documenting the effects of oil prices on stock markets, see for example Basher and Sadorsky (2006) and the references they cite) it is also the case that increases in emerging market stock market prices lead to an increase in oil prices (a result which to our knowledge has not been previously explored). This latter result makes sense within the context of global oil markets and global economic activity. Oil consumption in most developed economies is flat or in decline and as a result emerging market economic growth (as proxied by emerging market stock prices) is likely to be an important source of demand side pricing pressure in the oil market. The results in this paper offer support for the hypothesis that exchange rates respond to movements in oil prices and that most of the dynamic interaction takes place in the short run. In particular, a positive oil price shock leads to an immediate drop in the trade-weighted exchange rate. This result has a statistically significant impact for about 5–6 months. These results are consistent with Krugman's (1983b) model of speculation. Rising oil prices will generate a current account surplus for oil exporters and current account deficits for oil importers. The long-run expectation is that oil importers will experience a depreciation in their currencies because of the adverse terms of trade effect and this expectation of future depreciation is enough to produce a drop in the dollar in the short-run even if petro dollars are recycled. In comparison, no support is found for the hypothesis that oil prices respond to shocks to exchange rates. The results in this paper show that oil prices respond negatively to an unexpected increase in oil supply and oil prices respond positively to an unexpected increase in demand. These results are consistent with the predictions from a demand and supply model for the oil market. Oil prices respond positively to a positive shock to emerging stock markets. These results are important in establishing, that in addition to global supply and demand conditions for oil, oil prices also respond to emerging market equity markets. The results in this paper have a number of policy implications. As expected, oil prices respond to global oil production (supply) and real global economic activity (demand). Rapidly rising stock prices in emerging economies can also put pressure on oil prices to rise. While it has typically been the case that macroeconomic policy in developed economies, like the G7, was seen as an important factor affecting the global economy, it now must be recognized that monetary and fiscal policy in large emerging economies (like China and India) can affect their own economic growth prospects as well as global financial markets. As the results in this paper have shown, oil prices respond not just to economic fundamentals like oil supply and real economic activity but also to movements in emerging stock prices. Stock markets are often seen as leading economic indicators. Rapidly rising stock prices in emerging markets signal the expectation of higher economic growth ahead. If emerging market stock prices get trapped in a bubble, however, oil prices will overshoot in relation to economic fundamentals. This means that consumers in developed economies could end up paying more for oil and oil related products even if their own domestic economic growth remains sluggish and future realized economic growth in emerging economies is less than what the financial markets expected. Finally, the framework presented in this paper could be used to analyze the oil, stock market and exchange rate relationship separately for major emerging countries, such as BRIC (Brazil, Russia, India and China) and/or major oil-exporting (e.g. Indonesia, Mexico and Russia) countries. Such country-specific study would allow for a more in-depth understanding of the effect of oil price shocks on equity prices in these countries. We leave this to future research.