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It has been forty years since the oil crisis of 1973/74. This crisis has been one of the defining economic events of the 1970s and has shaped how many economists think about oil price shocks. In recent years, a large literature on the economic determinants of oil price fluctuations has emerged. Drawing on this literature, we first provide an overview of the causes of all major oil price fluctuations between 1973 and 2014. We then discuss why oil price fluctuations remain difficult to predict, despite economists’ improved understanding of oil markets. Unexpected oil price fluctuations are commonly referred to as oil price shocks. We document that, in practice, consumers, policymakers, financial market participants and economists may have different oil price expectations, and that, what may be surprising to some, need not be equally surprising to others.
We derive the Bayes estimator of vectors of structural VAR impulse responses under a range of alternative loss functions. We also derive joint credible regions for vectors of impulse responses as the lowest posterior risk region under the same loss functions. We show that conventional impulse response estimators such as the posterior median response function or the posterior mean response function are not in general the Bayes estimator of the impulse response vector obtained by stacking the impulse responses of interest. We show that such pointwise estimators may imply response function shapes that are incompatible with any possible parameterization of the underlying model. Moreover, conventional pointwise quantile error bands are not a valid measure of the estimation uncertainty about the impulse response vector because they ignore the mutual dependence of the responses. In practice, they tend to understate substantially the estimation uncertainty about the impulse response vector.
Several recent studies have expressed concern that the Haar prior typically imposed in estimating sign-identi.ed VAR models may be unintentionally informative about the implied prior for the structural impulse responses. This question is indeed important, but we show that the tools that have been used in the literature to illustrate this potential problem are invalid. Speci.cally, we show that it does not make sense from a Bayesian point of view to characterize the impulse response prior based on the distribution of the impulse responses conditional on the maximum likelihood estimator of the reduced-form parameters, since the the prior does not, in general, depend on the data. We illustrate that this approach tends to produce highly misleading estimates of the impulse response priors. We formally derive the correct impulse response prior distribution and show that there is no evidence that typical sign-identi.ed VAR models estimated using conventional priors tend to imply unintentionally informative priors for the impulse response vector or that the corre- sponding posterior is dominated by the prior. Our evidence suggests that concerns about the Haar prior for the rotation matrix have been greatly overstated and that alternative estimation methods are not required in typical applications. Finally, we demonstrate that the alternative Bayesian approach to estimating sign-identi.ed VAR models proposed by Baumeister and Hamilton (2015) su¤ers from exactly the same conceptual shortcoming as the conventional approach. We illustrate that this alternative approach may imply highly economically implausible impulse response priors.
Since the 1970s, exports and imports of manufactured goods have been the engine of international trade and much of that trade relies on container shipping. This paper introduces a new monthly index of the volume of container trade to and from North America. Incorporating this index into a structural macroeconomic VAR model facilitates the identification of shocks to domestic U.S. demand as well as foreign demand for U.S. manufactured goods. We show that, unlike in the Great Recession, the primary determinant of the U.S. economic contraction in early 2020 was a sharp drop in domestic demand. Although detrended data for personal consumption expenditures and manufacturing output suggest that the U.S. economy has recovered to near 90% of pre-pandemic levels as of March 2021, our structural VAR model shows that the component of manufacturing output driven by domestic demand had only recovered to 59% of pre-pandemic levels and that of real personal consumption only to 76%. The difference is mainly accounted for by unexpected reductions in frictions in the container shipping market.
We study the effects of releases from the U.S. Strategic Petroleum Reserve (SPR) within the context of fully specified models of the global oil market that explicitly allow for storage demand as well as unanticipated changes in the SPR. We show that historically SPR policy interventions, defined as sequences of exogenous SPR shocks during selected periods, have helped stabilize the price of oil. Their effect on the price of oil, however, has been modest. For example, the cumulative effect of the SPR releases after the invasion of Kuwait in 1990 was a reduction of $2/barrel in the real price of oil after 7 months. Whereas emergency drawdowns tend to lower the real price of oil, we find that exchanges tend to raise the real price of oil in the long run. We also provide a detailed analysis of the benefits of the 2018 White House proposal to sell off half of the SPR within the next decade. We show that the expected fiscal benefits of this plan are somewhat higher than the revenue of $16.6 billion dollars projected by the White House.
The conventional wisdom that inflation expectations respond to the level of the price of oil (or the price of gasoline) is based on testing the null hypothesis of a zero slope coefficient in a static single-equation regression model fit to aggregate data. Given that the regressor in this model is not stationary, the null distribution of the t-test statistic is nonstandard, invalidating the use of the normal approximation. Once the critical values are adjusted, these regressions provide no support for the conventional wisdom. Using a new structural vector regression model, however, we demonstrate that gasoline price shocks may indeed drive one-year household inflation expectations. The model shows that there have been several such episodes since 1990. In particular, the rise in household inflation expectations between 2009 and 2013 is almost entirely explained by a large increase in gasoline prices. However, on average, gasoline price shocks account for only 39% of the variation in household inflation expectations since 1981.
There has been much interest in the relationship between the price of crude oil, the value of the U.S. dollar, and the U.S. interest rate since the 1980s. For example, the sustained surge in the real price of oil in the 2000s is often attributed to the declining real value of the U.S. dollar as well as low U.S. real interest rates, along with a surge in global real economic activity. Quantifying these effects one at a time is difficult not only because of the close relationship between the interest rate and the exchange rate, but also because demand and supply shocks in the oil market in turn may affect the real value of the dollar and real interest rates. We propose a novel identification strategy for disentangling the causal effects of traditional oil demand and oil supply shocks from the effects of exogenous variation in the U.S. real interest rate and in the real value of the U.S. dollar. Our approach exploits a combination of sign and zero restrictions and narrative restrictions motivated by economic theory and extraneous evidence. We empirically evaluate popular views about the role of exogenous real exchange rate shocks in driving the real price of oil, and we examine the extent to which shocks in the global oil market drive the U.S real exchange rate and U.S. real interest rates. Our evidence for the first time provides direct empirical support for theoretical models of the link between these variables.
Using a novel dataset, we develop a structural model of the Very Large Crude Carrier (VLCC) market between the Arabian Gulf and the Far East. We study how fluctuations in oil tanker rates, oil exports, shipowner profits, and bunker fuel prices are determined by shocks to the supply and demand for oil tankers, to the utilization of tankers, and to the cost of operating tankers, including bunker fuel costs. Our analysis shows that time charter rates are largely unresponsive to tanker cost shocks. In response to higher costs, voyage profits decline, as cost shocks are only partially passed on to round-trip voyage rates. Oil exports from the Arabian Gulf also decline, reflecting lower demand for VLCCs. Positive utilization shocks are associated with higher profits, a slight increase in time charter rates and lower fuel prices and oil export volumes. Tanker supply and tanker demand shocks have persistent effects on time charter rates, round-trip voyage rates, the volume of oil exports, fuel prices, and profits with the expected sign.
This paper examines the advantages and drawbacks of alternative methods of estimating oil supply and oil demand elasticities and of incorporating this information into structural VAR models. I not only summarize the state of the literature, but also draw attention to a number of econometric problems that have been overlooked in this literature. Once these problems are recognized, seemingly conflicting conclusions in the recent literature can be resolved. My analysis reaffirms the conclusion that the one-month oil supply elasticity is close to zero, which implies that oil demand shocks are the dominant driver of the real price of oil. The focus of this paper is not only on correcting some misunderstandings in the recent literature, but on the substantive and methodological insights generated by this exchange, which are of broader interest to applied researchers.
We propose a new instrument for estimating the price elasticity of gasoline demand that exploits systematic differences across U.S. states in the pass-through of oil price shocks to retail gasoline prices. These differences, which are primarily driven by variation in the cost of producing and distributing gasoline, create cross-sectional dispersion in gasoline price growth in response to an aggregate oil price shock. We find that the elasticity was stable near -0.3 until the end of 2014, but subsequently rose to about -0.2. Our estimates inform the recent debate about gasoline-tax holidays and policies to reduce carbon emissions.
Consumers purchase energy in many forms. Sometimes energy goods are consumed directly, for instance, in the form of gasoline used to operate a vehicle, electricity to light a home, or natural gas to heat a home. At other times, the cost of energy is embodied in the prices of goods and services that consumers buy, say when purchasing an airline ticket or when buying online garden furniture made from plastic to be delivered by mail. Previous research has focused on quantifying the pass-through of the price of crude oil or the price of motor gasoline to U.S. inflation. Neither approach accounts for the fact that percent changes in refined product prices need not be proportionate to the percent change in the price of oil, that not all energy is derived from oil, and that the correlation of price shocks across energy markets is far from one. This paper develops a vector autoregressive model that quantifies the joint impact of shocks to several energy prices on headline and core CPI inflation. Our analysis confirms that focusing on gasoline price shocks alone will underestimate the inflationary pressures emanating from the energy sector, but not enough to overturn the conclusion that much of the observed increase in headline inflation in 2021 and 2022 reflected non-energy price shocks.
We have identified a mistake in how Fig. 1 is referenced in the text of the article Eur. Phys. J. C 77 (2017) no. 8, 569 which affected three paragraphs of the results section. The corrected three paragraphs as well as the unmodified accompanying figure are reproduced in this document with the correct labeling.
In addition, an editing issue led to a missing acknowledgements section. The missing section is reproduced at the end of this document in the manner in which it should have appeared in the published article.
The production of Z0 bosons at large rapidities in Pb–Pb collisions at √sNN = 5.02 TeV is reported. Z0 candidates are reconstructed in the dimuon decay channel (Z0 → μ+ μ−), based on muons selected with pseudo-rapidity −4.0 < η < −2.5 and pT > 20 GeV/c. The invariant yield and the nuclear modification factor, RAA, are presented as a function of rapidity and collision centrality. The value of RAA for the 0–20% central Pb–Pb collisions is 0.67 ± 0.11 (stat.) ± 0.03 (syst.) ± 0.06 (corr. syst.), exhibiting a deviation of 2.6σ from unity. The results are well-described by calculations that include nuclear modifications of the parton distribution functions, while the predictions using vacuum PDFs deviate from data by 2.3σ in the 0–90% centrality class and by 3σ in the 0–20% central collisions.
The transverse momentum distributions of the strange and double-strange hyperon resonances (Σ(1385)±, Ξ(1530)0) produced in p–Pb collisions at sNN−−−√=5.02 TeV were measured in the rapidity range −0.5<yCMS<0 for event classes corresponding to different charged-particle multiplicity densities, ⟨dNch/dηlab⟩. The mean transverse momentum values are presented as a function of ⟨dNch/dηlab⟩, as well as a function of the particle masses and compared with previous results on hyperon production. The integrated yield ratios of excited to ground-state hyperons are constant as a function of ⟨dNch/dηlab⟩. The equivalent ratios to pions exhibit an increase with ⟨dNch/dηlab⟩, depending on their strangeness content.
It is commonly believed that the response of the price of corn ethanol (and hence of the price of corn) to shifts in biofuel policies operates in part through market expectations and shifts in storage demand, yet to date it has proved difficult to measure these expectations and to empirically evaluate this view. We utilize a recently proposed methodology to estimate the market’s expectations of the prices of ethanol, unfinished motor gasoline and crude oil at horizons from three months to one year. We quantify the extent to which price changes were anticipated by the market, the extent to which they were unanticipated, and how the risk premium in these markets has evolved. We show that the Renewable Fuel Standard (RFS) is likely to have increased ethanol price expectations by as much $1.45 in the year before and in the year after the implementation of the RFS had started. Our analysis of the term structure of expectations provides support for the view that a shift in ethanol storage demand starting in 2005 caused an increase in the price of ethanol. There is no conclusive evidence that the tightening of the RFS in 2008 shifted market expectations, but our analysis suggests that policy uncertainty about how to deal with the blend wall raised the risk premium in the ethanol futures market in mid-2013 by as much as 50 cents at longer horizons. Finally, we present evidence against a tight link from ethanol price expectations to corn price expectations and hence to storage demand for corn in 2005-06.
A common practice in empirical macroeconomics is to examine alternative recursive orderings of the variables in structural vector autogressive (VAR) models. When the implied impulse responses look similar, the estimates are considered trustworthy. When they do not, the estimates are used to bound the true response without directly addressing the identification challenge. A leading example of this practice is the literature on the effects of uncertainty shocks on economic activity. We prove by counterexample that this practice is invalid in general, whether the data generating process is a structural VAR model or a dynamic stochastic general equilibrium model.
The multi-strange baryon yields in Pb--Pb collisions have been shown to exhibit an enhancement relative to pp reactions. In this work, Ξ and Ω production rates have been measured with the ALICE experiment as a function of transverse momentum, pT, in p-Pb collisions at a centre-of-mass energy of sNN−−−√ = 5.02 TeV. The results cover the kinematic ranges 0.6 GeV/c<pT<7.2 GeV/c and 0.8 GeV/c<pT< 5 GeV/c, for Ξ and Ω respectively, in the common rapidity interval -0.5 <yCMS< 0. Multi-strange baryons have been identified by reconstructing their weak decays into charged particles. The pT spectra are analysed as a function of event charged-particle multiplicity, which in p-Pb collisions ranges over one order of magnitude and lies between those observed in pp and Pb-Pb collisions. The measured pT distributions are compared to the expectations from a Blast-Wave model. The parameters which describe the production of lighter hadron species also describe the hyperon spectra in high multiplicity p-Pb. The yield of hyperons relative to charged pions is studied and compared with results from pp and Pb-Pb collisions. A statistical model is employed, which describes the change in the ratios with volume using a canonical suppression mechanism, in which the small volume causes a species-dependent relative reduction of hadron production. The calculations, in which the magnitude of the effect depends on the strangeness content, show good qualitative agreement with the data.
Particle identification is an important feature of the ALICE detector at the LHC. In particular, for particle identification via the time-of-flight technique, the precise determination of the event collision time represents an important ingredient of the quality of the measurement. In this paper, the different methods used for such a measurement in ALICE by means of the T0 and the TOF detectors are reviewed. Efficiencies, resolution and the improvement of the particle identification separation power of the methods used are presented for the different LHC colliding systems (pp , p-Pb and Pb-Pb) during the first period of data taking of LHC (Run 1).
Background: In the context of the investigation of the quark gluon plasma produced in heavy-ion collisions, hadrons containing heavy (charm or beauty) quarks play a special role for the characterization of the hot and dense medium created in the interaction. The measurement of the production of charm and beauty hadrons in proton–proton collisions, besides providing the necessary reference for the studies in heavy-ion reactions, constitutes an important test of perturbative quantum chromodynamics (pQCD) calculations. Heavy-flavor production in proton–nucleus collisions is sensitive to the various effects related to the presence of nuclei in the colliding system, commonly denoted cold-nuclear-matter effects. Most of these effects are expected to modify open-charm production at low transverse momenta (pT) and, so far, no measurement of D-meson production down to zero transverse momentum was available at mid-rapidity at the energies attained at the CERN Large Hadron Collider (LHC).
Purpose: The measurements of the production cross sections of promptly produced charmed mesons in p-Pb collisions at the LHC down to pT=0 and the comparison to the results from pp interactions are aimed at the assessment of cold-nuclear-matter effects on open-charm production, which is crucial for the interpretation of the results from Pb-Pb collisions.
Methods: The prompt charmed mesons D0,D+,D*+, and D+s were measured at mid-rapidity in p-Pb collisions at a center-of-mass energy per nucleon pair √sNN=5.02 TeV with the ALICE detector at the LHC. D mesons were reconstructed from their decays D0→K−π+,D+→K−π+π+, D*+→D0π+,D+s→ϕπ+→K−K+π+, and their charge conjugates, using an analysis method based on the selection of decay topologies displaced from the interaction vertex. In addition, the prompt D0 production cross section was measured in pp collisions at √s=7 TeV and p-Pb collisions at √sNN=5.02 TeV down to pT=0 using an analysis technique that is based on the estimation and subtraction of the combinatorial background, without reconstruction of the D0 decay vertex.
Results: The production cross section in pp collisions is described within uncertainties by different implementations of pQCD calculations down to pT=0. This allowed also a determination of the total c¯c production cross section in pp collisions, which is more precise than previous ALICE measurements because it is not affected by uncertainties owing to the extrapolation to pT=0. The nuclear modification factor RpPb(pT), defined as the ratio of the pT-differential D meson cross section in p-Pb collisions and that in pp collisions scaled by the mass number of the Pb nucleus, was calculated for the four D-meson species and found to be compatible with unity within uncertainties. The results are compared to theoretical calculations that include cold-nuclear-matter effects and to transport model calculations incorporating the interactions of charm quarks with an expanding deconfined medium.
Conclusions: These measurements add experimental evidence that the modification of the D-meson transverse momentum distributions observed in Pb–Pb collisions with respect to pp interactions is due to strong final-state effects induced by the interactions of the charm quarks with the hot and dense partonic medium created in ultrarelativistic heavy-ion collisions. The current precision of the measurement does not allow us to draw conclusions on the role of the different cold-nuclear-matter effects and on the possible presence of additional hot-medium effects in p-Pb collisions. However, the analysis technique without decay-vertex reconstruction, applied on future larger data samples, should provide access to the physics-rich range down to pT=0.