IDEAS home Printed from https://ideas.repec.org/r/zbw/kitwps/81.html

Semiparametric estimation with generated covariates

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Fabio Sanches & Daniel Silva Junior & Sorawoot Srisuma, 2018. "Minimum Distance Estimation of Search Costs Using Price Distribution," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(4), pages 658-671, October.
  2. repec:hum:wpaper:sfb649dp2011-064 is not listed on IDEAS
  3. Juan Carlos Escanciano & Telmo P'erez-Izquierdo, 2023. "Automatic Debiased Estimation with Machine Learning-Generated Regressors," Papers 2301.10643, arXiv.org, revised May 2025.
  4. Nir Billfeld & Moshe Kim, 2024. "Context-dependent Causality (the Non-Nonotonic Case)," Papers 2404.05021, arXiv.org.
  5. repec:hum:wpaper:sfb649dp2011-083 is not listed on IDEAS
  6. Escanciano, Juan Carlos & Jacho-Chávez, David T. & Lewbel, Arthur, 2014. "Uniform convergence of weighted sums of non and semiparametric residuals for estimation and testing," Journal of Econometrics, Elsevier, vol. 178(P3), pages 426-443.
  7. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
  8. repec:hum:wpaper:sfb649dp2011-069 is not listed on IDEAS
  9. Laage, Louise, 2024. "A Correlated Random Coefficient panel model with time-varying endogeneity," Journal of Econometrics, Elsevier, vol. 242(2).
  10. Delsol , Laurent & Van Keilegom, Ingrid, 2011. "Semiparametric M-Estimation with Non-Smooth Criterion Functions," LIDAM Discussion Papers ISBA 2011041, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  11. Patrick Saart & Jiti Gao & Nam Hyun Kim, 2014. "Semiparametric methods in nonlinear time series analysis: a selective review," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 141-169, March.
  12. Kanaya, Shin & Kristensen, Dennis, 2016. "Estimation Of Stochastic Volatility Models By Nonparametric Filtering," Econometric Theory, Cambridge University Press, vol. 32(4), pages 861-916, August.
  13. repec:hum:wpaper:sfb649dp2011-082 is not listed on IDEAS
  14. Jayeeta Bhattacharya, 2020. "Quantile regression with generated dependent variable and covariates," Papers 2012.13614, arXiv.org.
  15. repec:hum:wpaper:sfb649dp2011-065 is not listed on IDEAS
  16. Ghosh, Anisha & Linton, Oliver, 2023. "Estimation with mixed data frequencies: A bias-correction approach," Journal of Empirical Finance, Elsevier, vol. 74(C).
  17. Xiaohong Chen & Yin Jia Jeff Qiu, 2016. "Methods for Nonparametric and Semiparametric Regressions with Endogeneity: A Gentle Guide," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 259-290, October.
  18. repec:hum:wpaper:sfb649dp2011-072 is not listed on IDEAS
  19. repec:hum:wpaper:sfb649dp2011-085 is not listed on IDEAS
  20. Vanhems, Anne & Van Keilegom, Ingrid, 2019. "Estimation Of A Semiparametric Transformation Model In The Presence Of Endogeneity," Econometric Theory, Cambridge University Press, vol. 35(1), pages 73-110, February.
  21. Lee, Ying-Ying, 2018. "Efficient propensity score regression estimators of multivalued treatment effects for the treated," Journal of Econometrics, Elsevier, vol. 204(2), pages 207-222.
  22. Debopam Bhattacharya & Pascaline Dupas & Shin Kanaya, 2013. "Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets," CREATES Research Papers 2013-06, Department of Economics and Business Economics, Aarhus University.
  23. Elia Lapenta & Pascal Lavergne, 2022. "Encompassing Tests for Nonparametric Regressions," Papers 2203.06685, arXiv.org, revised Oct 2023.
  24. Hubner, Stefan, 2023. "Identification of unobserved distribution factors and preferences in the collective household model," Journal of Econometrics, Elsevier, vol. 234(1), pages 301-326.
  25. Ying-Ying Lee, 2014. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Economics Series Working Papers 706, University of Oxford, Department of Economics.
  26. Le‐Yu Chen & Sokbae Lee & Myung Jae Sung, 2014. "Maximum score estimation with nonparametrically generated regressors," Econometrics Journal, Royal Economic Society, vol. 17(3), pages 271-300, October.
  27. Yucong Lin & Jinhua Su & Yang Liu & Jue Hou & Feifei Wang, 2024. "Implicit profiling estimation for semiparametric models with bundled parameters," Statistical Papers, Springer, vol. 65(5), pages 3203-3234, July.
  28. Ying-Ying Lee, 2015. "Efficient propensity score regression estimators of multi-valued treatment effects for the treated," Economics Series Working Papers 738, University of Oxford, Department of Economics.
  29. repec:hum:wpaper:sfb649dp2011-071 is not listed on IDEAS
  30. Francesco Bravo & Ba M. Chu & David T. Jacho-Chávez, 2017. "Semiparametric estimation of moment condition models with weakly dependent data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(1), pages 108-136, January.
  31. Rothe, Christoph, 2016. "The Value of Knowing the Propensity Score for Estimating Average Treatment Effects," IZA Discussion Papers 9989, IZA Network @ LISER.
  32. Lu, Xun & White, Habert, 2015. "Testing For Treatment Dependence Of Effects Of A Continuous Treatment," Econometric Theory, Cambridge University Press, vol. 31(5), pages 1016-1053, October.
  33. Gao, Jiti & Kim, Nam Hyun & Saart, Patrick W., 2015. "A misspecification test for multiplicative error models of non-negative time series processes," Journal of Econometrics, Elsevier, vol. 189(2), pages 346-359.
  34. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
  35. Matsushita, Yukitoshi & Otsu, Taisuke, 2020. "Likelihood inference on semiparametric models with generated regressors," LSE Research Online Documents on Economics 102696, London School of Economics and Political Science, LSE Library.
  36. Mochen Yang & Edward McFowland & Gordon Burtch & Gediminas Adomavicius, 2022. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," INFORMS Joural on Data Science, INFORMS, vol. 1(2), pages 138-155, October.
  37. repec:hum:wpaper:sfb649dp2011-084 is not listed on IDEAS
  38. Buchholz, Nicholas & Shum, Matthew & Xu, Haiqing, 2021. "Semiparametric estimation of dynamic discrete choice models," Journal of Econometrics, Elsevier, vol. 223(2), pages 312-327.
  39. repec:hum:wpaper:sfb649dp2011-067 is not listed on IDEAS
  40. Laurent Delsol & Ingrid Van Keilegom, 2020. "Semiparametric M-estimation with non-smooth criterion functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(2), pages 577-605, April.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.