[en] Highlights: • This paper date-stamps periods of oil-price explosivity relative to the general price and oil inventory levels in the US, respectively, for the period 1876 – 2014. • We make use of the multiple bubble detection strategy outlined by Phillips, Shi & Yu (2013). • We identify for each series multiple periods of oil price explosivity. • We contextualize the contemporaneous events surrounding the periods of explosivity identified by the estimation procedure used. - Abstract: This paper sets out to date-stamp periods of historic oil price explosivity using the Generalized sup ADF (GSADF) test procedure developed by Phillips, Shi, and Yu (2013). The date-stamping procedure used in this paper is effective at identifying periodically collapsing bubbles; a feature found lacking with previous bubble detection methods. We set out to identify periods of oil price explosivity relative to the general price level and oil inventory supplies in the US since 1876 and 1920, respectively. The recursive identification algorithms used in this study identify multiple periods of price explosivity, and as such provides future researchers with a reference for studying the macroeconomic impact of historical periods of significant oil price build-ups.

[en] This paper examines whether there is a volatility transmission between oil prices and financial stress by means of the volatility spillover test. We employ WTI crude oil prices and Cleveland financial stress index for the period 1991–2014 and divide the sample into pre-crisis, in-crisis, and post-crisis periods due to the downward trend in oil price in 2008. The volatility model estimations indicate that oil prices and financial stress index are dominated by long-run volatility. The volatility spillover causality test supports evidence on risk transfer from oil prices to financial stress before the crisis and from financial stress to oil prices after the crisis. The impulse response analysis shows that the volatility transmission pattern has similar dynamics before and after the crisis and is characterized by higher and long-lived effects during the crisis. Our results have implications for both policy makers and investors, and for future work. -- Highlights: •Volatility spillover between oil prices and financial stress index is examined. •Analysis is conducted for sub-periods: pre-crisis, in-crisis, and post-crisis •Oil prices spill on financial stress before the crisis, but spillover reversed after the crisis. •Volatility transmission pattern has similar dynamics before and after the crisis. •Implications for investors and policy makers are discussed

[en] This paper investigates the role of permanent and transitory shocks, within the framework of common cycles and common trends, in explaining stock and oil prices. We perform a multivariate variance decomposition analysis of monthly data on the West Texas Intermediate (WTI) oil price and the S&P 500. The dataset used in the study spans a long period of 150 years and therefore contains a rich history to examine both the short- and long-run comovement properties of oil and stock prices. Given that the oil and stock markets might comove both in the short- and long-run, it is of interest to see the relative impacts of transitory and permanent shocks on both variables. We find that (log) oil price and (log) S&P 500 share a common stochastic trend for our full sample of September 1859 to July 2015, but a common cycle only exists during the post-WW II period. Full and post-WW II samples have quite different common feature estimates in terms of the impact of permanent and transitory shocks as measured by the impulse responses and forecast error variance decompositions. We also find that in the short-run oil is driven mostly by cycles (transitory shocks) and stock market is mostly driven by permanent shocks. But, permanent shocks dominate in the long-run. - Highlights: • Role of permanent and transitory shocks analyzed for oil and stock markets • The framework of common cycles and common trends used over 1859 to 2015 • Common stochastic trend for full-sample and common cycle post-World War II • Stock market driven by permanent shock in short- and long-runs • Oil market driven by temporary (permanent) shocks in short-run (long-run)

[en] There exists a huge international literature on the, so-called, Environmental Kuznets Curve (EKC) hypothesis, which in turn, postulates an inverted u-shaped relationship between environmental pollutants and output. The empirical literature on EKC has mainly used test for cointegration, based on polynomial relationships between pollution and income. Motivated by the fact that, measured in per capita CO_2 equivalent emissions, South Africa is the world's most carbon-intensive non-oil-producing developing country, this paper aims to test the validity of the EKC for South Africa. For this purpose, we use a century of data (1911–2010), to capture the process of development better compared to short sample-based research; and the concept of co-summability, which is designed to analyze non-linear long-run relations among persistent processes. Our results, however, provide no support of the EKC for South Africa, both for the full-sample and sub-samples (determined by tests of structural breaks), implying that to reduce emissions without sacrificing growth, policies should be aimed at promoting energy efficiency. - Highlights: • The co-summability concept is used to test the validity of the EKC for South Africa. • The case of structural breaks is also considered when testing for the EKC. • Results provide no support of the EKC for South Africa. • To reduce CO2 emissions without sacrificing growth, policies should be aimed at promoting energy efficiency.

[en] The resource curse is sometimes associated with poor resource-rich countries. However, using panel evidence from the United States, we find that the resource curse is also prevalent in a wealthy resource-rich country. This study investigates the impact of oil resources on income inequality, with a particular focus on distinguishing between the effects from oil abundance (i.e. production) versus oil dependency (i.e. consumption). We observe contrasting non-monotonic outcomes from oil abundance in comparison to oil dependency. For oil abundance, states with low oil production will have less inequality if they increase oil production, and states with high oil production will have increased income inequality if they increase production. The opposite holds true for oil dependency. The findings suggest several channels of concern. For example, oil-rich states are more vulnerable to rent-seeking behaviour as oil production and oil revenues increase, which can adversely affect the income distribution gap. On the other hand, oil-dependent states are more likely to be affected by commodity price shocks which can increase income inequality.

[en] Highlights: • Variants of the conditional autoregressive value at risk (CAViaR) are used to measure oil-market tail risk. • A heterogenous-autoregressive-tail-risk model is used to link tail risk to geopolitical risk, threats, and acts. • Full-sample results show that threats increase tail risk and actual acts reduce tail risk at longer forecast horizons. . • Out-of-sample results show that threats are statistically significant predictors of oil-market tail risk. Using monthly data for the period from 1916 to 2020, we report that geopolitical risk, when decomposed into threats and actual risk, has predictive value for tail risk in the oil market. When we study the full sample of data, we find that threats increase tail risk in the oil market, while actual acts related risk reduces tail risk at longer forecast horizons. While the findings of the full-sample analysis show that the effect of threats and acts on tail risk in the oil market is quantitatively small, results of an out-of-sample analysis show that, for several model configurations, geopolitical risks associated with threats are statistically significant predictors of tail risk in the oil market, even after controlling for a factor capturing global equity-market tail-risk spillovers. Our results have important investment implications.

[en] Highlights: • The impact of oil price uncertainty on economic growth in OECD countries is studied. • Taking a historic perspective, the sample covers a 144-year period starting in 1870. • The negative impact of uncertainty is more severe for oil producing countries. • A smaller impact is recorded in the post-World War II subsample period. • Reasons for declining impact of oil price uncertainty are proposed. -- Abstract: This paper uses a number of different panel data estimators, including fixed effects, bias-corrected least squares dummy variables (LSDVC), generalised methods of moments (GMM), feasible generalised least squares (FGLS), and random coefficients (RC) to analyse the impact of real oil price volatility on the growth in real GDP for 17 member countries of the Organisation for Economic Co-operation and Development (OECD), over a 144-year time period from 1870 to 2013. The main finding of the study is that oil price volatility has a negative and statistically significant impact on economic growth of the OECD countries in the sample. In addition, when allowing for slope heterogeneity, oil-producing countries are significantly negatively impacted by oil price uncertainty, most notably Norway and Canada.

[en] Highlights: • Predictive ability of M&A for WTI oil returns and volatility was analysed. • Nonparametric quantile-based methodology was used. • M&A activity predicts power oil return and volatility. • M&A activity by oil firms better predictor than same by non-oil acquirers - Abstract: This paper provides a novel perspective to the oil-stock market nexus by examining the predictive ability of mergers and acquisitions (M&A) over West Texas Intermediate (WTI) oil returns and volatility using a nonparametric quantile-based methodology. Our findings suggest that M&A activity carries significant predictive power over oil return and volatility, while predictability displays remarkably distinct patterns across various quantiles representing normal, bull and bear market states. We also observe that M&A activity by oil firms, i.e. both the acquiring and target firms considered active in the oil and gas (O&G) industry, generally carries greater predictive power over both oil returns and volatility compared to M&A activity by non-oil acquirers, i.e. acquirers that have entered the O&G industry by buying an oil company. Our findings imply that M&A activity in the O&G industry carries valuable fundamental information regarding future expectations on oil price dynamics and should be taken into account in forecasting exercises.

[en] This study reexamines the causal link between electricity consumption, economic growth and CO₂ emissions in the BRICS countries (i.e., Brazil, Russia, India, China, and South Africa) for the period 1990–2010, using panel causality analysis, accounting for dependency and heterogeneity across countries. Regarding the electricity–GDP nexus, the empirical results support evidence on the feedback hypothesis for Russia and the conservation hypothesis for South Africa. However, a neutrality hypothesis holds for Brazil, India and China, indicating neither electricity consumption nor economic growth is sensitive to each other in these three countries. Regarding the GDP–CO₂ emissions nexus, a feedback hypothesis for Russia, a one-way Granger causality running from GDP to CO₂ emissions in South Africa and reverse relationship from CO₂ emissions to GDP in Brazil is found. There is no evidence of Granger causality between GDP and CO₂ emissions in India and China. Furthermore, electricity consumption is found to Granger cause CO₂ emissions in India, while there is no Granger causality between electricity consumption and CO₂ emissions in Brazil, Russia, China and South Africa. Therefore, the differing results for the BRICS countries imply that policies cannot be uniformly implemented as they will have different effects in each of the BRICS countries under study. - Highlights: • We examine the nexus of electricity, GDP growth and CO₂ emissions in BRICS. • We take into account cross-sectional dependency and heterogeneity across countries. • Electricity–GDP: Feedback for Russia and conservation for South Africa. • CO₂–GDP feedback for Russia, from GDP to CO₂ in SA, CO₂ to GDP in Brazil. • Only from electricity consumption to emissions for India

[en] Highlights: • Predictive ability of rare disaster risks for WTI oil market returns and volatility analysed. • A nonparametric quantile-based methodology over the monthly period of 1918:01-2013:12 is employed. • Rare disaster-risks strongly affect both WTI returns and volatility, with stronger evidence at lower quantiles. • Results are robust to alternative specification of volatility and measures of rare disaster risks. - Abstract: This paper provides a novel perspective to the predictive ability of rare disaster risks for West Texas Intermediate (WTI) oil market returns and volatility using a nonparametric quantile-based methodology over the monthly period of 1918:01–2013:12. We show that a nonlinear relationship and structural breaks exists between oil returns and various rare disaster risks; hence, linear Granger causality tests are misspecified and the linear model results of non-predictability are unreliable. However, the quantile-causality test shows that rare disaster-risks strongly affect both WTI returns and volatility, with stronger evidence of predictability observed at lower quantiles of the respective conditional distributions. Our results are robust to alternative specification of volatility (based on a GARCH model), and measure of rare disaster risks (based on the number of crises).