Abstract The STIRPAT approach identifies human impacts on the environment. Most studies find higher ecological elasticities related to population compared to GDP per capita growth. Applying the logarithmic form of the STIRPAT equation, which mitigates the problem of the variables' different variances and units, further allows for appealing economic interpretation and policy conclusions. At the same time, the question of the predictor variables' relative importance cannot be finally answered by this approach. In response, the present paper complements the traditional ecological elasticities by the calculation of standardized β-coefficients (for a sample of 84 countries and the period between 1980 and 2014). Results indicate that GDP per capita rather than population growth matters more for explaining environmental impacts. Admittedly, interpretation of standardized coefficients is not without limitations. First, they are sample-specific and cannot be compared across different studies. Second, a predictor variable might not affect the environment only on its own, but joint impacts could be present. The paper addresses these problems and provides a careful interpretation of and comparison between non-standardized and standardized β-coefficients. Overall, there is good reason to assume that environmental impacts can be reduced more readily by a policy giving priority to economic rather than population growth.

中文翻译：

---

人口和经济驱动因素在传统和标准化 STIRPAT 分析中对环境的作用

摘要 STIRPAT 方法识别人类对环境的影响。大多数研究发现，与人均 GDP 增长相比，与人口相关的生态弹性更高。应用 STIRPAT 方程的对数形式，减轻了变量不同方差和单位的问题，进一步允许有吸引力的经济解释和政策结论。同时，这种方法无法最终回答预测变量相对重要性的问题。作为回应，本文通过计算标准化 β 系数（针对 84 个国家和 1980 年至 2014 年期间的样本）来补充传统的生态弹性。结果表明，人均 GDP 而非人口增长对于解释环境影响更重要。诚然，对标准化系数的解释并非没有限制。首先，它们是特定于样本的，不能在不同的研究中进行比较。其次，预测变量可能不会仅凭自身影响环境，但可能存在联合影响。本文解决了这些问题，并对非标准化和标准化 β 系数进行了仔细的解释和比较。总体而言，有充分的理由假设，通过优先考虑经济增长而非人口增长的政策，可以更容易地减少环境影响。本文解决了这些问题，并对非标准化和标准化 β 系数进行了仔细的解释和比较。总体而言，有充分的理由假设，通过优先考虑经济增长而非人口增长的政策，可以更容易地减少环境影响。本文解决了这些问题，并对非标准化和标准化 β 系数进行了仔细的解释和比较。总体而言，有充分的理由假设，通过优先考虑经济增长而非人口增长的政策，可以更容易地减少环境影响。