Serena Ng: h-index, Total Citations, and Citation Map
Serena Ng's h-index is 59 (99 i10-index, 42,640+ total citations across 184+ publications) according to Google Scholar as of July 2026. Serena Ng is affiliated with Columbia University.
Serena Ng is a researcher affiliated with Columbia University, specializing in various fields. Their work has been cited 42,640 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Serena Ng's Citation Metrics
Bibliometric impact based on 184 indexed publications.
- H-Index
- 59
- i10-Index
- 99
- Total Citations
- 42,640
- Citing Countries
- 36
As of July 2026.
Serena Ng has an h-index of 59 and 42,640 total citations across 184 publications, with research cited by institutions in 36 countries.
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Global Impact Map
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Determining the number of factors in approximate factor models
20026,231
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
2 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher advanced empirical asset pricing by analyzing risk-return relations via factor analysis and extending this framework to examine uncertainty's role in business cycles.
The researcher established a foundational methodology for determining the number of factors in approximate factor models, a seminal contribution that has become a standard reference in econometrics.
The researcher developed robust methodologies for lag length selection and unit root testing, significantly improving statistical size and power in time series analysis.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Serena Ng's research
Serena Ng is a researcher at Columbia University. Their work has been cited 42,640 times across 184 publications (h-index 59), according to Google Scholar.
Their most-cited work, “Determining the number of factors in approximate factor models” (2002), has accumulated 6,231 citations. Other influential works include “Lag length selection and the construction of unit root tests with good size and power” (2001) with 5,629 citations and “Measuring uncertainty” (2015) with 4,454 citations.
Citations of Serena Ng's research come primarily from China, United States and Spain, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
