R. Palmer-jones

Economics and Econometrics · 2003–2012

A researcher in the Science corpus: 3 papers; trusts 27 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Economics and Econometrics — 86 citations into it; #17,012 of 23,481 by trust here, #16,755 by citations
• Statistics and Probability — 40 citations into it
• Safety Research — 29 citations into it; #3,741 of 5,829 by trust here, #3,824 by citations
• Soil Science — 17 citations into it
• Sociology and Political Science — 16 citations into it; #13,686 of 22,756 by trust here, #17,766 by citations
• Management Information Systems — 12 citations into it
• Urban Studies — 12 citations into it
• Causal Inference & Discovery — 10 citations into it

Whom R. Palmer-jones trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Marco Caliendo
2. Donald B. Rubin
3. M. Pitt
4. Sascha O. Becker
5. M. Ravallion
6. Shahidur R. Khandker
7. Edward E. Leamer
8. Shanhui Fan
9. P. Hazell
10. James J. Heckman

Who trusts R. Palmer-jones overall

1. A. Kotwal
2. Bharat Ramaswami
3. Maren Duvendack
4. M. Bateman
5. J. Copestake
6. Wilima Wadhwa
7. Ira N. Gang

Papers from R. Palmer-jones's perspective

Ordered by how strongly the researchers R. Palmer-jones trusts endorse each paper. Same corpus, a different order for every researcher.

1. The central role of the propensity score in observational studies for causal effects
2. Observational Studies
3. Evaluating the Econometric Evaluations of Training Programs with Experimental Data
4. Estimation of Average Treatment Effects Based on Propensity Scores
5. [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
6. Matched Sampling for Causal Effects: The Use of Matched Sampling and Regression Adjustment to Remove Bias in Observational Studies
7. Some Practical Guidance for the Implementation of Propensity Score Matching (Social Science Research Network)
8. Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities, Guide to Replication of Miguel and Kremer (2004)
9. Practical propensity score matching: a reply to Smith and Todd
10. The Design of Experiments

Their papers

• High Noon for Microfinance Impact Evaluations: Re-investigating the Evidence from Bangladesh (2012) — 141 citations
• What has luck got to do with it? A regional analysis of poverty and agricultural growth in rural India (2003) — 111 citations
• Systematic Review. What is the evidence of the impact of microfinance on the well-being of poor people? (2011) — 250 citations