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Geert Mesters

Personal Details

First Name:Geert
Middle Name:
Last Name:Mesters
Suffix:
RePEc Short-ID:pme642
http://www.geertmesters.nl
Terminal Degree:2015 Afdeling Econometrie and Operations Research; School of Business and Economics; Vrije Universiteit Amsterdam (from RePEc Genealogy)

Affiliation

Departament d'Economia i Empresa
Universitat Pompeu Fabra
Barcelona School of Economics (BSE)

Barcelona, Spain
http://www.econ.upf.edu/
RePEc:edi:deupfes (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Adam Lee & Geert Mesters, 2021. "Robust Non-Gaussian Inference for Linear Simultaneous Equations Models," Working Papers 1278, Barcelona Graduate School of Economics.
  2. Régis Barnichon & Geert Mesters, 2021. "Fiscal Targeting," Working Papers 1277, Barcelona Graduate School of Economics.
  3. Régis Barnichon & Geert Mesters, 2020. "Testing Macroeconomic Policies with Sufficient Statistics," Working Papers 1171, Barcelona Graduate School of Economics.
  4. Régis Barnichon & Geert Mesters, 2020. "Optimal policy perturbations," Economics Working Papers 1716, Department of Economics and Business, Universitat Pompeu Fabra.
  5. Régis Barnichon & Geert Mesters, 2019. "Identifying modern macro equations with old shocks," Economics Working Papers 1659, Department of Economics and Business, Universitat Pompeu Fabra.
  6. Régis Barnichon & Geert Mesters, 2019. "The Phillips multiplier," Economics Working Papers 1632, Department of Economics and Business, Universitat Pompeu Fabra.
  7. Christian Brownlees & Geert Mesters, 2017. "Detecting Granular Time Series in Large Panels," Working Papers 991, Barcelona Graduate School of Economics.
  8. Geert Mesters & Bernd Schwaab & Siem Jan Koopman, 2014. "A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area," Tinbergen Institute Discussion Papers 14-071/III, Tinbergen Institute.
  9. Geert Mesters & Victor van der Geest & Catrien Bijleveld, 2014. "Crime, Employment and Social Welfare: an Individual-level Study on Disadvantaged Males," Tinbergen Institute Discussion Papers 14-091/III, Tinbergen Institute.
  10. Siem Jan Koopman & Geert Mesters, 2014. "Empirical Bayes Methods for Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-061/III, Tinbergen Institute.
  11. Geert Mesters & Siem Jan Koopman, 2012. "Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time," Tinbergen Institute Discussion Papers 12-009/4, Tinbergen Institute, revised 18 Mar 2014.
  12. Geert Mesters & Siem Jan Koopman, 2012. "A Forty Year Assessment of Forecasting the Boat Race," Tinbergen Institute Discussion Papers 12-110/III, Tinbergen Institute.
  13. Geert Mesters & Siem Jan Koopman & Marius Ooms, 2011. "Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models," Tinbergen Institute Discussion Papers 11-090/4, Tinbergen Institute.

Articles

  1. Barnichon, Regis & Mesters, Geert, 2021. "The Phillips multiplier," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 689-705.
  2. Brownlees, Christian & Mesters, Geert, 2021. "Detecting granular time series in large panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 544-561.
  3. Regis Barnichon & Geert Mesters, 2020. "Identifying Modern Macro Equations with Old Shocks," The Quarterly Journal of Economics, Oxford University Press, vol. 135(4), pages 2255-2298.
  4. Regis Barnichon & Geert Mesters, 2018. "On the Demographic Adjustment of Unemployment," The Review of Economics and Statistics, MIT Press, vol. 100(2), pages 219-231, May.
  5. Regis Barnichon & Geert Mesters, 2017. "How Tight Is the U.S. Labor Market?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.
  6. S. J. Koopman & G. Mesters, 2017. "Empirical Bayes Methods for Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 99(3), pages 486-498, July.
  7. G. Mesters & S. J. Koopman & M. Ooms, 2016. "Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 659-687, April.
  8. Mesters, G. & Koopman, S.J., 2014. "Generalized dynamic panel data models with random effects for cross-section and time," Journal of Econometrics, Elsevier, vol. 180(2), pages 127-140.

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. Régis Barnichon & Geert Mesters, 2019. "Identifying modern macro equations with old shocks," Economics Working Papers 1659, Department of Economics and Business, Universitat Pompeu Fabra.

    Cited by:

    1. William Chen & Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What’s Up with the Phillips Curve?," Liberty Street Economics 20200918a, Federal Reserve Bank of New York.
    2. Michael McLeay & Silvana Tenreyro, 2018. "Optimal Inflation and the Identification of the Phillips Curve," Discussion Papers 1815, Centre for Macroeconomics (CFM).
    3. Mario Alloza & Jesús Gonzalo & Carlos Sanz, 2019. "Dynamic effects of persistent shocks," Working Papers 1944, Banco de España.
    4. Jean-Louis Combes & Pierre Lesuisse, 2021. "Inflation and Unemployment, new insights during the EMU accession," Working Papers hal-03216478, HAL.
    5. Matthew Rognlie, 2019. "Comment on "Optimal Inflation and the Identification of the Phillips Curve"," NBER Chapters, in: NBER Macroeconomics Annual 2019, volume 34, pages 267-279, National Bureau of Economic Research, Inc.

  2. Régis Barnichon & Geert Mesters, 2019. "The Phillips multiplier," Economics Working Papers 1632, Department of Economics and Business, Universitat Pompeu Fabra.

    Cited by:

    1. Hideaki Aoyama & Corrado Di Guilmi & Yoshi Fujiwara & Hiroshi Yoshikawa, 2021. "Dual Labor Market and the "Phillips Curve Puzzle"," Papers 2103.06482, arXiv.org.
    2. Janice C. Eberly & James H. Stock & Jonathan H. Wright, 2020. "The Federal Reserve's Current Framework for Monetary Policy: A Review and Assessment," International Journal of Central Banking, International Journal of Central Banking, vol. 16(1), pages 5-71, February.
    3. Martins, Manuel M. F. & Verona, Fabio, 2021. "Inflation dynamics and forecast : frequency matters," Research Discussion Papers 8/2021, Bank of Finland.
    4. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2019. "The Phillips Curve at 60: time for time and frequency," CEF.UP Working Papers 1902, Universidade do Porto, Faculdade de Economia do Porto.
    5. Maurice Obstfeld, 2020. "Global Dimensions of U.S. Monetary Policy," International Journal of Central Banking, International Journal of Central Banking, vol. 16(1), pages 73-132, February.
    6. Eser, Fabian & Karadi, Peter & Lane, Philip R. & Moretti, Laura & Osbat, Chiara, 2020. "The Phillips Curve at the ECB," Working Paper Series 2400, European Central Bank.
    7. Lodge, David & Pérez, Javier J. & Albrizio, Silvia & Everett, Mary & De Bandt, Olivier & Georgiadis, Georgios & Ca' Zorzi, Michele & Lastauskas, Povilas & Carluccio, Juan & Parrága, Susana & Carvalho,, 2021. "The implications of globalisation for the ECB monetary policy strategy," Occasional Paper Series 263, European Central Bank.
    8. Jean-Louis Combes & Pierre Lesuisse, 2021. "Inflation and Unemployment, new insights during the EMU accession," Working Papers hal-03216478, HAL.
    9. Antonio M. Conti & Elisa Guglielminetti & Marianna Riggi, 2019. "Labour productivity and the wageless recovery," Temi di discussione (Economic working papers) 1257, Bank of Italy, Economic Research and International Relations Area.
    10. Ziegenbein, Alexander, 2021. "Macroeconomic shocks and Okun’s Law," Economics Letters, Elsevier, vol. 202(C).
    11. Ioannou, Demosthenes & Stracca, Livio & Pagliari, Maria Sole, 2020. "The international dimension of an incomplete EMU," Working Paper Series 2459, European Central Bank.
    12. Ioannou Demosthenes & Pagliari Maria Sole & Stracca Livio, 2020. "The international dimension of a fragile EMU," Working papers 795, Banque de France.

  3. Christian Brownlees & Geert Mesters, 2017. "Detecting Granular Time Series in Large Panels," Working Papers 991, Barcelona Graduate School of Economics.

    Cited by:

    1. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    2. Gabaix, Xavier & Koijen, Ralph, 2020. "Granular Instrumental Variables," CEPR Discussion Papers 15531, C.E.P.R. Discussion Papers.
    3. George Kapetanios & M. Hashem Pesaran & Simon Reese, 2018. "A Residual-based Threshold Method for Detection of Units that are Too Big to Fail in Large Factor Models," CESifo Working Paper Series 7401, CESifo.

  4. Geert Mesters & Bernd Schwaab & Siem Jan Koopman, 2014. "A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area," Tinbergen Institute Discussion Papers 14-071/III, Tinbergen Institute.

    Cited by:

    1. Christoph Trebesch & Jeromin Zettelmeyer, 2014. "ECB Interventions in Distressed Sovereign Debt Markets: The Case of Greek Bonds," CESifo Working Paper Series 4731, CESifo.
    2. Chamon, Marcos & Schumacher, Julian & Trebesch, Christoph, 2018. "Foreign-law bonds: can they reduce sovereign borrowing costs?," Working Paper Series 2162, European Central Bank.
    3. Recchioni, Maria Cristina & Tedeschi, Gabriele, 2017. "From bond yield to macroeconomic instability: A parsimonious affine model," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1116-1135.
    4. Kleppe, Tore Selland & Liesenfeld, Roman & Moura, Guilherme Valle & Oglend, Atle, 2022. "Analyzing Commodity Futures Using Factor State-Space Models with Wishart Stochastic Volatility," Econometrics and Statistics, Elsevier, vol. 23(C), pages 105-127.
    5. Pelizzon, Loriana & Subrahmanyam, Marti G. & Tomio, Davide & Uno, Jun, 2016. "Sovereign credit risk, liquidity, and European Central Bank intervention: Deus ex machina?," Journal of Financial Economics, Elsevier, vol. 122(1), pages 86-115.
    6. Eser, Fabian & Schwaab, Bernd, 2016. "Evaluating the impact of unconventional monetary policy measures: Empirical evidence from the ECB׳s Securities Markets Programme," Journal of Financial Economics, Elsevier, vol. 119(1), pages 147-167.
    7. Maria Cristina Recchioni & Gabriele Tedeschi, 2016. "From bond yield to macroeconomic instability: The effect of negative interest rates," Working Papers 2016/06, Economics Department, Universitat Jaume I, Castellón (Spain).

  5. Geert Mesters & Victor van der Geest & Catrien Bijleveld, 2014. "Crime, Employment and Social Welfare: an Individual-level Study on Disadvantaged Males," Tinbergen Institute Discussion Papers 14-091/III, Tinbergen Institute.

    Cited by:

    1. Christian Aßmann & Marcel Preising, 2020. "Bayesian estimation and model comparison for linear dynamic panel models with missing values," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 62(4), pages 536-557, December.

  6. Siem Jan Koopman & Geert Mesters, 2014. "Empirical Bayes Methods for Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-061/III, Tinbergen Institute.

    Cited by:

    1. James Sampi, 2016. "High Dimensional Factor Models: An Empirical Bayes Approach," Working Papers 2016-75, Peruvian Economic Association.
    2. Falk Bräuning & Siem Jan Koopman, 2016. "The dynamic factor network model with an application to global credit risk," Working Papers 16-13, Federal Reserve Bank of Boston.
    3. Michael W. McCracken & Serena Ng, 2021. "FRED-QD: A Quarterly Database for Macroeconomic Research," Review, Federal Reserve Bank of St. Louis, vol. 103(1), pages 1-44, January.
    4. Bräuning, Falk & Koopman, Siem Jan, 2020. "The dynamic factor network model with an application to international trade," Journal of Econometrics, Elsevier, vol. 216(2), pages 494-515.

  7. Geert Mesters & Siem Jan Koopman, 2012. "Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time," Tinbergen Institute Discussion Papers 12-009/4, Tinbergen Institute, revised 18 Mar 2014.

    Cited by:

    1. Siem Jan Koopman & Geert Mesters, 2014. "Empirical Bayes Methods for Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-061/III, Tinbergen Institute.
    2. Geert Mesters & Siem Jan Koopman, 2012. "Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time," Tinbergen Institute Discussion Papers 12-009/4, Tinbergen Institute, revised 18 Mar 2014.
    3. Falk Bräuning & Siem Jan Koopman, 2016. "The dynamic factor network model with an application to global credit risk," Working Papers 16-13, Federal Reserve Bank of Boston.
    4. Timothy Neal, 2018. "Multidimensional Parameter Heterogeneity in Panel Data Models," Discussion Papers 2016-15A, School of Economics, The University of New South Wales.
    5. Christian Aßmann & Marcel Preising, 2020. "Bayesian estimation and model comparison for linear dynamic panel models with missing values," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 62(4), pages 536-557, December.
    6. Geert Mesters & Victor van der Geest & Catrien Bijleveld, 2014. "Crime, Employment and Social Welfare: an Individual-level Study on Disadvantaged Males," Tinbergen Institute Discussion Papers 14-091/III, Tinbergen Institute.
    7. Geert Mesters & Bernd Schwaab & Siem Jan Koopman, 2014. "A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area," Tinbergen Institute Discussion Papers 14-071/III, Tinbergen Institute.
    8. Bräuning, Falk & Koopman, Siem Jan, 2020. "The dynamic factor network model with an application to international trade," Journal of Econometrics, Elsevier, vol. 216(2), pages 494-515.
    9. Eser, Fabian & Schwaab, Bernd, 2016. "Evaluating the impact of unconventional monetary policy measures: Empirical evidence from the ECB׳s Securities Markets Programme," Journal of Financial Economics, Elsevier, vol. 119(1), pages 147-167.
    10. Borus Jungbacker & Siem Jan Koopman, 2015. "Likelihood‐based dynamic factor analysis for measurement and forecasting," Econometrics Journal, Royal Economic Society, vol. 18(2), pages 1-21, June.
    11. Borus Jungbacker & Siem Jan Koopman, 2008. "Likelihood-based Analysis for Dynamic Factor Models," Tinbergen Institute Discussion Papers 08-007/4, Tinbergen Institute, revised 20 Mar 2014.

  8. Geert Mesters & Siem Jan Koopman, 2012. "A Forty Year Assessment of Forecasting the Boat Race," Tinbergen Institute Discussion Papers 12-110/III, Tinbergen Institute.

    Cited by:

    1. Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.

  9. Geert Mesters & Siem Jan Koopman & Marius Ooms, 2011. "Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models," Tinbergen Institute Discussion Papers 11-090/4, Tinbergen Institute.

    Cited by:

    1. Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).
    2. Tobias Hartl & Roland Jucknewitz, 2022. "Approximate state space modelling of unobserved fractional components," Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 75-98, January.
    3. Tobias Hartl & Roland Weigand, 2018. "Multivariate Fractional Components Analysis," Papers 1812.09149, arXiv.org, revised Jan 2019.
    4. Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
    5. Blasques, Francisco & Hoogerkamp, Meindert Heres & Koopman, Siem Jan & van de Werve, Ilka, 2021. "Dynamic factor models with clustered loadings: Forecasting education flows using unemployment data," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1426-1441.
    6. Siem Jan Koopman & Marcel Scharth, 2011. "The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures," Tinbergen Institute Discussion Papers 11-132/4, Tinbergen Institute.

Articles

  1. Barnichon, Regis & Mesters, Geert, 2021. "The Phillips multiplier," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 689-705.
    See citations under working paper version above.
  2. Brownlees, Christian & Mesters, Geert, 2021. "Detecting granular time series in large panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 544-561.
    See citations under working paper version above.
  3. Regis Barnichon & Geert Mesters, 2020. "Identifying Modern Macro Equations with Old Shocks," The Quarterly Journal of Economics, Oxford University Press, vol. 135(4), pages 2255-2298.
    See citations under working paper version above.
  4. Regis Barnichon & Geert Mesters, 2018. "On the Demographic Adjustment of Unemployment," The Review of Economics and Statistics, MIT Press, vol. 100(2), pages 219-231, May.

    Cited by:

    1. Andreas Hornstein & Marianna Kudlyak, 2019. "Aggregate Labor Force Participation and Unemployment and Demographic Trends," Working Paper Series 2019-7, Federal Reserve Bank of San Francisco.
    2. Francesco D'Amuri & Marta De Philippis & Elisa Guglielminetti & Salvatore Lo Bello, 2021. "Natural unemployment and activity rates: flow-based determinants and implications for price dynamics," Questioni di Economia e Finanza (Occasional Papers) 599, Bank of Italy, Economic Research and International Relations Area.
    3. Regis Barnichon & Davide Debortoli & Christian Matthes, 2020. "Understanding the Size of the Government Spending Multiplier: It's in the Sign," Working Paper Series 2021-01, Federal Reserve Bank of San Francisco.
    4. Richard K. Crump & Stefano Eusepi & Marc Giannoni & Aysegul Sahin, 2019. "A unified approach to measuring u," Staff Reports 889, Federal Reserve Bank of New York.
    5. Barnichon, Régis, 2019. "The Ins and Outs of Labor Force Participation," CEPR Discussion Papers 13481, C.E.P.R. Discussion Papers.
    6. Maik Wolters, 2017. "How the Baby Boomers' Retirement Wave Distorts Model-Based Output Gap Estimates," Jena Economic Research Papers 2017-008, Friedrich-Schiller-University Jena.
    7. Stephanie Aaronson & Mary C. Daly & William L. Wascher & David W. Wilcox, 2019. "Okun Revisited: Who Benefits Most from a Strong Economy," Finance and Economics Discussion Series 2019-072, Board of Governors of the Federal Reserve System (U.S.).
    8. Bruce Fallick & Pawel Krolikowski, 2019. "Excess Persistence in Employment of Disadvantaged Workers," Working Papers 18-01R, Federal Reserve Bank of Cleveland.
    9. Frohm, Erik, 2020. "Labor shortages and wage growth," Working Paper Series 394, Sveriges Riksbank (Central Bank of Sweden).
    10. D’Amuri, Francesco & De Philippis, Marta & Guglielminetti, Elisa & Lo Bello, Salvatore, 2022. "Slack and prices during Covid-19: Accounting for labor market participation," Labour Economics, Elsevier, vol. 75(C).
    11. Richard K. Crump & Christopher J. Nekarda & Nicolas Petrosky-Nadeau, 2020. "Unemployment Rate Benchmarks," Finance and Economics Discussion Series 2020-072, Board of Governors of the Federal Reserve System (U.S.).
    12. 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.
    13. Yuelin Liu, 2022. "How structural is unemployment in the United States?," Economic Inquiry, Western Economic Association International, vol. 60(3), pages 1258-1276, July.
    14. Blasques, Francisco & Hoogerkamp, Meindert Heres & Koopman, Siem Jan & van de Werve, Ilka, 2021. "Dynamic factor models with clustered loadings: Forecasting education flows using unemployment data," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1426-1441.
    15. Regis Barnichon & Geert Mesters, 2017. "How Tight Is the U.S. Labor Market?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.
    16. Brand, Claus & Obstbaum, Meri & Coenen, Günter & Sondermann, David & Lydon, Reamonn & Ajevskis, Viktors & Hammermann, Felix & Angino, Siria & Hernborg, Nils & Basso, Henrique & Hertweck, Matthias & Bi, 2021. "Employment and the conduct of monetary policy in the euro area," Occasional Paper Series 275, European Central Bank.
    17. Alonso, Andrés M. & Galeano, Pedro & Peña, Daniel, 2020. "A robust procedure to build dynamic factor models with cluster structure," Journal of Econometrics, Elsevier, vol. 216(1), pages 35-52.
    18. Regis Barnichon & Christian Matthes, 2017. "The Natural Rate of Unemployment over the Past 100 Years," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.
    19. Alexandre Ounnas, 2020. "Job Polarization and the Labor Market: A Worker Flow Analysis," LIDAM Discussion Papers IRES 2020010, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    20. Barnichon, Régis & Matthes, Christian, 2016. "Gaussian Mixture Approximations of Impulse Responses and The Non-Linear Effects of Monetary Shocks," CEPR Discussion Papers 11374, C.E.P.R. Discussion Papers.
    21. Bart Hobijn & Ayşegül Şahin, 2021. "Maximum Employment and the Participation Cycle," NBER Working Papers 29222, National Bureau of Economic Research, Inc.
    22. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23, Federal Reserve Bank of Cleveland.

  5. Regis Barnichon & Geert Mesters, 2017. "How Tight Is the U.S. Labor Market?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.

    Cited by:

    1. Lael Brainard, 2017. "Why Opportunity and Inclusion Matter to America’s Economic Strength : a speech at the Opportunity and Inclusive Growth Institute Conference, sponsored by the Federal Reserve Bank of Minneapolis, May 2," Speech 953, Board of Governors of the Federal Reserve System (U.S.).
    2. Janet L. Yellen, 2017. "Inflation, Uncertainty, and Monetary Policy : a speech at the \"Prospects for Growth: Reassessing the Fundamentals\" 59th Annual Meeting of the National Association for Business Economics, C," Speech 971, Board of Governors of the Federal Reserve System (U.S.).

  6. S. J. Koopman & G. Mesters, 2017. "Empirical Bayes Methods for Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 99(3), pages 486-498, July.
    See citations under working paper version above.
  7. G. Mesters & S. J. Koopman & M. Ooms, 2016. "Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 659-687, April.
    See citations under working paper version above.
  8. Mesters, G. & Koopman, S.J., 2014. "Generalized dynamic panel data models with random effects for cross-section and time," Journal of Econometrics, Elsevier, vol. 180(2), pages 127-140.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 18 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-MAC: Macroeconomics (11) 2014-07-13 2015-04-25 2019-02-11 2019-02-25 2019-05-20 2019-05-27 2019-07-22 2020-04-20 2020-05-11 2021-08-09 2021-08-16. Author is listed
  2. NEP-ECM: Econometrics (8) 2011-07-13 2012-11-03 2015-04-25 2017-09-24 2019-05-20 2019-05-27 2020-04-20 2021-08-09. Author is listed
  3. NEP-ORE: Operations Research (7) 2011-07-13 2012-11-03 2014-07-13 2014-11-17 2020-05-11 2021-08-09 2021-08-16. Author is listed
  4. NEP-ETS: Econometric Time Series (5) 2011-07-13 2012-08-23 2012-11-03 2015-04-25 2017-09-24. Author is listed
  5. NEP-MON: Monetary Economics (5) 2014-07-13 2015-04-25 2019-02-11 2019-02-25 2020-05-11. Author is listed
  6. NEP-CBA: Central Banking (4) 2015-04-25 2019-02-11 2019-02-25 2020-04-20
  7. NEP-DCM: Discrete Choice Models (2) 2014-11-22 2015-04-25
  8. NEP-EEC: European Economics (2) 2015-04-25 2021-08-09
  9. NEP-LAW: Law & Economics (2) 2014-11-22 2015-04-25
  10. NEP-BEC: Business Economics (1) 2019-05-20
  11. NEP-GEN: Gender (1) 2020-05-11
  12. NEP-ISF: Islamic Finance (1) 2021-08-16
  13. NEP-URE: Urban & Real Estate Economics (1) 2015-04-25

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