Reviewing studies of degrowth: Are claims matched by data, methods and policy analysis?
系统回顾了561篇去增长研究，发现近90%为观点而非分析，少数使用数据或模型，政策建议多为主观且缺乏评估，多数研究认为去增长策略在社会政治上不可行。
In the last decade many publications have appeared on degrowth as a strategy to confront environmental and social problems. We undertake a systematic review of their content, data and methods. This involves the use of computational linguistics to identify main topics investigated. Based on a sample of 561 studies we conclude that: (1) content covers 11 main topics; (2) the large majority (almost 90%) of studies are opinions rather than analysis; (3) few studies use quantitative or qualitative data, and even fewer ones use formal modelling; (4) the first and second type tend to include small samples or focus on non-representative cases; (5) most studies offer ad hoc and subjective policy advice, lacking policy evaluation and integration with insights from the literature on environmental/climate policies; (6) of the few studies on public support, a majority concludes that degrowth strategies and policies are socially-politically infeasible; (7) various studies represent a “reverse causality” confusion, i.e. use the term degrowth not for a deliberate strategy but to denote economic decline (in GDP terms) resulting from exogenous factors or public policies; (8) few studies adopt a system-wide perspective – instead most focus on small, local cases without a clear implication for the economy as a whole. We illustrate each of these findings for concrete studies. • We undertake a systematic review of degrowth studies. • This assesses the quality of content, data and methods. • The sample comprises 561 studies. • Computation linguistics identifies 11 main topics. • We draw eight main conclusions.