Demystifying Causal Inference : Public Policy Applications with R

by Vikram Dayal, Anand Murugesan

John Snow and causal inference -- RStudio and R -- Regression and simulation -- Potential outcomes -- Causal graphs -- Experiments -- Matching -- Instrumental Variables -- Regression Discontinuity Design -- Panel Data and fixed effects -- Difference-in-Differences -- Integrating and generalizing causal estimates.

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Year of publication:	2023
Authors:	Dayal, Vikram ; Murugesan, Anand
Publisher:	2023.: Singapore : Springer Nature Singapore 2023.: Singapore : Imprint: Springer
Subject:	Causal inference \| R \| Simulation \| Regression \| Regression Discontinuity \| Panel Data \| Public policy \| impact evaluation \| Causal graphs \| Experiments \| Matching \| Difference in Difference \| Instrumental variables \| Kausalanalyse \| Causality analysis \| Regressionsanalyse \| Regression analysis \| Induktive Statistik \| Statistical inference \| Wirkungsanalyse \| Impact assessment \| Theorie \| Theory \| Panel \| Panel study \| IV-Schätzung

Extent:	1 Online-Ressource (XV, 294 p. 125 illus., 85 illus. in color.)
Type of publication:	Book / Working Paper
Language:	English
ISBN:	978-981-99-3905-3 ; 978-981-99-3904-6 ; 978-981-99-3906-0 ; 978-981-99-3907-7
Other identifiers:	10.1007/978-981-99-3905-3 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014375030