Ping Wang

Economics and Econometrics · Energy Economics · 2013–2021

A researcher in the Science corpus: 9 papers; trusts 4 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Economics and Econometrics — 86 citations into it; #11,734 of 23,481 by trust here, #2,748 by citations
• Global and Planetary Change — 12 citations into it

Whom Ping Wang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Lean Yu

Who trusts Ping Wang overall

1. Yang Zhou
2. Yan-sui Liu
3. Wenjing Zhang
4. Shaojian Wang
5. Wenxiang Wu
6. Hengzhou Xu

Papers from Ping Wang's perspective

Ordered by how strongly the researchers Ping Wang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Carbon price volatility: Evidence from EU ETS
2. Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model
3. A hybrid ARIMA and support vector machines model in stock price forecasting
4. CO2 Prices, Energy and Weather
5. European Emission Trading Scheme and competitiveness: A case study on the iron and steel industry
6. Modeling the Price Dynamics of Co2 Emission Allowances
7. Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm
8. Generalized autoregressive conditional heteroskedasticity
9. The relationship between crude oil spot and futures prices: cointegration, linear and nonlinear causality
10. Price determination in the EU ETS market: Theory and econometric analysis with market fundamentals

Their papers

• Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China (2013) — 528 citations
• Carbon Price Analysis Using Empirical Mode Decomposition (2015) — 135 citations
• Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression (2017) — 276 citations
• Achieving the carbon intensity target of China: A least squares support vector machine with mixture kernel function approach (2019) — 113 citations
• Assessing global energy poverty: An integrated approach (2021) — 157 citations
• Exploring the effect of carbon trading mechanism on China's green development efficiency: A novel integrated approach (2020) — 197 citations
• A multiscale analysis for carbon price drivers (2019) — 173 citations
• Measuring the maturity of carbon market in China: An entropy-based TOPSIS approach (2019) — 196 citations
• On the road to China's 2020 carbon intensity target from the perspective of “double control” (2018) — 47 citations