Zhongjun Qu
Impact in
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- Monetary Policy and Economic Impact
- Economic Theory and Policy
- Finance top 1%
- Financial Risk and Volatility Modeling
- Global Financial Crisis and Policies
Papers in
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- Monetary Policy and Economic Impact 15
- Finance 13
- Financial Risk and Volatility Modeling 12
- Stochastic processes and financial applications 3
- Co-authors
- Pierre PerrónTatsushi OkaLei YuDong ZhangYi‐Ting ChenGuanjie ChenTimothy J. VogelsangSerena Ng
- Journals
- Journal of Econometrics (6 papers)Journal of Business and Economic Statistics (3 papers)Quantitative Economics (2 papers)Econometrics Journal (2 papers)The Review of Economic Studies (1 paper)
- Partner nations
- United StatesSingaporeChina
In The Last Decade
Zhongjun Qu
27 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 68
- General Economics, Econometrics and Finance 603
- Finance 545
- Statistics and Probability 245
- Economics and Econometrics 775
- Statistics, Probability and Uncertainty 47
Countries citing papers authored by Zhongjun Qu
This map shows the geographic impact of Zhongjun Qu'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 Zhongjun Qu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhongjun Qu more than expected).
Fields of papers citing papers by Zhongjun Qu
This network shows the impact of papers produced by Zhongjun Qu. 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 Zhongjun Qu. The network helps show where Zhongjun Qu may publish in the future.
Co-authorship network
The 8 scholars most cited alongside Zhongjun Qu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 0 | |
| 2 | 2023 | 2 | |
| 3 | 2021 | 3 | |
| 4 | 2021 | 0 | |
| 5 | 2018 | 2 | |
| 6 | 2017 | 6 | |
| 7 | 2014 | 17 | |
| 8 | 2014 | 4 | |
| 9 | Inference in DSGE Models with Possible Weak Identi…cation | 2013 | 3 |
| 10 | 2012 | 51 | |
| 11 | 2010 | 87 | |
| 12 | 2010 | 9 | |
| 13 | 2010 | 2 | |
| 14 | 2009 | 119 | |
| 15 | 2008 | 97 | |
| 16 | 2008 | 15 | |
| 17 | 2008 | 3 | |
| 18 | 2007 | 325 | |
| 19 | 2007 | 6 | |
| 20 | 2007 | 16 |
About Zhongjun Qu
Zhongjun Qu is a scholar working on General Economics, Econometrics and Finance, Finance, Statistics and Probability, Economics and Econometrics and Industrial and Manufacturing Engineering, having authored 29 papers that have together received 1.2k indexed citations. Recurring topics across this work include Monetary Policy and Economic Impact (15 papers), Market Dynamics and Volatility (12 papers), Financial Risk and Volatility Modeling (12 papers), Complex Systems and Time Series Analysis (6 papers), Statistical Methods and Inference (4 papers), Advanced Statistical Methods and Models (4 papers), Stochastic processes and financial applications (3 papers) and Economics of Agriculture and Food Markets (2 papers). The work is most often cited by research in General Economics, Econometrics and Finance (603 citations), Finance (545 citations), Statistics and Probability (245 citations), Economics and Econometrics (775 citations) and Statistics, Probability and Uncertainty (47 citations). Zhongjun Qu has collaborated with scholars based in United States, Singapore and China. Frequent co-authors include Pierre Perrón, Tatsushi Oka, Lei Yu, Dong Zhang, Yi‐Ting Chen, Guanjie Chen, Timothy J. Vogelsang and Serena Ng. Their work appears in journals such as Journal of Econometrics, Journal of Business and Economic Statistics, Quantitative Economics, Econometrics Journal and The Review of Economic Studies.
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.