Erik Wang

30 papers receiving 447 citations

Erik Wang's Hit Papers

Matching Methods for Causal Inference with Time‐Series Cross‐Sectional Data 2021 · 165 citations
1650+1+3Years since publication50100150

Peers

Erik Wang
Comparison fields: 5 of 97
  • Pathology and Forensic Medicine 118
  • Development 17
  • Political Science and International Relations 95
  • Economics and Econometrics 109
  • Surgery 144
Replace Damiano Sandri with:
Damiano Sandri United States
Eli Segal Canada
Daniel Blake Spain
Nicole Ball United Kingdom
François Theron South Africa
Sanjeev Gupta United States
Joseph A. Ritter United States
Cai Fang China
Ankur Khandelwal India
Erik Wang relative to Damiano Sandri United States Damiano Sandri's profile →
Citations per field
00.5×6.5×
Damiano Sandri · 1×
Citations per year

Countries citing papers authored by Erik Wang

Since Specialization
Citations

This map shows the geographic impact of Erik Wang'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 Erik Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erik Wang more than expected).

Fields of papers citing papers by Erik Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Erik Wang. 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 Erik Wang. The network helps show where Erik Wang may publish in the future.

Co-authors

The 25 scholars most cited alongside Erik Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Erik Wang Line = papers co-authored together Erik Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Matching Methods for Causal Inference with Time‐Series Cross‐Sectional Data
Hit paper breakdown →
2021165
2 201745
3 202038
4 202037
5 202232
6 202019
7 201818
8 201914
9 201911
10 202111
11 20209
12 20197
13 20196
14 20196
15 19965
16 20204
17 20204
18 20243
19 20193
20 20153

About Erik Wang

Erik Wang is a scholar working on Surgery, Pathology and Forensic Medicine, Sociology and Political Science, Economics and Econometrics and Political Science and International Relations, having authored 32 papers that have together received 461 indexed citations. Recurring topics across this work include Spine and Intervertebral Disc Pathology (13 papers), Spinal Fractures and Fixation Techniques (9 papers), Scoliosis diagnosis and treatment (5 papers), Corruption and Economic Development (4 papers), China's Socioeconomic Reforms and Governance (4 papers), Fiscal Policy and Economic Growth (3 papers), Medical Imaging and Analysis (3 papers) and Historical Economic and Social Studies (3 papers). The work is most often cited by research in Pathology and Forensic Medicine (118 citations), Development (17 citations), Political Science and International Relations (95 citations), Economics and Econometrics (109 citations) and Surgery (144 citations). Erik Wang has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Kosuke Imai, In Song Kim, Aaron J. Buckland, Yiqing Xu, Dennis Vasquez-Montes, Christopher Varlotta, Themistocles S. Protopsaltis, Peter G. Passias, Haddy Alas and Avery Brown. Their work appears in journals such as The Spine Journal, The International Journal of Spine Surgery, American Journal of Political Science, Spine and Global Spine Journal.

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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