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Whether environmental governance will cause unemployment has always been an aspect that the government needs to pay attention to in the process of making environmental policies, and is also a concern of residents. This paper analyzes the policy effect of environmental courts, which is a very important policy tool for the legalization of China’s environmental governance. While investigating whether environmental courts can effectively improve environmental quality, we also analyze its possible impact on employment and the specific mechanisms. The results show that: (1) After the establishment of environmental courts, the PM2.5 concentration has been significantly reduced. (2) While improving the environmental quality, environmental courts will produce a weak employment promotion effect. (3) Environmental courts affect the amount of employment through cost effect, factor substitution effect and innovation effect. This study provides empirical evidence for China and other developing countries to promote the legalization of environmental governance.
Ling-Yun He; Xiao-Feng Qi. Environmental Courts, Environment and Employment: Evidence from China. Sustainability 2021, 13, 6248 .
AMA StyleLing-Yun He, Xiao-Feng Qi. Environmental Courts, Environment and Employment: Evidence from China. Sustainability. 2021; 13 (11):6248.
Chicago/Turabian StyleLing-Yun He; Xiao-Feng Qi. 2021. "Environmental Courts, Environment and Employment: Evidence from China." Sustainability 13, no. 11: 6248.
Developing countries face the conflict between economic development and environmental protection. Resource misallocation will not only affect the effectiveness of economic development, but also have environmental impacts. Based on two large-scale enterprise databases in China, this paper measured the level of enterprise resource allocation, and further used empirical research methods to investigate the environmental impact of enterprise resource misallocation and specific mechanisms. The results show that the low efficiency of resource allocation will harm the quality of China’s environment. Further investigation, resource misallocation is accompanied by an increase in total energy input, a decrease in the labor-to-energy ratio and the capital-to-energy ratio, and a loss of energy efficiency, which in turn affects the environmental performance of enterprises. China is the largest developing country in the world, and research on China’s environmental and economic issues is important. The conclusions of this paper can provide experience and suggestions for other developing countries to improve environmental quality and promote sustainable development from the perspective of resource misallocation.
Ling-Yun He; Xiao-Feng Qi. Resource Misallocation and Energy-Related Pollution. International Journal of Environmental Research and Public Health 2021, 18, 5158 .
AMA StyleLing-Yun He, Xiao-Feng Qi. Resource Misallocation and Energy-Related Pollution. International Journal of Environmental Research and Public Health. 2021; 18 (10):5158.
Chicago/Turabian StyleLing-Yun He; Xiao-Feng Qi. 2021. "Resource Misallocation and Energy-Related Pollution." International Journal of Environmental Research and Public Health 18, no. 10: 5158.
In China, green credit aims to guide the flow of credit funds by regulating the quantity and price of credit, so as to support the development of green industries and curb the emission behavior of polluting enterprises. Based on the behavior of microeconomic entities we construct a Dynamic Stochastic Genernal Equilibrium (DSGE) model to analyze the output and welfare effect of green credit in China. Specifically, the incentive green credit is taken as an example to carry out an empirical study, and we further quantitatively measure the output and welfare effect of green credit under different environmental regulations. We find that both price-based and quantity-based green credit have obvious output, environment, health and utility welfare effect, which is conducive to the green upgrading of industrial structure and can achieve a win-win situation of output and environment in China. However, there are some differences in transmission mechanism and utility welfare. In addition, in the short term, the environmental tax regulation inhibits the economic expansion effect of green credit, and in the long term, this inhibitory effect gradually disappears. The DSGE comprehensive evaluation framework constructed in this paper expands the application scope of DSGE model, and provides a quantitative theoretical model for the mechanism analysis of China’s green credit policy and similar policies. Furthermore this study provides theoretical and quantitative basis for the formulation of green credit policies and the improvement of macro-control policies in China.
Li Liu; Ling-Yun He. Output and welfare effect of green credit in China: Evidence from an estimated DSGE model. Journal of Cleaner Production 2021, 294, 126326 .
AMA StyleLi Liu, Ling-Yun He. Output and welfare effect of green credit in China: Evidence from an estimated DSGE model. Journal of Cleaner Production. 2021; 294 ():126326.
Chicago/Turabian StyleLi Liu; Ling-Yun He. 2021. "Output and welfare effect of green credit in China: Evidence from an estimated DSGE model." Journal of Cleaner Production 294, no. : 126326.
Poverty alleviation, environmental protection, and healthcare are the three biggest challenges for the Sustainable Development Goals. However, they are also inter-linked. Therefore, it is imperative to achieve these goals in a compatible manner at the national level. Given the growing consumption caused by poverty alleviation in China, this paper investigates potential impacts of poverty alleviation on the environment and health based on an input–output approach, air quality estimation model, and health loss assessment. Due to data limitations, the base year was set as 2012. Nevertheless, the scientific value of the paper is that it offers an important supplement for a preliminary estimation on a macro level. We find that poverty alleviation could be a substantial threat to the environment and health from a consumption-based perspective, and this trade-off can be explained by the uneven pollution footprints per capita among different income groups. From a policy perspective, the government should promote green production, green lifestyles, and healthcare when reducing poverty.
Su-Mei Chen; Jia-Jia Ou; Ling-Yun He. The Environmental and Health Impacts of Poverty Alleviation in China: From a Consumption-Based Perspective. Sustainability 2021, 13, 1784 .
AMA StyleSu-Mei Chen, Jia-Jia Ou, Ling-Yun He. The Environmental and Health Impacts of Poverty Alleviation in China: From a Consumption-Based Perspective. Sustainability. 2021; 13 (4):1784.
Chicago/Turabian StyleSu-Mei Chen; Jia-Jia Ou; Ling-Yun He. 2021. "The Environmental and Health Impacts of Poverty Alleviation in China: From a Consumption-Based Perspective." Sustainability 13, no. 4: 1784.
Not only the fundamentals of supply and demand but also international oil prices are affected by nonfundamental indicators such as emergencies. With the development of big data technology, many unstructured and semistructured factors can be reflected through Internet information. Based on this, this paper proposes a HD-based oil price forecasting model to explore the impact of Internet information on international oil prices. Firstly, we use LDA and other methods to extract topics from massive online news. Secondly, based on conditional probability and correlation, the positive hot degree (PHD) and negative hot degree (NHD) of the oil market are constructed to realize the quantitative representation of Internet information. Finally, the SVAR method is established to explore the interactive relationship between HD and oil prices. The empirical results indicate that PHD and NHD have a better ability to predict international oil prices compared with Google Trends which is widely used in the other research. In addition, PHD has a significant positive impact on oil prices and NHD has a negative impact. In the long term, PHD accounts for 51.00% of oil price fluctuations, ranking the first among relevant influencing factors. The findings of this paper can provide support to investors and policy-makers.
Lu-Tao Zhao; Shi-Qiu Guo; Jing Miao; Ling-Yun He. How Does Internet Information Affect Oil Price Fluctuations? Evidence from the Hot Degree of Market. Discrete Dynamics in Nature and Society 2020, 2020, 1 -18.
AMA StyleLu-Tao Zhao, Shi-Qiu Guo, Jing Miao, Ling-Yun He. How Does Internet Information Affect Oil Price Fluctuations? Evidence from the Hot Degree of Market. Discrete Dynamics in Nature and Society. 2020; 2020 ():1-18.
Chicago/Turabian StyleLu-Tao Zhao; Shi-Qiu Guo; Jing Miao; Ling-Yun He. 2020. "How Does Internet Information Affect Oil Price Fluctuations? Evidence from the Hot Degree of Market." Discrete Dynamics in Nature and Society 2020, no. : 1-18.
Existing researches about environment regulation mainly focus on its effect on enterprises’ production decision-making behavior but neglects the effect on the individual and household behavior. Based on the micro survey data from the Chinese General Social Survey 2010 and corresponding city-level macroeconomic data, this paper investigates the effect of environmental regulations on residents’ willingness to pay (WTP) for protecting the environment. We find that environmental regulation has a significantly positive effect on residents’ WTP, especially where residents are at higher income levels, pollution levels, and government trust levels. The heterogeneous test shows that boosting the government’s credibility in environmental governance has become the key to improve the environmental preferences of the entire society. Finally, we show that reducing the expected cost and expected benefit of environmental protection is the main channel through which environmental regulation affected the residents’ WTP.
Ling-Yun He; Hong-Zhen Zhang. Spillover or crowding out? The effects of environmental regulation on residents’ willingness to pay for environmental protection. Natural Hazards 2020, 105, 611 -630.
AMA StyleLing-Yun He, Hong-Zhen Zhang. Spillover or crowding out? The effects of environmental regulation on residents’ willingness to pay for environmental protection. Natural Hazards. 2020; 105 (1):611-630.
Chicago/Turabian StyleLing-Yun He; Hong-Zhen Zhang. 2020. "Spillover or crowding out? The effects of environmental regulation on residents’ willingness to pay for environmental protection." Natural Hazards 105, no. 1: 611-630.
Environmental pollution is one of the major sustainability problems in China. As a major institutional innovation to supervise local governments to implement environmental governance measures, the effect of central environmental protection inspection needs to be carefully investigated. In this paper, the environmental protection inspection in July 2016 was used as a quasi-natural experiment to estimate the effect of central environmental protection inspection on air quality by using the synthetic control method. The study found that not all regions under inspection have significantly reduced the Air Quality Index (AQI). For the four inspected regions, the AQI decreased in Inner Mongolia Autonomous Region and Jiangsu Province during the period of inspection. But the inspection does not affect Henan Province and Jiangxi Province. In terms of individual pollutants, for Inner Mongolia Autonomous Region and Jiangsu Province where AQI has declined, not all individual pollutant concentrations have decreased. The treatment of specific individual pollutants still needs to be concerned.
Ling-Yun He; Meng-Meng Geng. Can Chinese Central Government Inspection on Environmental Protection Improve Air Quality? Atmosphere 2020, 11, 1025 .
AMA StyleLing-Yun He, Meng-Meng Geng. Can Chinese Central Government Inspection on Environmental Protection Improve Air Quality? Atmosphere. 2020; 11 (10):1025.
Chicago/Turabian StyleLing-Yun He; Meng-Meng Geng. 2020. "Can Chinese Central Government Inspection on Environmental Protection Improve Air Quality?" Atmosphere 11, no. 10: 1025.
Although processing export accounts for a great proportion of Chinese exports, Chinese processing trade is always different from the traditional trade in many aspects. Under the background of Chinese energy problems becoming energy problems of the world, it is critically significant to analyze Chinese energy efficiency performance from the perspective of processing export. Our research examines how firms’ processing export behaviors affect their energy efficiency. Our results illustrate that energy efficiency performance of China’s processing exporters is worse than that of non-processing exporters. Besides, there is an obvious inverse U-shaped relationship between processing export intensities and energy efficiency. When enterprises engage in processing exports, the promotional effects on energy efficiency are constantly improving when processing export intensity is low. However, when firm’s processing export intensity is high, the promotional effects of processing export activities on energy efficiency decline rapidly. Our results also suggest that the increased levels of participation in processing exports can promote firms’ energy efficiency through innovation effect when processing export intensity is low, while the increased participation in processing exports will decrease energy efficiency through cost reduction effect when firms’ processing export intensity is high. This research is the first attempt to examine the impacts of firms’ processing export activities on their energy use performance and provides significant policy advisories on transformation of China’s trade mode.
Ling-Yun He; Geng Huang. Processing trade and energy efficiency: Evidence from Chinese manufacturing firms. Journal of Cleaner Production 2020, 276, 122507 .
AMA StyleLing-Yun He, Geng Huang. Processing trade and energy efficiency: Evidence from Chinese manufacturing firms. Journal of Cleaner Production. 2020; 276 ():122507.
Chicago/Turabian StyleLing-Yun He; Geng Huang. 2020. "Processing trade and energy efficiency: Evidence from Chinese manufacturing firms." Journal of Cleaner Production 276, no. : 122507.
Correspondence to Ling-Yun He. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Reprints and Permissions He, L., Wu, H. Macroeconomic Dynamics and Modelling on Chinese Economy. Comput Econ (2020). https://doi.org/10.1007/s10614-020-09992-2 Download citation Published: 08 May 2020 DOI: https://doi.org/10.1007/s10614-020-09992-2
Ling-Yun He; Hua-Qing Wu. Macroeconomic Dynamics and Modelling on Chinese Economy. Computational Economics 2020, 55, 1045 -1046.
AMA StyleLing-Yun He, Hua-Qing Wu. Macroeconomic Dynamics and Modelling on Chinese Economy. Computational Economics. 2020; 55 (4):1045-1046.
Chicago/Turabian StyleLing-Yun He; Hua-Qing Wu. 2020. "Macroeconomic Dynamics and Modelling on Chinese Economy." Computational Economics 55, no. 4: 1045-1046.
In the context of anti-globalization and trade wars (especially between the US and China), China-ASEAN Free Trade Area (CAFTA) now plays a prominent role in many aspects. In this paper, we investigate how import tariff reduction in CAFTA affects the importers’ pollution emissions, using the firm-level data of Chinese manufacturing from 2002 to 2007. The mechanisms of import tariff reduction in CAFTA on pollution emissions are divided into technique, composition and scale effects. Our results indicate that import tariff reduction in CAFTA on final goods is conductive to importers’ pollution reduction, whereas that on intermediates significantly aggravates importers’ pollution emissions. Moreover, import tariff reduction has heterogeneous impacts on different types of enterprises in terms of industries, ownership, and region. Our results also find that the state-owned importers’ emissions can hardly be affected through technique, composition and scale effects.
Ling-Yun He; Geng Huang. Tariff Reduction and Environment: Evidence from CAFTA and Chinese Manufacturing Firms. Sustainability 2020, 12, 2017 .
AMA StyleLing-Yun He, Geng Huang. Tariff Reduction and Environment: Evidence from CAFTA and Chinese Manufacturing Firms. Sustainability. 2020; 12 (5):2017.
Chicago/Turabian StyleLing-Yun He; Geng Huang. 2020. "Tariff Reduction and Environment: Evidence from CAFTA and Chinese Manufacturing Firms." Sustainability 12, no. 5: 2017.
With the continuous advancement of economic interaction and vertical specialization in world economics, the importance of processing exports is catching up with ordinary exports. Although environmental consequences of export have been discussed from macro and micro perspectives, the effect of distinct exports, especially processing exports, on the environment at the plant level receives scant attention and remains unclear. To explore the firm-level environmental differences between processing exports and ordinary exports, in this paper we investigate how pollution emitted by individual establishments reacts to distinct export status by employing a panel of plant-level data from China manufacturing sector for the years 2006 and 2007. Our estimates indicate that exporters obtain both economic and environmental advantages over non-exporters, and processing exports generate fewer emissions than non-processing exports. For exporters, the beneficial effect of the decline in pollution intensity driven by the adoption of clean technology outweighs the negative effect of production expansion. Compared to non-processing exporters, processing ones have lower pollution intensity due to the inclination of abatement investments and the inclined inflows of FDI that bring advanced abatement technology to processing trade sectors.
Ling-Yun He; Liang Wang. Distinct exporters and the environment: Empirical evidence from China manufacturing. Journal of Cleaner Production 2020, 258, 120614 .
AMA StyleLing-Yun He, Liang Wang. Distinct exporters and the environment: Empirical evidence from China manufacturing. Journal of Cleaner Production. 2020; 258 ():120614.
Chicago/Turabian StyleLing-Yun He; Liang Wang. 2020. "Distinct exporters and the environment: Empirical evidence from China manufacturing." Journal of Cleaner Production 258, no. : 120614.
Given the importance of crude oil prices in the world economy, accurate price prediction has drawn extensive attention. Nevertheless, because of the complexity of the crude oil market, most traditional forecasting algorithms fail to meet the accuracy requirements. To achieve higher precision, this paper proposes a novel hybrid model for crude oil price forecasting by combining a Hodrick-Prescott filter with X12 methods and adjusting the order used. Application of our model on both West Texas Intermediate and Brent oil prices forecasting demonstrates its accuracy. The results of various forecasting performance evaluation criteria indicate that the model has stronger stability and better accuracy. The mechanism of seasonal and periodic factors is also analyzed, which provides remarkable references to other time-series predictions. Establishing two different types of predictive models that combine multiple knowledge effectively has obvious advantages over other models and provides more reliable cutting-edge information for designing a Chinese energy development strategy.
Lu-Tao Zhao; Zi-Jie Wang; Shu-Ping Wang; Ling-Yun He. Predicting Oil Prices: An Analysis of Oil Price Volatility Cycle and Financial Markets. Emerging Markets Finance and Trade 2019, 57, 1068 -1087.
AMA StyleLu-Tao Zhao, Zi-Jie Wang, Shu-Ping Wang, Ling-Yun He. Predicting Oil Prices: An Analysis of Oil Price Volatility Cycle and Financial Markets. Emerging Markets Finance and Trade. 2019; 57 (4):1068-1087.
Chicago/Turabian StyleLu-Tao Zhao; Zi-Jie Wang; Shu-Ping Wang; Ling-Yun He. 2019. "Predicting Oil Prices: An Analysis of Oil Price Volatility Cycle and Financial Markets." Emerging Markets Finance and Trade 57, no. 4: 1068-1087.
To achieve green development, the Chinese government has taken a number of steps to reduce pollution. Several provinces of China thereby are implementing pilot pollution emission trading schemes. However, problems remain before establishing a nationwide pollution emission trading system, i.e., at what price do polluters acquire another emission allowance in the stage of initial quota allocation. In this context, shadow prices of emissions could provide the policymakers important information for the allowance prices. Besides, environmental protection policies often result in the reduction of several pollutants simultaneously. Thus, considering the provincial and sectoral significant differences in China, this paper employs a nonparametric output distance function approach including multiple undesirable outputs to estimate shadow prices of SO2 and NOx at national level, provincial level and sectoral level. Our results suggest that multiple pollutants should be taken into account and shadow prices should be set differently at national, provincial and sectoral levels.
Jia-Jia Ou; Ling-Yun He. The Price of Pollution? A Distance Function Approach to Valuing Multiple Pollutants in China. Emerging Markets Finance and Trade 2019, 57, 1050 -1067.
AMA StyleJia-Jia Ou, Ling-Yun He. The Price of Pollution? A Distance Function Approach to Valuing Multiple Pollutants in China. Emerging Markets Finance and Trade. 2019; 57 (4):1050-1067.
Chicago/Turabian StyleJia-Jia Ou; Ling-Yun He. 2019. "The Price of Pollution? A Distance Function Approach to Valuing Multiple Pollutants in China." Emerging Markets Finance and Trade 57, no. 4: 1050-1067.
The rapid fluctuations in global crude oil prices are one of the important factors affecting both the sustainable development and the green transformation of the global economy. To accurately measure the risks of crude oil prices, in the context of big data, this study introduces the two-layer non-negative matrix factorization model, a kind of natural language processing, to extract the dynamic risk factors from online news and assign them as weighted factors to historical data. Finally, this study proposes a giant information history simulation (GIHS) method which is used to forecast the value-at-risk (VaR) of crude oil. In conclusion, this paper shows that considering the impact of dynamic risk factors from online news on the VaR can improve the accuracy of crude oil VaR measurement, providing an effective tool for analyzing crude oil price risks in oil market, providing risk management support for international oil market investors, and providing the country with a sense of risk analysis to achieve sustainable and green transformation.
Lu-Tao Zhao; Li-Na Liu; Zi-Jie Wang; Ling-Yun He. Forecasting Oil Price Volatility in the Era of Big Data: A Text Mining for VaR Approach. Sustainability 2019, 11, 3892 .
AMA StyleLu-Tao Zhao, Li-Na Liu, Zi-Jie Wang, Ling-Yun He. Forecasting Oil Price Volatility in the Era of Big Data: A Text Mining for VaR Approach. Sustainability. 2019; 11 (14):3892.
Chicago/Turabian StyleLu-Tao Zhao; Li-Na Liu; Zi-Jie Wang; Ling-Yun He. 2019. "Forecasting Oil Price Volatility in the Era of Big Data: A Text Mining for VaR Approach." Sustainability 11, no. 14: 3892.
This paper explores the popularity of internet finance and its potential shocks to the business of traditional commercial banking in China. Using data on 200 commercial banks in China during the period 2011 to 2016, this paper investigates whether internet finance, measured by P2P (peer-to-peer lending) lending and third-party payment, has a negative impact on the profitability of commercial banks. It concludes that P2P lending and third-party payment has significant negative influence on the profitability of loans and deposits at China’s commercial banks. By intensifying competition, the development of internet finance has decreased the interest income of loans, increased the interest cost of deposits, lowered the growth rate of loans and deposit, and brought about more risk. City and rural banks and unlisted banks are more vulnerable to internet finance than large government-owned and joint-stock banks.
Zhongfei Chen; Kexin Li; Ling-Yun He. Has Internet Finance Decreased the Profitability of Commercial Banks?: Evidence from China. Emerging Markets Finance and Trade 2019, 56, 3015 -3032.
AMA StyleZhongfei Chen, Kexin Li, Ling-Yun He. Has Internet Finance Decreased the Profitability of Commercial Banks?: Evidence from China. Emerging Markets Finance and Trade. 2019; 56 (13):3015-3032.
Chicago/Turabian StyleZhongfei Chen; Kexin Li; Ling-Yun He. 2019. "Has Internet Finance Decreased the Profitability of Commercial Banks?: Evidence from China." Emerging Markets Finance and Trade 56, no. 13: 3015-3032.
China’s economic development has entered a period of transformation. Does trade liberalization reshape transitional China? In this study, from the perspectives of heterogeneous exporters and firm-level pollution emissions, we employ the data of 372,861 samples from China’s manufacturing to empirically investigate the impacts of trade liberalization on China’s economic transformation. Our results indicate that both import and export liberalization significantly change the behaviors of Chinese exporters, and aggravates pollution emissions. The underlying mechanisms include scale, factor composition and technique effects by trade liberalization. In addition, trade liberalization has heterogeneous impacts on different types of firms, which refers to ownership reforms, manufacturing sector upgrades and regional-coordinated development that are the part of China’s economic transformation. Altogether, our findings provide important evidences on the impacts of trade liberalization on China’s economic transformation and firm-level pollution emissions.
Ling-Yun He; Xi Lin; Qiren Liu. How Did Free Trade Reshape the Transitional China? Evidence from Heterogeneous Exporters and Firm-Level Pollution Emissions. Emerging Markets Finance and Trade 2019, 56, 1651 -1676.
AMA StyleLing-Yun He, Xi Lin, Qiren Liu. How Did Free Trade Reshape the Transitional China? Evidence from Heterogeneous Exporters and Firm-Level Pollution Emissions. Emerging Markets Finance and Trade. 2019; 56 (8):1651-1676.
Chicago/Turabian StyleLing-Yun He; Xi Lin; Qiren Liu. 2019. "How Did Free Trade Reshape the Transitional China? Evidence from Heterogeneous Exporters and Firm-Level Pollution Emissions." Emerging Markets Finance and Trade 56, no. 8: 1651-1676.
This paper investigates how the import liberalization of intermediates affects firm-level pollution emissions. We divide the impact of freer import of intermediates on pollution emissions into induced scale, composition and technique effects and then develop interaction terms to examine these effects. Relying on a panel of plant-level data from China manufacturing sector for the period 2001 to 2007, we find freer import of intermediate inputs is conducive to pollution reductions at the plant level, lowering pollution via induced technique and composition effects and, in turn, increasing emission through induced scale effect. In summary, import liberalization of intermediate inputs can contribute to the better environmental performance of China manufacturing sector.
Ling-Yun He; Liang Wang. Import Liberalization of Intermediates and Environment: Empirical Evidence from Chinese Manufacturing. Sustainability 2019, 11, 2579 .
AMA StyleLing-Yun He, Liang Wang. Import Liberalization of Intermediates and Environment: Empirical Evidence from Chinese Manufacturing. Sustainability. 2019; 11 (9):2579.
Chicago/Turabian StyleLing-Yun He; Liang Wang. 2019. "Import Liberalization of Intermediates and Environment: Empirical Evidence from Chinese Manufacturing." Sustainability 11, no. 9: 2579.
This study proposes a decomposition-ensemble based carbon price forecasting model, which integrates ensemble empirical mode decomposition (EEMD) with local polynomial prediction (LPP). The EEMD method is used to decompose carbon price time series into several components, including some intrinsic mode functions (IMFs) and one residue. Motivated by the fully local characteristics of a time series decomposed by EEMD, we adopt the traditional LPP and regularized LPP (RLPP) to forecast each component. This led to two forecasting models, called the EEMD-LPP and EEMD-RLPP, respectively. Based on the fine-to-coarse reconstruction principle, an auto regressive integrated moving average (ARIMA) approach is used to forecast the high frequency IMFs, and LPP and RLPP is applied to forecast the low frequency IMFs and the residue. The study also proposes two other forecasting models, called the EEMD-ARIMA-LPP and EEMD-ARIMA-RLPP. The empirical study results showed that the EEMD-LPP and EEMD-ARIMA-LPP outperform the two other models. Furthermore, we examine the robustness and effects of parameter settings in the proposed model. Compared with existing state-of-art approaches, the results demonstrate that EEMD-ARIMA-LPP and EEMD-LPP can achieve higher level and directional predictions and higher robustness. The EEMD-LPP and EEMD-ARIMA-LPP are promising approaches for carbon price forecasting.
Quande Qin; Huangda He; Li Li; Ling-Yun He. A Novel Decomposition-Ensemble Based Carbon Price Forecasting Model Integrated with Local Polynomial Prediction. Computational Economics 2018, 55, 1249 -1273.
AMA StyleQuande Qin, Huangda He, Li Li, Ling-Yun He. A Novel Decomposition-Ensemble Based Carbon Price Forecasting Model Integrated with Local Polynomial Prediction. Computational Economics. 2018; 55 (4):1249-1273.
Chicago/Turabian StyleQuande Qin; Huangda He; Li Li; Ling-Yun He. 2018. "A Novel Decomposition-Ensemble Based Carbon Price Forecasting Model Integrated with Local Polynomial Prediction." Computational Economics 55, no. 4: 1249-1273.
GARCH-type models are frequently used to forecast crude oil price volatility, and whether we should consider multiple regimes for the GARCH-type models is of great significance for the forecasting work but does not have a final conclusion yet. To that end, this paper estimates and forecasts crude oil price volatility using three single-regime GARCH (i.e., GARCH, GJR-GARCH and EGARCH) and two regime-switching GARCH (i.e., MMGARCH and MRS-GARCH) models. Furthermore, the Model Confidence Set (MCS) procedure is employed to evaluate the forecasting performance. The in-sample results show that the MRS-GARCH model provides higher estimation accuracy in weekly data. However, the out-of-sample results show the limited significance of considering the regime switching. Overall, our results indicate that the incorporation of regime switching does not perform significantly better than the single-regime GARCH models. The findings are proved to be robust to both daily and weekly data for WTI and Brent over different time horizons.
Yue-Jun Zhang; Ting Yao; Ling-Yun He; Ronald Ripple. Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models? International Review of Economics & Finance 2018, 59, 302 -317.
AMA StyleYue-Jun Zhang, Ting Yao, Ling-Yun He, Ronald Ripple. Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models? International Review of Economics & Finance. 2018; 59 ():302-317.
Chicago/Turabian StyleYue-Jun Zhang; Ting Yao; Ling-Yun He; Ronald Ripple. 2018. "Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models?" International Review of Economics & Finance 59, no. : 302-317.
Price is an important guideline for measuring the changes in the oil market. Therefore, the forecasting of oil prices has become an important issue in oil market research. One of the problems, however, is that oil price is a non-linear or chaotic time-series, leading to difficulties in such research. In the forecasting methods commonly used, pattern matching model is a good method because of its simplicity, non-linearity, and accuracy, but when calculating its important input parameters, pattern matching model encounters certain problems in terms of accuracy and stability. In this case, the accuracy of the model prediction results will be affected. In this paper, the loss function is used to detect the source of the complexity of oil price forecast. On the basis of generalised pattern matching model based on genetic algorithm (GPGA), we introduce empirical distribution into genetic algorithm, which can dynamically compare the fitness among populations and tracks changes in individual evolutionary fitness to improve multiple modules. By using these information, directional evolution and full search elements are ensured. Finally, a generalised pattern matching model based on empirical genetic algorithm (GPEGA) is proposed. Empirical studies show that the accuracy and stability of GPEGA are 59.0% and 0.8% higher than that of GPGA. Moreover, the performance is 71.2% and 72.2% better than that of BPNN and ARIMA on mean square error. This study can help decision makers quickly and accurately grasp market information and provide support and reference for decision making on stabilizing economic markets and people’s lives.
Lu-Tao Zhao; Guan-Rong Zeng; Ling-Yun He; Ya Meng. Forecasting Short-Term Oil Price with a Generalised Pattern Matching Model Based on Empirical Genetic Algorithm. Computational Economics 2018, 55, 1151 -1169.
AMA StyleLu-Tao Zhao, Guan-Rong Zeng, Ling-Yun He, Ya Meng. Forecasting Short-Term Oil Price with a Generalised Pattern Matching Model Based on Empirical Genetic Algorithm. Computational Economics. 2018; 55 (4):1151-1169.
Chicago/Turabian StyleLu-Tao Zhao; Guan-Rong Zeng; Ling-Yun He; Ya Meng. 2018. "Forecasting Short-Term Oil Price with a Generalised Pattern Matching Model Based on Empirical Genetic Algorithm." Computational Economics 55, no. 4: 1151-1169.