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Imposing Moment Restrictions from Auxiliary Data by Weighting

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Cited by:

  1. Lee, Seojeong, 2016. "Asymptotic refinements of a misspecification-robust bootstrap for GEL estimators," Journal of Econometrics, Elsevier, vol. 192(1), pages 86-104.
  2. William J Carrington & John L Eltinge & Kristin McCue, 2000. "An Economist's Primer on Survey Samples," Working Papers 00-15, Center for Economic Studies, U.S. Census Bureau.
  3. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
  4. Esmeralda A. Ramalho & Joaquim J. S. Ramalho, 2006. "Two‐Step Empirical Likelihood Estimation Under Stratified Sampling When Aggregate Information Is Available," Manchester School, University of Manchester, vol. 74(5), pages 577-592, September.
  5. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
  6. Ryosuke Igari & Takahiro Hoshino, 2018. "A Bayesian Gamma Frailty Model Using the Sum of Independent Random Variables: Application of the Estimation of an Interpurchase Timing Model," Keio-IES Discussion Paper Series 2018-021, Institute for Economics Studies, Keio University.
  7. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
  8. Amélie Crepet & Hugo Harari-Kermadec & Jessica Tressou, 2007. "Using Empirical Likelihood to Combine Data : Application to Food Risk Assessment," Working Papers 2007-20, Center for Research in Economics and Statistics.
  9. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
  10. Esmeralda A. Ramalho & Joaquim J. S. Ramalho & Rui Evangelista, 2017. "Combining micro and macro data in hedonic price indexes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(2), pages 317-332, June.
  11. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
  12. 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.
  13. Nail Kashaev, 2022. "Estimation of Parametric Binary Outcome Models with Degenerate Pure Choice-Based Data with Application to COVID-19-Positive Tests from British Columbia," University of Western Ontario, Departmental Research Report Series 20225, University of Western Ontario, Department of Economics.
  14. Bryan S. Graham & Cristine Campos de Xavier Pinto & Daniel Egel, 2016. "Efficient Estimation of Data Combination Models by the Method of Auxiliary-to-Study Tilting (AST)," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 288-301, April.
  15. Michael S. Rendall, 2007. "Book Review: Constrained Statistical Inference: Inequality, Order, and Shape Restrictions," Sociological Methods & Research, , vol. 35(3), pages 447-451, February.
  16. Keisuke Hirano & Guido W. Imbens & Geert Ridder & Donald B. Rubin, 2001. "Combining Panel Data Sets with Attrition and Refreshment Samples," Econometrica, Econometric Society, vol. 69(6), pages 1645-1659, November.
  17. Michael S. Rendall & Bonnie Ghosh-Dastidar & Margaret M. Weden & Zafar Nazarov, 2011. "Multiple Imputation for Combined-Survey Estimation With Incomplete Regressors In One But Not Both Surveys," Working Papers WR-887-1, RAND Corporation.
  18. Denis Heng Yan Leung & Ken Yamada & Biao Zhang, 2015. "Enriching Surveys with Supplementary Data and its Application to Studying Wage Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 155-179, March.
  19. Buchinsky, Moshe & Li, Fanghua & Liao, Zhipeng, 2022. "Estimation and inference of semiparametric models using data from several sources," Journal of Econometrics, Elsevier, vol. 226(1), pages 80-103.
  20. Changchun Wu & Runchu Zhang, 2006. "An Information-theoretic Approach to the Effective Usage of Auxiliary Information from Survey Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(3), pages 499-509, September.
  21. Butler, J. S., 2000. "Efficiency results of MLE and GMM estimation with sampling weights," Journal of Econometrics, Elsevier, vol. 96(1), pages 25-37, May.
  22. Isaiah Andrews & Emily Oster, 2017. "A Simple Approximation for Evaluating External Validity Bias," NBER Working Papers 23826, National Bureau of Economic Research, Inc.
  23. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 251-299.
  24. Devereux, Paul J. & Tripathi, Gautam, 2009. "Optimally combining censored and uncensored datasets," Journal of Econometrics, Elsevier, vol. 151(1), pages 17-32, July.
  25. F Bravo, 2008. "Effcient M-estimators with auxiliary information," Discussion Papers 08/26, Department of Economics, University of York.
  26. Michael S. Rendall & Mark S. Handcock & Stefan H. Jonsson, 2007. "Bayesian Estimation of Hispanic Fertility Hazards from Survey and Population Data," Working Papers 496, RAND Corporation.
  27. Hirukawa, Masayuki & Prokhorov, Artem, 2018. "Consistent estimation of linear regression models using matched data," Journal of Econometrics, Elsevier, vol. 203(2), pages 344-358.
  28. Ramalho, Esmeralda A., 2002. "Regression models for choice-based samples with misclassification in the response variable," Journal of Econometrics, Elsevier, vol. 106(1), pages 171-201, January.
  29. Yuichi Kitamura, 2020. "A Comment on: “On the Informativeness of Descriptive Statistics for Structural Estimates” by Isaiah Andrews, Matthew Gentzkow, and Jesse M. Shapiro," Econometrica, Econometric Society, vol. 88(6), pages 2265-2269, November.
  30. Nevo, Aviv, 2003. "Using Weights to Adjust for Sample Selection When Auxiliary Information Is Available," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 43-52, January.
  31. Elbers, Chris & Lanjouw, Jean O. & Lanjouw, Peter, 2002. "Micro-level estimation of welfare," Policy Research Working Paper Series 2911, The World Bank.
  32. Adam N. Glynn & Jon Wakefield & Mark S. Handcock & Thomas S. Richardson, 2008. "Alleviating linear ecological bias and optimal design with subsample data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 179-202, January.
  33. Chris Elbers & Jean Lanjouw, 2000. "Welfare in Village and Towns: Micro-Measurement of Poverty and Inequality," Tinbergen Institute Discussion Papers 00-029/2, Tinbergen Institute.
  34. Lee, Seojeong, 2014. "Asymptotic refinements of a misspecification-robust bootstrap for generalized method of moments estimators," Journal of Econometrics, Elsevier, vol. 178(P3), pages 398-413.
  35. Judith K. Hellerstein & Melinda Sandler Morrill, 2011. "Dads and Daughters: The Changing Impact of Fathers on Women’s Occupational Choices," Journal of Human Resources, University of Wisconsin Press, vol. 46(2), pages 333-372.
  36. Golan, Amos, 2001. "A simultaneous estimation and variable selection rule," Journal of Econometrics, Elsevier, vol. 101(1), pages 165-193, March.
  37. Michael Rendall & Ryan Admiraal & Alessandra DeRose & Paola DiGiulio & Mark Handcock & Filomena Racioppi, 2008. "Population constraints on pooled surveys in demographic hazard modeling," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(4), pages 519-539, October.
  38. Sasaki, Yuya, 2015. "Heterogeneity and selection in dynamic panel data," Journal of Econometrics, Elsevier, vol. 188(1), pages 236-249.
  39. d'Haultfoeuille, Xavier, 2010. "A new instrumental method for dealing with endogenous selection," Journal of Econometrics, Elsevier, vol. 154(1), pages 1-15, January.
  40. Michael S. Rendall & Ryan Admiraal & Alessandra De Rose & Paola Di Giulio & Mark S. Handcock & Filomena Racioppi, 2006. "Population constraints on pooled surveys in demographic hazard modeling," MPIDR Working Papers WP-2006-039, Max Planck Institute for Demographic Research, Rostock, Germany.
  41. Michael S. Rendall & Bonnie Ghosh-Dastidar & Margaret M. Weden & Elizabeth H. Baker & Zafar Nazarov, 2013. "Multiple Imputation for Combined-survey Estimation With Incomplete Regressors in One but Not Both Surveys," Sociological Methods & Research, , vol. 42(4), pages 483-530, November.
  42. Hainmueller, Jens, 2012. "Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies," Political Analysis, Cambridge University Press, vol. 20(1), pages 25-46, January.
  43. Hamori, Shigeyuki & Motegi, Kaiji & Zhang, Zheng, 2019. "Calibration estimation of semiparametric copula models with data missing at random," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 85-109.
  44. Han, Chirok & Kim, Beomsoo, 2011. "A GMM interpretation of the paradox in the inverse probability weighting estimation of the average treatment effect on the treated," Economics Letters, Elsevier, vol. 110(2), pages 163-165, February.
  45. Michael S. Rendall & Mark S. Handcock & Stefan H. Jonsson, 2007. "Bayesian Estimation of Hispanic Fertility Hazards from Survey and Population Data," Working Papers WR-496, RAND Corporation.
  46. Alexander G. Nikolaev & Sheldon H. Jacobson & Wendy K. Tam Cho & Jason J. Sauppe & Edward C. Sewell, 2013. "Balance Optimization Subset Selection (BOSS): An Alternative Approach for Causal Inference with Observational Data," Operations Research, INFORMS, vol. 61(2), pages 398-412, April.
  47. Andreas Tryphonides, 2018. "Tilting Approximate Models," Papers 1805.10869, arXiv.org, revised Mar 2024.
  48. Bryan S. Graham & Cristine Campos De Xavier Pinto & Daniel Egel, 2012. "Inverse Probability Tilting for Moment Condition Models with Missing Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 1053-1079.
  49. JM Abowd & Bruno Crépon & Francis Kramarz, 1997. "Moment Estimation with Attrition," Working Papers 97-35, Center for Research in Economics and Statistics.
  50. Nevo, Aviv, 2002. "Sample selection and information-theoretic alternatives to GMM," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 149-157, March.
  51. Seojeong Lee, 2018. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Empirical Likelihood Estimators," Papers 1806.00953, arXiv.org, revised Jun 2018.
  52. Esmeralda A. Ramalho & Richard J. Smith, 2013. "Discrete Choice Non-Response," Review of Economic Studies, Oxford University Press, vol. 80(1), pages 343-364.
  53. Bayram, Deniz & Dayé, Modeste, 2014. "Asymptotic Properties of the Weighted Least Squares Estimator Under Moments Restriction," MPRA Paper 60465, University Library of Munich, Germany.
  54. Mark Handcock & Sami Huovilainen & Michael Rendall, 2000. "Combining registration-system and survey data to estimate birth probabilities," Demography, Springer;Population Association of America (PAA), vol. 37(2), pages 187-192, May.
  55. Kwun Chuen Gary Chan & Sheung Chi Phillip Yam & Zheng Zhang, 2016. "Globally efficient non-parametric inference of average treatment effects by empirical balancing calibration weighting," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 673-700, June.
  56. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian Instrumental Variables Estimation for Nonignorable Missing Instruments," Discussion Paper Series DP2020-06, Research Institute for Economics & Business Administration, Kobe University.
  57. Brocker, Johannes, 2005. "Necessary and unnecessary parameter restrictions for CDES demand systems," Conference papers 331358, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
  58. Prokhorov, Artem & Schmidt, Peter, 2009. "GMM redundancy results for general missing data problems," Journal of Econometrics, Elsevier, vol. 151(1), pages 47-55, July.
  59. Amélie Crépet & Hugo Harari-Kermadec & Jessica Tressou, 2009. "Using Empirical Likelihood to Combine Data: Application to Food Risk Assessment," Biometrics, The International Biometric Society, vol. 65(1), pages 257-266, March.
  60. Heng Chen & Marie-Hélène Felt & Christopher Henry, 2018. "2017 Methods-of-Payment Survey: Sample Calibration and Variance Estimation," Technical Reports 114, Bank of Canada.
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