Real Oil Price Research Articles

The impact of oil price shocks on the agricultural commodity prices

AbstractIn this study, we empirically examine the effects of oil‐related shocks on the prices of nine agricultural commodities for the period 1974:01–2022:02. We decompose real oil prices into three independent parts: oil supply shocks; global demand shocks; demand shocks that are specific to the crude oil market applying a symmetric VAR model. Then, we assess the effects of these three shocks on the prices of nine major agricultural commodities individually. Based on our findings, we reveal that the responses of agricultural commodity prices to an oil price change depend significantly on the timing and the driver of the underlying oil price change.

Oil prices in the real economy

SummaryThis paper presents a macro‐finance model of the US economy and the spot and futures markets for oil. The performance of the model is greatly enhanced by using the Kalman filter to model latent variables representing the inflation asymptote, the real price of oil and the slope of the futures curve. We find that these are dominated by innovations in observed futures prices, reflecting the importance of market expectations. Using the Kalman filter to capture inflationary shocks helps solve the notorious price puzzle, the tendency for increases in interest rates to anticipate such developments and apparently cause inflation. Futures prices also depend upon risk premiums, which we find are dominated by the latent variable representing the real oil price rather than macro variables like inflation and interest rates.

Inflation Expectations and the Pass-Through of Oil Prices

Abstract Inflation expectations and the associated pass-through of oil price shocks depend on demand and supply conditions underlying the global oil market. We establish this result using a structural VAR model of the global oil market that jointly identifies transmissions of oil demand and supply shocks through real oil prices to both expected and actual inflation. We demonstrate that economic activity shocks have a significantly longer-lasting effect on inflation expectations and actual inflation than other types of real oil price shocks, and resolve disagreements around the role of oil prices in explaining the missing deflation puzzle of the Great Recession.

A weekly structural VAR model of the US crude oil market

We present a weekly structural Vector Autoregressive model of the US crude oil market. Exploiting weekly data we can explain short-run crude oil price dynamics, including variations related with the COVID-19 pandemic and with the Russia’s invasion of Ukraine. The model is set identified with a Bayesian approach that allows to impose restrictions directly on structural parameters of interest, such as supply and demand elasticizes. Our model incorporates both the futures-spot price spread to capture shocks to the real price of crude oil driven by changes in expectations and US inventories to describe price fluctuations due to unexpected variations of above-ground stocks. Including the futures-spot price spread is key for accounting for feedback effects from the financial to the physical market for crude oil and for identifying a new structural shock that we label expectational shock. This shock plays a crucial role when describing the series of events that have led to the spike in the price of crude oil recorded in the aftermath of Russia’s invasion of Ukraine.

Estimating Long-run Elasticity between Crude Oil Consumption, Real Oil Price, and Real GDP in Global Markets

The study examine the long-run relationship between crude oil consumption, real oil price, and real GDP using a quarterly time series from 1993 to 2020. the empirical analysis uses the Dynamic Least Squares (DOLS) model for both short-run and long-run elasticity among the model variables to estimate the short-run and long-run elasticity of demand for crude oil consumption in 10 regions using Panel Dynamic Least Squares (DOLS) and Pooled Mean Group-AR Distributed Lag Models (PMG/ARDL). The empirical analysis findings confirme that the demand for crude oil internationally is highly insensitive to changes in price and real GDP.

Analysis of Factors Affecting the Dynamics of Residential Real Estate Prices in Russia

In this paper, we have constructed a VAR model to identify and assess the impact of real interest rate shocks, real estate demand, oil prices, uncertainty, and aggregate business activity on residential real estate prices in Russia. The relevance of the research is due to the following: the dynamics of real estate prices determines the consumer and investment behavior of households, and serious fluctuations in real estate prices lead to adverse consequences in many areas of life, so more and more researchers are asking questions about the presence of bubbles in the real estate market, which can be dangerous to the stability of the economy. In addition, a sharp increase in the cost of housing in Russia in 2020 is an open question for researchers. Our goal is to determine what factors caused the rise in real estate prices in Russia in the time interval from the Q1 of 2000 to the Q2 of 2022. A VAR model with a Cholesky decomposition was used for the evaluation. Several specifications were considered with the inclusion of the real oil price as an exogenous variable and a set of endogenous variables: real GDP, real interest rate, uncertainty index and housing price index. The main conclusion of the paper is that the housing market is sensitive to identified macroeconomic shocks, and a decrease in the interest rate leads to an increase in demand and real estate prices. The estimate of the long-term elasticity of housing prices for oil prices was 0.35, the dynamics of oil prices explained a significant proportion of the variation in real estate prices, but the predominant role in housing price fluctuations is given to housing demand shocks. The housing demand shocks in Russia itself had a negligible impact on GDP.

Estimating the real exchange rate misalignment of the Algerian dinar during the period (1980-2019) : an empirical study (Arabic)

The aim of this study is to estimate the long-run Equilibrium Real Exchange Rate (ERER) and to assess the degree of misalignment of the Algerian Dinar for the period (1980-2019) using ARDL approach. Considering that the equilibrium exchange rate of the Algerian dinar is determined by a set of fundamentals of the national economy, the study reached the following main results: In the long run, there are positive relationships between the real effective exchange rate and the differential productivity, real oil price and net capital flows. Whereas, there are inverse relationships between the dependent variable and each of the trade openness, General government final consumption expenditure (% of GDP). The second result is that the REER registered a number of deviations from its equilibrium level, that vary between overvaluation and undervaluation. The third result is that the exchange rate cannot be the only adjustment variable, given the extent of macroeconomic imbalances (internal and external). Parallel efforts at fiscal consolidation and deep structural reforms to diversify the economy and accelerate growth are also essential.

Asymmetric effects of oil price shocks on the demand for money in Algeria

This paper investigates the symmetric and asymmetric effects of real oil prices on real money demand in Algeria over the period 1999:Q1–2020:Q1. Using a linear autoregressive distributed lag model (ARDL), and a nonlinear autoregressive distributed lag model (NARDL), we find no evidence of a long-term relationship among the variables. Interestingly, we reveal that the NARDL model provides strong evidence of a stable money demand. Moreover, the evidence shows that, in the short-term, only real oil price reductions will result in a decrease in real money demand. In the long-term, our findings suggest that oil price increases (decreases) will lead to higher (lower) money demand. Additionally, we find that negative oil price shocks will yield a stronger effect on money demand compared to positive shocks. These results indicate that money demand is a channel through which oil price shocks may affect the macroeconomic activity in Algeria. Therefore, Algerian policymakers should incorporate this asymmetric relationship between oil prices and money demand in designing their monetary policies.

Identifying Money and Inflation Expectation Shocks on Real Oil Prices

Identifying Money and Inflation Expectation Shocks on Real Oil Prices

How oil price and exchange rate affect stock price in China using Bayesian Quantile_on_Quantile with GARCH approach

We revisit the links of real exchange rate, oil price and stock market price for China using Bayesian Multivariate Quantile_on_Quantile with GARCH approach over the period of September 14, 2001 to June 17, 2022 (a total of 4051 days). Results indicate both the links between stock price and oil price and between stock price and exchange rate varying under different combinations of quantiles. GARCH model also indicate that yesterday news and persistence measures varying with current conditional variance under different quantiles. We further estimate half-life of a shock to our whole markets and find out the half-life of a shock range from 0.415 to 4.015 days. Result not found in previous study. Our study has important policy implications for the investors, practitioners, and the government.

The contribution of different aspects of financial development to renewable energy consumption in E7 countries: The transition to a sustainable future

In order to combat climate change, a country must invest in the development of renewable energy sources and the upgrading of its energy infrastructure. Capital is one of the obstacles to the energy revolution because green energy development is often expensive and risky, especially in its infancy. It is imperative to understand how financial development affects renewable energy consumption as well as which aspects of financial development are most essential to its development. This study used Method of Moments Quantile Regression (MMQR) to investigate the impact of different aspects of financial development on renewable energy consumption using panel data from seven emerging (E7) countries from 1991 to 2018. The model is enhanced by controlling for the effects of foreign direct investment, economic growth, real oil prices, and trade openness. In the empirical findings of MMQR, it is confirmed that the influence of independent variables varies among quantiles of renewable energy consumption. Overall, we find that all three facets of financial development (financial development overall, financial markets-related development, and financial institutions-related development) positively impact renewable energy consumption. The results of our study further indicate that although all three aspects of financial development increase renewable energy consumption, but the effect is greater in the case of financial markets-related development. The findings of our empirical study have significant policy implications for the achievement of Sustainable Development Goals.

Comparative analysis of two resources-based economies: A study of policy recommendation toward sustainable development

This is a comparative study between two resource endowed economies, Norway and Nigeria towards ascertaining the impact of the resources in the sustainable development (SD) of the countries. The findings are expected to be a highlight for the poor performing economy (Nigeria) and to replicate the tested and workable policies of Norway to Nigeria economic performance. Separate empirical estimates and analyses with quarterly data of (1992QI-2018QIV and 1992QI-2019QIV) for both countries (Nigeria and Norway) respectively are done for each in a time series manner. The results from the both autoregressive distributed lag (ARDL) and granger causality for both countries are as follows: Dutch disease is found via government spending effects and crude oil price on agriculture. Foreign direct investment (FDI), real gross domestic product (GDP) and real exchange rate are found positively impacting Nigerian agricultural sectors. The findings for the Norway's case are as follows: Dutch disease symptom is found via government spending effects, real exchange rate and crude oil price on manufacturing sector. From granger causality findings, there is a clear exposition of nexus among the government spending, oil price, FDI and real exchange rate which shows implication of government spending and oil price in both studies. This is a pointer towards existence of Dutch disease in both countries. This, notwithstanding, Norway as a country is among the best performing economies of the world due to efficient and effective policies. Nigeria having performed so poor is expected to consider Norway as a model in mitigating her Dutch diseases.

Oil prices and gold prices on housing market in China: novel findings from the bootstrap approach

PurposeThis study aims to assess how real income, oil prices and gold prices affect housing prices in China from 2010 to 2021.Design/methodology/approachThis study uses a novel bootstrap autoregressive distributed lag (ARDL) testing to empirically analyze the short and long links among the tested variables.FindingsThe ARDL estimations demonstrate a positive impact of oil price shocks and real income on housing market prices in both the phrases of the short and long run. Furthermore, the results reveal that gold price shocks negatively affect housing prices both in the short and long run. The result can be attributed to China’s housing market and advanced infrastructure, resulting in a drop in housing prices as gold prices increase. Additionally, the prediction of housing market prices will provide a base and direction for housing market investors to forecast housing prices and avoid losses.Originality/valueTo the best of the authors’ knowledge, this is the first attempt to analyze the effect of gold price shocks on housing market prices in China.

The Impact of Oil Prices on the Capital Expenditures of the State Budget in Azerbaijan

The article studies the theoretical and practical approaches related to the allocation of oil revenues for public investment. Based on the two-step Engel-Granger procedure for cointegration analysis, the relationship between the ratio of the capital expenditures of the state budget to non-oil GDP and the logarithm of real oil prices in Azerbaijan is investigated. It has been determined that public investment in Azerbaijan is highly dependent on the oil price, and the volatility of the oil price also affects the volatility of these expenditures. So, it was proposed that the capital expenditures of the state budget should be determined based on the goals of economic development, and not depending on changes in oil prices.

Unexpected economic growth and oil price shocks

Profit-maximizing oil producers base their production schedules on expected economic growth which usually has impacts on oil demand. However, in the wake of unexpected economic growth, oil price shocks can ensue, when no additional oil supply meets unexpected demand. This paper examines whether and how unexpected economic growth could explain oil price shocks. Forecasting errors of mainstream institutions which represent the global market are employed to measure unexpected economic growth and oil price shocks. We find that because the market underestimated China's economic prospects, it is not the strong economic growth but the unexpected growth that raised the oil price during 2000–2008. Afterwards, this impact was on the wane, possibly due to the enhanced accuracy in economic growth expectations for China. Lower-than-expected economic growth might lead to the decline in the real oil price after 2014. The results emphasize the role of expectation in oil price variations.

Forecasting the real prices of crude oil: A robust weighted least squares approach

The ordinary least squares (OLS) estimator inflates the estimation variance of parameters in the presence of outliers, thus providing poor out-of-sample forecasts. We forecast the real price of crude oil using a robust weighted least squares (RWLS) approach that has the potential to improve forecasting performance by dealing with outliers. This approach down-weights extreme observations using a class of kernel functions. Our results show that the RWLS improves forecasting accuracy relative to the standard OLS approach. Furthermore, the predictability of oil prices revealed by the RWLS is statistically significant for longer horizons. The predictive ability of the RWLS comes from more efficient estimates and the trade-off between forecast bias and variance. Sensitivity analyses indicate that the findings are robust to alternative validation samples, kernel functions, and combination strategies.

Equity premium prediction using the price of crude oil: Uncovering the nonlinear predictive impact

Highly cited studies, such as Mork (1989), Hamilton (1996), Hamilton (2003) and Kilian and Vigfusson (2013) establish a nonlinear connection between movements in the real (nominal) price of crude oil and the real gross domestic product (GDP) growth rate. Based on the observation that crude oil price increases have a different impact on the real GDP growth rate than crude oil price decreases, the authors introduce various nonlinear transformations of the price of crude oil to account for the nonlinear predictive impact. Using predictive regressions à la Goyal and Welch (2008), a growing number of studies in recent years have conditioned on these nonlinear crude oil price measures to predict equity premium out-of-sample. By applying the dynamic rotation rule suggested in Zhu and Timmermann (2021), we demonstrate that the form of nonlinearity that helps improve relative out-of-sample point prediction accuracy the most does not have to do with crude oil price increases (decreases) relative to recent prices as perceived by the current literature, but with connecting the relative out-of-sample point prediction performance between the benchmark and the crude oil price-based model with movements in economic variables measuring equity market volatility, economic activity, uncertainty and financial conditions. The statistical evidence of out-of-sample equity premium predictability also translates to economic gains.

The influence from a demand perspective with real economic activity: China versus the United States in world oil markets

AbstractIn this paper, we provide direct evidence for an increasingly critical role of China in the world oil markets. Specifically, our empirical results confirm that the influence of China's oil demand on the oil price of the world has increased over time and surpassed that of the United States. The contribution of demand perspective from China are formally quantified by three key variables of world oil market, which are world oil production, real economic activity and the real price of crude oil. The impact of oil demand from China is used to compared with those from other oil markets, including shocks from the United States. We also construct suitable proxies that reflect real economic activity from these economies, and identify them via a structural vector autoregressive model to disentangle the influence of oil demand from China, the United States and the rest of the world. Our results confirm the finding of recent research, which is the increasing demand for oil from developing countries has become a key driver of the price of oil.

The Asymmetric Impact of Oil Prices and Production on Drilling Rig Trajectory: A correction

• This paper provides a correction to a coding error in a previously published paper. • The study utilizes linear and nonlinear ARDL bounds testing to examine relationships between the type of drilling rig, real oil prices, and oil production. • The results illustrate the importance of drilling rig trajectory in the operations of oil producing firms.

Oil Prices and Exchange Rates: Measurement Matters

This paper examines the relevancy of price measurement for characterizing the relation between real oil prices and real exchange rates. The current empirical literature shows a consensus on using the U.S. CPI to deflate the nominal oil price simply because of its numerous advantages. However, reliance on the U.S. CPI assumes that the worldwide alternative to a barrel of oil is the U.S. consumption basket. There are, however, alternative baskets, and I consider two: the price of gold and the IMF Global Commodity Price Index. Inspection of the results reveals that the relation between real oil prices and real exchange rates is sensitive to the choice of deflator for the price of oil and to the use of effective or bilateral exchange rates. Specifically, using the IMF’s Global Commodity Price Index as a deflator reveals that real oil prices and real exchange rates (effective or bilateral) are clustered along a long-run relation with unitary elasticity. Further, this choice of deflator has the lowest forecast errors. To be sure, much work remains to be completed along the lines of measurement and estimation methods. However, extending the results of this paper will emphasize its main point—namely, that measurement matters.