波特假设今天比30年前更相关吗? 图书统计和内容分析
Lenart Milan Lah1, Žiga Kotnik1
1Chair of Economics and Public Sector Management, University of Ljubljana, Faculty of Public Administration, SI-1000, Ljubljana, Slovenia.
Journal of environmental management
|February 28, 2026
概括
波特假设 (PH) 认为环境法规可以促进创新和生产力. 这一综述表明,关于PH的研究已经增长,最近的研究支持其弱势和有条件的强势版本,特别是具有灵活的法规.
科学领域:
- 环境经济学环境经济学
- 创新研究 研究 创新研究
- 政策分析 政策分析
背景情况:
- 波特假设 (PH) 认为,严格的环境法规可以激励创新,提高生产力.
- 尽管它有超过三十年的相关性,但缺乏对PH研究演变的全面,最新的概述.
研究的目的:
- 在波特假设文献中,系统地审查和分析研究主题,方法和经验重点的演变.
- 确定当前的趋势,知识差距,并为未来的研究和环境政策制定提供见解.
主要方法:
- 对800篇PH相关文章 (1991-2024) 的图书统计分析,比较早期 (1991-2013) 和后期 (2014-2024) 的时间段.
- 对15项最具影响力的研究进行定性内容分析,以评估对PH版本的经验支持.
主要成果:
- 在过去的十年中,出版活动,方法的复杂性和政策相关性显著增加,中国的增长显著.
- 强有力的支持弱小的PH和有条件的支持强大的PH,特别是在灵活的,基于市场的监管制度下.
- 转向使用先进的计量经济学和绿色指标 (例如,绿色创新,绿色总因子生产力) 的经验基础研究.
结论:
- 智能,情境敏感的监管框架,整合基于市场的工具和创新激励措施,对于将环境保护与经济绩效相协调至关重要.
- 未来的研究应该专注于细微的经验研究和综合政策方法的开发.
- 该研究为学者和政策制定者提供了基础参考,以推进波特假说的理论和应用.
相关概念视频
01:08Outliers and Influential Points
6.5K
An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
6.5K
01:11Statistical Analysis: Overview
16.7K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
16.7K
02:46Chi-square Analysis
44.4K
The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
44.4K
01:11Regression Analysis
8.7K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
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:
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:
8.7K
01:17Hypothesis: Accept or Fail to Reject?
29.7K
The outcome of any hypothesis testing leads to rejecting or not rejecting the null hypothesis. This decision is taken based on the analysis of the data, an appropriate test statistic, an appropriate confidence level, the critical values, and P-values. However, when the evidence suggests that the null hypothesis cannot be rejected, is it right to say, 'Accept' the null hypothesis?
There are two ways to indicate that the null hypothesis is not rejected. 'Accept' the null...
There are two ways to indicate that the null hypothesis is not rejected. 'Accept' the null...
29.7K
01:16Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
544
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
544