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Modelling Errors in Survey and Administrative Data on Employment Earnings: Sensitivity to the Fraction Assumed to Have Error-Free Earnings. (2020). Jenkins, Stephen ; Rios-Avila, Fernando.
In: IZA Discussion Papers.
RePEc:iza:izadps:dp13196.

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Cited: 8

Citations received by this document

Cites: 6

References cited by this document

Cocites: 50

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Coauthors: 0

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Citations

Citations received by this document

  1. Assessing data from summary questions about earnings and income. (2023). Crossley, Thomas ; Hussein, Omar ; Fisher, Paul.
    In: Labour Economics.
    RePEc:eee:labeco:v:81:y:2023:i:c:s0927537123000064.

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  2. A Model of Errors in BMI Based on Self-Reported and Measured Anthropometrics with Evidence from Brazilian Data. (2022). Jones, Andrew M ; de Oliveira, Victor Hugo ; Davillas, Apostolos.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp15380.

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  3. Underreporting of Top Incomes and Inequality: A Comparison of Correction Methods using Simulations and Linked Survey and Tax Data. (2022). Vigorito, Andrea ; Lustig, Nora ; Flachaire, Emmanuel.
    In: Post-Print.
    RePEc:hal:journl:hal-03879312.

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  4. Model of Errors in BMI Based on Self?reported and Measured Anthropometrics with Evidence from Brazilian Data. (2022). Jones, Andrew ; de Oliveira, Victor Hugo ; Davillas, Apostolos.
    In: CINCH Working Paper Series (since 2020).
    RePEc:ajt:wcinch:76143.

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  5. Measurement error in earnings data: Replication of Meijer, Rohwedder, and Wansbeeks mixture model approach to combining survey and register data. (2021). Jenkins, Stephen ; Avila, Fernando Rios ; Riosavila, Fernando.
    In: Journal of Applied Econometrics.
    RePEc:wly:japmet:v:36:y:2021:i:4:p:474-483.

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  6. Reconciling Reports: Modelling Employment Earnings and Measurement Errors Using Linked Survey and Administrative Data. (2021). Rios-Avila, Fernando ; Jenkins, Stephen.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp14405.

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  7. Finite Mixture Models for Linked Survey and Administrative Data: Estimation and Post-estimation. (2021). Rios-Avila, Fernando ; Jenkins, Stephen.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp14404.

    Full description at Econpapers || Download paper

References

References cited by this document

  1. Abowd, J. and Stinson, M. (2013). Estimating measurement error in annual job earnings: a comparison of survey and administrative data. Review of Economics and Statistics, 95, 1451–1467.

  2. Bollinger, C. R., Hirsch, B. T., Hokayem, C. M., and Ziliak, J. P. (2018). The good, the bad and the ugly: measurement error, non-response and administrative mismatch in the CPS. Working Paper, Gatton College of Business, University of Kentucky.
    Paper not yet in RePEc: Add citation now

  3. Department for Work and Pensions (2013). Family Resources Survey United Kingdom, 2011/12. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_ data/file/206887/frs_2011_12_report.pdf Hyslop, D. R. and Townsend, W. (2020). Earnings dynamics and measurement error in matched survey and administrative data. Journal of Business and Economic Statistics, 38, 457– 469.

  4. Jenkins, S. P. and Rios-Avila, F. (2020). Measurement error in UK survey and administrative data on gross labour earnings. Unpublished paper, LSE.
    Paper not yet in RePEc: Add citation now

  5. Kapteyn, A. and Ypma, J. Y. (2007). Measurement error and misclassification: a comparison of survey and administrative data. Journal of Labor Economics, 25, 513–551.

  6. Meijer, E., Rohwedder, S., and Wansbeek, T. (2012). Measurement error in earnings data: using a mixture model approach to combine survey and register data. Journal of Business and Economic Statistics, 30, 191–201.

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    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp13196.

    Full description at Econpapers || Download paper

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