Jin Seo Cho
- Economics and Econometrics top 2%
- General Economics, Econometrics and Finance top 5%
- Finance top 5%
- Renewable Energy, Sustainability and the Environment top 10%
- Statistics and Probability top 5%
- Co-authors
- Yongcheol ShinTae‐Hwan KimHalbert WhitePeter C.B. PhillipsChirok HanMatthew Greenwood‐NimmoWalid MensiShawkat Hammoudeh
- Topics
- Monetary Policy and Economic Impact (12 papers)Financial Risk and Volatility Modeling (12 papers)Advanced Statistical Methods and Models (7 papers)
- Partner nations
- South KoreaUnited StatesNew Zealand
In The Last Decade
Jin Seo Cho
30 papers receiving 614 citations
Hit Papers
Peers
Comparison fields: 5 of 72
- Economics and Econometrics 439
- General Economics, Econometrics and Finance 165
- Finance 155
- Renewable Energy, Sustainability and the Environment 148
- Statistics and Probability 105
Countries citing papers authored by Jin Seo Cho
This map shows the geographic impact of Jin Seo Cho'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 Jin Seo Cho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Seo Cho more than expected).
Fields of papers citing papers by Jin Seo Cho
This network shows the impact of papers produced by Jin Seo Cho. 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 Jin Seo Cho. The network helps show where Jin Seo Cho may publish in the future.
Co-authorship network of co-authors of Jin Seo Cho
This figure shows the co-authorship network connecting the top 25 collaborators of Jin Seo Cho. A scholar is included among the top collaborators of Jin Seo Cho 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 Jin Seo Cho. Jin Seo Cho is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 9 | |
| 8 | 10 | |
| 9 | 2 | |
| 10 | Testing the Linearity Hypothesis Using Power Transformations | 1 |
| 11 | 1 | |
| 12 | 4 | |
| 13 | Quasi-Maximum Likelihood Estimation Revisited Using the Distance and Direction Method | 2 |
| 14 | 2 | |
| 15 | 11 | |
| 16 | Experience with the weighted bootstrap in testing for unobserved heterogeneity in exponential and weibull duration models | 6 |
| 17 | 9 | |
| 18 | 18 | |
| 19 | 3 | |
| 20 | Testing for the Mixture Hypothesis of Geometric Distributions | 2 |
About Jin Seo Cho
Jin Seo Cho is a scholar working on Statistics and Probability, General Economics, Econometrics and Finance and Finance, having authored 34 papers that have together received 638 indexed citations. Recurring topics across this work include Monetary Policy and Economic Impact (12 papers), Financial Risk and Volatility Modeling (12 papers) and Advanced Statistical Methods and Models (7 papers). The work is most often cited by research in General Economics, Econometrics and Finance (165 citations), Economics and Econometrics (439 citations) and Finance (155 citations). Jin Seo Cho has collaborated with scholars based in South Korea, United States and New Zealand. Frequent co-authors include Yongcheol Shin, Tae‐Hwan Kim, Halbert White, Peter C.B. Phillips, Chirok Han, Matthew Greenwood‐Nimmo, Walid Mensi, Shawkat Hammoudeh, Tae‐Hwan Kim and Juwon Seo. Their work appears in journals such as Econometrica, Journal of Econometrics and Neural Computation.
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.