We analyze the long-run relationship between the world price of crude oil and international stock markets over 1971:1–2008:3 using a cointegrated vector error correction model with additional regressors. Allowing for endogenously identified breaks in the cointegrating and error correction matrices, we find evidence for breaks after 1980:5, 1988:1, and 1999:9. There is a clear long-run relationship between these series for six OECD countries for 1971:1–1980.5 and 1988:2–1999.9, suggesting that stock market indices respond negatively to increases in the oil price in the long run. During 1980.6–1988.1, we find relationships that are not statistically significantly different from either zero or from the relationships of the previous period. The expected negative long-run relationship appears to disintegrate after 1999.9. This finding supports a conjecture of change in the relationship between real oil price and real stock prices in the last decade compared to earlier years, which may suggest the presence of several stock market bubbles and/or oil price bubbles since the turn of the century.
The relationship between oil prices and economic activity has been investigated by a number of researchers. On the issue of the effect of oil price shocks on stock market returns, Jones and Kaul (1996), Sadorsky (1999) and Ciner (2001) report a significant negative connection, while Chen et al. (1986) and Huang et al. (1996) do not. A negative association between oil price shocks and stock market returns has been reported in several recent papers. Nandha and Faff (2008) find oil prices rises have a detrimental effect on stock returns in all sectors except mining and oil and gas industries, O'Neill et al. (2008) find that oil price increases lead to reduced stock returns in the United States, the United Kingdom and France, and Park and Ratti (2008) report that oil price shocks have a statistically significant negative impact on real stock returns in the U.S. and 12 European oil importing countries.1 In new strands in the literature, Kilian and Park (2007) report that only oil price increases driven by precautionary demand for oil over concern about future oil supplies negatively affect stock prices, and Gogineni (2007) finds that industry stock price returns depends on demand and cost side reliance on oil and on size of oil price changes.
Research on the effect of oil prices on stock prices parallels a larger literature on the connection of oil price shocks with real activity. Much of this research has been influenced by Hamilton's (1983) connection of oil price shocks with recession in the U.S. Hamilton's finding has been elaborated on and confirmed by Mork (1989), Lee et al. (1995), Hooker (1996), Hamilton, 1996 and Hamilton, 2003 and Gronwald (2008), among others.2 The research in the two areas is clearly connected, since oil price shocks influence stock prices through affecting expected cash flows and/or discount rates. Oil price shocks can affect corporate cash flow since oil is an input in production and because oil price changes can influence the demand for output at industry and national levels. Oil price shocks can affect the discount rate for cash flow by influencing the expected rate of inflation and the expected real interest rate. The corporate investment decision can be affected directly by changes in the latter and by changes in stock price relative to book value.
In recent work emphasis has been placed on the changing nature of the connection between oil prices and real activity. Blanchard and Gali (2007) find smaller effects of oil price shocks on macroeconomic variables in recent years. Kilian (2008b) reports that while exogenous oil supply shocks, identified as oil production disruptions, have a significant effect on the economy, their impact on the U.S. economy since the 1970s has been small compared to the impact of other factors. Along similar lines, Cologni and Manera (2009) report that the role of oil shocks in explaining recessions has decreased over time in G7 countries. This change in the relationship between oil prices and real activity in recent years from earlier decades is attributed to several causes including improvements in energy efficiency and in the conduct of monetary and fiscal authorities.
In this paper, we analyze the long-run relationship between the price of crude oil and international stock markets from January 1971 to March 2008 using a vector error correction model (VECM). The basic model we employ includes additional regressors to control for short-run dynamics between stock market prices for six OECD countries and a single international crude oil price and other macroeconomic series. The contribution of this paper is in the analysis of the long-run relationship between oil price and stock prices in a number of major countries jointly while allowing for short-run macroeconomic influences on stock price. This is in contrast to much recent work which has focused on the short-term impact of oil price increases on stock market returns.3 Moreover, we allow for the possibility of endogenously identified structural breaks in both the long-run and short-run relationships.
We find a clear long-run relationship between these series for six OECD countries from 1971 until May 1980 and again from February 1988 until September 1999, suggesting that stock market indices respond negatively to increases in the oil price. Although we do not find long-run relationships to be statistically significant in the intervening period, they are not statistically significantly different from those in the previous period, either.4
The long-run relationship appears to disintegrate and even change signs in some cases after September 1999, based on data through March 2008. Such an empirical finding supports a conjecture, not only of a change in the relationship between oil prices and real variables in recent years from earlier decades, but possibly of several stock market bubbles and/or oil price bubbles since the turn of the century.
The remainder of the paper is structured as follows. In the following section, we provide a non-quantitative motivation for our analysis. Our econometric model and explanations of our estimation technique and breakpoint identification procedure are contained in Section 3. Section 4 discusses specification test results, while Section 5 holds our main empirical results. Section 6 concludes. Data and sources are discussed in Appendix A.
