The hidden semi-Markov model (HSMM) is more flexible than the hidden Markov model (HMM). As an extension of the HMM, the sojourn time distribution in the HSMM can be explicitly specified by any distribution, either nonparametric or parametric, facilitating the modelling for the stylised features of electricity prices, such as the short-lived spike and the time-varying mean. By using a three-regime HSMM, this paper investigates the hidden regimes in five Australian States (Queensland, New South Wales, Victoria, South Australia, and Tasmania), spanning the period from June 8, 2008 to July 3, 2016. Based on the estimation results, we find evidence that the three hidden regimes correspond to a low-price regime, a high-price regime, and a spike regime. Running the decoding algorithm, the analysis systemically finds the timing of the three regimes, and thus, we link the empirical results to the policy changes in the Australian National Electricity Market. We further discuss the contributing factors for the different characteristics of the Australian electricity markets at the state-level.

From an electricity market design perspective, it is relevant and practical to know which market structures allow for price convergence, and how long this takes to achieve. This study employs the Phillips and Sul (2007, 2009) methodology to test for the convergence of wholesale electricity prices across the Australian States. We identify a long-run, common price growth pattern that applies to a cluster formed by three Eastern States that share common market characteristics and limited physical interconnection. We also find another cluster with less competitive market structures that, although not interconnected, strongly converge towards their own trend. These findings confirm theoretical expectations while quantifying the rate of convergence. Finally, we also investigate the role that the carbon tax regime has played in the convergence process, with new empirical showing that the previous results are not affected, with the notable exception being the case of South Australia.

This study examines, for the first time in the energy issues literature, the long-run relationship between rare earth prices and the consumption of energy from renewables. The study applies standard time series econometric methodologies and monthly data in relevance to regional and income classification groups of countries, spanning the period 2004–2016. The empirical findings indicate the presence of a long-run relationship between these variables, but for certain rare earths and regions. The findings survive a multivariate robustness test, while they are expected to be of substantial importance for the world community, given that a few countries have control of those materials. The importance is lying on the need to establish a global green energy environment.

Efficient delivery of network services and the electricity infrastructure to meet the long-term consumer's interests are the main objectives and the strategies of a national electricity market, while the main interests of generators are to maximize their profit through pricing strategies. Therefore, the objective of this study is to explore whether electricity prices across the four Australian States display symmetric price volatility connectedness. The study is the first attempt in the literature to make use of intraday 5-min Australian dispatch electricity prices, spanning the period December 8th, 1998 to May 5th, 2016 to quantify asymmetries in volatility connectedness emerging from good, and bad volatility. The results provide supportive evidence that the Australian electricity markets are connected asymmetrically implying the presence of some degree of market power that is exercised by generators across regional electricity markets.

This study extends the literature on the convergence of per capita carbon dioxide emissions by examining the 50 U.S. states including the District of Columbia in the aggregate, by sector, and by fossil fuel source using the Phillips-Sul club convergence approach for the period 1980 to 2013. The results indicate multiple convergence clubs in the aggregate, by sector (residential, commercial, industrial, transport, and electric power), and for two of the three fossil fuel sources (natural gas and coal) with full panel club convergence in the case of petroleum. The presence of multiple equilibria suggests that environmental policies should recognize the distinctive convergence paths associated with each cluster of states.

There is a growing concern among both individuals and policy makers in relevance to increasing CO2 emissions across the world. As a result, international organizations have started to pressurize economies to minimize their carbon emissions by increasing the share of clean energy consumption in total energy use. Hence, the goal of this paper is to empirically explore to what extent both domestic (stock market) and foreign (FDI inflows) capital affect clean energy uses across the EU, the G20, and OECD, spanning the period 1993–2012. The results of long-run elasticities document that both FDI and stock market developments play a significant role in promoting clean energy uses across all three-country groups. The results also suggest that clean energy consumption has a considerable positive and negative effect on economic output and CO2 emissions, respectively, while the political globalization has a substantial negative impact on carbon emissions across the EU, the G20 and OECD economies.

This study examines the cointegration between city-gate and residential retail natural gas prices at the U.S. state level using monthly data from 1989:1 to 2012:12. Both price series are tested for unit roots using the Harris (2009) procedure to endogenously identify structural breaks related to deregulation associated with FERC Order No. 636. The endogenously determined structural breaks are then used in the Saikkonen and Lütkepohl (2000a, 2000b, 2000c) maximum likelihood approach to test cointegration of the series. Tests show cointegration of the two price series for all 50 states. Estimates of the long-run relationship in the pre- and post-structural break periods result in mixed evidence about the degree of perfect market integration induced by deregulation, although the magnitude and variation of parameters indicate increased integration. A vector error correction model is used to infer causality in the short and long-run dynamics for the pre and post-structural break periods for each state. The post-break period exhibits bidirectional causality in both short and long-run dynamics for all states, an indication of greater downstream integration of the natural gas market.

This study examines the determinants of renewable energy consumption per capita for a panel of seven Central American countries over the period 1980 to 2010. Specifically, we find that a long-run cointegrated relationship exists between renewable energy consumption per capita, real GDP per capita, carbon emissions per capita, real coal prices, and real oil prices with the respective coefficients positive and statistically significant. A structural break in the cointegrating relationship appears in 2002 which coincides with the establishment of the Energy and Environment Partnership with Central America initiative to expand the use of renewable energy sources. Recognizing the regime shift in 2002, we estimate a nonlinear panel smooth transition vector error correction model to show that for the post-2002 period, the influence of renewable energy consumption per capita upon real coal and oil prices strengthened relative to the pre-2002 period as well as a greater sensitivity of real GDP per capita to carbon emissions per capita.

This paper presents an efficiency assessment of selected OECD countries using a Slacks Based Model with undesirable or bad outputs (SBM-Undesirable). In this research, SBM-Undesirable is used first in a two-stage approach to assess the relative efficiency of OECD countries using the most frequent indicators adopted by the literature on energy efficiency. Besides, in the second stage, GLMM–MCMC methods are combined with SBM-Undesirable results as part of an attempt to produce a model for energy performance with effective predictive ability. The results reveal different impacts of contextual variables, such as economic blocks and capital–labor ratio, on energy efficiency levels.

This paper investigates the effect of oil rents on agriculture value added in oil producing Middle East and North African (MENA) countries. Annual data from 1970 to 2011, panel cointegration tests by Pedroni (1999), long ran panel causality tests by Canning and Pedroni (2008), and two-step System GMM by Blundell and Bond (1998) are used in this study. We find a negative relationship between oil rents and agriculture value added in the long run, with a rather slow rate of short run adjustment of agriculture value added back to equilibrium after a boom in oil rents. These results indicate that an oil sector boom is associated with a contraction in the agriculture sectors of the countries in the panel in the long run. This is probably attributable to a resource movement effect from other economic sectors to the booming oil sector in these countries. This serves as evidence of a Dutch disease effect of an oil sector boom on agriculture in the MENA countries in this study.