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Mark Bognanni

Personal Details

First Name:Mark
Middle Name:
Last Name:Bognanni
Suffix:
RePEc Short-ID:pbo762
[This author has chosen not to make the email address public]
http://markbognanni.com/
Terminal Degree:2013 Department of Economics; University of Pennsylvania (from RePEc Genealogy)

Affiliation

(50%) Federal Reserve Bank of Cleveland

Cleveland, Ohio (United States)
https://www.clevelandfed.org/
RePEc:edi:frbclus (more details at EDIRC)

(50%) Economic Research
Federal Reserve Bank of Cleveland

Cleveland, Ohio (United States)
https://www.clevelandfed.org/our-research/
RePEc:edi:efrbcus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Mark Bognanni & Douglas Hanley & Daniel Kolliner & Kurt Mitman, 2020. "Economics and Epidemics: Evidence from an Estimated Spatial Econ-SIR Model," Finance and Economics Discussion Series 2020-091, Board of Governors of the Federal Reserve System (U.S.).
  2. Mark Bognanni & John Zito, 2019. "Sequential Bayesian Inference for Vector Autoregressions with Stochastic Volatility," Working Papers 19-29, Federal Reserve Bank of Cleveland.
  3. Mark Bognanni, 2018. "A Class of Time-Varying Parameter Structural VARs for Inference under Exact or Set Identification," Working Papers (Old Series) 1811, Federal Reserve Bank of Cleveland.
  4. Mark Bognanni & Edward P. Herbst, 2014. "Estimating (Markov-Switching) VAR Models without Gibbs Sampling: A Sequential Monte Carlo Approach," Working Papers (Old Series) 1427, Federal Reserve Bank of Cleveland.

Articles

  1. Mark Bognanni, 2020. "A Forecasting Assessment of Market-Based PCE Inflation," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2020(01), January.
  2. Mark Bognanni, 2019. "Has the Real-Time Reliability of Monthly Indicators Changed over Time?," Economic Commentary, Federal Reserve Bank of Cleveland, issue October.
  3. Mark Bognanni & Tristan Young, 2018. "An Assessment of the ISM Manufacturing Price Index for Inflation Forecasting," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2018(05), pages 1-6, May.
  4. Mark Bognanni & John Zito, 2016. "New Normal or Real-Time Noise? Revisiting the Recent Data on Labor Productivity," Economic Commentary, Federal Reserve Bank of Cleveland, issue December.

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.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Mark Bognanni & Douglas Hanley & Daniel Kolliner & Kurt Mitman, 2020. "Economics and Epidemics: Evidence from an Estimated Spatial Econ-SIR Model," Finance and Economics Discussion Series 2020-091, Board of Governors of the Federal Reserve System (U.S.).

    Mentioned in:

    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Modelling > Statistical Modelling

Working papers

  1. Mark Bognanni & Douglas Hanley & Daniel Kolliner & Kurt Mitman, 2020. "Economics and Epidemics: Evidence from an Estimated Spatial Econ-SIR Model," Finance and Economics Discussion Series 2020-091, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Fernández-Villaverde, Jesús & Arias, Jonas & Rubio-Ramírez, Juan Francisco & Shin, Minchul, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," CEPR Discussion Papers 15951, C.E.P.R. Discussion Papers.
    2. Glover, Andrew & Heathcote, Jonathan & Krueger, Dirk, 2022. "Optimal age-Based vaccination and economic mitigation policies for the second phase of the covid-19 pandemic," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
    3. Houštecká, Anna & Koh, Dongya & Santaeulàlia-Llopis, Raül, 2021. "Contagion at work: Occupations, industries and human contact," Journal of Public Economics, Elsevier, vol. 200(C).
    4. Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," Working Papers 21-18, Federal Reserve Bank of Philadelphia.
    5. Sewon Hur, 2023. "The Distributional Effects Of Covid‐19 And Optimal Mitigation Policies," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(1), pages 261-294, February.
    6. Lazebnik, Teddy, 2023. "Computational applications of extended SIR models: A review focused on airborne pandemics," Ecological Modelling, Elsevier, vol. 483(C).
    7. Matteo Bizzarri & Fabrizio Panebianco & Paolo Pin, 2023. "Homophily and infections: static and dynamic effects," Papers 2304.11934, arXiv.org.
    8. Luiz Brotherhood, 2020. "Slums and Pandemics," Working Papers w202015, Banco de Portugal, Economics and Research Department.
    9. Hakan Yilmazkuday, 2021. "Welfare Costs of Travel Reductions within the U.S. due to COVID-19," Working Papers 2114, Florida International University, Department of Economics.
    10. Jonas E. Arias & Jesús Fernández-Villaverde & Juan Rubio Ramírez & Minchul Shin, 2021. "The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes," NBER Working Papers 28617, National Bureau of Economic Research, Inc.
    11. Lazebnik, Teddy & Shami, Labib & Bunimovich-Mendrazitsky, Svetlana, 2023. "Intervention policy influence on the effect of epidemiological crisis on industry-level production through input–output networks," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    12. Makris, M. & Toxvaerd, F., 2020. "Great Expectations: Social Distancing in Anticipation of Pharmaceutical Innovations," Cambridge Working Papers in Economics 2097, Faculty of Economics, University of Cambridge.
    13. Mitman, Kurt & Rabinovich, Stanislav, 2021. "Whether, when and how to extend unemployment benefits: Theory and application to COVID-19," Journal of Public Economics, Elsevier, vol. 200(C).
    14. Raül Santaeulàlia-Llopis, 2021. "Economic Activity and Public Health Policy: A Note," Working Papers 1284, Barcelona School of Economics.
    15. Ma, Xiangyu & Zhou, Huijie & Li, Zhiyi, 2021. "On the resilience of modern power systems: A complex network perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).

  2. Mark Bognanni & John Zito, 2019. "Sequential Bayesian Inference for Vector Autoregressions with Stochastic Volatility," Working Papers 19-29, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Edward P. Herbst & Fabian Winkler, 2021. "The Factor Structure of Disagreement," Finance and Economics Discussion Series 2021-046, Board of Governors of the Federal Reserve System (U.S.).

  3. Mark Bognanni, 2018. "A Class of Time-Varying Parameter Structural VARs for Inference under Exact or Set Identification," Working Papers (Old Series) 1811, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2024. "Large Order-Invariant Bayesian VARs with Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 825-837, April.
    2. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    3. Qazi Haque & Leandro M. Magnusson & Kazuki Tomioka, 2019. "Empirical evidence on the dynamics of investment under uncertainty in the U.S," Economics Discussion / Working Papers 19-18, The University of Western Australia, Department of Economics.
    4. Jonas E. Arias & Juan F. Rubio-Ramirez & Daniel F. Waggoner, 2018. "Inference in Bayesian Proxy-SVARs," FRB Atlanta Working Paper 2018-16, Federal Reserve Bank of Atlanta.
    5. Prüser, Jan, 2021. "The horseshoe prior for time-varying parameter VARs and Monetary Policy," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    6. Bognanni, Mark & Zito, John, 2020. "Sequential Bayesian inference for vector autoregressions with stochastic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    7. Etienne Vaccaro-Grange, 2019. "Quantitative Easing and the Term Premium as a Monetary Policy Instrument," Working Papers halshs-02359503, HAL.
    8. Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023. "Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
    9. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    10. Hartwig, Benny, 2020. "Robust Inference in Time-Varying Structural VAR Models: The DC-Cholesky Multivariate Stochastic Volatility Model," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224528, Verein für Socialpolitik / German Economic Association.
    11. Wu, Ping & Koop, Gary, 2023. "Estimating the ordering of variables in a VAR using a Plackett–Luce prior," Economics Letters, Elsevier, vol. 230(C).
    12. Mark Bognanni & John Zito, 2019. "Sequential Bayesian Inference for Vector Autoregressions with Stochastic Volatility," Working Papers 19-29, Federal Reserve Bank of Cleveland.
    13. Harrison, Andre & Liu, Xiaochun & Stewart, Shamar L., 2023. "Structural sources of oil market volatility and correlation dynamics," Energy Economics, Elsevier, vol. 121(C).
    14. Joshua Chan & Eric Eisenstat & Xuewen Yu, 2022. "Large Bayesian VARs with Factor Stochastic Volatility: Identification, Order Invariance and Structural Analysis," Papers 2207.03988, arXiv.org.
    15. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    16. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    17. Laura Liu & Christian Matthes & Katerina Petrova & Jessica Sackett Romero, 2019. "Monetary Policy across Space and Time," Richmond Fed Economic Brief, Federal Reserve Bank of Richmond, issue August.
    18. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019. "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, vol. 212(1), pages 137-154.
    19. Aymeric Ortmans, 2020. "Evolving Monetary Policy in the Aftermath of the Great Recession," Documents de recherche 20-01, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.

  4. Mark Bognanni & Edward P. Herbst, 2014. "Estimating (Markov-Switching) VAR Models without Gibbs Sampling: A Sequential Monte Carlo Approach," Working Papers (Old Series) 1427, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Dario Caldara & Edward Herbst, 2019. "Monetary Policy, Real Activity, and Credit Spreads: Evidence from Bayesian Proxy SVARs," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(1), pages 157-192, January.
    2. Edward P. Herbst & Frank Schorfheide, 2016. "Tempered Particle Filtering," Finance and Economics Discussion Series 2016-072, Board of Governors of the Federal Reserve System (U.S.).
    3. Pierre Guérin & Danilo Leiva-Leon, 2017. "Monetary policy, stock market and sectoral comovement," Working Papers 1731, Banco de España.
    4. Daniel F. Waggoner & Hongwei Wu & Tao Zha, 2014. "The Dynamic Striated Metropolis-Hastings Sampler for High-Dimensional Models," FRB Atlanta Working Paper 2014-21, Federal Reserve Bank of Atlanta.

Articles

  1. Mark Bognanni & Tristan Young, 2018. "An Assessment of the ISM Manufacturing Price Index for Inflation Forecasting," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2018(05), pages 1-6, May.

    Cited by:

    1. José Francisco Lima & Fernanda Catarina Pereira & Arminda Manuela Gonçalves & Marco Costa, 2023. "Bootstrapping State-Space Models: Distribution-Free Estimation in View of Prediction and Forecasting," Forecasting, MDPI, vol. 6(1), pages 1-19, December.

  2. Mark Bognanni & John Zito, 2016. "New Normal or Real-Time Noise? Revisiting the Recent Data on Labor Productivity," Economic Commentary, Federal Reserve Bank of Cleveland, issue December.

    Cited by:

    1. Roberto Pinheiro & Meifeng Yang, 2020. "Revisiting Wage Growth after the Recession," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2020(02), pages 1-5, January.

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 5 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-ETS: Econometric Time Series (4) 2014-11-28 2016-02-29 2018-09-17 2019-12-23
  2. NEP-MAC: Macroeconomics (4) 2014-11-28 2016-02-29 2018-09-17 2020-11-09
  3. NEP-ORE: Operations Research (4) 2014-11-28 2016-02-29 2018-09-17 2019-12-23
  4. NEP-ECM: Econometrics (3) 2014-11-28 2018-09-17 2019-12-23
  5. NEP-CMP: Computational Economics (1) 2019-12-23
  6. NEP-HEA: Health Economics (1) 2020-11-09

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