Estimation and Inference with Weak, Semi-strong, and Strong Identification

Citations

Cited by:

1. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
   • Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
   • Christoph Breunig & Enno Mammen & Anna Simoni, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Post-Print hal-03089879, HAL.
2. Isaiah Andrews & Anna Mikusheva, 2016. "Conditional Inference With a Functional Nuisance Parameter," Econometrica, Econometric Society, vol. 84, pages 1571-1612, July.
3. Andrews, Donald W.K. & Cheng, Xu, 2013. "Maximum likelihood estimation and uniform inference with sporadic identification failure," Journal of Econometrics, Elsevier, vol. 173(1), pages 36-56.
   • Donald W. K. Andrews & Xu Cheng, 2011. "Maximum Likelihood Estimation and Uniform Inference with Sporadic Identification Failure," Cowles Foundation Discussion Papers 1824, Cowles Foundation for Research in Economics, Yale University.
   • Donald W. K. Andrews & Xu Cheng, 2011. "Maximum Likelihood Estimation and Uniform Inference with Sporadic Identification Failure," Cowles Foundation Discussion Papers 1824R, Cowles Foundation for Research in Economics, Yale University, revised Oct 2012.
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. Lily Y. Liu, 2017. "Estimating Loss Given Default from CDS under Weak Identification," Supervisory Research and Analysis Working Papers RPA 17-1, Federal Reserve Bank of Boston.
6. Alexis Akira Toda & Kieran James Walsh, 2017. "Fat tails and spurious estimation of consumption‐based asset pricing models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1156-1177, September.
   • Toda, Alexis Akira & Walsh, Kieran James, 2016. "Fat Tails and Spurious Estimation of Consumption-Based Asset Pricing Models," MPRA Paper 78980, University Library of Munich, Germany.
   • Toda, Alexis Akira & Walsh, Kieran James, 2017. "Fat tails and spurious estimation of consumption-based asset pricing models," University of California at San Diego, Economics Working Paper Series qt8df3x7gw, Department of Economics, UC San Diego.
7. Peter C.B. Phillips & Igor Kheifets, 2021. "On Multicointegration," Cowles Foundation Discussion Papers 2306, Cowles Foundation for Research in Economics, Yale University.
8. Stephen L. Ross & Zhentao Shi, 2022. "Measuring Social Interaction Effects When Instruments Are Weak," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 995-1006, June.
   • Stephen L. Ross & Zhentao Shi, 2016. "Measuring Social Interaction Effects when Instruments are Weak," Working Papers 2016-033, Human Capital and Economic Opportunity Working Group.
   • Stephen L. Ross & Zhentao Shi, 2016. "Measuring Social Interaction Effects when Instruments are Weak," Working papers 2016-37, University of Connecticut, Department of Economics.
9. Hiroaki Kaido & Francesca Molinari & Jörg Stoye, 2019. "Confidence Intervals for Projections of Partially Identified Parameters," Econometrica, Econometric Society, vol. 87(4), pages 1397-1432, July.
   • Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confidence Intervals for Projections of Partially Identified Parameters," Papers 1601.00934, arXiv.org, revised Jun 2019.
   • 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.
   • Stoye, Joerg & Kaido, Hiroaki & Molinari, Francesca, 2016. "Confidence Intervals for Projections of Partially Identified Parameters," VfS Annual Conference 2016 (Augsburg): Demographic Change 145485, Verein für Socialpolitik / German Economic Association.
   • Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2017. "Confidence intervals for projections of partially identified parameters," CeMMAP working papers 49/17, Institute for Fiscal Studies.
   • Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2019. "Confi dence Intervals for Projections of Partially Identifi ed Parameters," CeMMAP working papers CWP26/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
   • Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confidence intervals for projections of partially identified parameters," CeMMAP working papers CWP02/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
   • Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2017. "Confidence intervals for projections of partially identified parameters," CeMMAP working papers CWP49/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
   • Hiroaki Kaido & Francesca Molinari & Jörg Stoye, 2016. "Confidence intervals for projections of partially identified parameters," CeMMAP working papers 02/16, Institute for Fiscal Studies.
10. 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.
11. Dovonon, Prosper & Renault, Eric, 2011. "Testing for Common GARCH Factors," MPRA Paper 40224, University Library of Munich, Germany.
    • Prosper Dovonon & Eric Renault, 2012. "Testing for Common GARCH Factors," CIRANO Working Papers 2012s-34, CIRANO.
12. Tetsuya Kaji, 2019. "Theory of Weak Identification in Semiparametric Models," Papers 1908.10478, arXiv.org, revised Aug 2020.
13. Bertille Antoine & Pascal Lavergne, 2020. "Identification-Robust Nonparametric Interference in a Linear IV Model," Discussion Papers dp20-03, Department of Economics, Simon Fraser University.
14. Kleibergen, Frank, 2021. "Efficient size correct subset inference in homoskedastic linear instrumental variables regression," Journal of Econometrics, Elsevier, vol. 221(1), pages 78-96.
15. Brandts, Jordi & El Baroudi, Sabrine & Huber, Stefanie J. & Rott, Christina, 2021. "Gender differences in private and public goal setting," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 222-247.
    • Jordi Brandts & Sabrine El Baroudi & Stefanie J. Huber & Cristina Rott, 2021. "Gender Differences in Private and Public Goal Setting," Working Papers 1231, Barcelona School of Economics.
    • Jordi Brandts & Sabrine El Baroudi & Stefanie Huber & Christina Rott, 2022. "Gender Differences in Private and Public Goal Setting," Tinbergen Institute Discussion Papers 22-008/II, Tinbergen Institute.
16. Tiemen M. Woutersen & John Ham, 2013. "Calculating confidence intervals for continuous and discontinuous functions of parameters," CeMMAP working papers CWP23/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • 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.
17. Sukjin Han, 2020. "Nonparametric estimation of triangular simultaneous equations models under weak identification," Quantitative Economics, Econometric Society, vol. 11(1), pages 161-202, January.
    • Sukjin Han, 2012. "Nonparametric Estimation of Triangular Simultaneous Equations Models under Weak Identification," Department of Economics Working Papers 140414, The University of Texas at Austin, Department of Economics, revised Apr 2014.
18. Lee, Adam & Mesters, Geert, 2024. "Locally robust inference for non-Gaussian linear simultaneous equations models," Journal of Econometrics, Elsevier, vol. 240(1).
    • Adam Lee & Geert Mesters, 2021. "Locally Robust Inference for Non-Gaussian Linear Simultaneous Equations Models," Working Papers 1278, Barcelona School of Economics.
19. Antoine, Bertille & Lavergne, Pascal, 2023. "Identification-robust nonparametric inference in a linear IV model," Journal of Econometrics, Elsevier, vol. 235(1), pages 1-24.
    • Bertille Antoine & Pascal Lavergne, 2019. "Identification-Robust Nonparametric Inference in a Linear IV Model," Discussion Papers dp19-02, Department of Economics, Simon Fraser University.
    • Antoine Bertille & Pascal Lavergne, 2023. "Identification-Robust Nonparametric Inference in a Linear IV Model," Post-Print hal-04141433, HAL.
    • Bertille Antoine & Pascal Lavergne, 2021. "Identifcation-Robust Nonparametric Inference in a Linear IV Model," Discussion Papers dp21-12, Department of Economics, Simon Fraser University.
    • Antoine, Bertille & Lavergne, Pascal, 2019. "Identification-Robust Nonparametric Inference in a Linear IV Model," TSE Working Papers 19-1004, Toulouse School of Economics (TSE), revised May 2021.
20. 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.
21. Komunjer, Ivana & Zhu, Yinchu, 2020. "Likelihood ratio testing in linear state space models: An application to dynamic stochastic general equilibrium models," Journal of Econometrics, Elsevier, vol. 218(2), pages 561-586.
22. Angelini, Giovanni & Cavaliere, Giuseppe & Fanelli, Luca, 2024. "An identification and testing strategy for proxy-SVARs with weak proxies," Journal of Econometrics, Elsevier, vol. 238(2).
    • Giovanni Angelini & Giuseppe Cavaliere & Luca Fanelli, 2022. "An identification and testing strategy for proxy-SVARs with weak proxies," Papers 2210.04523, arXiv.org, revised Oct 2023.
23. McCloskey, Adam, 2017. "Bonferroni-based size-correction for nonstandard testing problems," Journal of Econometrics, Elsevier, vol. 200(1), pages 17-35.
    • Adam McCloskey, 2012. "Bonferroni-Based Size-Correction for Nonstandard Testing Problems," Working Papers 2012-16, Brown University, Department of Economics.
24. Martínez-Iriarte, Julián & Sun, Yixiao & Wang, Xuexin, 2020. "Asymptotic F tests under possibly weak identification," Journal of Econometrics, Elsevier, vol. 218(1), pages 140-177.
    • Julian Martinez-Iriarte & Yixiao Sun & Xuexin Wang, 2019. "Asymptotic F Tests under Possibly Weak Identification," Working Papers 2019-03-12, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    • Martínez-Iriarte, Julián & Sun, Yixiao & Wang, Xuexin, 2019. "Asymptotic F Tests under Possibly Weak Identification," University of California at San Diego, Economics Working Paper Series qt6qk200q8, Department of Economics, UC San Diego.
25. Freyaldenhoven, Simon, 2022. "Factor models with local factors — Determining the number of relevant factors," Journal of Econometrics, Elsevier, vol. 229(1), pages 80-102.
    • Simon Freyaldenhoven, 2021. "Factor Models with Local Factors—Determining the Number of Relevant Factors," Working Papers 21-15, Federal Reserve Bank of Philadelphia.
26. Denni Tommasi & Alexander Wolf, 2016. "Overcoming Weak Identification in the Estimation of Household Resource Shares," Working Papers ECARES ECARES 2016-12, ULB -- Universite Libre de Bruxelles.
27. Joachim Freyberger, 2012. "Asymptotic theory for differentiated products demand models with many markets," CeMMAP working papers 19/12, Institute for Fiscal Studies.
28. Antoine, Bertille & Renault, Eric, 2024. "GMM with Nearly-Weak Identification," Econometrics and Statistics, Elsevier, vol. 30(C), pages 36-59.
29. Wang, Wenjie & Zhang, Yichong, 2024. "Wild bootstrap inference for instrumental variables regressions with weak and few clusters," Journal of Econometrics, Elsevier, vol. 241(1).
30. Li, Jia & Phillips, Peter C. B. & Shi, Shuping & Yu, Jun, 2022. "Weak Identification of Long Memory with Implications for Inference," Economics and Statistics Working Papers 8-2022, Singapore Management University, School of Economics.
    • Jia Li & Peter C. B. Phillips & Shuping Shi & Jun Yu, 2022. "Weak Identification of Long Memory with Implications for Inference," Cowles Foundation Discussion Papers 2334, Cowles Foundation for Research in Economics, Yale University.
31. Chevillon, Guillaume & Mavroeidis, Sophocles & Zhan, Zhaoguo, 2016. "Robust inference in structural VARs with long-run restrictions," ESSEC Working Papers WP1702, ESSEC Research Center, ESSEC Business School.
32. Chen, Xiaohong & Ponomareva, Maria & Tamer, Elie, 2014. "Likelihood inference in some finite mixture models," Journal of Econometrics, Elsevier, vol. 182(1), pages 87-99.
    • Xiaohong Chen & Maria Ponomareva & Elie Tamer, 2013. "Likelihood Inference in Some Finite Mixture Models," Cowles Foundation Discussion Papers 1895, Cowles Foundation for Research in Economics, Yale University.
    • Xiaohong Chen & Maria Ponomareva & Elie Tamer, 2013. "Likelihood inference in some finite mixture models," CeMMAP working papers 19/13, Institute for Fiscal Studies.
    • Xiaohong Chen & Maria Ponomareva & Elie Tamer, 2013. "Likelihood inference in some finite mixture models," CeMMAP working papers CWP19/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
33. Ke-Li Xu & Jui-Chung Yang, 2015. "Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non-stationary Volatility," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 63-86, March.
34. Jinyuan Chang & Zhentao Shi & Jia Zhang, 2021. "Culling the herd of moments with penalized empirical likelihood," Papers 2108.03382, arXiv.org, revised May 2022.
35. Andrews, Donald W.K. & Cheng, Xu, 2014. "Gmm Estimation And Uniform Subvector Inference With Possible Identification Failure," Econometric Theory, Cambridge University Press, vol. 30(2), pages 287-333, April.
    • Donald W.K. Andrews & Xu Cheng, 2011. "GMM Estimation and Uniform Subvector Inference with Possible Identification Failure," Cowles Foundation Discussion Papers 1828, Cowles Foundation for Research in Economics, Yale University, revised Jan 2013.
    • Donald W.K. Andrews & Xu Cheng, 2011. "GMM Estimation and Uniform Subvector Inference with Possible Identification Failure," Cowles Foundation Discussion Papers 1828, Cowles Foundation for Research in Economics, Yale University.
36. Patrick Kline & Raffaele Saggio & Mikkel Sølvsten, 2020. "Leave‐Out Estimation of Variance Components," Econometrica, Econometric Society, vol. 88(5), pages 1859-1898, September.
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    • Patrick Kline & Raffaele Saggio & Mikkel Sølvsten, 2019. "Leave-out Estimation of Variance Components," NBER Working Papers 26244, National Bureau of Economic Research, Inc.
37. Andrews, Donald W.K. & Cheng, Xu & Guggenberger, Patrik, 2020. "Generic results for establishing the asymptotic size of confidence sets and tests," Journal of Econometrics, Elsevier, vol. 218(2), pages 496-531.
    • Donald W.K. Andrews & Xu Cheng & Patrik Guggenberger, 2011. "Generic Results for Establishing the Asymptotic Size of Confidence Sets and Tests," Cowles Foundation Discussion Papers 1813, Cowles Foundation for Research in Economics, Yale University.
38. Andrea Fracasso & Giuseppe Vittucci Marzetti, 2014. "International R&D Spillovers, Absorptive Capacity and Relative Backwardness: A Panel Smooth Transition Regression Model," International Economic Journal, Taylor & Francis Journals, vol. 28(1), pages 137-160, March.
    • Andrea Fracasso & Giuseppe Vittucci Marzetti, 2012. "International R&D spillovers, absorptive capacity and relative backwardness: a panel smooth transition regression model," Department of Economics Working Papers 1203, Department of Economics, University of Trento, Italia.
39. Joachim Freyberger, 2012. "Asymptotic theory for differentiated products demand models with many markets," CeMMAP working papers CWP19/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
40. Jean-Jacques Forneron, 2019. "Detecting Identification Failure in Moment Condition Models," Papers 1907.13093, arXiv.org, revised Oct 2023.
41. Ketz, Philipp, 2019. "Testing overidentifying restrictions with a restricted parameter space," Economics Letters, Elsevier, vol. 185(C).
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42. Khan, Shakeeb & Nekipelov, Denis, 2024. "On uniform inference in nonlinear models with endogeneity," Journal of Econometrics, Elsevier, vol. 240(2).
43. Simon Freyaldenhoven, 2017. "A Generalized Factor Model with Local Factors," 2017 Papers pfr361, Job Market Papers.
    • Simon Freyaldenhoven, 2019. "A Generalized Factor Model with Local Factors," Working Papers 19-23, Federal Reserve Bank of Philadelphia.
44. Yicong Lin & Hanno Reuvers, 2020. "Cointegrating Polynomial Regressions with Power Law Trends: Environmental Kuznets Curve or Omitted Time Effects?," Papers 2009.02262, arXiv.org, revised Dec 2021.
    • Yicong Lin & Hanno Reuvers, 2022. "Cointegrating Polynomial Regressions With Power Law Trends: Environmental Kuznets Curve or Omitted Time Effects?," Tinbergen Institute Discussion Papers 22-092/III, Tinbergen Institute.
45. Xu Cheng & Winston Wei Dou & Zhipeng Liao, 2022. "Macro‐Finance Decoupling: Robust Evaluations of Macro Asset Pricing Models," Econometrica, Econometric Society, vol. 90(2), pages 685-713, March.
    • Xu Cheng & Winston Wei Dou & Zhipeng Liao, 2020. "Macro-Finance Decoupling: Robust Evaluations of Macro Asset Pricing Models," PIER Working Paper Archive 20-019, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
46. Joel L. Horowitz, 2017. "Non-asymptotic inference in instrumental variables estimation," CeMMAP working papers CWP46/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
47. Jules Tinang & Nour Meddahi, 2016. "GMM estimation of the Long Run Risks model," 2016 Meeting Papers 1107, Society for Economic Dynamics.
48. Artūras Juodis, 2018. "Rank based cointegration testing for dynamic panels with fixed T," Empirical Economics, Springer, vol. 55(2), pages 349-389, September.
49. Corradi, Valentina & Silvapulle, Mervyn J. & Swanson, Norman R., 2018. "Testing for jumps and jump intensity path dependence," Journal of Econometrics, Elsevier, vol. 204(2), pages 248-267.
50. Philip Kostov & Julie Le Gallo, 2018. "What role for human capital in the growth process: new evidence from endogenous latent factor panel quantile regressions," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(5), pages 501-527, November.
51. Gregory Cox, 2018. "Almost Sure Uniqueness of a Global Minimum Without Convexity," Papers 1803.02415, arXiv.org, revised Feb 2019.
52. Gregory Cox, 2022. "Weak Identification in Low-Dimensional Factor Models with One or Two Factors," Papers 2211.00329, arXiv.org, revised Mar 2024.
53. Xu, Ke-Li, 2020. "Inference of local regression in the presence of nuisance parameters," Journal of Econometrics, Elsevier, vol. 218(2), pages 532-560.
54. David H. Bernstein & Bent Nielsen, 2019. "Asymptotic Theory for Cointegration Analysis When the Cointegration Rank Is Deficient," Econometrics, MDPI, vol. 7(1), pages 1-24, January.
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55. Mingmian Cheng & Norman R. Swanson, 2019. "Fixed and Long Time Span Jump Tests: New Monte Carlo and Empirical Evidence," Econometrics, MDPI, vol. 7(1), pages 1-32, March.
56. Hu, Zhishui & Phillips, Peter C.B. & Wang, Qiying, 2021. "Nonlinear Cointegrating Power Function Regression With Endogeneity," Econometric Theory, Cambridge University Press, vol. 37(6), pages 1173-1213, December.
    • Zhishui Hu & Peter C.B. Phillips & Qiying Wang, 2019. "Nonlinear Cointegrating Power Function Regression with Endogeneity," Cowles Foundation Discussion Papers 2211, Cowles Foundation for Research in Economics, Yale University.
57. Ketz, Philipp, 2019. "On asymptotic size distortions in the random coefficients logit model," Journal of Econometrics, Elsevier, vol. 212(2), pages 413-432.
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58. Shakeeb Khan & Denis Nekipelov, 2013. "On Uniform Inference in Nonlinear Models with Endogeneity," Working Papers 13-16, Duke University, Department of Economics.
    • Shakeeb Khan & Denis Nekipelov, 2019. "On Uniform Inference in Nonlinear Models with Endogeneity," Boston College Working Papers in Economics 986, Boston College Department of Economics.
59. Xu Cheng & Zhipeng Liao & Ruoyao Shi, 2013. "Uniform Asymptotic Risk of Averaging GMM Estimator Robust to Misspecification, Second Version," PIER Working Paper Archive 15-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 Mar 2015.
60. Antoine, Bertille & Renault, Eric, 2020. "Testing identification strength," Journal of Econometrics, Elsevier, vol. 218(2), pages 271-293.
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61. Chen, Heng & Fan, Yanqin & Liu, Ruixuan, 2016. "Inference for the correlation coefficient between potential outcomes in the Gaussian switching regime model," Journal of Econometrics, Elsevier, vol. 195(2), pages 255-270.
62. Lukas Hoesch & Adam Lee & Geert Mesters, 2022. "Robust inference for non-Gaussian SVAR models," Economics Working Papers 1847, Department of Economics and Business, Universitat Pompeu Fabra.
63. Donald W. K. Andrews & Patrik Guggenberger, 2015. "Identification- and Singularity-Robust Inference for Moment Condition," Cowles Foundation Discussion Papers 1978, Cowles Foundation for Research in Economics, Yale University.
    • Donald W. K. Andrews & Patrik Guggenberger, 2015. "Identification- and Singularity-Robust Inference for Moment Condition," Cowles Foundation Discussion Papers 1978R2, Cowles Foundation for Research in Economics, Yale University, revised Jan 2019.
    • Donald W. K. Andrews & Patrik Guggenberger, 2015. "Identification- and Singularity-Robust Inference for Moment Condition," Cowles Foundation Discussion Papers 1978R, Cowles Foundation for Research in Economics, Yale University, revised Oct 2018.
64. Phillips, Peter C.B. & Kheifets, Igor L., 2024. "High-dimensional IV cointegration estimation and inference," Journal of Econometrics, Elsevier, vol. 238(2).
65. Xu Cheng, 2014. "Uniform Inference in Nonlinear Models with Mixed Identification Strength," PIER Working Paper Archive 14-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
66. Lukas Hoesch & Adam Lee & Geert Mesters, 2022. "Locally Robust Inference for Non-Gaussian SVAR Models," Working Papers 1367, Barcelona School of Economics.
67. Lynda Khalaf & Beatriz Peraza López, 2020. "Simultaneous Indirect Inference, Impulse Responses and ARMA Models," Econometrics, MDPI, vol. 8(2), pages 1-26, April.
68. Antoine, Bertille & Lavergne, Pascal, 2014. "Conditional moment models under semi-strong identification," Journal of Econometrics, Elsevier, vol. 182(1), pages 59-69.
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69. Anna Mikusheva, 2014. "Estimation of dynamic stochastic general equilibrium models (in Russian)," Quantile, Quantile, issue 12, pages 1-21, February.
70. Bertille Antoine & Otilia, 2015. "Inference in linear models with structural changes and mixed identification strength," Discussion Papers dp15-05, Department of Economics, Simon Fraser University.
71. D’Amour, Alexander & Ding, Peng & Feller, Avi & Lei, Lihua & Sekhon, Jasjeet, 2021. "Overlap in observational studies with high-dimensional covariates," Journal of Econometrics, Elsevier, vol. 221(2), pages 644-654.
72. Joel L. Horowitz, 2017. "Non-asymptotic inference in instrumental variables estimation," CeMMAP working papers 46/17, Institute for Fiscal Studies.
73. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
74. Ketz, Philipp, 2018. "Subvector inference when the true parameter vector may be near or at the boundary," Journal of Econometrics, Elsevier, vol. 207(2), pages 285-306.
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75. Cheng, Xu, 2015. "Robust inference in nonlinear models with mixed identification strength," Journal of Econometrics, Elsevier, vol. 189(1), pages 207-228.
76. Joel L. Horowitz, 2018. "Non-Asymptotic Inference in Instrumental Variables Estimation," Papers 1809.03600, arXiv.org.
77. Horowitz, Joel L., 2021. "Bounding the difference between true and nominal rejection probabilities in tests of hypotheses about instrumental variables models," Journal of Econometrics, Elsevier, vol. 222(2), pages 1057-1082.
78. Gregory Cox, 2022. "A Generalized Argmax Theorem with Applications," Papers 2209.08793, arXiv.org.
79. Prosper Dovonon & Firmin Doko Tchatoka & Michael Aguessy, 2019. "Relevant moment selection under mixed identification strength," School of Economics and Public Policy Working Papers 2019-04, University of Adelaide, School of Economics and Public Policy.
80. Jui-Chung Yang & Ke-Li Xu, 2013. "Estimation and Inference under Weak Identi cation and Persistence: An Application on Forecast-Based Monetary Policy Reaction Function," 2013 Papers pya307, Job Market Papers.
81. Khalaf, Lynda & Kichian, Maral & Saunders, Charles J. & Voia, Marcel, 2021. "Dynamic panels with MIDAS covariates: Nonlinearity, estimation and fit," Journal of Econometrics, Elsevier, vol. 220(2), pages 589-605.
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82. Lee, Nayoung & Moon, Hyungsik Roger & Zhou, Qiankun, 2017. "Many IVs estimation of dynamic panel regression models with measurement error," Journal of Econometrics, Elsevier, vol. 200(2), pages 251-259.
83. Lim, Dennis & Wang, Wenjie & Zhang, Yichong, 2024. "A conditional linear combination test with many weak instruments," Journal of Econometrics, Elsevier, vol. 238(2).
84. 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.
85. Donald W. K. Andrews & Xu Cheng, 2012. "Estimation and Inference With Weak, Semi‐Strong, and Strong Identification," Econometrica, Econometric Society, vol. 80(5), pages 2153-2211, September.
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86. Philipp Ketz, 2022. "Allowing for weak identification when testing GARCH-X type models," Papers 2210.11398, arXiv.org.
87. Fan, Yanqin & Shi, Xuetao, 2023. "Wald, QLR, and score tests when parameters are subject to linear inequality constraints," Journal of Econometrics, Elsevier, vol. 235(2), pages 2005-2026.
88. Joel L. Horowitz, 2018. "Non-asymptotic inference in instrumental variables estimation," CeMMAP working papers CWP52/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
89. Forneron, Jean-Jacques, 2024. "Detecting identification failure in moment condition models," Journal of Econometrics, Elsevier, vol. 238(1).
90. Isaiah Andrews & Anna Mikusheva, 2016. "Conditional Inference With a Functional Nuisance Parameter," Econometrica, Econometric Society, vol. 84(4), pages 1571-1612, July.
91. Zhongjun Qu, 2011. "Inference and Speci?cation Testing in DSGE Models with Possible Weak Identification," Boston University - Department of Economics - Working Papers Series WP2011-058, Boston University - Department of Economics.
92. Xiaohong Chen & Elie Tamer & Alexander Torgovitsky, 2011. "Sensitivity Analysis in Semiparametric Likelihood Models," Cowles Foundation Discussion Papers 1836, Cowles Foundation for Research in Economics, Yale University.
93. Gregory Cox, 2020. "Weak Identification with Bounds in a Class of Minimum Distance Models," Papers 2012.11222, arXiv.org, revised Dec 2022.
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