The recent fall in oil prices has led to extensive capital rationing, and thereby given rise to a renewed focus on parameters for project selection which supplement net present value. While the financial crisis was creating capital constraints, the oil industry seemed to be paying great...

Oil and gas company returns are compared between upstream, midstream, and down-stream sectors from 2000 through 2020. Crude oil, natural gas, and distillate returns reflect project risk, infrastructure, and conditions within the industry. Equity, commodity, and distillate markets positively...

This paper investigates the impact of oil price variations on sectoral inflation for a sample of 10 top oil importing and exporting countries. Specifically, we analyze the effects of oil prices on the consumer price index using monthly data spanning the July 2009 to February 2021 period. Two...

Revealing the precise thresholds at which fluctuations in oil prices start to affect gross domestic product and its various components (consumption, investment, expenditure and exports) holds significant implications for policymakers in both oil-importing and oil-exporting countries. Existing...

After a boom and bust cycle in the early 2010s, venture capital (VC) investments are, once again, flowing towards green businesses. In this paper, we use Crunchbase data on 150,000 US startups founded between 2000 and 2020 to better understand why VC initially did not prove successful in funding...

The recent dramatic fall in oil prices has led to extensive capital rationing in international oil companies, and subsequent fierce competition between resource extraction countries to attract scarce investment. This situation is not adequately addressed by the large literature on international...

Regression model error assumptions are essential to estimator properties. Least squares model parameters are consistent and efficient when the underlying error terms are normally distributed but yield inefficient estimators when errors are not normally distributed. Partially adaptive and...

We analyse the drivers of European Power Exchange (EPEX) retail electricity prices between 2012 and early 2022 using machine learning. The agnostic random forest approach that we use is able to reduce in-sample root mean square errors (RMSEs) by around 50% when compared to a standard linear...

This paper is an innovative attempt to empirically investigate the determinants of crude oil prices. The main objective is to distinguish between short- and long-term effects of some covariates on oil prices. The autoregressive distributed lag (ARDL) approach is applied to daily series spanning...

This paper investigates the co-movements of oil prices and the exchange rates of 10 top oil-importing and oil-exporting countries. Firstly, we estimated the total static spillover index based on vector autoregressive (VAR) models. Secondly, we adopted the recent DCC-GARCH-CONNECTEDNESS approach...