Christian Hansen
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Christian |
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Hansen |
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Contact
Affiliations
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University of Chicago
/ Booth School of Business
Research profile
author of:
- Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments
American Economic Review, American Economic Association (2015)
by Victor Chernozhukov & Christian Hansen & Martin Spindler
(ReDIF-article, aea:aecrev:v:105:y:2015:i:5:p:486-90) - Double/Debiased/Neyman Machine Learning of Treatment Effects
American Economic Review, American Economic Association (2017)
by Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey
(ReDIF-article, aea:aecrev:v:107:y:2017:i:5:p:261-65) - Pre-event Trends in the Panel Event-Study Design
American Economic Review, American Economic Association (2019)
by Simon Freyaldenhoven & Christian Hansen & Jesse M. Shapiro
(ReDIF-article, aea:aecrev:v:109:y:2019:i:9:p:3307-38) - High-Dimensional Methods and Inference on Structural and Treatment Effects
Journal of Economic Perspectives, American Economic Association (2014)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-article, aea:jecper:v:28:y:2014:i:2:p:29-50) - Quantile Models with Endogeneity
Annual Review of Economics, Annual Reviews (2013)
by V. Chernozhukov & C. Hansen
(ReDIF-article, anr:reveco:v:5:y:2013:p:57-81) - Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach
Annual Review of Economics, Annual Reviews (2015)
by Victor Chernozhukov & Christian Hansen & Martin Spindler
(ReDIF-article, anr:reveco:v:7:y:2015:p:649-688) - Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain
Papers, arXiv.org (2010)
by Alexandre Belloni & Daniel Chen & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, arx:papers:1010.4345) - LASSO Methods for Gaussian Instrumental Variables Models
Papers, arXiv.org (2010)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, arx:papers:1012.1297) - Inference for High-Dimensional Sparse Econometric Models
Papers, arXiv.org (2011)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, arx:papers:1201.0220) - Inference on Treatment Effects After Selection Amongst High-Dimensional Controls
Papers, arXiv.org (2011)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, arx:papers:1201.0224) - Quantile Models with Endogeneity
Papers, arXiv.org (2013)
by Victor Chernozhukov & Christian Hansen
(ReDIF-paper, arx:papers:1303.7050) - Supplementary Appendix for "Inference on Treatment Effects After Selection Amongst High-Dimensional Controls"
Papers, arXiv.org (2013)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, arx:papers:1305.6099) - Program Evaluation and Causal Inference with High-Dimensional Data
Papers, arXiv.org (2013)
by Alexandre Belloni & Victor Chernozhukov & Ivan Fern'andez-Val & Christian Hansen
(ReDIF-paper, arx:papers:1311.2645) - Inference in High Dimensional Panel Models with an Application to Gun Control
Papers, arXiv.org (2014)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur
(ReDIF-paper, arx:papers:1411.6507) - Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments
Papers, arXiv.org (2015)
by Victor Chernozhukov & Christian Hansen & Martin Spindler
(ReDIF-paper, arx:papers:1501.03185) - Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach
Papers, arXiv.org (2015)
by Victor Chernozhukov & Christian Hansen & Martin Spindler
(ReDIF-paper, arx:papers:1501.03430) - A lava attack on the recovery of sums of dense and sparse signals
Papers, arXiv.org (2015)
by Victor Chernozhukov & Christian Hansen & Yuan Liao
(ReDIF-paper, arx:papers:1502.03155) - Double/Debiased Machine Learning for Treatment and Causal Parameters
Papers, arXiv.org (2016)
by Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins
(ReDIF-paper, arx:papers:1608.00060) - The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications
Papers, arXiv.org (2016)
by Christian Hansen & Yuan Liao
(ReDIF-paper, arx:papers:1611.09420) - Simultaneous Confidence Intervals for High-dimensional Linear Models with Many Endogenous Variables
Papers, arXiv.org (2017)
by Alexandre Belloni & Christian Hansen & Whitney Newey
(ReDIF-paper, arx:papers:1712.08102) - High-Dimensional Econometrics and Regularized GMM
Papers, arXiv.org (2018)
by Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato
(ReDIF-paper, arx:papers:1806.01888) - lassopack: Model selection and prediction with regularized regression in Stata
Papers, arXiv.org (2019)
by Achim Ahrens & Christian B. Hansen & Mark E. Schaffer
(ReDIF-paper, arx:papers:1901.05397) - Instrumental Variable Quantile Regression
Papers, arXiv.org (2020)
by Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich
(ReDIF-paper, arx:papers:2009.00436) - Inference for Low-Rank Models
Papers, arXiv.org (2021)
by Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu
(ReDIF-paper, arx:papers:2107.02602) - pystacked: Stacking generalization and machine learning in Stata
Papers, arXiv.org (2022)
by Achim Ahrens & Christian B. Hansen & Mark E. Schaffer
(ReDIF-paper, arx:papers:2208.10896) - ddml: Double/debiased machine learning in Stata
Papers, arXiv.org (2023)
by Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann
(ReDIF-paper, arx:papers:2301.09397) - Post-selection and post-regularization inference in linear models with many controls and instruments
CeMMAP working papers, Institute for Fiscal Studies (2015)
by Victor Chernozhukov & Christian Hansen & Martin Spindler
(ReDIF-paper, azt:cemmap:02/15) - A lava attack on the recovery of sums of dense and sparse signals
CeMMAP working papers, Institute for Fiscal Studies (2015)
by Victor Chernozhukov & Christian Hansen & Yuan Liao
(ReDIF-paper, azt:cemmap:05/15) - Inference on treatment effects after selection amongst high-dimensional controls
CeMMAP working papers, Institute for Fiscal Studies (2012)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, azt:cemmap:10/12) - Program evaluation and causal inference with high-dimensional data
CeMMAP working papers, Institute for Fiscal Studies (2016)
by Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen
(ReDIF-paper, azt:cemmap:13/16) - Quantile models with endogeneity
CeMMAP working papers, Institute for Fiscal Studies (2013)
by Victor Chernozhukov & Christian Hansen
(ReDIF-paper, azt:cemmap:25/13) - Inference on treatment effects after selection amongst high-dimensional controls
CeMMAP working papers, Institute for Fiscal Studies (2013)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, azt:cemmap:26/13) - Double/debiased machine learning for treatment and structural parameters
CeMMAP working papers, Institute for Fiscal Studies (2017)
by Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins
(ReDIF-paper, azt:cemmap:28/17) - Program evaluation with high-dimensional data
CeMMAP working papers, Institute for Fiscal Studies (2014)
by Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen
(ReDIF-paper, azt:cemmap:33/14) - Valid post-selection and post-regularization inference: An elementary, general approach
CeMMAP working papers, Institute for Fiscal Studies (2016)
by Victor Chernozhukov & Christian Hansen & Martin Spindler
(ReDIF-paper, azt:cemmap:36/16) - hdm: High-Dimensional Metrics
CeMMAP working papers, Institute for Fiscal Studies (2016)
by Victor Chernozhukov & Christian Hansen & Martin Spindler
(ReDIF-paper, azt:cemmap:37/16) - Estimation of treatment effects with high-dimensional controls
CeMMAP working papers, Institute for Fiscal Studies (2011)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, azt:cemmap:42/11) - Double machine learning for treatment and causal parameters
CeMMAP working papers, Institute for Fiscal Studies (2016)
by Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey
(ReDIF-paper, azt:cemmap:49/16) - Inference in high dimensional panel models with an application to gun control
CeMMAP working papers, Institute for Fiscal Studies (2014)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur
(ReDIF-paper, azt:cemmap:50/14) - Program evaluation with high-dimensional data
CeMMAP working papers, Institute for Fiscal Studies (2015)
by Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen
(ReDIF-paper, azt:cemmap:55/15) - A lava attack on the recovery of sums of dense and sparse signals
CeMMAP working papers, Institute for Fiscal Studies (2015)
by Victor Chernozhukov & Christian Hansen & Yuan Liao
(ReDIF-paper, azt:cemmap:56/15) - Program evaluation with high-dimensional data
CeMMAP working papers, Institute for Fiscal Studies (2013)
by Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen
(ReDIF-paper, azt:cemmap:57/13) - High dimensional methods and inference on structural and treatment effects
CeMMAP working papers, Institute for Fiscal Studies (2013)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, azt:cemmap:59/13) - Simultaneous confidence intervals for high-dimensional linear models with many endogenous variables
CeMMAP working papers, Institute for Fiscal Studies (2017)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Whitney K. Newey
(ReDIF-paper, azt:cemmap:63/17) - Program evaluation with high-dimensional data
CeMMAP working papers, Institute for Fiscal Studies (2013)
by Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen
(ReDIF-paper, azt:cemmap:77/13) - Visualization, Identification, and Estimation in the Linear Panel Event Study Design
Working Papers, Banco de México (2022)
by Freyaldenhoven Simon & Hansen Christian & Pérez Pérez Jorge & Shapiro Jesse M.
(ReDIF-paper, bdm:wpaper:2022-07) - Estimation With Many Instrumental Variables
Journal of Business & Economic Statistics, American Statistical Association (2008)
by Hansen, Christian & Hausman, Jerry & Newey, Whitney
(ReDIF-article, bes:jnlbes:v:26:y:2008:p:398-422) - A Penalty Function Approach to Bias Reduction in Nonlinear Panel Models with Fixed Effects
Journal of Business & Economic Statistics, American Statistical Association (2009)
by Bester, C. Alan & Hansen, Christian
(ReDIF-article, bes:jnlbes:v:27:i:2:y:2009:p:131-148) - Identification of Marginal Effects in a Nonparametric Correlated Random Effects Model
Journal of Business & Economic Statistics, American Statistical Association (2009)
by Bester, C. Alan & Hansen, Christian
(ReDIF-article, bes:jnlbes:v:27:i:2:y:2009:p:235-250) - Instrumental Variables Estimation With Flexible Distributions
Journal of Business & Economic Statistics, American Statistical Association (2010)
by Hansen, Christian & McDonald, James B. & Newey, Whitney K.
(ReDIF-article, bes:jnlbes:v:28:i:1:y:2010:p:13-25) - Inference with Dependent Data in Accounting and Finance Applications
Journal of Accounting Research, Wiley Blackwell (2018)
by Timothy Conley & Silvia Gonçalves & Christian Hansen
(ReDIF-article, bla:joares:v:56:y:2018:i:4:p:1139-1203) - LASSOPACK: Stata module for lasso, square-root lasso, elastic net, ridge, adaptive lasso estimation and cross-validation
Statistical Software Components, Boston College Department of Economics (2018)
by Achim Ahrens & Christian B. Hansen & Mark E Schaffer
(ReDIF-software, boc:bocode:s458458) - PDSLASSO: Stata module for post-selection and post-regularization OLS or IV estimation and inference
Statistical Software Components, Boston College Department of Economics (2018)
by Achim Ahrens & Christian B. Hansen & Mark E Schaffer
(ReDIF-software, boc:bocode:s458459) - XTEVENT: Stata module to estimate and visualize linear panel event-study models
Statistical Software Components, Boston College Department of Economics (2021)
by Simon Freyaldenhoven & Christian Hansen & Jorge Eduardo Perez Perez & Jesse Shapiro
(ReDIF-software, boc:bocode:s458987) - PYSTACKED: Stata module for stacking generalization and machine learning in Stata
Statistical Software Components, Boston College Department of Economics (2022)
by Achim Ahrens & Christian B. Hansen & Mark E Schaffer
(ReDIF-software, boc:bocode:s459115) - DDML: Stata module for Double/Debiased Machine Learning
Statistical Software Components, Boston College Department of Economics (2023)
by Achim Ahrens & Christian B. Hansen & Mark E Schaffer & Thomas Wiemann
(ReDIF-software, boc:bocode:s459175) - pystacked: Stacking generalization and machine learning in Stata
Swiss Stata Conference 2022, Stata Users Group (2022)
by Christian B. Hansen & Mark E. Schaffer & Achim Ahrens
(ReDIF-paper, boc:csug22:01) - ddml: Double/debiased machine learning in Stata
Swiss Stata Conference 2022, Stata Users Group (2022)
by Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann & Achim Ahrens
(ReDIF-paper, boc:csug22:02) - pystacked and ddml: machine learning for prediction and causal inference in Stata
UK Stata Conference 2023, Stata Users Group (2023)
by Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann
(ReDIF-paper, boc:lsug23:12) - LASSOPACK and PDSLASSO: Prediction, model selection and causal inference with regularized regression
London Stata Conference 2018, Stata Users Group (2018)
by Achim Ahrens & Christian B Hansen & Mark E Schaffer
(ReDIF-paper, boc:usug18:12) - Admissible Invariant Similar Tests For Instrumental Variables Regression
Econometric Theory, Cambridge University Press (2009)
by Chernozhukov, Victor & Hansen, Christian & Jansson, Michael
(ReDIF-article, cup:etheor:v:25:y:2009:i:03:p:806-818_09) - FIXED-b ASYMPTOTICS FOR SPATIALLY DEPENDENT ROBUST NONPARAMETRIC COVARIANCE MATRIX ESTIMATORS
Econometric Theory, Cambridge University Press (2016)
by Bester, C. Alan & Conley, Timothy G. & Hansen, Christian B. & Vogelsang, Timothy J.
(ReDIF-article, cup:etheor:v:32:y:2016:i:01:p:154-186_00) - The Factor-Lasso And K-Step Bootstrap Approach For Inference In High-Dimensional Economic Applications
Econometric Theory, Cambridge University Press (2019)
by Hansen, Christian & Liao, Yuan
(ReDIF-article, cup:etheor:v:35:y:2019:i:03:p:465-509_00) - An IV Model of Quantile Treatment Effects
Econometrica, Econometric Society (2005)
by Victor Chernozhukov & Christian Hansen
(ReDIF-article, ecm:emetrp:v:73:y:2005:i:1:p:245-261) - Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain
Econometrica, Econometric Society (2012)
by A. Belloni & D. Chen & V. Chernozhukov & C. Hansen
(ReDIF-article, ecm:emetrp:v:80:y:2012:i:6:p:2369-2429) - Finite-Sample Inference Methods for Quantile Regression Models
Econometric Society 2004 North American Winter Meetings, Econometric Society (2004)
by Christian Hansen & Victor Chernozhukov
(ReDIF-paper, ecm:nawm04:393) - The reduced form: A simple approach to inference with weak instruments
Economics Letters, Elsevier (2008)
by Chernozhukov, Victor & Hansen, Christian
(ReDIF-article, eee:ecolet:v:100:y:2008:i:1:p:68-71) - Inference approaches for instrumental variable quantile regression
Economics Letters, Elsevier (2007)
by Chernozhukov, Victor & Hansen, Christian & Jansson, Michael
(ReDIF-article, eee:ecolet:v:95:y:2007:i:2:p:272-277) - Instrumental quantile regression inference for structural and treatment effect models
Journal of Econometrics, Elsevier (2006)
by Chernozhukov, Victor & Hansen, Christian
(ReDIF-article, eee:econom:v:132:y:2006:i:2:p:491-525) - Generalized least squares inference in panel and multilevel models with serial correlation and fixed effects
Journal of Econometrics, Elsevier (2007)
by Hansen, Christian B.
(ReDIF-article, eee:econom:v:140:y:2007:i:2:p:670-694) - Asymptotic properties of a robust variance matrix estimator for panel data when T is large
Journal of Econometrics, Elsevier (2007)
by Hansen, Christian B.
(ReDIF-article, eee:econom:v:141:y:2007:i:2:p:597-620) - Instrumental variable quantile regression: A robust inference approach
Journal of Econometrics, Elsevier (2008)
by Chernozhukov, Victor & Hansen, Christian
(ReDIF-article, eee:econom:v:142:y:2008:i:1:p:379-398) - A semi-parametric Bayesian approach to the instrumental variable problem
Journal of Econometrics, Elsevier (2008)
by Conley, Timothy G. & Hansen, Christian B. & McCulloch, Robert E. & Rossi, Peter E.
(ReDIF-article, eee:econom:v:144:y:2008:i:1:p:276-305) - Finite sample inference for quantile regression models
Journal of Econometrics, Elsevier (2009)
by Chernozhukov, Victor & Hansen, Christian & Jansson, Michael
(ReDIF-article, eee:econom:v:152:y:2009:i:2:p:93-103) - Inference with dependent data using cluster covariance estimators
Journal of Econometrics, Elsevier (2011)
by Bester, C. Alan & Conley, Timothy G. & Hansen, Christian B.
(ReDIF-article, eee:econom:v:165:y:2011:i:2:p:137-151) - Instrumental variables estimation with many weak instruments using regularized JIVE
Journal of Econometrics, Elsevier (2014)
by Hansen, Christian & Kozbur, Damian
(ReDIF-article, eee:econom:v:182:y:2014:i:2:p:290-308) - Grouped effects estimators in fixed effects models
Journal of Econometrics, Elsevier (2016)
by Bester, C. Alan & Hansen, Christian B.
(ReDIF-article, eee:econom:v:190:y:2016:i:1:p:197-208) - High-dimensional linear models with many endogenous variables
Journal of Econometrics, Elsevier (2022)
by Belloni, Alexandre & Hansen, Christian & Newey, Whitney
(ReDIF-article, eee:econom:v:228:y:2022:i:1:p:4-26) - Pre-event Trends in the Panel Event-study Design
Working Papers, Federal Reserve Bank of Philadelphia (2019)
by Simon Freyaldenhoven & Christian Hansen & Jesse Shapiro
(ReDIF-paper, fip:fedpwp:19-27) - Visualization, Identification, and stimation in the Linear Panel Event-Study Design
Working Papers, Federal Reserve Bank of Philadelphia (2021)
by Simon Freyaldenhoven & Christian Hansen & Jorge Perez Perez & Jesse Shapiro
(ReDIF-paper, fip:fedpwp:93518) - Post-selection and post-regularization inference in linear models with many controls and instruments
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2015)
by Victor Chernozhukov & Christian Hansen & Martin Spindler
(ReDIF-paper, ifs:cemmap:02/15) - A lava attack on the recovery of sums of dense and sparse signals
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2015)
by Victor Chernozhukov & Christian Hansen & Yuan Liao
(ReDIF-paper, ifs:cemmap:05/15) - Inference on treatment effects after selection amongst high-dimensional controls
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2012)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, ifs:cemmap:10/12) - Program evaluation and causal inference with high-dimensional data
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2016)
by Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen
(ReDIF-paper, ifs:cemmap:13/16) - Estimation with many instrumental variables
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2006)
by Christian Hansen & Jerry Hausman & Whitney K. Newey
(ReDIF-paper, ifs:cemmap:19/06) - Instrumental variables estimation with flexible distribution
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2007)
by Christian Hansen & James B. McDonald & Whitney K. Newey
(ReDIF-paper, ifs:cemmap:21/07) - Quantile models with endogeneity
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2013)
by Victor Chernozhukov & Christian Hansen
(ReDIF-paper, ifs:cemmap:25/13) - Inference on treatment effects after selection amongst high-dimensional controls
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2013)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, ifs:cemmap:26/13) - Double/debiased machine learning for treatment and structural parameters
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2017)
by Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins
(ReDIF-paper, ifs:cemmap:28/17) - Sparse models and methods for optimal instruments with an application to eminent domain
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2010)
by Alexandre Belloni & D. Chen & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, ifs:cemmap:31/10) - Inference for heterogeneous effects using low-rank estimations
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2019)
by Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu
(ReDIF-paper, ifs:cemmap:31/19) - Program evaluation with high-dimensional data
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2014)
by Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen
(ReDIF-paper, ifs:cemmap:33/14) - High-dimensional econometrics and regularized GMM
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2018)
by Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato
(ReDIF-paper, ifs:cemmap:35/18) - Valid post-selection and post-regularization inference: An elementary, general approach
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2016)
by Victor Chernozhukov & Christian Hansen & Martin Spindler
(ReDIF-paper, ifs:cemmap:36/16) - hdm: High-Dimensional Metrics
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2016)
by Victor Chernozhukov & Christian Hansen & Martin Spindler
(ReDIF-paper, ifs:cemmap:37/16) - Inference for high-dimensional sparse econometric models
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2011)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, ifs:cemmap:41/11) - Estimation of treatment effects with high-dimensional controls
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2011)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, ifs:cemmap:42/11) - Double machine learning for treatment and causal parameters
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2016)
by Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey
(ReDIF-paper, ifs:cemmap:49/16) - Inference in high dimensional panel models with an application to gun control
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2014)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur
(ReDIF-paper, ifs:cemmap:50/14) - Program evaluation with high-dimensional data
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2015)
by Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen
(ReDIF-paper, ifs:cemmap:55/15) - A lava attack on the recovery of sums of dense and sparse signals
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2015)
by Victor Chernozhukov & Christian Hansen & Yuan Liao
(ReDIF-paper, ifs:cemmap:56/15) - Program evaluation with high-dimensional data
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2013)
by Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen
(ReDIF-paper, ifs:cemmap:57/13) - High dimensional methods and inference on structural and treatment effects
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2013)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-paper, ifs:cemmap:59/13) - Simultaneous confidence intervals for high-dimensional linear models with many endogenous variables
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2017)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Whitney K. Newey
(ReDIF-paper, ifs:cemmap:63/17) - Program evaluation with high-dimensional data
CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (2013)
by Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen
(ReDIF-paper, ifs:cemmap:77/13) - lassopack: Model Selection and Prediction with Regularized Regression in Stata
IZA Discussion Papers, Institute of Labor Economics (IZA) (2019)
by Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E
(ReDIF-paper, iza:izadps:dp12081) - ddml: Double/Debiased Machine Learning in Stata
IZA Discussion Papers, Institute of Labor Economics (IZA) (2023)
by Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E & Wiemann, Thomas
(ReDIF-paper, iza:izadps:dp15963) - Double/Debiased Machine Learning for Treatment and Structural Parameters
NBER Working Papers, National Bureau of Economic Research, Inc (2017)
by Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins
(ReDIF-paper, nbr:nberwo:23564) - Pre-event Trends in the Panel Event-study Design
NBER Working Papers, National Bureau of Economic Research, Inc (2018)
by Simon Freyaldenhoven & Christian Hansen & Jesse M. Shapiro
(ReDIF-paper, nbr:nberwo:24565) - Visualization, Identification, and Estimation in the Linear Panel Event-Study Design
NBER Working Papers, National Bureau of Economic Research, Inc (2021)
by Simon Freyaldenhoven & Christian Hansen & Jorge Pérez Pérez & Jesse M. Shapiro
(ReDIF-paper, nbr:nberwo:29170) - Inference on Treatment Effects after Selection among High-Dimensional Controlsâ€
The Review of Economic Studies, Review of Economic Studies Ltd (2014)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen
(ReDIF-article, oup:restud:v:81:y:2014:i:2:p:608-650) - The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications
MPRA Paper, University Library of Munich, Germany (2016)
by Hansen, Christian & Liao, Yuan
(ReDIF-paper, pra:mprapa:75313) - The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications
Departmental Working Papers, Rutgers University, Department of Economics (2016)
by Christian Hansen & Yuan Liao
(ReDIF-paper, rut:rutres:201610) - Inference in High-Dimensional Panel Models With an Application to Gun Control
Journal of Business & Economic Statistics, Taylor & Francis Journals (2016)
by Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur
(ReDIF-article, taf:jnlbes:v:34:y:2016:i:4:p:590-605) - Targeted Undersmoothing: Sensitivity Analysis for Sparse Estimators
The Review of Economics and Statistics, MIT Press (2023)
by Christian Hansen & Damian Kozbur & Sanjog Misra
(ReDIF-article, tpr:restat:v:105:y:2023:i:1:p:101-112) - The Effects of 401(K) Participation on the Wealth Distribution: An Instrumental Quantile Regression Analysis
The Review of Economics and Statistics, MIT Press (2004)
by Victor Chernozhukov & Christian Hansen
(ReDIF-article, tpr:restat:v:86:y:2004:i:3:p:735-751) - Plausibly Exogenous
The Review of Economics and Statistics, MIT Press (2012)
by Timothy G. Conley & Christian B. Hansen & Peter E. Rossi
(ReDIF-article, tpr:restat:v:94:y:2012:i:1:p:260-272) - lassopack: Model selection and prediction with regularized regression in Stata
Stata Journal, StataCorp LP (2020)
by Achim Ahrens & Christian B. Hansen & Mark E. Schaffer
(ReDIF-article, tsj:stataj:v:20:y:2020:i:1:p:176-235) - pystacked: Stacking generalization and machine learning in Stata
Stata Journal, StataCorp LP (2023)
by Achim Ahrens & Christian B. Hansen & Mark E. Schaffer
(ReDIF-article, tsj:stataj:v:23:y:2023:i:4:p:909-931) - ddml: Double/debiased machine learning in Stata
Stata Journal, StataCorp LP (2024)
by Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann
(ReDIF-article, tsj:stataj:v:24:y:2024:i:1:p:3-45) - Program Evaluation and Causal Inference With High‐Dimensional Data
Econometrica, Econometric Society (2017)
by A. Belloni & V. Chernozhukov & I. Fernández‐Val & C. Hansen
(ReDIF-article, wly:emetrp:v:85:y:2017:i::p:233-298) - Double/debiased machine learning for treatment and structural parameters
Econometrics Journal, Royal Economic Society (2018)
by Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins
(ReDIF-article, wly:emjrnl:v:21:y:2018:i:1:p:c1-c68) - Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models
Economics Discussion Papers, Kiel Institute for the World Economy (IfW Kiel) (2007)
by Theodossiou, Panayiotis & McDonald, James B. & Hansen, Christian B.
(ReDIF-paper, zbw:ifwedp:5527) - Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models
Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel) (2007)
by Theodossiou, Panayiotis & McDonald, James B. & Hansen, Christian B.
(ReDIF-article, zbw:ifweej:5742) - Targeted undersmoothing
ECON - Working Papers, Department of Economics - University of Zurich (2016)
by Christian Hansen & Damian Kozbur & Sanjog Misra
(ReDIF-paper, zur:econwp:282)