Aubrey Poon

434 total citations
28 papers, 221 citations indexed

About

Aubrey Poon is a scholar working on General Economics, Econometrics and Finance, Economics and Econometrics and Finance. According to data from OpenAlex, Aubrey Poon has authored 28 papers receiving a total of 221 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in General Economics, Econometrics and Finance, 21 papers in Economics and Econometrics and 10 papers in Finance. Recurrent topics in Aubrey Poon's work include Monetary Policy and Economic Impact (23 papers), Market Dynamics and Volatility (13 papers) and Financial Risk and Volatility Modeling (5 papers). Aubrey Poon is often cited by papers focused on Monetary Policy and Economic Impact (23 papers), Market Dynamics and Volatility (13 papers) and Financial Risk and Volatility Modeling (5 papers). Aubrey Poon collaborates with scholars based in United Kingdom, Sweden and Australia. Aubrey Poon's co-authors include Jamie Cross, Gary Koop, Stuart McIntyre, James Mitchell, Dan Zhu, Joshua C. C. Chan, Luca Rossini, Juan A. Garcia, Pär Österholm and Alain Kabundi and has published in prestigious journals such as Journal of Econometrics, Journal of Business and Economic Statistics and Economics Letters.

In The Last Decade

Aubrey Poon

24 papers receiving 213 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Aubrey Poon United Kingdom 8 161 144 65 37 14 28 221
Eric Eisenstat Australia 7 163 1.0× 151 1.0× 98 1.5× 30 0.8× 13 0.9× 16 256
Christophe Planas Italy 8 142 0.9× 128 0.9× 64 1.0× 22 0.6× 8 0.6× 21 207
Genaro Sucarrat Norway 12 294 1.8× 124 0.9× 251 3.9× 42 1.1× 21 1.5× 31 396
Giuseppe Storti Italy 9 164 1.0× 61 0.4× 157 2.4× 67 1.8× 18 1.3× 30 237
Vincent Labhard Germany 9 184 1.1× 190 1.3× 83 1.3× 80 2.2× 12 0.9× 21 285
Michel van der Wel Netherlands 10 176 1.1× 164 1.1× 283 4.4× 28 0.8× 7 0.5× 32 363
Guilherme V. Moura Brazil 11 175 1.1× 113 0.8× 193 3.0× 71 1.9× 12 0.9× 42 309
Alain Guay Canada 12 274 1.7× 281 2.0× 138 2.1× 30 0.8× 9 0.6× 32 389
Guoshi Tong China 7 307 1.9× 135 0.9× 188 2.9× 85 2.3× 11 0.8× 11 404
Carlos Trucíos Brazil 10 205 1.3× 53 0.4× 192 3.0× 45 1.2× 5 0.4× 27 262

Countries citing papers authored by Aubrey Poon

Since Specialization
Citations

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

Fields of papers citing papers by Aubrey Poon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aubrey Poon

This figure shows the co-authorship network connecting the top 25 collaborators of Aubrey Poon. A scholar is included among the top collaborators of Aubrey Poon 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 Aubrey Poon. Aubrey Poon 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
1.
Chan, Joshua C. C., Davide Pettenuzzo, Aubrey Poon, & Dan Zhu. (2025). Conditional forecasts in large Bayesian VARs with multiple equality and inequality constraints. Journal of Economic Dynamics and Control. 173. 105061–105061.
2.
Poon, Aubrey & Dan Zhu. (2024). Do Recessions and Bear Markets Occur Concurrently across Countries? A Multinomial Logistic Approach. Journal of Financial Econometrics. 22(5). 1482–1502. 1 indexed citations
3.
Mitchell, James, Aubrey Poon, & Dan Zhu. (2024). Constructing density forecasts from quantile regressions: Multimodality in macrofinancial dynamics. Journal of Applied Econometrics. 39(5). 790–812. 1 indexed citations
4.
Poon, Aubrey, et al.. (2024). Time-Varying Parameter MIDAS Models: Application to Nowcasting US Real GDP. SSRN Electronic Journal.
5.
Chan, Joshua C. C., Aubrey Poon, & Dan Zhu. (2023). High-dimensional conditionally Gaussian state space models with missing data. Journal of Econometrics. 236(1). 105468–105468. 9 indexed citations
6.
Koop, Gary, et al.. (2023). Incorporating short data into large mixed-frequency vector autoregressions for regional nowcasting. Journal of the Royal Statistical Society Series A (Statistics in Society). 187(2). 477–495. 2 indexed citations
7.
Cross, Jamie, et al.. (2023). Large stochastic volatility in mean VARs. Journal of Econometrics. 236(1). 105469–105469. 6 indexed citations
8.
Poon, Aubrey, et al.. (2023). Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP. Journal of Economic Dynamics and Control. 157. 104757–104757. 6 indexed citations
9.
Koop, Gary, Stuart McIntyre, James Mitchell, & Aubrey Poon. (2022). Reconciled Estimates of Monthly GDP in the United States. Journal of Business and Economic Statistics. 41(2). 563–577. 6 indexed citations
10.
Koop, Gary, et al.. (2022). Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage. International Journal of Forecasting. 39(1). 346–363. 17 indexed citations
11.
Österholm, Pär & Aubrey Poon. (2022). Trend Inflation in Sweden. International Journal of Finance & Economics. 28(4). 4707–4716. 1 indexed citations
12.
Mitchell, James, Dan Zhu, & Aubrey Poon. (2022). Constructing Density Forecasts from Quantile Regressions: Multimodality in Macro-Financial Dynamics. SSRN Electronic Journal. 2 indexed citations
13.
Koop, Gary, Stuart McIntyre, James Mitchell, & Aubrey Poon. (2021). NOWCASTING ‘TRUE’ MONTHLY U.S. GDP DURING THE PANDEMIC. National Institute Economic Review. 256. 44–70. 6 indexed citations
14.
Koop, Gary, et al.. (2020). Computationally efficient inference in large Bayesian mixed frequency VARs. Economics Letters. 191. 109120–109120. 11 indexed citations
15.
Koop, Gary, Stuart McIntyre, James Mitchell, & Aubrey Poon. (2020). RECONCILED ESTIMATES AND NOWCASTS OF REGIONAL OUTPUT IN THE UK. National Institute Economic Review. 253. R44–R59. 9 indexed citations
16.
Cross, Jamie, et al.. (2020). Macroeconomic forecasting with large Bayesian VARs: Global-local priors and the illusion of sparsity. International Journal of Forecasting. 36(3). 899–915. 45 indexed citations
17.
Cross, Jamie & Aubrey Poon. (2019). On the contribution of international shocks in Australian business cycle fluctuations. Empirical Economics. 59(6). 2613–2637. 4 indexed citations
18.
Koop, Gary, Stuart McIntyre, James Mitchell, & Aubrey Poon. (2019). Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970. Journal of Applied Econometrics. 35(2). 176–197. 35 indexed citations
19.
Garcia, Juan A. & Aubrey Poon. (2018). Trend Inflation and Inflation Compensation. IMF Working Paper. 18(154). 1–1. 2 indexed citations
20.
Poon, Aubrey. (2018). Assessing the Synchronicity and Nature of Australian State Business Cycles. Economic Record. 94(307). 372–390. 8 indexed citations

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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