Azeem M. Shaikh

3.4k total citations · 1 hit paper
59 papers, 1.6k citations indexed

About

Azeem M. Shaikh is a scholar working on Statistics and Probability, Economics and Econometrics and Management Science and Operations Research. According to data from OpenAlex, Azeem M. Shaikh has authored 59 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Statistics and Probability, 14 papers in Economics and Econometrics and 9 papers in Management Science and Operations Research. Recurrent topics in Azeem M. Shaikh's work include Statistical Methods and Inference (30 papers), Statistical Methods in Clinical Trials (23 papers) and Statistical Methods and Bayesian Inference (21 papers). Azeem M. Shaikh is often cited by papers focused on Statistical Methods and Inference (30 papers), Statistical Methods in Clinical Trials (23 papers) and Statistical Methods and Bayesian Inference (21 papers). Azeem M. Shaikh collaborates with scholars based in United States, Switzerland and United Kingdom. Azeem M. Shaikh's co-authors include Joseph P. Romano, Ivan A. Canay, John A. List, Yang Xu, Edward Vytlacil, Michael Wolf, Andres Santos, Federico A. Bugni, Jay Bhattacharya and Andrés Santos and has published in prestigious journals such as Journal of the American Statistical Association, American Economic Review and Econometrica.

In The Last Decade

Azeem M. Shaikh

57 papers receiving 1.5k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Multiple hypothesis testing in experimental economics

2019 256 citations John A. List, Azeem M. Shaikh et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Azeem M. Shaikh	843	539	209	175	161	59	1.6k
Sokbae Lee	835 1.0×	712 1.3×	127 0.6×	161 0.9×	37 0.2×	64	1.6k
Andrew Chesher	798 0.9×	1.1k 2.0×	200 1.0×	233 1.3×	69 0.4×	67	2.2k
Francesca Molinari	276 0.3×	612 1.1×	140 0.7×	117 0.7×	67 0.4×	36	1.2k
Elie Tamer	966 1.1×	1.3k 2.3×	550 2.6×	187 1.1×	99 0.6×	44	2.5k
Rosa L. Matzkin	329 0.4×	973 1.8×	169 0.8×	89 0.5×	40 0.2×	34	1.4k
Michael Jansson	466 0.6×	710 1.3×	91 0.4×	148 0.8×	81 0.5×	43	1.6k
R. L. Basmann	265 0.3×	711 1.3×	132 0.6×	218 1.2×	88 0.5×	63	1.5k
Stéphane Bonhomme	244 0.3×	1.1k 1.9×	75 0.4×	196 1.1×	33 0.2×	48	1.5k
Marcelo J. Moreira	556 0.7×	631 1.2×	78 0.4×	227 1.3×	62 0.4×	25	1.6k
Chris D. Orme	170 0.2×	779 1.4×	227 1.1×	65 0.4×	239 1.5×	32	1.3k

Countries citing papers authored by Azeem M. Shaikh

Since Specialization

Citations

This map shows the geographic impact of Azeem M. Shaikh's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Azeem M. Shaikh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Azeem M. Shaikh more than expected).

Fields of papers citing papers by Azeem M. Shaikh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Azeem M. Shaikh. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Azeem M. Shaikh. The network helps show where Azeem M. Shaikh may publish in the future.

Co-authorship network of co-authors of Azeem M. Shaikh

This figure shows the co-authorship network connecting the top 25 collaborators of Azeem M. Shaikh. A scholar is included among the top collaborators of Azeem M. Shaikh based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Azeem M. Shaikh. Azeem M. Shaikh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Heckman, James J., Rodrigo Pinto, & Azeem M. Shaikh. (2024). Dealing with imperfect randomization: Inference for the highscope perry preschool program. Journal of Econometrics. 243(1-2). 105683–105683. 1 indexed citations

Bugni, Federico A., et al.. (2024). Inference for Cluster Randomized Experiments with Nonignorable Cluster Sizes. RePEc: Research Papers in Economics. 3(2). 255–288. 3 indexed citations

Shaikh, Azeem M., et al.. (2024). Inference in cluster randomized trials with matched pairs. Journal of Econometrics. 245(1-2). 105873–105873.

Romano, Joseph P., et al.. (2024). Covariate adjustment in experiments with matched pairs. Journal of Econometrics. 241(1). 105740–105740. 2 indexed citations

List, John A., et al.. (2023). Multiple testing with covariate adjustment in experimental economics. Journal of Applied Econometrics. 38(6). 920–939. 8 indexed citations

Romano, Joseph P., et al.. (2023). Covariate Adjustment in Experiments with Matched Pairs. SSRN Electronic Journal. 3 indexed citations

Canay, Ivan A., et al.. (2022). On the Implementation of Approximate Randomization Tests in Linear Models with a Small Number of Clusters. 12(1). 85–103. 4 indexed citations

Mogstad, Magne, Joseph P. Romano, Azeem M. Shaikh, & Daniel Wilhelm. (2021). Confidence Sets for Ranks with Applications to Intergenerational Mobility and Neighborhoods. UCL Discovery (University College London). 1 indexed citations

Bugni, Federico A., Ivan A. Canay, & Azeem M. Shaikh. (2019). Inference under Covariate-Adaptive Randomization with Multiple Treatments. SSRN Electronic Journal. 2 indexed citations

10.

Shaikh, Azeem M., et al.. (2018). Instrumental Variables and the Sign of the Average Treatment Effect. SSRN Electronic Journal. 3 indexed citations

11.

Canay, Ivan A., Joseph P. Romano, & Azeem M. Shaikh. (2017). Randomization Tests Under an Approximate Symmetry Assumption. Econometrica. 85(3). 1013–1030. 58 indexed citations

12.

Canay, Ivan A., Andrés Santos, & Azeem M. Shaikh. (2013). On the Testability of Identification in Some Nonparametric Models With Endogeneity. Econometrica. 81(6). 2535–2559. 60 indexed citations

13.

Lee, Soohyung & Azeem M. Shaikh. (2013). MULTIPLE TESTING AND HETEROGENEOUS TREATMENT EFFECTS: RE‐EVALUATING THE EFFECT OF PROGRESA ON SCHOOL ENROLLMENT. Journal of Applied Econometrics. 29(4). 612–626. 30 indexed citations

14.

Kitamura, Yuichi, Andres Santos, & Azeem M. Shaikh. (2012). On the Asymptotic Optimality of Empirical Likelihood for Testing Moment Restrictions. Econometrica. 80(1). 413–423. 18 indexed citations

15.

Romano, Joseph P., Azeem M. Shaikh, & Michael Wolf. (2011). Consonance and the Closure Method in Multiple Testing. The International Journal of Biostatistics. 7(1). 24 indexed citations

16.

Shaikh, Azeem M. & Edward Vytlacil. (2011). Partial Identification in Triangular Systems of Equations With Binary Dependent Variables. Econometrica. 79(3). 949–955. 62 indexed citations

17.

Romano, Joseph P., Azeem M. Shaikh, & Michael Wolf. (2009). Hypothesis Testing in Econometrics. SSRN Electronic Journal. 14 indexed citations

18.

Romano, Joseph P., Azeem M. Shaikh, & Michael Wolf. (2008). Control of the False Discovery Rate Under Dependence Using the Bootstrap and Subsampling. SSRN Electronic Journal. 13 indexed citations

19.

Shaikh, Azeem M. & Edward Vytlacil. (2007). Endogenous binary choice models with median restrictions: A comment. Economics Letters. 98(1). 23–28. 3 indexed citations

20.

Romano, Joseph P. & Azeem M. Shaikh. (2006). Step-up procedures for control of generalizations of the familywise error rate. 57 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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