Pricing and Forecasting Carbon Markets
Models and Empirical Analyses
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Factors influencing the patent value in reverse innovation of develo** country under background of carbon neutrality
Global carbon neutrality needs to improve develo** countries’ innovation. Reverse innovation is not only a strategic action of innovation internationalization for enterprises in developed economies, but also...
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Forecasting carbon market volatility with big data
This paper proposes an ensemble forecasting model for carbon market volatility with structural factors and non-structural Baidu search index. Firstly, wavelet analysis is introduced into carbon price denoising...
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WT combined early warning model and applications for loaning platform customers default prediction in smart city
Due to the huge losses caused by the default of credit customers, the major loan platforms attach great importance to the testing and forecasting of non-performing loans. From the point of view of loan custome...
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Open AccessDoes hometown connection between chairmen and CEOs improve compensation–performance sensitivity in China?
Based on a the micro dataset set of private Chinese-listed companies, this study examines the in detail the impact of hometown connections between chief executive officers (CEOs) and chairmen on CEO compensati...
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Correction to: The estimation of influencing factors for carbon emissions based on EKC hypothesis and STIRPAT model: Evidence from top 10 countries
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On Market Power, Permit Banking Borrowing, and Interactions with the Firm’s Production Market
The carbon trading scheme has been recognized as a cost-saving and effective way to promote carbon emission abatement. This paper constructs an intertemporal carbon market model considering product market and ...
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The estimation of influencing factors for carbon emissions based on EKC hypothesis and STIRPAT model: Evidence from top 10 countries
Global climate change due to greenhouse gas emissions has observable impacts on environment. Among the GHG emissions, carbon dioxide is the primary source of global climate change. In order to provide appropri...
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Forecasting Inflection Points: Hybrid Methods with Multiscale Machine Learning Algorithms
This paper investigates hybrid time series forecasting models, which are based on combinations of ensemble empirical mode decomposition and least squares support vector machines. Several algorithms are conside...
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The role of service quality and perceived behavioral control in shared electric bicycle in China: Does residual effects of past behavior matters?
With the climate change problems being strongly emphasized by the international communities, sharing electric bicycle is promoted to reduce air pollution in China. However, the consumer attitude, intention, an...
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Behavioral intention of environmentally friendly agricultural food: the role of policy, perceived value, subjective norm
This study explores the determinants of intention and behavior towards environmentally friendly agricultural (EFA) food in China. We conduct the influencing factor model on behavioral intention and behavior to...
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Measuring the risk of European carbon market: an empirical mode decomposition-based value at risk approach
Unlike common financial markets, the European carbon market is a typically heterogeneous market, characterized by multiple timescales and affected by extreme events. The traditional Value-at-Risk (VaR) with si...
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Including intangible costs into the cost-of-illness approach: a method refinement illustrated based on the PM2.5 economic burden in China
The concentrations of particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) and 10 µm (PM10) is a widespread concern and has been demonstrated for 103 countries. During the past few years, the ex...
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Exploring the drivers of energy consumption-related CO2 emissions in China: a multiscale analysis
The exploration and modeling of the drivers of CO2 emissions can help make effective CO2 emission reduction policies. In this study, we examine the drivers of energy consumption-related CO2 emissions in China dur...
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Erratum to: Hilbert Spectra and Empirical Mode Decomposition: A Multiscale Event Analysis Method to Detect the Impact of Economic Crises on the European Carbon Market
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Hilbert Spectra and Empirical Mode Decomposition: A Multiscale Event Analysis Method to Detect the Impact of Economic Crises on the European Carbon Market
Exploring the effect of an economic crisis on the carbon market can be propitious to understand the formation mechanisms of carbon pricing, and prompt the healthy development of the carbon market. Through the ...
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Has foreign direct investment increased air pollution in China? A hierarchical linear model approach
Focusing on the mechanism of foreign direct investment on environment, we attempt to build a series of hierarchical linear models to explore the impact of foreign direct investment on China’s sulfur dioxide (SO2)...
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Electricity-savings pressure and electricity-savings potential among China’s inter-provincial manufacturing sectors
The Inter-Regional Input Output (IRIO) model is developed in 11 manufacturing sectors of China’s 30 provincial-level regions. Against the background of electricity pricing and energy-savings, this paper develo...
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Book
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Chapter
Forecasting Carbon Price with Empirical Mode Decomposition and Least Squares Support Vector Regression
This chapter contains another hybrid model of carbon price forecasting that combines empirical mode decomposition and least squares support vector regression. This multiscale prediction methodology yields accu...
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Chapter
New Perspectives on the Econometrics of Carbon Markets
This chapter provides an accessible introduction to this book. First, we detail the importance of pricing and forecasting carbon market. Second, we review the pricing and forecasting carbon market from the per...
