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Nalan Baştürk
(Nalan Basturk)

Personal Details

First Name:Nalan
Middle Name:
Last Name:Basturk
Suffix:
RePEc Short-ID:pba1173
[This author has chosen not to make the email address public]
https://www.maastrichtuniversity.nl/n.basturk

Affiliation

Vakgroep Kwantitatieve Economie
School of Business and Economics
Maastricht University

Maastricht, Netherlands
http://www.maastrichtuniversity.nl/web/Faculties/SBE/Theme/Departments/QuantitativeEconomics.htm
RePEc:edi:dqmaanl (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart (L.F.) Hoogerheide & Herman (H.K.) van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Tinbergen Institute Discussion Papers 18-076/III, Tinbergen Institute.
  2. Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2017. "Bayesian Analysis of Boundary and Near-Boundary Evidence in Econometric Models with Reduced Rank," Tinbergen Institute Discussion Papers 17-058/III, Tinbergen Institute.
  3. Nalan Basturk & Stefano Grassi & Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2017. "The R package MitISEM: Efficient and robust simulation procedures for Bayesian inference," Working Paper 2017/10, Norges Bank.
  4. Nalan Basturk & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2016. "Time-varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies," Tinbergen Institute Discussion Papers 16-099/III, Tinbergen Institute.
  5. Baştürk, N. & Grassi, S. & Hoogerheide, L. & van Dijk, H.K., 2016. "Parallelization experience with four canonical econometric models using ParMitISEM," Research Memorandum 013, Maastricht University, Graduate School of Business and Economics (GSBE).
  6. Nalan Basturk & Pinar Ceyhan & Herman K. van Dijk, 2014. "Bayesian Forecasting of US Growth using Basic Time Varying Parameter Models and Expectations Data," Tinbergen Institute Discussion Papers 14-119/III, Tinbergen Institute, revised 14 Sep 2014.
  7. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
  8. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series," Tinbergen Institute Discussion Papers 13-011/III, Tinbergen Institute.
  9. Almeida e Santos Nogueira, R.J. & Basturk, N. & Kaymak, U. & Costa Sousa, J.M., 2013. "Estimation of flexible fuzzy GARCH models for conditional density estimation," ERIM Report Series Research in Management ERS-2013-013-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  10. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
  11. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended New Keynesian Phillips Curve Models with Non-filtered Data," Tinbergen Institute Discussion Papers 13-090/III, Tinbergen Institute.
  12. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended Phillips Curve Models with non-filtered Data," Koç University-TUSIAD Economic Research Forum Working Papers 1321, Koc University-TUSIAD Economic Research Forum.
  13. Nalan Basturk & Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2012. "The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation," Tinbergen Institute Discussion Papers 12-096/III, Tinbergen Institute.
  14. Arnold Zellner (posthumously) & Tomohiro Ando & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2012. "Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo," Tinbergen Institute Discussion Papers 12-098/III, Tinbergen Institute.
  15. Arnold Zellner & Tomohiro Ando & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2011. "Instrumental Variables, Errors in Variables, and Simultaneous Equations Models: Applicability and Limitations of Direct Monte Carlo," Tinbergen Institute Discussion Papers 11-137/4, Tinbergen Institute.
  16. David Ardia & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2010. "A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihood," Tinbergen Institute Discussion Papers 10-059/4, Tinbergen Institute.
  17. Basturk, N. & Paap, R. & van Dijk, D.J.C., 2010. "Financial Development and Convergence Clubs," Econometric Institute Research Papers EI 2010-52, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  18. Nalan Basturk & Richard Paap & Dick van Dijk, 2008. "Structural Differences in Economic Growth," Tinbergen Institute Discussion Papers 08-085/4, Tinbergen Institute.

Articles

  1. Baştürk, Nalan & Grassi, Stefano & Hoogerheide, Lennart & Opschoor, Anne & van Dijk, Herman K., 2017. "The R Package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i01).
  2. Nalan Baştürk & Stefano Grassi & Lennart Hoogerheide & Herman K. Van Dijk, 2016. "Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM," Econometrics, MDPI, vol. 4(1), pages 1-20, March.
  3. Nalan Baştürk & Roberto Casarin & Francesco Ravazzolo & Herman K. Van Dijk, 2016. "Computational Complexity and Parallelization in Bayesian Econometric Analysis," Econometrics, MDPI, vol. 4(1), pages 1-3, February.
  4. Nalan Baştürk & Cem Çakmakli & S. Pinar Ceyhan & Herman K. Van Dijk, 2014. "Posterior‐Predictive Evidence On Us Inflation Using Extended New Keynesian Phillips Curve Models With Non‐Filtered Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1164-1182, November.
  5. Tervonen, Tommi & van Valkenhoef, Gert & Baştürk, Nalan & Postmus, Douwe, 2013. "Hit-And-Run enables efficient weight generation for simulation-based multiple criteria decision analysis," European Journal of Operational Research, Elsevier, vol. 224(3), pages 552-559.
  6. Nalan Baştürk & Richard Paap & Dick van Dijk, 2012. "Structural differences in economic growth: an endogenous clustering approach," Applied Economics, Taylor & Francis Journals, vol. 44(1), pages 119-134, January.
  7. Ardia, David & Baştürk, Nalan & Hoogerheide, Lennart & van Dijk, Herman K., 2012. "A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3398-3414.

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.

    Mentioned in:

    1. The Rise of Bayesian Econometrics
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2014-11-20 03:57:00

Working papers

  1. Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart (L.F.) Hoogerheide & Herman (H.K.) van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Tinbergen Institute Discussion Papers 18-076/III, Tinbergen Institute.

    Cited by:

    1. Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
    2. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    3. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    4. Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Papers 2009.09592, arXiv.org.
    5. van Dijk Herman K., 2024. "Challenges and Opportunities for Twenty First Century Bayesian Econometricians: A Personal View," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 155-176, April.
    6. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    7. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    8. Berggrun, Luis & Cardona, Emilio & Lizarzaburu, Edmundo, 2020. "Profitability of momentum strategies in Latin America," International Review of Financial Analysis, Elsevier, vol. 70(C).
    9. Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.
    10. Casarin, Roberto & Grassi, Stefano & Ravazzolo, Francesco & van Dijk, Herman K., 2023. "A flexible predictive density combination for large financial data sets in regular and crisis periods," Journal of Econometrics, Elsevier, vol. 237(2).
    11. David T. Frazier & Ruben Loaiza-Maya & Gael M. Martin & Bonsoo Koo, 2021. "Loss-Based Variational Bayes Prediction," Papers 2104.14054, arXiv.org, revised May 2022.
    12. Roberto Casarin & Stefano Grassi & Francesco Ravazzollo & Herman K. van Dijk, 2019. "Forecast Density Combinations with Dynamic Learning for Large Data Sets in Economics and Finance," Tinbergen Institute Discussion Papers 19-025/III, Tinbergen Institute.
    13. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2021. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Tinbergen Institute Discussion Papers 21-016/III, Tinbergen Institute.

  2. Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2017. "Bayesian Analysis of Boundary and Near-Boundary Evidence in Econometric Models with Reduced Rank," Tinbergen Institute Discussion Papers 17-058/III, Tinbergen Institute.

    Cited by:

    1. M Hashem Pesaran & Ron P Smith, 2017. "Posterior Means and Precisions of the Coefficients in Linear Models with Highly Collinear Regressors," BCAM Working Papers 1707, Birkbeck Centre for Applied Macroeconomics.
    2. van Dijk Herman K., 2024. "Challenges and Opportunities for Twenty First Century Bayesian Econometricians: A Personal View," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 155-176, April.
    3. Christian Aßmann & Jens Boysen-Hogrefe & Markus Pape, 2024. "Post-processing for Bayesian analysis of reduced rank regression models with orthonormality restrictions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(3), pages 577-609, September.
    4. Pesaran, M. Hashem & Smith, Ron P., 2019. "A Bayesian analysis of linear regression models with highly collinear regressors," Econometrics and Statistics, Elsevier, vol. 11(C), pages 1-21.
    5. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    6. Casarin Roberto & Peruzzi Antonio, 2024. "A Dynamic Latent-Space Model for Asset Clustering," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 379-402, April.

  3. Nalan Basturk & Stefano Grassi & Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2017. "The R package MitISEM: Efficient and robust simulation procedures for Bayesian inference," Working Paper 2017/10, Norges Bank.

    Cited by:

    1. Mengheng Li & Ivan Mendieta-Munoz, 2019. "The multivariate simultaneous unobserved components model and identification via heteroskedasticity," Working Paper Series 2019/08, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    2. Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Working Paper 2018/10, Norges Bank.
    3. Dellaportas, Petros & Tsionas, Mike G., 2019. "Importance sampling from posterior distributions using copula-like approximations," Journal of Econometrics, Elsevier, vol. 210(1), pages 45-57.
    4. Geweke, John & Durham, Garland, 2019. "Sequentially adaptive Bayesian learning algorithms for inference and optimization," Journal of Econometrics, Elsevier, vol. 210(1), pages 4-25.
    5. Nalan Basturk & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2016. "Time-varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies," Tinbergen Institute Discussion Papers 16-099/III, Tinbergen Institute.

  4. Nalan Basturk & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2016. "Time-varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies," Tinbergen Institute Discussion Papers 16-099/III, Tinbergen Institute.

    Cited by:

    1. Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Working Paper 2018/10, Norges Bank.
    2. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    3. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.

  5. Baştürk, N. & Grassi, S. & Hoogerheide, L. & van Dijk, H.K., 2016. "Parallelization experience with four canonical econometric models using ParMitISEM," Research Memorandum 013, Maastricht University, Graduate School of Business and Economics (GSBE).

    Cited by:

    1. Jamie L. Cross & Lennart Hoogerheide & Paul Labonne & Herman K. van Dijk, 2024. "Flexible Negative Binomial Mixtures for Credible Mode Inference in Heterogeneous Count Data from Finance, Economics and Bioinformatics," Tinbergen Institute Discussion Papers 24-056/III, Tinbergen Institute.
    2. Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Working Paper 2018/10, Norges Bank.
    3. Casarin, Roberto & Grassi, Stefano & Ravazzolo, Francesco & van Dijk, Herman K., 2023. "A flexible predictive density combination for large financial data sets in regular and crisis periods," Journal of Econometrics, Elsevier, vol. 237(2).
    4. Stefano Grassi & Marco Lorusso & Francesco Ravazzolo, 2021. "Adaptive Importance Sampling for DSGE Models," BEMPS - Bozen Economics & Management Paper Series BEMPS84, Faculty of Economics and Management at the Free University of Bozen.
    5. Geweke, John & Durham, Garland, 2019. "Sequentially adaptive Bayesian learning algorithms for inference and optimization," Journal of Econometrics, Elsevier, vol. 210(1), pages 4-25.
    6. Nalan Basturk & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2016. "Time-varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies," Tinbergen Institute Discussion Papers 16-099/III, Tinbergen Institute.

  6. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.

    Cited by:

    1. Nalan Baştürk & Stefano Grassi & Lennart Hoogerheide & Herman K. Van Dijk, 2016. "Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM," Econometrics, MDPI, vol. 4(1), pages 1-20, March.
    2. Thomas R. Dyckman, 2016. "Significance Testing: We Can Do Better," Abacus, Accounting Foundation, University of Sydney, vol. 52(2), pages 319-342, June.

  7. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series," Tinbergen Institute Discussion Papers 13-011/III, Tinbergen Institute.

    Cited by:

    1. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Interactions between Eurozone and US Booms and Busts: A Bayesian Panel Markov-switching VAR Model," Tinbergen Institute Discussion Papers 13-142/III, Tinbergen Institute, revised 01 Nov 2014.
    2. Michal Andrle & Jan Bruha & Mr. Serhat Solmaz, 2013. "Inflation and Output Comovement in the Euro Area: Love at Second Sight?," IMF Working Papers 2013/192, International Monetary Fund.
    3. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    4. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.

  8. Almeida e Santos Nogueira, R.J. & Basturk, N. & Kaymak, U. & Costa Sousa, J.M., 2013. "Estimation of flexible fuzzy GARCH models for conditional density estimation," ERIM Report Series Research in Management ERS-2013-013-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.

  9. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.

    Cited by:

    1. Glötzl, Florentin & Aigner, Ernest, 2015. "Pluralism in the Market of Science? A citation network analysis of economic research at universities in Vienna," Ecological Economic Papers 5, WU Vienna University of Economics and Business.
    2. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.

  10. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended New Keynesian Phillips Curve Models with Non-filtered Data," Tinbergen Institute Discussion Papers 13-090/III, Tinbergen Institute.

    Cited by:

    1. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Interactions between Eurozone and US Booms and Busts: A Bayesian Panel Markov-switching VAR Model," Tinbergen Institute Discussion Papers 13-142/III, Tinbergen Institute, revised 01 Nov 2014.
    2. Joshua C.C. Chan & Angelia L. Grant, 2016. "Reconciling output gaps: unobserved components model and Hodrick-Prescott filter," CAMA Working Papers 2016-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Khalaf, Lynda & Lin, Zhenjiang, 2021. "Projection-based inference with particle swarm optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 128(C).
    4. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    5. Altug, Sumru & Çakmaklı, Cem, 2015. "Forecasting Inflation using Survey Expectations and Target Inflation: Evidence for Brazil and Turkey," CEPR Discussion Papers 10419, C.E.P.R. Discussion Papers.
    6. Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
    7. Grassi, Stefano & Ravazzolo, Francesco & Vespignani, Joaquin & Vocalelli, Giorgio, 2023. "Global money supply and energy and non-energy commodity prices: A MS-TV-VAR approach," Working Papers 2023-01, University of Tasmania, Tasmanian School of Business and Economics.
    8. Nalan Baştürk & Stefano Grassi & Lennart Hoogerheide & Herman K. Van Dijk, 2016. "Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM," Econometrics, MDPI, vol. 4(1), pages 1-20, March.
    9. Marcellino, Massimiliano & Kapetanios, George & Khalaf, Lynda, 2015. "Factor based identification-robust inference in IV regressions," CEPR Discussion Papers 10390, C.E.P.R. Discussion Papers.
    10. Francesca Rondina, 2018. "Estimating unobservable inflation expectations in the New Keynesian Phillips Curve," Working Papers 1804E, University of Ottawa, Department of Economics.
    11. Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
    12. Yingying XU & Zhixin LIU & Jaime ORTIZ, 2018. "Actual and Expected Inflation in the U.S.: A Time-Frequency View," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 42-62, December.
    13. Nalan Basturk & Pinar Ceyhan & Herman K. van Dijk, 2014. "Bayesian Forecasting of US Growth using Basic Time Varying Parameter Models and Expectations Data," Tinbergen Institute Discussion Papers 14-119/III, Tinbergen Institute, revised 14 Sep 2014.
    14. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.

  11. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended Phillips Curve Models with non-filtered Data," Koç University-TUSIAD Economic Research Forum Working Papers 1321, Koc University-TUSIAD Economic Research Forum.

    Cited by:

    1. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Interactions between Eurozone and US Booms and Busts: A Bayesian Panel Markov-switching VAR Model," Tinbergen Institute Discussion Papers 13-142/III, Tinbergen Institute, revised 01 Nov 2014.
    2. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    3. Altug, Sumru & Çakmaklı, Cem, 2015. "Forecasting Inflation using Survey Expectations and Target Inflation: Evidence for Brazil and Turkey," CEPR Discussion Papers 10419, C.E.P.R. Discussion Papers.
    4. Michal Andrle & Jan Bruha & Mr. Serhat Solmaz, 2013. "Inflation and Output Comovement in the Euro Area: Love at Second Sight?," IMF Working Papers 2013/192, International Monetary Fund.
    5. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    6. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    7. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.

  12. Nalan Basturk & Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2012. "The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation," Tinbergen Institute Discussion Papers 12-096/III, Tinbergen Institute.

    Cited by:

    1. Hoogerheide, Lennart & Opschoor, Anne & van Dijk, Herman K., 2012. "A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation," Journal of Econometrics, Elsevier, vol. 171(2), pages 101-120.

  13. Arnold Zellner (posthumously) & Tomohiro Ando & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2012. "Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo," Tinbergen Institute Discussion Papers 12-098/III, Tinbergen Institute.

    Cited by:

    1. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended Phillips Curve Models with non-filtered Data," Koç University-TUSIAD Economic Research Forum Working Papers 1321, Koc University-TUSIAD Economic Research Forum.
    2. Nalan Baştürk & Stefano Grassi & Lennart Hoogerheide & Herman K. Van Dijk, 2016. "Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM," Econometrics, MDPI, vol. 4(1), pages 1-20, March.
    3. Baştürk, N. & Grassi, S. & Hoogerheide, L. & Opschoor, A. & van Dijk, H.K., 2015. "The R package MitISEM : efficient and robust simulation procedures for Bayesian inference," Research Memorandum 011, Maastricht University, Graduate School of Business and Economics (GSBE).
    4. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series," Tinbergen Institute Discussion Papers 13-011/III, Tinbergen Institute.
    5. Martin Halla & Martina Zweimüller, 2014. "Parental Response to Early Human Capital Shocks: Evidence from the Chernobyl Accident," NRN working papers 2014-01, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
    6. Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2017. "Bayesian Analysis of Boundary and Near-Boundary Evidence in Econometric Models with Reduced Rank," Tinbergen Institute Discussion Papers 17-058/III, Tinbergen Institute.
    7. Frühwirth-Schnatter, Sylvia & Halla, Martin & Posekany, Alexandra & Pruckner, Gerald J. & Schober, Thomas, 2014. "The Quantity and Quality of Children: A Semi-Parametric Bayesian IV Approach," IZA Discussion Papers 8024, Institute of Labor Economics (IZA).
    8. Nalan Baştürk & Cem Çakmakli & S. Pinar Ceyhan & Herman K. Van Dijk, 2014. "Posterior‐Predictive Evidence On Us Inflation Using Extended New Keynesian Phillips Curve Models With Non‐Filtered Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1164-1182, November.
    9. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    10. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    11. Pedro Saramago & Karl Claxton & Nicky J. Welton & Marta Soares, 2020. "Bayesian econometric modelling of observational data for cost‐effectiveness analysis: establishing the value of negative pressure wound therapy in the healing of open surgical wounds," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1575-1593, October.
    12. Geweke, John & Durham, Garland, 2019. "Sequentially adaptive Bayesian learning algorithms for inference and optimization," Journal of Econometrics, Elsevier, vol. 210(1), pages 4-25.
    13. Chuanming Gao & Kajal Lahiri, 2019. "A Comparison of Some Bayesian and Classical Procedures for Simultaneous Equation Models with Weak Instruments," Econometrics, MDPI, vol. 7(3), pages 1-28, July.

  14. Arnold Zellner & Tomohiro Ando & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2011. "Instrumental Variables, Errors in Variables, and Simultaneous Equations Models: Applicability and Limitations of Direct Monte Carlo," Tinbergen Institute Discussion Papers 11-137/4, Tinbergen Institute.

    Cited by:

    1. Cogley, Timothy & Startz, Richard, 2012. "Bayesian IV: the normal case with multiple endogenous variables," University of California at Santa Barbara, Economics Working Paper Series qt40v0x246, Department of Economics, UC Santa Barbara.

  15. David Ardia & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2010. "A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihood," Tinbergen Institute Discussion Papers 10-059/4, Tinbergen Institute.

    Cited by:

    1. Bauwens, Luc & Dufays, Arnaud & Rombouts, Jeroen V.K., 2014. "Marginal likelihood for Markov-switching and change-point GARCH models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 508-522.
    2. Bauwens, Luc & Carpantier, Jean-François & Dufays, Arnaud, 2015. "Autoregressive moving average infinite hidden markov-switching models," LIDAM Discussion Papers CORE 2015007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Chan, Joshua & Eisenstat, Eric, 2012. "Marginal Likelihood Estimation with the Cross-Entropy Method," MPRA Paper 40051, University Library of Munich, Germany.
    4. Gholamreza Hajargasht & D.S. Prasada Rao, 2019. "Multilateral Index Number Systems for International Price Comparisons: Properties, Existence and Uniqueness," CEPA Working Papers Series WP032019, School of Economics, University of Queensland, Australia.
    5. Perrakis, Konstantinos & Ntzoufras, Ioannis & Tsionas, Efthymios G., 2014. "On the use of marginal posteriors in marginal likelihood estimation via importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 54-69.
    6. Lennart Hoogerheide & Richard Kleijn & Francesco Ravazzolo & Herman K. Van Dijk & Marno Verbeek, 2010. "Forecast accuracy and economic gains from Bayesian model averaging using time-varying weights," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 251-269.
    7. Ardia, David & Baştürk, Nalan & Hoogerheide, Lennart & van Dijk, Herman K., 2012. "A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3398-3414.
    8. Reichl Johannes, 2020. "Estimating marginal likelihoods from the posterior draws through a geometric identity," Monte Carlo Methods and Applications, De Gruyter, vol. 26(3), pages 205-221, September.
    9. Fiorentini, G. & Planas, C. & Rossi, A., 2012. "The marginal likelihood of dynamic mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2650-2662.
    10. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    11. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    12. David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.
    13. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    14. Nalan Baştürk & Stefano Grassi & Lennart Hoogerheide & Herman K. Van Dijk, 2016. "Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM," Econometrics, MDPI, vol. 4(1), pages 1-20, March.
    15. Ardia, David & Hoogerheide, Lennart F., 2014. "GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts," Economics Letters, Elsevier, vol. 123(2), pages 187-190.
    16. Gael M. Martin & David T. Frazier & Christian P. Robert, 2022. "Computing Bayes: From Then `Til Now," Monash Econometrics and Business Statistics Working Papers 14/22, Monash University, Department of Econometrics and Business Statistics.
    17. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "An automated prior robustness analysis in Bayesian model comparison," CAMA Working Papers 2019-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    18. Guidolin, Massimo & Ravazzolo, Francesco & Tortora, Andrea Donato, 2013. "Alternative econometric implementations of multi-factor models of the U.S. financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(2), pages 87-111.
    19. Jean-François Carpantier & Arnaud Dufays, 2014. "Specific Markov-switching behaviour for ARMA parameters," Working Papers hal-01821134, HAL.
    20. Arnold Zellner & Tomohiro Ando & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2011. "Instrumental Variables, Errors in Variables, and Simultaneous Equations Models: Applicability and Limitations of Direct Monte Carlo," Tinbergen Institute Discussion Papers 11-137/4, Tinbergen Institute.
    21. Gael M. Martin & David T. Frazier & Christian P. Robert, 2021. "Approximating Bayes in the 21st Century," Monash Econometrics and Business Statistics Working Papers 24/21, Monash University, Department of Econometrics and Business Statistics.
    22. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    23. Lukasz Gatarek & Lennart Hoogerheide & Koen Hooning & Herman K. van Dijk, 2013. "Censored Posterior and Predictive Likelihood in Left-Tail Prediction for Accurate Value at Risk Estimation," Tinbergen Institute Discussion Papers 13-060/III, Tinbergen Institute, revised 06 Mar 2014.
    24. Joshua C. C. Chan & Eric Eisenstat, 2018. "Bayesian model comparison for time‐varying parameter VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 509-532, June.
    25. Loza-Reyes, E. & Hurn, M.A. & Robinson, A., 2014. "Classification of molecular sequence data using Bayesian phylogenetic mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 81-95.
    26. Geweke, John & Durham, Garland, 2019. "Sequentially adaptive Bayesian learning algorithms for inference and optimization," Journal of Econometrics, Elsevier, vol. 210(1), pages 4-25.

  16. Basturk, N. & Paap, R. & van Dijk, D.J.C., 2010. "Financial Development and Convergence Clubs," Econometric Institute Research Papers EI 2010-52, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2021. "Bayes estimates of multimodal density features using DNA and Economic Data," Tinbergen Institute Discussion Papers 21-017/III, Tinbergen Institute.

  17. Nalan Basturk & Richard Paap & Dick van Dijk, 2008. "Structural Differences in Economic Growth," Tinbergen Institute Discussion Papers 08-085/4, Tinbergen Institute.

    Cited by:

    1. Eberhardt, Markus & Teal, Francis, 2009. "Econometrics for Grumblers: A New Look at the Literature on Cross-Country Growth Empirics," MPRA Paper 15813, University Library of Munich, Germany.
    2. Michelle Gilmartin & Dimitris Korobilis, 2012. "On Regional Unemployment: An Empirical Examination of the Determinants of Geographical Differentials in the UK," Scottish Journal of Political Economy, Scottish Economic Society, vol. 59(2), pages 179-195, May.
    3. Morier, Bruno & Teles, Vladimir Kühl, 2016. "A Time-Varying Markov-Switching Model For Economic Growth," Macroeconomic Dynamics, Cambridge University Press, vol. 20(6), pages 1550-1580, September.

Articles

  1. Baştürk, Nalan & Grassi, Stefano & Hoogerheide, Lennart & Opschoor, Anne & van Dijk, Herman K., 2017. "The R Package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i01).
    See citations under working paper version above.
  2. Nalan Baştürk & Stefano Grassi & Lennart Hoogerheide & Herman K. Van Dijk, 2016. "Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM," Econometrics, MDPI, vol. 4(1), pages 1-20, March.
    See citations under working paper version above.
  3. Nalan Baştürk & Cem Çakmakli & S. Pinar Ceyhan & Herman K. Van Dijk, 2014. "Posterior‐Predictive Evidence On Us Inflation Using Extended New Keynesian Phillips Curve Models With Non‐Filtered Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1164-1182, November.
    See citations under working paper version above.
  4. Tervonen, Tommi & van Valkenhoef, Gert & Baştürk, Nalan & Postmus, Douwe, 2013. "Hit-And-Run enables efficient weight generation for simulation-based multiple criteria decision analysis," European Journal of Operational Research, Elsevier, vol. 224(3), pages 552-559.

    Cited by:

    1. Govindan, Kannan & Kadziński, Miłosz & Ehling, Ronja & Miebs, Grzegorz, 2019. "Selection of a sustainable third-party reverse logistics provider based on the robustness analysis of an outranking graph kernel conducted with ELECTRE I and SMAA," Omega, Elsevier, vol. 85(C), pages 1-15.
    2. Ru, Zice & Liu, Jiapeng & Kadziński, Miłosz & Liao, Xiuwu, 2022. "Bayesian ordinal regression for multiple criteria choice and ranking," European Journal of Operational Research, Elsevier, vol. 299(2), pages 600-620.
    3. Ciomek, Krzysztof & Kadziński, Miłosz & Tervonen, Tommi, 2017. "Heuristics for selecting pair-wise elicitation questions in multiple criteria choice problems," European Journal of Operational Research, Elsevier, vol. 262(2), pages 693-707.
    4. Anna Labijak-Kowalska & Miłosz Kadziński, 2023. "Exact and stochastic methods for robustness analysis in the context of Imprecise Data Envelopment Analysis," Operational Research, Springer, vol. 23(1), pages 1-34, March.
    5. Kadziński, Miłosz & Wójcik, Michał & Ciomek, Krzysztof, 2022. "Review and experimental comparison of ranking and choice procedures for constructing a univocal recommendation in a preference disaggregation setting," Omega, Elsevier, vol. 113(C).
    6. Vetschera, Rudolf, 2017. "Deriving rankings from incomplete preference information: A comparison of different approaches," European Journal of Operational Research, Elsevier, vol. 258(1), pages 244-253.
    7. Patrick Gasser & Marco Cinelli & Anna Labijak & Matteo Spada & Peter Burgherr & Miłosz Kadziński & Božidar Stojadinović, 2020. "Quantifying Electricity Supply Resilience of Countries with Robust Efficiency Analysis," Energies, MDPI, vol. 13(7), pages 1-35, March.
    8. Luca Anzilli & Silvio Giove, 2020. "Multi-criteria and medical diagnosis for application to health insurance systems: a general approach through non-additive measures," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 43(2), pages 559-582, December.
    9. R. Pelissari & M. C. Oliveira & S. Ben Amor & A. Kandakoglu & A. L. Helleno, 2020. "SMAA methods and their applications: a literature review and future research directions," Annals of Operations Research, Springer, vol. 293(2), pages 433-493, October.
    10. Corrente, Salvatore & Figueira, José Rui & Greco, Salvatore, 2014. "The SMAA-PROMETHEE method," European Journal of Operational Research, Elsevier, vol. 239(2), pages 514-522.
    11. Durbach, Ian N. & Calder, Jon M., 2016. "Modelling uncertainty in stochastic multicriteria acceptability analysis," Omega, Elsevier, vol. 64(C), pages 13-23.
    12. Arcidiacono, Sally Giuseppe & Corrente, Salvatore & Greco, Salvatore, 2018. "GAIA-SMAA-PROMETHEE for a hierarchy of interacting criteria," European Journal of Operational Research, Elsevier, vol. 270(2), pages 606-624.
    13. Corrente, Salvatore & Figueira, José Rui & Greco, Salvatore & Słowiński, Roman, 2017. "A robust ranking method extending ELECTRE III to hierarchy of interacting criteria, imprecise weights and stochastic analysis," Omega, Elsevier, vol. 73(C), pages 1-17.
    14. Mavrotas, George & Pechak, Olena & Siskos, Eleftherios & Doukas, Haris & Psarras, John, 2015. "Robustness analysis in Multi-Objective Mathematical Programming using Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 240(1), pages 193-201.
    15. Angilella, Silvia & Corrente, Salvatore & Greco, Salvatore, 2015. "Stochastic multiobjective acceptability analysis for the Choquet integral preference model and the scale construction problem," European Journal of Operational Research, Elsevier, vol. 240(1), pages 172-182.
    16. Corrente, S. & Figueira, J.R. & Greco, S., 2021. "Pairwise comparison tables within the deck of cards method in multiple criteria decision aiding," European Journal of Operational Research, Elsevier, vol. 291(2), pages 738-756.
    17. Durbach, Ian & Lahdelma, Risto & Salminen, Pekka, 2014. "The analytic hierarchy process with stochastic judgements," European Journal of Operational Research, Elsevier, vol. 238(2), pages 552-559.
    18. Kadziński, Miłosz & Cinelli, Marco & Ciomek, Krzysztof & Coles, Stuart R. & Nadagouda, Mallikarjuna N. & Varma, Rajender S. & Kirwan, Kerry, 2018. "Co-constructive development of a green chemistry-based model for the assessment of nanoparticles synthesis," European Journal of Operational Research, Elsevier, vol. 264(2), pages 472-490.
    19. Dias, Luis C. & Antunes, Carlos Henggeler & Dantas, Guilherme & de Castro, Nivalde & Zamboni, Lucca, 2018. "A multi-criteria approach to sort and rank policies based on Delphi qualitative assessments and ELECTRE TRI: The case of smart grids in Brazil," Omega, Elsevier, vol. 76(C), pages 100-111.
    20. Kadziński, Miłosz & Tervonen, Tommi & Rui Figueira, José, 2015. "Robust multi-criteria sorting with the outranking preference model and characteristic profiles," Omega, Elsevier, vol. 55(C), pages 126-140.
    21. van Valkenhoef, Gert & Tervonen, Tommi, 2016. "Entropy-optimal weight constraint elicitation with additive multi-attribute utility models," Omega, Elsevier, vol. 64(C), pages 1-12.
    22. Zeng, Jing & Wang, Zhenjun & Chen, Guobin, 2021. "Biological characteristics of energy conversion in carbon fixation by microalgae," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    23. Kadziński, Miłosz & Tervonen, Tommi, 2013. "Robust multi-criteria ranking with additive value models and holistic pair-wise preference statements," European Journal of Operational Research, Elsevier, vol. 228(1), pages 169-180.
    24. Kadziński, Miłosz & Labijak, Anna & Napieraj, Małgorzata, 2017. "Integrated framework for robustness analysis using ratio-based efficiency model with application to evaluation of Polish airports," Omega, Elsevier, vol. 67(C), pages 1-18.
    25. Silvia Angilella & Maria Rosaria Pappalardo, 2022. "Performance assessment of energy companies employing Hierarchy Stochastic Multi-Attribute Acceptability Analysis," Operational Research, Springer, vol. 22(1), pages 299-370, March.
    26. Doumpos, Michael & Zopounidis, Constantin & Galariotis, Emilios, 2014. "Inferring robust decision models in multicriteria classification problems: An experimental analysis," European Journal of Operational Research, Elsevier, vol. 236(2), pages 601-611.
    27. Mastorakis, Kostis & Siskos, Eleftherios, 2016. "Value focused pharmaceutical strategy determination with multicriteria decision analysis techniques," Omega, Elsevier, vol. 59(PA), pages 84-96.
    28. Zhang, Zhiying & Liao, Huchang & Tang, Anbin, 2022. "Renewable energy portfolio optimization with public participation under uncertainty: A hybrid multi-attribute multi-objective decision-making method," Applied Energy, Elsevier, vol. 307(C).
    29. Brunelli, Matteo & Corrente, Salvatore, 2024. "Modeling criteria and project interactions in portfolio decision analysis with the Choquet integral," Omega, Elsevier, vol. 126(C).
    30. Liu, Jiapeng & Liao, Xiuwu & Huang, Wei & Liao, Xianzhao, 2019. "Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision," Omega, Elsevier, vol. 83(C), pages 1-13.
    31. Ciomek, Krzysztof & Kadziński, Miłosz & Tervonen, Tommi, 2017. "Heuristics for prioritizing pair-wise elicitation questions with additive multi-attribute value models," Omega, Elsevier, vol. 71(C), pages 27-45.
    32. Ru, Zice & Liu, Jiapeng & Kadziński, Miłosz & Liao, Xiuwu, 2023. "Probabilistic ordinal regression methods for multiple criteria sorting admitting certain and uncertain preferences," European Journal of Operational Research, Elsevier, vol. 311(2), pages 596-616.
    33. Miłosz Kadziński & Magdalena Martyn, 2021. "Enriched preference modeling and robustness analysis for the ELECTRE Tri-B method," Annals of Operations Research, Springer, vol. 306(1), pages 173-207, November.
    34. Silvia Angilella & Sally Giuseppe Arcidiacono & Salvatore Corrente & Salvatore Greco & Benedetto Matarazzo, 2020. "An application of the SMAA–Choquet method to evaluate the performance of sailboats in offshore regattas," Operational Research, Springer, vol. 20(2), pages 771-793, June.
    35. Arcidiacono, Sally Giuseppe & Corrente, Salvatore & Greco, Salvatore, 2024. "Inducing a probability distribution in Stochastic Multicriteria Acceptability Analysis," Omega, Elsevier, vol. 123(C).
    36. Aur'elien Hazan, 2017. "Stock-flow consistent macroeconomic model with nonuniform distributional constraint," Papers 1708.00645, arXiv.org.
    37. Angilella, Silvia & Corrente, Salvatore & Greco, Salvatore & Słowiński, Roman, 2016. "Robust Ordinal Regression and Stochastic Multiobjective Acceptability Analysis in multiple criteria hierarchy process for the Choquet integral preference model," Omega, Elsevier, vol. 63(C), pages 154-169.
    38. Costa, Ana Sara & Corrente, Salvatore & Greco, Salvatore & Figueira, José Rui & Borbinha, José, 2020. "A robust hierarchical nominal multicriteria classification method based on similarity and dissimilarity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 986-1001.
    39. Hazan, Aurélien, 2017. "Volume of the steady-state space of financial flows in a monetary stock-flow-consistent model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 589-602.
    40. Gehrlein, Jonas & Miebs, Grzegorz & Brunelli, Matteo & Kadziński, Miłosz, 2023. "An active preference learning approach to aid the selection of validators in blockchain environments," Omega, Elsevier, vol. 118(C).
    41. Zheng, Buhong & Zheng, Charles, 2015. "Fuzzy ranking of human development: A proposal," Mathematical Social Sciences, Elsevier, vol. 78(C), pages 39-47.
    42. Zhang, Xinwei & Yan, Yong & Wang, Lilin & Wang, Yang, 2024. "A ranking approach for robust portfolio decision analysis based on multilinear portfolio utility functions and incomplete preference information," Omega, Elsevier, vol. 122(C).
    43. Miłosz Kadziński & Lucia Rocchi & Grzegorz Miebs & David Grohmann & Maria Elena Menconi & Luisa Paolotti, 2018. "Multiple Criteria Assessment of Insulating Materials with a Group Decision Framework Incorporating Outranking Preference Model and Characteristic Class Profiles," Group Decision and Negotiation, Springer, vol. 27(1), pages 33-59, February.
    44. Gryazina, Elena & Polyak, Boris, 2014. "Random sampling: Billiard Walk algorithm," European Journal of Operational Research, Elsevier, vol. 238(2), pages 497-504.
    45. Ciomek, Krzysztof & Ferretti, Valentina & Kadzinski, Milosz, 2018. "Predictive analytics and disused railways requalification: insights from a Post Factum Analysis perspective," LSE Research Online Documents on Economics 85922, London School of Economics and Political Science, LSE Library.
    46. Kadziński, Miłosz & Ciomek, Krzysztof, 2021. "Active learning strategies for interactive elicitation of assignment examples for threshold-based multiple criteria sorting," European Journal of Operational Research, Elsevier, vol. 293(2), pages 658-680.
    47. Francesca Abastante & Salvatore Corrente & Salvatore Greco & Isabella M. Lami & Beatrice Mecca, 2022. "The introduction of the SRF-II method to compare hypothesis of adaptive reuse for an iconic historical building," Operational Research, Springer, vol. 22(3), pages 2397-2436, July.
    48. Haag, Fridolin & Chennu, Arjun, 2023. "Assessing whether decisions are more sensitive to preference or prediction uncertainty with a value of information approach," Omega, Elsevier, vol. 121(C).
    49. Aur'elien Hazan, 2016. "Volume of the steady-state space of financial flows in a monetary stock-flow-consistent model," Papers 1601.00822, arXiv.org, revised Jan 2017.
    50. van Valkenhoef, Gert & Tervonen, Tommi & Postmus, Douwe, 2014. "Notes on ‘Hit-And-Run enables efficient weight generation for simulation-based multiple criteria decision analysis’," European Journal of Operational Research, Elsevier, vol. 239(3), pages 865-867.
    51. Luis V. Montiel & J. Eric Bickel, 2014. "A Generalized Sampling Approach for Multilinear Utility Functions Given Partial Preference Information," Decision Analysis, INFORMS, vol. 11(3), pages 147-170, September.

  5. Nalan Baştürk & Richard Paap & Dick van Dijk, 2012. "Structural differences in economic growth: an endogenous clustering approach," Applied Economics, Taylor & Francis Journals, vol. 44(1), pages 119-134, January.

    Cited by:

    1. Tim Salimans, 2011. "Variable Selection and Functional Form Uncertainty in Cross-Country Growth Regressions," Tinbergen Institute Discussion Papers 11-012/4, Tinbergen Institute.
    2. Basturk, N. & Paap, R. & van Dijk, D.J.C., 2010. "Financial Development and Convergence Clubs," Econometric Institute Research Papers EI 2010-52, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Evaluation of technology clubs by clustering: A cautionary note," MPRA Paper 109138, University Library of Munich, Germany.
    4. Michelle Gilmartin & Dimitris Korobilis, 2012. "On Regional Unemployment: An Empirical Examination of the Determinants of Geographical Differentials in the UK," Scottish Journal of Political Economy, Scottish Economic Society, vol. 59(2), pages 179-195, May.

  6. Ardia, David & Baştürk, Nalan & Hoogerheide, Lennart & van Dijk, Herman K., 2012. "A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3398-3414.
    See citations under working paper version above.

More information

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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 20 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-ECM: Econometrics (11) 2008-09-20 2011-02-26 2011-10-09 2013-11-16 2014-11-12 2015-04-25 2016-02-12 2016-11-27 2017-07-02 2017-07-23 2018-10-15. Author is listed
  2. NEP-CMP: Computational Economics (5) 2011-10-09 2015-05-09 2016-02-12 2016-04-30 2017-07-23. Author is listed
  3. NEP-ETS: Econometric Time Series (4) 2013-08-16 2014-01-17 2015-04-25 2016-11-27
  4. NEP-MAC: Macroeconomics (4) 2013-11-16 2014-11-17 2015-04-25 2015-04-25
  5. NEP-FOR: Forecasting (3) 2012-10-06 2013-01-26 2013-11-16
  6. NEP-SOG: Sociology of Economics (3) 2014-11-12 2015-04-25 2015-04-25
  7. NEP-HIS: Business, Economic and Financial History (2) 2014-11-12 2015-04-25
  8. NEP-RMG: Risk Management (2) 2013-08-16 2018-10-15
  9. NEP-BIG: Big Data (1) 2017-07-23
  10. NEP-CBA: Central Banking (1) 2015-04-25
  11. NEP-DEV: Development (1) 2008-09-20
  12. NEP-EVO: Evolutionary Economics (1) 2018-10-15
  13. NEP-HPE: History and Philosophy of Economics (1) 2015-04-25
  14. NEP-ORE: Operations Research (1) 2016-11-27
  15. NEP-SPO: Sports and Economics (1) 2013-08-16

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