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Sylvain Barde

Personal Details

First Name:Sylvain
Middle Name:
Last Name:Barde
Suffix:Dr
RePEc Short-ID:pba530
[This author has chosen not to make the email address public]
http://sylvain.barde.free.fr
School of Economics Keynes College University of Kent Canterbury, Kent CT2 7NP United Kingdom

Affiliation

(50%) Centre de recherche en Économie (OFCE)
Sciences économiques
Sciences Po

Paris, France
http://www.ofce.sciences-po.fr/
RePEc:edi:ofcspfr (more details at EDIRC)

(50%) School of Economics
University of Kent

Canterbury, United Kingdom
http://www.kent.ac.uk/economics/
RePEc:edi:deukcuk (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Sylvain Barde, 2022. "Bayesian Estimation of Large-Scale Simulation Models with Gaussian Process Regression Surrogates," Studies in Economics 2203, School of Economics, University of Kent.
  2. Barde, Sylvain & Klein, Alexander, 2021. "Transportation Costs in the Age of Highways: Evidence from United States 1955-2010," CAGE Online Working Paper Series 597, Competitive Advantage in the Global Economy (CAGE).
  3. Sylvain Barde, 2019. "Macroeconomic simulation comparison with a multivariate extension of the Markov Information Criterion," Studies in Economics 1908, School of Economics, University of Kent.
  4. Sylvain Barde, 2017. "A Practical, Accurate, Information Criterion for Nth Order Markov Processes," Post-Print hal-03471817, HAL.
  5. Sylvain Barde & Sander van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," SciencePo Working papers Main hal-03458672, HAL.
  6. Sylvain Barde & Sander van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," SciencePo Working papers Main hal-03458672, HAL.
  7. Sylvain Barde & Ofce Observatoire Français Des Conjonctures Économiques, 2016. "Direct comparison of agent-based models of herding in financial markets," Post-Print hal-03604749, HAL.
  8. Sylvain Barde, 2015. "Direct calibration and comparison of agent-based herding models of financial markets," Studies in Economics 1507, School of Economics, University of Kent.
  9. Jérôme Creel, 2015. "Introduction," SciencePo Working papers Main hal-03459518, HAL.
  10. Sylvain Barde, 2015. "A fast algorithm for finding the confidence set of large collections of models," Studies in Economics 1519, School of Economics, University of Kent.
  11. Sylvain Barde, 2015. "A Practical, Universal, Information Criterion over Nth Order Markov Processes," Studies in Economics 1504, School of Economics, University of Kent.
  12. Sylvain Barde, 2012. "Back to the future: economic rationality and maximum entropy prediction," Studies in Economics 1202, School of Economics, University of Kent.
  13. Sylvain Barde, 2012. "Of ants and voters: maximum entropy prediction and agent based models with recruitment," SciencePo Working papers Main hal-01071853, HAL.
  14. Sylvain Barde, 2012. "Of ants and voters: maximum entropy prediction and agent based models with recruitment," Post-Print hal-01071853, HAL.
  15. Sylvain Barde, 2011. "Back to the future: a simple solution to schelling segregation," Documents de Travail de l'OFCE 2011-05, Observatoire Francais des Conjonctures Economiques (OFCE).
  16. Stein Ostbye & Sylvain Barde, 2011. "Micro foundations for knowledge spillovers in spatial equilibrium models," ERSA conference papers ersa10p794, European Regional Science Association.
  17. Sylvain Barde, 2011. "Ignorance is bliss: rationality, information and equilibrium," Documents de Travail de l'OFCE 2011-04, Observatoire Francais des Conjonctures Economiques (OFCE).
  18. Sylvain Barde, 2011. "Back to the future: a simple solution to schelling segregation," SciencePo Working papers Main hal-01069479, HAL.
  19. Sarah Guillou & Lionel Nesta & Mauro Napoletano & Evens Salies & Sylvain Barde & Jean-Luc Gaffard, 2010. "L'industrie manufacturière française," Post-Print hal-03398431, HAL.
  20. Sylvain Barde & John Peirson, 2009. "Over-simplification and tractability in quasi-linear neg models," Documents de Travail de l'OFCE 2009-14, Observatoire Francais des Conjonctures Economiques (OFCE).
  21. Sylvain Barde & John Pierson, 2009. "Over-simplification and tractability in quasi-linear neg models," SciencePo Working papers Main hal-03461777, HAL.
  22. Sarah Guillou & Mauro Napoletano & Lionel Nesta & Evens Salies & Sylvain Barde & Jean-Luc Gaffard, 2009. "Mérites et limites du Pacte automobile," Post-Print hal-01071847, HAL.
  23. Sylvain Barde, 2009. "The Google thought experiment: rationality, information and equilibrium in an exchange economy," Documents de Travail de l'OFCE 2009-34, Observatoire Francais des Conjonctures Economiques (OFCE).
  24. Sylvain Barde, 2008. "A Generalised Variable Elasticity of Substitution Model of New Economic Geography," Documents de Travail de l'OFCE 2008-33, Observatoire Francais des Conjonctures Economiques (OFCE).
  25. Sylvain Barde, 2008. "A Generalized Variable Elasticity of Substitution Model of New Economic Geography," SciencePo Working papers Main hal-01066187, HAL.
  26. Sylvain Barde & Jean-Luc Gaffard, 2008. "La variable géographique en économie: interactions spatiales et action publique," Post-Print halshs-00375503, HAL.
  27. Sylvain Barde, 2008. "The spatial structure of French wages: Investigating the robustness of two-stage least squares estimations of spatial autoregressive models," Documents de Travail de l'OFCE 2008-03, Observatoire Francais des Conjonctures Economiques (OFCE).
  28. Sylvain Barde, 2008. "Agglomeration incentives in a spatial Cournot model with increasing returns to scale," Post-Print hal-03415835, HAL.
  29. Sylvain Barde, 2008. "Knowledge spillovers and the equilibrium location of vertically linked industries: the return of the black hole," Documents de Travail de l'OFCE 2008-05, Observatoire Francais des Conjonctures Economiques (OFCE).
  30. Sylvain Barde & Jean-Luc Gaffard, 2008. "La variable géographique en économie : interactions spatiales et action publique. Introduction," Post-Print hal-01071845, HAL.
  31. Sylvain Barde, 2008. "Rendements croissants et structure spatiale des salaires en France," Post-Print hal-03389303, HAL.
  32. Sylvain Barde, 2008. "Knowledge spillovers and the equilibrium location of vertically linked industries: the return of the black hole," SciencePo Working papers Main hal-03605869, HAL.
  33. Sylvain Barde, 2007. "Stable Partial Agglomeration in a New Economic Geography Model with Urban Frictions," SciencePo Working papers Main hal-01073764, HAL.
  34. Sylvain Barde, 2007. "Modelling the Folk Theorem: A Spatial Cournot Model with Explicit Increasing Returns to Scale," Studies in Economics 0701, School of Economics, University of Kent.
  35. Sylvain Barde, 2007. "Stable Partial Agglomeration in a New Economic Geography Model with Urban Frictions," SciencePo Working papers Main hal-01073764, HAL.

    repec:spo:wpmain:info:hdl:2441/5fafm6me7k8omq5jbo61urqq27 is not listed on IDEAS
    repec:spo:wpmain:info:hdl:2441/eu4vqp9ompqllr09hc01g3029 is not listed on IDEAS
    repec:spo:wpmain:info:hdl:2441/6159 is not listed on IDEAS
    repec:spo:wpmain:info:hdl:2441/6441 is not listed on IDEAS
    repec:spo:wpmain:info:hdl:2441/5l6uh8ogmqildh09h56484hg0 is not listed on IDEAS
    repec:spo:wpmain:info:hdl:2441/eu4vqp9ompqllr09hc02i31ok is not listed on IDEAS
    repec:spo:wpmain:info:hdl:2441/7kr9gv74ut9ngo58gia97t83i7 is not listed on IDEAS

Articles

  1. Alessandro Cusimano & Fabio Mazzola & Sylvain Barde, 2021. "Place-based policy in southern Italy: evidence from a dose–response approach," Regional Studies, Taylor & Francis Journals, vol. 55(8), pages 1442-1458, August.
  2. Barde, Sylvain, 2020. "Macroeconomic simulation comparison with a multivariate extension of the Markov information criterion," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
  3. Sylvain Barde, 2017. "A Practical, Accurate, Information Criterion for Nth Order Markov Processes," Computational Economics, Springer;Society for Computational Economics, vol. 50(2), pages 281-324, August.
  4. Barde, Sylvain, 2016. "Direct comparison of agent-based models of herding in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 329-353.
  5. Sylvain Barde, 2015. "Back to the Future: Economic Self-Organisation and Maximum Entropy Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 337-358, February.
  6. Alessandro Cusimano & Sylvain Barde & Fabio Mazzola, 2015. "Selection bias, incentivi alle imprese e sviluppo locale: una valutazione ex-post," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2015(3 Suppl.), pages 103-128.
  7. Sylvain Barde, 2012. "Comments on the paper. "Reconstructing Aggregate Dynamics in Heterogeneous Agents Models" by D. Delli Gatti et al," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 21-24.
  8. Sylvain Barde, 2012. "Of Ants and Voters. Maximum Entropy Prediction of Agent-Based Models with Recruitment," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 147-175.
  9. Sylvain Barde, 2012. "Reply to Comments," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 37-39.
  10. Sylvain Barde & John Peirson, 2011. "Non-negativity and agglomeration behaviour of the quasi-linear logarithmic model of NEG," Letters in Spatial and Resource Sciences, Springer, vol. 4(1), pages 91-101, March.
  11. Sylvain Barde, 2010. "Knowledge spillovers, black holes and the equilibrium location of vertically linked industries," Journal of Economic Geography, Oxford University Press, vol. 10(1), pages 27-53, January.
  12. Sylvain Barde, 2010. "Increasing Returns and the Spatial Structure of French Wages," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 73-91.
  13. Sylvain Barde, 2008. "Agglomeration incentives in a spatial Cournot model with increasing returns to scale," Letters in Spatial and Resource Sciences, Springer, vol. 1(1), pages 27-35, July.
  14. Sylvain Barde & Jean-Luc Gaffard, 2008. "Introduction," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(1), pages 137-140.
  15. Sylvain Barde, 2008. "Rendements croissants et structure spatiale des salaires en France," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(1), pages 179-201.

    RePEc:fce:ofcrev:y:2008:i:104:p:179-201 is not listed on IDEAS
    RePEc:fce:ofcrev:y:2008:i:104:p:137-40 is not listed on IDEAS

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. Sylvain Barde, 2022. "Bayesian Estimation of Large-Scale Simulation Models with Gaussian Process Regression Surrogates," Studies in Economics 2203, School of Economics, University of Kent.

    Cited by:

    1. Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.

  2. Barde, Sylvain & Klein, Alexander, 2021. "Transportation Costs in the Age of Highways: Evidence from United States 1955-2010," CAGE Online Working Paper Series 597, Competitive Advantage in the Global Economy (CAGE).

    Cited by:

    1. Klein, Alexander & Crafts, Nicholas, 2023. "Unconditional Convergence in Manufacturing Productivity across U.S. States: What the Long-Run Data Show," CAGE Online Working Paper Series 660, Competitive Advantage in the Global Economy (CAGE).
    2. Klein, Alexander, 2023. "From the Manufacturing Belt to the Rust Belt. Spatial Inequalities in the United States: An Interdisciplinary Literature Review," CAGE Online Working Paper Series 657, Competitive Advantage in the Global Economy (CAGE).
    3. Ignatov, Augustin, 2024. "European highway networks, transportation costs, and regional income," Regional Science and Urban Economics, Elsevier, vol. 104(C).

  3. Sylvain Barde, 2019. "Macroeconomic simulation comparison with a multivariate extension of the Markov Information Criterion," Studies in Economics 1908, School of Economics, University of Kent.

    Cited by:

    1. Barde, Sylvain, 2024. "Bayesian estimation of large-scale simulation models with Gaussian process regression surrogates," Computational Statistics & Data Analysis, Elsevier, vol. 196(C).
    2. Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.
    3. Sylvain Barde, 2022. "Bayesian Estimation of Large-Scale Simulation Models with Gaussian Process Regression Surrogates," Studies in Economics 2203, School of Economics, University of Kent.
    4. Dave, Chetan & Sorge, Marco M., 2021. "Equilibrium indeterminacy and sunspot tales," European Economic Review, Elsevier, vol. 140(C).
    5. Alperen Bektas & Valentino Piana & René Schumann, 2021. "A meso-level empirical validation approach for agent-based computational economic models drawing on micro-data: a use case with a mobility mode-choice model," SN Business & Economics, Springer, vol. 1(6), pages 1-25, June.
    6. Donovan Platt, 2022. "Bayesian Estimation of Economic Simulation Models Using Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 599-650, February.
    7. Dave, Chetan & Sorge, Marco, 2023. "Fat Tailed DSGE Models: A Survey and New Results," Working Papers 2023-3, University of Alberta, Department of Economics.

  4. Sylvain Barde, 2017. "A Practical, Accurate, Information Criterion for Nth Order Markov Processes," Post-Print hal-03471817, HAL.

    Cited by:

    1. T. Balint & F. Lamperti & Antoine Mandel & Mauro Napoletano & A. Roventini & A. Sapio, 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01906003, HAL.
    2. Barde, Sylvain, 2024. "Bayesian estimation of large-scale simulation models with Gaussian process regression surrogates," Computational Statistics & Data Analysis, Elsevier, vol. 196(C).
    3. Zhang, Jinyu & Zhang, Qiaosen & Li, Yong & Wang, Qianchao, 2023. "Sequential Bayesian inference for agent-based models with application to the Chinese business cycle," Economic Modelling, Elsevier, vol. 126(C).
    4. Ernesto Carrella & Richard M. Bailey & Jens Koed Madsen, 2018. "Indirect inference through prediction," Papers 1807.01579, arXiv.org.
    5. Seri, Raffaello & Martinoli, Mario & Secchi, Davide & Centorrino, Samuele, 2021. "Model calibration and validation via confidence sets," Econometrics and Statistics, Elsevier, vol. 20(C), pages 62-86.
    6. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2017. "Faraway, so Close: Coupled Climate and Economic Dynamics in an Agent-Based Integrated Assessment Model," LEM Papers Series 2017/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. Sylvain Barde & Sander van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," SciencePo Working papers Main hal-03458672, HAL.
    8. Guerini, Mattia & Moneta, Alessio, 2017. "A method for agent-based models validation," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 125-141.
    9. Francesco Lamperti & Andrea Roventini & Amir Sani, 2017. "Agent-Based Model Calibration using Machine Learning Surrogates," Papers 1703.10639, arXiv.org, revised Apr 2017.
    10. Grazzini, Jakob & Richiardi, Matteo G. & Tsionas, Mike, 2017. "Bayesian estimation of agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 26-47.
    11. Chenkai Wang & Junji Ren & Peng Yang, 2024. "Alleviating Non-identifiability: a High-fidelity Calibration Objective for Financial Market Simulation with Multivariate Time Series Data," Papers 2407.16566, arXiv.org, revised Oct 2024.
    12. Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.
    13. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
    14. Platt, Donovan & Gebbie, Tim, 2018. "Can agent-based models probe market microstructure?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1092-1106.
    15. Gennaro Catapano & Francesco Franceschi & Valentina Michelangeli & Michele Loberto, 2021. "Macroprudential Policy Analysis via an Agent Based Model of the Real Estate Sector," Temi di discussione (Economic working papers) 1338, Bank of Italy, Economic Research and International Relations Area.
    16. Barde, Sylvain, 2020. "Macroeconomic simulation comparison with a multivariate extension of the Markov information criterion," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    17. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2019. "Validation of Agent-Based Models in Economics and Finance," Post-Print halshs-02375423, HAL.
    18. Sander Hoog, 2019. "Surrogate Modelling in (and of) Agent-Based Models: A Prospectus," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1245-1263, March.
    19. Nils Bertschinger & Iurii Mozzhorin, 2021. "Bayesian estimation and likelihood-based comparison of agent-based volatility models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(1), pages 173-210, January.
    20. Dawid, Herbert & Harting, Philipp & Neugart, Michael & Hoog, Sander van der, 2019. "Macroeconomics with heterogeneous agent models: fostering transparency, reproducibility and replication," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 113126, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    21. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    22. Dyer, Joel & Cannon, Patrick & Farmer, J. Doyne & Schmon, Sebastian M., 2024. "Black-box Bayesian inference for agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 161(C).
    23. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    24. Lamperti, Francesco, 2018. "An information theoretic criterion for empirical validation of simulation models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 83-106.
    25. Donovan Platt, 2022. "Bayesian Estimation of Economic Simulation Models Using Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 599-650, February.

  5. Sylvain Barde & Sander van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," SciencePo Working papers Main hal-03458672, HAL.

    Cited by:

    1. Francesco Lamperti & Andrea Roventini & Amir Sani, 2017. "Agent-Based Model Calibration using Machine Learning Surrogates," Papers 1703.10639, arXiv.org, revised Apr 2017.
    2. Farmer, J. Doyne & Heinrich, Torsten & Sabuco, Juan, 2019. "A simulation of the insurance industry: The problem of risk model homogeneity," INET Oxford Working Papers 2019-12, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    3. Herbert Dawid & Philipp Harting & Sander van der Hoog, 2019. "Manager remuneration, share buybacks, and firm performance," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 28(3), pages 681-706.
    4. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
    5. Domenico Delli Gatti & Jakob Grazzini, 2019. "Rising to the Challenge: Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models," CESifo Working Paper Series 7894, CESifo.
    6. Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.
    7. Donovan Platt, 2019. "A Comparison of Economic Agent-Based Model Calibration Methods," Papers 1902.05938, arXiv.org.
    8. Leonardo Bargigli & Luca Riccetti & Alberto Russo & Mauro Gallegati, 2020. "Network calibration and metamodeling of a financial accelerator agent based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(2), pages 413-440, April.
    9. Siyan Chen & Saul Desiderio, 2022. "A Regression-Based Calibration Method for Agent-Based Models," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 687-700, February.
    10. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2019. "Validation of Agent-Based Models in Economics and Finance," Post-Print halshs-02375423, HAL.
    11. Severin Reissl, 2021. "Heterogeneous expectations, forecasting behaviour and policy experiments in a hybrid Agent-based Stock-flow-consistent model," Journal of Evolutionary Economics, Springer, vol. 31(1), pages 251-299, January.
    12. Sander Hoog, 2019. "Surrogate Modelling in (and of) Agent-Based Models: A Prospectus," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1245-1263, March.
    13. Dawid, Herbert & Harting, Philipp & Neugart, Michael & Hoog, Sander van der, 2019. "Macroeconomics with heterogeneous agent models: fostering transparency, reproducibility and replication," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 113126, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    14. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    15. Siyan Chen & Saul Desiderio, 2022. "Calibration of Agent-Based Models by Means of Meta-Modeling and Nonparametric Regression," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1457-1478, December.
    16. Guus ten Broeke & George van Voorn & Arend Ligtenberg & Jaap Molenaar, 2021. "The Use of Surrogate Models to Analyse Agent-Based Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 24(2), pages 1-3.
    17. Alperen Bektas & Valentino Piana & René Schumann, 2021. "A meso-level empirical validation approach for agent-based computational economic models drawing on micro-data: a use case with a mobility mode-choice model," SN Business & Economics, Springer, vol. 1(6), pages 1-25, June.

  6. Sylvain Barde & Sander van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," SciencePo Working papers Main hal-03458672, HAL.

    Cited by:

    1. Francesco Lamperti & Andrea Roventini & Amir Sani, 2017. "Agent-Based Model Calibration using Machine Learning Surrogates," Papers 1703.10639, arXiv.org, revised Apr 2017.
    2. Farmer, J. Doyne & Heinrich, Torsten & Sabuco, Juan, 2019. "A simulation of the insurance industry: The problem of risk model homogeneity," INET Oxford Working Papers 2019-12, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    3. Herbert Dawid & Philipp Harting & Sander van der Hoog, 2019. "Manager remuneration, share buybacks, and firm performance," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 28(3), pages 681-706.
    4. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
    5. Domenico Delli Gatti & Jakob Grazzini, 2019. "Rising to the Challenge: Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models," CESifo Working Paper Series 7894, CESifo.
    6. Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.
    7. Donovan Platt, 2019. "A Comparison of Economic Agent-Based Model Calibration Methods," Papers 1902.05938, arXiv.org.
    8. Leonardo Bargigli & Luca Riccetti & Alberto Russo & Mauro Gallegati, 2020. "Network calibration and metamodeling of a financial accelerator agent based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(2), pages 413-440, April.
    9. Siyan Chen & Saul Desiderio, 2022. "A Regression-Based Calibration Method for Agent-Based Models," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 687-700, February.
    10. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2019. "Validation of Agent-Based Models in Economics and Finance," Post-Print halshs-02375423, HAL.
    11. Severin Reissl, 2021. "Heterogeneous expectations, forecasting behaviour and policy experiments in a hybrid Agent-based Stock-flow-consistent model," Journal of Evolutionary Economics, Springer, vol. 31(1), pages 251-299, January.
    12. Sander Hoog, 2019. "Surrogate Modelling in (and of) Agent-Based Models: A Prospectus," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1245-1263, March.
    13. Dawid, Herbert & Harting, Philipp & Neugart, Michael & Hoog, Sander van der, 2019. "Macroeconomics with heterogeneous agent models: fostering transparency, reproducibility and replication," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 113126, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    14. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    15. Siyan Chen & Saul Desiderio, 2022. "Calibration of Agent-Based Models by Means of Meta-Modeling and Nonparametric Regression," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1457-1478, December.
    16. Guus ten Broeke & George van Voorn & Arend Ligtenberg & Jaap Molenaar, 2021. "The Use of Surrogate Models to Analyse Agent-Based Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 24(2), pages 1-3.
    17. Alperen Bektas & Valentino Piana & René Schumann, 2021. "A meso-level empirical validation approach for agent-based computational economic models drawing on micro-data: a use case with a mobility mode-choice model," SN Business & Economics, Springer, vol. 1(6), pages 1-25, June.

  7. Sylvain Barde & Ofce Observatoire Français Des Conjonctures Économiques, 2016. "Direct comparison of agent-based models of herding in financial markets," Post-Print hal-03604749, HAL.

    Cited by:

    1. Gallegati, Mauro & Kirman, Alan, 2019. "20 years of WEHIA: A journey in search of a safer road," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 5-14.
    2. Zhang, Jinyu & Zhang, Qiaosen & Li, Yong & Wang, Qianchao, 2023. "Sequential Bayesian inference for agent-based models with application to the Chinese business cycle," Economic Modelling, Elsevier, vol. 126(C).
    3. Schmitt, Noemi & Westerhoff, Frank H., 2019. "Trend followers, contrarians and fundamentalists: Explaining the dynamics of financial markets," BERG Working Paper Series 151, Bamberg University, Bamberg Economic Research Group.
    4. Seri, Raffaello & Martinoli, Mario & Secchi, Davide & Centorrino, Samuele, 2021. "Model calibration and validation via confidence sets," Econometrics and Statistics, Elsevier, vol. 20(C), pages 62-86.
    5. Sylvain Barde & Sander van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," SciencePo Working papers Main hal-03458672, HAL.
    6. Guerini, Mattia & Moneta, Alessio, 2017. "A method for agent-based models validation," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 125-141.
    7. Francesco Lamperti & Andrea Roventini & Amir Sani, 2017. "Agent-Based Model Calibration using Machine Learning Surrogates," Papers 1703.10639, arXiv.org, revised Apr 2017.
    8. Lux, Thomas, 2017. "Estimation of agent-based models using sequential Monte Carlo methods," Economics Working Papers 2017-07, Christian-Albrechts-University of Kiel, Department of Economics.
    9. Lucas Fievet & Didier Sornette, 2018. "Calibrating emergent phenomena in stock markets with agent based models," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
    10. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
    11. Donovan Platt, 2019. "A Comparison of Economic Agent-Based Model Calibration Methods," Papers 1902.05938, arXiv.org.
    12. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    13. Emna Mnif & Anis Jarboui & M. Kabir Hassan & Khaireddine Mouakhar, 2020. "Big data tools for Islamic financial analysis," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(1), pages 10-21, January.
    14. Platt, Donovan & Gebbie, Tim, 2018. "Can agent-based models probe market microstructure?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1092-1106.
    15. Zhenxi Chen & Thomas Lux, 2018. "Estimation of Sentiment Effects in Financial Markets: A Simulated Method of Moments Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 711-744, October.
    16. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    17. Barde, Sylvain, 2020. "Macroeconomic simulation comparison with a multivariate extension of the Markov information criterion," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    18. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2019. "Validation of Agent-Based Models in Economics and Finance," Post-Print halshs-02375423, HAL.
    19. Kirill S. Glavatskiy & Mikhail Prokopenko & Adrian Carro & Paul Ormerod & Michael Harré, 2021. "Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large-scale agent-based model," SN Business & Economics, Springer, vol. 1(6), pages 1-21, June.
    20. Sander Hoog, 2019. "Surrogate Modelling in (and of) Agent-Based Models: A Prospectus," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1245-1263, March.
    21. Nils Bertschinger & Iurii Mozzhorin, 2021. "Bayesian estimation and likelihood-based comparison of agent-based volatility models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(1), pages 173-210, January.
    22. Dawid, Herbert & Harting, Philipp & Neugart, Michael & Hoog, Sander van der, 2019. "Macroeconomics with heterogeneous agent models: fostering transparency, reproducibility and replication," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 113126, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    23. Venelina Nikolova & Juan E. Trinidad Segovia & Manuel Fernández-Martínez & Miguel Angel Sánchez-Granero, 2020. "A Novel Methodology to Calculate the Probability of Volatility Clusters in Financial Series: An Application to Cryptocurrency Markets," Mathematics, MDPI, vol. 8(8), pages 1-15, July.
    24. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    25. Matteo Richiardi, 2016. "Editorial," International Journal of Microsimulation, International Microsimulation Association, vol. 9(3), pages 1-4.
    26. Francesco Lamperti, 2018. "Empirical validation of simulated models through the GSL-div: an illustrative application," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 143-171, April.
    27. Donovan Platt & Tim Gebbie, 2016. "Can Agent-Based Models Probe Market Microstructure?," Papers 1611.08510, arXiv.org, revised Aug 2017.
    28. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2021. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," Papers 2102.05405, arXiv.org, revised Nov 2023.
    29. Lux, Thomas, 2018. "Estimation of agent-based models using sequential Monte Carlo methods," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 391-408.
    30. Adam Majewski & Stefano Ciliberti & Jean-Philippe Bouchaud, 2018. "Co-existence of Trend and Value in Financial Markets: Estimating an Extended Chiarella Model," Papers 1807.11751, arXiv.org.
    31. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    32. Alperen Bektas & Valentino Piana & René Schumann, 2021. "A meso-level empirical validation approach for agent-based computational economic models drawing on micro-data: a use case with a mobility mode-choice model," SN Business & Economics, Springer, vol. 1(6), pages 1-25, June.
    33. Donovan Platt & Tim Gebbie, 2016. "The Problem of Calibrating an Agent-Based Model of High-Frequency Trading," Papers 1606.01495, arXiv.org, revised Mar 2017.
    34. Majewski, Adam A. & Ciliberti, Stefano & Bouchaud, Jean-Philippe, 2020. "Co-existence of trend and value in financial markets: Estimating an extended Chiarella model," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
    35. Lamperti, Francesco, 2018. "An information theoretic criterion for empirical validation of simulation models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 83-106.
    36. Donovan Platt, 2022. "Bayesian Estimation of Economic Simulation Models Using Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 599-650, February.

  8. Sylvain Barde, 2015. "Direct calibration and comparison of agent-based herding models of financial markets," Studies in Economics 1507, School of Economics, University of Kent.

    Cited by:

    1. Guerini, Mattia & Moneta, Alessio, 2017. "A method for agent-based models validation," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 125-141.
    2. Pruna, Radu T. & Polukarov, Maria & Jennings, Nicholas R., 2018. "Avoiding regret in an agent-based asset pricing model," Finance Research Letters, Elsevier, vol. 24(C), pages 273-277.
    3. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2020. "Loss aversion in an agent-based asset pricing model," Quantitative Finance, Taylor & Francis Journals, vol. 20(2), pages 275-290, February.
    4. Zhenxi Chen & Thomas Lux, 2018. "Estimation of Sentiment Effects in Financial Markets: A Simulated Method of Moments Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 711-744, October.
    5. Donovan Platt & Tim Gebbie, 2016. "Can Agent-Based Models Probe Market Microstructure?," Papers 1611.08510, arXiv.org, revised Aug 2017.
    6. Donovan Platt & Tim Gebbie, 2016. "The Problem of Calibrating an Agent-Based Model of High-Frequency Trading," Papers 1606.01495, arXiv.org, revised Mar 2017.
    7. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2016. "A new structural stochastic volatility model of asset pricing and its stylized facts," Papers 1604.08824, arXiv.org.

  9. Sylvain Barde, 2015. "A Practical, Universal, Information Criterion over Nth Order Markov Processes," Studies in Economics 1504, School of Economics, University of Kent.

    Cited by:

    1. Johann Lussange & Ivan Lazarevich & Sacha Bourgeois-Gironde & Stefano Palminteri & Boris Gutkin, 2021. "Modelling Stock Markets by Multi-agent Reinforcement Learning," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 113-147, January.
    2. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2017. "Faraway, so Close: Coupled Climate and Economic Dynamics in an Agent-Based Integrated Assessment Model," LEM Papers Series 2017/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Sylvain Barde & Sander van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," SciencePo Working papers Main hal-03458672, HAL.
    4. Francesco Lamperti & Andrea Roventini & Amir Sani, 2017. "Agent-Based Model Calibration using Machine Learning Surrogates," Papers 1703.10639, arXiv.org, revised Apr 2017.
    5. Francesco Lamperti, 2016. "Empirical Validation of Simulated Models through the GSL-div: an Illustrative Application," LEM Papers Series 2016/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Alexandru Mandes & Peter Winker, 2015. "Complexity and Model Comparison in Agent Based Modeling of Financial Markets," MAGKS Papers on Economics 201528, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    7. Sylvain Barde & Ofce Observatoire Français Des Conjonctures Économiques, 2016. "Direct comparison of agent-based models of herding in financial markets," Post-Print hal-03604749, HAL.
    8. Johann Lussange & Stefano Vrizzi & Stefano Palminteri & Boris Gutkin, 2024. "Modelling crypto markets by multi-agent reinforcement learning," Papers 2402.10803, arXiv.org.
    9. Johann Lussange & Stefano Vrizzi & Sacha Bourgeois-Gironde & Stefano Palminteri & Boris Gutkin, 2023. "Stock Price Formation: Precepts from a Multi-Agent Reinforcement Learning Model," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1523-1544, April.
    10. Francesco Lamperti, 2015. "An Information Theoretic Criterion for Empirical Validation of Time Series Models," LEM Papers Series 2015/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    11. Sylvain Barde, 2015. "Direct calibration and comparison of agent-based herding models of financial markets," Studies in Economics 1507, School of Economics, University of Kent.
    12. Sander van der Hoog, 2017. "Deep Learning in (and of) Agent-Based Models: A Prospectus," Papers 1706.06302, arXiv.org.

  10. Sylvain Barde, 2012. "Back to the future: economic rationality and maximum entropy prediction," Studies in Economics 1202, School of Economics, University of Kent.

    Cited by:

    1. Zakaria Babutsidze, 2012. "Comments on the paper "Of Ants and Voters: Maximum entropy prediction of agent-based models with recruitment" by S. Barde," Post-Print halshs-01926892, HAL.
    2. Sylvain Barde, 2012. "Of ants and voters: maximum entropy prediction and agent based models with recruitment," SciencePo Working papers Main hal-01071853, HAL.
    3. Farmer, J. Doyne & Kolic, Blas & Sabuco, Juan, 2021. "Estimating initial conditions for dynamical systems with incomplete information," INET Oxford Working Papers 2021-20, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.

  11. Sylvain Barde, 2012. "Of ants and voters: maximum entropy prediction and agent based models with recruitment," SciencePo Working papers Main hal-01071853, HAL.

    Cited by:

    1. Sylvain Barde, 2012. "Back to the future: economic rationality and maximum entropy prediction," Studies in Economics 1202, School of Economics, University of Kent.

  12. Sylvain Barde, 2012. "Of ants and voters: maximum entropy prediction and agent based models with recruitment," Post-Print hal-01071853, HAL.

    Cited by:

    1. Sylvain Barde, 2012. "Back to the future: economic rationality and maximum entropy prediction," Studies in Economics 1202, School of Economics, University of Kent.

  13. Stein Ostbye & Sylvain Barde, 2011. "Micro foundations for knowledge spillovers in spatial equilibrium models," ERSA conference papers ersa10p794, European Regional Science Association.

    Cited by:

    1. Kii, Masanobu & Nakanishi, Hitomi & Nakamura, Kazuki & Doi, Kenji, 2016. "Transportation and spatial development: An overview and a future direction," Transport Policy, Elsevier, vol. 49(C), pages 148-158.

  14. Sylvain Barde, 2011. "Ignorance is bliss: rationality, information and equilibrium," Documents de Travail de l'OFCE 2011-04, Observatoire Francais des Conjonctures Economiques (OFCE).

    Cited by:

    1. Sylvain Barde, 2011. "Back to the future: a simple solution to schelling segregation," Documents de Travail de l'OFCE 2011-05, Observatoire Francais des Conjonctures Economiques (OFCE).

  15. Sylvain Barde, 2008. "A Generalised Variable Elasticity of Substitution Model of New Economic Geography," Documents de Travail de l'OFCE 2008-33, Observatoire Francais des Conjonctures Economiques (OFCE).

    Cited by:

    1. Igor G. Pospelov & Stanislav A. Radionov, 2014. "On The Social Efficiency In Monopolistic Competitioin Models," HSE Working papers WP BRP 80/EC/2014, National Research University Higher School of Economics.
    2. Kristian Behrens & Sergey Kichko & Philip Ushchev & Sergei Kichko, 2018. "Intersectoral Markup Divergence," CESifo Working Paper Series 6965, CESifo.

  16. Sylvain Barde, 2008. "A Generalized Variable Elasticity of Substitution Model of New Economic Geography," SciencePo Working papers Main hal-01066187, HAL.

    Cited by:

    1. Igor G. Pospelov & Stanislav A. Radionov, 2014. "On The Social Efficiency In Monopolistic Competitioin Models," HSE Working papers WP BRP 80/EC/2014, National Research University Higher School of Economics.
    2. Kristian Behrens & Sergey Kichko & Philip Ushchev & Sergei Kichko, 2018. "Intersectoral Markup Divergence," CESifo Working Paper Series 6965, CESifo.

  17. Sylvain Barde, 2008. "The spatial structure of French wages: Investigating the robustness of two-stage least squares estimations of spatial autoregressive models," Documents de Travail de l'OFCE 2008-03, Observatoire Francais des Conjonctures Economiques (OFCE).

    Cited by:

    1. Vinko Mustra & Blanka Skrabic & Pasko Burnac, 2011. "Spatial determinants of sectors wage inequaities: Analysis for the region of Croatia," ERSA conference papers ersa10p573, European Regional Science Association.

  18. Sylvain Barde, 2007. "Stable Partial Agglomeration in a New Economic Geography Model with Urban Frictions," SciencePo Working papers Main hal-01073764, HAL.

    Cited by:

    1. Sylvain Barde, 2007. "Modelling the Folk Theorem: A Spatial Cournot Model with Explicit Increasing Returns to Scale," Studies in Economics 0701, School of Economics, University of Kent.

  19. Sylvain Barde, 2007. "Stable Partial Agglomeration in a New Economic Geography Model with Urban Frictions," SciencePo Working papers Main hal-01073764, HAL.

    Cited by:

    1. Sylvain Barde, 2007. "Modelling the Folk Theorem: A Spatial Cournot Model with Explicit Increasing Returns to Scale," Studies in Economics 0701, School of Economics, University of Kent.

Articles

  1. Alessandro Cusimano & Fabio Mazzola & Sylvain Barde, 2021. "Place-based policy in southern Italy: evidence from a dose–response approach," Regional Studies, Taylor & Francis Journals, vol. 55(8), pages 1442-1458, August.

    Cited by:

    1. Zehong Wang & Shaojian Wang & Jieyu Wang & Yuqu Wang, 2022. "Development zones and urban economic performance in China: Direct impact and channel effects," Growth and Change, Wiley Blackwell, vol. 53(4), pages 1762-1782, December.
    2. Boto-García, David & Pérez, Levi, 2023. "The effect of high-speed rail connectivity and accessibility on tourism seasonality," Journal of Transport Geography, Elsevier, vol. 107(C).
    3. Kaimeng Li & Shuang Gao & Yuantao Liao & Ke Luo & Shaojian Wang, 2022. "The Impact of Development Zones on China’s Urbanization from the Perspectives of the Population, Land, and the Economy," Land, MDPI, vol. 11(10), pages 1-16, October.

  2. Barde, Sylvain, 2020. "Macroeconomic simulation comparison with a multivariate extension of the Markov information criterion," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    See citations under working paper version above.
  3. Sylvain Barde, 2017. "A Practical, Accurate, Information Criterion for Nth Order Markov Processes," Computational Economics, Springer;Society for Computational Economics, vol. 50(2), pages 281-324, August.
    See citations under working paper version above.
  4. Barde, Sylvain, 2016. "Direct comparison of agent-based models of herding in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 329-353.
    See citations under working paper version above.
  5. Alessandro Cusimano & Sylvain Barde & Fabio Mazzola, 2015. "Selection bias, incentivi alle imprese e sviluppo locale: una valutazione ex-post," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2015(3 Suppl.), pages 103-128.

    Cited by:

    1. Chiara Bocci & Annalisa Caloffi & Marco Mariani & Alessandro Sterlacchini, 2023. "Evaluating Public Support to the Investment Activities of Business Firms: A Multilevel Meta-Regression Analysis of Italian Studies," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(1), pages 1-34, March.

  6. Sylvain Barde, 2012. "Of Ants and Voters. Maximum Entropy Prediction of Agent-Based Models with Recruitment," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 147-175.

    Cited by:

    1. Carl Chiarella & Corrado Di Guilmi, 2011. "Limit Distribution of Evolving Strategies in Financial Markets," Research Paper Series 294, Quantitative Finance Research Centre, University of Technology, Sydney.
    2. Jean-Luc Gaffard & Mauro Napoletano, 2012. "Introduction - Improving the Toolbox: New Advances in Agent-Based and Computational Models," SciencePo Working papers Main hal-01053562, HAL.
    3. Sylvain Barde, 2012. "Back to the future: economic rationality and maximum entropy prediction," Studies in Economics 1202, School of Economics, University of Kent.

  7. Sylvain Barde & John Peirson, 2011. "Non-negativity and agglomeration behaviour of the quasi-linear logarithmic model of NEG," Letters in Spatial and Resource Sciences, Springer, vol. 4(1), pages 91-101, March.

    Cited by:

    1. Fabien Candau & Elisa Dienesch, 2015. "Spatial Distribution of Skills and Regional Trade Integration," Working papers of CATT hal-01885150, HAL.

  8. Sylvain Barde, 2010. "Knowledge spillovers, black holes and the equilibrium location of vertically linked industries," Journal of Economic Geography, Oxford University Press, vol. 10(1), pages 27-53, January.

    Cited by:

    1. Shixiang Wang & Minyuan Zhao, 2018. "A tale of two distances: a study of technological distance, geographic distance and multilocation firms," Journal of Economic Geography, Oxford University Press, vol. 18(5), pages 1091-1120.
    2. Álvarez, Inmaculada C. & Gude, Alberto & Orea, Luis, 2019. "Effects of inter-industry and spatial spillovers on regional productivity: Evidence from Spanish panel data," Efficiency Series Papers 2019/01, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).

  9. Sylvain Barde, 2010. "Increasing Returns and the Spatial Structure of French Wages," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 73-91.

    Cited by:

    1. Luisa Corrado & Bernard Fingleton, 2012. "Where Is The Economics In Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 210-239, May.
    2. Gabriel Ahlfeldt & Elisabetta Pietrostefani, 2017. "The Economic Effects of Density: A Synthesis," CESifo Working Paper Series 6744, CESifo.
    3. Elliott, Robert J.R. & Zhou, Ying, 2015. "Co-location and Spatial Wage Spillovers in China: The Role of Foreign Ownership and Trade," World Development, Elsevier, vol. 66(C), pages 629-644.
    4. Gabriel M. Ahfeldt & Elisabetta Pietrostefani, 2017. "The Compact City in Empirical Research: A Quantitative Literature Review," SERC Discussion Papers 0215, Centre for Economic Performance, LSE.
    5. Ahfeldt, Gabriel M. & Pietrostefani, Elisabetta, 2017. "The compact city in empirical research: A quantitative literature review," LSE Research Online Documents on Economics 83638, London School of Economics and Political Science, LSE Library.
    6. Flora Bellone & Patrick Musso & Lionel Nesta & Frédéric Warzynski, 2016. "International Trade and Firm-Level Markups when Location and Quality Matter," SciencePo Working papers Main halshs-01062918, HAL.
    7. Fichet de Clairfontaine, Aurélien & Hammer, Christoph, 2016. "Trade Costs and Income in European Regions: Evidence from a regional bilateral trade dataset," Department of Economics Working Paper Series 220, WU Vienna University of Economics and Business.
    8. Bernard FINGLETON & Silvia PALOMBI, 2013. "The Wage Curve Reconsidered: Is It Truly An 'Empirical Law Of Economics'?," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 38, pages 49-92.

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 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-URE: Urban and Real Estate Economics (9) 2007-06-11 2007-06-11 2008-07-14 2008-12-14 2011-03-19 2011-06-18 2011-11-14 2012-07-29 2022-01-10. Author is listed
  2. NEP-ECM: Econometrics (7) 2015-03-13 2015-05-30 2015-10-10 2017-07-23 2018-06-11 2019-06-17 2022-09-19. Author is listed
  3. NEP-GEO: Economic Geography (7) 2007-06-11 2007-06-11 2008-07-14 2008-07-14 2008-12-14 2011-03-19 2012-07-29. Author is listed
  4. NEP-CMP: Computational Economics (3) 2017-07-23 2019-03-25 2019-06-17
  5. NEP-ORE: Operations Research (3) 2015-10-10 2018-06-11 2019-06-17
  6. NEP-CSE: Economics of Strategic Management (2) 2008-07-14 2012-07-29
  7. NEP-HME: Heterodox Microeconomics (2) 2017-07-23 2019-06-17
  8. NEP-KNM: Knowledge Management and Knowledge Economy (2) 2008-07-14 2012-07-29
  9. NEP-DCM: Discrete Choice Models (1) 2022-09-19
  10. NEP-ENE: Energy Economics (1) 2022-01-10
  11. NEP-FOR: Forecasting (1) 2015-10-10
  12. NEP-GTH: Game Theory (1) 2011-03-19
  13. NEP-HIS: Business, Economic and Financial History (1) 2022-01-10
  14. NEP-IND: Industrial Organization (1) 2007-06-11
  15. NEP-INO: Innovation (1) 2012-07-29
  16. NEP-MAC: Macroeconomics (1) 2019-06-17
  17. NEP-MIC: Microeconomics (1) 2011-03-19
  18. NEP-TID: Technology and Industrial Dynamics (1) 2008-07-14
  19. NEP-TRE: Transport Economics (1) 2022-01-10
  20. NEP-UPT: Utility Models and Prospect Theory (1) 2012-04-10

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