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Tiemen Woutersen

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. Tiemen M. Woutersen & Jerry Hausman, 2018. "Increasing the power of specification tests," CeMMAP working papers CWP46/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Gao, Yanjie & Chen, Hang & Tauni, Muhammad Zubair & Alnafrah, Ibrahim & Yu, Jiaqi, 2024. "Unpacking the impact of financialization and globalization on environmental degradation in BRICS economies," Resources Policy, Elsevier, vol. 88(C).
    2. Enrico Fabrizi & Chiara Mussida, 2020. "Assessing poverty persistence in households with children," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(4), pages 551-569, December.
    3. Som Sekhar Bhattacharyya & Praveen Nemana, 2024. "Effect of Demonetization on Advertising, Research & Development and Human Resource Intensities and its Impact on Firm’s Performance," Vision, , vol. 28(3), pages 361-373, June.

  2. John Chao & Jerry Hausman & Whitney Newey & Norman Swanson & Tiemen Woutersen, 2013. "An Expository Note on the Existence of Moments of Fuller and HFUL Estimators," Departmental Working Papers 201311, Rutgers University, Department of Economics.

    Cited by:

    1. Stuart Lane, 2025. "The moment is here: a generalised class of estimators for fuzzy regression discontinuity designs," Papers 2511.03424, arXiv.org.

  3. Tiemen M. Woutersen & John Ham, 2013. "Calculating confidence intervals for continuous and discontinuous functions of parameters," CeMMAP working papers 23/13, Institute for Fiscal Studies.

    Cited by:

    1. 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.
    2. Lechene, Valérie & Pendakur, Krishna & Wolf, Alexander, 2021. "OLS Estimation of the Intra-Household Distribution of Expenditure," CEPR Discussion Papers 15955, C.E.P.R. Discussion Papers.

  4. Govert Bijwaard & Geert Ridder & Tiemen Woutersen, 2012. "A Simple GMM Estimator for the Semiparametric Mixed Proportional Hazard Model," Norface Discussion Paper Series 2012035, Norface Research Programme on Migration, Department of Economics, University College London.

    Cited by:

    1. Govert Bijwaard & Christian Schluter, 2016. "Interdependent Hazards, Local Interactions, and the Return Decision of Recent Migrants," RFBerlin Discussion Paper Series 1620, ROCKWOOL Foundation Berlin (RFBerlin).
    2. Janys, Lena, 2017. "A General Semiparametric Approach to Inference with Marker-Dependent Hazard Rate Models," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168077, Verein für Socialpolitik / German Economic Association.
    3. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    4. van den Berg, Gerard. J. & Janys, Lena & Mammen, Enno & Nielsen, Jens Perch, 2021. "A general semiparametric approach to inference with marker-dependent hazard rate models," Journal of Econometrics, Elsevier, vol. 221(1), pages 43-67.
    5. Hausman, Jerry A. & Woutersen, Tiemen, 2014. "Estimating a semi-parametric duration model without specifying heterogeneity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 114-131.
    6. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.

  5. Norman R. Swanson & John C. Chao & Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen, 2011. "Testing Overidentifying Restrictions with Many Instruments and Heteroskedasticity," Departmental Working Papers 201118, Rutgers University, Department of Economics.

    Cited by:

    1. Walter Beckert, 2020. "A Note on Specification Testing in Some Structural Regression Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(3), pages 686-695, June.
    2. Matej Tomec & Timotej Jagric, 2017. "Does the Amount and Time of Recapitalization Affect the Profitability of Commercial Banks?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(4), pages 318-341, August.
    3. Norman E. Hutchison & Alla Koblyakova & Bryan D. MacGregor, 2024. "Equity Release Mortgages in the UK: Regional Characteristics of Demand and Supply," International Real Estate Review, Global Social Science Institute, vol. 27(4), pages 441-469.
    4. Alla Koblyakova & Larisa Fleishman & Orly Furman, 2022. "Accuracy of Households’ Dwelling Valuations, Housing Demand and Mortgage Decisions: Israeli Case," The Journal of Real Estate Finance and Economics, Springer, vol. 65(1), pages 48-74, July.
    5. Stanislav Anatolyev & Mikkel S{o}lvsten, 2020. "Testing Many Restrictions Under Heteroskedasticity," Papers 2003.07320, arXiv.org, revised Jan 2023.
    6. Jafari-Sadeghi, Vahid & Sukumar, Arun & Pagán-Castaño, Esther & Dana, Léo-Paul, 2021. "What drives women towards domestic vs international business venturing? An empirical analysis in emerging markets," Journal of Business Research, Elsevier, vol. 134(C), pages 647-660.
    7. Matsushita, Yukitoshi & Otsu, Taisuke, 2024. "A jackknife Lagrange multiplier test with many weak instruments," LSE Research Online Documents on Economics 116392, London School of Economics and Political Science, LSE Library.
    8. Paul Goldsmith-Pinkham & Isaac Sorkin & Henry Swift, 2020. "Bartik Instruments: What, When, Why, and How," American Economic Review, American Economic Association, vol. 110(8), pages 2586-2624, August.
    9. Frank Windmeijer, 2018. "Testing Over- and Underidentification in Linear Models, with Applications to Dynamic Panel Data and Asset-Pricing Models," Bristol Economics Discussion Papers 18/696, School of Economics, University of Bristol, UK.
    10. Hyunseok Jung & Xiaodong Liu, 2023. "Testing for Peer Effects without Specifying the Network Structure," Papers 2306.09806, arXiv.org, revised Oct 2025.
    11. Patrick Kline & Raffaele Saggio & Mikkel Sølvsten, 2019. "Leave-out Estimation of Variance Components," NBER Working Papers 26244, National Bureau of Economic Research, Inc.
    12. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
    13. Khemakongkanonth, Chate, 2025. "An empirical analysis on relationships between over-the-top applications for communication and traditional mobile voice services," Telecommunications Policy, Elsevier, vol. 49(3).
    14. Tugrul Gurgur, 2016. "Voice, exit and local capture in public provision of private goods," Economics of Governance, Springer, vol. 17(4), pages 397-424, November.
    15. Windmeijer, Frank, 2024. "Testing underidentification in linear models, with applications to dynamic panel and asset pricing models," Journal of Econometrics, Elsevier, vol. 240(2).
    16. Federico Crudu & Giovanni Mellace & Zsolt Sandor, 2017. "Inference in instrumental variables models with heteroskedasticity and many instruments," Department of Economics University of Siena 761, Department of Economics, University of Siena.
    17. Bekker, Paul A. & Crudu, Federico, 2015. "Jackknife instrumental variable estimation with heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 332-342.
    18. Chao, John C. & Swanson, Norman R. & Woutersen, Tiemen, 2023. "Jackknife estimation of a cluster-sample IV regression model with many weak instruments," Journal of Econometrics, Elsevier, vol. 235(2), pages 1747-1769.
    19. Marine Carrasco & Mohamed Doukali, 2022. "Testing overidentifying restrictions with many instruments and heteroscedasticity using regularised jackknife IV," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 71-97.
    20. Hongwei Shi & Xinyu Zhang & Xu Guo & Baihua He & Chenyang Wang, 2025. "Testing overidentifying restrictions on high-dimensional instruments and covariates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 77(2), pages 331-352, April.
    21. Wang, Wenjie, 2022. "Wild bootstrap test of overidentification with many instruments and heteroskedasticity," MPRA Paper 115168, University Library of Munich, Germany.
    22. Qingliang Fan & Zijian Guo & Ziwei Mei, 2022. "A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates," Papers 2205.00171, arXiv.org, revised May 2024.
    23. Kohtaro Hitomi & Masamune Iwasawa & Yoshihiko Nishiyama, 2020. "Optimal Minimax Rates against Non-smooth Alternatives," KIER Working Papers 1051, Kyoto University, Institute of Economic Research.
    24. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    25. Antonia Diaz & Luis A. Puch, 2016. "Investment, Technological Progress and Energy Efficiency," Working Papers 909, Barcelona School of Economics.
    26. Tom Boot & Johannes W. Ligtenberg, 2023. "Identification- and many moment-robust inference via invariant moment conditions," Papers 2303.07822, arXiv.org, revised Oct 2025.
    27. Jafari-Sadeghi, Vahid, 2020. "The motivational factors of business venturing: Opportunity versus necessity? A gendered perspective on European countries," Journal of Business Research, Elsevier, vol. 113(C), pages 279-289.
    28. Atsushi Inoue & Barbara Rossi, 2015. "Tests for the validity of portfolio or group choice in financial and panel regressions," Economics Working Papers 1523, Department of Economics and Business, Universitat Pompeu Fabra.
    29. Wang, Wenjie, 2020. "On Bootstrap Validity for the Test of Overidentifying Restrictions with Many Instruments and Heteroskedasticity," MPRA Paper 104858, University Library of Munich, Germany.
    30. Johannes W. Ligtenberg, 2023. "Inference in clustered IV models with many and weak instruments," Papers 2306.08559, arXiv.org, revised Oct 2025.
    31. Zhenhong Huang & Chen Wang & Jianfeng Yao, 2023. "The First-stage F Test with Many Weak Instruments," Papers 2302.14423, arXiv.org, revised Sep 2024.
    32. Kolesár, Michal, 2018. "Minimum distance approach to inference with many instruments," Journal of Econometrics, Elsevier, vol. 204(1), pages 86-100.
    33. Kohtaro Hitomi & Masamune Iwasawa & Yoshihiko Nishiyama, 2018. "Rate Optimal Specification Test When the Number of Instruments is Large," KIER Working Papers 986, Kyoto University, Institute of Economic Research.

  6. Norman R. Swanson & John C. Chao & Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen, 2011. "Asymptotic Distribution of JIVE in a Heteroskedastic IV Regression with Many Instruments," Departmental Working Papers 201110, Rutgers University, Department of Economics.

    Cited by:

    1. Matias D. Cattaneo & Michael Jansson & Whitney K. Newey, 2015. "Alternative Asymptotics and the Partially Linear Model with Many Regressors," Papers 1505.08120, arXiv.org.
    2. Matsushita, Yukitoshi & Otsu, Taisuke, 2023. "Second-order refinements for t-ratios with many instruments," Journal of Econometrics, Elsevier, vol. 232(2), pages 346-366.
    3. Tsiboe, Francis & Turner, Dylan, 2023. "The crop insurance demand response to premium subsidies: Evidence from U.S. Agriculture," Food Policy, Elsevier, vol. 119(C).
    4. Dennis Lim & Wenjie Wang & Yichong Zhang, 2022. "A Conditional Linear Combination Test with Many Weak Instruments," Papers 2207.11137, arXiv.org, revised Apr 2023.
    5. Cheng Hsiao & Qiankun Zhou, 2017. "JIVE for Panel Dynamic Simultaneous Equations Models," Departmental Working Papers 2017-10, Department of Economics, Louisiana State University.
    6. Wang, Wenjie, 2021. "Wild Bootstrap for Instrumental Variables Regression with Weak Instruments and Few Clusters," MPRA Paper 106227, University Library of Munich, Germany.
    7. Chenchuan (Mark) Li & Ulrich K. Müller, 2020. "Linear Regression with Many Controls of Limited Explanatory Power," Working Papers 2020-57, Princeton University. Economics Department..
    8. Brian Asquith, 2019. "Do Rent Increases Reduce the Housing Supply Under Rent Control? Evidence from Evictions in San Francisco," Upjohn Working Papers 19-296, W.E. Upjohn Institute for Employment Research.
    9. Federico Crudu & Giovanni Mellace & Zsolt Sándor, 2020. "Inference in instrumental variables models with heteroskedasticity and many instruments," Department of Economics University of Siena 821, Department of Economics, University of Siena.
    10. Matsushita, Yukitoshi & Otsu, Taisuke, 2024. "A jackknife Lagrange multiplier test with many weak instruments," LSE Research Online Documents on Economics 116392, London School of Economics and Political Science, LSE Library.
    11. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2014. "Inference in high dimensional panel models with an application to gun control," CeMMAP working papers 50/14, Institute for Fiscal Studies.
    12. Norman R. Swanson & John C. Chao & Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen, 2011. "Testing Overidentifying Restrictions with Many Instruments and Heteroskedasticity," Departmental Working Papers 201118, Rutgers University, Department of Economics.
    13. Matsushita, Yukitoshi & Otsu, Taisuke, 2020. "Jackknife empirical likelihood: small bandwidth, sparse network and high-dimension asymptotic," LSE Research Online Documents on Economics 106488, London School of Economics and Political Science, LSE Library.
    14. Joshua Angrist & Brigham Frandsen, 2019. "Machine Labor," NBER Working Papers 26584, National Bureau of Economic Research, Inc.
    15. Brian P. Poi, 2006. "Jackknife instrumental variables estimation in Stata," Stata Journal, StataCorp LLC, vol. 6(3), pages 364-376, September.
    16. Murray Michael P., 2017. "Linear Model IV Estimation When Instruments Are Many or Weak," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    17. Eric Gautier & Christiern Rose, 2022. "Fast, Robust Inference for Linear Instrumental Variables Models using Self-Normalized Moments," Papers 2211.02249, arXiv.org, revised Nov 2022.
    18. Michal Kolesár & Raj Chetty & John N. Friedman & Edward L. Glaeser & Guido W. Imbens, 2011. "Identification and Inference with Many Invalid Instruments," NBER Working Papers 17519, National Bureau of Economic Research, Inc.
    19. Hyunseok Jung & Xiaodong Liu, 2023. "Testing for Peer Effects without Specifying the Network Structure," Papers 2306.09806, arXiv.org, revised Oct 2025.
    20. Byunghoon Kang, 2017. "Inference in Nonparametric Series Estimation with Data-Dependent Undersmoothing," Working Papers 170712442, Lancaster University Management School, Economics Department.
    21. Liyu Dou & Pengjin Min & Wenjie Wang & Yichong Zhang, 2025. "An Improved Inference for IV Regressions," Papers 2506.23816, arXiv.org, revised Feb 2026.
    22. Patrick Kline & Raffaele Saggio & Mikkel Sølvsten, 2019. "Leave-out Estimation of Variance Components," NBER Working Papers 26244, National Bureau of Economic Research, Inc.
    23. Anna Mikusheva & Mikkel Sølvsten, 2025. "Linear regression with weak exogeneity," Quantitative Economics, Econometric Society, vol. 16(2), pages 367-403, May.
    24. Carrasco, Marine & Tchuente, Guy, 2015. "Regularized LIML for many instruments," Journal of Econometrics, Elsevier, vol. 186(2), pages 427-442.
    25. Wang, Wenjie & Doko Tchatoka, Firmin, 2018. "On Bootstrap inconsistency and Bonferroni-based size-correction for the subset Anderson–Rubin test under conditional homoskedasticity," Journal of Econometrics, Elsevier, vol. 207(1), pages 188-211.
    26. Alena Skolkova, 2023. "Instrumental Variable Estimation with Many Instruments Using Elastic-Net IV," CERGE-EI Working Papers wp759, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    27. Stanislav Anatolyev & Anna Mikusheva, 2018. "Limit Theorems for Factor Models," Papers 1807.06338, arXiv.org, revised Sep 2020.
    28. Bekker, Paul A. & Crudu, Federico, 2015. "Jackknife instrumental variable estimation with heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 332-342.
    29. John Chao & Jerry Hausman & Whitney Newey & Norman Swanson & Tiemen Woutersen, 2013. "Combining Two Consistent Estimators," Departmental Working Papers 201310, Rutgers University, Department of Economics.
    30. Matsushita, Yukitoshi & Otsu, Taisuke, 2023. "Second-order refinements for t-ratios with many instruments," LSE Research Online Documents on Economics 111065, London School of Economics and Political Science, LSE Library.
    31. Anatolyev, Stanislav & Sølvsten, Mikkel, 2023. "Testing many restrictions under heteroskedasticity," Journal of Econometrics, Elsevier, vol. 236(1).
    32. Yukitoshi Matsushita & Taisuke Otsu, 2020. "Jackknife Lagrange multiplier test with many weak instruments," STICERD - Econometrics Paper Series 613, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    33. Hansen, Christian & Kozbur, Damian, 2014. "Instrumental variables estimation with many weak instruments using regularized JIVE," Journal of Econometrics, Elsevier, vol. 182(2), pages 290-308.
    34. Chao, John C. & Swanson, Norman R. & Woutersen, Tiemen, 2023. "Jackknife estimation of a cluster-sample IV regression model with many weak instruments," Journal of Econometrics, Elsevier, vol. 235(2), pages 1747-1769.
    35. Marine Carrasco & Mohamed Doukali, 2022. "Testing overidentifying restrictions with many instruments and heteroscedasticity using regularised jackknife IV," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 71-97.
    36. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    37. Jinyuan Chang & Zhentao Shi & Jia Zhang, 2021. "Culling the herd of moments with penalized empirical likelihood," Papers 2108.03382, arXiv.org, revised May 2022.
    38. Lim, Dennis & Wang, Wenjie & Zhang, Yichong, 2024. "A conditional linear combination test with many weak instruments," Journal of Econometrics, Elsevier, vol. 238(2).
    39. Luther Yap, 2024. "Inference with Many Weak Instruments and Heterogeneity," Papers 2408.11193, arXiv.org, revised Apr 2025.
    40. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    41. Manu Navjeevan, 2023. "An Identification and Dimensionality Robust Test for Instrumental Variables Models," Papers 2311.14892, arXiv.org, revised Dec 2024.
    42. Antonia Diaz & Luis A. Puch, 2016. "Investment, Technological Progress and Energy Efficiency," Working Papers 909, Barcelona School of Economics.
    43. Jonas Andersson & Jarle Møen, 2016. "A Simple Improvement of the IV-estimator for the Classical Errors-in-Variables Problem," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 113-125, February.
    44. Stanislav Anatolyev, 2012. "Instrumental variables estimation and inference in the presence of many exogenous regressors," Working Papers w0162, Center for Economic and Financial Research (CEFIR).
    45. Luther Yap, 2023. "Valid Wald Inference with Many Weak Instruments," Papers 2311.15932, arXiv.org.
    46. Tom Boot & Johannes W. Ligtenberg, 2023. "Identification- and many moment-robust inference via invariant moment conditions," Papers 2303.07822, arXiv.org, revised Oct 2025.
    47. Byunghoon Kang, 2018. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Working Papers 240829404, Lancaster University Management School, Economics Department.
    48. Kirill S. Evdokimov & Michal Kolesár, 2018. "Inference in Instrumental Variable Regression Analysis with Heterogeneous Treatment Effects," Working Papers 2018-16, Princeton University. Economics Department..
    49. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
    50. Bekker, Paul & Wansbeek, Tom, 2016. "Simple many-instruments robust standard errors through concentrated instrumental variables," Economics Letters, Elsevier, vol. 149(C), pages 52-55.
    51. Yukitoshi Matsushita & Taisuke Otsu, 2019. "Jackknife, small bandwidth and high-dimensional asymptotics," STICERD - Econometrics Paper Series 605, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    52. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
    53. Anna Mikusheva & Liyang Sun, 2020. "Inference with Many Weak Instruments," Papers 2004.12445, arXiv.org, revised Oct 2021.
    54. Anatolyev, Stanislav & Smirnov, Maksim, 2024. "Off-diagonal elements of projection matrices and dimension asymptotics," Economics Letters, Elsevier, vol. 239(C).
    55. Michal Kolesár, 2013. "Estimation in an Instrumental Variables Model With Treatment Effect Heterogeneity," Working Papers 2013-2, Princeton University. Economics Department..
    56. Qu Feng & Sombut Jaidee & Wenjie Wang, 2025. "Robust Inference with High-Dimensional Instruments," Papers 2506.23834, arXiv.org.
    57. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers 36/16, Institute for Fiscal Studies.
    58. Boot, Tom, 2023. "Joint inference based on Stein-type averaging estimators in the linear regression model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1542-1563.
    59. Atsushi Inoue & Barbara Rossi, 2015. "Tests for the validity of portfolio or group choice in financial and panel regressions," Economics Working Papers 1523, Department of Economics and Business, Universitat Pompeu Fabra.
    60. Wang, Wenjie, 2020. "On Bootstrap Validity for the Test of Overidentifying Restrictions with Many Instruments and Heteroskedasticity," MPRA Paper 104858, University Library of Munich, Germany.
    61. Jochmans, Koen, 2023. "Many (Weak) Judges in Judge-Leniency Designs," TSE Working Papers 23-1481, Toulouse School of Economics (TSE).
    62. Johannes W. Ligtenberg, 2023. "Inference in clustered IV models with many and weak instruments," Papers 2306.08559, arXiv.org, revised Oct 2025.
    63. Lei Bill Wang, 2023. "Estimating overidentified linear models with heteroskedasticity and outliers," Papers 2305.17615, arXiv.org, revised Aug 2024.
    64. Kolesár, Michal, 2018. "Minimum distance approach to inference with many instruments," Journal of Econometrics, Elsevier, vol. 204(1), pages 86-100.
    65. Matthew Harding & Carlos Lamarche & Chris Muris, 2022. "Estimation of a Factor-Augmented Linear Model with Applications Using Student Achievement Data," Papers 2203.03051, arXiv.org.
    66. Tom Boot & Didier Nibbering, 2024. "Inference on LATEs with covariates," Papers 2402.12607, arXiv.org, revised Nov 2024.
    67. Anna Mikusheva & Liyang Sun, 2023. "Weak Identification with Many Instruments," Papers 2308.09535, arXiv.org, revised Jan 2024.
    68. Byunghoon Kang, 2019. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Papers 1909.12162, arXiv.org, revised Feb 2020.
    69. Shobande, Olatunji A., 2023. "Rethinking social change: Does the permanent and transitory effects of electricity and solid fuel use predict health outcome in Africa?," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    70. Sølvsten, Mikkel, 2020. "Robust estimation with many instruments," Journal of Econometrics, Elsevier, vol. 214(2), pages 495-512.

  7. Jerry Hausman & Whitney K. Newey & Tiemen M. Woutersen & John Chao & Norman Swanson, 2007. "Instrumental variable estimation with heteroskedasticity and many instruments," CeMMAP working papers CWP22/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Barnichon, Regis & Mesters, Geert, 2019. "Identifying Modern Macro Equations with Old Shocks," CEPR Discussion Papers 13765, C.E.P.R. Discussion Papers.
    2. Naoto Kunitomo & Yukitoshi Matsushita, 2008. "Improving the Rank-Adjusted Anderson-Rubin Test with Many Instruments and Persistent Heteroscedasticity," CIRJE F-Series CIRJE-F-588, CIRJE, Faculty of Economics, University of Tokyo.
    3. Ng Serena & Bai Jushan, 2009. "Selecting Instrumental Variables in a Data Rich Environment," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-34, April.
    4. Grant, Matthew & Soderbery, Anson, 2024. "Heteroskedastic supply and demand estimation: Analysis and testing," Journal of International Economics, Elsevier, vol. 150(C).
    5. Matsushita, Yukitoshi & Otsu, Taisuke, 2023. "Second-order refinements for t-ratios with many instruments," Journal of Econometrics, Elsevier, vol. 232(2), pages 346-366.
    6. Sadhan Kumar Chattopadhyay & Siddhartha Nath & Sreerupa Sengupta, 2023. "Recent Dynamics of Women Labour Force Participation in India," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 66(4), pages 1041-1059, December.
    7. Jorge Gallego & Stanislao Maldonado & Lorena Trujillo, 2018. "Blessing a Curse? Institutional Reform and Resource Booms in Colombia," Working Papers 122, Peruvian Economic Association.
    8. Morricone, Serena & Munari, Federico & Oriani, Raffaele & de Rassenfosse, Gaetan, 2017. "Commercialization Strategy and IPO Underpricing," Research Policy, Elsevier, vol. 46(6), pages 1133-1141.
    9. Einiö, Elias, 2016. "The loss of production work: evidence from quasiexperimental identification of labour demand functions," LSE Research Online Documents on Economics 69019, London School of Economics and Political Science, LSE Library.
    10. Giacomo Di Pasquale & Elisa Parazzi, 2024. "Shifts in the Boot: Understanding Inequality’s Impact on Interregional Migration Patterns in Italy," Economies, MDPI, vol. 12(12), pages 1-21, November.
    11. Eric French & Jae Song, 2014. "The Effect of Disability Insurance Receipt on Labor Supply," American Economic Journal: Economic Policy, American Economic Association, vol. 6(2), pages 291-337, May.
    12. Dennis Lim & Wenjie Wang & Yichong Zhang, 2022. "A Conditional Linear Combination Test with Many Weak Instruments," Papers 2207.11137, arXiv.org, revised Apr 2023.
    13. Alexandre Belloni & Daniel Chen & Victor Chernozhukov & Christian Hansen, 2010. "Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain," Papers 1010.4345, arXiv.org, revised Apr 2015.
    14. Xiduo Chen & Xingdong Feng & Antonio F. Galvao & Yeheng Ge, 2025. "Treatment Effects Inference with High-Dimensional Instruments and Control Variables," Papers 2503.20149, arXiv.org, revised Oct 2025.
    15. Wang, Wenjie, 2021. "Wild Bootstrap for Instrumental Variables Regression with Weak Instruments and Few Clusters," MPRA Paper 106227, University Library of Munich, Germany.
    16. Bekker, Paul A. & Crudu, Federico, 2012. "Symmetric Jackknife Instrumental Variable Estimation," MPRA Paper 37853, University Library of Munich, Germany.
    17. Alyssa G. Anderson & Wenxin Du & Bernd Schlusche, 2021. "Arbitrage Capital of Global Banks," Finance and Economics Discussion Series 2021-032, Board of Governors of the Federal Reserve System (U.S.).
    18. Fan, Qingliang & Zhong, Wei, 2018. "Nonparametric Additive Instrumental Variable Estimator: A Group Shrinkage Estimation Perspective," IRTG 1792 Discussion Papers 2018-052, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    19. Agan, Amanda & Doleac, Jennifer & Harvey, Anna, 2021. "Misdemeanor Prosecution," IZA Discussion Papers 14234, Institute of Labor Economics (IZA).
    20. Canay, Ivan A., 2010. "Simultaneous selection and weighting of moments in GMM using a trapezoidal kernel," Journal of Econometrics, Elsevier, vol. 156(2), pages 284-303, June.
    21. Johannes W. Ligtenberg & Tiemen Woutersen, 2024. "Multidimensional clustering in judge designs," Papers 2406.09473, arXiv.org.
    22. John Chao & Jerry Hausman & Whitney Newey & Norman Swanson & Tiemen Woutersen, 2013. "An Expository Note on the Existence of Moments of Fuller and HFUL Estimators," Departmental Working Papers 201311, Rutgers University, Department of Economics.
    23. Federico Crudu & Giovanni Mellace & Zsolt Sándor, 2020. "Inference in instrumental variables models with heteroskedasticity and many instruments," Department of Economics University of Siena 821, Department of Economics, University of Siena.
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    63. Yukitoshi Matsushita & Taisuke Otsu, 2020. "Jackknife Lagrange multiplier test with many weak instruments," STICERD - Econometrics Paper Series 613, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
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    66. Wang, Wenjie, 2022. "Wild bootstrap test of overidentification with many instruments and heteroskedasticity," MPRA Paper 115168, University Library of Munich, Germany.
    67. Lim, Dennis & Wang, Wenjie & Zhang, Yichong, 2024. "A conditional linear combination test with many weak instruments," Journal of Econometrics, Elsevier, vol. 238(2).
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    69. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    70. Naoto Kunitomo, 2008. "An Optimal Modification of the LIML Estimation for Many Instruments and Persistent Heteroscedasticity," CIRJE F-Series CIRJE-F-576, CIRJE, Faculty of Economics, University of Tokyo.
    71. Hausman, Jerry & Lewis, Randall & Menzel, Konrad & Newey, Whitney, 2011. "Properties of the CUE estimator and a modification with moments," Journal of Econometrics, Elsevier, vol. 165(1), pages 45-57.
    72. Crudu, Federico & Sándor, Zsolt, 2011. "On the finite-sample properties of conditional empirical likelihood estimators," MPRA Paper 34116, University Library of Munich, Germany.
    73. Zhenhong Huang & Chen Wang & Jianfeng Yao, 2023. "A specification test for the strength of instrumental variables," Papers 2302.14396, arXiv.org.
    74. Priebe, Jan, 2011. "Child Costs and the Causal Effect of Fertility on Female Labor Supply: An investigation for Indonesia 1993-2008," Proceedings of the German Development Economics Conference, Berlin 2011 67, Verein für Socialpolitik, Research Committee Development Economics.
    75. Huntington-Klein Nick, 2020. "Instruments with Heterogeneous Effects: Bias, Monotonicity, and Localness," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 182-208, January.
    76. Tom Wansbeek & Dennis Prak, 2017. "LIML in the static linear panel data model," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 385-395, March.
    77. Einiö, Elias, 2015. "The Loss of Production Work: Identification of Demand Shifts Based on Local Soviet Trade Shocks," Working Papers 61, VATT Institute for Economic Research.
    78. Bekker, Paul & Wansbeek, Tom, 2016. "Simple many-instruments robust standard errors through concentrated instrumental variables," Economics Letters, Elsevier, vol. 149(C), pages 52-55.
    79. Keisuke Hirano & Jack R. Porter, 2015. "Location Properties of Point Estimators in Linear Instrumental Variables and Related Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 720-733, December.
    80. Yukitoshi Matsushita & Taisuke Otsu, 2019. "Jackknife, small bandwidth and high-dimensional asymptotics," STICERD - Econometrics Paper Series 605, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    81. Abutaliev, Albert & Anatolyev, Stanislav, 2013. "Asymptotic variance under many instruments: Numerical computations," Economics Letters, Elsevier, vol. 118(2), pages 272-274.
    82. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
    83. Zhaonan Qu & Yongchan Kwon, 2024. "Distributionally Robust Instrumental Variables Estimation," Papers 2410.15634, arXiv.org, revised Dec 2024.
    84. Michal Kolesár, 2013. "Estimation in an Instrumental Variables Model With Treatment Effect Heterogeneity," Working Papers 2013-2, Princeton University. Economics Department..
    85. Qu Feng & Sombut Jaidee & Wenjie Wang, 2025. "Robust Inference with High-Dimensional Instruments," Papers 2506.23834, arXiv.org.
    86. Wang, Wenjie, 2020. "On Bootstrap Validity for the Test of Overidentifying Restrictions with Many Instruments and Heteroskedasticity," MPRA Paper 104858, University Library of Munich, Germany.
    87. Johannes W. Ligtenberg, 2023. "Inference in clustered IV models with many and weak instruments," Papers 2306.08559, arXiv.org, revised Oct 2025.
    88. Eric French & Jae Song, 2012. "The effect of Disability Insurance receipt on labor supply: a dynamic analysis," Working Paper Series WP-2012-12, Federal Reserve Bank of Chicago.
    89. Attanasio, O. & Levell, P. & Low, H. & Sanchez-Marcos, V., 2017. "Aggregating Elasticities: Intensive and Extensive Margins of Female Labour Supply," Cambridge Working Papers in Economics 1711, Faculty of Economics, University of Cambridge.
    90. Jaeger, David A. & Parys, Juliane, 2009. "On the Sensitivity of Return to Schooling Estimates to Estimation Methods, Model Specification, and Influential Outliers If Identification Is Weak," IZA Discussion Papers 3961, Institute of Labor Economics (IZA).
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    93. Hübler, Olaf, 2013. "Methods in empirical economics - a selective review with applications," Hannover Economic Papers (HEP) dp-513, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    94. Tom Boot & Didier Nibbering, 2024. "Inference on LATEs with covariates," Papers 2402.12607, arXiv.org, revised Nov 2024.
    95. Anna Mikusheva & Liyang Sun, 2023. "Weak Identification with Many Instruments," Papers 2308.09535, arXiv.org, revised Jan 2024.
    96. Van Bellegem, Sébastien & Florens, Jean-Pierre, 2014. "Instrumental variable estimation in functional linear models," LIDAM Discussion Papers CORE 2014056, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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  8. Jerry Hausman & Tiemen M. Woutersen, 2005. "Estimating a semi-parametric duration model without specifying heterogeneity," CeMMAP working papers CWP11/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Chen, Songnian, 2019. "Quantile regression for duration models with time-varying regressors," Journal of Econometrics, Elsevier, vol. 209(1), pages 1-17.
    2. Gallant, A. Ronald & Hong, Han & Leung, Michael P. & Li, Jessie, 2022. "Constrained estimation using penalization and MCMC," Journal of Econometrics, Elsevier, vol. 228(1), pages 85-106.
    3. Burda, Martin & Harding, Matthew, 2014. "Environmental Justice: Evidence from Superfund cleanup durations," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 380-401.
    4. Khan, Shakeeb & Tamer, Elie, 2007. "Partial rank estimation of duration models with general forms of censoring," Journal of Econometrics, Elsevier, vol. 136(1), pages 251-280, January.
    5. Jiun-Hua Su, 2019. "Counterfactual Inference in Duration Models with Random Censoring," Papers 1902.08502, arXiv.org.
    6. Gerard J. van den Berg & Petyo Bonev & Enno Mammen, 2020. "Nonparametric Instrumental Variable Methods for Dynamic Treatment Evaluation," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 355-367, May.
    7. Anderl, Eva & Schumann, Jan Hendrik & Kunz, Werner, 2016. "Helping Firms Reduce Complexity in Multichannel Online Data: A New Taxonomy-Based Approach for Customer Journeys," Journal of Retailing, Elsevier, vol. 92(2), pages 185-203.
    8. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    9. van den Berg, Gerard. J. & Janys, Lena & Mammen, Enno & Nielsen, Jens Perch, 2021. "A general semiparametric approach to inference with marker-dependent hazard rate models," Journal of Econometrics, Elsevier, vol. 221(1), pages 43-67.
    10. Shin, Youngki, 2008. "Rank estimation of monotone hazard models," Economics Letters, Elsevier, vol. 100(1), pages 80-82, July.
    11. Arulampalam, Wiji & Corradi, Valentina & Gutknecht, Daniel, 2017. "Modeling heaped duration data: An application to neonatal mortality," Journal of Econometrics, Elsevier, vol. 200(2), pages 363-377.

  9. Tiemen Woutersen & Robert M. de Jong, 2004. "Dynamic time series binary choice," Econometric Society 2004 North American Summer Meetings 365, Econometric Society.

    Cited by:

    1. Don Harding & Adrian Pagan, 2009. "An Econometric Analysis of Some Models for Constructed Binary Time Series," NCER Working Paper Series 39, National Centre for Econometric Research, revised 02 Jul 2009.
    2. Seo, Myung Hwan & Linton, Oliver, 2007. "A smoothed least squares estimator for threshold regression models," Journal of Econometrics, Elsevier, vol. 141(2), pages 704-735, December.
    3. Hahn, Jinyong & Kuersteiner, Guido, 2010. "Stationarity and mixing properties of the dynamic Tobit model," Economics Letters, Elsevier, vol. 107(2), pages 105-111, May.
    4. Geert Dhaene & Koen Jochmans, 2014. "Split-Panel Jackknife Estimation of Fixed-Effect Models," Sciences Po Economics Publications (main) hal-01070553, HAL.
    5. Lei, J., 2013. "Smoothed Spatial Maximum Score Estimation of Spatial Autoregressive Binary Choice Panel Models," Discussion Paper 2013-061, Tilburg University, Center for Economic Research.
    6. Dardanoni, Valentino & Li Donni, Paolo, 2012. "Incentive and selection effects of Medigap insurance on inpatient care," Journal of Health Economics, Elsevier, vol. 31(3), pages 457-470.
    7. António R. Antunes & Diana Bonfim & Nuno Monteiro & Paulo M.M. Rodrigues, 2016. "Forecasting banking crises with dynamic panel probit models," Working Papers w201613, Banco de Portugal, Economics and Research Department.
    8. Christiansen, Charlotte & Eriksen, Jonas N. & Møller, Stig V., 2019. "Negative house price co-movements and US recessions," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 382-394.
    9. Lei, J., 2013. "Smoothed Spatial Maximum Score Estimation of Spatial Autoregressive Binary Choice Panel Models," Other publications TiSEM d63bf400-7ff2-4a1c-8067-1, Tilburg University, School of Economics and Management.
    10. Siddhartha Chib & Michael J. Dueker, 2004. "Non-Markovian regime switching with endogenous states and time-varying state strengths," Working Papers 2004-030, Federal Reserve Bank of St. Louis.
    11. Frazier, David T. & Liu, Xiaochun, 2016. "A new approach to risk-return trade-off dynamics via decomposition," Journal of Economic Dynamics and Control, Elsevier, vol. 62(C), pages 43-55.
    12. Igor Kheifets & Carlos Velasco, 2012. "Model Adequacy Checks for Discrete Choice Dynamic Models," Working Papers w0170, Center for Economic and Financial Research (CEFIR).
    13. Woutersen, Tiemen & Hausman, Jerry A., 2019. "Increasing the power of specification tests," Journal of Econometrics, Elsevier, vol. 211(1), pages 166-175.
    14. David P. Brown & Andrew Eckert & James Lin, 2018. "Information and transparency in wholesale electricity markets: evidence from Alberta," Journal of Regulatory Economics, Springer, vol. 54(3), pages 292-330, December.
    15. Harri Pönkä & Markku Stenborg, 2020. "Forecasting the state of the Finnish business cycle," Finnish Economic Papers, Finnish Economic Association, vol. 29(1), pages 81-99, Spring.
    16. Andrei Zeleneev & Weisheng Zhang, 2025. "Tractable Estimation of Nonlinear Panels with Interactive Fixed Effects," Papers 2511.15427, arXiv.org.
    17. Francis Bismans & Reynald Majetti, 2013. "Forecasting recessions using financial variables: the French case," Empirical Economics, Springer, vol. 44(2), pages 419-433, April.
    18. Byeong U. Park & Leopold Simar & Valentin Zelenyuk, 2016. "Nonparametric Estimation of Dynamic Discrete Choice Models for Time Series Data," CEPA Working Papers Series WP062016, School of Economics, University of Queensland, Australia.
    19. Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
    20. Gnabo, Jean-Yves & Laurent, Sébastien & Lecourt, Christelle, 2009. "Does transparency in central bank intervention policy bring noise to the FX market?: The case of the Bank of Japan," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(1), pages 94-111, February.
    21. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
    22. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.
    23. Henri Nyberg & Harri Pönkä, 2015. "International Sign Predictability of Stock Returns: The Role of the United States," CREATES Research Papers 2015-20, Department of Economics and Business Economics, Aarhus University.
    24. Moysiadis, Theodoros & Fokianos, Konstantinos, 2014. "On binary and categorical time series models with feedback," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 209-228.
    25. Nissilä, Wilma, 2020. "Probit based time series models in recession forecasting – A survey with an empirical illustration for Finland," BoF Economics Review 7/2020, Bank of Finland.
    26. Byeong U. Park & Léopold Simar & Valentin Zelenyuk, 2013. "Non-Parametric Approach to Dynamic Time Series Discrete Choice Models," CEPA Working Papers Series WP092013, School of Economics, University of Queensland, Australia.
    27. Benjamin Williams, 2018. "Identification of a Nonseparable Model under Endogeneity using Binary Proxies for Unobserved Heterogeneity," Working Papers 2018-003, The George Washington University, The Center for Economic Research.
    28. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, Center for Economic and Financial Research (CEFIR).
    29. Moreira, Afonso M. & Martins, Luis F., 2020. "A new mechanism for anticipating price exuberance," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 199-221.
    30. Christophe Schalck & Meryem Schalck, 2021. "Predicting French SME Failures: New Evidence from Machine Learning Techniques," Working Papers 2021-009, Department of Research, Ipag Business School.
    31. Taisuke Otsu & Myung Hwan Seo, 2014. "Asymptotics for maximum score method under general conditions," STICERD - Econometrics Paper Series 571, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    32. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    33. Taylor, James W., 2017. "Probabilistic forecasting of wind power ramp events using autoregressive logit models," European Journal of Operational Research, Elsevier, vol. 259(2), pages 703-712.
    34. Jean-Yves Gnabo & Luiz de Mello & Diego Moccero, 2008. "Interdependencies between Monetary Policy and Foreign Exchange Intervention under Inflation Targeting: The Case of Brazil and the Czech Republic," WIDER Working Paper Series RP2008-95, World Institute for Development Economic Research (UNU-WIDER).
    35. Schumann, Martin & Severini, Thomas A. & Tripathi, Gautam, 2023. "The role of score and information bias in panel data likelihoods," Journal of Econometrics, Elsevier, vol. 235(2), pages 1215-1238.
    36. Truquet, Lionel, 2023. "Strong mixing properties of discrete-valued time series with exogenous covariates," Stochastic Processes and their Applications, Elsevier, vol. 160(C), pages 294-317.
    37. James W. Taylor & Keming Yu, 2016. "Using auto-regressive logit models to forecast the exceedance probability for financial risk management," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 1069-1092, October.
    38. Anatolyev Stanislav, 2009. "Multi-Market Direction-of-Change Modeling Using Dependence Ratios," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-24, March.
    39. Freitag, L., 2014. "Procyclicality and path dependence of sovereign credit ratings: The example of Europe," Research Memorandum 020, Maastricht University, Graduate School of Business and Economics (GSBE).
    40. Michel, Jon & de Jong, Robert M., 2018. "Mixing properties of the dynamic Tobit model with mixing errors," Economics Letters, Elsevier, vol. 162(C), pages 112-115.
    41. Fokianos, Konstantinos & Moysiadis, Theodoros, 2017. "Binary time series models driven by a latent process," Econometrics and Statistics, Elsevier, vol. 2(C), pages 117-130.
    42. Leung, Michael P., 2019. "A weak law for moments of pairwise stable networks," Journal of Econometrics, Elsevier, vol. 210(2), pages 310-326.
    43. Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.
    44. Harri Pönkä, 2015. "The Role of Credit in Predicting US Recessions," CREATES Research Papers 2015-48, Department of Economics and Business Economics, Aarhus University.
    45. George Monokroussos, 2013. "A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 42(1), pages 71-105, June.
    46. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    47. Fokianos, Konstantinos & Truquet, Lionel, 2019. "On categorical time series models with covariates," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3446-3462.
    48. Brause, Alexander, 2008. "Foreign exchange interventions in emerging market countries: New lessons from Argentina," W.E.P. - Würzburg Economic Papers 79, University of Würzburg, Department of Economics.
    49. Chen, Songnian & Zhang, Hanghui, 2015. "Binary quantile regression with local polynomial smoothing," Journal of Econometrics, Elsevier, vol. 189(1), pages 24-40.
    50. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.

  10. Geert Ridder & Tiemen Woutersen, 2002. "The Singularity of the Information Matrix of the Mixed Proportional Hazard Model," University of Western Ontario, Departmental Research Report Series 20026, University of Western Ontario, Department of Economics.

    Cited by:

    1. St'ephane Bonhomme & Kevin Dano & Bryan S. Graham, 2025. "Moment Restrictions for Nonlinear Panel Data Models with Feedback," Papers 2506.12569, arXiv.org, revised Jul 2025.
    2. Arkadiusz Szydłowski, 2019. "Endogenous censoring in the mixed proportional hazard model with an application to optimal unemployment insurance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1086-1101, November.
    3. Burda, Martin & Harding, Matthew, 2014. "Environmental Justice: Evidence from Superfund cleanup durations," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 380-401.
    4. 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. Chen, Xiaohong & Liao, Zhipeng, 2014. "Sieve M inference on irregular parameters," Journal of Econometrics, Elsevier, vol. 182(1), pages 70-86.
    6. Jaap H. Abbring, 2012. "Mixed Hitting‐Time Models," Econometrica, Econometric Society, vol. 80(2), pages 783-819, March.
    7. Bo Honore & Aureo de Paula, 2008. "Interdependent Durations," PIER Working Paper Archive 08-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    8. Effraimidis, Georgios, 2016. "Nonparametric Identification of a Time-Varying Frailty Model," DaCHE discussion papers 2016:6, University of Southern Denmark, Dache - Danish Centre for Health Economics.
    9. Jerry Hausman & Tiemen M. Woutersen, 2005. "Estimating a semi-parametric duration model without specifying heterogeneity," CeMMAP working papers CWP11/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Ruixuan Liu, 2020. "A competing risks model with time‐varying heterogeneity and simultaneous failure," Quantitative Economics, Econometric Society, vol. 11(2), pages 535-577, May.
    11. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    12. Jaap H. Abbring, 2010. "Identification of Dynamic Discrete Choice Models," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 367-394, September.
    13. van den Berg, Gerard. J. & Janys, Lena & Mammen, Enno & Nielsen, Jens Perch, 2021. "A general semiparametric approach to inference with marker-dependent hazard rate models," Journal of Econometrics, Elsevier, vol. 221(1), pages 43-67.
    14. Bo E. Honore & Aureo de Paula, 2007. "Interdependent Durations, Second Version," PIER Working Paper Archive 08-044, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Nov 2008.
    15. Jaap H. Abbring, 0000. "Mixed Hitting-Time Models," Tinbergen Institute Discussion Papers 07-057/3, Tinbergen Institute, revised 11 Aug 2009.
    16. Jaap H. Abbring, 2006. "The Event-History Approach to Program Evaluation," Tinbergen Institute Discussion Papers 06-057/3, Tinbergen Institute, revised 29 Oct 2007.
    17. Stéphane Bonhomme & Kevin Dano & Bryan S. Graham, 2025. "Moment restrictions for nonlinear panel data models with feedback," CeMMAP working papers 12/25, Institute for Fiscal Studies.
    18. Sasaki, Yuya, 2015. "Heterogeneity and selection in dynamic panel data," Journal of Econometrics, Elsevier, vol. 188(1), pages 236-249.
    19. Mansi Sharma & Steven Stern, 2024. "Generalized Weibull Distributions," Department of Economics Working Papers 24-05, Stony Brook University, Department of Economics.
    20. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    21. Bo E. Honoré & Aureo de Paula, 2009. ""Interdependent Durations" Third Version," PIER Working Paper Archive 09-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Feb 2008.
    22. Arulampalam, Wiji & Corradi, Valentina & Gutknecht, Daniel, 2017. "Modeling heaped duration data: An application to neonatal mortality," Journal of Econometrics, Elsevier, vol. 200(2), pages 363-377.

  11. Tiemen Woutersen, 2002. "Robustness against Incidental Parameters," University of Western Ontario, Departmental Research Report Series 20028, University of Western Ontario, Department of Economics.

    Cited by:

    1. Antonio F. Galvao & Jiaying Gu & Stanislav Volgushev, 2018. "On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects," Papers 1807.11863, arXiv.org, revised Feb 2020.
    2. Geert Dhaene & Koen Jochmans, 2014. "Split-Panel Jackknife Estimation of Fixed-Effect Models," Sciences Po Economics Publications (main) hal-01070553, HAL.
    3. Mingli Chen & Iv'an Fern'andez-Val & Martin Weidner, 2014. "Nonlinear Factor Models for Network and Panel Data," Papers 1412.5647, arXiv.org, revised Oct 2019.
    4. Ivan Fernandez-Val & Martin Weidner, 2015. "Individual and time effects in nonlinear panel models with large N, T," CeMMAP working papers CWP17/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Haruo Iwakura, 2014. "Deriving the Information Bounds for Nonlinear Panel Data Models with Fixed Effects," KIER Working Papers 886, Kyoto University, Institute of Economic Research.
    6. Ivan Fernandez-Val & Martin Weidner, 2017. "Fixed effect estimation of large T panel data models," CeMMAP working papers 42/17, Institute for Fiscal Studies.
    7. Arthur Lewbel, 2006. "Modeling Heterogeneity," Boston College Working Papers in Economics 650, Boston College Department of Economics.
    8. Hospido, Laura, 2010. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," IZA Discussion Papers 4712, Institute of Labor Economics (IZA).
    9. Martin Weidner & Thomas Zylkin, 2021. "Bias and consistency in three-way gravity models," CeMMAP working papers CWP11/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney K. Newey, 2009. "Identification and estimation of marginal effects in nonlinear panel models," CeMMAP working papers CWP05/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Michael Lechner & Stefan Lollivier & Thierry Magnac, 2005. "Parametric Binary Choice Models," University of St. Gallen Department of Economics working paper series 2005 2005-23, Department of Economics, University of St. Gallen.
    12. Geert Dhaene & Koen Jochmans, 2013. "Likelihood inference in an Autoregression with fixed effects," Sciences Po Economics Discussion Papers hal-01070434, HAL.
    13. Manuel Arellano & Stéphane Bonhomme, 2007. "Robust priors in nonlinear panel data models," CeMMAP working papers CWP07/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Giovanni Forchini & Bin Peng, 2016. "A Conditional Approach to Panel Data Models with Common Shocks," Econometrics, MDPI, vol. 4(1), pages 1-12, January.
    15. St'ephane Bonhomme & Koen Jochmans & Martin Weidner, 2024. "A Neyman-Orthogonalization Approach to the Incidental Parameter Problem," Papers 2412.10304, arXiv.org, revised Jan 2025.
    16. Alvarez, Javier & Arellano, Manuel, 2022. "Robust likelihood estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 226(1), pages 21-61.
    17. Martin Browning & Jesus Carro, 2006. "Heterogeneity and Microeconometrics Modelling," CAM Working Papers 2006-03, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    18. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    19. Fernández-Val, Iván, 2009. "Fixed effects estimation of structural parameters and marginal effects in panel probit models," Journal of Econometrics, Elsevier, vol. 150(1), pages 71-85, May.
    20. Schumann, Martin & Severini, Thomas A. & Tripathi, Gautam, 2021. "Integrated likelihood based inference for nonlinear panel data models with unobserved effects," Journal of Econometrics, Elsevier, vol. 223(1), pages 73-95.
    21. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    22. Fernández-Val, Iván & Vella, Francis, 2011. "Bias corrections for two-step fixed effects panel data estimators," Journal of Econometrics, Elsevier, vol. 163(2), pages 144-162, August.
    23. Hausman, Jerry A. & Woutersen, Tiemen, 2014. "Estimating a semi-parametric duration model without specifying heterogeneity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 114-131.
    24. Iv'an Fern'andez-Val & Martin Weidner, 2017. "Fixed Effect Estimation of Large T Panel Data Models," Papers 1709.08980, arXiv.org, revised Mar 2018.
    25. Jinyong Hahn & Whitney K. Newey, 2003. "Jackknife and analytical bias reduction for nonlinear panel models," CeMMAP working papers CWP17/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Hahn, Jinyong, 2004. "Does Jeffrey's prior alleviate the incidental parameter problem?," Economics Letters, Elsevier, vol. 82(1), pages 135-138, January.
    27. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    28. Kyoo il Kim, 2006. "Higher Order Bias Correcting Moment Equation for M-Estimation and its Higher Order Efficiency," Labor Economics Working Papers 22453, East Asian Bureau of Economic Research.
    29. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    30. Pakel, Cavit, 2019. "Bias reduction in nonlinear and dynamic panels in the presence of cross-section dependence," Journal of Econometrics, Elsevier, vol. 213(2), pages 459-492.
    31. Amaresh Tiwari & Franz Palm, 2011. "Nonlinear Panel Data Models with Expected a Posteriori Values of Correlated Random Effects," CREPP Working Papers 1113, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.

  12. Tiemen Woutersen & Marcel Voia, 2002. "Adaptive Estimation of the Dynamic Linear Model with Fixed Effects," University of Western Ontario, Departmental Research Report Series 200210, University of Western Ontario, Department of Economics.

    Cited by:

    1. Geert Dhaene & Koen Jochmans, 2013. "Likelihood inference in an Autoregression with fixed effects," Working Papers hal-01070434, HAL.

  13. Tiemen Woutersen, 2001. "Robustness Against Incidental Parameters and Mixing Distributions," University of Western Ontario, Departmental Research Report Series 200110, University of Western Ontario, Department of Economics.

    Cited by:

    1. Carro, Jesus M., 2007. "Estimating dynamic panel data discrete choice models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 503-528, October.
    2. Dhaene, Geert & Sun, Yutao, 2021. "Second-order corrected likelihood for nonlinear panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 220(2), pages 227-252.
    3. Manuel Arellano, 2003. "Discrete choices with panel data," Investigaciones Economicas, Fundación SEPI, vol. 27(3), pages 423-458, September.

  14. Geert Ridder & Tiemen Woutersen, 2001. "The Singularity of the Efficiency Bound of the Mixed Proportional Hazard Model," University of Western Ontario, Departmental Research Report Series 20019, University of Western Ontario, Department of Economics.

    Cited by:

    1. G.E. Bijwaard, 2002. "Instrumental Variable Estimation for Duration Data: A Reappraisal of the Illinois Reemployment Bonus Experiment," Econometrics 0204001, University Library of Munich, Germany.
    2. Govert Bijwaard & Geert Ridder & Tiemen Woutersen, 2012. "A Simple GMM Estimator for the Semiparametric Mixed Proportional Hazard Model," Norface Discussion Paper Series 2012035, Norface Research Programme on Migration, Department of Economics, University College London.
    3. Govert Bijwaard, 2012. "Unobserved Heterogeneity in Multiple-Spell Multiple-States Duration Models," Norface Discussion Paper Series 2012033, Norface Research Programme on Migration, Department of Economics, University College London.
    4. Bijwaard, G.E., 2002. "Instrumental variable estimation for duration data," Econometric Institute Research Papers EI 2002-39, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Govert Ewout Bijwaard, 2014. "Multistate event history analysis with frailty," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(58), pages 1591-1620.

  15. Tiemen Woutersen, 2000. "Estimators for Panel Duration Data with Endogenous Censoring and Endogenous Regressors," Econometric Society World Congress 2000 Contributed Papers 1581, Econometric Society.

    Cited by:

    1. Horowitz, Joel L. & Lee, Sokbae, 2004. "Semiparametric estimation of a panel data proportional hazards model with fixed effects," Journal of Econometrics, Elsevier, vol. 119(1), pages 155-198, March.
    2. Govert Bijwaard & Geert Ridder & Tiemen Woutersen, 2012. "A Simple GMM Estimator for the Semiparametric Mixed Proportional Hazard Model," Norface Discussion Paper Series 2012035, Norface Research Programme on Migration, Department of Economics, University College London.
    3. Van den Berg, Gerard J., 2000. "Duration Models: Specification, Identification, and Multiple Durations," MPRA Paper 9446, University Library of Munich, Germany.
    4. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    5. Hausman, Jerry A. & Woutersen, Tiemen, 2014. "Estimating a semi-parametric duration model without specifying heterogeneity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 114-131.
    6. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.

Articles

  1. Chao, John C. & Swanson, Norman R. & Woutersen, Tiemen, 2023. "Jackknife estimation of a cluster-sample IV regression model with many weak instruments," Journal of Econometrics, Elsevier, vol. 235(2), pages 1747-1769.

    Cited by:

    1. Xiduo Chen & Xingdong Feng & Antonio F. Galvao & Yeheng Ge, 2025. "Treatment Effects Inference with High-Dimensional Instruments and Control Variables," Papers 2503.20149, arXiv.org, revised Oct 2025.
    2. Johannes W. Ligtenberg & Tiemen Woutersen, 2024. "Multidimensional clustering in judge designs," Papers 2406.09473, arXiv.org.
    3. Liyu Dou & Pengjin Min & Wenjie Wang & Yichong Zhang, 2025. "An Improved Inference for IV Regressions," Papers 2506.23816, arXiv.org, revised Feb 2026.
    4. Lim, Dennis & Wang, Wenjie & Zhang, Yichong, 2024. "A conditional linear combination test with many weak instruments," Journal of Econometrics, Elsevier, vol. 238(2).
    5. Qu Feng & Sombut Jaidee & Wenjie Wang, 2025. "Robust Inference with High-Dimensional Instruments," Papers 2506.23834, arXiv.org.
    6. Tom Boot & Didier Nibbering, 2024. "Inference on LATEs with covariates," Papers 2402.12607, arXiv.org, revised Nov 2024.
    7. Anna Mikusheva & Liyang Sun, 2023. "Weak Identification with Many Instruments," Papers 2308.09535, arXiv.org, revised Jan 2024.

  2. Woutersen, Tiemen & Hausman, Jerry A., 2019. "Increasing the power of specification tests," Journal of Econometrics, Elsevier, vol. 211(1), pages 166-175.
    See citations under working paper version above.
  3. Hu, Yingyao & Shiu, Ji-Liang & Woutersen, Tiemen, 2016. "Identification in nonseparable models with measurement errors and endogeneity," Economics Letters, Elsevier, vol. 144(C), pages 33-36.

    Cited by:

    1. Nguimkeu, Pierre & Denteh, Augustine & Tchernis, Rusty, 2019. "On the estimation of treatment effects with endogenous misreporting," Journal of Econometrics, Elsevier, vol. 208(2), pages 487-506.
    2. Bollinger, Christopher R. & van Hasselt, Martijn, 2017. "Bayesian moment-based inference in a regression model with misclassification error," Journal of Econometrics, Elsevier, vol. 200(2), pages 282-294.

  4. Yingyao Hu & Ji‐Liang Shiu & Tiemen Woutersen, 2015. "Identification and estimation of single‐index models with measurement error and endogeneity," Econometrics Journal, Royal Economic Society, vol. 18(3), pages 347-362, October.

    Cited by:

    1. Nguimkeu, Pierre & Denteh, Augustine & Tchernis, Rusty, 2019. "On the estimation of treatment effects with endogenous misreporting," Journal of Econometrics, Elsevier, vol. 208(2), pages 487-506.
    2. Francis J. DiTraglia & Camilo Garcia-Jimeno, 2020. "Identifying the effect of a mis-classified, binary, endogenous regressor," Papers 2011.07272, arXiv.org.
    3. Hiroyuki Kasahara & Katsumi Shimotsu, 2019. "Identification of Regression Models with a Misclassified and Endogenous Binary Regressor," Papers 1904.11143, arXiv.org, revised Aug 2021.
    4. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Second Version," PIER Working Paper Archive 15-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 11 Nov 2015.
    5. Bollinger, Christopher R. & van Hasselt, Martijn, 2017. "Bayesian moment-based inference in a regression model with misclassification error," Journal of Econometrics, Elsevier, vol. 200(2), pages 282-294.
    6. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Third Version," PIER Working Paper Archive 15-040, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 24 Nov 2015.
    7. DiTraglia, Francis J. & García-Jimeno, Camilo, 2019. "Identifying the effect of a mis-classified, binary, endogenous regressor," Journal of Econometrics, Elsevier, vol. 209(2), pages 376-390.
    8. Denni Tommasi & Arthur Lewbel & Rossella Calvi, 2017. "LATE with Mismeasured or Misspecified Treatment: An application to Women's Empowerment in India," Working Papers ECARES ECARES 2017-27, ULB -- Universite Libre de Bruxelles.
    9. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.

  5. Chao, John C. & Hausman, Jerry A. & Newey, Whitney K. & Swanson, Norman R. & Woutersen, Tiemen, 2014. "Testing overidentifying restrictions with many instruments and heteroskedasticity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 15-21.
    See citations under working paper version above.
  6. Jerry Hausman & Tiemen Woutersen, 2014. "Estimating the Derivative Function and Counterfactuals in Duration Models with Heterogeneity," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 472-496, August.

    Cited by:

    1. Lo Simon M.S. & Stephan Gesine & Wilke Ralf A., 2017. "Competing Risks Copula Models for Unemployment Duration: An Application to a German Hartz Reform," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-20, January.
    2. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    3. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.

  7. Hausman, Jerry A. & Woutersen, Tiemen, 2014. "Estimating a semi-parametric duration model without specifying heterogeneity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 114-131.
    See citations under working paper version above.
  8. Bijwaard Govert E. & Ridder Geert & Woutersen Tiemen, 2013. "A Simple GMM Estimator for the Semiparametric Mixed Proportional Hazard Model," Journal of Econometric Methods, De Gruyter, vol. 2(1), pages 1-23, July.
    See citations under working paper version above.
  9. Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen & John C. Chao & Norman R. Swanson, 2012. "Instrumental variable estimation with heteroskedasticity and many instruments," Quantitative Economics, Econometric Society, vol. 3(2), pages 211-255, July.
    See citations under working paper version above.
  10. Chao, John C. & Swanson, Norman R. & Hausman, Jerry A. & Newey, Whitney K. & Woutersen, Tiemen, 2012. "Asymptotic Distribution Of Jive In A Heteroskedastic Iv Regression With Many Instruments," Econometric Theory, Cambridge University Press, vol. 28(1), pages 42-86, February.
    See citations under working paper version above.
  11. Geert Ridder & Tiemen M. Woutersen, 2003. "The Singularity of the Information Matrix of the Mixed Proportional Hazard Model," Econometrica, Econometric Society, vol. 71(5), pages 1579-1589, September.
    See citations under working paper version above.

Chapters

  1. John C. Chao & Jerry A. Hausman & Whitney K. Newey & Norman R. Swanson & Tiemen Woutersen, 2012. "An Expository Note on the Existence of Moments of Fuller and HFUL Estimators," Advances in Econometrics, in: Essays in Honor of Jerry Hausman, pages 87-106, Emerald Group Publishing Limited.
    See citations under working paper version above.
  2. Tiemen Woutersen, 2011. "Consistent Estimation and Orthogonality," Advances in Econometrics, in: Missing Data Methods: Cross-sectional Methods and Applications, pages 155-178, Emerald Group Publishing Limited.

    Cited by:

    1. Moins, Théo & Arbel, Julyan & Girard, Stéphane & Dutfoy, Anne, 2023. "Reparameterization of extreme value framework for improved Bayesian workflow," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).

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