Technological change and the rebound effect in the STIRPAT model: A critical view

By Johan-Andrés Vélez-Henao, David Font Vivanco, Jesús-Antonio Hernández-Riveros. Energy Policy, 2019

145 citations recorded by the source corpus.

Abstract Technological change is key to understand the explanatory variables behind environmental impacts in the context of the STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model. An adequate representation and analysis of the significance of the technology variable (T) in the STIRPAT model becomes crucial, even more if one aims to better understand underlying processes such as the (environmental) rebound effect (E)RE. A critical review of the application of the STIRPAT model has been conducted to understand the diversity and value of the variables, scopes, assumptions, statistical approaches, and the environmental impacts commonly studied. The findings highlight that, despite the multiple applications and the high potential of the STIRPAT model, inconclusive results and/or knowledge gaps remain, notably (1) a geographical imbalance in the scope of studies, (2) the almost exclusive focus on carbon emissions, (3) a lack of agreement on the choice of data, additional explanatory variables, and regression models, (4) a lack of consensus on how to approximate T, and (5) a lack of explicit analyses of the (E)RE. Our findings are useful to both policymakers and academics for method design, further research, and policy evaluation.

Subfields: Automotive Engineering, Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/bc67f1e72717a9bda813994026eb5dbf923e1776

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Tanaya Saha
2. Tuhin Sengupta
3. Avik Sinha

In Economics and Econometrics

1. Avik Sinha
2. Tuhin Sengupta
3. Tanaya Saha
4. Muhammad Shahbaz
5. Arshian Sharif
6. Umer Shahzad
7. Syed Abdul Rehman Khan
8. Olimpia Neagu

In Renewable Energy, Sustainability and the Environment

1. Tuhin Sengupta
2. Avik Sinha
3. Tanaya Saha
4. Muhammad Shahbaz

Citations in the corpus

• Technology policy and environmental quality at crossroads: Designing SDG policies for select Asia Pacific countries (2020, methodology): “The 3 estimation schema is designed depending on the available literature on the EKC hypothesis and 4 IPAT modeling (Paramati et al., 2017; Vélez-Henao et al., 2019; Sinha and Sengupta, 2019).”