<abstract xmlns="http://www.w3.org/1999/xhtml"><p>We use work histories retrospectively reported and matched to register data from the Swedish unemployment office to assess: 1) the prevalence of measurement error in reported spells of unemployment; 2) the impact of using such spells as the response variable of an exponential model; and 3) strategies for the adjustment of the measurement error. Due to the omission or misclassification of spells in work histories we cannot carry out typical adjustments for memory failures based on multiplicative models. Instead we suggest an adjustment method based on a mixture Bayesian model capable of differentiating between misdated spells and those for which the observed and true durations are unrelated. This adjustment is applied in two manners, one assuming access to a validation subsample and another relying on a strong prior for the mixture mechanism. Both solutions demonstrate a substantial reduction in the vast biases observed in the regression coefficients of the exponential model when survey data is used.</p></abstract>

We use work histories retrospectively reported and matched to register data from the Swedish unemployment office to assess: 1) the prevalence of measurement error in reported spells of unemployment; 2) the impact of using such spells as the response variable of an exponential model; and 3) strategies for the adjustment of the measurement error. Due to the omission or misclassification of spells in work histories we cannot carry out typical adjustments for memory failures based on multiplicative models. Instead we suggest an adjustment method based on a mixture Bayesian model capable of differentiating between misdated spells and those for which the observed and true durations are unrelated. This adjustment is applied in two manners, one assuming access to a validation subsample and another relying on a strong prior for the mixture mechanism. Both solutions demonstrate a substantial reduction in the vast biases observed in the regression coefficients of the exponential model when survey data is used.

Adjusting for Measurement Error in Retrospectively Reported Work Histories: An Analysis Using Swedish Register Data

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

We use work histories retrospectively reported and matched to register data from the Swedish unemployment office to assess: 1) the prevalence of measurement...

Adjusting for Measurement Error in Retrospectively Reported Work Histories: An Analysis Using Swedish Register Data

Data publikacji: 26 mar 2019

Zakres stron: 203 - 229

Otrzymano: 01 lip 2017

Przyjęty: 01 sie 2018

DOI: https://doi.org/10.2478/jos-2019-0010

Słowa kluczowe
Bayesian statistics, measurement error, mixture model, retrospective data, unemployment

© 2019 Jose Pina-Sánchez et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Adjusting for Measurement Error in Retrospectively Reported Work Histories: An Analysis Using Swedish Register Data

Data publikacji: 26 mar 2019

Zakres stron: 203 - 229

Otrzymano: 01 lip 2017

Przyjęty: 01 sie 2018

DOI: https://doi.org/10.2478/jos-2019-0010

Słowa kluczoweBayesian statistics, measurement error, mixture model, retrospective data, unemployment

© 2019 Jose Pina-Sánchez et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
Bayesian statistics, measurement error, mixture model, retrospective data, unemployment