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We provide a comprehensive analysis of the relationship between greenhouse gas (GHG) emissions and GDP in China using both aggregate and provincial data. The Kuznets elasticity is about 0.6 for China, higher than that in advanced countries but below that of major emerging markets. The elasticity is somewhat lower for consumption-based emissions than for production-based emissions, providing mild evidence consistent with the “pollution haven” hypothesis. The Kuznets elasticity is much lower for the last three decades than for the three previous decades, suggesting a longer-term trend toward decoupling as China has become richer. Further evidence of this comes from provincial data: richer provinces tend to have smaller Kuznets elasticities than poorer ones. In addition to the trend relationship, we find that the Environmental Okun's Law holds in China.

A model of global oil production is applied to study cartelization by OPEC countries. Writing out the shadow price on quota allocations so as to draw correspondence to coefficients of cooperation (Cyert et al. 1973), we examine the incentives that different OPEC members to collude. We find that heterogeneity in OPEC and the supplies of the non-OPEC fringe create strong incentives against OPEC cooperation. OPEC’s optimal supply strategy although observed to be substantially more restrictive than that of a Cournot-Nash oligopoly, is found to still be more accommodative than that of a perfect cartel. The strategy involves allocating larger than proportionate quotas to smaller and relatively costlier producers as if to bribe their participation in the cartel. This is contrary to predictions of the standard cartel model that such producers should be allocated relatively more stringent quotas. Furthermore, we find that cartel collusion is likely to be sustained for elastic than inelastic demand. Since global oil demand is well known to be inelastic, this observation provides another structural explanation for why OPEC behavior is inconsistent with that of a perfect cartel. Our study points to multiple headwinds that limit OPECs ability to raise long-run global oil prices.

Abstract In this study, a novel multiscale nonlinear ensemble leaning paradigm incorporating empirical mode decomposition (EMD) and least square support vector machine (LSSVM) with kernel function prototype is proposed for carbon price forecasting. The EMD algorithm is used to decompose the carbon price into simple intrinsic mode functions (IMFs) and one residue, which are identified as the components of high frequency, low frequency and trend by using the Lempel-Ziv complexity algorithm. The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to forecast the high frequency IMFs with ARCH effects. The LSSVM model with kernel function prototype is employed to forecast the high frequency IMFs without ARCH effects, the low frequency and trend components. The forecasting values of all the components are aggregated into the ones of original carbon price by the LSSVM with kernel function prototype-based nonlinear ensemble approach. Furthermore, particle swarm optimization is used for model selections of the LSSVM with kernel function prototype. Taking the popular prediction methods as benchmarks, the empirical analysis demonstrates that the proposed model can achieve higher level and directional predictions and higher robustness. The findings show that the proposed model seems an advanced approach for predicting the high nonstationary, nonlinear and irregular carbon price.

Relying on real options theory, we employ a multistage decision model to analyze the effect of delaying the introduction of emission trading systems (ETS) on power plant investments in carbon capture and storage (CCS) retrofits, on plant operation, and on carbon dioxide (CO2) abatement. Unlike previous studies, we assume that the investment decision is made before the ETS is in place, and we allow CCS operating flexibility for new power plant investments. Thus, the plant may be run in CCS-off mode if carbon prices are low. We employ Monte Carlo simulation methods to account for uncertainties in the prices of CO2 certificates, other inputs, and output prices, relying on a realistic parameterization for a supercritical pulverized coal plant in China. We find that CCS operating flexibility lowers the critical carbon price needed to support CCS investment because it renders CCS investment less irreversible. For a low carbon price path, operating flexibility also implies that delaying the introduction of an ETS hardly affects plant CO2 abatement since the plant operator is better off purchasing emission certificates rather than operating the plant in CCS mode. Interestingly, for low carbon prices we find a U-shaped relation between the length of the delay and the economic value of the plant. Thus, delaying the introduction of an ETS may make investors worse off.

Abstract A heated debate has arisen over whether the Asian premium (i.e., higher prices in Asia than elsewhere) in natural gas trade is due to price discrimination or different market fundamentals. Determining the origin of this premium can help to guide the gas industries and policy makers in Asia, especially when the traditional oil-indexed price mechanism fades away. Using a new systemic time-series approach, this paper explores the extent to which oil prices and market fundamentals contribute to variations in gas prices in Japan, the United States, and Germany. We find clear cross-country differences and time-varying patterns. Gas prices are much less affected by supply and demand factors than oil prices in Japan and Germany, whereas these factors are more important than oil prices in the US market, which has a pricing hub. Through rolling-windows and subsample analysis, we discover that oil prices were important in Japan and Germany, but the level of importance has declined significantly in recent years, though the contribution of fundamentals does not change much. The results show that Asian gas prices are determined more by oil prices than by the market fundamentals; thus the Asian premium is more likely due to this oil indexed pricing mechanism, rather than market fundamentals. This suggests that developing Asia's benchmark prices (through trading hubs) with a better reflection of regional specific fundamentals can lead to a more efficient allocation of gas resources.

Abstract The Global Financial Crisis (GFC) of 2007–2009 that originated in the US has revealed the need for measuring and monitoring the transmission of extreme downside market risk. This paper investigates the risk transmission mechanism between the oil and natural gas markets. We apply the recently introduced test statistics based on cross-quantilogram function and the multivariate quantile regression model (VAR for VaR) to the US oil and natural gas prices, which are independently formed. Our results show two asymmetric patterns. First, the shocks in the oil market substantially increase the Value at Risk (VaR) in the natural gas market, but the reverse impact does not exist. Second, we highlight the significant asymmetric response of gains and losses transmission in energy markets, cautioning about the underlying weakness of adopting volatility to measure risk in the energy market. Moreover, an extreme market risk is more easily transmitted across markets than moderate risks. Our results are in general robust in application to other regional energy markets, such as Europe and Asia, but the heterogeneities in responses are underpinned by the different role of natural gas in regions. The findings in this paper have important implications for academic researchers, policy makers in gas-dependent economies, and business practitioners in light of projected increases in the use of natural gas worldwide as well as the development of independent gas-on-gas competitive (hub) prices in Asia and Europe.