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Recent Advances in the Measurement Error Literature
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Cited by:
- Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2022.
"Estimation of varying coefficient models with measurement error,"
Journal of Econometrics, Elsevier, vol. 230(2), pages 388-415.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Estimation of Varying Coefficient Models with Measurement Error," Departmental Working Papers 1905, Southern Methodist University, Department of Economics.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Estimation of Varying Coefficient Models with Measurement Error," STICERD - Econometrics Paper Series 607, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2022. "Estimation of varying coefficient models with measurement error," LSE Research Online Documents on Economics 108147, London School of Economics and Political Science, LSE Library.
- De Neve, Jan-Walter & Fink, Günther, 2018. "Children’s education and parental old age survival – Quasi-experimental evidence on the intergenerational effects of human capital investment," Journal of Health Economics, Elsevier, vol. 58(C), pages 76-89.
- Yingyao Hu & Zhongjian Lin, 2018. "Misclassification and the hidden silent rivalry," CeMMAP working papers CWP12/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
- Hahn, Jinyong & Hausman, Jerry & Kim, Jeonghwan, 2021. "A small sigma approach to certain problems in errors-in-variables models," Economics Letters, Elsevier, vol. 208(C).
- Richard Murphy & Felix Weinhardt, 2020.
"Top of the Class: The Importance of Ordinal Rank,"
The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(6), pages 2777-2826.
- Murphy, Richard & Weinhardt, Felix, 2020. "Top of the Class: The Importance of Ordinal Rank," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 87(6), pages 2777-2826.
- Richard Murphy & Felix Weinhardt, 2014. "Top of the Class: The Importance of Ordinal Rank," CESifo Working Paper Series 4815, CESifo.
- Murphy, Richard & Weinhardt, Felix, 2020. "Top of the class: the importance of ordinal rank," LSE Research Online Documents on Economics 105077, London School of Economics and Political Science, LSE Library.
- Murphy, Richard, & Weinhardt, Felix, 2019. "Top of the Class: The Importance of Ordinal Rank," Rationality and Competition Discussion Paper Series 194, CRC TRR 190 Rationality and Competition.
- Richard Murphy & Felix Weinhardt, 2018. "Top of the Class: The Importance of Ordinal Rank," NBER Working Papers 24958, National Bureau of Economic Research, Inc.
- Weinhardt, Felix & Murphy, Richard, 2016. "Top of the Class: The Importance of Ordinal Rank," VfS Annual Conference 2016 (Augsburg): Demographic Change 145626, Verein für Socialpolitik / German Economic Association.
- Christian Gourieroux & Joann Jasiak, 2023. "Dynamic deconvolution and identification of independent autoregressive sources," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 151-180, March.
- Takahide Yanagi, 2019.
"Inference on local average treatment effects for misclassified treatment,"
Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 938-960, September.
- YANAGI, Takahide & 柳, 貴英, 2017. "Inference on Local Average Treatment Effects for Misclassified Treatment," Discussion Papers 2017-02, Graduate School of Economics, Hitotsubashi University.
- Takahide Yanagi, 2018. "Inference on Local Average Treatment Effects for Misclassified Treatment," Papers 1804.03349, arXiv.org.
- Zhang, Han, 2021. "How Using Machine Learning Classification as a Variable in Regression Leads to Attenuation Bias and What to Do About It," SocArXiv 453jk, Center for Open Science.
- Hao, Zhuang & Zhang, Xudong & Wang, Yuze, 2024. "Assessing the accuracy of self-reported health expenditure data: Evidence from two public surveys in China," Social Science & Medicine, Elsevier, vol. 356(C).
- Carletto,Calogero & Dillon,Andrew S. & Zezza,Alberto, 2021. "Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage," Policy Research Working Paper Series 9745, The World Bank.
- Pablo Mitnik, 2018. "Estimating the Intergenerational Elasticity of Expected Income with Short-Run Income Measures: A Generalized Error-in-Variables Model," Working Papers 2018-045, Human Capital and Economic Opportunity Working Group.
- Hu, Yingyao & Schennach, Susanne & Shiu, Ji-Liang, 2022. "Identification of nonparametric monotonic regression models with continuous nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 226(2), pages 269-294.
- Andrew Chesher & Adam Rosen, 2018.
"Generalized instrumental variable models, methods, and applications,"
CeMMAP working papers
CWP43/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Andrew Chesher & Adam Rosen, 2019. "Generalized Instrumental Variable Models, Methods, and Applications," CeMMAP working papers CWP41/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Hu, Yingyao, 2021. "Identification of Causal Models with Unobservables: A Self-Report Approach," Economics Working Paper Archive 64330, The Johns Hopkins University,Department of Economics.
- Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
- 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.
- Mochen Yang & Edward McFowland III & Gordon Burtch & Gediminas Adomavicius, 2020. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," Papers 2012.10790, arXiv.org.
- Bastianin, Andrea & Castelnovo, Paolo & Florio, Massimo, 2017.
"The empirics of regulatory reforms proxied by categorical variables: recent findings and methodological issues,"
MPRA Paper
78256, University Library of Munich, Germany.
- Andrea Bastianin & Paolo Castelnovo & Massimo Florio, 2018. "Evaluating regulatory reform of network industries: a survey of empirical models based on categorical proxies," Papers 1810.03348, arXiv.org.
- Andrea Bastianin & Paolo Castelnovo & Massimo Florio, 2017. "The Empirics of Regulatory Reforms Proxied by Categorical Variables: Recent Findings and Methodological Issues," Working Papers 2017.22, Fondazione Eni Enrico Mattei.
- Andrea Bastianin & Paolo Castelnovo & Massimo Florio, 2017. "The Empirics of Regulatory Reforms Proxied by Categorical Variables: Recent Findings and Methodological Issues," ETA: Economic Theory and Applications 257877, Fondazione Eni Enrico Mattei (FEEM).
- Flavio Cunha & Irma Elo & Jennifer Culhane, 2021. "Maternal Subjective Expectations about the Technology of Skill Formation Predict Investments in Children One Year Later," Working Papers 2021-018, Human Capital and Economic Opportunity Working Group.
- van Bergeijk, P.A.G., 2017. "Measurement error of global production," ISS Working Papers - General Series 632, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
- Gilles E. Gignac & Elizabeth Ooi, 2022. "Measurement error in research on financial literacy: How much error is there and how does it influence effect size estimates?," Journal of Consumer Affairs, Wiley Blackwell, vol. 56(2), pages 938-956, June.
- Eric Blankmeyer, 2018. "Measurement Errors as Bad Leverage Points," Papers 1807.02814, arXiv.org, revised Mar 2020.
- Lin, Zhongjian & Hu, Yingyao, 2024. "Binary choice with misclassification and social interactions, with an application to peer effects in attitude," Journal of Econometrics, Elsevier, vol. 238(1).
- Daniel Wilhelm, 2018.
"Testing for the presence of measurement error,"
CeMMAP working papers
CWP45/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Daniel Wilhelm, 2019. "Testing for the presence of measurement error," CeMMAP working papers CWP48/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Daniel Wilhelm, 2019. "Testing for the Presence of Measurement Error," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-18, Economic Statistics Centre of Excellence (ESCoE).
- Nagasawa, Kenichi, 2020. "Identification and Estimation of Group-Level Partial Effects," The Warwick Economics Research Paper Series (TWERPS) 1243, University of Warwick, Department of Economics.
- Aurélie Bertrand & Ingrid Van Keilegom & Catherine Legrand, 2019. "Flexible parametric approach to classical measurement error variance estimation without auxiliary data," Biometrics, The International Biometric Society, vol. 75(1), pages 297-307, March.
- Hao Dong & Yuya Sasaki, 2022.
"Estimation of average derivatives of latent regressors: with an application to inference on buffer-stock saving,"
Departmental Working Papers
2204, Southern Methodist University, Department of Economics.
- Hao Dong & Yuya Sasaki, 2022. "Estimation of Average Derivatives of Latent Regressors: With an Application to Inference on Buffer-Stock Saving," Papers 2209.05914, arXiv.org.
- JoonHwan Cho & Yao Luo & Ruli Xiao, 2022. "Deconvolution from Two Order Statistics," Working Papers tecipa-739, University of Toronto, Department of Economics.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2023.
"Bandwidth selection for nonparametric regression with errors-in-variables,"
Econometric Reviews, Taylor & Francis Journals, vol. 42(4), pages 393-419, April.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2021. "Bandwidth Selection for Nonparametric Regression with Errors-in-Variables," Departmental Working Papers 2104, Southern Methodist University, Department of Economics.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2022. "Bandwidth selection for nonparametric regression with errors-in-variables," STICERD - Econometrics Paper Series 620, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2023. "Bandwidth selection for nonparametric regression with errors-in-variables," LSE Research Online Documents on Economics 115551, London School of Economics and Political Science, LSE Library.
- Hao Dong & Daniel L. Millimet, 2020.
"Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions,"
JRFM, MDPI, vol. 13(11), pages 1-24, November.
- Dong, Hao & Millimet, Daniel L., 2020. "Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions," IZA Discussion Papers 13893, Institute of Labor Economics (IZA).
- Hao Dong & Daniel L. Millimet, 2020. "Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions," Departmental Working Papers 2013, Southern Methodist University, Department of Economics.
- Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
- Kyle L Marquardt, 2020. "How and how much does expert error matter? Implications for quantitative peace research," Journal of Peace Research, Peace Research Institute Oslo, vol. 57(6), pages 692-700, November.
- Hong Li & Qifan Song & Jianxi Su, 2021. "Robust estimates of insurance misrepresentation through kernel quantile regression mixtures," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(3), pages 625-663, September.
- Chen, Linkun & Clarke, Philip M. & Petrie, Dennis J. & Staub, Kevin E., 2021.
"The effects of self-assessed health: Dealing with and understanding misclassification bias,"
Journal of Health Economics, Elsevier, vol. 78(C).
- Cheny, L.; & Clarke, P.M.; & Petrie, D.J.; & Staub, K.E.;, 2018. "The effects of self-assessed health: Dealing with and understanding misclassification bias," Health, Econometrics and Data Group (HEDG) Working Papers 18/26, HEDG, c/o Department of Economics, University of York.
- Aguiar, Victor H. & Kashaev, Nail & Allen, Roy, 2023.
"Prices, profits, proxies, and production,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 666-693.
- Victor H. Aguiar & Nail Kashaev & Roy Allen, 2018. "Prices, Profits, Proxies, and Production," Papers 1810.04697, arXiv.org, revised Jun 2022.
- Victor H. Aguiar & Roy Allen & Nail Kashaev, 2020. "Prices, Profits, Proxies, and Production," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20202, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
- Victor H. Aguiar & Nail Kashaev & Roy Allen, 2022. "Prices, Profits, Proxies, and Production," University of Western Ontario, Departmental Research Report Series 20226, University of Western Ontario, Department of Economics.
- Batarce, Marco, 2024. "Estimation of discrete choice models with error in variables: An application to revealed preference data with aggregate service level variables," Transportation Research Part B: Methodological, Elsevier, vol. 185(C).
- Öberg, Stefan, 2021. "Treatment for natural experiments: How to improve causal estimates using conceptual definitions and substantive interpretations," SocArXiv pkyue, Center for Open Science.
- Aguiar, Victor H. & Serrano, Roberto, 2017. "Slutsky matrix norms: The size, classification, and comparative statics of bounded rationality," Journal of Economic Theory, Elsevier, vol. 172(C), pages 163-201.
- Mohamed Doukali & Xiaojun Song & Abderrahim Taamouti, 2024.
"Value‐at‐Risk under Measurement Error,"
Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 690-713, June.
- Mohamed Doukali & Xiaojun Song & Abderrahim Taamouti, 2022. "Value-at Risk under Measurement Error," Working Papers 202209, University of Liverpool, Department of Economics.
- Vitor Possebom, 2021. "Crime and Mismeasured Punishment: Marginal Treatment Effect with Misclassification," Papers 2106.00536, arXiv.org, revised Jul 2023.
- Dong, Hao & Millimet, Daniel L., 2023. "Embrace the Noise: It Is OK to Ignore Measurement Error in a Covariate, Sometimes," IZA Discussion Papers 16508, Institute of Labor Economics (IZA).
- Peter A.G. van Bergeijk, 2017. "Making Data Measurement Errors Transparent: The Case of the IMF," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 18(3), pages 133-154, July.
- Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
- Lenin Arango-Castillo & Francisco J. Martínez-Ramírez & María José Orraca, 2024. "Univariate Measures of Persistence: A Comparative Analysis," Working Papers 2024-11, Banco de México.
- Dong, Hao & Taylor, Luke, 2022.
"Nonparametric Significance Testing In Measurement Error Models,"
Econometric Theory, Cambridge University Press, vol. 38(3), pages 454-496, June.
- Hao Dong & Luke Taylor, 2020. "Nonparametric Significance Testing in Measurement Error Models," Departmental Working Papers 2003, Southern Methodist University, Department of Economics.
- Erik Meijer & Edward Oczkowski & Tom Wansbeek, 2021. "How measurement error affects inference in linear regression," Empirical Economics, Springer, vol. 60(1), pages 131-155, January.
- Martin T. Bohl & Nicole Branger & Mark Trede, 2019. "Measurement Errors in Index Trader Positions Data: Is the Price Pressure Hypothesis Still Invalid?," CQE Working Papers 8019, Center for Quantitative Economics (CQE), University of Muenster.
- Tom Boot & Art=uras Juodis, 2023. "Uniform Inference in Linear Error-in-Variables Models: Divide-and-Conquer," Papers 2301.04439, arXiv.org.
- Li, Siran & Zheng, Xunjie, 2020. "A generalization of Lemma 1 in Kotlarski (1967)," Statistics & Probability Letters, Elsevier, vol. 165(C).
- Schennach, Susanne M., 2019.
"Convolution without independence,"
Journal of Econometrics, Elsevier, vol. 211(1), pages 308-318.
- Susanne M. Schennach, 2013. "Convolution without independence," CeMMAP working papers CWP46/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Susanne M. Schennach, 2013. "Convolution without independence," CeMMAP working papers 46/13, Institute for Fiscal Studies.
- Bastianin, Andrea & Castelnovo, Paolo & Florio, Massimo, 2018.
"Evaluating regulatory reform of network industries: a survey of empirical models based on categorical proxies,"
Utilities Policy, Elsevier, vol. 55(C), pages 115-128.
- Andrea Bastianin & Paolo Castelnovo & Massimo Florio, 2018. "Evaluating regulatory reform of network industries: a survey of empirical models based on categorical proxies," Papers 1810.03348, arXiv.org.
- Evan S. Totty & Thor Watson, 2024.
"Privacy Protection and Accuracy: What Do We Know? Do We Know Things?? Let's Find Out!,"
NBER Chapters, in: Data Privacy Protection and the Conduct of Applied Research: Methods, Approaches and their Consequences,
National Bureau of Economic Research, Inc.
- Evan S. Totty & Thor Watson, 2024. "Privacy Protection and Accuracy: What Do We Know? Do We Know Things?? Let's Find Out!," NBER Working Papers 32989, National Bureau of Economic Research, Inc.
- Bertrand, Aurelie & Van Keilegom, Ingrid & Legrand, Catherine, 2017. "Flexible parametric approach to classical measurement error variance estimation without auxiliary data," LIDAM Discussion Papers ISBA 2017025, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Naqib Ullah Khan & Peng Zhongyi & Heesup Han & Antonio Ariza-Montes, 2023. "Linking public leadership and public project success: the mediating role of team building," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
- Cunha, Flávio & Elo, Irma & Culhane, Jennifer, 2022. "Maternal subjective expectations about the technology of skill formation predict investments in children one year later," Journal of Econometrics, Elsevier, vol. 231(1), pages 3-32.
- Kato, Kengo & Sasaki, Yuya, 2018. "Uniform confidence bands in deconvolution with unknown error distribution," Journal of Econometrics, Elsevier, vol. 207(1), pages 129-161.
- Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
- Marica Valente & Timm Gries & Lorenzo Trapani, 2023. "Informal employment from migration shocks," Working Papers 2023-09, Faculty of Economics and Statistics, Universität Innsbruck.
- Young Jun Lee & Daniel Wilhelm, 2020.
"Testing for the presence of measurement error in Stata,"
Stata Journal, StataCorp LP, vol. 20(2), pages 382-404, June.
- Young Jun Lee & Daniel Wilhelm, 2018. "Testing for the presence of measurement error in Stata," CeMMAP working papers CWP51/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Young Jun Lee & Daniel Wilhelm, 2019. "Testing for the presence of measurement error in Stata," CeMMAP working papers CWP47/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.