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Boyuan Zhang

Personal Details

First Name:Boyuan
Middle Name:
Last Name:Zhang
Suffix:
RePEc Short-ID:pzh926
https://boyuan-zhang.site
Terminal Degree: Department of Economics; University of Pennsylvania (from RePEc Genealogy)

Affiliation

Department of Economics
University of Pennsylvania

Philadelphia, Pennsylvania (United States)
http://www.econ.upenn.edu/
RePEc:edi:deupaus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Francis X. Diebold & Glenn D. Rudebusch & Maximilian Goebel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," Papers 2203.04040, arXiv.org, revised May 2023.
  2. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2022. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," NBER Working Papers 29635, National Bureau of Economic Research, Inc.
  3. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
  4. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe & Glenn D. Rudebusch & Boyuan Zhang, 2020. "Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach," Papers 2003.14276, arXiv.org, revised Aug 2020.

Articles

  1. Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe & Rudebusch, Glenn D. & Zhang, Boyuan, 2021. "Optimal combination of Arctic sea ice extent measures: A dynamic factor modeling approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1509-1519.
  2. Shin, Minchul & Zhang, Boyuan & Zhong, Molin & Lee, Dong Jin, 2018. "Measuring international uncertainty: The case of Korea," Economics Letters, Elsevier, vol. 162(C), pages 22-26.
  3. D. N. Burrows & J. A. Kennea & G. Ghisellini & V. Mangano & B. Zhang & K. L. Page & M. Eracleous & P. Romano & T. Sakamoto & A. D. Falcone & J. P. Osborne & S. Campana & A. P. Beardmore & A. A. Breeve, 2011. "Relativistic jet activity from the tidal disruption of a star by a massive black hole," Nature, Nature, vol. 476(7361), pages 421-424, August.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Francis X. Diebold & Glenn D. Rudebusch & Maximilian Goebel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," Papers 2203.04040, arXiv.org, revised May 2023.

    Cited by:

    1. Francis X. Diebold & Glenn D. Rudebusch, 2023. "Climate Models Underestimate the Sensitivity of Arctic Sea Ice to Carbon Emissions," PIER Working Paper Archive 24-010, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    2. B. Cooper Boniece & Lajos Horv'ath & Lorenzo Trapani, 2023. "On changepoint detection in functional data using empirical energy distance," Papers 2310.04853, arXiv.org.

  2. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2022. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," NBER Working Papers 29635, National Bureau of Economic Research, Inc.

    Cited by:

    1. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020. "Machine Learning Advances for Time Series Forecasting," Papers 2012.12802, arXiv.org, revised Apr 2021.
    2. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    3. Chernis Tony, 2024. "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 293-317, April.
    4. Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019. "Empirically-transformed linear opinion pools," CAMA Working Papers 2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers 22-37, Federal Reserve Bank of Cleveland.
    6. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.

  3. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.

    Cited by:

    1. Jorge A. Rivero, 2023. "Unobserved Grouped Heteroskedasticity and Fixed Effects," Papers 2310.14068, arXiv.org, revised Oct 2023.
    2. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.

  4. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe & Glenn D. Rudebusch & Boyuan Zhang, 2020. "Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach," Papers 2003.14276, arXiv.org, revised Aug 2020.

    Cited by:

    1. Diebold, Francis X. & Rudebusch, Glenn D., 2022. "Probability assessments of an ice-free Arctic: Comparing statistical and climate model projections," Journal of Econometrics, Elsevier, vol. 231(2), pages 520-534.
    2. Ar'anzazu de Juan & Pilar Poncela & Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2022. "Economic activity and climate change," Papers 2206.03187, arXiv.org, revised Jun 2022.
    3. Francis X. Diebold & Glenn D. Rudebusch, 2023. "Climate Models Underestimate the Sensitivity of Arctic Sea Ice to Carbon Emissions," PIER Working Paper Archive 24-010, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    4. Hee Soo (test record) Kim & Christian Matthes & Toan Phan, 2011. "Extreme Weather and the Macroeconomy," Working Paper 21-14, Federal Reserve Bank of Richmond.
    5. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    6. Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe, 2023. "Assessing and comparing fixed-target forecasts of Arctic sea ice: Glide charts for feature-engineered linear regression and machine learning models," Energy Economics, Elsevier, vol. 124(C).
    7. Escribano, Alvaro & Peña, Daniel & Ruiz, Esther, 2021. "30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1333-1337.
    8. Marina Friedrich & Luca Margaritella & Stephan Smeekes, 2023. "High-Dimensional Granger Causality for Climatic Attribution," Papers 2302.03996, arXiv.org, revised Jun 2024.
    9. Robert Amano & Marc-André Gosselin & Julien McDonald-Guimond, 2021. "Evolving Temperature Dynamics in Canada: Preliminary Evidence Based on 60 Years of Data," Staff Working Papers 21-22, Bank of Canada.
    10. Atin Aboutorabi & Ga'etan de Rassenfosse, 2024. "Nowcasting R&D Expenditures: A Machine Learning Approach," Papers 2407.11765, arXiv.org.
    11. Diego Fresoli & Pilar Poncela & Esther Ruiz, 2024. "Dealing with idiosyncratic cross-correlation when constructing confidence regions for PC factors," Papers 2407.06883, arXiv.org.

Articles

  1. Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe & Rudebusch, Glenn D. & Zhang, Boyuan, 2021. "Optimal combination of Arctic sea ice extent measures: A dynamic factor modeling approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1509-1519.
    See citations under working paper version above.
  2. Shin, Minchul & Zhang, Boyuan & Zhong, Molin & Lee, Dong Jin, 2018. "Measuring international uncertainty: The case of Korea," Economics Letters, Elsevier, vol. 162(C), pages 22-26.

    Cited by:

    1. Liang, Chin Chia & Troy, Carol & Rouyer, Ellen, 2020. "U.S. uncertainty and Asian stock prices: Evidence from the asymmetric NARDL model," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    2. Cho, Dooyeon & Kim, Husang, 2023. "Macroeconomic effects of uncertainty shocks: Evidence from Korea," Journal of Asian Economics, Elsevier, vol. 84(C).
    3. Sangyup Choi & Myungkyu Shim, 2019. "Financial vs. Policy Uncertainty in Emerging Market Economies," Open Economies Review, Springer, vol. 30(2), pages 297-318, April.
    4. Tran, Quoc Trung, 2020. "Creditor protection, shareholder protection and investment efficiency: New evidence," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    5. Avellán, Guillermo & González-Astudillo, Manuel & Salcedo, Juan José, 2020. "A Streamlined Procedure to Construct a Macroeconomic Uncertainty Index with an Application to the Ecuadorian Economy," MPRA Paper 102593, University Library of Munich, Germany.
    6. Park, Jin Seok & Suh, Donghyun, 2019. "Uncertainty and household portfolio choice : Evidence from South Korea," Economics Letters, Elsevier, vol. 180(C), pages 21-24.
    7. Quoc Trung Tran, 2020. "Corporate cash holdings and financial crisis: new evidence from an emerging market," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 10(2), pages 271-285, June.
    8. Serdar Ongan & Ismet Gocer, 2022. "Japan-US bilateral commodity-level trade and trade policy-related uncertainty under the COVID-19 pandemic: the nonlinear ARDL model," Economic Change and Restructuring, Springer, vol. 55(3), pages 1397-1418, August.
    9. Youngjoon Lee & Soohyon Kim & Ki Young Park, 2018. "Deciphering Monetary Policy Committee Minutes with Text Mining Approach: A Case of South Korea," Working papers 2018rwp-132, Yonsei University, Yonsei Economics Research Institute.
    10. Ioannis Dokas & Georgios Oikonomou & Minas Panagiotidis & Eleftherios Spyromitros, 2023. "Macroeconomic and Uncertainty Shocks’ Effects on Energy Prices: A Comprehensive Literature Review," Energies, MDPI, vol. 16(3), pages 1-35, February.
    11. Aviral Kumar Tiwari & Muhammad Ali Nasir & Muhammad Shahbaz, 2021. "Synchronisation of policy related uncertainty, financial stress and economic activity in the United States," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 6406-6415, October.
    12. Śmiech, Sławomir & Papież, Monika & Dąbrowski, Marek A., 2019. "How important are different aspects of uncertainty in driving industrial production in the CEE countries?," Research in International Business and Finance, Elsevier, vol. 50(C), pages 252-266.
    13. Tran, Quoc Trung, 2021. "Economic policy uncertainty and cost of debt financing: International evidence," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    14. Ogbuabor, Jonathan E. & Ukwueze, Ezebuilo R. & Mba, Ifeoma C. & Ojonta, Obed I. & Orji, Anthony, 2023. "The asymmetric impact of economic policy uncertainty on global retail energy markets: Are the markets responding to the fear of the unknown?," Applied Energy, Elsevier, vol. 334(C).
    15. Kevin Larcher & Jaebeom Kim & Youngju Kim, 2019. "Uncertainty shocks and asymmetric dynamics in Korea: a non-linear approach," Applied Economics, Taylor & Francis Journals, vol. 51(6), pages 594-610, February.
    16. Lin Liu, 2022. "Economic Uncertainty and Exchange Market Pressure: Evidence From China," SAGE Open, , vol. 12(1), pages 21582440211, January.
    17. Bukalska Elżbieta & Maziarczyk Anna, 2023. "Impact of financial constraints and financial distress on cash holdings," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 59(1), pages 13-31, March.
    18. Guillermo Avellán & Manuel González-Astudillo & Juan José Salcedo Cruz, 2022. "Measuring uncertainty: A streamlined application for the Ecuadorian economy," Empirical Economics, Springer, vol. 62(4), pages 1517-1542, April.
    19. Hwang, So Jung & Suh, Hyunduk, 2021. "Overall and time-varying effects of global and domestic uncertainty on the Korean economy," Journal of Asian Economics, Elsevier, vol. 76(C).

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 6 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ENV: Environmental Economics (3) 2020-04-13 2022-05-02 2023-01-09
  2. NEP-ECM: Econometrics (2) 2020-09-07 2022-02-07
  3. NEP-FOR: Forecasting (2) 2020-09-07 2021-02-01
  4. NEP-CMP: Computational Economics (1) 2020-09-07
  5. NEP-ETS: Econometric Time Series (1) 2020-04-13
  6. NEP-IFN: International Finance (1) 2023-01-09

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