This paper assesses the role of political tensions between the USA and China and global market forces in explaining oil price fluctuations. To this end, we take part of the previous literature, which highlights (i) the importance of political events in explaining oil price dynamics, (ii) time-varying patterns in the oil market, and (iii) asymmetries in the impact of political tensions and uncertainty on oil prices. While this literature generally focuses on one of these features, we account for all of them simultaneously, allowing for a complete and meaningful investigation of political tensions on oil prices. To this end, we rely on quantile autoregressive distributed lag error-correction models, which are specifically designed to address both the long-run and short-run dynamics across a range of quantiles in a fully parametric setting. Our results show evidence of a quantile-dependent long-term relationship between oil prices and their determinants over the 1958–2022 period, which is also time varying across quantiles: the adjustment speed toward the long-term equilibrium is faster for the highest quantiles, fluctuating between 4% and 6% in the recent period. Overall, our findings highlight the increased role played by China in the oil market since the mid-2000s.

Nine out of the last ten recessions in the United States have been preceded by an increase in the price of oil as noted by Hamilton [Palgrave Dictionary of Economics]. Given the small share of energy in gross domestic product this phenomenon is difficult to explain using standard models. In this paper, I show that firm entry can be an important transmission and amplifying channel for energy price shocks. The results from the baseline dynamic stochastic general equilibrium (DSGE) model predict a drop in output that is two times the impact in a model without entry. The model also predicts an increase in energy prices would lead to a decline in real wages, investment, consumption, and return on investment. Additionally, using US firm level data, I demonstrate that a rise in energy prices has a negative impact on firm entry as predicted by the DSGE model. This lends further support toward endogenizing firm entry when analyzing the effects of energy price shocks.

This article examines the historical emergence of the Middle East oil-pricing system. The collapse of the Gulf-plus system, combined with outstanding discoveries of new reservoirs across the Arabian Peninsula and Persia, awoke latent competitive forces within the oligopolistic oil industry. After World War II, business differences regarding vertical integration, market priorities, and global competition worsened existing fractures among the multinational oil companies generally referred to as “the seven sisters.” The conclusions underscore the role of the “fringe” companies Texaco, Standard of California–Chevron, and Gulf Oil in prompting new price equilibriums for Persian Gulf crude oil.

We estimate asymmetries in innovations to Solow residuals for 11 Organization for Economic Co-operation and Development (OECD) countries using stochastic frontier analysis. Likelihood ratio statistics and variance ratios imply that all countries with net energy imports have significant negative asymmetries, whereas other countries do not. We construct a simple theoretical model in which the measured Solow residual combines effects from technology, factor utilization, and the terms of trade. For oil importers, the model implies an asymmetric response of measured total factor productivity to oil price increases and decreases. When we condition Solow residuals separately on positive and negative oil price changes to allow asymmetric responses, evidence for remaining negative asymmetric innovations to the Solow residuals vanishes for all countries except Switzerland. Switzerland's relatively dominant financial sector suggests that their asymmetries could be due to a financial crisis, a hypothesis that we test and fail to reject.

This paper emphasizes the use of data-driven techniques to discern trends in commodity prices. Whereas many previous papers rely on parametric assumptions, we take as our departure point the view that such trends are inherently nonparametric, driven by complex forces of innovation and obsolescence, competition and strategic behavior, resource depletion and discovery, and supply and demand. Our reference specification is the partial linear model yt = f(t) + ztβ + ϵt where macroeconomic variables z enter parametrically, and f is nonparametric, to be discovered using cross-validation.

We analyze data on 11 commodities—3 hydrocarbons and 8 metals. For the majority of these commodities, our data-driven estimates of f bear close similarity to band pass estimates which include long term trends and super cycles. The OPEC effect is estimated to have increased oil prices by over 50% on average and coal prices by about 25%. U.S. coal mining legislation is estimated to have increased coal prices by 9% to 15%.

Oil prices rose sharply prior to the onset of the 2007–2009 recession. Hamilton [in the Palgrave Dictionary of Macroeconomics (2008)] noted that nine of the last ten recessions in the United States were preceded by a substantial increases in the price of oil. In this paper, we consider whether oil price shocks significantly increase the probability of recessions in a number of countries. Because business cycle turning points generally are not available for other countries, we estimate the turning points together with oil's effect in a Markov-switching model with time-varying transition probabilities. We find that, for most countries, oil shocks do affect the likelihood of entering a recession. In particular, for a constant, zero-term spread, an average-sized shock to WTI oil prices increases the probability of recession in the United States by nearly 50 percentage points after one year and nearly 90 percentage points after two years.

Although previous work shows strong relationships between oil prices and economic activity, the empirical evidence on the impact of oil prices on stock market returns has been mixed. This article investigates the existence of long-term relationships between oil prices and stock market indices in Europe using both aggregate and sector indices and linear and asymmetric cointegration. Our findings show that the response of stock prices to oil price depends greatly on the sector of activity and that oil prices affect stock returns in an asymmetric fashion.