Songnian Chen

806 citations
49 papers · 541 indexed · h-index 13
Topics
Statistical Methods and Inference (36 papers)Spatial and Panel Data Analysis (18 papers)Statistical Methods and Bayesian Inference (13 papers)

In The Last Decade

Songnian Chen

45 papers receiving 511 citations

Peers

Songnian Chen
Comparison fields: 5 of 61
  • Statistics and Probability 333
  • Economics and Econometrics 226
  • General Economics, Econometrics and Finance 85
  • Management Science and Operations Research 46
  • Finance 38
Replace Federico A. Bugni with:
Federico A. Bugni United States
Alexander Torgovitsky United States
Stephen R. Cosslett United States
Kimio Morimune Japan
Toru Kitagawa United Kingdom
Yannis Bilias United States
Tiemen Woutersen United States
Christian Bontemps France
Anna Mikusheva United States
R. Carter Hill United States
Songnian Chen relative to Federico A. Bugni United States Federico A. Bugni's profile →
Citations per field
00.5×2.9×
Federico A. Bugni · 1×
Citations per year

Countries citing papers authored by Songnian Chen

Since Specialization
Citations

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

Fields of papers citing papers by Songnian Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Songnian Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Songnian Chen. A scholar is included among the top collaborators of Songnian Chen 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 Songnian Chen. Songnian Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 1
5 3
6 6
7 1
8 1
9 4
10 7
11 7
12 16
13
Estimation of a Nonparametric Censored Regression Model with an Application to Unemployment Insurance Spells
1
14 35
15 28
16 71
17
Estimation of a Nonparametric Censored Regression Model
1
18 28
19
Quantile Estimation of Non-Stationary Panel Data Censored Regression Models
1
20 12

About Songnian Chen

Songnian Chen is a scholar working on Statistics and Probability, General Economics, Econometrics and Finance and Economics and Econometrics, having authored 49 papers that have together received 541 indexed citations. Recurring topics across this work include Statistical Methods and Inference (36 papers), Spatial and Panel Data Analysis (18 papers) and Statistical Methods and Bayesian Inference (13 papers). The work is most often cited by research in Statistics and Probability (333 citations), General Economics, Econometrics and Finance (85 citations) and Economics and Econometrics (226 citations). Songnian Chen has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Shakeeb Khan, Yannis Bilias, Zhiliang Ying, Gordon B. Dahl, Qi Li, Lung‐fei Lee, Qian Wang, Qian Wang, Xi Wang and Qian Wang. Their work appears in journals such as Journal of the American Statistical Association, Econometrica and Journal of Econometrics.

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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