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 · Masyarakat dan Pembangunan Manusia
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 perlindungan sosial, education and humanitarian programmes and the effects of disasters and conflict on wellbeing.
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 pengurangan risiko measures actually work. It supports allocating resources toward interventions with demonstrated effect across connected risks. The canonical description is on STEM Commons.
Randomised or quasi-experimental designs compare households that received transfers with similar households that did not, measuring effects on consumption, schooling and wellbeing.
Panel surveys before and after disasters, with comparison areas, estimate effects on income, health and education and how long they last.
Learning programmes are evaluated with comparison groups and validated assessments to estimate effects on foundational skills.
Layar yang akan digunakan sebuah tim untuk mengikuti metode ini: ukuran, status, dan keputusannya. Nama adalah contoh dan nilai bersifat ilustratif.
Society and human development · Impact evaluation for human · Run R-0051
| Main specification | 0.28 | Ya |
| Drop early adopters | 0.05 | Ya |
| Synthetic control | 0.18 | Weaker |
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 register sumber.
| Data | Peran | Label |
|---|---|---|
| Programme administrative data | Treatment | Statistik terbitan |
| Panel household surveys | Outcomes over time | DILAPORKAN |
| Learning assessments | Pendidikan outcomes | TERAMATI |
Dua stok, tekanan dan kapasitas adaptif, dihubungkan oleh lingkar pertumbuhan yang saling menguatkan, respons penyeimbang yang tertunda, dan kerusakan ketika tekanan melampaui kapasitas; melewati ambang, sistem dapat berbalik. Model pengajaran dengan nilai ilustratif yang dinyatakan, bukan prediksi.
Kendali
Pembacaan
| Tahun | Tekanan | Kapasitas | Dirasakan |
|---|---|---|---|
| 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 |
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.
Di seluruh enam pilar, dipimpin oleh Nexus Consortium
Identification assumptions are probed through placebo tests, falsification checks and analisis sensitivitas. Replication across settings tests external validity.
| Pemeriksaan | Cara pelaksanaannya |
|---|---|
| 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.
Model, asumsi, data, dan ketidakpastiannya, dalam bentuk yang akan diperiksa ilmuwan atau insinyur. Strukturnya mengikuti metode yang dipublikasikan. Nilai yang digambar bersifat ilustratif, bukan temuan.
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.
Pembangunan Ekonomi stewards causal inference and impact evaluation for the Consortium and reviews how it is applied across platforms.
Laporan 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.
Jangan pernah mengirim data pribadi, rincian infrastruktur sensitif, atau apa pun yang tidak berhak Anda bagikan. Kontribusi ditinjau sebelum digunakan. Mengirimkannya tidak memberikan hak kepenulisan atau editorial, dan sponsor tidak pernah membeli sebuah temuan.
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