Mastering 'Metrics: The Path from Cause to Effect
By Isa Steinmann. 2015
470 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Management Science and Operations Research, Soil Science
View Paper: https://www.semanticscholar.org/paper/95f5ff1c868bb539f8d4bff4196664abcc5c6a86
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- M. D. Cattaneo
- Alberto Abadie
- Christian Leuz
- Peter D. Wysocki
- F. Curran
- R. Shanmugam
- Guido W. Imbens
- Pedro H. C. Sant’Anna
In Management Science and Operations Research
- M. D. Cattaneo
- Christian Leuz
- Peter D. Wysocki
- F. Curran
- Alberto Abadie
- R. Shanmugam
- R. Titiunik
- Max H. Farrell
In Soil Science
Citations in the corpus
- Econometric Methods for Program Evaluation (2018, background): “…of causal treatment effects and the econometrics of program evaluation from different perspectives and disciplines include Abadie (2005a), Angrist and Pischke (2008, 2014), Athey and Imbens (2017c), Blundell and Costa Dias (2009), DiNardo and Lee (2011), Heckman and Vytlacil (2007),…”
- Estimating the Effect of State Zero Tolerance Laws on Exclusionary Discipline, Racial Discipline Gaps, and Student Behavior (2016, methodology): “To account for this threat to the validity of the study, I followed the suggestion of Angrist and Pischke (2015) by rerunning the primary models predicting suspension rates while including statespecific time trends.”
- Causal inference (2011, methodology): “Angrist and Pischke [2] is one of the few recent sources in the economics literature that discusses causation in structural models explicitly and clearly (although, in our view, not correctly).”
- The Economics of Disclosure and Financial Reporting Regulation: Evidence and Suggestions for Future Research (2015, background): “…for researchers to improve and tighten their research designs and to embrace 10 new econometric methods of estimating treatment effects (e.g., Angrist and Pischke, 2009, 2014), the main limitation is how the underlying data are generated, i.e., the institutional settings themselves and the…”
- Spatial Regression Models: A Systematic Comparison of Different Model Specifications Using Monte Carlo Experiments (2019, unknown): “To identify the (spatial) causal effects between two variables of interest, it is necessary to use designs or methods following the counterfactual approach like natural experiments (Angrist and Pischke 2009, 2015; Morgan and Winship 2015).”