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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/
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. 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.

    Cited by:

    1. D'esir'e K'edagni & Lixiong Li & Ismael Mourifi'e, 2020. "Discordant Relaxations of Misspecified Models," Papers 2012.11679, arXiv.org, revised Dec 2021.

  2. 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.

  3. 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. Ivan A Canay & Vishal Kamat, 2018. "Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design," Review of Economic Studies, Oxford University Press, vol. 85(3), pages 1577-1608.
    3. Athey, Susan & Imbens, Guido W. & Bayati, Mohsen, 2019. "Optimal Experimental Design for Staggered Rollouts," Research Papers 3837, Stanford University, Graduate School of Business.
    4. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jun 2021.
    5. Young, Alwyn, 2019. "Channeling Fisher: randomization tests and the statistical insignificance of seemingly significant experimental results," LSE Research Online Documents on Economics 101401, London School of Economics and Political Science, LSE Library.
    6. John A. List & Azeem M. Shaikh & Yang Xu, 2019. "Multiple hypothesis testing in experimental economics," Experimental Economics, Springer;Economic Science Association, vol. 22(4), pages 773-793, December.
    7. Tong Wang & Wei Ma, 2021. "The impact of misclassification on covariate‐adaptive randomized clinical trials," Biometrics, The International Biometric Society, vol. 77(2), pages 451-464, June.
    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. Sloczynski, Tymon, 2018. "A General Weighted Average Representation of the Ordinary and Two-Stage Least Squares Estimands," IZA Discussion Papers 11866, Institute of Labor Economics (IZA).
    10. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Jul 2021.
    11. Yichong Zhang & Xin Zheng, 2020. "Quantile treatment effects and bootstrap inference under covariate‐adaptive randomization," Quantitative Economics, Econometric Society, vol. 11(3), pages 957-982, July.
    12. Liang Jiang & Peter C. B. Phillips & Yubo Tao & Yichong Zhang, 2021. "Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations," Papers 2105.14752, arXiv.org, revised Jul 2021.
    13. Simon Heß, 2017. "Randomization inference with Stata: A guide and software," Stata Journal, StataCorp LP, vol. 17(3), pages 630-651, September.
    14. Isaiah Andrews & Emily Oster, 2017. "A Simple Approximation for Evaluating External Validity Bias," NBER Working Papers 23826, National Bureau of Economic Research, Inc.
    15. Edward N. Okeke, 2021. "Money and my mind: Maternal cash transfers and mental health," Health Economics, John Wiley & Sons, Ltd., vol. 30(11), pages 2879-2904, November.
    16. Abhijit Banerjee & Sylvain Chassang & Sergio Montero & Erik Snowberg, 2017. "A Theory of Experimenters," NBER Working Papers 23867, National Bureau of Economic Research, Inc.
    17. 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.
    18. Liang Jiang & Xiaobin Liu & Peter C.B. Phillips & Yichong Zhang, 2021. "Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations," Cowles Foundation Discussion Papers 2288, Cowles Foundation for Research in Economics, Yale University.

  4. 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. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    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. 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.
    4. 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.
    5. Yinghua He & Gabrielle Fack & Julien Grenet, 2020. "Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions," Working Papers halshs-01215998, HAL.
    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. 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.
    8. 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.
    9. Lee, Ying-Ying & Bhattacharya, Debopam, 2019. "Applied welfare analysis for discrete choice with interval-data on income," Journal of Econometrics, Elsevier, vol. 211(2), pages 361-387.
    10. 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.

  5. 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. 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.
    2. Yinghua He & Gabrielle Fack & Julien Grenet, 2020. "Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions," Working Papers halshs-01215998, HAL.
    3. 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," NBER Working Papers 23079, National Bureau of Economic Research, Inc.
    4. Yuichi Kitamura & Jorg Stoye, 2016. "Nonparametric analysis of random utility models," CeMMAP working papers CWP27/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. 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.
    6. Russell Davidson & Victoria Zinde-Walsh, 2017. "Advances in specification testing," Post-Print hal-01684821, HAL.
    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. JoonHwan Cho & Thomas M. Russell, 2018. "Simple Inference on Functionals of Set-Identified Parameters Defined by Linear Moments," Papers 1810.03180, arXiv.org, revised Nov 2021.
    12. 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.
    13. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  6. 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. Shintaro Yamaguchi, 2016. "Effects of Parental Leave Policies on Female Career and Fertility Choices," Department of Economics Working Papers 2016-10, McMaster University.
    2. 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.
    3. 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.

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

    Cited by:

    1. Kraus, David & Stefanucci, Marco, 2020. "Ridge reconstruction of partially observed functional data is asymptotically optimal," Statistics & Probability Letters, Elsevier, vol. 165(C).
    2. Mojirsheibani, Majid & Shaw, Crystal, 2018. "Classification with incomplete functional covariates," Statistics & Probability Letters, Elsevier, vol. 139(C), pages 40-46.
    3. Kraus, David, 2019. "Inferential procedures for partially observed functional data," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 583-603.

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.
    See citations under working paper version above.
  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.

    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. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Jul 2021.
    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.

  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.
    See citations under working paper version above.
  4. 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.
  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.

    Cited by:

    1. 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.
    2. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    3. 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.
    4. Lavergne, Pascal, 2015. "Assessing the Approximate Validity of Moment Restrictions," TSE Working Papers 15-562, Toulouse School of Economics (TSE), revised May 2020.
    5. 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.
    6. Guggenberger, Patrik, 2012. "A note on the relation between local power and robustness to misspecification," Economics Letters, Elsevier, vol. 116(2), pages 133-135.
    7. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Oct 2021.
    8. 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.
    9. Kaido, Hiroaki & White, Halbert, 2014. "A two-stage procedure for partially identified models," Journal of Econometrics, Elsevier, vol. 182(1), pages 5-13.

  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.

    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. Stoye, Jörg & Kitamura, Yuichi, 2013. "Nonparametric Analysis of Random Utility Models: Testing," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79753, Verein für Socialpolitik / German Economic Association.
    4. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    5. 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.
    6. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    7. 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.
    8. 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.
    9. 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.
    10. Laffers, Lukas, 2013. "Identification in Models with Discrete Variables," Discussion Paper Series in Economics 1/2013, Norwegian School of Economics, Department of Economics.
    11. Christian Bontemps & Thierry Magnac, 2017. "Set identification, moment restrictions, and inference," Post-Print hal-01575813, HAL.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Yuan Liao & Anna Simoni, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," Papers 1212.3267, arXiv.org, revised Nov 2013.
    17. Shosei Sakaguchi, 2020. "Partial Identification and Inference in Duration Models with Endogenous Censoring," CeMMAP working papers CWP8/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. 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.
    19. Rosen, Adam M., 2012. "Set identification via quantile restrictions in short panels," Journal of Econometrics, Elsevier, vol. 166(1), pages 127-137.
    20. Armstrong, Timothy B., 2014. "Weighted KS statistics for inference on conditional moment inequalities," Journal of Econometrics, Elsevier, vol. 181(2), pages 92-116.
    21. 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.
    22. Mammen, Enno & Polonik, Wolfgang, 2013. "Confidence regions for level sets," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 202-214.
    23. Madeira, Carlos, 2020. "Learning your own ability," Journal of Economic Dynamics and Control, Elsevier, vol. 121(C).
    24. Chen, Le-Yu & Szroeter, Jerzy, 2014. "Testing multiple inequality hypotheses: A smoothed indicator approach," Journal of Econometrics, Elsevier, vol. 178(P3), pages 678-693.
    25. 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.
    26. 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.
    27. 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," NBER Working Papers 23079, National Bureau of Economic Research, Inc.
    28. Beresteanu, Arie & Molchanov, Ilya & Molinari, Francesca, 2012. "Partial identification using random set theory," Journal of Econometrics, Elsevier, vol. 166(1), pages 17-32.
    29. Yuichi Kitamura & Jorg Stoye, 2016. "Nonparametric analysis of random utility models," CeMMAP working papers CWP27/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. 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.
    31. 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.
    32. Andrew Chesher & Adam Rosen & Konrad Smolinski, 2011. "An instrumental variable model of multiple discrete choice," CeMMAP working papers CWP39/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    33. Marc Henry & Ismael Mourifié, 2013. "Set inference in latent variables models," Econometrics Journal, Royal Economic Society, vol. 16(1), pages 93-105, February.
    34. Andrew Chesher & Adam Rosen, 2013. "Generalized instrumental variable models," CeMMAP working papers CWP43/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    35. Armstrong, Timothy B., 2015. "Asymptotically exact inference in conditional moment inequality models," Journal of Econometrics, Elsevier, vol. 186(1), pages 51-65.
    36. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    37. 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.
    38. Coroneo, Laura & Corradi, Valentina & Santos Monterio, Paulo, 2012. "Testing for optimal monetary policy via moment inequalities," Economic Research Papers 270654, University of Warwick - Department of Economics.
    39. Cherchye, Laurens & Demuynck, Thomas & Rock, Bram De, 2019. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Journal of Econometrics, Elsevier, vol. 211(2), pages 483-506.
    40. 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.
    41. Magnac, Thierry, 2014. "Identification partielle: méthodes et conséquences pour les applications empiriques," IDEI Working Papers 814, Institut d'Économie Industrielle (IDEI), Toulouse.
    42. Blundell, Richard & Kristensen, Dennis & Matzkin, Rosa, 2014. "Bounding quantile demand functions using revealed preference inequalities," Journal of Econometrics, Elsevier, vol. 179(2), pages 112-127.
    43. Lukáš Lafférs, 2019. "Identification in Models with Discrete Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 657-696, February.
    44. 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.
    45. Donald W.K. Andrews, 2011. "Similar-on-the-Boundary Tests for Moment Inequalities Exist, But Have Poor Power," Cowles Foundation Discussion Papers 1815R, Cowles Foundation for Research in Economics, Yale University, revised Mar 2012.
    46. Shi, Xiaoxia, 2015. "Model selection tests for moment inequality models," Journal of Econometrics, Elsevier, vol. 187(1), pages 1-17.
    47. Kaido, Hiroaki, 2016. "A dual approach to inference for partially identified econometric models," Journal of Econometrics, Elsevier, vol. 192(1), pages 269-290.
    48. 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.
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  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.

    Cited by:

    1. 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.
    2. 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.
    3. Federico A. Bugni & Joel L. Horowitz, 2018. "Permutation Tests for Equality of Distributions of Functional Data," Papers 1803.00798, arXiv.org, revised Jun 2021.
    4. Graciela Estévez-Pérez & Philippe Vieu, 2021. "A new way for ranking functional data with applications in diagnostic test," Computational Statistics, Springer, vol. 36(1), pages 127-154, March.

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NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 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

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