Socio-Economic and Attitudinal Diversity in Ex-ante Versus Ex-post Studies of Climate-Policy: A Systematic Literature Review
Foroogh Salekpay et al.
Abstract
We discuss two features of quantitative studies of climate policy that have not received much attention but could considerably affect insights: ex-ante versus ex-post approaches, and heterogeneity of socio-economic and attitudinal characteristics of individuals. The reason to combine them in one study is that the heterogeneous factors seem to differ considerably between ex-ante and ex-post approaches. This might translate in systematic differences in policy insights between the two types of studies. To clarify this issue, we undertake a systematic literature review comparing the studies in terms of topics and socio-economic and attitudinal characteristics covered. Our assessment uses both quantitative and qualitative analysis: the former provides an overview of topics across studies using computational linguistic analysis, while the latter offers detailed insights into heterogeneous characteristics and their relationship to study findings. We find that while many studies examine the impact of climate policy on equity, few studies examine the influence of considering heterogeneous individual characteristics on outcomes of evaluating alternative climate policies. Our assessment covers two policy issues, namely public support of climate policy and the impact of such policy on carbon emissions. We show that the two approaches differ systematically in both method use and the policy instruments studied. Overall, integrating both approaches yields a more nuanced understanding of climate policy. Future research, especially ex-ante studies, should examine a broader range of heterogeneous factors and their effects on policy effectiveness and public support.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.