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Bertille Antoine

Personal Details

First Name:Bertille
Middle Name:
Last Name:Antoine
Suffix:
RePEc Short-ID:pan175
[This author has chosen not to make the email address public]
http://www.sfu.ca/~baa7
Terminal Degree:2007 Département de Sciences Économiques; Université de Montréal (from RePEc Genealogy)

Affiliation

Department of Economics
Simon Fraser University

Burnaby, Canada
https://www.sfu.ca/economics/
RePEc:edi:desfuca (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Bertille Antoine & Otilia Boldea & Niccolo Zaccaria, 2024. "Efficient two-sample instrumental variable estimators with change points and near-weak identification," Papers 2406.17056, arXiv.org.
  2. Antoine Bertille & Pascal Lavergne, 2023. "Identification-Robust Nonparametric Inference in a Linear IV Model," Post-Print hal-04141433, HAL.
  3. Bertille Antoine & Xiaolin Sun, 2020. "Partially Linear Models with Endogeneity: a conditional moment based approach," Discussion Papers dp20-06, Department of Economics, Simon Fraser University.
  4. Bertille Antoine & Pascal Lavergne, 2020. "Identification-Robust Nonparametric Interference in a Linear IV Model," Discussion Papers dp20-03, Department of Economics, Simon Fraser University.
  5. Bertille Antoine & Prosper Dovonon, 2018. "Robust Estimation with Exponentially Tilted Hellinger Distance," CIRANO Working Papers 2018s-38, CIRANO.
  6. Bertille Antoine & Otilia Boldea, 2015. "Efficient Inference with Time-Varying Information and the New Keynesian Phillips Curve," Discussion Papers dp15-04, Department of Economics, Simon Fraser University, revised 25 Aug 2016.
  7. Bertille Antoine & Otilia, 2015. "Inference in linear models with structural changes and mixed identification strength," Discussion Papers dp15-05, Department of Economics, Simon Fraser University.
  8. Bertille Antoine & Eric Renault, 2014. "On the relevance of weaker instruments," Discussion Papers dp14-04, Department of Economics, Simon Fraser University, revised 10 Oct 2016.
  9. Bertille Antoine & Otilia Boldea, 2014. "Efficient Inference with Time-Varying Identification Strength," Discussion Papers dp14-03, Department of Economics, Simon Fraser University.
  10. Bertille Antoine & Eric Renault, 2012. "Efficient Minimum Distance Estimation with Multiple Rates of Convergence," Discussion Papers dp12-03, Department of Economics, Simon Fraser University.
  11. Bertille Antoine & Eric Renault, 2012. "Efficient Inference with Poor Instruments: a General Framework," Discussion Papers dp12-04, Department of Economics, Simon Fraser University.
  12. Bertille Antoine & Eric Renault, 2012. "Testing Identification Strength," Discussion Papers dp12-17, Department of Economics, Simon Fraser University, revised Jan 2017.
  13. Bertille Antoine & Pascal Lavergne, 2011. "Conditional Moment Models under Semi-Strong Identification," Discussion Papers dp11-04, Department of Economics, Simon Fraser University, revised Dec 2012.

Articles

  1. Antoine, Bertille & Renault, Eric, 2024. "GMM with Nearly-Weak Identification," Econometrics and Statistics, Elsevier, vol. 30(C), pages 36-59.
  2. Antoine, Bertille & Lavergne, Pascal, 2023. "Identification-robust nonparametric inference in a linear IV model," Journal of Econometrics, Elsevier, vol. 235(1), pages 1-24.
  3. Bertille Antoine & Lynda Khalaf & Maral Kichian & Zhenjiang Lin, 2023. "Identification-Robust Inference With Simulation-Based Pseudo-Matching," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 321-338, April.
  4. Bertille Antoine & Xiaolin Sun, 2022. "Partially linear models with endogeneity: a conditional moment-based approach [Efficient estimation of models with conditional moment restrictions containing unknown functions]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 256-275.
  5. Antoine, Bertille & Dovonon, Prosper, 2021. "Robust estimation with exponentially tilted Hellinger distance," Journal of Econometrics, Elsevier, vol. 224(2), pages 330-344.
  6. Antoine, Bertille & Renault, Eric, 2020. "Testing identification strength," Journal of Econometrics, Elsevier, vol. 218(2), pages 271-293.
  7. Antoine, Bertille & Boldea, Otilia, 2018. "Efficient estimation with time-varying information and the New Keynesian Phillips Curve," Journal of Econometrics, Elsevier, vol. 204(2), pages 268-300.
  8. Bertille Antoine & Eric Renault, 2017. "On the relevance of weaker instruments," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 928-945, October.
  9. Antoine, Bertille & Lavergne, Pascal, 2014. "Conditional moment models under semi-strong identification," Journal of Econometrics, Elsevier, vol. 182(1), pages 59-69.
  10. Antoine, Bertille & Renault, Eric, 2012. "Efficient minimum distance estimation with multiple rates of convergence," Journal of Econometrics, Elsevier, vol. 170(2), pages 350-367.
  11. Bertille Antoine, 2010. "Portfolio Selection with Estimation Risk: A Test-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 10(1), pages 164-197, 2012 10 1.
  12. Bertille Antoine & Eric Renault, 2009. "Efficient GMM with nearly-weak instruments," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 135-171, January.
  13. Antoine, Bertille & Bonnal, Helene & Renault, Eric, 2007. "On the efficient use of the informational content of estimating equations: Implied probabilities and Euclidean empirical likelihood," Journal of Econometrics, Elsevier, vol. 138(2), pages 461-487, June.
  14. Bertille Antoine & Kevin Proulx & Eric Renault, 0. "Pseudo-True SDFs in Conditional Asset Pricing Models," Journal of Financial Econometrics, Oxford University Press, vol. 18(4), pages 656-714.
  15. Bertille Antoine & Kevin Proulx & Eric Renault, 0. "Rejoinder on: Pseudo-True SDFs in Conditional Asset Pricing Models," Journal of Financial Econometrics, Oxford University Press, vol. 18(4), pages 776-790.

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. Antoine Bertille & Pascal Lavergne, 2023. "Identification-Robust Nonparametric Inference in a Linear IV Model," Post-Print hal-04141433, HAL.

    Cited by:

    1. Bertille Antoine & Xiaolin Sun, 2022. "Partially linear models with endogeneity: a conditional moment-based approach [Efficient estimation of models with conditional moment restrictions containing unknown functions]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 256-275.
    2. Xiaohong Chen & Sokbae Lee & Myung Hwan Seo & Myunghyun Song, 2020. "Inference for parameters identified by conditional moment restrictions using a generalized Bierens maximum statistic," Papers 2008.11140, arXiv.org, revised Oct 2024.
    3. Jiafeng Chen & Daniel L. Chen & Greg Lewis, 2020. "Mostly Harmless Machine Learning: Learning Optimal Instruments in Linear IV Models," Papers 2011.06158, arXiv.org, revised Jun 2021.

  2. Bertille Antoine & Xiaolin Sun, 2020. "Partially Linear Models with Endogeneity: a conditional moment based approach," Discussion Papers dp20-06, Department of Economics, Simon Fraser University.

    Cited by:

    1. Juan Carlos Escanciano & Joel Robert Terschuur, 2022. "Machine Learning Inference on Inequality of Opportunity," Papers 2206.05235, arXiv.org, revised Oct 2023.
    2. Kunyang Song & Feiyu Jiang & Ke Zhu, 2024. "Estimation for conditional moment models based on martingale difference divergence," Papers 2404.11092, arXiv.org.
    3. Wayne Yuan Gao & Rui Wang, 2023. "IV Regressions without Exclusion Restrictions," Papers 2304.00626, arXiv.org, revised Jul 2023.

  3. Bertille Antoine & Pascal Lavergne, 2020. "Identification-Robust Nonparametric Interference in a Linear IV Model," Discussion Papers dp20-03, Department of Economics, Simon Fraser University.

    Cited by:

    1. Bertille Antoine & Xiaolin Sun, 2022. "Partially linear models with endogeneity: a conditional moment-based approach [Efficient estimation of models with conditional moment restrictions containing unknown functions]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 256-275.

  4. Bertille Antoine & Prosper Dovonon, 2018. "Robust Estimation with Exponentially Tilted Hellinger Distance," CIRANO Working Papers 2018s-38, CIRANO.

    Cited by:

    1. Hengfang Wang & Jae Kwang Kim, 2025. "Information projection approach to smoothed propensity score weighting for handling selection bias under missing at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 77(1), pages 127-153, February.
    2. Daniel Ober-Reynolds, 2024. "Robustness to Missing Data: Breakdown Point Analysis," Papers 2406.06804, arXiv.org.
    3. Pietro Emilio Spini, 2021. "Robustness, Heterogeneous Treatment Effects and Covariate Shifts," Papers 2112.09259, arXiv.org, revised Aug 2024.
    4. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.

  5. Bertille Antoine & Otilia Boldea, 2015. "Efficient Inference with Time-Varying Information and the New Keynesian Phillips Curve," Discussion Papers dp15-04, Department of Economics, Simon Fraser University, revised 25 Aug 2016.

    Cited by:

    1. Marcellino, Massimiliano & Kapetanios, George & Giraitis, Liudas, 2020. "Time-Varying Instrumental Variable Estimation," CEPR Discussion Papers 15210, C.E.P.R. Discussion Papers.
    2. Regis Barnichon & Geert Mesters, 2020. "Identifying Modern Macro Equations with Old Shocks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(4), pages 2255-2298.
    3. Rothfelder, Mario & Boldea, Otilia, 2016. "Testing for a Threshold in Models with Endogenous Regressors," Discussion Paper 2016-029, Tilburg University, Center for Economic Research.
    4. Alastair R. Hall & Denise R. Osborn & Nikolaos Sakkas, 2017. "The asymptotic behaviour of the residual sum of squares in models with multiple break points," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 667-698, October.
    5. Aquino, Juan, 2019. "The Small Open Economy New-Keynesian Phillips Curve: Specification, Structural Breaks and Robustness," Working Papers 2019-019, Banco Central de Reserva del Perú.
    6. Bertille Antoine & Otilia, 2015. "Inference in linear models with structural changes and mixed identification strength," Discussion Papers dp15-05, Department of Economics, Simon Fraser University.

  6. Bertille Antoine & Otilia, 2015. "Inference in linear models with structural changes and mixed identification strength," Discussion Papers dp15-05, Department of Economics, Simon Fraser University.

    Cited by:

    1. Rothfelder, Mario & Boldea, Otilia, 2016. "Testing for a Threshold in Models with Endogenous Regressors," Discussion Paper 2016-029, Tilburg University, Center for Economic Research.
    2. Bertille Antoine & Otilia Boldea, 2015. "Efficient Inference with Time-Varying Information and the New Keynesian Phillips Curve," Discussion Papers dp15-04, Department of Economics, Simon Fraser University, revised 25 Aug 2016.
    3. Antoine, Bertille & Boldea, Otilia, 2018. "Efficient estimation with time-varying information and the New Keynesian Phillips Curve," Journal of Econometrics, Elsevier, vol. 204(2), pages 268-300.

  7. Bertille Antoine & Eric Renault, 2014. "On the relevance of weaker instruments," Discussion Papers dp14-04, Department of Economics, Simon Fraser University, revised 10 Oct 2016.

    Cited by:

    1. Hao, Bowen & Prokhorov, Artem & Qian, Hailong, 2018. "Moment redundancy test with application to efficiency-improving copulas," Economics Letters, Elsevier, vol. 171(C), pages 29-33.
    2. Bertille Antoine & Otilia Boldea & Niccolo Zaccaria, 2024. "Efficient two-sample instrumental variable estimators with change points and near-weak identification," Papers 2406.17056, arXiv.org.
    3. Grundke, Robert & Moser, Christoph, 2019. "Hidden protectionism? Evidence from non-tariff barriers to trade in the United States," Journal of International Economics, Elsevier, vol. 117(C), pages 143-157.
    4. Bertille Antoine & Otilia, 2015. "Inference in linear models with structural changes and mixed identification strength," Discussion Papers dp15-05, Department of Economics, Simon Fraser University.

  8. Bertille Antoine & Eric Renault, 2012. "Efficient Minimum Distance Estimation with Multiple Rates of Convergence," Discussion Papers dp12-03, Department of Economics, Simon Fraser University.

    Cited by:

    1. Inoue, Atsushi & Kilian, Lutz, 2016. "Joint confidence sets for structural impulse responses," Journal of Econometrics, Elsevier, vol. 192(2), pages 421-432.
    2. Pablo Guerron-quintana & Atsushi Inoue & Lutz Kilian, 2014. "Impulse response matching estimators for DSGE models," Vanderbilt University Department of Economics Working Papers 14-00014, Vanderbilt University Department of Economics.
    3. David T. Frazierz & Eric Renault, 2016. "Efficient Two-Step Estimation via Targeting," CIRANO Working Papers 2016s-16, CIRANO.
    4. Hill, Jonathan B. & Aguilar, Mike, 2013. "Moment condition tests for heavy tailed time series," Journal of Econometrics, Elsevier, vol. 172(2), pages 255-274.
    5. Donna Feir & Thomas Lemieux & Vadim Marmer, 2016. "Weak Identification in Fuzzy Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 185-196, April.
    6. Antoine, Bertille & Renault, Eric, 2024. "GMM with Nearly-Weak Identification," Econometrics and Statistics, Elsevier, vol. 30(C), pages 36-59.
    7. Simon Freyaldenhoven, 2017. "A Generalized Factor Model with Local Factors," 2017 Papers pfr361, Job Market Papers.
    8. Alessandro Gregorio & Francesco Iafrate, 2021. "Regularized bridge-type estimation with multiple penalties," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(5), pages 921-951, October.
    9. Zhentao Shi & Huanhuan Zheng, 2018. "Structural estimation of behavioral heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 690-707, August.
    10. Frazier, David T. & Renault, Eric, 2017. "Efficient two-step estimation via targeting," Journal of Econometrics, Elsevier, vol. 201(2), pages 212-227.
    11. Antoine, Bertille & Renault, Eric, 2020. "Testing identification strength," Journal of Econometrics, Elsevier, vol. 218(2), pages 271-293.
    12. Antoine, Bertille & Lavergne, Pascal, 2014. "Conditional moment models under semi-strong identification," Journal of Econometrics, Elsevier, vol. 182(1), pages 59-69.
    13. Gagliardini, Patrick & Ronchetti, Diego, 2013. "Semi-parametric estimation of American option prices," Journal of Econometrics, Elsevier, vol. 173(1), pages 57-82.
    14. Cheng, Xu, 2015. "Robust inference in nonlinear models with mixed identification strength," Journal of Econometrics, Elsevier, vol. 189(1), pages 207-228.
    15. Prosper Dovonon & Firmin Doko Tchatoka & Michael Aguessy, 2019. "Relevant moment selection under mixed identification strength," School of Economics and Public Policy Working Papers 2019-04, University of Adelaide, School of Economics and Public Policy.
    16. Chao, John C. & Swanson, Norman R. & Woutersen, Tiemen, 2023. "Jackknife estimation of a cluster-sample IV regression model with many weak instruments," Journal of Econometrics, Elsevier, vol. 235(2), pages 1747-1769.
    17. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    18. Leong, Soon Heng & Urga, Giovanni, 2023. "A practical multivariate approach to testing volatility spillover," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    19. Forneron, Jean-Jacques, 2024. "Detecting identification failure in moment condition models," Journal of Econometrics, Elsevier, vol. 238(1).
    20. Krogh, Tord S., 2015. "Macro frictions and theoretical identification of the New Keynesian Phillips curve," Journal of Macroeconomics, Elsevier, vol. 43(C), pages 191-204.
    21. Chaudhuri, Saraswata & Renault, Eric, 2020. "Score tests in GMM: Why use implied probabilities?," Journal of Econometrics, Elsevier, vol. 219(2), pages 260-280.
    22. Antoine, Bertille & Boldea, Otilia, 2018. "Efficient estimation with time-varying information and the New Keynesian Phillips Curve," Journal of Econometrics, Elsevier, vol. 204(2), pages 268-300.

  9. Bertille Antoine & Eric Renault, 2012. "Efficient Inference with Poor Instruments: a General Framework," Discussion Papers dp12-04, Department of Economics, Simon Fraser University.

    Cited by:

    1. Donald W. K. Andrews & Xu Cheng, 2011. "Maximum Likelihood Estimation and Uniform Inference with Sporadic Identification Failure," Cowles Foundation Discussion Papers 1824R, Cowles Foundation for Research in Economics, Yale University, revised Oct 2012.
    2. Donald W.K. Andrews & Xu Cheng, 2011. "GMM Estimation and Uniform Subvector Inference with Possible Identification Failure," Cowles Foundation Discussion Papers 1828, Cowles Foundation for Research in Economics, Yale University.
    3. Antoine, Bertille & Lavergne, Pascal, 2014. "Conditional moment models under semi-strong identification," Journal of Econometrics, Elsevier, vol. 182(1), pages 59-69.
    4. Sentana, Enrique, 2024. "Finite underidentification," Journal of Econometrics, Elsevier, vol. 240(1).

  10. Bertille Antoine & Eric Renault, 2012. "Testing Identification Strength," Discussion Papers dp12-17, Department of Economics, Simon Fraser University, revised Jan 2017.

    Cited by:

    1. Antoine, Bertille & Renault, Eric, 2024. "GMM with Nearly-Weak Identification," Econometrics and Statistics, Elsevier, vol. 30(C), pages 36-59.
    2. Jean-Jacques Forneron, 2019. "Detecting Identification Failure in Moment Condition Models," Papers 1907.13093, arXiv.org, revised Oct 2023.
    3. David T. Frazier & Eric Renault & Lina Zhang & Xueyan Zhao, 2020. "Weak Identification in Discrete Choice Models," Papers 2011.06753, arXiv.org, revised Jan 2021.
    4. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    5. Forneron, Jean-Jacques, 2024. "Detecting identification failure in moment condition models," Journal of Econometrics, Elsevier, vol. 238(1).

  11. Bertille Antoine & Pascal Lavergne, 2011. "Conditional Moment Models under Semi-Strong Identification," Discussion Papers dp11-04, Department of Economics, Simon Fraser University, revised Dec 2012.

    Cited by:

    1. Jinho Choi & Juan Carlos Escanciano & Junjie Guo, 2022. "Generalized band spectrum estimation with an application to the New Keynesian Phillips curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1055-1078, August.
    2. Bertille Antoine & Pascal Lavergne, 2020. "Identification-Robust Nonparametric Interference in a Linear IV Model," Discussion Papers dp20-03, Department of Economics, Simon Fraser University.
    3. Bertille Antoine & Pascal Lavergne, 2021. "Identifcation-Robust Nonparametric Inference in a Linear IV Model," Discussion Papers dp21-12, Department of Economics, Simon Fraser University.
    4. Donna Feir & Thomas Lemieux & Vadim Marmer, 2016. "Weak Identification in Fuzzy Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 185-196, April.
    5. Marine Carrasco & Guy Tchuente, 2015. "Efficient estimation with many weak instruments using regularization techniques," Studies in Economics 1517, School of Economics, University of Kent.
    6. 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.
    7. Kotchoni, Rachidi, 2014. "The indirect continuous-GMM estimation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 464-488.
    8. Jean Thomas Bernard & Ba Chu & Lynda Khalaf & Marcel Voia, 2019. "Non-Standard Confidence Sets for Ratios and Tipping Points with Applications to Dynamic Panel Data," Post-Print hal-03549991, HAL.
    9. Raymond Kan & Cesare Robotti, 0. "Comment on: Pseudo-True SDFs in Conditional Asset Pricing Models," Journal of Financial Econometrics, Oxford University Press, vol. 18(4), pages 729-735.
    10. Xiaolin Sun, 2022. "Estimation of Heterogeneous Treatment Effects Using a Conditional Moment Based Approach," Papers 2210.15829, arXiv.org, revised Oct 2024.
    11. Juan Carlos Escanciano & Joel Robert Terschuur, 2022. "Machine Learning Inference on Inequality of Opportunity," Papers 2206.05235, arXiv.org, revised Oct 2023.
    12. Bertille Antoine & Xiaolin Sun, 2022. "Partially linear models with endogeneity: a conditional moment-based approach [Efficient estimation of models with conditional moment restrictions containing unknown functions]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 256-275.
    13. Carlos Velasco & Xuexin Wang, 2021. "Instrumental variable estimation via a continuum of instruments with an application to estimating the elasticity of intertemporal substitution in consumption," Working Papers 2024-09-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    14. Dakyung Seong, 2022. "Binary response model with many weak instruments," Papers 2201.04811, arXiv.org, revised Jun 2024.
    15. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    16. Khalaf, Lynda & Urga, Giovanni, 2014. "Identification robust inference in cointegrating regressions," Journal of Econometrics, Elsevier, vol. 182(2), pages 385-396.

Articles

  1. Antoine, Bertille & Lavergne, Pascal, 2023. "Identification-robust nonparametric inference in a linear IV model," Journal of Econometrics, Elsevier, vol. 235(1), pages 1-24.
    See citations under working paper version above.
  2. Bertille Antoine & Xiaolin Sun, 2022. "Partially linear models with endogeneity: a conditional moment-based approach [Efficient estimation of models with conditional moment restrictions containing unknown functions]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 256-275.
    See citations under working paper version above.
  3. Antoine, Bertille & Dovonon, Prosper, 2021. "Robust estimation with exponentially tilted Hellinger distance," Journal of Econometrics, Elsevier, vol. 224(2), pages 330-344.
    See citations under working paper version above.
  4. Antoine, Bertille & Renault, Eric, 2020. "Testing identification strength," Journal of Econometrics, Elsevier, vol. 218(2), pages 271-293.
    See citations under working paper version above.
  5. Antoine, Bertille & Boldea, Otilia, 2018. "Efficient estimation with time-varying information and the New Keynesian Phillips Curve," Journal of Econometrics, Elsevier, vol. 204(2), pages 268-300.

    Cited by:

    1. Marcellino, Massimiliano & Kapetanios, George & Giraitis, Liudas, 2020. "Time-Varying Instrumental Variable Estimation," CEPR Discussion Papers 15210, C.E.P.R. Discussion Papers.
    2. Regis Barnichon & Geert Mesters, 2020. "Identifying Modern Macro Equations with Old Shocks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(4), pages 2255-2298.
    3. Jinho Choi & Juan Carlos Escanciano & Junjie Guo, 2022. "Generalized band spectrum estimation with an application to the New Keynesian Phillips curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1055-1078, August.
    4. Rothfelder, Mario & Boldea, Otilia, 2016. "Testing for a Threshold in Models with Endogenous Regressors," Discussion Paper 2016-029, Tilburg University, Center for Economic Research.
    5. Bertille Antoine & Otilia Boldea & Niccolo Zaccaria, 2024. "Efficient two-sample instrumental variable estimators with change points and near-weak identification," Papers 2406.17056, arXiv.org.
    6. Aquino, Juan, 2019. "The Small Open Economy New-Keynesian Phillips Curve: Specification, Structural Breaks and Robustness," Working Papers 2019-019, Banco Central de Reserva del Perú.

  6. Bertille Antoine & Eric Renault, 2017. "On the relevance of weaker instruments," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 928-945, October.
    See citations under working paper version above.
  7. Antoine, Bertille & Lavergne, Pascal, 2014. "Conditional moment models under semi-strong identification," Journal of Econometrics, Elsevier, vol. 182(1), pages 59-69.
    See citations under working paper version above.
  8. Antoine, Bertille & Renault, Eric, 2012. "Efficient minimum distance estimation with multiple rates of convergence," Journal of Econometrics, Elsevier, vol. 170(2), pages 350-367.
    See citations under working paper version above.
  9. Bertille Antoine, 2010. "Portfolio Selection with Estimation Risk: A Test-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 10(1), pages 164-197, 2012 10 1.

    Cited by:

    1. Fan, Jianqing & Liao, Yuan & Shi, Xiaofeng, 2015. "Risks of large portfolios," Journal of Econometrics, Elsevier, vol. 186(2), pages 367-387.
    2. Jin-Ray Lu & Chih-Ming Chan & Wen-Shen Li, 2011. "Portfolio Selections with Innate Learning Ability," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 10(3), pages 201-217, December.
    3. Ertugrul Bayraktar & Ayse Humeyra Bilge, 2012. "Determination the Parameters of Markowitz Portfolio Optimization Model," Papers 1210.5859, arXiv.org.

  10. Bertille Antoine & Eric Renault, 2009. "Efficient GMM with nearly-weak instruments," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 135-171, January.

    Cited by:

    1. Isaiah Andrews & Anna Mikusheva, 2016. "Conditional Inference With a Functional Nuisance Parameter," Econometrica, Econometric Society, vol. 84, pages 1571-1612, July.
    2. Donald W. K. Andrews & Xu Cheng, 2011. "Maximum Likelihood Estimation and Uniform Inference with Sporadic Identification Failure," Cowles Foundation Discussion Papers 1824R, Cowles Foundation for Research in Economics, Yale University, revised Oct 2012.
    3. Caner, Mehmet, 2014. "Near exogeneity and weak identification in generalized empirical likelihood estimators: Many moment asymptotics," Journal of Econometrics, Elsevier, vol. 182(2), pages 247-268.
    4. Donna Feir & Thomas Lemieux & Vadim Marmer, 2016. "Weak Identification in Fuzzy Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 185-196, April.
    5. Martínez-Iriarte, Julián & Sun, Yixiao & Wang, Xuexin, 2020. "Asymptotic F tests under possibly weak identification," Journal of Econometrics, Elsevier, vol. 218(1), pages 140-177.
    6. Antoine, Bertille & Renault, Eric, 2024. "GMM with Nearly-Weak Identification," Econometrics and Statistics, Elsevier, vol. 30(C), pages 36-59.
    7. Juodis, Artūras & Sarafidis, Vasilis, 2022. "An incidental parameters free inference approach for panels with common shocks," Journal of Econometrics, Elsevier, vol. 229(1), pages 19-54.
    8. Bertille Antoine & Otilia Boldea & Niccolo Zaccaria, 2024. "Efficient two-sample instrumental variable estimators with change points and near-weak identification," Papers 2406.17056, arXiv.org.
    9. Mehmet Caner, 2010. "Testing, Estimation in GMM and CUE with Nearly-Weak Identification," Econometric Reviews, Taylor & Francis Journals, vol. 29(3), pages 330-363.
    10. Donald W.K. Andrews & Xu Cheng, 2011. "GMM Estimation and Uniform Subvector Inference with Possible Identification Failure," Cowles Foundation Discussion Papers 1828, Cowles Foundation for Research in Economics, Yale University.
    11. Jean-Jacques Forneron, 2019. "Detecting Identification Failure in Moment Condition Models," Papers 1907.13093, arXiv.org, revised Oct 2023.
    12. Bertille Antoine & Otilia Boldea, 2015. "Efficient Inference with Time-Varying Information and the New Keynesian Phillips Curve," Discussion Papers dp15-04, Department of Economics, Simon Fraser University, revised 25 Aug 2016.
    13. David T. Frazier & Eric Renault & Lina Zhang & Xueyan Zhao, 2020. "Weak Identification in Discrete Choice Models," Papers 2011.06753, arXiv.org, revised Jan 2021.
    14. Fallaw Sowell & Nandana Sengupta, 2021. "Inference for the Linear IV Model Ridge Estimator Using Training and Test Samples," Stats, MDPI, vol. 4(3), pages 1-20, September.
    15. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    16. Alexander Mayer, 2022. "Estimation and inference in adaptive learning models with slowly decreasing gains," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 720-749, September.
    17. Bertille Antoine & Eric Renault, 2012. "Efficient Minimum Distance Estimation with Multiple Rates of Convergence," Discussion Papers dp12-03, Department of Economics, Simon Fraser University.
    18. Antoine, Bertille & Renault, Eric, 2020. "Testing identification strength," Journal of Econometrics, Elsevier, vol. 218(2), pages 271-293.
    19. Prosper Donovon & Alastair R. Hall, 2015. "GMM and Indirect Inference: An appraisal of their connections and new results on their properties under second order identification," Economics Discussion Paper Series 1505, Economics, The University of Manchester.
    20. Xu Cheng, 2014. "Uniform Inference in Nonlinear Models with Mixed Identification Strength," PIER Working Paper Archive 14-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    21. Antoine, Bertille & Lavergne, Pascal, 2014. "Conditional moment models under semi-strong identification," Journal of Econometrics, Elsevier, vol. 182(1), pages 59-69.
    22. Cheng, Xu, 2015. "Robust inference in nonlinear models with mixed identification strength," Journal of Econometrics, Elsevier, vol. 189(1), pages 207-228.
    23. Prosper Dovonon & Firmin Doko Tchatoka & Michael Aguessy, 2019. "Relevant moment selection under mixed identification strength," School of Economics and Public Policy Working Papers 2019-04, University of Adelaide, School of Economics and Public Policy.
    24. Rachida Ouysse, 2014. "On the performance of block-bootstrap continuously updated GMM for a class of non-linear conditional moment models," Computational Statistics, Springer, vol. 29(1), pages 233-261, February.
    25. Dakyung Seong, 2022. "Binary response model with many weak instruments," Papers 2201.04811, arXiv.org, revised Jun 2024.
    26. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    27. Nandana Sengupta & Fallaw Sowell, 2019. "The Ridge Path Estimator for Linear Instrumental Variables," Papers 1908.09237, arXiv.org.
    28. Forneron, Jean-Jacques, 2024. "Detecting identification failure in moment condition models," Journal of Econometrics, Elsevier, vol. 238(1).
    29. Krogh, Tord S., 2015. "Macro frictions and theoretical identification of the New Keynesian Phillips curve," Journal of Macroeconomics, Elsevier, vol. 43(C), pages 191-204.
    30. Antoine, Bertille & Boldea, Otilia, 2018. "Efficient estimation with time-varying information and the New Keynesian Phillips Curve," Journal of Econometrics, Elsevier, vol. 204(2), pages 268-300.
    31. Bertille Antoine & Otilia Boldea, 2014. "Efficient Inference with Time-Varying Identification Strength," Discussion Papers dp14-03, Department of Economics, Simon Fraser University.
    32. Nandana Sengupta & Fallaw Sowell, 2020. "On the Asymptotic Distribution of Ridge Regression Estimators Using Training and Test Samples," Econometrics, MDPI, vol. 8(4), pages 1-25, October.

  11. Antoine, Bertille & Bonnal, Helene & Renault, Eric, 2007. "On the efficient use of the informational content of estimating equations: Implied probabilities and Euclidean empirical likelihood," Journal of Econometrics, Elsevier, vol. 138(2), pages 461-487, June.

    Cited by:

    1. Seojeong Lee, 2014. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for GEL Estimators," Discussion Papers 2014-02, School of Economics, The University of New South Wales.
    2. Pierre Chaussé, 2011. "Generalized empirical likelihood for a continuum of moment conditions," Working Papers 1104, University of Waterloo, Department of Economics, revised Oct 2011.
    3. Lavergne, Pascal & Patilea, Valentin, 2013. "Smooth minimum distance estimation and testing with conditional estimating equations: Uniform in bandwidth theory," Journal of Econometrics, Elsevier, vol. 177(1), pages 47-59.
    4. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2018. "Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models," Econometric Reviews, Taylor & Francis Journals, vol. 37(7), pages 695-718, August.
    5. Daniel Becker & Alois Kneip & Valentin Patilea, 2021. "Semiparametric inference for partially linear regressions with Box-Cox transformation," Papers 2106.10723, arXiv.org.
    6. Pierre Chausse & George Luta, 2017. "Casual Inference using Generalized Empirical Likelihood Methods," Working Papers 1707, University of Waterloo, Department of Economics, revised Dec 2017.
    7. Hansen, Lars Peter, 2013. "Uncertainty Outside and Inside Economic Models," Nobel Prize in Economics documents 2013-7, Nobel Prize Committee.
    8. Morales-Oñate, Víctor & Crudu, Federico & Bevilacqua, Moreno, 2021. "Blockwise Euclidean likelihood for spatio-temporal covariance models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 176-201.
    9. Lorenzo Camponovo & Taisuke Otsu, 2015. "Robustness of Bootstrap in Instrumental Variable Regression," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 352-393, March.
    10. Saraswata Chaudhuri & Eric Renault, 2015. "Shrinkage of Variance for Minimum Distance Based Tests," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 328-351, March.
    11. Lavergne, Pascal, 2015. "Assessing the Approximate Validity of Moment Restrictions," TSE Working Papers 15-562, Toulouse School of Economics (TSE), revised May 2020.
    12. Lavergne, Pascal & Nguimkeu, Pierre, 2016. "A Hausman Specification Test of Conditional Moment Restrictions," TSE Working Papers 16-743, Toulouse School of Economics (TSE).
    13. Susanne M. Schennach, 2007. "Point estimation with exponentially tilted empirical likelihood," Papers 0708.1874, arXiv.org.
    14. Francisco Peñaranda & Enrique Sentana, 2015. "A Unifying Approach to the Empirical Evaluation of Asset Pricing Models," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 412-435, May.
    15. Hill, Jonathan B. & Prokhorov, Artem, 2016. "GEL estimation for heavy-tailed GARCH models with robust empirical likelihood inference," Journal of Econometrics, Elsevier, vol. 190(1), pages 18-45.
    16. Kiwitt, Sebastian & Nagel, Eva-Renate & Neumeyer, Natalie, 2005. "Empirical likelihood estimators for the error distribution in nonparametric regression models," Technical Reports 2005,45, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    17. Amélie Crepet & Hugo Harari-Kermadec & Jessica Tressou, 2007. "Using Empirical Likelihood to Combine Data : Application to Food Risk Assessment," Working Papers 2007-20, Center for Research in Economics and Statistics.
    18. Lars Peter Hansen, 2014. "Nobel Lecture: Uncertainty Outside and Inside Economic Models," Journal of Political Economy, University of Chicago Press, vol. 122(5), pages 945-987.
    19. Hill, Jonathan B., 2015. "Robust Generalized Empirical Likelihood for heavy tailed autoregressions with conditionally heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 131-152.
    20. Bertille Antoine & Prosper Dovonon, 2020. "Robust Estimation with Exponentially Tilted Hellinger Distance," Discussion Papers dp20-02, Department of Economics, Simon Fraser University.
    21. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    22. Fan, Yanqin & Gentry, Matthew & Li, Tong, 2011. "A new class of asymptotically efficient estimators for moment condition models," Journal of Econometrics, Elsevier, vol. 162(2), pages 268-277, June.
    23. Israelov, Roni & Lugauer, Steven, 2011. "Combining empirical likelihood and generalized method of moments estimators: Asymptotics and higher order bias," Statistics & Probability Letters, Elsevier, vol. 81(9), pages 1339-1347, September.
    24. Wang, Xuexin, 2016. "A New Class of Tests for Overidentifying Restrictions in Moment Condition Models," MPRA Paper 69004, University Library of Munich, Germany.
    25. Patrick Gagliardini & Diego Ronchetti, 2020. "Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 333-394.
    26. Crudu, Federico & Sándor, Zsolt, 2011. "On the finite-sample properties of conditional empirical likelihood estimators," MPRA Paper 34116, University Library of Munich, Germany.
    27. Bertille Antoine & Eric Renault, 2012. "Efficient Inference with Poor Instruments: a General Framework," Discussion Papers dp12-04, Department of Economics, Simon Fraser University.
    28. Enrique Sentana & Francisco Penaranda, 2004. "Spanning Tests in Return and Stochastic Discount Factor Mean-Variance Frontiers: A Unifying Approach," FMG Discussion Papers dp497, Financial Markets Group.
    29. Vitaliy Oryshchenko & Richard J. Smith, 2018. "Improved density and distribution function estimation," CeMMAP working papers CWP47/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. Xu, Ke-Li, 2020. "Inference of local regression in the presence of nuisance parameters," Journal of Econometrics, Elsevier, vol. 218(2), pages 532-560.
    31. Dovonon, Prosper, 2008. "Large sample properties of the three-step euclidean likelihood estimators under model misspecification," MPRA Paper 40025, University Library of Munich, Germany, revised 16 May 2010.
    32. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    33. Jose Blanchet & Yang Kang, 2021. "Sample Out-of-Sample Inference Based on Wasserstein Distance," Operations Research, INFORMS, vol. 69(3), pages 985-1013, May.
    34. Antoine, Bertille & Renault, Eric, 2020. "Testing identification strength," Journal of Econometrics, Elsevier, vol. 218(2), pages 271-293.
    35. Chunrong Ai & Xiaohong Chen, 2009. "Semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions," CeMMAP working papers CWP28/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    36. Alain Guay & Jean-Francois Lamarche, 2005. "The Information Content of Implied Probabilities to Detect Structural Change," Working Papers 0804, Brock University, Department of Economics, revised Oct 2008.
    37. Gospodinov, Nikolay & Otsu, Taisuke, 2012. "Local GMM estimation of time series models with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 170(2), pages 476-490.
    38. Almeida, Caio & Garcia, René, 2012. "Assessing misspecified asset pricing models with empirical likelihood estimators," Journal of Econometrics, Elsevier, vol. 170(2), pages 519-537.
    39. Gagliardini, Patrick & Ronchetti, Diego, 2013. "Semi-parametric estimation of American option prices," Journal of Econometrics, Elsevier, vol. 173(1), pages 57-82.
    40. Alain Guay & Florian Pelgrin, 2016. "Using Implied Probabilities to Improve the Estimation of Unconditional Moment Restrictions for Weakly Dependent Data," Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 344-372, March.
    41. Pierre Chaussé & Jin Liu & George Luta, 2016. "A Simulation-Based Comparison of Covariate Adjustment Methods for the Analysis of Randomized Controlled Trials," IJERPH, MDPI, vol. 13(4), pages 1-15, April.
    42. de Carvalho, Miguel & Oumow, Boris & Segers, Johan & WarchoÅ‚, MichaÅ‚, 2012. "A Euclidean likelihood estimator for bivariate tail dependence," LIDAM Discussion Papers ISBA 2012013, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    43. Seojeong Lee, 2018. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Empirical Likelihood Estimators," Papers 1806.00953, arXiv.org, revised Jun 2018.
    44. Federico Crudu, 2017. "Errors-in-Variables Models with Many Proxies," Department of Economics University of Siena 774, Department of Economics, University of Siena.
    45. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    46. Amélie Crépet & Hugo Harari-Kermadec & Jessica Tressou, 2009. "Using Empirical Likelihood to Combine Data: Application to Food Risk Assessment," Biometrics, The International Biometric Society, vol. 65(1), pages 257-266, March.
    47. Chaudhuri, Saraswata & Renault, Eric, 2020. "Score tests in GMM: Why use implied probabilities?," Journal of Econometrics, Elsevier, vol. 219(2), pages 260-280.
    48. Alain Guay & Florian Pelgrin, 2007. "Using Implied Probabilities to Improve Estimation with Unconditional Moment Restrictions," Cahiers de recherche 0747, CIRPEE.
    49. Guggenberger, Patrik & Ramalho, Joaquim J.S. & Smith, Richard J., 2012. "GEL statistics under weak identification," Journal of Econometrics, Elsevier, vol. 170(2), pages 331-349.

  12. Bertille Antoine & Kevin Proulx & Eric Renault, 0. "Pseudo-True SDFs in Conditional Asset Pricing Models," Journal of Financial Econometrics, Oxford University Press, vol. 18(4), pages 656-714.

    Cited by:

    1. Patrick Gagliardini & Diego Ronchetti, 2020. "Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 333-394.
    2. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.

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NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 14 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 (13) 2012-04-10 2012-04-10 2012-09-30 2014-07-13 2014-08-09 2015-06-13 2015-06-20 2017-09-24 2019-04-29 2020-03-16 2020-08-10 2021-10-11 2024-08-12. Author is listed
  2. NEP-ORE: Operations Research (6) 2015-06-20 2019-04-29 2020-03-09 2020-03-16 2020-08-10 2021-10-11. Author is listed
  3. NEP-ETS: Econometric Time Series (1) 2024-08-12
  4. NEP-PBE: Public Economics (1) 2012-04-10

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