Impact evaluation: treatment effects and causal analysis
In recent years, interest in rigorous impact evaluation has grown tremendously in policy-making, economics, public health, social sciences and international relations. Evidence-based policy-making has become a recurring theme in public policy, alongside greater demands for accountability in public p...
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| Format: | E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2019
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| Links: | https://www.cambridge.org/core/product/identifier/9781107337008/type/BOOK |
| Zusammenfassung: | In recent years, interest in rigorous impact evaluation has grown tremendously in policy-making, economics, public health, social sciences and international relations. Evidence-based policy-making has become a recurring theme in public policy, alongside greater demands for accountability in public policies and public spending, and requests for independent and rigorous impact evaluations for policy evidence. Frölich and Sperlich offer a comprehensive and up-to-date approach to quantitative impact evaluation analysis, also known as causal inference or treatment effect analysis, illustrating the main approaches for identification and estimation: experimental studies, randomization inference and randomized control trials (RCTs), matching and propensity score matching and weighting, instrumental variable estimation, difference-in-differences, regression discontinuity designs, quantile treatment effects, and evaluation of dynamic treatments. The book is designed for economics graduate courses but can also serve as a manual for professionals in research institutes, governments, and international organizations, evaluating the impact of a wide range of public policies in health, environment |
| Umfang: | 1 Online-Ressource (xii, 417 Seiten) |
| ISBN: | 9781107337008 |
Internformat
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| spelling | Frölich, Markus Impact evaluation treatment effects and causal analysis Markus Frölich, Stefan Sperlich Cambridge Cambridge University Press 2019 1 Online-Ressource (xii, 417 Seiten) txt c cr In recent years, interest in rigorous impact evaluation has grown tremendously in policy-making, economics, public health, social sciences and international relations. Evidence-based policy-making has become a recurring theme in public policy, alongside greater demands for accountability in public policies and public spending, and requests for independent and rigorous impact evaluations for policy evidence. Frölich and Sperlich offer a comprehensive and up-to-date approach to quantitative impact evaluation analysis, also known as causal inference or treatment effect analysis, illustrating the main approaches for identification and estimation: experimental studies, randomization inference and randomized control trials (RCTs), matching and propensity score matching and weighting, instrumental variable estimation, difference-in-differences, regression discontinuity designs, quantile treatment effects, and evaluation of dynamic treatments. The book is designed for economics graduate courses but can also serve as a manual for professionals in research institutes, governments, and international organizations, evaluating the impact of a wide range of public policies in health, environment Sperlich, Stefan Erscheint auch als Druck-Ausgabe 9781107042469 Erscheint auch als Druck-Ausgabe 9781107616066 |
| spellingShingle | Frölich, Markus Impact evaluation treatment effects and causal analysis |
| title | Impact evaluation treatment effects and causal analysis |
| title_auth | Impact evaluation treatment effects and causal analysis |
| title_exact_search | Impact evaluation treatment effects and causal analysis |
| title_full | Impact evaluation treatment effects and causal analysis Markus Frölich, Stefan Sperlich |
| title_fullStr | Impact evaluation treatment effects and causal analysis Markus Frölich, Stefan Sperlich |
| title_full_unstemmed | Impact evaluation treatment effects and causal analysis Markus Frölich, Stefan Sperlich |
| title_short | Impact evaluation |
| title_sort | impact evaluation treatment effects and causal analysis |
| title_sub | treatment effects and causal analysis |
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