Empirical essays about the effects of oil market shocks on the US economy

This thesis examines the impact of oil market shocks on the US economy. Chapter 1 offers an introduction to the topic and provides an overview of the remaining four chapters. Chapter 2 extends the existing understanding of the relation between oil prices and the US stock market in two ways: (i) by evaluating the effects of oil market shocks on the US stock market both, at an aggregate level and for all 49 US industry specific portfolios, and (ii) by scrutinizing the dynamic nature of this relation within a Structural Vector Autoregression (SVAR) model for a large set of rolling samples. The empirical results indicate that the effects of oil prices on the US stock market depend on the type and the timing of the shocks. An oil supply shock generally does not have a statistically measurable impact on stock market performance. Conversely, an aggregate demand shock has a positive effect on nearly all sectors, while an oilspecific demand shock has a negative, but statistically insignificant impact on stock returns for most industries. These results suggest that the importance of investors’ efforts to hedge against oil market shocks might be declining over time. In addition, the costs of carbon taxes and/or tradeable permits may be smaller than commonly thought if stock prices represent the net present value of profits. Chapter 3 examines whether the alternative identification techniques for oil market shocks could be responsible for the mixed results in the oil-stock market literature. This study employs a Bayesian Structural Vector Autoregression (SVAR) to compare the implications of traditional identification approaches (SVAR with zero/sign restrictions) with those from the baseline model (Bayesian SVAR) for the case of the US. We find that the baseline model implies more plausible posterior price elasticities of oil supply and demand and a more profound effect of oil supply shocks on oil prices. Nonetheless, all models provide qualitatively similar conclusions for the effects of oil market shocks on the US stock market, with demand-side shocks playing a more important role than oil supply shocks. Overall, this study reveals that traditional identification schemes remain a good approximation in practice for the oil-stock market relationship. Chapter 4 provides a novel perspective on the role of US oil production in both, the global oil market and the US economy. It employs a Bayesian Structural Vector Autoregression for the global oil market to identify distinct demand and supply oil market shocks. It differs from earlier studies by distinguishing explicitly between US and non-US oil production. In addition, a rolling-sample estimation approach is employed to investigate oil market shocks in a dynamic framework. The study finds considerable time variation in the effects of oil market shocks on the US economy. In particular, it identifies a sharp increase in the price elasticity of US oil supply after the shale oil revolution in the US. This increased price responsiveness of US oil production is partly responsible for the resilience of the US economy to global oil market shocks in recent years. This conclusion remains robust regardless of whether the global oil market shocks originate from the demand or supply side. Finally, Chapter 5 summarizes the most important contributions of the thesis. It also tries to link the econometric methodologies and results in the individual chapters and aims to provide an overarching picture of the results in this thesis.