Oil Price Shocks Research Articles

Do oil market shocks affect financial distress? Evidence from firm-level global data

This study investigates the impact of three oil price shocks on financial distress of global firms using a dataset of 8130 firms across 48 countries from 2002 to 2022. It also analyses the role of energy diversification in the relationship between oil shocks and firm distress. The findings reveal that aggregate demand and specific demand shocks increase firm distress risk, while supply shocks reduce it. Furthermore, the results suggest that energy diversification mitigates the impact of specific demand shocks on firm distress. The study also implements several robustness checks, and the results remain consistent. Potential policy implications are also discussed.

Asymmetric impact of oil structural shocks on non-ferrous metals supply chains: A groundbreaking multidimensional quantile-on-quantile regression

This paper examines the predictability of various oil price shocks on the returns of non-ferrous metals from the supply and demand sides in the US, UK, and China under different market conditions. An innovative multidimensional quantile-on-quantile (MD-QQ) regression approach is proposed to address this topic, which extends traditional univariate QQ regression to multivariate cases, addressing the limitation of omitted variables in the benchmark QQ method. The findings reveal that the forecasting of oil supply shocks on the non-ferrous metal supply chain is generally insignificant. Nevertheless, oil supply shocks will transmit negative (positive) actions when the non-ferrous metal supply-side (demand-side) is in a bear (bull) market. The implication of oil demand shocks on the non-ferrous metal supply chain is generally positive, while the supply-side market of Chinese non-ferrous metals displays mutability in response to oil demand shocks under certain extreme market conditions. Conversely, oil risk shocks have a negative impact across the entire non-ferrous metal supply chain. Their effects are more pronounced when the non-ferrous metal demand market is bearish, exhibiting asymmetric characteristics. Oil demand shocks and risk shocks have a stronger impact on non-ferrous metal supply chains in the US and UK than in China. Our research not only confirms the estimation bias caused by missing variables in traditional baseline models but also provides new insights into the connection between the non-ferrous metals and oil markets by adopting the fresh method.

Oil price shocks and human capital channels in Nigeria

Nigeria faces persistent challenges of high unemployment and poverty, worsened by its over-reliance on the oil sector. While many studies have investigated the relationship between oil price volatility and human capital development, few have examined how this relationship impacts both basic and advanced human capital channels in developing economies; this study addresses that gap by using a Structural Vector Auto Regression (SVAR) approach to investigate how oil price shocks influence human capital channels. Co-integration tests reveal significant long-term relationships among the variables. For the basic channel, oil price shocks are negatively associated with secondary school enrollment but positively linked to primary school enrollment. In the advanced channel, oil price has a positive effect on government expenditure on tertiary education but negatively affects tertiary institution enrollment. The impulse response function confirms that oil price fluctuations significantly affect both basic and advanced channels of human capital. The findings show the detrimental impact of oil price shocks on Nigeria's human capital development, which may negatively affect sustainable development. The study emphasises the urgent need for economic diversification to reduce the economy's vulnerability to oil shocks and promote long-term growth and human capital development.

Information flow between stock returns of advanced markets and emerging African economies

This article used transfer entropy techniques to examine information flows of daily stock market returns between advanced markets and emerging African economies. We modelled the information transfers across different periods of global shocks – the Federal Reserve Bank normalisation post the Global Financial Crisis, oil price shocks, BREXIT, the U.S.-China trade war, and COVID-19. Information interactions from advanced to African markets were moderate, occasionally mixed, and insignificant, leaving room for portfolio diversification. We also discovered some progress regarding the integration process between the developed and African markets on the back of noticeable information exchanges. Our findings from the information exchanges indicate that the stock markets of South Africa, Egypt, Nigeria, and Kenya have led the integration process ahead of their peers. To robust-check our results, we employed the wavelet multiple correlation (WMC) technique by modelling the multi-structure relationship among all the stock markets and confirmed the fast integration between the South African stock market and the developed markets. Our WMC results also revealed that portfolio diversification opportunities are feasible in the short term. The results present important implications for optimal risk management strategies and policy measures to anchor markets to withstand shocks.

G20 systemic risk: Are structural oil price shocks driving factors?

Investigating systemic risk and its driving factors has always been a hot topic. Based on this, we combine the tail-event driven network (TENET) and structural vector autoregression (SVAR) model to study characteristics of G20 systemic risk and the impact of structural oil price shocks on it. The results of TENET model are as follows: From a systemic perspective, G20 systemic risk is high and exhibits significant time-varying characteristics. It can reflect periods of economic stress. From a group perspective, systemic risk in developing countries is often higher than developed countries and is more susceptible to extreme events. The systemic risk in developing countries mainly transmits and receives within the group. The systemic risk in developed countries is more balanced in its sources and mainly releases risk to developing countries. From an individual perspective, the risk spillover in G20 stock markets shows significant regional characteristics. Additionally, Argentina is most sensitive to G20 systemic risk, while India exhibits the strongest risk spillover to other G20 members. The results of SVAR model are as follows: Oil price shocks are important factors in explaining changes in G20 systemic risk, with the most significant being specific demand shock. The supply shock exacerbates systemic risk. The aggregate demand shock increases systemic risk in the short term but reduce it in the long term. The specific demand shock significantly reduces systemic risk. Against the backdrop of increasing uncertainty and economic globalization, these findings are of great significance for accurately identifying key points in regulatory frameworks and mitigating systemic risk.

The Impact of Restrictive Macroprudential Policies through Borrower-Targeted Instruments on Income Inequality: Evidence from a Bayesian Approach

This study used the panel data from 15 emerging markets to examine the impact of restrictive macroprudential policies on income inequality from 2000–2019 using Bayesian panel vector autoregression and Bayesian panel dynamics generalised method of moments models. The chosen models are suitable for addressing multiple entity dynamics, accommodating a wide range of variables, handling dense parameterisation, and optimising formativeness and heterogeneous individual-specific factors. The empirical analysis utilised various macroprudential policy proxies and income inequality measures. The results show that when the central banks tighten systems using macroprudential policy instruments to sticker debt-to-income and financial instruments for lower-income borrowers (the bottom 40% of the income distribution), they promote income inequality in these countries while reducing income inequality for high-income borrowers (the high 1 percent of the income distribution). The impact of loan-to-value ratios was found to be insignificant in these countries. Fiscal policy through government expenditure and economic development reduces income inequality, while money supply and oil-price shocks exacerbate it. The study suggests implementing a progressive debt-to-income (DTI) ratio system in emerging markets to address income inequality among lower-income borrowers. This would adjust DTI thresholds based on income brackets, allowing lenient credit access for lower-income borrowers while maintaining stricter limits for higher-income borrowers. This would improve financial stability and reduce income disparities. Additionally, targeted financial literacy programs and a petroleum-linked basic income program could be implemented to distribute oil revenue to lower-income households. A monetary supply stabilisation fund could also be established to maintain financial stability and prevent excessive inflation.

Do oil price shocks drive systematic risk premia in stock markets? A novel investment application

This paper examines the effect of oil price shocks on factor returns in a set of 62 stock markets. Oil price shocks capture significant predictive information regarding the size and direction of factor returns in global markets, depending on the market classification and nature of oil shock. Oil supply and precautionary demand shocks possess the greatest predictive power over risk premia, particularly for value and momentum. We argue that time varying investor sentiment and the flexibility of firms to respond to economic shocks drive the responses of factors to oil shocks. More importantly, a conditional global factor investing strategy wherein the investment positions are tilted towards factor-based portfolios, conditional on the size and direction of the oil price shock, yields significant improvements in returns. Our findings show that smart beta strategies can be significantly improved by conditioning factor positions based on the size and direction of oil market shocks.

Time-varying effects of structural oil price shocks on financial market uncertainty

This study employed the structural oil price decomposition method proposed by Ready (2018) to decompose oil price shocks into oil risk shocks, demand shocks, and supply shocks. By using the Diebold and Yilmaz (DY) spillover index and rolling window methods, the static and dynamic spillovers of structural oil price shocks on financial market uncertainty were examined. The findings suggest that oil risk shocks exhibited the strongest spillover effects on financial market uncertainty (except for South Africa), followed by oil demand shocks, while oil supply shocks had virtually no impact. Second, the effects of structural oil price shocks on financial market uncertainty were time-varying. Third, significant differences in the spillover effects of structural oil price shocks on financial market uncertainty were found across countries, and the spillover effect of oil risk shocks on the financial market uncertainty in the United States was the largest in all periods. Fourth, the spillover effects of oil demand shocks on financial market uncertainty were larger in the high than in the low oil price period (except for Japan). Finally, during the COVID-19 (coronavirus disease) pandemic compared with the pre-epidemic period, the spillover effects of oil risk shocks on the financial market uncertainty in China significantly decreased, while simultaneously, the spillover effects of oil supply shocks on the financial market uncertainty in Australia substantially increased.

The impact of renewable and non-renewable energy consumption on aggregate output in Pakistan: robust evidence from the RALS cointegration test.

Over the past three decades, Pakistan's energy consumption has surged due to industrialization, population growth, and development activities. To meet the escalating energy demands, the country has primarily relied on thermal power projects, which are financially burdensome and environmentally detrimental, compared to hydropower projects. This reliance exposes Pakistan to global oil price shocks and environmental degradation. To address this dilemma, this empirical research investigates the impact of both non-energy factors (labour and capital) and energy-specific factors (renewable and non-renewable) on Pakistan's aggregate output, using annual time-series data from 1980 to 2021. The analysis employs the newly established Residual Augmented Least Square (RALS) cointegration test and the Autoregressive Distributed Lag (ARDL) methodology to estimate the long-term cointegrating relationship among the examined variables. The empirical findings demonstrate that both non-energy and energy-specific factors positively and significantly influence Pakistan's long-term aggregate output. However, petroleum consumption exerts a positive but insignificant influence on Pakistan's long-term aggregate output. The study recommends diversifying the energy supply mix to include more hydroelectricity, non-hydroelectric renewables (mainly solar and wind), and natural gas. Specifically, transitioning from imported, expensive, and more greenhouse gas (GHG)-generating petroleum products to domestically produced natural gas could potentially reduce Pakistan's trade deficit and its vulnerability to global oil price shocks. Besides the economic benefits, shifting from non-renewable energy sources (specifically oil) to renewable energy would enhance Pakistan's image and increase its geopolitical influence over neighboring countries. Additionally, the study emphasizes the need to encourage private sector participation in renewable energy projects and suggests implementing effective carbon tax policies to mitigate CO2 emissions and foster economic growth.

Analysing Oil Prices Fluctuations, Carbon Emissions and Renewable Energy Trends in Uncovering the Eco‐Economic Interplay in China's Trade Liberalization

ABSTRACTThis study evaluates the factors contributing to carbon emissions in China between 2002 and 2021, considering the impact of GDP growth, shocks in oil prices, trade liberalization and energy use. Using the dynamic simulated ARDL (SARDL) model, we indicate a long‐term link between trade liberalization, oil prices (WTI) shocks, GDP growth, energy use and CO2. The novel SARDL revealed a direct relationship between trade liberalization and CO2 in China in the long term. However, the results show a negative impact of WTI shocks on CO2 emissions. The study suggests that renewable energy (RE) significantly and negatively affects China's CO2 emissions. In addition, the findings conclude that, in the case of China, GDP has an insignificant long‐run relationship with CO2 emissions. The outcomes provide valuable insights for policymakers, researchers and industry stakeholders to enhance RE and promote sustainable energy practices.

Risk spillovers and diversification benefits between crude oil and agricultural commodity futures markets

This study examines the dependence structure and risk spillovers between crude oil and eight major agricultural futures (wheat, corn, soybean coffee, cotton, lumber, cocoa, and live cattle) markets. It also analyzes the potential conditional diversification benefits using a variety of copula functions and Conditional Value at Risk (CoVaR) measure. The results show significant crisis-sensitive and temporal dependence between oil and agricultural markets. Moreover, crude oil shows a symmetric tail dependence with both wheat, corn, soybeans, and cotton futures, whereas oil exhibits an average dependence with coffee. A strong dependence is observed between oil and cocoa (lumber) during bearish (bullish) market conditions. Oil and Live cattle have a symmetric dependence during bearish and bullish market conditions. On the other hand, we find asymmetric and bidirectional risk spillovers from oil to agricultural markets. Furthermore, the wheat futures contract appears to be the most dominating and vulnerable asset to oil price shocks, followed by lumber and corn futures, respectively, while the live cattle contracts are the least. Finally, an equally weighted portfolio offers the highest diversification benefits at a 5 % expected shortfall.

The response of oil-importing and oil-exporting countries’ macroeconomic aggregates to crude oil price shocks: some international evidence

The response of oil-importing and oil-exporting countries’ macroeconomic aggregates to crude oil price shocks: some international evidence

Regulating Carry Trades: Evidence from Foreign Currency Borrowing of Corporations in India

Abstract We establish that macroprudential controls limiting capital flows can curb risks arising from foreign currency borrowing by corporates in emerging markets. Firm-level data show that Indian firms tend to issue more foreign currency debt when the interest rate differential between India and the United States is higher. This “carry trade” relationship, however, breaks down once regulators institute more stringent interest rate caps on borrowing; in response, riskier borrowers cut issuance most. Prior to adoption of this macroprudential measure, stock price exposure of issuers to currency risk rises after issuance, as witnessed during the “taper tantrum” episode of 2013; this source of vulnerability is nullified by the measure, as confirmed during the October 2018 oil price shock and the COVID-19 outbreak. We find no evidence of the policy’s efficacy being undermined by leakage or regulatory arbitrage.

Impact of Oil Price Shocks on Islamic and Conventional Bank Performance: Empirical Evidence from Saudi Arabia

This paper aims to investigate and compare the effect of oil price shocks on the bank performance at the aggregate level as well as the level of conventional and Islamic banks. The Autoregressive Distributed Lag (ARDL) methodology was adopted to analyze a panel of 10 Saudi banks, including 6 conventional and 4 Islamic banks, between 2006 Q1 and 2022 Q4. The results revealed that oil price shocks have a direct impact on banking performance. A rise (fall) in oil prices led to an increase (decrease) in bank performance through the channel of price-induced bank deposits. Additionally, oil price shocks have asymmetric effects, with positive oil shocks having a greater impact on bank performance than negative shocks. The findings highlighted that conventional banks tend to benefit more from oil price shocks, especially during oil price booms, as they experience higher positive impacts. However, during oil price busts, Islamic banks were more adversely impacted by oil shocks.

Effects of oil shocks on markets in G7 countries

This paper aims to assess the effects of oil price shocks on the stock markets of the G7 countries. We develop an oil sentiment indicator that measures the volatility of oil prices. We analyze oil shocks on the stock market of the G7 countries, using a structural VAR and Local Projection approach. Our results suggest that oil shocks explain 8% of the US stock market, 10% in Germany, and 7% in the UK. These results point out the possibility of using this sentiment variable for forecasting the stock market’s volatility.

Are All Shocks Alike? Evidence From the Effects of Oil Shocks on Military Expenditure in Nigeria

This study investigated the asymmetric effects of oil shocks–oil price, oil demand and oil supply shocks–on military expenditure in Nigeria. Our study confirmed the presence of short-run and long-run asymmetries in all the three models used. Generally, positive oil price and demand shocks positively influence military expenditure and vice versa for negative shocks. However, a positive oil supply shock is detrimental to military expenditure.

Economic activities, dry bulk freight, and economic policy uncertainties as drivers of oil prices: A tail-behaviour time-varying causality perspective

This paper examines the dynamic impact of economic activity, Baltic dry bulk and economic policy uncertainty on oil prices. Drawing on demand-side economic theory, we focus on how economic activity and economic policy uncertainty drive oil prices and subsequently contribute to the formation of market equilibrium. In this context, we first introduce a unidirectional quantile and time-varying Granger-causality mechanism for the drivers of oil prices. Our novel rolling window quantile Granger causality approach reveals that economic activity drives crude oil price fluctuations and highlights their important role in market imbalances. In particular, economic activity and the Baltic exchange rate index emerge as essential drivers of oil prices, confirming our hypothesis of a demand-side effect. Moreover, our robustness wavelet quantile correlation (WQC) analyses reveal that economic activity promotes oil price fluctuations along both long-term equilibrium trends and short-term dynamics. In contrast, economic policy uncertainty has a dampening effect on oil prices. More broadly, economic activity is positively correlated with the Baltic exchange dry index, highlighting its broader impact on global trade indicators. Moreover, we use a bivariate Quantile on Quantile regression method to identify the equilibrium searches of different thresholds and estimate the robustness of the validity of the WQC findings. Analyzing the quantile and frequency connectedness spillovers, we observe that shocks from economic activity are particularly pronounced in the tail quantiles, reinforcing the demand-side narrative. Overall, the increased risk in extreme tails underscores the increased interaction between economic activity, oil prices and economic policy uncertainties. Our findings have important implications for policymakers and highlight the need for adaptive strategies to manage potential oil price shocks. Thus, by adopting a demand-side perspective, policymakers can better anticipate and respond to oil price fluctuations, promoting more resilient economic policies.

The Impact of Oil Price Shocks on Oil and Gas Production Amidst Geopolitical Risk in OPEC: Insights from Method of Moments Quantile Regression

The Impact of Oil Price Shocks on Oil and Gas Production Amidst Geopolitical Risk in OPEC: Insights from Method of Moments Quantile Regression

Impact of Oil Price Shocks on Russian Macroeconomic Performance

Impact of Oil Price Shocks on Russian Macroeconomic Performance

Forecasting and unveiling the impeded factors of total export of Bangladesh using nonlinear autoregressive distributed lag and machine learning algorithms

Rising global oil prices are a major challenge for an emerging oil-importing nation such as Bangladesh. The majority of prior research on the economic effects of an oil price shock has concentrated on developed countries, with emerging economies receiving comparatively less attention. Bangladesh is vulnerable to price shocks due to its rising oil consumption over the past decade. This study aims to investigate how changes in oil prices would affect Bangladesh's total export earnings and to forecast the overall export volume. This study utilized a nonlinear autoregressive distributed lag (NARDL) approach to account for the asymmetric behavior of oil prices from 1991 to 2021. To assess the accuracy of predictions, the study employed the Prophet forecasting model and the Long Short-Term Memory (LSTM) method. Additionally, the symmetry test revealed a nonlinear relationship between export volume and oil price but a linear relationship between inflation and export volume. According to the NARDL assessment, both positive and negative oil shocks increase export earnings over the long run. The short run summary clarifies that both positive and negative changes in oil prices exert a significant negative effect on exports. Also, Inflation influences export earnings negatively in the short run but positively over the long term. Moreover, using machine learning methods, it was found that the LSTM method outperforms the prophet model in prediction performance with a low root mean square error (RMSE) of 1.88. Also, the analysis revealed policymakers that the export sector requires diversification to reduce its exposure to oil price shocks.