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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/

Affiliation

Economics Department
Georgetown University

Washington, District of Columbia (United States)
http://econ.georgetown.edu/

202-687-5601
202-687-6102
ICC 580, Georgetown University, Washington, D.C. 20057-1036
RePEc:edi:edgeous (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Software

Working papers

  1. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2020. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Papers 2012.15716, arXiv.org.
  2. Matthew Masten & Alexandre Poirier, 2019. "tesensitivity: A Stata Package for Assessing the Unconfoundedness Assumption," 2019 Stata Conference 51, Stata Users Group.
  3. Matthew A. Masten & Alexandre Poirier, 2018. "Salvaging Falsified Instrumental Variable Models," Papers 1812.11598, arXiv.org, revised Jan 2020.
  4. Matthew A. Masten & Alexandre Poirier, 2018. "Interpreting Quantile Independence," Papers 1804.10957, arXiv.org.
  5. Matthew A. Masten & Alexandre Poirier, 2017. "Identification of Treatment Effects under Conditional Partial Independence," Papers 1707.09563, arXiv.org.
  6. Matthew Masten & Alexandre Poirier, 2017. "Inference on breakdown frontiers," CeMMAP working papers CWP20/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  7. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers CWP34/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  8. Matthew Masten & Alexandre Poirier, 2016. "Partial independence in nonseparable models," CeMMAP working papers CWP26/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  9. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers CWP12/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

Articles

  1. Matthew A. Masten & Alexandre Poirier, 2020. "Inference on breakdown frontiers," Quantitative Economics, Econometric Society, vol. 11(1), pages 41-111, January.
  2. Antonio F. Galvao & Alexandre Poirier, 2019. "Quantile Regression Random Effects," Annals of Economics and Statistics, GENES, issue 134, pages 109-148.
  3. 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.
  4. Matthew A. Masten & Alexandre Poirier, 2018. "Identification of Treatment Effects Under Conditional Partial Independence," Econometrica, Econometric Society, vol. 86(1), pages 317-351, January.
  5. 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.
  6. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
  7. 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. 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. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2020. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Papers 2012.15716, arXiv.org.

    Cited by:

    1. Jacob Dorn & Kevin Guo, 2021. "Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing," Papers 2102.04543, arXiv.org.

  2. 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. Ban, Kyunghoon & Kedagni, Desire, 2020. "Nonparametric Bounds on Treatment Effects with Imperfect Instruments," ISU General Staff Papers 202010120700001113, Iowa State University, Department of Economics.
    3. Xavier D'Haultfoeuille & Christophe Gaillac & Arnaud Maurel, 2020. "Rationalizing Rational Expectations: Characterization and Tests," Papers 2003.11537, arXiv.org, revised Dec 2020.
    4. D'esir'e K'edagni & Lixiong Li & Ismael Mourifi'e, 2020. "Discordant Relaxations of Misspecified Models," Papers 2012.11679, arXiv.org.
    5. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    6. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Moyu Liao, 2020. "Estimating Economic Models with Testable Assumptions: Theory and Applications," Papers 2002.10415, arXiv.org, revised Jul 2020.

  3. 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. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    3. 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.
    4. Tenglong Li & Kenneth A. Frank, 2019. "On the probability of a causal inference is robust for internal validity," Papers 1906.08726, arXiv.org.
    5. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2020. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Papers 2012.15716, arXiv.org.

  4. Matthew Masten & Alexandre Poirier, 2017. "Inference on breakdown frontiers," CeMMAP working papers CWP20/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    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. Hiroaki Kaido & Jiaxuan Li & Marc Rysman, 2018. "Moment Inequalities in the Context of Simulated and Predicted Variables," Papers 1804.03674, arXiv.org.
    3. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    4. 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).
    5. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Dec 2020.
    6. Zheng Fang & Juwon Seo, 2019. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Papers 1910.07689, arXiv.org, revised Jan 2021.
    7. 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.
    8. Sergio Firpo & Antonio F. Galvao & Thomas Parker, 2019. "Uniform inference for value functions," Papers 1911.10215, arXiv.org, revised Dec 2020.
    9. Matthew A. Masten & Alexandre Poirier, 2018. "Salvaging Falsified Instrumental Variable Models," Papers 1812.11598, arXiv.org, revised Jan 2020.
    10. Tamara Broderick & Ryan Giordano & Rachael Meager, 2020. "An Automatic Finite-Sample Robustness Metric: Can Dropping a Little Data Change Conclusions?," Papers 2011.14999, arXiv.org.
    11. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2018. "Covariate Distribution Balance via Propensity Scores," Papers 1810.01370, arXiv.org, revised Apr 2020.

  5. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers CWP34/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Liang Chen & Yulong Huo, 2019. "A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions," Papers 1911.04729, arXiv.org.
    2. 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.
    3. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    4. 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.
    5. 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.
    6. Patrick Kline & Raffaele Saggio & Mikkel S{o}lvsten, 2018. "Leave-out estimation of variance components," Papers 1806.01494, arXiv.org, revised Aug 2019.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org.
    12. 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.
    13. Antonio F. Galvao & Jiaying Gu & Stanislav Volgushev, 2018. "On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects," Papers 1807.11863, arXiv.org, revised Feb 2020.
    14. 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.
    15. Theodore Panagiotidis & Panagiotis Printzis, 2021. "Investment and Uncertainty: Are large firms different from small ones?," Discussion Paper Series 2021_06, Department of Economics, University of Macedonia, revised Feb 2021.
    16. Sungwon Lee, 2020. "Nonparametric Identication and Estimation of Panel Quantile Models with Sample Selection," Working Papers 2012, Research Institute for Market Economy, Sogang University.
    17. 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).
    18. 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).

  6. Matthew Masten & Alexandre Poirier, 2016. "Partial independence in nonseparable models," CeMMAP working papers CWP26/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Matthew A. Masten & Alexandre Poirier, 2018. "Interpreting Quantile Independence," Papers 1804.10957, arXiv.org.
    2. Matthew Masten & Alexandre Poirier, 2017. "Inference on breakdown frontiers," CeMMAP working papers CWP20/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Andrii Babii & Jean-Pierre Florens, 2017. "Are Unobservables Separable?," Papers 1705.01654, arXiv.org, revised Mar 2021.
    4. Matthew A. Masten & Alexandre Poirier, 2017. "Identification of Treatment Effects under Conditional Partial Independence," Papers 1707.09563, arXiv.org.
    5. Alexander Torgovitsky, 2019. "Partial identification by extending subdistributions," Quantitative Economics, Econometric Society, vol. 10(1), pages 105-144, January.

  7. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers CWP12/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. 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;Working Papers Homepage.
    2. 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.
    3. 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.
    4. Pietro Santoleri, 2019. "Innovation and job creation in (high-growth) new firms," LEM Papers Series 2019/31, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. 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.
    6. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154, arXiv.org, revised Jun 2020.

Articles

  1. 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.
  2. Antonio F. Galvao & Alexandre Poirier, 2019. "Quantile Regression Random Effects," Annals of Economics and Statistics, GENES, issue 134, pages 109-148.

    Cited by:

    1. 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.
    2. 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.

  3. 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, 2016. "Long-run Consequences of Exposure to Natural Disasters," Discussion paper series HIAS-E-36, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    2. 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. 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.
  5. 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.
  6. 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:

    1. Martin Kniepert, 2014. "Die (Neue) Institutionenökonomik als Ansatz für einen erweiterten, offeneren Zugang zur Volkswirtschaftslehre," Working Papers 552014, Institute for Sustainable Economic Development, Department of Economics and Social Sciences, University of Natural Resources and Life Sciences, Vienna.

Software components

    Sorry, no citations of software components recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 8 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 (7) 2015-03-27 2016-07-16 2017-05-14 2017-11-05 2018-05-07 2019-01-14 2021-02-01. Author is listed
  2. NEP-DCM: Discrete Choice Models (4) 2016-07-16 2017-11-05 2019-08-26 2021-02-01
  3. NEP-GER: German Papers (1) 2016-07-16
  4. NEP-RMG: Risk Management (1) 2018-05-07

Corrections

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