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Jean-David Fermanian

Personal Details

First Name:Jean-David
Middle Name:
Last Name:Fermanian
Suffix:
RePEc Short-ID:pfe659
[This author has chosen not to make the email address public]
https://sites.google.com/view/jdfermanian/

Affiliation

Centre de Recherche en Économie et Statistique (CREST)

Palaiseau, France
http://crest.science/
RePEc:edi:crestfr (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Books

Working papers

  1. Jean-David Fermanian & Dominique Guegan, 2021. "Fair learning with bagging," Post-Print halshs-03500906, HAL.
  2. Jean-David Fermanian & Dominique Guegan, 2021. "Fair learning with bagging," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03500906, HAL.
  3. Jean-David Fermanian & Dominique Guégan, 2021. "Fair learning with bagging," Documents de travail du Centre d'Economie de la Sorbonne 21034, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  4. Benjamin Poignard & Jean-David Fermanian, 2019. "The finite sample properties of Sparse M-estimators with Pseudo-Observations," Working Papers 2019-01, Center for Research in Economics and Statistics.
  5. Alexis Derumigny & Jean-David Fermanian, 2018. "About Kendall's regression," Working Papers 2018-01, Center for Research in Economics and Statistics.
  6. Alexis Derumigny & Jean-David Fermanian, 2017. "About tests of the “simplifying” assumption for conditional copulas," Working Papers 2017-02, Center for Research in Economics and Statistics.
  7. Jean-David Fermanian & Clément Florentin, 2016. "Multi-factor Granularity Adjustments for Market and Counterparty Risks," Working Papers 2016-35, Center for Research in Economics and Statistics.
  8. Jean-David Fermanian & Olivier Guéant & Jiang Pu, 2016. "The behavior of dealers and clients on the European corporate bond market: the case of Multi-Dealer-to-Client platforms," Working Papers 2016-34, Center for Research in Economics and Statistics.
  9. Benjamin Poignard & Jean-David Fermanian, 2016. "Vine-GARCH process: Stationarity and Asymptotic Properties," Working Papers 2016-03, Center for Research in Economics and Statistics.
  10. Jean-David Fermanian & Olivier Lopez, 2015. "Single-index copulae," Working Papers 2015-12, Center for Research in Economics and Statistics.
  11. Jean-David Fermanian & Olivier Guéant & Arnaud Rachez, 2015. "Agents' Behavior on Multi-Dealer-to-Client Bond Trading Platforms," Working Papers 2015-11, Center for Research in Economics and Statistics.
  12. Benjamin Poignard & Jean-Davis Fermanian, 2014. "Dynamic Asset Correlations Based on Vines," Working Papers 2014-46, Center for Research in Economics and Statistics.
  13. Jean-David Fermanian & Hassan Malongo, 2013. "On the Stationarity of Dynamic Conditional Correlation Models," Working Papers 2013-26, Center for Research in Economics and Statistics.
  14. Jean-David Fermanian, 2013. "The Limits of Granularity Adjustments," Working Papers 2013-27, Center for Research in Economics and Statistics.

Articles

  1. Jean-David Fermanian & Benjamin Poignard & Panos Xidonas, 2025. "Model-based vs. agnostic methods for the prediction of time-varying covariance matrices," Annals of Operations Research, Springer, vol. 346(1), pages 511-548, March.
  2. Brück, Florian & Fermanian, Jean-David & Min, Aleksey, 2023. "A corrected Clarke test for model selection and beyond," Journal of Econometrics, Elsevier, vol. 235(1), pages 105-132.
  3. Benjamin Poignard & Jean-David Fermanian, 2022. "The finite sample properties of sparse M-estimators with pseudo-observations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(1), pages 1-31, February.
  4. Derumigny, Alexis & Fermanian, Jean-David, 2019. "A classification point-of-view about conditional Kendall’s tau," Computational Statistics & Data Analysis, Elsevier, vol. 135(C), pages 70-94.
  5. Poignard, Benjamin & Fermanian, Jean-David, 2019. "Dynamic Asset Correlations Based On Vines," Econometric Theory, Cambridge University Press, vol. 35(1), pages 167-197, February.
  6. Fermanian, Jean-David & Malongo, Hassan, 2017. "On The Stationarity Of Dynamic Conditional Correlation Models," Econometric Theory, Cambridge University Press, vol. 33(3), pages 636-663, June.
  7. Fermanian, Jean-David, 2014. "The limits of granularity adjustments," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 9-25.
  8. Fermanian, Jean-David & Scaillet, Olivier, 2005. "Sensitivity analysis of VaR and Expected Shortfall for portfolios under netting agreements," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 927-958, April.
  9. Fermanian, Jean-David & Salanié, Bernard, 2004. "A Nonparametric Simulated Maximum Likelihood Estimation Method," Econometric Theory, Cambridge University Press, vol. 20(4), pages 701-734, August.

Books

  1. Malongo, Hassan, 2014. "Couverture du risque de volatilité et de corrélation dans un portefeuille," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/14035 edited by Fermanian, Jean-David.

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. Alexis Derumigny & Jean-David Fermanian, 2018. "About Kendall's regression," Working Papers 2018-01, Center for Research in Economics and Statistics.

    Cited by:

    1. Azadgar, Anahita & Luciani, Giulia & Nyka, Lucyna, 2025. "Spatial allocation of nature-based solutions in the form of public green infrastructure in relation to the socio-economic district profile–a GIS-based comparative study of Gdańsk and Rome," Land Use Policy, Elsevier, vol. 150(C).
    2. Derumigny, Alexis & Fermanian, Jean-David, 2019. "A classification point-of-view about conditional Kendall’s tau," Computational Statistics & Data Analysis, Elsevier, vol. 135(C), pages 70-94.

  2. Alexis Derumigny & Jean-David Fermanian, 2017. "About tests of the “simplifying” assumption for conditional copulas," Working Papers 2017-02, Center for Research in Economics and Statistics.

    Cited by:

    1. Portier, François & Segers, Johan, 2018. "On the weak convergence of the empirical conditional copula under a simplifying assumption," Journal of Multivariate Analysis, Elsevier, vol. 166(C), pages 160-181.
    2. Brantly Callaway & Tong Li & Irina Murtazashvili & Emmanuel Tsyawo, 2021. "Distributional Effects with Two-Sided Measurement Error: An Application to Intergenerational Income Mobility," Papers 2107.09235, arXiv.org, revised Sep 2025.
    3. Levi, Evgeny & Craiu, Radu V., 2018. "Bayesian inference for conditional copulas using Gaussian Process single index models," Computational Statistics & Data Analysis, Elsevier, vol. 122(C), pages 115-134.
    4. Guannan Liu & Wei Long & Bingduo Yang & Zongwu Cai, 2022. "Semiparametric estimation and model selection for conditional mixture copula models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 287-330, March.
    5. Bücher Axel & Jaser Miriam & Min Aleksey, 2021. "Detecting departures from meta-ellipticity for multivariate stationary time series," Dependence Modeling, De Gruyter, vol. 9(1), pages 121-140, January.
    6. Gijbels Irène & Matterne Margot, 2021. "Study of partial and average conditional Kendall’s tau," Dependence Modeling, De Gruyter, vol. 9(1), pages 82-120, January.

  3. Jean-David Fermanian & Olivier Guéant & Jiang Pu, 2016. "The behavior of dealers and clients on the European corporate bond market: the case of Multi-Dealer-to-Client platforms," Working Papers 2016-34, Center for Research in Economics and Statistics.

    Cited by:

    1. Gündüz, Yalin & Ottonello, Giorgio & Pelizzon, Loriana & Schneider, Michael & Subrahmanyam, Marti G., 2018. "Lighting up the dark: Liquidity in the German corporate bond market," SAFE Working Paper Series 230, Leibniz Institute for Financial Research SAFE.
    2. Auster, Sarah & Gottardi, Piero & Wolthoff, Ronald P., 2024. "Simultaneous Search and Adverse Selection," IZA Discussion Papers 16822, Institute of Labor Economics (IZA).
    3. Olivier Gu'eant & Jiang Pu, 2018. "Mid-price estimation for European corporate bonds: a particle filtering approach," Papers 1810.05884, arXiv.org, revised Mar 2019.
    4. Alicia Vidler & Toby Walsh, 2025. "Shifting Power: Leveraging LLMs to Simulate Human Aversion in ABMs of Bilateral Financial Exchanges, A bond market study," Papers 2503.00320, arXiv.org, revised Mar 2025.
    5. Pierre-Olivier Weill, 2020. "The search theory of OTC markets," NBER Working Papers 27354, National Bureau of Economic Research, Inc.
    6. Adel Javanmard & Jingwei Ji & Renyuan Xu, 2024. "Multi-Task Dynamic Pricing in Credit Market with Contextual Information," Papers 2410.14839, arXiv.org, revised May 2025.
    7. Riggs, Lynn & Onur, Esen & Reiffen, David & Zhu, Haoxiang, 2020. "Swap trading after Dodd-Frank: Evidence from index CDS," Journal of Financial Economics, Elsevier, vol. 137(3), pages 857-886.
    8. Xin Guo & Charles-Albert Lehalle & Renyuan Xu, 2019. "Transaction Cost Analytics for Corporate Bonds," Papers 1903.09140, arXiv.org, revised Dec 2021.

  4. Jean-David Fermanian & Olivier Guéant & Arnaud Rachez, 2015. "Agents' Behavior on Multi-Dealer-to-Client Bond Trading Platforms," Working Papers 2015-11, Center for Research in Economics and Statistics.

    Cited by:

    1. Ben Hambly & Renyuan Xu & Huining Yang, 2021. "Recent Advances in Reinforcement Learning in Finance," Papers 2112.04553, arXiv.org, revised Feb 2023.
    2. Xin Guo & Charles-Albert Lehalle & Renyuan Xu, 2019. "Transaction Cost Analytics for Corporate Bonds," Papers 1903.09140, arXiv.org, revised Dec 2021.

  5. Jean-David Fermanian & Hassan Malongo, 2013. "On the Stationarity of Dynamic Conditional Correlation Models," Working Papers 2013-26, Center for Research in Economics and Statistics.

    Cited by:

    1. Benjamin Poignard & Jean-Davis Fermanian, 2014. "Dynamic Asset Correlations Based on Vines," Working Papers 2014-46, Center for Research in Economics and Statistics.

Articles

  1. Derumigny, Alexis & Fermanian, Jean-David, 2019. "A classification point-of-view about conditional Kendall’s tau," Computational Statistics & Data Analysis, Elsevier, vol. 135(C), pages 70-94.

    Cited by:

    1. Adrian Tantau & András Puskás-Tompos & Costel Stanciu & Laurentiu Fratila & Catalin Curmei, 2021. "Key Factors Which Contribute to the Participation of Consumers in Demand Response Programs and Enable the Proliferation of Renewable Energy Sources," Energies, MDPI, vol. 14(24), pages 1-22, December.
    2. Derumigny, Alexis & Fermanian, Jean-David, 2020. "On Kendall’s regression," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
    3. Derumigny Alexis & Fermanian Jean-David, 2019. "On kernel-based estimation of conditional Kendall’s tau: finite-distance bounds and asymptotic behavior," Dependence Modeling, De Gruyter, vol. 7(1), pages 292-321, January.

  2. Poignard, Benjamin & Fermanian, Jean-David, 2019. "Dynamic Asset Correlations Based On Vines," Econometric Theory, Cambridge University Press, vol. 35(1), pages 167-197, February.

    Cited by:

    1. Jean-David Fermanian & Benjamin Poignard & Panos Xidonas, 2025. "Model-based vs. agnostic methods for the prediction of time-varying covariance matrices," Annals of Operations Research, Springer, vol. 346(1), pages 511-548, March.
    2. Shanshan Jiang & Jie Wang & Ruiting Dong & Yutong Li & Min Xia, 2023. "Systemic Risk with Multi-Channel Risk Contagion in the Interbank Market," Sustainability, MDPI, vol. 15(3), pages 1-24, February.
    3. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.

  3. Fermanian, Jean-David & Malongo, Hassan, 2017. "On The Stationarity Of Dynamic Conditional Correlation Models," Econometric Theory, Cambridge University Press, vol. 33(3), pages 636-663, June.

    Cited by:

    1. Jean-David Fermanian & Benjamin Poignard & Panos Xidonas, 2025. "Model-based vs. agnostic methods for the prediction of time-varying covariance matrices," Annals of Operations Research, Springer, vol. 346(1), pages 511-548, March.
    2. Barassi, Marco & Horvath, Lajos & Zhao, Yuqian, 2018. "Change Point Detection in the Conditional Correlation Structure of Multivariate Volatility Models," MPRA Paper 87837, University Library of Munich, Germany.
    3. Stefano Grassi & Francesco Violante, 2021. "Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas," CREATES Research Papers 2021-05, Department of Economics and Business Economics, Aarhus University.
    4. Sylvia Gottschalk, 2023. "From Black Wednesday to Brexit: Macroeconomic shocks and correlations of equity returns in France, Germany, Italy, Spain, and the United Kingdom," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2843-2873, July.

  4. Fermanian, Jean-David, 2014. "The limits of granularity adjustments," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 9-25.

    Cited by:

    1. Greig Smith & Goncalo dos Reis, 2017. "Robust and Consistent Estimation of Generators in Credit Risk," Papers 1702.08867, arXiv.org, revised Oct 2017.
    2. Laurent, Jean-Paul & Sestier, Michael & Thomas, Stéphane, 2016. "Trading book and credit risk: How fundamental is the Basel review?," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 211-223.

  5. Fermanian, Jean-David & Scaillet, Olivier, 2005. "Sensitivity analysis of VaR and Expected Shortfall for portfolios under netting agreements," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 927-958, April.

    Cited by:

    1. Borgonovo, Emanuele & Hazen, Gordon B. & Jose, Victor Richmond R. & Plischke, Elmar, 2021. "Probabilistic sensitivity measures as information value," European Journal of Operational Research, Elsevier, vol. 289(2), pages 595-610.
    2. So Yeon Chun & Alexander Shapiro & Stan Uryasev, 2012. "Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics," Operations Research, INFORMS, vol. 60(4), pages 739-756, August.
    3. Hatem Salah & Marwa Souissi, 2016. "Financial Stability and Macro Prudential Regulation: Policy Implication of Systemic Expected Shortfall Measure," Working Papers 985, Economic Research Forum, revised Apr 2016.
    4. Christian Gourieroux & Wei Liu, 2006. "Efficient Portfolio Analysis Using Distortion Risk Measures," Working Papers 2006-17, Center for Research in Economics and Statistics.
    5. Yao, Haixiang & Huang, Jinbo & Li, Yong & Humphrey, Jacquelyn E., 2021. "A general approach to smooth and convex portfolio optimization using lower partial moments," Journal of Banking & Finance, Elsevier, vol. 129(C).
    6. Banulescu, Georgiana-Denisa & Dumitrescu, Elena-Ivona, 2015. "Which are the SIFIs? A Component Expected Shortfall approach to systemic risk," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 575-588.
    7. Ivanov Roman V., 2018. "On risk measuring in the variance-gamma model," Statistics & Risk Modeling, De Gruyter, vol. 35(1-2), pages 23-33, January.
    8. Härdle, Wolfgang Karl & Ling, Chengxiu, 2018. "How Sensitive are Tail-related Risk Measures in a Contamination Neighbourhood?," IRTG 1792 Discussion Papers 2018-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    9. Jin Peng, 2011. "Credibilistic value and average value at risk in fuzzy risk analysis," Fuzzy Information and Engineering, Springer, vol. 3(1), pages 69-79, March.
    10. J. Christopher Westland, 2015. "Economics of eBay’s buyer protection plan," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-20, December.
    11. Scaillet, Olivier & Trojani, Fabio & Camponovo, Lorenzo, 2016. "Comments on : Nonparametric Tail Risk, Stock Returns and the Macroeconomy," Working Papers unige:84999, University of Geneva, Geneva School of Economics and Management.
    12. Monica Billio & Lorenzo Frattarolo & Loriana Pelizzon, 2016. "Hedge Fund Tail Risk: An investigation in stressed markets, extended version with appendix," Working Papers 2016:01, Department of Economics, University of Venice "Ca' Foscari".
    13. Deepak Jadhav & T.V. Ramanathan & U.V. Naik-Nimbalkar, 2009. "Modified Estimators of the Expected Shortfall," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 8(2), pages 87-107, May.
    14. Brandtner, Mario & Kürsten, Wolfgang, 2015. "Decision making with Expected Shortfall and spectral risk measures: The problem of comparative risk aversion," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 268-280.
    15. Bauer, Daniel & Zanjani, George, 2021. "Economic capital and RAROC in a dynamic model," Journal of Banking & Finance, Elsevier, vol. 125(C).
    16. Christian Gourieroux & Wei Liu, 2006. "Sensitivity Analysis of Distortion Risk Measures," Working Papers 2006-33, Center for Research in Economics and Statistics.
    17. Gunay, Samet & Kirimhan, Destan & Cevik, Emrah Ismail, 2024. "Commodity market downturn: Systemic risk and spillovers during left tail events," Journal of Commodity Markets, Elsevier, vol. 36(C).
    18. Wang, Chuan-Sheng & Zhao, Zhibiao, 2016. "Conditional Value-at-Risk: Semiparametric estimation and inference," Journal of Econometrics, Elsevier, vol. 195(1), pages 86-103.
    19. Kellner, Ralf & Rösch, Daniel, 2016. "Quantifying market risk with Value-at-Risk or Expected Shortfall? – Consequences for capital requirements and model risk," Journal of Economic Dynamics and Control, Elsevier, vol. 68(C), pages 45-63.

  6. Fermanian, Jean-David & Salanié, Bernard, 2004. "A Nonparametric Simulated Maximum Likelihood Estimation Method," Econometric Theory, Cambridge University Press, vol. 20(4), pages 701-734, August.

    Cited by:

    1. Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Juan F. Rubio-Ramírez, 2010. "Fortune or Virtue: Time-Variant Volatilities Versus Parameter Drifting in U.S. Data," NBER Working Papers 15928, National Bureau of Economic Research, Inc.
    2. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers 45/13, Institute for Fiscal Studies.
    3. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2007. "Estimating Macroeconomic Models: A Likelihood Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1059-1087.
    4. Dennis Kristensen, 2008. "Uniform Convergence Rates of Kernel Estimators with Heterogenous, Dependent Data," CREATES Research Papers 2008-37, Department of Economics and Business Economics, Aarhus University.
    5. Corradi, Valentina & Distaso, Walter & Mele, Antonio, 2013. "Macroeconomic determinants of stock volatility and volatility premiums," Journal of Monetary Economics, Elsevier, vol. 60(2), pages 203-220.
    6. Gutknecht, Daniel, 2016. "Testing for monotonicity under endogeneity," Journal of Econometrics, Elsevier, vol. 190(1), pages 100-114.
    7. Dennis Kristensen & Patrick K. Mogensen & Jong Myun Moon & Bertel Schjerning, 2019. "Solving Dynamic Discrete Choice Models Using Smoothing and Sieve Methods," Papers 1904.05232, arXiv.org, revised Feb 2020.
    8. John Kennes & Daniel le Maire, 2016. "Competing Auctions of Skills," Economics Working Papers 2016-02, Department of Economics and Business Economics, Aarhus University.
    9. Bruins, Marianne & Duffy, James A. & Keane, Michael P. & Smith, Anthony A., 2018. "Generalized indirect inference for discrete choice models," Journal of Econometrics, Elsevier, vol. 205(1), pages 177-203.
    10. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Oct 2021.
    11. Michela M. Tincani, 2021. "Teacher labor markets, school vouchers, and student cognitive achievement: Evidence from Chile," Quantitative Economics, Econometric Society, vol. 12(1), pages 173-216, January.
    12. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    13. John Kennes & Daniel le Maire, 2013. "Job Heterogeneity and Coordination Frictions," Economics Working Papers 2013-09, Department of Economics and Business Economics, Aarhus University.
    14. Valentina Corradi & Norman R. Swanson, 2011. "Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models," Post-Print hal-00796745, HAL.
    15. Carrasco, Marine & Chernov, Mikhail & Florens, Jean-Pierre & Ghysels, Eric, 2007. "Efficient estimation of general dynamic models with a continuum of moment conditions," Journal of Econometrics, Elsevier, vol. 140(2), pages 529-573, October.
    16. Dennis Kristensen & Bernard Salanié, 2010. "Higher Order Improvements for Approximate Estimators," CAM Working Papers 2010-04, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    17. Joakim Westerlund & Per Hjertstrand, 2014. "Indirect Estimation of Semiparametric Binary Choice Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 298-314, April.
    18. Dennis Kristensen & Michael Creel, 2015. "Indirect Likelihood Inference," Working Papers 558, Barcelona School of Economics.
    19. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    20. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    21. Norman R. Swanson & Lili Cai, 2011. "In- and Out-of-Sample Specification Analysis of Spot Rate Models: Further Evidence for the Period 1982-2008," Departmental Working Papers 201102, Rutgers University, Department of Economics.
    22. Daniel Gutknecht, 2013. "Testing for Monotonicity under Endogeneity An Application to the Reservation Wage Function," Economics Series Working Papers 673, University of Oxford, Department of Economics.
    23. Jules H. van Binsbergen & Jesús Fernández-Villaverde & Ralph S.J. Koijen & Juan F. Rubio-Ramírez, 2010. "The Term Structure of Interest Rates in a DSGE Model with Recursive Preferences," PIER Working Paper Archive 10-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    24. Jean-Jacques Forneron & Serena Ng, 2015. "The ABC of Simulation Estimation with Auxiliary Statistics," Papers 1501.01265, arXiv.org, revised Oct 2017.
    25. Lee, Donghoon & Song, Kyungchul, 2015. "Simulated maximum likelihood estimation for discrete choices using transformed simulated frequencies," Journal of Econometrics, Elsevier, vol. 187(1), pages 131-153.
    26. Santiago Carbo-Valverde & Héctor Pérez Saiz & Hongyu Xiao, 2023. "Geographical and Cultural Proximity in Retail Banking," Staff Working Papers 23-2, Bank of Canada.
    27. Corradi, Valentina & Silvapulle, Mervyn J. & Swanson, Norman R., 2018. "Testing for jumps and jump intensity path dependence," Journal of Econometrics, Elsevier, vol. 204(2), pages 248-267.
    28. Pierluigi Vallarino, 2024. "Dynamic kernel models," Tinbergen Institute Discussion Papers 24-082/III, Tinbergen Institute.
    29. Bertl Johanna & Ewing Gregory & Kosiol Carolin & Futschik Andreas, 2017. "Approximate maximum likelihood estimation for population genetic inference," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(5-6), pages 291-312, December.
    30. Michael Creel, 2008. "Estimation of Dynamic Latent Variable Models Using Simulated Nonparametric Moments," UFAE and IAE Working Papers 725.08, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 02 Jun 2008.
    31. Nickl, Richard & Pötscher, Benedikt M., 2009. "Efficient Simulation-Based Minimum Distance Estimation and Indirect Inference," MPRA Paper 16608, University Library of Munich, Germany.
    32. Gach, Florian & Pötscher, Benedikt M., 2010. "Non-Parametric Maximum Likelihood Density Estimation and Simulation-Based Minimum Distance Estimators," MPRA Paper 27512, University Library of Munich, Germany.
    33. Michael Creel & Dennis Kristensen, 2013. "Indirect Likelihood Inference (revised)," UFAE and IAE Working Papers 931.13, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).

Books

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Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 6 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (4) 2018-01-22 2018-08-13 2019-04-01 2022-01-10
  2. NEP-BIG: Big Data (3) 2022-01-10 2022-01-31 2022-02-21
  3. NEP-CMP: Computational Economics (1) 2022-01-10

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