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Liqun Wang

Personal Details

First Name:Liqun
Middle Name:
Last Name:Wang
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RePEc Short-ID:pwa363
http://home.cc.umanitoba.ca/~wangl1/

Affiliation

University of Manitoba, Department of Statistics

http://umanitoba.ca/
Canada, Winnipeg/Manitoba

Research output

as
Jump to: Working papers Articles

Working papers

  1. Marcel Voia & Liqun Wang & Ricardas Zitikis, 2009. "A Distributional Analysis of Treatment Effects on Subpopulations of a Socioeconomic Experiment," Carleton Economic Papers 09-02, Carleton University, Department of Economics, revised 05 Feb 2010.

Articles

  1. Mustafa Salamh & Liqun Wang, 2021. "Second-Order Least Squares Estimation in Nonlinear Time Series Models with ARCH Errors," Econometrics, MDPI, vol. 9(4), pages 1-17, November.
  2. Mustafa Salamh & Liqun Wang, 2021. "Second-Order Least Squares Method for Dynamic Panel Data Models with Application," JRFM, MDPI, vol. 14(9), pages 1-19, September.
  3. Zhiyong Jin & Liqun Wang, 2017. "First Passage Time for Brownian Motion and Piecewise Linear Boundaries," Methodology and Computing in Applied Probability, Springer, vol. 19(1), pages 237-253, March.
  4. Li, Daniel H. & Wang, Liqun, 2016. "A weighted simulation-based estimator for incomplete longitudinal data models," Statistics & Probability Letters, Elsevier, vol. 113(C), pages 16-22.
  5. Kun Xu & Yanyuan Ma & Liqun Wang, 2015. "Instrument Assisted Regression for Errors in Variables Models with Binary Response," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 104-117, March.
  6. Wang, Liqun & Lee, Chel Hee, 2014. "Discretization-based direct random sample generation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1001-1010.
  7. Taraneh Abarin & Liqun Wang, 2012. "Instrumental variable approach to covariate measurement error in generalized linear models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(3), pages 475-493, June.
  8. Chen, Songnian & Hsiao, Cheng & Wang, Liqun, 2012. "Measurement Errors And Censored Structural Latent Variables Models," Econometric Theory, Cambridge University Press, vol. 28(3), pages 696-703, June.
  9. Wang, Liqun & Hsiao, Cheng, 2011. "Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 165(1), pages 30-44.
  10. Liqun Wang, 2009. "Robert E. Weiss (2006): Modeling longitudinal data," Statistical Papers, Springer, vol. 50(1), pages 213-214, January.
  11. Liqun Wang & Alexandre Leblanc, 2008. "Second-order nonlinear least squares estimation," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(4), pages 883-900, December.
  12. Liqun Wang & James Fu, 2007. "A practical sampling approach for a Bayesian mixture model with unknown number of components," Statistical Papers, Springer, vol. 48(4), pages 631-653, October.
  13. Liqun Wang & Klaus Pötzelberger, 2007. "Crossing Probabilities for Diffusion Processes with Piecewise Continuous Boundaries," Methodology and Computing in Applied Probability, Springer, vol. 9(1), pages 21-40, March.
  14. Liqun Wang & Cheng Hsiao, 2007. "Two-stage estimation of limited dependent variable models with errors-in-variables," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 426-438, July.
  15. Wang, Liqun, 2002. "A simple adjustment for measurement errors in some limited dependent variable models," Statistics & Probability Letters, Elsevier, vol. 58(4), pages 427-433, July.
  16. James C. Fu & Liqun Wang, 2002. "A Random-Discretization Based Monte Carlo Sampling Method and its Applications," Methodology and Computing in Applied Probability, Springer, vol. 4(1), pages 5-25, March.
  17. Wang, Liqun, 1998. "Estimation of censored linear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 84(2), pages 383-400, June.

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

    Sorry, no citations of working papers recorded.

Articles

  1. Mustafa Salamh & Liqun Wang, 2021. "Second-Order Least Squares Estimation in Nonlinear Time Series Models with ARCH Errors," Econometrics, MDPI, vol. 9(4), pages 1-17, November.

    Cited by:

    1. Alexander Mayer, 2022. "Two-step estimation in linear regressions with adaptive learning," Papers 2204.05298, arXiv.org, revised Nov 2022.

  2. Mustafa Salamh & Liqun Wang, 2021. "Second-Order Least Squares Method for Dynamic Panel Data Models with Application," JRFM, MDPI, vol. 14(9), pages 1-19, September.

    Cited by:

    1. Mustafa Salamh & Liqun Wang, 2021. "Second-Order Least Squares Estimation in Nonlinear Time Series Models with ARCH Errors," Econometrics, MDPI, vol. 9(4), pages 1-17, November.

  3. Zhiyong Jin & Liqun Wang, 2017. "First Passage Time for Brownian Motion and Piecewise Linear Boundaries," Methodology and Computing in Applied Probability, Springer, vol. 19(1), pages 237-253, March.

    Cited by:

    1. Hu, Jiawen & Shen, Jingyuan & Shen, Lijuan, 2020. "Opportunistic maintenance for two-component series systems subject to dependent degradation and shock," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    2. Zhang, Ao & Wang, Zhihua & Bao, Rui & Liu, Chengrui & Wu, Qiong & Cao, Shihao, 2023. "A novel failure time estimation method for degradation analysis based on general nonlinear Wiener processes," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    3. Lee, Taeho, 2023. "Exact simulation for the first hitting time of Brownian motion and Brownian bridge," Statistics & Probability Letters, Elsevier, vol. 193(C).
    4. Qinglai Dong & Lirong Cui, 2019. "First Hitting Time Distributions for Brownian Motion and Regions with Piecewise Linear Boundaries," Methodology and Computing in Applied Probability, Springer, vol. 21(1), pages 1-23, March.

  4. Kun Xu & Yanyuan Ma & Liqun Wang, 2015. "Instrument Assisted Regression for Errors in Variables Models with Binary Response," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 104-117, March.

    Cited by:

    1. Qianqian Wang & Yanyuan Ma & Guangren Yang, 2020. "Locally efficient estimation in generalized partially linear model with measurement error in nonlinear function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 553-572, June.

  5. Taraneh Abarin & Liqun Wang, 2012. "Instrumental variable approach to covariate measurement error in generalized linear models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(3), pages 475-493, June.

    Cited by:

    1. Weiming Yang & Yiping Yang, 2020. "Composite quantile regression estimation of linear error-in-variable models using instrumental variables," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(1), pages 1-16, January.
    2. Heng Chen & Matthew Strathearn & Marcel Voia, 2021. "Consumer Cash Withdrawal Behaviour: Branch Networks and Online Financial Innovation," Staff Working Papers 21-28, Bank of Canada.
    3. Kun Xu & Yanyuan Ma & Liqun Wang, 2015. "Instrument Assisted Regression for Errors in Variables Models with Binary Response," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 104-117, March.

  6. Wang, Liqun & Hsiao, Cheng, 2011. "Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 165(1), pages 30-44.

    Cited by:

    1. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    2. Taraneh Abarin & Liqun Wang, 2012. "Instrumental variable approach to covariate measurement error in generalized linear models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(3), pages 475-493, June.
    3. Michele De Nadai & Arthur Lewbel, 2012. "Nonparametric Errors in Variables Models with Measurement Errors on both sides of the Equation," Boston College Working Papers in Economics 790, Boston College Department of Economics, revised 01 Jul 2013.
    4. Naoto Kunitomo & Michael McAleer & Yoshihiko Nishiyama, 2010. "Moment Restriction-based Econometric Methods: An Overview," KIER Working Papers 734, Kyoto University, Institute of Economic Research.
    5. Susanne M. Schennach, 2013. "Convolution without independence," CeMMAP working papers CWP46/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Kun Xu & Yanyuan Ma & Liqun Wang, 2015. "Instrument Assisted Regression for Errors in Variables Models with Binary Response," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 104-117, March.
    7. Andrei Zeleneev & Kirill Evdokimov, 2023. "Simple estimation of semiparametric models with measurement errors," CeMMAP working papers 10/23, Institute for Fiscal Studies.
    8. Kirill S. Evdokimov & Andrei Zeleneev, 2023. "Simple Estimation of Semiparametric Models with Measurement Errors," Papers 2306.14311, arXiv.org, revised Mar 2024.
    9. Jingxuan Luo & Lili Yue & Gaorong Li, 2023. "Overview of High-Dimensional Measurement Error Regression Models," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
    10. Anish Agarwal & Rahul Singh, 2021. "Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy," Papers 2107.02780, arXiv.org, revised Feb 2024.
    11. Zhang, Jun & Feng, Zhenghui & Zhou, Bu, 2014. "A revisit to correlation analysis for distortion measurement error data," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 116-129.
    12. ZINDE-WALSH, Victoria, 2007. "Errors-in-Variables Models : A Generalized Functions Approach," Cahiers de recherche 14-2007, Centre interuniversitaire de recherche en économie quantitative, CIREQ.

  7. Liqun Wang & Alexandre Leblanc, 2008. "Second-order nonlinear least squares estimation," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(4), pages 883-900, December.

    Cited by:

    1. S. Huda & Rahul Mukerjee, 2018. "Optimal designs with string property under asymmetric errors and SLS estimation," Statistical Papers, Springer, vol. 59(3), pages 1255-1268, September.
    2. Cheng Maolin & Jiang Zedi, 2016. "A New Class of Production Function Model and Its Application," Journal of Systems Science and Information, De Gruyter, vol. 4(2), pages 177-185, April.
    3. Taraneh Abarin & Liqun Wang, 2012. "Instrumental variable approach to covariate measurement error in generalized linear models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(3), pages 475-493, June.
    4. Wang, Liqun & Hsiao, Cheng, 2011. "Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 165(1), pages 30-44.
    5. Dedi Rosadi & Shelton Peiris, 2014. "Second-order least-squares estimation for regression models with autocorrelated errors," Computational Statistics, Springer, vol. 29(5), pages 931-943, October.
    6. Lucy L. Gao & Julie Zhou, 2017. "D-optimal designs based on the second-order least squares estimator," Statistical Papers, Springer, vol. 58(1), pages 77-94, March.
    7. Mustafa Salamh & Liqun Wang, 2021. "Second-Order Least Squares Method for Dynamic Panel Data Models with Application," JRFM, MDPI, vol. 14(9), pages 1-19, September.
    8. D. Rosadi & P. Filzmoser, 2019. "Robust second-order least-squares estimation for regression models with autoregressive errors," Statistical Papers, Springer, vol. 60(1), pages 105-122, February.
    9. He, Lei, 2018. "Optimal designs for multi-factor nonlinear models based on the second-order least squares estimator," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 201-208.
    10. Francesco Bravo, 2013. "Partially linear varying coefficient models with missing at random responses," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(4), pages 721-762, August.
    11. Xin Wang & Lingchen Kong & Liqun Wang, 2022. "Estimation of Error Variance in Regularized Regression Models via Adaptive Lasso," Mathematics, MDPI, vol. 10(11), pages 1-19, June.
    12. Lei He & Rong-Xian Yue, 2022. "$$I_L$$ I L -optimal designs for regression models under the second-order least squares estimator," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(1), pages 53-66, January.
    13. Maria Karlsson & Thomas Laitila, 2014. "Finite mixture modeling of censored regression models," Statistical Papers, Springer, vol. 55(3), pages 627-642, August.
    14. Mustafa Salamh & Liqun Wang, 2021. "Second-Order Least Squares Estimation in Nonlinear Time Series Models with ARCH Errors," Econometrics, MDPI, vol. 9(4), pages 1-17, November.
    15. Xin Chen & Min Tsao & Julie Zhou, 2012. "Robust second-order least-squares estimator for regression models," Statistical Papers, Springer, vol. 53(2), pages 371-386, May.
    16. Fei Jiang & Yanyuan Ma & J. Jack Lee, 2017. "A second-order semiparametric method for survival analysis, with application to an acquired immune deficiency syndrome clinical trial study," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 833-846, August.
    17. Chi-Kuang Yeh & Julie Zhou, 2021. "Properties of optimal regression designs under the second-order least squares estimator," Statistical Papers, Springer, vol. 62(1), pages 75-92, February.
    18. Cheng Maolin, 2016. "A Generalized Constant Elasticity of Substitution Production Function Model and Its Application," Journal of Systems Science and Information, De Gruyter, vol. 4(3), pages 269-279, June.
    19. Cheng Maolin & Shi Guojun & Han Yun, 2019. "A Modified CES Production Function Model and Its Application in Calculating the Contribution Rate of Energy and Other Influencing Factors to Economic Growth," Journal of Systems Science and Information, De Gruyter, vol. 7(2), pages 161-172, April.
    20. Mijeong Kim & Yanyuan Ma, 2012. "The efficiency of the second-order nonlinear least squares estimator and its extension," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(4), pages 751-764, August.
    21. Maolin Cheng, 2019. "A Grey CES Production Function Model and Its Application in Calculating the Contribution Rate of Economic Growth Factors," Complexity, Hindawi, vol. 2019, pages 1-8, April.

  8. Liqun Wang & James Fu, 2007. "A practical sampling approach for a Bayesian mixture model with unknown number of components," Statistical Papers, Springer, vol. 48(4), pages 631-653, October.

    Cited by:

    1. Wang, Liqun & Lee, Chel Hee, 2014. "Discretization-based direct random sample generation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1001-1010.

  9. Liqun Wang & Klaus Pötzelberger, 2007. "Crossing Probabilities for Diffusion Processes with Piecewise Continuous Boundaries," Methodology and Computing in Applied Probability, Springer, vol. 9(1), pages 21-40, March.

    Cited by:

    1. Zhiyong Jin & Liqun Wang, 2017. "First Passage Time for Brownian Motion and Piecewise Linear Boundaries," Methodology and Computing in Applied Probability, Springer, vol. 19(1), pages 237-253, March.
    2. Mario Abundo, 2010. "On the First Hitting Time of a One-dimensional Diffusion and a Compound Poisson Process," Methodology and Computing in Applied Probability, Springer, vol. 12(3), pages 473-490, September.
    3. Lee, Taeho, 2023. "Exact simulation for the first hitting time of Brownian motion and Brownian bridge," Statistics & Probability Letters, Elsevier, vol. 193(C).
    4. Hangsuck Lee & Hongjun Ha & Minha Lee, 2022. "Piecewise linear double barrier options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 125-151, January.
    5. Qinglai Dong & Lirong Cui, 2019. "First Hitting Time Distributions for Brownian Motion and Regions with Piecewise Linear Boundaries," Methodology and Computing in Applied Probability, Springer, vol. 21(1), pages 1-23, March.
    6. Hangsuck Lee & Hongjun Ha & Minha Lee, 2022. "Piecewise linear boundary crossing probabilities, barrier options, and variable annuities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2248-2272, December.
    7. Andrew N. Downes & Konstantin Borovkov, 2008. "First Passage Densities and Boundary Crossing Probabilities for Diffusion Processes," Methodology and Computing in Applied Probability, Springer, vol. 10(4), pages 621-644, December.

  10. Liqun Wang & Cheng Hsiao, 2007. "Two-stage estimation of limited dependent variable models with errors-in-variables," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 426-438, July.

    Cited by:

    1. Wang, Liqun & Hsiao, Cheng, 2011. "Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 165(1), pages 30-44.

  11. Wang, Liqun, 2002. "A simple adjustment for measurement errors in some limited dependent variable models," Statistics & Probability Letters, Elsevier, vol. 58(4), pages 427-433, July.

    Cited by:

    1. Wang, Liqun & Hsiao, Cheng, 2011. "Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 165(1), pages 30-44.
    2. Gibson, Fiona L. & Burton, Michael P., 2009. "Biased estimates in discrete choice models: the appropriate inclusion of psychometric data into the valuation of recycled wastewater," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47943, Australian Agricultural and Resource Economics Society.
    3. Gustavo Rocha & Reinaldo Arellano-Valle & Rosangela Loschi, 2015. "Maximum likelihood methods in a robust censored errors-in-variables model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(4), pages 857-877, December.

  12. James C. Fu & Liqun Wang, 2002. "A Random-Discretization Based Monte Carlo Sampling Method and its Applications," Methodology and Computing in Applied Probability, Springer, vol. 4(1), pages 5-25, March.

    Cited by:

    1. Antonio Punzo & Alessandro Zini, 2012. "Discrete approximations of continuous and mixed measures on a compact interval," Statistical Papers, Springer, vol. 53(3), pages 563-575, August.
    2. Liqun Wang & James Fu, 2007. "A practical sampling approach for a Bayesian mixture model with unknown number of components," Statistical Papers, Springer, vol. 48(4), pages 631-653, October.
    3. Wang, Liqun & Lee, Chel Hee, 2014. "Discretization-based direct random sample generation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1001-1010.

  13. Wang, Liqun, 1998. "Estimation of censored linear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 84(2), pages 383-400, June.

    Cited by:

    1. Xuejun Wang & Aiting Shen & Zhiyong Chen & Shuhe Hu, 2015. "Complete convergence for weighted sums of NSD random variables and its application in the EV regression model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 166-184, March.
    2. Yingyao Hu & Geert Ridder, 2005. "Estimation of Nonlinear Models with Mismeasured Regressors Using Marginal Information," IEPR Working Papers 05.39, Institute of Economic Policy Research (IEPR).
    3. Taraneh Abarin & Liqun Wang, 2012. "Instrumental variable approach to covariate measurement error in generalized linear models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(3), pages 475-493, June.
    4. Wang, Liqun & Hsiao, Cheng, 2011. "Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 165(1), pages 30-44.
    5. Stoker, Thomas M. & Berndt, Ernst R. & Denny Ellerman, A. & Schennach, Susanne M., 2005. "Panel data analysis of U.S. coal productivity," Journal of Econometrics, Elsevier, vol. 127(2), pages 131-164, August.
    6. Xiaohong Chen & Yingyao Hu, 2006. "Identification and Inference of Nonlinear Models Using Two Samples with Arbitrary Measurement Errors," Cowles Foundation Discussion Papers 1590, Cowles Foundation for Research in Economics, Yale University.
    7. Yu Miao & Fangfang Zhao & Ke Wang & Yanping Chen, 2013. "Asymptotic normality and strong consistency of LS estimators in the EV regression model with NA errors," Statistical Papers, Springer, vol. 54(1), pages 193-206, February.
    8. Hu, Yingyao, 2008. "Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution," Journal of Econometrics, Elsevier, vol. 144(1), pages 27-61, May.
    9. Song, Weixing & Yao, Weixin, 2011. "A lack-of-fit test in Tobit errors-in-variables regression models," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1792-1801.
    10. Geert Ridder & Yingyao Hu, 2004. "Estimation of Nonlinear Models with Measurement Error Using Marginal Information," Econometric Society 2004 North American Summer Meetings 21, Econometric Society.
    11. 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.
    12. Wang, Liqun, 2002. "A simple adjustment for measurement errors in some limited dependent variable models," Statistics & Probability Letters, Elsevier, vol. 58(4), pages 427-433, July.
    13. Schennach, Susanne M., 2008. "Quantile Regression With Mismeasured Covariates," Econometric Theory, Cambridge University Press, vol. 24(4), pages 1010-1043, August.
    14. Xuejun Wang & Yi Wu & Shuhe Hu, 2018. "Strong and weak consistency of LS estimators in the EV regression model with negatively superadditive-dependent errors," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(1), pages 41-65, January.
    15. Sukhbir Singh & Kanchan Jain & Suresh Sharma, 2014. "Replicated measurement error model under exact linear restrictions," Statistical Papers, Springer, vol. 55(2), pages 253-274, May.
    16. Chen, Xiaohong & Hong, Han & Tarozzi, Alessandro, 2008. "Semiparametric Efficiency in GMM Models of Nonclassical Measurement Errors, Missing Data and Treatment Effects," Working Papers 42, Yale University, Department of Economics.
    17. Gustavo Rocha & Reinaldo Arellano-Valle & Rosangela Loschi, 2015. "Maximum likelihood methods in a robust censored errors-in-variables model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(4), pages 857-877, December.
    18. ZINDE-WALSH, Victoria, 2007. "Errors-in-Variables Models : A Generalized Functions Approach," Cahiers de recherche 14-2007, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    19. Han Hong, 2010. "Comment for identification and estimation of nonlinear models using two samples with nonclassical measurement errors, by Carroll, Chen and Hu," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(4), pages 405-408.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-EXP: Experimental Economics (1) 2009-09-19

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