Oil-specific Demand Shocks Research Articles

Do heterogeneous oil price shocks really have different effects on earnings management?

Under the modern corporate governance structure, there is a knowledge gap in how companies' financial reporting practices respond to oil price shocks in China. To fill this gap, we employ China's A-share listed companies and follow Kilian (2009) study to investigate how the three types of classical oil shocks affect corporate earnings management heterogeneously. We also consider the role of oil implied volatility in this relationship and further examine the possible heterogeneity between energy-related and non-energy-related subsamples. The empirical results show that there are variant effects among the heterogeneous oil price shocks on earnings management. Specifically, oil supply shocks stimulate firms to manipulate more accrual and real earnings, and firms are more likely to carry out accrual earnings management downward. Oil aggregate demand shocks weaken the degree of accrual earnings manipulation and mainly reduce the negative accrual earnings manipulation. Oil-specific demand shocks constrain the earnings management behavior of companies and improve their accounting quality. Besides, the increased uncertainty of oil price weakens the promotion effect of oil supply shocks on earnings manipulation, and the moderating effect occurs mainly in downward earnings management. Furthermore, the subsample estimated results reveal that oil price shocks do not affect the degree of accrual earnings management of energy-related companies. Instead, they impact the non-energy-related companies. Overall, our findings provide a series of targeted policy recommendations to mitigate the principal-agent problems and cope with energy price volatility risks.

What matters for consumer sentiment in the euro area? World crude oil price or retail gasoline price?

We investigate the link between crude oil prices, retail gasoline prices and consumer sentiment in the euro area. Our results reveal that consumer sentiment and its key components deteriorate notably as a response to positive shocks to real gasoline prices at the pump. On the contrary, positive oil-specific demand shocks do not trigger such a strong deterioration of consumer sentiment. The analysis is further refined to analyse the effects of these shocks to six key sub-components of consumer sentiment, which include household finance, conditions for buying durable products and the macroeconomy.

The Dynamic Impact of Structural Oil Price Shocks on the Macroeconomy

Abstract In this paper, we apply the structural vector autoregression (SVAR) model to decompose the international oil price shock into oil supply shocks, aggregate demand shocks and oil-specific demand shocks, and then use the DCC-GARCH model to analyse the dynamic correlations between these three kinds of oil price shocks and the macroeconomic variables of several oil importing and exporting countries. To quantify the intensity of the effect of oil shocks on these variables, we propose a measure, conditional expectation (CoE), to capture the percent change of the economic variable under oil price shocks relative to the median state. The time-varying copula model is employed to estimate the proposed measure through time. The empirical results show that, for instance, the impacts of oil price shocks on macroeconomic variables are different in different periods, showing the time-varying characteristics. Additionally, the impacts of oil price shocks on macroeconomic variables show great differences and some similarities among different countries. Finally, we give some policy suggestions for these countries, in particular for China’s special results.

Asymmetries in the transmission of oil price shocks to inflation in the eurozone

Theory predicts that the level of inflation in an economy and the trend in the prevailing inflation rate may affect how oil price shocks, through their influence on firms’ expectations and price-setting behaviors, are transmitted to inflation. However, empirical evidence regarding this relationship is limited and calls for further exploration. Using data for 12 eurozone countries over the period from 1999 to 2020, we analyze how the inflation environment in which an oil price shock occurs influences its transmission. We find that the inflation environment is a determinant in the way oil supply shocks and oil-specific demand shocks are transmitted to inflation, with positive shocks displaying higher transmission in high inflation environments. Furthermore, transmission of shocks to core inflation, which represents an indirect effect, only occurs in high inflation environments. These findings highlight the need to consider the inflation environment in order to define appropriate monetary policies in response to inflationary pressures caused by oil price shocks.

Oil and the U.S. stock market: Implications for low carbon policies

We extend the existing understanding of the relation between oil prices and stock markets in two ways: (1) by evaluating the effects of the oil market on the U.S. stock market, at an aggregate level and for all forty-nine U.S. industry specific portfolios, and (2) by scrutinizing the dynamic nature of this relation within a Structural Vector Autoregression (SVAR) specification for a large set of rolling samples with fixed size. Results indicate that the effect of oil prices on the U.S. stock market depends on the type and timing of the shock. An oil supply shock generally does not have a statistically measurable effect on stock market performance. Conversely, an aggregate demand shock has a positive effect on nearly all sectors while an oil-specific demand shock has a negative effect on stock returns for most industries. These results suggest that investors can shift the portfolios consistent with smaller effects of oil-related shocks and 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.

The time-varying responses of financial intermediation and inflation to oil supply and demand shocks in the US: Evidence from Bayesian TVP-SVAR-SV approach

The perception of the pass-through of oil price shocks on the real and financial spheres has undergone considerable evolution with the emergence of a literature devoted to the sources of oil price fluctuations. This perception is also found to evolve over time depending on market expectations, structural changes or crises. Focusing on the specific case of the US, this paper investigates the time-varying effects of oil price shocks on financial intermediation (credit market) and inflation as a transmission channel. Monthly data are used for a period that encompasses the recent Covid-19 pandemic crisis. Prior to the construction of a time-varying parameter structural vector autoregression stochastic volatility (TVP-SVAR-SV), a structural VAR (SVAR) model is estimated to disentangle oil price shocks in four shocks: oil supply, aggregate demand, domestic demand and oil-specific demand shocks. The results underscore the increasing response of financial intermediation to oil supply, aggregate demand and oil specific demand shocks since the shale revolution. In addition, the response of credit markets to aggregate demand shocks during the covid-19 pandemic is different from that observed during the subprime crisis. It appears also that the response of inflation influence the reaction of the credit market to aggregate and domestic demand shocks.

Dynamics and causality of oil price shocks on commodities: Quantile-on-quantile and causality-in-quantiles methods

We aimed to use rolling quantile regression, quantile-on-quantile, and causality-in-quantiles methods to document the dynamics and causal relationships between oil price shocks and commodities using a dataset from January 1992 to June 2019. The empirical results indicated that the coefficients of the rolling window quantile regression varied over time periods and were most significant for oil supply shock effects on commodities. Furthermore, the causality results showed that oil shocks can provide some predictability for commodities in some quantiles. The quantile-on-quantile analysis revealed that the effects of oil shocks on commodities varied across quantiles and were heterogeneous and asymmetrical. The impact of supply shock on commodities was mainly negative, whereas for aggregate demand shock, the effects were positive in bearish markets. For oil-specific demand shock, a symmetric dependence structure was detected.

Uncertainty-dependent and sign-dependent effects of oil market shocks

This paper investigates the uncertainty-dependent and sign-dependent effects of the oil market fundamental shocks, namely supply, aggregate demand and oil-specific demand shocks. We do so by first proposing a novel oil uncertainty index that is measured by the stochastic volatility of the unpredictable component of oil prices. We then employ a nonlinear model and find that the all reactions of oil production, real price of oil, and global economic activity to the structural shocks are regime-dependent. Moreover, we extend the model to accommodate positive and negative oil market shocks to examine the possible asymmetric effects. In relation to real economic activity, the effects of oil supply shocks are asymmetric regardless of the state of the market, but oil-specific demand shocks are only asymmetric when oil price uncertainty is high.

The Impact of Oil Shocks on Exchange Rates: The Case of Selected OPEC Countries

OPEC countries are heavily dependent on oil dollar revenues through which impact on exchange rates. The purpose of this study is to investigate the effect of oil shocks on the real exchange rates for selected OPEC countries for the period 1980-2018. The oil shocks are first obtained using the vector auto-regression model and then their effects on the exchange rates are estimated using a panel quantile regression model. The results show that effect of oil shocks on exchange rates varies across quantiles. The oil specific-demand shock and global demand shock have a negative and significant effect on the real exchange rates while the oil supply shock has a positive and significant effect on the real exchange rates in OPEC countries. Furthermore, oil specific-demand shock has the most impact on the real exchange rates.

Oil price shocks, exchange rate and uncertainty: case of Latin American economies

ABSTRACT This paper examines the effects of oil demand and supply shocks on emerging market economies in Latin America using a Bayesian vector autoregressive (VAR) model that combines zero and sign restrictions. Our results highlight the importance of separately identify the oil market shocks. The higher price of oil driven by increased global demand produces higher output growth in Brazil, Colombia, and Chile. The results are more persistent for Brazil and Colombia likely due to increased income from oil exports, as both economies are net oil exporters. The better times in the domestic economies result in lower uncertainty and appreciation of the exchange rate in all countries in the sample. Oil supply shocks and oil-specific demand shocks are not statistically significant for most variables. Our results provide important insights into the appropriate exchange rate policy in emerging market economies.

Impact of oil demand and supply shocks on the exchange rates of selected Southeast Asian countries

This study examines the impact of structural oil demand and supply shocks, derived from a structural vector autoregression model proposed by Kilian (2009), on the real effective exchange rates (REER) of Indonesia, Malaysia, Singapore, Thailand, and the Philippines. Our results show that the REER of these countries are not impacted by oil supply shocks. Oil-specific demand shocks affect the REER of Thailand contemporaneously and those of Indonesia, Singapore, and the Philippines with a one-month lag. However, more than one-month-old oil-specific demand shocks usually do not affect the REER of these countries.

Do oil shocks affect Chinese bank risk?

This paper used the panel vector autoregression model to decompose oil shock into four discrete kinds of shocks: Supply, global demand, specific demand for oil, and oil speculation. Thereafter, their impacts on the stock returns risk of 16 listed banks in China were estimated. The results show a slight increase in bank risk in the second month affected by oil supply shock, which turned negative between the third and the 10th months. The impact of global demand shock on banking sector risk was significantly negative and recovered after 10 months. Oil-specific demand shock briefly and rapidly reduced banking sector risk in the first three months and returned to normal in the fourth month. The impact of oil speculative shock was not significant in the first four months, but increased bank risk levels between the fifth and eighth months. Additionally, the banks' group discussion results demonstrate the absence of impact of oil shock on state-owned banks, although it significantly affected the risk level of non-state-owned banks, indicating that the latter are more sensitive to oil shock

On the Nonlinear Impact of Oil Price Shocks on the World Food Prices Under Different Markets Conditions

This paper investigates the impact of oil price shocks on the world food prices. We use the structural VAR model to disentangle oil price shocks into supply, aggregate demand, and oil-specific demand-driven shocks. Moreover, we employ a new approach based on the Markov regime-switching quantile regression (MRS-QR) model to investigate the response of food prices to different oil price shocks. Based on monthly data from 1992 to 2018, results show that the reaction of food prices to different structural oil shocks depends on the oil price regimes and varies in significance, sign, and size throughout the food market conditions. Besides, the increases in regression coefficients and smoothed probability during food and oil crisis periods confirm the existence of contagion effects between oil and food markets. Moreover, we find that the supply and aggregate demand shocks do not show a strong contribution to the presence of this phenomenon. Conversely, oil-specific demand shocks represent the main factor that contributes to contagion between oil and food markets.

Responses of macroeconomy and stock markets to structural oil price shocks: new evidence from Asian oil refinery

In extensive oil-related literature, less attention has been paid to Asia and particularly little evidence is known for oil-refining countries. This paper examines how the economy of an oil-refining country reacts to an oil price shock and performs cross-country comparisons with oil-exporting and oil-importing countries. Singapore (oil refiner), Japan (oil importer), and Malaysia (oil exporter) are analysed through a structural vector autoregression (SVAR) model using both macroeconomic and financial variables. Results show limited reactions of both macroeconomic indicators and stock returns to an oil supply shock, and an oil aggregate demand shock negatively impacts economic activities. Our findings reveal that the country's status in the oil market is important when an oil-specific demand shock is analysed. Our findings inform policymakers of the effectiveness of using monetary policy tools such as interest rate and exchange rate to mitigate the adverse effects of an oil price shock.

Responses of macroeconomy and stock markets to structural oil price shocks: new evidence from Asian oil refinery

In extensive oil-related literature, less attention has been paid to Asia and particularly little evidence is known for oil-refining countries. This paper examines how the economy of an oil-refining country reacts to an oil price shock and performs cross-country comparisons with oil-exporting and oil-importing countries. Singapore (oil refiner), Japan (oil importer), and Malaysia (oil exporter) are analysed through a structural vector autoregression (SVAR) model using both macroeconomic and financial variables. Results show limited reactions of both macroeconomic indicators and stock returns to an oil supply shock, and an oil aggregate demand shock negatively impacts economic activities. Our findings reveal that the country's status in the oil market is important when an oil-specific demand shock is analysed. Our findings inform policymakers of the effectiveness of using monetary policy tools such as interest rate and exchange rate to mitigate the adverse effects of an oil price shock.

The relation between petroleum product prices and crude oil prices

We present an empirical examination of the relation between real spot Brent oil prices and real spot petroleum product prices, specifically gasoline and heating oil prices. Based upon weekly price data spanning a 30-year period ending in April 2019, we provide consistent evidence of Granger causality running from oil prices to product prices accounting for both non-stationarity of the series, and separately conditional heteroskedasticity. No evidence of Granger causality from product prices to oil prices is found for the full sample period nor the period up to the end of 2005, but evidence that gasoline prices Granger-caused oil prices is found for post-2005. Similar results are found for an extended model that also includes potentially endogenous real market variables related to supply and demand in the oil, heating oil and gasoline markets. Given the reduced form model results that oil prices Granger-cause gasoline and heating oil prices, we specify and estimate recursively identified structural vector autoregressive models that specifically account for structural supply and demand shocks in the oil market as well as the petroleum product markets. The oil market block follows Kilian (2009). We find that real spot gasoline prices and real heating oil prices do not respond to structural oil supply shocks, respond transiently to global commodity demand shocks, but do respond to oil-specific demand shocks. We conclude the result that spot oil prices Granger-cause spot gasoline and heating oil prices largely occurs through the channel of oil-specific demand shocks.

Spillover and quantile linkage between oil price shocks and stock returns: new evidence from G7 countries

The link between crude oil price and stock returns of the Group of Seven (G7) countries (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) was analyzed in this study using monthly data from January 1999 to March 2020. We adopt a similar approach to Kilian (Am Econ Rev 99(3):1053–1069, 2009) and construct a structural vector autoregression framework to decompose crude oil price shocks into oil supply shock, oil aggregate demand shock, and oil-specific demand shock. We then explore the distinct effects of different kinds of oil price shocks from various sources.Based on the decomposed oil price shocks, we apply the connectedness approach and QQ regression to find time-varying co-movements and tail dependence between oil price shocks and G7 stock returns.There is no general correlation between the decomposed oil prices and stock returns in these countries. The effects of oil price shocks on stock returns across different stock market conditions appear to be heterogeneous. Oil supply shock appears to be a net transmitter of spillover effects for all G7 countries within the sample period.

The threat of oil market turmoils to food price stability in Sub-Saharan Africa

Abstract While the causal relationship between different types of oil shocks and food prices in the US and other developed countries has been extensively studied, the inter-dynamics between global oil market turmoils and food prices in Sub-Saharan Africa (SSA) remain unclear. This gap in the literature is particularly striking as populations in developing countries are much more vulnerable to food crises than those in developed countries. In this paper we use structural vector autoregressive (SVAR) models to investigate the impacts of global oil market shocks on local corn prices in several SSA countries. We estimate the structural shocks through independent component analysis, which allows for a more agnostic identification compared with conventional methods. Our key findings are that unlike US or global corn markets, African corn markets are much less sensitive to the impacts of oil-specific demand shocks, instead, disruptions in global oil supply can lead to an increase in food prices in several markets. Countries suffering from oil-supply shocks have neither strategic or natural oil reserves to buffer import shortages, nor efficient oil distribution systems that translate into food prices through higher transport costs. We show that a large share of corn price surges in 2011 and 2012 can be attributed to oil-supply shortages caused by the Libyan revolution and the oil embargo against Iran. Conversely, the shale oil boom in the US and the oil production expansion in the Middle East exerted downward pressures on corn prices in three African countries in 2014/15. Finally, political events related to the oil market, e.g. the tensions between the US and Iran or the recent oil price war between Saudi Arabia and Russia, have the potential to raise or lower corn prices by up to 25%.

Do structural shocks in the crude oil market affect biofuel prices?

Literature shows that the crude oil market has a vital link with subcomponents products, i.e., gasoline and diesel, and alternative energy markets, i.e., natural gas and biofuels. The biofuel industry is a promising solution for many problems such as global warming and high oil prices. Therefore, our paper explores the effect of structural crude oil market shocks on the real price of biofuel. We use structural vector autoregression (SVAR) model as proposed by Kilian (2009) over the period from March 1995 to June 2019. Our main finding reveals that long-run fluctuations in the real prices of biofuel are attributed mainly to global demand shocks and oil-market specific shocks, whereas oil supply shocks have an insignificant role. Our results also indicate that the three shocks combined can justify 68 percent of the variation in the real prices of biofuel, whereas the aggregate demand shocks are the most significant contributor because it justifies 35 percent, and oil-specific demand shocks explain 28 percent. The policy implication of our paper is that the stability of the biofuel market comes from the demand side, not the supply side. Thus, energy demand management is a critical tool to stabilize the biofuel market.

Explaining the nonlinear response of stock markets to oil price shocks

This paper is set to reconcile the existent conflicting empirical evidence on the effect of oil prices on stock prices. We estimate various nonlinear models where the response changes according to a first-order Markov switching process. More importantly, we model the transition probabilities between the high- and low-response regimes to depend on state variables to allow us to explain the forces behind the asymmetry in the response. The results show statistically significant asymmetries that can be explained by economic recessions and to a lower extent depend on the magnitude of the oil price shift and on whether the shift is positive or negative. In the high response regime, the effect is positive and lasts longer. We also find evidence of asymmetries in the response of stock prices to crude oil supply shocks, global aggregate demand shocks, and oil-specific demand shocks.