Evaluating cash transfers
Randomised or quasi-experimental designs compare households that received transfers with similar households that did not, measuring effects on consumption, schooling and wellbeing.
GCRI · 社会与人类发展
人类发展影响评估
Causal inference and impact evaluation estimate whether programmes and shocks changed people’s lives, compared with what would otherwise have happened. In this field they evaluate 社会保护, education and humanitarian programmes and the effects of disasters and conflict on wellbeing.
02申请
What causal inference and impact evaluation does here.
Causal inference and impact evaluation develop methods to determine whether and how interventions or exposures cause outcomes. They separate genuine effects from correlation. In society and human development and information and public trust, causal inference shows which 风险 measures actually work. It supports allocating resources toward interventions with demonstrated effect across connected risks. The canonical description is on STEM Commons.
Effects of disasters on households
Panel surveys before and after disasters, with comparison areas, estimate effects on income, health and education and how long they last.
Education programme evaluation
Learning programmes are evaluated with comparison groups and validated assessments to estimate effects on foundational skills.
03监测
Impact evaluation.
团队遵循该方法时会使用的界面：其指标、状态与决策。名称为示例，数值仅作示意。
影响评估
Society and human development · Impact evaluation for human · Run R-0051
Parallel trends holdGCRI · 社会与人类发展
Event study
方法卡
- 方法
- 因果推断与影响评估
- 设计
- difference in differences
- 单位
- 63
- 标签
- 模型生成
Robustness checks
| Main specification | 0.28 | 是 |
| Drop early adopters | 0.05 | 是 |
| Synthetic control | 0.18 | Weaker |
04数据
该方法使用的输入。
Datasets and records used by causal inference and impact evaluation on this platform, with the role each plays and the label its values carry. Sources are listed in 来源登记册.
| 数据 | 角色 | 标签 |
|---|---|---|
| Programme administrative data | Treatment | 已发布统计 |
| Panel household surveys | Outcomes over time | 已报告 |
| Learning assessments | 教育 outcomes | 观测 |
05模拟器
存量、流量、延迟和一个临界阈值。
两个存量，即压力和 适应能力，由一个增强的增长回路、一个延迟的平衡响应以及压力超过能力时产生的损害相连；越过阈值后，系统可能发生突变。这是使用明示示例数值的教学模型，不是预测。
控制措施
- 压力增长
- 每年 6.0%
- 能力在降低压力方面的效力
- 每年 4.0%
- 对感知压力的投资响应
- 20%
- 感知延迟
- 4.0 年
- 压力的临界阈值
- 60 项指数
- 越过阈值后的放大
- 2.0 倍
- 模拟年数
- 50 年
读数
- 峰值压力
- 113 指数
- 期末能力
- 186 指数
- 超过阈值的年数
- 15.8 年
数字、方法与来源
| 年份 | 压力 | 能力 | 感知 |
|---|---|---|---|
| 0 | 20.0 | 50.0 | 20.0 |
| 4 | 23.3 | 44.9 | 21.2 |
| 8 | 27.2 | 42.2 | 24.0 |
| 12 | 31.7 | 42.3 | 27.7 |
| 16 | 36.8 | 45.5 | 32.2 |
| 20 | 42.3 | 51.5 | 37.2 |
| 24 | 47.9 | 60.3 | 42.6 |
| 28 | 53.2 | 71.3 | 48.0 |
| 32 | 57.8 | 84.3 | 53.1 |
| 36 | 66.4 | 98.4 | 58.4 |
| 40 | 82.7 | 115.9 | 69.7 |
| 44 | 97.8 | 139.7 | 83.8 |
| 48 | 109.1 | 169.4 | 97.3 |
方法
- 系统动力学 Forrester (1961), Industrial Dynamics, MIT Press; Sterman (2000), Business Dynamics
- 临界转变与临界点 Scheffer and others (2009), Early-warning signals for critical transitions, Nature 461
- 因果回路图 Sterman (2000), Business Dynamics, McGraw-Hill
- 不确定性扇形图（参数蒙特卡罗） Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- 单因素敏感性（龙卷风图） Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
数据
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.
贯穿六大支柱，由 Nexus Consortium 牵头
- 实验 实验室
- 构建于 Foundry 中的社会与人类发展
- 检验地点 Universe 中的社会与人类发展
- 编入 Standards 中的治理、安全与社会
- 发表于 Reports 中的社会与人类发展
- 授课于 Academy 中的健康与社会学院
06验证
结果如何核查。
Identification assumptions are probed through placebo tests, falsification checks and 敏感性分析. Replication across settings tests external validity.
| 核查 | 如何开展 |
|---|---|
| Pre-registration | Evaluation designs and analyses are registered before results |
| Balance and attrition checks | Groups are compared at baseline and attrition is analysed |
| Heterogeneity analysis | Effects are examined by gender, age and other groups |
Unobserved confounding and spillovers can bias estimates. Effects found in one context may not transfer to another.
07方法与证据
How impact evaluation for human development is modelled, measured and tested.
模型、其假设、数据和不确定性，以科学家或工程师会核查的形式呈现。结构遵循已发表的方法。所取数值仅为示意，不是研究发现。
系统模型
The couplings between the systems in impact evaluation for human development: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
FAIR 指导原则 · GO FAIR 和 FORCE11W3C PROV · 万维网联盟关于一致处理不确定性的指南 · IPCCCEOS 分析就绪数据 · 地球观测卫星委员会
09管理责任
由谁维护该方法。
经济发展 stewards causal inference and impact evaluation for the Consortium and reviews how it is applied across platforms.
10已关联
本页在整个联合体中通向何处。
11问题
问题与解答。
What are the limits of causal inference and impact evaluation in this field?
Unobserved confounding and spillovers can bias estimates. Effects found in one context may not transfer to another.
结果如何核查？
Identification assumptions are probed through placebo tests, falsification checks and sensitivity analysis. Replication across settings tests external validity.
本页面上的数值是真实的吗？
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
该方法还应用于何处？
维持社会运转的 规范方法页面 列出应用该方法的每个平台。
报告贡献
从本页贡献证据。
报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
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法律
法律文件。
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