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Gautam Tripathi

Personal Details

First Name:Gautam
Middle Name:
Last Name:Tripathi
Suffix:
RePEc Short-ID:ptr18
http://wwwen.uni.lu/fdef/economics_and_management/faculty_members/gautam_tripathi
Terminal Degree:1995 Department of Economics; Northwestern University (from RePEc Genealogy)

Affiliation

Centre de Recherche en Économie Appliquée (CREA)
Faculté de droit, d'économie et de finance
Université du Luxembourg

Luxembourg, Luxembourg
http://wwwen.uni.lu/research/fdef/crea

: (+352) 46 66 44
(+352) 46 66 44 ext 633
162a avenue de la Faïencerie, L-1511 Luxembourg
RePEc:edi:crcrplu (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Tao Chen & Gautam Tripathi, 2014. "A simple consistent test of conditional symmetry in symmetrically trimmed tobit models," CREA Discussion Paper Series 14-04, Center for Research in Economic Analysis, University of Luxembourg.
  2. Thomas A Severini & Gautam Tripathi, 2013. "A survey of semiparametric efficiency bounds for some microeconometric models," CREA Discussion Paper Series 13-10, Center for Research in Economic Analysis, University of Luxembourg.
  3. Tao Chen & Gautam Tripathi, 2011. "Testing Conditional Symmetry Without Smoothing," Working papers 2011-01, University of Connecticut, Department of Economics.
  4. Gautam Tripathi, 2008. "GMM Based Inference with Standard Stratified Samples when the Aggregate Shares are Known," Working papers 2008-31, University of Connecticut, Department of Economics, revised Nov 2009.
  5. Thomas A. Severini & Gautam Tripathi, 2007. "Efficiency Bounds for Estimating Linear Functionals of Nonparametric Regression Models with Endogenous Regressors," Working papers 2007-18, University of Connecticut, Department of Economics.
  6. Gautam Tripathi, 2005. "Moment Based Inference with Stratified Data," Working papers 2005-38, University of Connecticut, Department of Economics, revised Jan 2007.
  7. Thomas A. Severini & Gautam Tripathi, 2005. "Some Identification Issues in Nonparametric Linear Models with Endogenous Regressors," Working papers 2005-12, University of Connecticut, Department of Economics.
  8. Paul J. Devereux & Gautam Tripathi, 2005. "Optimally Combining Censored and Uncensored Datasets," Working papers 2005-10, University of Connecticut, Department of Economics, revised Oct 2007.
  9. Yuichi Kitamura & Gautam Tripathi & Hyungtaik Ahn, 2001. "Empirical Likelihood-Based Inference in Conditional Moment Restriction Models," CIRJE F-Series CIRJE-F-124, CIRJE, Faculty of Economics, University of Tokyo.
  10. Tripathi, Gautam & Kim, Woocheol, 2000. "Nonparametric estimation of homogeneous function," SFB 373 Discussion Papers 2000,85, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  11. Härdle, Wolfgang & Kim, Woocheol & Tripathi, Gautam, 2000. "Nonparametric estimation of additive models with homogeneous components," SFB 373 Discussion Papers 2000,48, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  12. Tripathi, Gautam & Kitamura, Yuichi, 2000. "On testing conditional moment restrictions: The canonical case," SFB 373 Discussion Papers 2000,88, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  13. Tripathi, G., 1997. "Semiparametric Efficiency Bounds Under Shape Restrictions," Working papers 9720, Wisconsin Madison - Social Systems.

Articles

  1. Severini, Thomas A. & Tripathi, Gautam, 2013. "Semiparametric Efficiency Bounds for Microeconometric Models: A Survey," Foundations and Trends(R) in Econometrics, now publishers, vol. 6(3-4), pages 163-397, December.
  2. Severini, Thomas A. & Tripathi, Gautam, 2012. "Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors," Journal of Econometrics, Elsevier, vol. 170(2), pages 491-498.
  3. Tripathi, Gautam, 2011. "Generalized method of moments (GMM) based inference with stratified samples when the aggregate shares are known," Journal of Econometrics, Elsevier, vol. 165(2), pages 258-265.
  4. Tripathi, Gautam, 2011. "Moment-Based Inference With Stratified Data," Econometric Theory, Cambridge University Press, vol. 27(01), pages 47-73, February.
  5. Devereux, Paul J. & Tripathi, Gautam, 2009. "Optimally combining censored and uncensored datasets," Journal of Econometrics, Elsevier, vol. 151(1), pages 17-32, July.
  6. Severini, Thomas A. & Tripathi, Gautam, 2006. "Some Identification Issues In Nonparametric Linear Models With Endogenous Regressors," Econometric Theory, Cambridge University Press, vol. 22(02), pages 258-278, April.
  7. Yuichi Kitamura & Gautam Tripathi & Hyungtaik Ahn, 2004. "Empirical Likelihood-Based Inference in Conditional Moment Restriction Models," Econometrica, Econometric Society, vol. 72(6), pages 1667-1714, November.
  8. Tripathi, Gautam & Kim, Woocheol, 2003. "Nonparametric Estimation Of Homogeneous Functions," Econometric Theory, Cambridge University Press, vol. 19(04), pages 640-663, August.
  9. Severini, Thomas A. & Tripathi, Gautam, 2001. "A simplified approach to computing efficiency bounds in semiparametric models," Journal of Econometrics, Elsevier, vol. 102(1), pages 23-66, May.
  10. Tripathi, Gautam, 2000. "Econometric Methods," Econometric Theory, Cambridge University Press, vol. 16(01), pages 139-142, February.
  11. Tripathi, Gautam, 2000. "Local Semiparametric Efficiency Bounds Under Shape Restrictions," Econometric Theory, Cambridge University Press, vol. 16(05), pages 729-739, October.
  12. Tripathi, Gautam, 1999. "A matrix extension of the Cauchy-Schwarz inequality," Economics Letters, Elsevier, vol. 63(1), pages 1-3, April.

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. Thomas A Severini & Gautam Tripathi, 2013. "A survey of semiparametric efficiency bounds for some microeconometric models," CREA Discussion Paper Series 13-10, Center for Research in Economic Analysis, University of Luxembourg.

    Cited by:

    1. Chen, Tao & Parker, Thomas, 2014. "Semiparametric efficiency for partially linear single-index regression models," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 376-386.

  2. Tao Chen & Gautam Tripathi, 2011. "Testing Conditional Symmetry Without Smoothing," Working papers 2011-01, University of Connecticut, Department of Economics.

    Cited by:

    1. Tao Chen & Gautam Tripathi, 2014. "A simple consistent test of conditional symmetry in symmetrically trimmed tobit models," CREA Discussion Paper Series 14-04, Center for Research in Economic Analysis, University of Luxembourg.
    2. Masayuki Hirukawa & Mari Sakudo, 2016. "Testing Symmetry of Unknown Densities via Smoothing with the Generalized Gamma Kernels," Econometrics, MDPI, Open Access Journal, vol. 4(2), pages 1-27, June.
    3. Chen, Tao & Tripathi, Gautam, 2017. "A simple consistent test of conditional symmetry in symmetrically trimmed tobit models," Journal of Econometrics, Elsevier, vol. 198(1), pages 29-40.

  3. Thomas A. Severini & Gautam Tripathi, 2007. "Efficiency Bounds for Estimating Linear Functionals of Nonparametric Regression Models with Endogenous Regressors," Working papers 2007-18, University of Connecticut, Department of Economics.

    Cited by:

    1. Carolina Caetano & Juan Carlos Escaniano, 2015. "Identifying Multiple Marginal Effects with a Single Binary Instrument or by Regression Discontinuity," Caepr Working Papers 2015-009 Classification-C, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
    2. Michael Jansson & Demian Pouzo, 2017. "Some Large Sample Results for the Method of Regularized Estimators," Papers 1712.07248, arXiv.org.
    3. Claire-Océane Chevallier, 2017. "Empirical Investigation of the Effect of Bank Long Term Debt on Loans and Output in the Euro-zone," CREA Discussion Paper Series 17-04, Center for Research in Economic Analysis, University of Luxembourg.
    4. Santos, Andres, 2011. "Instrumental variable methods for recovering continuous linear functionals," Journal of Econometrics, Elsevier, vol. 161(2), pages 129-146, April.
    5. Juan Carlos Escanciano & Wei Li, 2013. "On the identification of structural linear functionals," CeMMAP working papers CWP48/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Laurent Davezies & Xavier d'Haultfoeuille, 2013. "Endogenous Attrition in Panels," Working Papers 2013-17, Center for Research in Economics and Statistics.
    7. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers CWP06/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  4. Gautam Tripathi, 2005. "Moment Based Inference with Stratified Data," Working papers 2005-38, University of Connecticut, Department of Economics, revised Jan 2007.

    Cited by:

    1. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    2. Kyungchul Song, 2009. "Efficient Estimation of Average Treatment Effects under Treatment-Based Sampling," PIER Working Paper Archive 09-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    3. Bryan S. Graham & Cristine Campos De Xavier Pinto & Daniel Egel, 2012. "Inverse Probability Tilting for Moment Condition Models with Missing Data," Review of Economic Studies, Oxford University Press, vol. 79(3), pages 1053-1079.
    4. Tripathi, Gautam, 2011. "Generalized method of moments (GMM) based inference with stratified samples when the aggregate shares are known," Journal of Econometrics, Elsevier, vol. 165(2), pages 258-265.

  5. Thomas A. Severini & Gautam Tripathi, 2005. "Some Identification Issues in Nonparametric Linear Models with Endogenous Regressors," Working papers 2005-12, University of Connecticut, Department of Economics.

    Cited by:

    1. Yevgeniy Kovchegov & Nese Yildiz, 2014. "Orthogonal Polynomials for Seminonparametric Instrumental Variables Model," Papers 1409.1620, arXiv.org.
    2. Timothy M. Christensen, 2014. "Nonparametric identification of positive eigenfunctions," CeMMAP working papers CWP37/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Andrews, Donald W.K., 2017. "Examples of L2-complete and boundedly-complete distributions," Journal of Econometrics, Elsevier, vol. 199(2), pages 213-220.
    4. Carolina Caetano & Juan Carlos Escaniano, 2015. "Identifying Multiple Marginal Effects with a Single Binary Instrument or by Regression Discontinuity," Caepr Working Papers 2015-009 Classification-C, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
    5. Thomas A. Severini & Gautam Tripathi, 2007. "Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors," CeMMAP working papers CWP13/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Chiappori, Pierre-Andre & Komunjer, Ivana, 2008. "Correct Specification and Identification of Nonparametric Transformation Models," University of California at San Diego, Economics Working Paper Series qt4v12m2rg, Department of Economics, UC San Diego.
    7. Xiaohong Chen & Demian Pouzo, 2012. "Estimation of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals," Econometrica, Econometric Society, vol. 80(1), pages 277-321, January.
    8. Liao, Yuan & Jiang, Wenxin, 2011. "Posterior consistency of nonparametric conditional moment restricted models," MPRA Paper 38700, University Library of Munich, Germany.
    9. Cohen, Michael & Shaw, Philip & Chen, Tao, 2008. "Nonparametric Instrumental Variable Estimation in Practice," Research Reports 149936, University of Connecticut, Food Marketing Policy Center.
    10. Komunjer, Ivana, 2007. "Global Identification In Nonlinear Semiparametric Models," University of California at San Diego, Economics Working Paper Series qt8dk0n386, Department of Economics, UC San Diego.
    11. Steven T. Berry & Philip A. Haile, 2010. "Identification in Differentiated Products Markets Using Market Level Data," NBER Working Papers 15641, National Bureau of Economic Research, Inc.
    12. Chernozhukov, Victor & Imbens, Guido W. & Newey, Whitney K., 2007. "Instrumental variable estimation of nonseparable models," Journal of Econometrics, Elsevier, vol. 139(1), pages 4-14, July.
    13. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2016. "Locally Robust Semiparametric Estimation," Papers 1608.00033, arXiv.org, revised May 2018.
    14. Xiaohong Chen & Demian Pouzo, 2008. "Estimation of nonparametric conditional moment models with possibly nonsmooth moments," CeMMAP working papers CWP12/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Santos, Andres, 2011. "Instrumental variable methods for recovering continuous linear functionals," Journal of Econometrics, Elsevier, vol. 161(2), pages 129-146, April.
    16. Juan Carlos Escanciano & Wei Li, 2013. "On the identification of structural linear functionals," CeMMAP working papers CWP48/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. Xavier d'Haultfoeuille & Philippe Février, 2011. "Identification of Nonseparable Modes with Endogeneity and Discrete Instruments," Working Papers 2011-28, Center for Research in Economics and Statistics.
    18. Laurent Davezies & Xavier d'Haultfoeuille, 2013. "Endogenous Attrition in Panels," Working Papers 2013-17, Center for Research in Economics and Statistics.
    19. Krief, Jerome M., 2017. "Direct instrumental nonparametric estimation of inverse regression functions," Journal of Econometrics, Elsevier, vol. 201(1), pages 95-107.

  6. Paul J. Devereux & Gautam Tripathi, 2005. "Optimally Combining Censored and Uncensored Datasets," Working papers 2005-10, University of Connecticut, Department of Economics, revised Oct 2007.

    Cited by:

    1. Maria K. Humlum & Jannie H.G. Kristoffersen & Rune Vejlin, 2012. "Timing of College Enrollment and Family Formation Decisions," Economics Working Papers 2012-01, Department of Economics and Business Economics, Aarhus University.
    2. Humlum, Maria Knoth & Kristoffersen, Jannie H.G. & Vejlin, Rune, 2017. "College admissions decisions, educational outcomes, and family formation," Labour Economics, Elsevier, vol. 48(C), pages 215-230.
    3. Powdthavee, Nattavudh & Adireksombat, Kampon, 2010. "From Classroom to Wedding Aisle: The Effect of a Nationwide Change in the Compulsory Schooling Law on Age at First Marriage in the UK," IZA Discussion Papers 5019, Institute for the Study of Labor (IZA).
    4. Xiaohong Chen & Han Hong & Denis Nekipelov, 2011. "Nonlinear Models of Measurement Errors," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 901-937, December.

  7. Yuichi Kitamura & Gautam Tripathi & Hyungtaik Ahn, 2001. "Empirical Likelihood-Based Inference in Conditional Moment Restriction Models," CIRJE F-Series CIRJE-F-124, CIRJE, Faculty of Economics, University of Tokyo.

    Cited by:

    1. Pierre Chaussé, 2011. "Generalized empirical likelihood for a continuum of moment conditions," Working Papers 1104, University of Waterloo, Department of Economics, revised Oct 2011.
    2. Lars Peter Hansen, 2014. "Uncertainty Outside and Inside Economic Models," Working Papers 2014-06, Becker Friedman Institute for Research In Economics.
    3. Stefan Boes, 2010. "Count Data Models with Correlated Unobserved Heterogeneity," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(3), pages 382-402.
    4. Chen, Songxi & Peng, Liang & Yu, Cindy, 2013. "Parameter Estimation and Model Testing for Markov Processes via Conditional Characteristic Functions," MPRA Paper 46273, University Library of Munich, Germany.
    5. Lavergne, Pascal & Patilea, Valentin, 2013. "Smooth minimum distance estimation and testing with conditional estimating equations: Uniform in bandwidth theory," Journal of Econometrics, Elsevier, vol. 177(1), pages 47-59.
    6. Sueishi, Naoya, 2016. "A simple derivation of the efficiency bound for conditional moment restriction models," Economics Letters, Elsevier, vol. 138(C), pages 57-59.
    7. Wen-Tai Hsu & Tomoya Mori & Tony E. Smith, 2014. "Spatial Patterns and Size Distributions of Cities," KIER Working Papers 882, Kyoto University, Institute of Economic Research.
    8. Chen, Ziqi & Shi, Ning-Zhong & Gao, Wei & Tang, Man-Lai, 2011. "Efficient semiparametric estimation via Cholesky decomposition for longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3344-3354, December.
    9. Naoto Kunitomo & Yukitoshi Matsushita, 2009. "Asymptotic Expansions and Higher Order Properties of Semi-Parametric Estimators in a System of Simultaneous Equations," CIRJE F-Series CIRJE-F-611, CIRJE, Faculty of Economics, University of Tokyo.
    10. Song, Kyungchul, 2010. "Testing semiparametric conditional moment restrictions using conditional martingale transforms," Journal of Econometrics, Elsevier, vol. 154(1), pages 74-84, January.
    11. Naoto Kunitomo, 2002. "Improving Small Sample Properties of the Empirical Likelihood Estimation," CIRJE F-Series CIRJE-F-184, CIRJE, Faculty of Economics, University of Tokyo.
    12. Wang, Yafeng & Graham, Brett, 2010. "Simulation Based Estimation of Discrete Sequential Move Games of Perfect Information," MPRA Paper 23153, University Library of Munich, Germany.
    13. Hill, Jonathan B. & Aguilar, Mike, 2013. "Moment condition tests for heavy tailed time series," Journal of Econometrics, Elsevier, vol. 172(2), pages 255-274.
    14. João Madeira & Nuno Palma, 2018. "Measuring monetary policy deviations from the Taylor rule," The School of Economics Discussion Paper Series 1803, Economics, The University of Manchester.
    15. Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January.
    16. Donald, Stephen G. & Imbens, Guido W. & Newey, Whitney K., 2003. "Empirical likelihood estimation and consistent tests with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 117(1), pages 55-93, November.
    17. Yuan, Ao & Xu, Jinfeng & Zheng, Gang, 2014. "On empirical likelihood statistical functions," Journal of Econometrics, Elsevier, vol. 178(P3), pages 613-623.
    18. Moon, Hyungsik Roger & Schorfheide, Frank, 2009. "Estimation with overidentifying inequality moment conditions," Journal of Econometrics, Elsevier, vol. 153(2), pages 136-154, December.
    19. Komunjer, Ivana & Ragusa, Giuseppe, 2016. "Existence And Characterization Of Conditional Density Projections," Econometric Theory, Cambridge University Press, vol. 32(04), pages 947-987, August.
    20. Lavergne, Pascal & Nguimkeu, Pierre, 2016. "A Hausman Specification Test of Conditional Moment Restrictions," TSE Working Papers 16-743, Toulouse School of Economics (TSE).
    21. Smith, Richard J., 2007. "Efficient information theoretic inference for conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 138(2), pages 430-460, June.
    22. Kiwitt, Sebastian & Nagel, Eva-Renate & Neumeyer, Natalie, 2005. "Empirical likelihood estimators for the error distribution in nonparametric regression models," Technical Reports 2005,45, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    23. Taisuke Otsu & Myung Hwan Seo & Yoon-Jae Whang, 2008. "Testing for Non-Nested Conditional Moment Restrictions Using Unconditional Empirical Likelihood," Cowles Foundation Discussion Papers 1660, Cowles Foundation for Research in Economics, Yale University.
    24. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    25. Fan, Yanqin & Gentry, Matthew & Li, Tong, 2011. "A new class of asymptotically efficient estimators for moment condition models," Journal of Econometrics, Elsevier, vol. 162(2), pages 268-277, June.
    26. Fan, Jianqing & Liao, Yuan, 2012. "Endogeneity in ultrahigh dimension," MPRA Paper 38698, University Library of Munich, Germany.
    27. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    28. Liu, Tianqing & Yuan, Xiaohui, 2012. "Combining quasi and empirical likelihoods in generalized linear models with missing responses," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 39-58.
    29. Kotchoni, Rachidi, 2014. "The indirect continuous-GMM estimation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 464-488.
    30. Moon, Hyungsik Roger & Schorfheide, Frank, 2006. "Boosting Your Instruments: Estimation with Overidentifying Inequality Moment Conditions," CEPR Discussion Papers 5605, C.E.P.R. Discussion Papers.
    31. Otsu, Taisuke & Whang, Yoon-Jae, 2011. "Testing For Nonnested Conditional Moment Restrictions Via Conditional Empirical Likelihood," Econometric Theory, Cambridge University Press, vol. 27(01), pages 114-153, February.
    32. Han, Peisong & Song, Peter X.-K. & Wang, Lu, 2015. "Achieving semiparametric efficiency bound in longitudinal data analysis with dropouts," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 59-70.
    33. Crudu, Federico & Sándor, Zsolt, 2011. "On the finite-sample properties of conditional empirical likelihood estimators," MPRA Paper 34116, University Library of Munich, Germany.
    34. Naoto Kunitomo & Yukitoshi Matsushita, 2003. "On Finite Sample Distributions of the Empirical Likelihood Estimator and the GMM Estimator," CIRJE F-Series CIRJE-F-200, CIRJE, Faculty of Economics, University of Tokyo.
    35. Komunjer, Ivana & Vuong, Quang, 2010. "Efficient estimation in dynamic conditional quantile models," Journal of Econometrics, Elsevier, vol. 157(2), pages 272-285, August.
    36. Liu, Qingfeng & Nishiyama, Yoshihiko, 2008. "Maximum empirical likelihood estimation of continuous-time models with conditional characteristic functions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 341-350.
    37. Chen, Xiaohong & Hong, Han & Shum, Matthew, 2007. "Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models," Journal of Econometrics, Elsevier, vol. 141(1), pages 109-140, November.
    38. Dovonon, Prosper, 2008. "Large sample properties of the three-step euclidean likelihood estimators under model misspecification," MPRA Paper 40025, University Library of Munich, Germany, revised 16 May 2010.
    39. Komunjer, Ivana & Ragusa, Giuseppe, 2009. "Existence and Uniqueness of Semiparametric Projections," University of California at San Diego, Economics Working Paper Series qt0wg3j51c, Department of Economics, UC San Diego.
    40. Su, Liangjun & White, Halbert, 2003. "Testing Conditional Independence Via Empirical Likelihood," University of California at San Diego, Economics Working Paper Series qt35v8g0fm, Department of Economics, UC San Diego.
    41. Chen, Song Xi & Cui, Hengjian, 2007. "On the second-order properties of empirical likelihood with moment restrictions," Journal of Econometrics, Elsevier, vol. 141(2), pages 492-516, December.
    42. Richard Smith, 2005. "Local GEL methods for conditional moment restrictions," CeMMAP working papers CWP15/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    43. Chunrong Ai & Xiaohong Chen, 2009. "Semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions," CeMMAP working papers CWP28/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    44. Gospodinov, Nikolay & Otsu, Taisuke, 2012. "Local GMM estimation of time series models with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 170(2), pages 476-490.
    45. Naoto Kunitomo & Takashi Owada, 2004. "Empirical Likelihood Estimation of Levy Processes (Revised in March 2005)," CARF F-Series CARF-F-002, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    46. Wu Wang & Zhongyi Zhu, 2017. "Conditional empirical likelihood for quantile regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(1), pages 1-16, January.
    47. Parente, Paulo M.D.C. & Smith, Richard J., 2017. "Tests of additional conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 200(1), pages 1-16.
    48. Andreas Tryphonides, 2017. "Conditional moment restrictions and the role of density information in estimated structural models," SFB 649 Discussion Papers SFB649DP2017-016, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    49. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    50. Gagliardini, Patrick & Ronchetti, Diego, 2013. "Semi-parametric estimation of American option prices," Journal of Econometrics, Elsevier, vol. 173(1), pages 57-82.
    51. Hsu, Shih-Hsun & Kuan, Chung-Ming, 2011. "Estimation of conditional moment restrictions without assuming parameter identifiability in the implied unconditional moments," Journal of Econometrics, Elsevier, vol. 165(1), pages 87-99.
    52. Carrasco, Marine, 2012. "A regularization approach to the many instruments problem," Journal of Econometrics, Elsevier, vol. 170(2), pages 383-398.
    53. Xu, Ke-Li & Phillips, Peter C.B., 2008. "Adaptive estimation of autoregressive models with time-varying variances," Journal of Econometrics, Elsevier, vol. 142(1), pages 265-280, January.
    54. Zhu, Lixing & Lin, Lu & Cui, Xia & Li, Gaorong, 2010. "Bias-corrected empirical likelihood in a multi-link semiparametric model," Journal of Multivariate Analysis, Elsevier, vol. 101(4), pages 850-868, April.
    55. Philip Kostov, 2013. "Empirical likelihood estimation of the spatial quantile regression," Journal of Geographical Systems, Springer, vol. 15(1), pages 51-69, January.
    56. Ai, Chunrong & Chen, Xiaohong, 2012. "The semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions," Journal of Econometrics, Elsevier, vol. 170(2), pages 442-457.
    57. Otsu, Taisuke, 2007. "Penalized empirical likelihood estimation of semiparametric models," Journal of Multivariate Analysis, Elsevier, vol. 98(10), pages 1923-1954, November.
    58. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics,in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76 Elsevier.
    59. Naoto Kunitomo & Takashi Owada, 2004. "Empirical Likelihood Estimation of Levy Processes (Revised: March 2005)," CIRJE F-Series CIRJE-F-272, CIRJE, Faculty of Economics, University of Tokyo.
    60. Yuan, Xiaohui & Liu, Tianqing & Lin, Nan & Zhang, Baoxue, 2010. "Combining conditional and unconditional moment restrictions with missing responses," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2420-2433, November.
    61. Naoto Kunitomo & Yukitoshi Matsushita, 2003. "Asymptotic Expansions of the Distributions of Semi-Parametric Estimators in a Linear Simultaneous Equations System," CIRJE F-Series CIRJE-F-237, CIRJE, Faculty of Economics, University of Tokyo.

  8. Tripathi, Gautam & Kim, Woocheol, 2000. "Nonparametric estimation of homogeneous function," SFB 373 Discussion Papers 2000,85, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Lewbel, Arthur & Linton, Oliver, 2003. "Nonparametric estimation of homothetic and homothetically separable functions," LSE Research Online Documents on Economics 2066, London School of Economics and Political Science, LSE Library.
    2. David Jacho-Chavez & Arthur Lewbel & Oliver Linton, 2006. "Identification and Nonparametric Estimation of a Transformed Additively Separable Model," Boston College Working Papers in Economics 652, Boston College Department of Economics, revised 26 Nov 2008.
    3. Haag, Berthold R. & Hoderlein, Stefan & Pendakur, Krishna, 2009. "Testing and imposing Slutsky symmetry in nonparametric demand systems," Journal of Econometrics, Elsevier, vol. 153(1), pages 33-50, November.
    4. Arthur Lewbel & Oliver Linton, 2003. "Nonparametric Matching and Efficient Estimators of Homothetically Separable Functions," Boston College Working Papers in Economics 585, Boston College Department of Economics, revised 04 Sep 2006.

  9. Härdle, Wolfgang & Kim, Woocheol & Tripathi, Gautam, 2000. "Nonparametric estimation of additive models with homogeneous components," SFB 373 Discussion Papers 2000,48, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Lewbel, Arthur & Linton, Oliver, 2003. "Nonparametric estimation of homothetic and homothetically separable functions," LSE Research Online Documents on Economics 2066, London School of Economics and Political Science, LSE Library.
    2. Arthur Lewbel & Oliver Linton, 2003. "Nonparametric Matching and Efficient Estimators of Homothetically Separable Functions," Boston College Working Papers in Economics 585, Boston College Department of Economics, revised 04 Sep 2006.

  10. Tripathi, Gautam & Kitamura, Yuichi, 2000. "On testing conditional moment restrictions: The canonical case," SFB 373 Discussion Papers 2000,88, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Chen, Song Xi & Gao, Jiti, 2007. "An adaptive empirical likelihood test for parametric time series regression models," Journal of Econometrics, Elsevier, vol. 141(2), pages 950-972, December.
    2. Song Xi Chen & Wolfgang Härdle & Ming Li, 2003. "An empirical likelihood goodness-of-fit test for time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(3), pages 663-678.
    3. Yuichi Kitamura & Gautam Tripathi & Hyungtaik Ahn, 2004. "Empirical Likelihood-Based Inference in Conditional Moment Restriction Models," Econometrica, Econometric Society, vol. 72(6), pages 1667-1714, November.

  11. Tripathi, G., 1997. "Semiparametric Efficiency Bounds Under Shape Restrictions," Working papers 9720, Wisconsin Madison - Social Systems.

    Cited by:

    1. Hendrik Wolff & Thomas Heckelei & Ron C. Mittelhammer, 2004. "Imposing Curvature and Monotonicity on Flexible Functional Forms: An Efficient Regional Approach," Econometric Society 2004 North American Summer Meetings 450, Econometric Society.
    2. Ait-Sahalia, Yacine & Duarte, Jefferson, 2003. "Nonparametric option pricing under shape restrictions," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 9-47.
    3. Wolff, Hendrik & Heckelei, Thomas & Mittelhammer, Ronald C., 2004. "Imposing Monotonicity And Curvature On Flexible Functional Forms," 2004 Annual meeting, August 1-4, Denver, CO 20256, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Severini, Thomas A. & Tripathi, Gautam, 2001. "A simplified approach to computing efficiency bounds in semiparametric models," Journal of Econometrics, Elsevier, vol. 102(1), pages 23-66, May.
    5. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
    6. Kyungchul Song, 2009. "Point Decisions for Interval-Identified Parameters," PIER Working Paper Archive 09-036, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

Articles

  1. Severini, Thomas A. & Tripathi, Gautam, 2013. "Semiparametric Efficiency Bounds for Microeconometric Models: A Survey," Foundations and Trends(R) in Econometrics, now publishers, vol. 6(3-4), pages 163-397, December.

    Cited by:

    1. Chen, Tao & Parker, Thomas, 2014. "Semiparametric efficiency for partially linear single-index regression models," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 376-386.

  2. Severini, Thomas A. & Tripathi, Gautam, 2012. "Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors," Journal of Econometrics, Elsevier, vol. 170(2), pages 491-498.
    See citations under working paper version above.
  3. Tripathi, Gautam, 2011. "Moment-Based Inference With Stratified Data," Econometric Theory, Cambridge University Press, vol. 27(01), pages 47-73, February.
    See citations under working paper version above.
  4. Devereux, Paul J. & Tripathi, Gautam, 2009. "Optimally combining censored and uncensored datasets," Journal of Econometrics, Elsevier, vol. 151(1), pages 17-32, July.
    See citations under working paper version above.
  5. Severini, Thomas A. & Tripathi, Gautam, 2006. "Some Identification Issues In Nonparametric Linear Models With Endogenous Regressors," Econometric Theory, Cambridge University Press, vol. 22(02), pages 258-278, April.
    See citations under working paper version above.
  6. Yuichi Kitamura & Gautam Tripathi & Hyungtaik Ahn, 2004. "Empirical Likelihood-Based Inference in Conditional Moment Restriction Models," Econometrica, Econometric Society, vol. 72(6), pages 1667-1714, November.
    See citations under working paper version above.
  7. Tripathi, Gautam & Kim, Woocheol, 2003. "Nonparametric Estimation Of Homogeneous Functions," Econometric Theory, Cambridge University Press, vol. 19(04), pages 640-663, August.
    See citations under working paper version above.
  8. Severini, Thomas A. & Tripathi, Gautam, 2001. "A simplified approach to computing efficiency bounds in semiparametric models," Journal of Econometrics, Elsevier, vol. 102(1), pages 23-66, May.

    Cited by:

    1. Thomas A. Severini & Gautam Tripathi, 2007. "Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors," CeMMAP working papers CWP13/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Sueishi, Naoya, 2016. "A simple derivation of the efficiency bound for conditional moment restriction models," Economics Letters, Elsevier, vol. 138(C), pages 57-59.
    3. Magnac, Thierry & Maurin, Eric, 2007. "Identification and information in monotone binary models," Journal of Econometrics, Elsevier, vol. 139(1), pages 76-104, July.
    4. Cosslett, Stephen R., 2013. "Efficient semiparametric estimation for endogenously stratified regression via smoothed likelihood," Journal of Econometrics, Elsevier, vol. 177(1), pages 116-129.
    5. Chu, Ba & Jacho-Chávez, David T., 2012. "k-NEAREST NEIGHBOR ESTIMATION OF INVERSE-DENSITY-WEIGHTED EXPECTATIONS WITH DEPENDENT DATA," Econometric Theory, Cambridge University Press, vol. 28(04), pages 769-803, August.
    6. Fan, Jianqing & Liao, Yuan, 2012. "Endogeneity in ultrahigh dimension," MPRA Paper 38698, University Library of Munich, Germany.
    7. J. M. Krief, 2009. "Two Stage Semi Parametric Quantile Regression," Departmental Working Papers 2009-05, Department of Economics, Louisiana State University.
    8. Devereux, Paul J. & Tripathi, Gautam, 2009. "Optimally combining censored and uncensored datasets," Journal of Econometrics, Elsevier, vol. 151(1), pages 17-32, July.
    9. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
    10. Kaido, Hiroaki, 2017. "Asymptotically Efficient Estimation Of Weighted Average Derivatives With An Interval Censored Variable," Econometric Theory, Cambridge University Press, vol. 33(05), pages 1218-1241, October.
    11. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355.
    12. Antoine, Bertille & Bonnal, Helene & Renault, Eric, 2007. "On the efficient use of the informational content of estimating equations: Implied probabilities and Euclidean empirical likelihood," Journal of Econometrics, Elsevier, vol. 138(2), pages 461-487, June.
    13. Ying-Ying Lee, 2015. "Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification," Econometrics, MDPI, Open Access Journal, vol. 4(1), pages 1-14, December.
    14. Tripathi, Gautam, 2011. "Generalized method of moments (GMM) based inference with stratified samples when the aggregate shares are known," Journal of Econometrics, Elsevier, vol. 165(2), pages 258-265.
    15. Chen, Tao & Parker, Thomas, 2014. "Semiparametric efficiency for partially linear single-index regression models," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 376-386.
    16. Patrick Gagliardini & Christian Gourieroux, 2002. "Duration Time Series Models with Proportional Hazard," Working Papers 2002-21, Center for Research in Economics and Statistics.
    17. Dennis Kristensen, 2009. "Semiparametric Modelling and Estimation: A Selective Overview," CREATES Research Papers 2009-44, Department of Economics and Business Economics, Aarhus University.
    18. Dennis Kristensen, 2004. "Estimation in Two Classes of Semiparametric Diffusion Models," FMG Discussion Papers dp500, Financial Markets Group.

  9. Tripathi, Gautam, 2000. "Econometric Methods," Econometric Theory, Cambridge University Press, vol. 16(01), pages 139-142, February.

    Cited by:

    1. Peter C.B. Phillips & Jun Yu, 2007. "Simulation-based Estimation of Contingent-claims Prices," Cowles Foundation Discussion Papers 1596, Cowles Foundation for Research in Economics, Yale University.
    2. Peter Fuleky & Eric Zivot, 2010. "Indirect Inference Based on the Score," Working Papers UWEC-2010-08, University of Washington, Department of Economics.
    3. Gould, Brian W. & Yen, Steven T., 2002. "Food Demand In Mexico: A Quasi-Maximum Likelihood Approach," 2002 Annual meeting, July 28-31, Long Beach, CA 19667, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Jun Yu, 2009. "Econometric Analysis of Continuous Time Models : A Survey of Peter Phillips’ Work and Some New Results," Microeconomics Working Papers 23046, East Asian Bureau of Economic Research.
    5. Garbis Iradian, 2005. "Inequality, Poverty, and Growth; Cross-Country Evidence," IMF Working Papers 05/28, International Monetary Fund.
    6. Carroll, Christopher D. & Parker, Jonathan A. & Souleles, Nicholas S., 2014. "The benefits of panel data in consumer expenditure surveys," CFS Working Paper Series 465, Center for Financial Studies (CFS).
    7. Christian Gouriéroux & Peter C. B. Phillips & Jun Yu, 2006. "Indirect Inference for Dynamic Panel Models," Development Economics Working Papers 22421, East Asian Bureau of Economic Research.
    8. Antonis Demos & Stelios Arvanitis, 2010. "Stochastic Expansions and Moment Approximations for Three Indirect Estimators," DEOS Working Papers 1004, Athens University of Economics and Business.
    9. Peter C.B. Philips & Yangru Wu & Jun Yu, 2009. "Explosive Behavior in the 1990s Nasdaq : When Did Exuberance Escalate Asset Values?," Finance Working Papers 23050, East Asian Bureau of Economic Research.
    10. Alexandre Manoel Angelo da Silva, 2001. "Setor Aéreo Doméstico Brasileiro: uma Função Custo," Anais do XXIX Encontro Nacional de Economia [Proceedings of the 29th Brazilian Economics Meeting] 069, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    11. Peter C.B. Phillips & Jun Yu, 2007. "Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance," Cowles Foundation Discussion Papers 1597, Cowles Foundation for Research in Economics, Yale University.
    12. Chihwa Kao & Lung-fei Lee & Mark M. Pitt, 2000. "Simulated Maximum Likelihood Estimation of the Linear Expenditure System with Binding Non-Negativity Constraints," CEMA Working Papers 50, China Economics and Management Academy, Central University of Finance and Economics, revised Apr 2001.
    13. Siem Jan Koopman & Neil Shephard, 2002. "Testing the Assumptions Behind the Use of Importance Sampling," Economics Papers 2002-W17, Economics Group, Nuffield College, University of Oxford.
    14. Grammig, Joachim G. & Peter, Franziska J., 2008. "International price discovery in the presence of market microstructure effects," CFR Working Papers 08-10, University of Cologne, Centre for Financial Research (CFR).
    15. Yu, Jun, 2014. "Econometric Analysis Of Continuous Time Models: A Survey Of Peter Phillips’S Work And Some New Results," Econometric Theory, Cambridge University Press, vol. 30(04), pages 737-774, August.
    16. Stuart J. Fowler & Jennifer J. Wilgus, 2011. "An Estimatable DCDP Model of Search and Matching in Real Estate Markets," Working Papers 201105, Middle Tennessee State University, Department of Economics and Finance.

  10. Tripathi, Gautam, 2000. "Local Semiparametric Efficiency Bounds Under Shape Restrictions," Econometric Theory, Cambridge University Press, vol. 16(05), pages 729-739, October.

    Cited by:

    1. Hendrik Wolff & Thomas Heckelei & Ron C. Mittelhammer, 2004. "Imposing Curvature and Monotonicity on Flexible Functional Forms: An Efficient Regional Approach," Econometric Society 2004 North American Summer Meetings 450, Econometric Society.
    2. Wolff, Hendrik & Heckelei, Thomas & Mittelhammer, Ronald C., 2004. "Imposing Monotonicity And Curvature On Flexible Functional Forms," 2004 Annual meeting, August 1-4, Denver, CO 20256, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Kyungchul Song, 2009. "Point Decisions for Interval-Identified Parameters," PIER Working Paper Archive 09-036, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

  11. Tripathi, Gautam, 1999. "A matrix extension of the Cauchy-Schwarz inequality," Economics Letters, Elsevier, vol. 63(1), pages 1-3, April.

    Cited by:

    1. Cizek, P. & Jacobs, J. & Ligthart, J.E. & Vrijburg, H., 2015. "GMM Estimation of Fixed Effects Dynamic Panel Data Models with Spatial Lag and Spatial Errors (Revised version of CentER DP 2011-134)," Discussion Paper 2015-003, Tilburg University, Center for Economic Research.
    2. 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.
    3. Pierre Nguimkeu & Augustine Denteh & Rusty Tchernis, 2017. "On the Estimation of Treatment Effects with Endogenous Misreporting," NBER Working Papers 24117, National Bureau of Economic Research, Inc.
    4. Sherwood, Ben, 2016. "Variable selection for additive partial linear quantile regression with missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 206-223.
    5. Anatolyev, Stanislav, 2004. "Inference when a nuisance parameter is weakly identified under the null hypothesis," Economics Letters, Elsevier, vol. 84(2), pages 245-254, August.
    6. R H Spady & S Stouli, 2018. "Dual regression," Biometrika, Biometrika Trust, vol. 105(1), pages 1-18.
    7. 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.
    8. Cheng, Xu, 2015. "Robust inference in nonlinear models with mixed identification strength," Journal of Econometrics, Elsevier, vol. 189(1), pages 207-228.
    9. Wu, Jianghong & Song, Weixing, 2015. "On Hong–Tamer’s estimator in nonlinear errors-in-variable regression models," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 165-175.
    10. 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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  1. NEP-ECM: Econometrics (12) 2001-07-30 2005-04-30 2005-09-29 2006-06-03 2007-06-11 2007-11-24 2008-09-13 2008-09-29 2009-02-28 2011-01-16 2013-06-30 2014-03-22. Author is listed

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