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Alexandre Poirier

Personal Details

First Name:Alexandre
Middle Name:
Last Name:Poirier
Suffix:
RePEc Short-ID:ppo600
[This author has chosen not to make the email address public]
https://sites.google.com/site/alexpoirierecon/
Terminal Degree:2013 Department of Economics; University of California-Berkeley (from RePEc Genealogy)

Affiliation

Economics Department
Georgetown University

Washington, District of Columbia (United States)
http://econ.georgetown.edu/
RePEc:edi:edgeous (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Software

Working papers

  1. Alexandre Poirier & Tymon S{l}oczy'nski, 2024. "Quantifying the Internal Validity of Weighted Estimands," Papers 2404.14603, arXiv.org.
  2. Matthew A. Masten & Alexandre Poirier, 2022. "The Effect of Omitted Variables on the Sign of Regression Coefficients," Papers 2208.00552, arXiv.org, revised Feb 2023.
  3. Paul Diegert & Matthew A. Masten & Alexandre Poirier, 2022. "Assessing Omitted Variable Bias when the Controls are Endogenous," Papers 2206.02303, arXiv.org, revised Jul 2023.
  4. Matthew A. Masten & Alexandre Poirier, 2022. "Choosing Exogeneity Assumptions in Potential Outcome Models," Papers 2205.02288, arXiv.org.
  5. Laura Liu & Alexandre Poirier & Ji-Liang Shiu, 2021. "Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models," Papers 2105.12891, arXiv.org, revised Jul 2024.
  6. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2020. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Papers 2012.15716, arXiv.org.
  7. Matthew Masten & Alexandre Poirier, 2019. "tesensitivity: A Stata Package for Assessing the Unconfoundedness Assumption," 2019 Stata Conference 51, Stata Users Group.
  8. Matthew A. Masten & Alexandre Poirier, 2018. "Interpreting Quantile Independence," Papers 1804.10957, arXiv.org.
  9. Matthew A. Masten & Alexandre Poirier, 2018. "Salvaging Falsified Instrumental Variable Models," Papers 1812.11598, arXiv.org, revised Jan 2020.
  10. Matthew A. Masten & Alexandre Poirier, 2017. "Identification of Treatment Effects under Conditional Partial Independence," Papers 1707.09563, arXiv.org.
  11. Matthew A. Masten & Alexandre Poirier, 2017. "Inference on Breakdown Frontiers," Papers 1705.04765, arXiv.org, revised Feb 2019.
  12. Matthew Masten & Alexandre Poirier, 2016. "Partial independence in nonseparable models," CeMMAP working papers 26/16, Institute for Fiscal Studies.
  13. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.
  14. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers 12/15, Institute for Fiscal Studies.

Articles

  1. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2024. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(1), pages 1-13, January.
  2. Matthew A Masten & Alexandre Poirier, 2023. "Choosing exogeneity assumptions in potential outcome models," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 327-349.
  3. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
  4. Matthew A. Masten & Alexandre Poirier, 2021. "Salvaging Falsified Instrumental Variable Models," Econometrica, Econometric Society, vol. 89(3), pages 1449-1469, May.
  5. Matthew A. Masten & Alexandre Poirier, 2020. "Inference on breakdown frontiers," Quantitative Economics, Econometric Society, vol. 11(1), pages 41-111, January.
  6. Antonio F. Galvao & Alexandre Poirier, 2019. "Quantile Regression Random Effects," Annals of Economics and Statistics, GENES, issue 134, pages 109-148.
  7. Alexandre Poirier & Nicolas L. Ziebarth, 2019. "Estimation of Models With Multiple-Valued Explanatory Variables," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 586-597, October.
  8. Matthew A. Masten & Alexandre Poirier, 2018. "Identification of Treatment Effects Under Conditional Partial Independence," Econometrica, Econometric Society, vol. 86(1), pages 317-351, January.
  9. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
  10. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
  11. Jose Miguel Abito & Katarina Borovickova & Hays Golden & Jacob Goldin & Matthew A. Masten & Miguel Morin & Alexandre Poirier & Vincent Pons & Israel Romem & Tyler Williams & Chamna Yoon, 2011. "How Should the Graduate Economics Core be Changed?," The Journal of Economic Education, Taylor & Francis Journals, vol. 42(4), pages 414-417, October.

Software components

  1. Paul Diegert & Matthew A. Masten & Alexandre Poirier, 2022. "REGSENSITIVITY: Stata module for regression sensitivity analysis," Statistical Software Components S459088, Boston College Department of Economics, revised 07 Aug 2022.
  2. Linqi Zhang & Paul Diegert & Matthew A. Masten & Alexandre Poirier, 2021. "TESENSITIVITY: Stata module for assessing sensitivity to the unconfoundedness assumption," Statistical Software Components S458896, Boston College Department of Economics.

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. Paul Diegert & Matthew A. Masten & Alexandre Poirier, 2022. "Assessing Omitted Variable Bias when the Controls are Endogenous," Papers 2206.02303, arXiv.org, revised Jul 2023.

    Cited by:

    1. Jeremy Clark & Abel François & Olivier Gergaud, 2024. "Social capital, social heterogeneity, and electoral turnout," Kyklos, Wiley Blackwell, vol. 77(4), pages 1142-1168, November.
    2. Alberto Montagnoli & Karl Taylor, 2024. "Who Cares about Investing Responsibly? Attitudes and Financial Decisions," Working Papers 2024010, The University of Sheffield, Department of Economics.
    3. Kaicheng Chen & Kyoo il Kim, 2024. "Identification of Nonseparable Models with Endogenous Control Variables," Papers 2401.14395, arXiv.org.
    4. João Martins & Linda Veiga & Bruno Fernandes, 2023. "Are electronic government innovations helpful to deter corruption? Evidence from across the world," Economics and Politics, Wiley Blackwell, vol. 35(3), pages 1177-1203, November.

  2. Laura Liu & Alexandre Poirier & Ji-Liang Shiu, 2021. "Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models," Papers 2105.12891, arXiv.org, revised Jul 2024.

    Cited by:

    1. Senay Sokullu & Irene Botosaru & Chris Muris, 2022. "Time-Varying Linear Transformation Models with Fixed Effects and Endogeneity for Short Panels," Bristol Economics Discussion Papers 22/756, School of Economics, University of Bristol, UK.

  3. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2020. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Papers 2012.15716, arXiv.org.

    Cited by:

    1. Paul Diegert & Matthew A. Masten & Alexandre Poirier, 2022. "Assessing Omitted Variable Bias when the Controls are Endogenous," Papers 2206.02303, arXiv.org, revised Jul 2023.
    2. Jacob Dorn & Kevin Guo, 2021. "Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing," Papers 2102.04543, arXiv.org, revised Aug 2023.
    3. Miklin Nikolai & Gachechiladze Mariami & Moreno George & Chaves Rafael, 2022. "Causal inference with imperfect instrumental variables," Journal of Causal Inference, De Gruyter, vol. 10(1), pages 45-63, January.
    4. Santiago Acerenza & Vitor Possebom & Pedro H. C. Sant'Anna, 2023. "Was Javert right to be suspicious? Unpacking treatment effect heterogeneity of alternative sentences on time-to-recidivism in Brazil," Papers 2311.13969, arXiv.org, revised May 2024.
    5. Adamecz, Anna & Lovász, Anna & Vujic, Suncica, 2024. "Beyond the Degree: Fertility Outcomes of 'First in Family' Graduates," IZA Discussion Papers 17216, Institute of Labor Economics (IZA).
    6. Alberto Montagnoli & Karl Taylor, 2024. "Who Cares about Investing Responsibly? Attitudes and Financial Decisions," Working Papers 2024010, The University of Sheffield, Department of Economics.
    7. Tabe-Ojong, Martin Paul Jr. & Nshakira-Rukundo, Emmanuel, 2021. "Religiosity and parental educational aspirations for children in Kenya," World Development Perspectives, Elsevier, vol. 23(C).

  4. Matthew A. Masten & Alexandre Poirier, 2018. "Salvaging Falsified Instrumental Variable Models," Papers 1812.11598, arXiv.org, revised Jan 2020.

    Cited by:

    1. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    2. Nicolas Apfel & Frank Windmeijer, 2022. "The Falsification Adaptive Set in Linear Models with Instrumental Variables that Violate the Exclusion or Conditional Exogeneity Restriction," Papers 2212.04814, arXiv.org, revised Apr 2024.
    3. Han, Sukjin & Yang, Shenshen, 2024. "A computational approach to identification of treatment effects for policy evaluation," Journal of Econometrics, Elsevier, vol. 240(1).
    4. Timothy B. Armstrong & Michal Koles'r, 2018. "Sensitivity Analysis using Approximate Moment Condition Models," Cowles Foundation Discussion Papers 2158R, Cowles Foundation for Research in Economics, Yale University, revised Feb 2019.
    5. Ban, Kyunghoon & Kedagni, Desire, 2020. "Nonparametric Bounds on Treatment Effects with Imperfect Instruments," ISU General Staff Papers 202010120700001113, Iowa State University, Department of Economics.
    6. Jakob Madsen & Holger Strulik, 2023. "Testing unified growth theory: Technological progress and the child quantity‐quality tradeoff," Quantitative Economics, Econometric Society, vol. 14(1), pages 235-275, January.
    7. Charles F. Manski, 2019. "Econometrics For Decision Making: Building Foundations Sketched By Haavelmo And Wald," Papers 1912.08726, arXiv.org, revised Feb 2021.
    8. Nicolas Apfel & Julia Hatamyar & Martin Huber & Jannis Kueck, 2024. "Learning control variables and instruments for causal analysis in observational data," Papers 2407.04448, arXiv.org.
    9. Xavier D'Haultfoeuille & Christophe Gaillac & Arnaud Maurel, 2021. "Rationalizing rational expectations: Characterizations and tests," Quantitative Economics, Econometric Society, vol. 12(3), pages 817-842, July.
    10. Lixiong Li & D'esir'e K'edagni & Ismael Mourifi'e, 2020. "Discordant Relaxations of Misspecified Models," Papers 2012.11679, arXiv.org, revised Apr 2024.
    11. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    12. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Adnan M.S. Fakir & Tushar Bharati, 2022. "Health Costs of a "Healthy Democracy": The Impact of Peaceful Political Protests on Healthcare Utilization," Working Paper Series 0522, Department of Economics, University of Sussex Business School.
    14. Matthew A. Masten & Alexandre Poirier, 2021. "Salvaging Falsified Instrumental Variable Models," Econometrica, Econometric Society, vol. 89(3), pages 1449-1469, May.
    15. Moyu Liao, 2020. "Estimating Economic Models with Testable Assumptions: Theory and Applications," Papers 2002.10415, arXiv.org, revised Mar 2022.
    16. Mathieu Marcoux & Thomas Russell & Yuanyuan Wan, 2023. "A Simple Specification Test for Models with Many Conditional Moment Inequalities," Working Papers tecipa-764, University of Toronto, Department of Economics.
    17. Stéphane Bonhomme & Martin Weidner, 2022. "Minimizing sensitivity to model misspecification," Quantitative Economics, Econometric Society, vol. 13(3), pages 907-954, July.

  5. Matthew A. Masten & Alexandre Poirier, 2017. "Identification of Treatment Effects under Conditional Partial Independence," Papers 1707.09563, arXiv.org.

    Cited by:

    1. Tenglong Li & Kenneth A. Frank, 2020. "The probability of a robust inference for internal validity and its applications in regression models," Papers 2005.12784, arXiv.org.
    2. Paul Diegert & Matthew A. Masten & Alexandre Poirier, 2022. "Assessing Omitted Variable Bias when the Controls are Endogenous," Papers 2206.02303, arXiv.org, revised Jul 2023.
    3. Sakaue, Katsuki & Wokadala, James, 2022. "Effects of including refugees in local government schools on pupils’ learning achievement: Evidence from West Nile, Uganda," International Journal of Educational Development, Elsevier, vol. 90(C).
    4. Yiwei Sun, 2023. "Extrapolating Away from the Cutoff in Regression Discontinuity Designs," Papers 2311.18136, arXiv.org.
    5. Sungwon Lee, 2021. "Partial Identification and Inference for Conditional Distributions of Treatment Effects," Papers 2108.00723, arXiv.org, revised Nov 2023.
    6. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    7. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2024. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(1), pages 1-13, January.
    8. Arkadiusz Szydłowski, 2019. "Endogenous censoring in the mixed proportional hazard model with an application to optimal unemployment insurance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1086-1101, November.
    9. Christophe Bruneel-Zupanc, 2023. "Don't (fully) exclude me, it's not necessary! Identification with semi-IVs," Papers 2303.12667, arXiv.org, revised Jul 2023.
    10. Nathan Canen & Kyungchul Song, 2019. "Counterfactual Analysis under Partial Identification Using Locally Robust Refinement," Papers 1906.00003, arXiv.org, revised Jan 2021.
    11. Tenglong Li & Kenneth A. Frank, 2019. "On the probability of a causal inference is robust for internal validity," Papers 1906.08726, arXiv.org.
    12. Matthew A. Masten & Alexandre Poirier, 2022. "The Effect of Omitted Variables on the Sign of Regression Coefficients," Papers 2208.00552, arXiv.org, revised Feb 2023.
    13. Tenglong Li & Kenneth A. Frank & Mingming Chen, 2024. "A Conceptual Framework for Quantifying the Robustness of a Regression-Based Causal Inference in Observational Study," Mathematics, MDPI, vol. 12(3), pages 1-14, January.
    14. Sungwon Lee, 2024. "Partial identification and inference for conditional distributions of treatment effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 107-127, January.

  6. Matthew A. Masten & Alexandre Poirier, 2017. "Inference on Breakdown Frontiers," Papers 1705.04765, arXiv.org, revised Feb 2019.

    Cited by:

    1. Brantly Callaway, 2020. "Bounds on Distributional Treatment Effect Parameters using Panel Data with an Application on Job Displacement," Papers 2008.08117, arXiv.org.
    2. Gunsilius, Florian F., 2023. "A condition for the identification of multivariate models with binary instruments," Journal of Econometrics, Elsevier, vol. 235(1), pages 220-238.
    3. Raffaella Giacomini & Toru Kitagawa & Alessio Volpicella, 2017. "Uncertain identification," CeMMAP working papers 18/17, Institute for Fiscal Studies.
    4. Kaspar W thrich, 2014. "A Comparison of two Quantile Models with Endogeneity," Diskussionsschriften dp1408, Universitaet Bern, Departement Volkswirtschaft.
    5. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    6. Hiroaki Kaido & Jiaxuan Li & Marc Rysman, 2018. "Moment Inequalities in the Context of Simulated and Predicted Variables," Papers 1804.03674, arXiv.org.
    7. Harsh Parikh & Marco Morucci & Vittorio Orlandi & Sudeepa Roy & Cynthia Rudin & Alexander Volfovsky, 2023. "A Double Machine Learning Approach to Combining Experimental and Observational Data," Papers 2307.01449, arXiv.org, revised Apr 2024.
    8. Firpo, Sergio & Galvao, Antonio F. & Parker, Thomas, 2023. "Uniform inference for value functions," Journal of Econometrics, Elsevier, vol. 235(2), pages 1680-1699.
    9. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    10. Vitor Possebom, 2021. "Crime and Mismeasured Punishment: Marginal Treatment Effect with Misclassification," Papers 2106.00536, arXiv.org, revised Jul 2023.
    11. Daniel Ober-Reynolds, 2024. "Robustness to Missing Data: Breakdown Point Analysis," Papers 2406.06804, arXiv.org.
    12. Firpo, Sergio & Galvao, Antonio F. & Kobus, Martyna & Parker, Thomas & Rosa-Dias, Pedro, 2020. "Loss Aversion and the Welfare Ranking of Policy Interventions," IZA Discussion Papers 13176, Institute of Labor Economics (IZA).
    13. Kamat, Vishal, 2024. "Identifying the effects of a program offer with an application to Head Start," Journal of Econometrics, Elsevier, vol. 240(1).
    14. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Oct 2021.
    15. Zheng Fang & Juwon Seo, 2019. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Papers 1910.07689, arXiv.org, revised Sep 2021.
    16. Isaiah Andrews & Matthew Gentzkow & Jesse M. Shapiro, 2020. "Transparency in Structural Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(4), pages 711-722, October.
    17. Matthew A. Masten & Alexandre Poirier, 2021. "Salvaging Falsified Instrumental Variable Models," Econometrica, Econometric Society, vol. 89(3), pages 1449-1469, May.
    18. Stéphane Bonhomme & Martin Weidner, 2020. "Minimizing Sensitivity to Model Misspecification," CeMMAP working papers CWP37/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Tamara Broderick & Ryan Giordano & Rachael Meager, 2020. "An Automatic Finite-Sample Robustness Metric: When Can Dropping a Little Data Make a Big Difference?," Papers 2011.14999, arXiv.org, revised Jul 2023.
    20. Pietro Emilio Spini, 2021. "Robustness, Heterogeneous Treatment Effects and Covariate Shifts," Papers 2112.09259, arXiv.org, revised Aug 2024.
    21. Claudia Noack, 2021. "Sensitivity of LATE Estimates to Violations of the Monotonicity Assumption," Papers 2106.06421, arXiv.org.
    22. Candelaria, Luis E. & Ura, Takuya, 2023. "Identification and inference of network formation games with misclassified links," Journal of Econometrics, Elsevier, vol. 235(2), pages 862-891.

  7. Matthew Masten & Alexandre Poirier, 2016. "Partial independence in nonseparable models," CeMMAP working papers 26/16, Institute for Fiscal Studies.

    Cited by:

    1. Matthew A. Masten & Alexandre Poirier, 2018. "Interpreting Quantile Independence," Papers 1804.10957, arXiv.org.
    2. Matthew A Masten & Alexandre Poirier, 2023. "Choosing exogeneity assumptions in potential outcome models," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 327-349.
    3. Matthew Masten & Alexandre Poirier, 2017. "Inference on breakdown frontiers," CeMMAP working papers 20/17, Institute for Fiscal Studies.
    4. Andrii Babii & Jean-Pierre Florens, 2017. "Are Unobservables Separable?," Papers 1705.01654, arXiv.org, revised Mar 2021.
    5. Matthew A. Masten & Alexandre Poirier, 2017. "Identification of Treatment Effects under Conditional Partial Independence," Papers 1707.09563, arXiv.org.
    6. Alexander Torgovitsky, 2019. "Partial identification by extending subdistributions," Quantitative Economics, Econometric Society, vol. 10(1), pages 105-144, January.

  8. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Younes Ben Zaied & Béchir Ben Lahouel, 2021. "Does environmental CSR performance matter for corporate financial performance? Evidence from panel quantile regression," Economics Bulletin, AccessEcon, vol. 41(3), pages 938-951.
    3. Liang Chen & Yulong Huo, 2019. "A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions," Papers 1911.04729, arXiv.org.
    4. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.
    5. Fateh Belaïd & Ahmed Elsayed & Anis Omri, 2021. "Key drivers of renewable energy deployment in the MENA Region: Empirical evidence using panel quantile regression," Post-Print hal-03272568, HAL.
    6. Ming Li, 2021. "Identification and Estimation in a Time-Varying Endogenous Random Coefficient Panel Data Model," Papers 2110.00982, arXiv.org, revised Nov 2024.
    7. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    8. Xin Liu, 2024. "A quantile-based nonadditive fixed effects model," Papers 2405.03826, arXiv.org.
    9. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.
    10. Fateh Belaid & Ahmed H. Elsayed, 2019. "What drives renewable energy production in MENA Region? Investigating the roles of political stability, governance and financial sector," Working Papers 1322, Economic Research Forum, revised 21 Aug 2019.
    11. Georges Bresson & Guy Lacroix & Mohammad Arshad Rahman, 2021. "Bayesian panel quantile regression for binary outcomes with correlated random effects: an application on crime recidivism in Canada," Empirical Economics, Springer, vol. 60(1), pages 227-259, January.
    12. Panagiotidis, Theodore & Printzis, Panagiotis, 2021. "Investment and uncertainty: Are large firms different from small ones?," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 302-317.
    13. Patrick Kline & Raffaele Saggio & Mikkel S{o}lvsten, 2018. "Leave-out estimation of variance components," Papers 1806.01494, arXiv.org, revised Aug 2019.
    14. Galvao, Antonio F. & Gu, Jiaying & Volgushev, Stanislav, 2020. "On the unbiased asymptotic normality of quantile regression with fixed effects," Journal of Econometrics, Elsevier, vol. 218(1), pages 178-215.
    15. Yonggang Ji & Haifang Shi, 2020. "Bayesian variable selection in linear quantile mixed models for longitudinal data with application to macular degeneration," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-34, October.
    16. Xiao, Zhijie & Xu, Lan, 2019. "What do mean impacts miss? Distributional effects of corporate diversification," Journal of Econometrics, Elsevier, vol. 213(1), pages 92-120.
    17. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
    18. Alexandre Belloni & Mingli Chen & Oscar Hernan Madrid Padilla & Zixuan & Wang, 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," Papers 1912.02151, arXiv.org, revised Aug 2022.
    19. Lethiwe Nzama & Thanda Sithole & Sezer Bozkus Kahyaoglu, 2022. "The Impact of Government Effectiveness on Trade and Financial Openness: The Generalized Quantile Panel Regression Approach," JRFM, MDPI, vol. 16(1), pages 1-20, December.
    20. Jaepil Han, 2020. "Identifying the effects of technology transfer policy using a quantile regression: the case of South Korea," The Journal of Technology Transfer, Springer, vol. 45(6), pages 1690-1717, December.
    21. Jennifer Betz & Maximilian Nagl & Daniel Rösch, 2022. "Credit line exposure at default modelling using Bayesian mixed effect quantile regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2035-2072, October.
    22. Sungwon Lee, 2020. "Nonparametric Identification and Estimation of Panel Quantile Models with Sample Selection," Working Papers 2012, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    23. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    24. Asfaw, Solomon & Pallante, Giacomo & Palma, Alessandro, 2020. "Distributional impacts of soil erosion on agricultural productivity and welfare in Malawi," Ecological Economics, Elsevier, vol. 177(C).

  9. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers 12/15, Institute for Fiscal Studies.

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2020. "Network and Panel Quantile Effects Via Distribution Regression," CeMMAP working papers CWP27/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Jorge E. Galán, 2020. "The benefits are at the tail: uncovering the impact of macroprudential policy on growth-at-risk," Working Papers 2007, Banco de España.
    3. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers CWP40/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Pietro Santoleri, 2020. "Innovation and job creation in (high-growth) new firms," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 29(3), pages 731-756.
    5. Sandra Kendo & Josephine Tchakounte, 2022. "Impact of asset size on performance and outreach using panel quantile regression with non-additive fixed effects," Empirical Economics, Springer, vol. 62(1), pages 65-92, January.
    6. Borsati, Mattia & Nocera, Silvio & Percoco, Marco, 2022. "Questioning the spatial association between the initial spread of COVID-19 and transit usage in Italy," Research in Transportation Economics, Elsevier, vol. 95(C).
    7. Klayme, Tania & Gokmenoglu, Korhan K. & Rustamov, Bezhan, 2023. "Economic policy uncertainty, COVID-19 and corporate investment: Evidence from the gold mining industry," Resources Policy, Elsevier, vol. 85(PA).
    8. Roula Inglesi-Lotz & Anna Maria Oosthuizen & Sharifa Jumaniyazova & Bekhzod Kuziboev & Jie Liu, 2024. "Exploring the Impact of Women Governance on CO2 Emissions in the European Union and Central Asia," International Journal of Energy Economics and Policy, Econjournals, vol. 14(3), pages 639-646, May.
    9. George S. Atsalakis & Elie Bouri & Fotios Pasiouras, 2021. "Natural disasters and economic growth: a quantile on quantile approach," Annals of Operations Research, Springer, vol. 306(1), pages 83-109, November.
    10. Talan, Amogh & Rao, Amar & Sharma, Gagan Deep & Apostu, Simona-Andreea & Abbas, Shujaat, 2023. "Transition towards clean energy consumption in G7: Can financial sector, ICT and democracy help?," Resources Policy, Elsevier, vol. 82(C).
    11. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    12. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
    13. Kendo, Sandra & Tchakounte, Josephine, 2022. "The drivers of the financial integration of microfinance Institutions: Do financial development, agency costs and microfinance performance matter?," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 128-142.
    14. Wei Feng & Yanrui Wu & Yue Fu, 2021. "Dialect Diversity and Foreign Direct Investment in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(2), pages 49-72, March.
    15. Yuya Sasaki & Takuya Ura, 2021. "Slow Movers in Panel Data," Papers 2110.12041, arXiv.org.
    16. Yanay Farja & Avi Tillman & Ori Zax, 2022. "The Gender Gap: Looking at the Entire Distribution," Journal of Interdisciplinary Economics, , vol. 34(1), pages 51-68, January.
    17. Sandra Kendo & Josephine Tchakounte, 2022. "The drivers of the financial integration of microfinance Institutions: Do financial development, agency costs and microfinance performance matter?," Post-Print hal-04529938, HAL.
    18. Kusiyah Kusiyah & Mansoor Mushtaq & Shabbir Ahmed & Ansar Abbas & Mochammad Fahlevi, 2024. "Impact of Urbanization on Environmental Eminence: Moderating Role of Renewable Energy," International Journal of Energy Economics and Policy, Econjournals, vol. 14(2), pages 244-257, March.

Articles

  1. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2024. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(1), pages 1-13, January.
    See citations under working paper version above.
  2. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.

    Cited by:

    1. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.

  3. Matthew A. Masten & Alexandre Poirier, 2021. "Salvaging Falsified Instrumental Variable Models," Econometrica, Econometric Society, vol. 89(3), pages 1449-1469, May.
    See citations under working paper version above.
  4. Matthew A. Masten & Alexandre Poirier, 2020. "Inference on breakdown frontiers," Quantitative Economics, Econometric Society, vol. 11(1), pages 41-111, January.
    See citations under working paper version above.
  5. Antonio F. Galvao & Alexandre Poirier, 2019. "Quantile Regression Random Effects," Annals of Economics and Statistics, GENES, issue 134, pages 109-148.

    Cited by:

    1. Paulo M.M. Rodrigues & Matei Demetrescu, 2022. "Cross-Sectional Error Dependence in Panel Quantile Regressions," Working Papers w202213, Banco de Portugal, Economics and Research Department.
    2. Demetrescu, Matei & Hosseinkouchack, Mehdi & Rodrigues, Paulo M. M., 2023. "Tests of no cross-sectional error dependence in panel quantile regressions," Ruhr Economic Papers 1041, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. Haddou, Samira, 2024. "Determinants of CDS in core and peripheral European countries: A comparative study during crisis and calm periods," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    4. Georges Bresson & Guy Lacroix & Mohammad Arshad Rahman, 2021. "Bayesian panel quantile regression for binary outcomes with correlated random effects: an application on crime recidivism in Canada," Empirical Economics, Springer, vol. 60(1), pages 227-259, January.
    5. Schorr, A. & Lips, M., 2018. "Influence of milk yield on profitability a quantile regression analysis," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277000, International Association of Agricultural Economists.
    6. Jennifer Betz & Maximilian Nagl & Daniel Rösch, 2022. "Credit line exposure at default modelling using Bayesian mixed effect quantile regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2035-2072, October.
    7. Martina Pons & Blaise Melly, 2022. "Stata commands to estimate quantile regression with panel and grouped data," Swiss Stata Conference 2022 05, Stata Users Group.

  6. Alexandre Poirier & Nicolas L. Ziebarth, 2019. "Estimation of Models With Multiple-Valued Explanatory Variables," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 586-597, October.

    Cited by:

    1. KARBOWNIK, Krzysztof & WRAY, Anthony & レイ, アンソニ, 2016. "Long-run Consequences of Exposure to Natural Disasters," Discussion paper series HIAS-E-36, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    2. Millimet, Daniel L., 2024. "(Don't) Walk This Way: The Econometrics of Crosswalks," IZA Discussion Papers 17154, Institute of Labor Economics (IZA).
    3. Sarada, Sarada & Andrews, Michael J. & Ziebarth, Nicolas L., 2019. "Changes in the demographics of American inventors, 1870–1940," Explorations in Economic History, Elsevier, vol. 74(C).
    4. Hwang, Sam Il Myoung & Squires, Munir, 2024. "Linked samples and measurement error in historical US census data," Explorations in Economic History, Elsevier, vol. 93(C).

  7. Matthew A. Masten & Alexandre Poirier, 2018. "Identification of Treatment Effects Under Conditional Partial Independence," Econometrica, Econometric Society, vol. 86(1), pages 317-351, January.
    See citations under working paper version above.
  8. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    See citations under working paper version above.
  9. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.

    Cited by:

    1. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    2. Jad Beyhum & Lorenzo Tedesco & Ingrid Van Keilegom, 2022. "Instrumental variable quantile regression under random right censoring," Papers 2209.01429, arXiv.org, revised Feb 2023.
    3. Junlong Feng & Sokbae Lee, 2023. "Individual Welfare Analysis: Random Quasilinear Utility, Independence, and Confidence Bounds," Papers 2304.01921, arXiv.org, revised Nov 2024.

  10. Jose Miguel Abito & Katarina Borovickova & Hays Golden & Jacob Goldin & Matthew A. Masten & Miguel Morin & Alexandre Poirier & Vincent Pons & Israel Romem & Tyler Williams & Chamna Yoon, 2011. "How Should the Graduate Economics Core be Changed?," The Journal of Economic Education, Taylor & Francis Journals, vol. 42(4), pages 414-417, October.

    Cited by:

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 13 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 (12) 2015-03-27 2016-07-16 2017-05-14 2017-11-05 2018-05-07 2019-01-14 2021-02-01 2021-05-31 2022-06-13 2022-07-18 2022-09-05 2024-06-10. Author is listed
  2. NEP-DCM: Discrete Choice Models (5) 2016-07-16 2017-11-05 2019-08-26 2021-02-01 2021-05-31. Author is listed
  3. NEP-DEM: Demographic Economics (1) 2022-07-18
  4. NEP-GER: German Papers (1) 2016-07-16
  5. NEP-RMG: Risk Management (1) 2018-05-07

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