Reinhard Hujer
Statistics and Probability · 2001–2008
A researcher in the Science corpus: 5 papers; trusts 21 researchers and is trusted by 17 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 54 citations into it; #2,889 of 12,932 by trust here, #2,965 by citations
- Economics and Econometrics — 35 citations into it; #4,365 of 23,481 by trust here, #6,470 by citations
- Causal Inference & Discovery — 11 citations into it
- Gender Studies — 8 citations into it; #2,183 of 4,924 by trust here, #2,594 by citations
- Sociology and Political Science — 6 citations into it
- Probabilistic & Bayesian Methods — 5 citations into it
Whom Reinhard Hujer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- M. Lechner
- Donald B. Rubin
- Guido W. Imbens
- Jeffrey A. Smith
- James J. Heckman
- Joshua D. Angrist
- Gerard J. van den Berg
- B. Sianesi
- Richard Blundell
- Paul R. Rosenbaum
Who trusts Reinhard Hujer overall
- Marco Caliendo
- Degnet Abebaw
- Jochen Kluve
- Victor Owusu
- Maren Duvendack
- Hans J. Baumgartner
- Awudu Abdulai
- Sascha O. Becker
- Mekbib G. Haile
- J. Fersterer
Papers from Reinhard Hujer's perspective
Ordered by how strongly the researchers Reinhard Hujer trusts endorse each paper. Same corpus, a different order for every researcher.
- Estimating causal effects of treatments in randomized and nonrandomized studies.
- Evaluating the Econometric Evaluations of Training Programs with Experimental Data
- The Role of the Propensity Score in Estimating Dose-Response Functions
- Making the Most out of Programme Evaluations and Social Experiments: Accounting for Heterogeneity in Programme Impacts
- Statistics and Causal Inference
- The central role of the propensity score in observational studies for causal effects
- Identification and Estimation of Local Average Treatment Effects
- Identification of Causal effects Using Instrumental Variables
- [On the Application of Probability Theory to Agricultural Experiments. Essay on Principles. Section 9.] Comment: Neyman (1923) and Causal Inference in Experiments and Observational Studies
- Problems with Instrumental Variables Estimation when the Correlation between the Instruments and the Endogenous Explanatory Variable is Weak
Their papers
- The Employment Effects of Job Creation Schemes in Germany: A Microeconometric Evaluation (2008) — 191 citations
- The microeconometric estimation of treatment effects—An overview (2006) — 161 citations
- New Evidence on the Effects of Job Creation Schemes in Germany - a Matching Approach with Threefold Heterogeneity (2004) — 174 citations
- Testing for uniform wage trends in West-Germany: A cohort analysis using quantile regressions for censored data (2001) — 117 citations
- The effects of vocational training programmes on the duration of unemployment in Eastern Germany (2004) — 126 citations