Related Experiment Video
Updated: Aug 15, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
The Combined Effect of Environmental Policies on China's Renewable Energy Development: A Multi-Perspective Study
Xiaolei Yang1, Shuiying Zhong1
1Economics and Management School, Wuhan University, Wuhan 430072, China.
Abstract:
Based on a sample of 92 listed renewable energy enterprises in China from 2007-2017, this paper empirically examines the nonlinear effect of environmental policies on renewable energy investments using a semiparametric regression model. Environmental policies are divided into three groups in terms of pre-control, in-process governance, and post-accounting-the groups being green supervision and public regulations, green standardized regulations, and green accounting regulations-and this paper explores the differences in the effects of environmental policies at different stages. The results indicate that the relationship between environmental policies and renewable energy development has been unstable, following a "W-shaped" pattern. Green supervision and public regulations can greatly enhance investments in the renewable energy industry, with an estimated coefficient of 10.8173. Green standardized regulations have a similar "W-shaped" impact on renewable energy development. However, the nonlinear impact of green accounting regulations on renewable energy development fails the significance test. In addition, the effect of environmental policies on investment in the solar energy industry is positive, with a coefficient of 1.0697. The positive effect of environmental policies on investments in the renewable energy industry is reflected mainly in medium-, small-, and micro-sized enterprises. These findings contribute to the literature on the effectiveness of environmental policies by putting a set of environmental policies into a unified framework to explore their combined effects.
Related Concept Videos
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Background and Environment Affect Phenotype
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
Global Regulatory Systems
Regression Toward the Mean
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...

