IDEAS home Printed from https://ideas.repec.org/e/pbu197.html
   My authors  Follow this author

Federico Andres Bugni

Personal Details

First Name:Federico
Middle Name:Andres
Last Name:Bugni
Suffix:
RePEc Short-ID:pbu197
[This author has chosen not to make the email address public]
http://fds.duke.edu/db/aas/Economics/faculty/fb32

Affiliation

Department of Economics
Duke University

Durham, North Carolina (United States)
http://www.econ.duke.edu/

: (919) 660-1800
(919) 684-8974
305 Social Sciences Building, Box 90097, Durham, NC 27708-0097
RePEc:edi:dedukus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Federico A. Bugni & Joel L. Horowitz, 2017. "Permutation tests for equality of distributions of functional data," CeMMAP working papers CWP17/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  2. Aucejo, Esteban M. & Bugni, Federico A. & Hotz, V. Joseph, 2017. "Identification and inference on regressions with missing covariate data," LSE Research Online Documents on Economics 62524, London School of Economics and Political Science, LSE Library.
  3. Federico A. Bugni & Mehmet Caner & Anders Bredahl Kock & Soumendra Lahiri, 2016. "Inference in partially identified models with many moment inequalities using Lasso," CREATES Research Papers 2016-12, Department of Economics and Business Economics, Aarhus University.
  4. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2015. "Inference under covariate-adaptive randomization," CeMMAP working papers CWP45/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  5. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Inference for functions of partially identified parameters in moment inequality models," CeMMAP working papers CWP22/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  6. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Specification tests for partially identified models defined by moment inequalities," CeMMAP working papers CWP19/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  7. Peter Arcidiacono & Patrick Bayer & Federico Bugni & Jon James, 2012. "Approximating High-Dimensional Dynamic Models: Sieve Value Function Iteration," Working Papers 12-07, Duke University, Department of Economics.
  8. Federico A Bugni, 2010. "Specification Test for Missing Functional Data," Working Papers 10-41, Duke University, Department of Economics.

Articles

  1. Aucejo, Esteban M. & Bugni, Federico A. & Hotz, V. Joseph, 2017. "Identification And Inference On Regressions With Missing Covariate Data," Econometric Theory, Cambridge University Press, vol. 33(1), pages 196-241, February.
  2. Bugni, Federico A., 2016. "Comparison Of Inferential Methods In Partially Identified Models In Terms Of Error In Coverage Probability," Econometric Theory, Cambridge University Press, vol. 32(1), pages 187-242, February.
  3. Bugni, Federico A. & Canay, Ivan A. & Shi, Xiaoxia, 2015. "Specification tests for partially identified models defined by moment inequalities," Journal of Econometrics, Elsevier, vol. 185(1), pages 259-282.
  4. Bugni, Federico A., 2012. "Specification Test For Missing Functional Data," Econometric Theory, Cambridge University Press, vol. 28(5), pages 959-1002, October.
  5. Federico A. Bugni & Ivan A. Canay & Patrik Guggenberger, 2012. "Distortions of Asymptotic Confidence Size in Locally Misspecified Moment Inequality Models," Econometrica, Econometric Society, vol. 80(4), pages 1741-1768, July.
  6. Federico A. Bugni, 2010. "Bootstrap Inference in Partially Identified Models Defined by Moment Inequalities: Coverage of the Identified Set," Econometrica, Econometric Society, vol. 78(2), pages 735-753, March.
  7. Federico A. Bugni & Peter Hall & Joel L. Horowitz & George R. Neumann, 2009. "Goodness-of-fit tests for functional data," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 1-18, January.

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. Federico A. Bugni & Mehmet Caner & Anders Bredahl Kock & Soumendra Lahiri, 2016. "Inference in partially identified models with many moment inequalities using Lasso," CREATES Research Papers 2016-12, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Nick Koning & Paul Bekker, 2019. "Exact Testing of Many Moment Inequalities Against Multiple Violations," Papers 1904.12775, arXiv.org, revised Jun 2020.
    2. Andrew Chesher & Adam Rosen, 2019. "Generalized Instrumental Variable Models, Methods, and Applications," CeMMAP working papers CWP41/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Allen, Roy, 2018. "Testing moment inequalities: Selection versus recentering," Economics Letters, Elsevier, vol. 162(C), pages 124-126.

  2. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2015. "Inference under covariate-adaptive randomization," CeMMAP working papers CWP45/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2017. "Inference under covariate-adaptive randomization," CeMMAP working papers CWP25/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Simon Heß, 2017. "Randomization inference with Stata: A guide and software," Stata Journal, StataCorp LP, vol. 17(3), pages 630-651, September.
    3. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jun 2019.
    4. Isaiah Andrews & Emily Oster, 2017. "Weighting for External Validity," NBER Working Papers 23826, National Bureau of Economic Research, Inc.
    5. John A. List & Azeem M. Shaikh & Yang Xu, 2016. "Multiple Hypothesis Testing in Experimental Economics," NBER Working Papers 21875, National Bureau of Economic Research, Inc.
    6. Ivan A. Canay & Vishal Kamat, 2017. "Approximate permutation tests and induced order statistics in the regression discontinuity design," CeMMAP working papers CWP21/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Abhijit Banerjee & Sylvain Chassang & Sergio Montero & Erik Snowberg, 2017. "A Theory of Experimenters," NBER Working Papers 23867, National Bureau of Economic Research, Inc.
    8. Tymon S{l}oczy'nski, 2018. "Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights," Papers 1810.01576, arXiv.org, revised May 2020.
    9. Tymon Sloczynski, 2018. "A General Weighted Average Representation of the Ordinary and Two-Stage Least Squares Estimands," Working Papers 125, Brandeis University, Department of Economics and International Businesss School.
    10. Guiteras, Raymond P. & Levine, David I. & Polley, Thomas H., 2016. "The pursuit of balance in sequential randomized trials," Development Engineering, Elsevier, vol. 1(C), pages 12-25.
    11. Vishal Kamat, 2017. "Identification with Latent Choice Sets," Papers 1711.02048, arXiv.org, revised Aug 2019.

  3. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Inference for functions of partially identified parameters in moment inequality models," CeMMAP working papers CWP22/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Gabrielle Fack & Julien Grenet & Yinghua He, 2019. "Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions," Post-Print halshs-01884369, HAL.
    2. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    3. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2013. "Specification tests for partially identified models defined by moment inequalities," CeMMAP working papers CWP01/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confi dence Intervals for Projections of Partially Identi fied Parameters," Boston University - Department of Economics - Working Papers Series wp2016-001, Boston University - Department of Economics.
    5. Battey, Heather & Feng, Qiang & Smith, Richard J., 2016. "Improving confidence set estimation when parameters are weakly identified," Statistics & Probability Letters, Elsevier, vol. 118(C), pages 117-123.
    6. Arkadiusz Szydlowski, 2015. "Endogenous Censoring in the Mixed Proportional Hazard Model with an Application to Optimal Unemployment Insurance," Discussion Papers in Economics 15/06, Division of Economics, School of Business, University of Leicester.
    7. Lee, Y-Y. & Bhattacharya, D., 2018. "Applied Welfare Analysis for Discrete Choice with Interval-data on Income," Cambridge Working Papers in Economics 1882, Faculty of Economics, University of Cambridge.
    8. Ivan A. Canay & Azeem M. Shaikh, 2016. "Practical and theoretical advances in inference for partially identified models," CeMMAP working papers CWP05/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Fack, Gabrielle & Grenet, Julien & He, Yinghua, 2015. "Beyond Truth-Telling: Preference Estimation with Centralized School Choice," CEPR Discussion Papers 10907, C.E.P.R. Discussion Papers.
    10. Victor Chernozhukov & Whitney K. Newey & Andres Santos, 2015. "Constrained conditional moment restriction models," CeMMAP working papers CWP59/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  4. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Specification tests for partially identified models defined by moment inequalities," CeMMAP working papers CWP19/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Gabrielle Fack & Julien Grenet & Yinghua He, 2019. "Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions," Post-Print halshs-01884369, HAL.
    2. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Inference for functions of partially identified parameters in moment inequality models," CeMMAP working papers CWP05/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Arkadiusz Szydlowski, 2015. "Endogenous Censoring in the Mixed Proportional Hazard Model with an Application to Optimal Unemployment Insurance," Discussion Papers in Economics 15/06, Division of Economics, School of Business, University of Leicester.
    4. Kristin F. Butcher & Kyung H. Park & Anne Morrison Piehl, 2017. "Comparing Apples to Oranges: Differences in Women’s and Men’s Incarceration and Sentencing Outcomes," Journal of Labor Economics, University of Chicago Press, vol. 35(S1), pages 201-234.
    5. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers CWP56/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Ivan A. Canay & Azeem M. Shaikh, 2016. "Practical and theoretical advances in inference for partially identified models," CeMMAP working papers CWP05/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Hong, Han & Li, Jessie, 2018. "The numerical delta method," Journal of Econometrics, Elsevier, vol. 206(2), pages 379-394.
    8. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    9. Fan, Yanqin & Liu, Ruixuan, 2018. "Partial identification and inference in censored quantile regression," Journal of Econometrics, Elsevier, vol. 206(1), pages 1-38.
    10. Dovonon, Prosper & Gonçalves, Sílvia, 2017. "Bootstrapping the GMM overidentification test under first-order underidentification," Journal of Econometrics, Elsevier, vol. 201(1), pages 43-71.
    11. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. JoonHwan Cho & Thomas M. Russell, 2018. "Simple Inference on Functionals of Set-Identified Parameters Defined by Linear Moments," Papers 1810.03180, arXiv.org, revised Sep 2019.

  5. Peter Arcidiacono & Patrick Bayer & Federico Bugni & Jon James, 2012. "Approximating High-Dimensional Dynamic Models: Sieve Value Function Iteration," Working Papers 12-07, Duke University, Department of Economics.

    Cited by:

    1. Meredith Fowlie & Mar Reguant & Stephen P. Ryan, 2016. "Market-Based Emissions Regulation and Industry Dynamics," Journal of Political Economy, University of Chicago Press, vol. 124(1), pages 249-302.
    2. Panle Jia Barwick & Parag A. Pathak, 2015. "The costs of free entry: an empirical study of real estate agents in Greater Boston," RAND Journal of Economics, RAND Corporation, vol. 46(1), pages 103-145, March.
    3. Shintaro Yamaguchi, 2016. "Effects of Parental Leave Policies on Female Career and Fertility Choices," Department of Economics Working Papers 2016-10, McMaster University.

  6. Federico A Bugni, 2010. "Specification Test for Missing Functional Data," Working Papers 10-41, Duke University, Department of Economics.

    Cited by:

    1. Kraus, David, 2019. "Inferential procedures for partially observed functional data," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 583-603.
    2. Mojirsheibani, Majid & Shaw, Crystal, 2018. "Classification with incomplete functional covariates," Statistics & Probability Letters, Elsevier, vol. 139(C), pages 40-46.

Articles

  1. Bugni, Federico A., 2016. "Comparison Of Inferential Methods In Partially Identified Models In Terms Of Error In Coverage Probability," Econometric Theory, Cambridge University Press, vol. 32(1), pages 187-242, February.

    Cited by:

    1. Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2016. "Testing many moment inequalities," CeMMAP working papers CWP42/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Joseph P. Romano & Azeem M. Shaikh & Michael Wolf, 2014. "A Practical Two‐Step Method for Testing Moment Inequalities," Econometrica, Econometric Society, vol. 82, pages 1979-2002, September.
    3. Vishal Kamat, 2017. "Identification with Latent Choice Sets," Papers 1711.02048, arXiv.org, revised Aug 2019.
    4. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    5. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  2. Bugni, Federico A. & Canay, Ivan A. & Shi, Xiaoxia, 2015. "Specification tests for partially identified models defined by moment inequalities," Journal of Econometrics, Elsevier, vol. 185(1), pages 259-282.
    See citations under working paper version above.
  3. Bugni, Federico A., 2012. "Specification Test For Missing Functional Data," Econometric Theory, Cambridge University Press, vol. 28(5), pages 959-1002, October.
    See citations under working paper version above.
  4. Federico A. Bugni & Ivan A. Canay & Patrik Guggenberger, 2012. "Distortions of Asymptotic Confidence Size in Locally Misspecified Moment Inequality Models," Econometrica, Econometric Society, vol. 80(4), pages 1741-1768, July.

    Cited by:

    1. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Jul 2020.
    2. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2013. "Specification tests for partially identified models defined by moment inequalities," CeMMAP working papers CWP01/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    4. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Inference for functions of partially identified parameters in moment inequality models," CeMMAP working papers CWP05/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Lavergne, Pascal, 2015. "Assessing the Approximate Validity of Moment Restrictions," TSE Working Papers 15-562, Toulouse School of Economics (TSE), revised May 2020.
    6. Kaido, Hiroaki & White, Halbert, 2014. "A two-stage procedure for partially identified models," Journal of Econometrics, Elsevier, vol. 182(1), pages 5-13.
    7. Federico A. Bugni & Mehmet Caner & Anders Bredahl Kock & Soumendra Lahiri, 2016. "Inference in partially identified models with many moment inequalities using Lasso," CREATES Research Papers 2016-12, Department of Economics and Business Economics, Aarhus University.
    8. Guggenberger, Patrik, 2012. "A note on the relation between local power and robustness to misspecification," Economics Letters, Elsevier, vol. 116(2), pages 133-135.

  5. Federico A. Bugni, 2010. "Bootstrap Inference in Partially Identified Models Defined by Moment Inequalities: Coverage of the Identified Set," Econometrica, Econometric Society, vol. 78(2), pages 735-753, March.

    Cited by:

    1. Xiaohong Chen & Timothy Christensen & Keith O'Hara & Elie Tamer, 2016. "MCMC Confidence sets for Identified Sets," Cowles Foundation Discussion Papers 2037R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2016.
    2. Christian Bontemps & Thierry Magnac & Eric Maurin, 2012. "Set Identified Linear Models," Econometrica, Econometric Society, vol. 80(3), pages 1129-1155, May.
    3. Christian Bontemps & Rohit Kumar, 2020. "A Geometric Approach to Inference in Set-Identified Entry Games," Post-Print hal-02137356, HAL.
    4. Marc Henry & Romuald Méango & Maurice Queyranne, 2012. "Combinatorial Bootstrap Inference IN in Prtially Identified Incomplete Structural Models," CIRJE F-Series CIRJE-F-837, CIRJE, Faculty of Economics, University of Tokyo.
    5. Stoye, Jörg & Kitamura, Yuichi, 2013. "Nonparametric Analysis of Random Utility Models: Testing," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79753, Verein für Socialpolitik / German Economic Association.
    6. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    7. Okumura, Tsunao & Usui, Emiko, 2010. "Concave-Monotone Treatment Response and Monotone Treatment Selection: With an Application to the Returns to Schooling," PIE/CIS Discussion Paper 475, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
    8. Liao, Yuan & Simoni, Anna, 2019. "Bayesian inference for partially identified smooth convex models," Journal of Econometrics, Elsevier, vol. 211(2), pages 338-360.
    9. Andrew Chesher & Adam Rosen, 2019. "Generalized Instrumental Variable Models, Methods, and Applications," CeMMAP working papers CWP41/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2013. "Specification tests for partially identified models defined by moment inequalities," CeMMAP working papers CWP01/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    12. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2017. "Monte Carlo confidence sets for identified sets," CeMMAP working papers CWP43/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confi dence Intervals for Projections of Partially Identi fied Parameters," Boston University - Department of Economics - Working Papers Series wp2016-001, Boston University - Department of Economics.
    14. Wooyoung Kim & Koohyun Kwon & Soonwoo Kwon & Sokbae Lee, 2018. "The identification power of smoothness assumptions in models with counterfactual outcomes," Quantitative Economics, Econometric Society, vol. 9(2), pages 617-642, July.
    15. Laffers, Lukas, 2013. "Identification in Models with Discrete Variables," Discussion Paper Series in Economics 1/2013, Norwegian School of Economics, Department of Economics.
    16. Donald W.K. Andrews & Panle Jia, 2008. "Inference for Parameters Defined by Moment Inequalities: A Recommended Moment Selection Procedure," Cowles Foundation Discussion Papers 1676, Cowles Foundation for Research in Economics, Yale University.
    17. Christian Bontemps & Thierry Magnac, 2017. "Set identification, moment restrictions, and inference," Post-Print hal-01575813, HAL.
    18. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Inference for functions of partially identified parameters in moment inequality models," CeMMAP working papers CWP05/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Zeng-Hua Lu, 2020. "Bahadur intercept with applications to one-sided testing," Statistical Papers, Springer, vol. 61(2), pages 645-658, April.
    20. Larry G. Epstein & Hiroaki Kaido & Kyoungwon Seo, 2015. "Robust Confidence Regions for Incomplete Models," Boston University - Department of Economics - Working Papers Series wp2015-008, Boston University - Department of Economics.
    21. Charles Grant & Mario Padula, 2012. "Using Bounds to Investigate Household Debt Repayment Behaviour," CEDI Discussion Paper Series 12-06, Centre for Economic Development and Institutions(CEDI), Brunel University.
    22. Sokbae (Simon) Lee & Kyungchui (Kevin) Song & Yoon-Jae Whang, 2014. "Testing for a general class of functional inequalities," CeMMAP working papers CWP09/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. Yuan Liao & Anna Simoni, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," Papers 1212.3267, arXiv.org, revised Nov 2013.
    24. Donald W.K. Andrews & Xiaoxia Shi, 2010. "Inference Based on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1761R2, Cowles Foundation for Research in Economics, Yale University, revised May 2012.
    25. Rosen, Adam M., 2012. "Set identification via quantile restrictions in short panels," Journal of Econometrics, Elsevier, vol. 166(1), pages 127-137.
    26. Andrew Chesher & Adam M. Rosen & Konrad Smolinski, 2013. "An instrumental variable model of multiple discrete choice," Quantitative Economics, Econometric Society, vol. 4(2), pages 157-196, July.
    27. Fan, Yanqin & Park, Sang Soo, 2014. "Nonparametric inference for counterfactual means: Bias-correction, confidence sets, and weak IV," Journal of Econometrics, Elsevier, vol. 178(P1), pages 45-56.
    28. Armstrong, Timothy B., 2014. "Weighted KS statistics for inference on conditional moment inequalities," Journal of Econometrics, Elsevier, vol. 181(2), pages 92-116.
    29. Kristin F. Butcher & Kyung H. Park & Anne Morrison Piehl, 2017. "Comparing Apples to Oranges: Differences in Women’s and Men’s Incarceration and Sentencing Outcomes," Journal of Labor Economics, University of Chicago Press, vol. 35(S1), pages 201-234.
    30. Arie Beresteanu & Ilya Molchanov & Francesca Molinari, 2010. "Partial identification using random set theory," CeMMAP working papers CWP40/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    31. Isabel Mourifie & Marc Henry, 2011. "Set Inference in Latent Variables Models," CIRJE F-Series CIRJE-F-820, CIRJE, Faculty of Economics, University of Tokyo.
    32. Andrew Chesher & Adam Rosen, 2014. "Generalized instrumental variable models," CeMMAP working papers CWP04/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    33. Jason R. Blevins, 2013. "Non-Standard Rates of Convergence of Criterion-Function-Based Set Estimators," Working Papers 13-02, Ohio State University, Department of Economics.
    34. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2011. "Bounding quantile demand functions using revealed preference inequalities," CeMMAP working papers CWP21/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    35. Mammen, Enno & Polonik, Wolfgang, 2013. "Confidence regions for level sets," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 202-214.
    36. Andriy Norets & Xun Tang, 2013. "Semi-Parametric Inference in Dynamic Binary Choice Models," PIER Working Paper Archive 13-054, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    37. Ting Ye & Luke Keele & Raiden Hasegawa & Dylan S. Small, 2020. "A Negative Correlation Strategy for Bracketing in Difference-in-Differences with Application to the Effect of Voter Identification Laws on Voter Turnout," Papers 2006.02423, arXiv.org.
    38. Magnac, Thierry, 2014. "Identification partielle: méthodes et conséquences pour les applications empiriques," TSE Working Papers 14-458, Toulouse School of Economics (TSE).
    39. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers CWP56/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    40. Donald W.K. Andrews, 2011. "Similar-on-the-Boundary Tests for Moment Inequalities Exist, But Have Poor Power," Cowles Foundation Discussion Papers 1815, Cowles Foundation for Research in Economics, Yale University.
    41. Chen, Le-Yu & Szroeter, Jerzy, 2014. "Testing multiple inequality hypotheses: A smoothed indicator approach," Journal of Econometrics, Elsevier, vol. 178(P3), pages 678-693.
    42. Fan, Yanqin & Park, Sang Soo, 2012. "Confidence intervals for the quantile of treatment effects in randomized experiments," Journal of Econometrics, Elsevier, vol. 167(2), pages 330-344.
    43. Andrew Chesher & Adam Rosen, 2016. "Characterizations of identified sets delivered by structural econometric models," CeMMAP working papers CWP44/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    44. Kaido, Hiroaki & White, Halbert, 2014. "A two-stage procedure for partially identified models," Journal of Econometrics, Elsevier, vol. 182(1), pages 5-13.
    45. Ivan A. Canay & Azeem M. Shaikh, 2016. "Practical and theoretical advances in inference for partially identified models," CeMMAP working papers CWP05/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    46. Bontemps, Christian & Kumar, Rohit, 2018. "A Geometric Approach to Inference in Set-Identified Entry Games," TSE Working Papers 18-943, Toulouse School of Economics (TSE), revised Mar 2019.
    47. Juan Carlos Escanciano & Lin Zhu, 2013. "Set inferences and sensitivity analysis in semiparametric conditionally identified models," CeMMAP working papers CWP55/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    48. Laura Coroneo & Valentina Corradi & Paulo Santos Monteiro, 2013. "Testing for optimal monetary policy via moment inequalities," Discussion Papers 13/07, Department of Economics, University of York.
    49. Laurens Cherchye & Thomas Demuynck & Bram De Rock, 2017. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Working Papers of Department of Economics, Leuven 598907, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    50. Canay, Ivan A., 2010. "EL inference for partially identified models: Large deviations optimality and bootstrap validity," Journal of Econometrics, Elsevier, vol. 156(2), pages 408-425, June.
    51. Zeng-Hua Lu & Alec Zuo, 2017. "Child disability, welfare payments, marital status and mothers’ labor supply: Evidence from Australia," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1339769-133, January.
    52. Armstrong, Timothy B. & Chan, Hock Peng, 2016. "Multiscale adaptive inference on conditional moment inequalities," Journal of Econometrics, Elsevier, vol. 194(1), pages 24-43.
    53. Timothy B. Armstrong & Hock Peng Chan, 2013. "Multiscale Adaptive Inference on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1885R, Cowles Foundation for Research in Economics, Yale University, revised Dec 2015.
    54. Fan, Yanqin & Park, Sang Soo, 2010. "Confidence sets for some partially identified parameters," MPRA Paper 37149, University Library of Munich, Germany.
    55. Armstrong, Timothy B., 2015. "Asymptotically exact inference in conditional moment inequality models," Journal of Econometrics, Elsevier, vol. 186(1), pages 51-65.
    56. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    57. Christian Bontemps & Rohit Kumar, 2019. "A Geometric Approach to Inference in Set-Identified Entry Games," Working Papers hal-02137356, HAL.
    58. Timothy B. Armstrong & Hock Peng Chan, 2013. "Multiscale Adaptive Inference on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1885, Cowles Foundation for Research in Economics, Yale University.
    59. Arun Chandrasekhar & Victor Chernozhukov & Francesca Molinari & Paul Schrimpf, 2012. "Inference for best linear approximations to set identified functions," CeMMAP working papers CWP43/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    60. Timothy B. Armstrong & Hock Peng Chan, 2013. "Multiscale Adaptive Inference on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1885R, Cowles Foundation for Research in Economics, Yale University, revised Oct 2014.
    61. Xiaohong Chen & Elie Tamer & Alexander Torgovitsky, 2011. "Sensitivity Analysis in Semiparametric Likelihood Models," Cowles Foundation Discussion Papers 1836, Cowles Foundation for Research in Economics, Yale University.
    62. Yuan Liao & Anna Simoni, 2016. "Bayesian Inference for Partially Identified Convex Models: Is it Valid for Frequentist Inference?," Departmental Working Papers 201607, Rutgers University, Department of Economics.
    63. Lukáš Lafférs, 2019. "Identification in Models with Discrete Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 657-696, February.
    64. Federico A. Bugni & Mehmet Caner & Anders Bredahl Kock & Soumendra Lahiri, 2016. "Inference in partially identified models with many moment inequalities using Lasso," CREATES Research Papers 2016-12, Department of Economics and Business Economics, Aarhus University.
    65. Denis Chetverikov, 2012. "Adaptive test of conditional moment inequalities," CeMMAP working papers CWP36/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    66. Shi, Xiaoxia, 2015. "Model selection tests for moment inequality models," Journal of Econometrics, Elsevier, vol. 187(1), pages 1-17.
    67. Kaido, Hiroaki, 2016. "A dual approach to inference for partially identified econometric models," Journal of Econometrics, Elsevier, vol. 192(1), pages 269-290.
    68. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    69. Li, Tong & Oka, Tatsushi, 2015. "Set identification of the censored quantile regression model for short panels with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 363-377.

  6. Federico A. Bugni & Peter Hall & Joel L. Horowitz & George R. Neumann, 2009. "Goodness-of-fit tests for functional data," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 1-18, January.

    Cited by:

    1. Oleksandr Gromenko & Piotr Kokoszka & Matthew Reimherr, 2017. "Detection of change in the spatiotemporal mean function," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 29-50, January.
    2. Federico A. Bugni & Joel L. Horowitz, 2018. "Permutation Tests for Equality of Distributions of Functional Data," Papers 1803.00798, arXiv.org, revised Dec 2019.
    3. Federico A. Bugni & Joel L. Horowitz, 2018. "Permutation tests for equality of distributions of functional data," CeMMAP working papers CWP18/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Rankings

This author is among the top 5% authors according to these criteria:
  1. Number of Journal Pages, Weighted by Number of Authors and Recursive Impact Factors

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 11 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 (8) 2012-03-08 2013-02-03 2014-02-21 2014-04-18 2015-11-01 2016-05-28 2017-01-22 2017-05-14. Author is listed
  2. NEP-DGE: Dynamic General Equilibrium (3) 2012-03-08 2012-05-15 2012-05-22
  3. NEP-ORE: Operations Research (3) 2013-02-03 2015-11-01 2017-05-14
  4. NEP-CMP: Computational Economics (1) 2012-05-15
  5. NEP-EXP: Experimental Economics (1) 2017-05-14

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Federico Andres Bugni should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.