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Earnings nonresponse in household surveys is widespread, yet there is limited knowledge of how nonresponse biases earnings measures. We examine the consequences of nonresponse on earnings gaps and inequality using Current Population Survey individual records linked to administrative earnings...
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Earnings nonresponse in the Current Population Survey is roughly 30% in the monthly surveys and 20% in the annual March survey. Even if nonresponse is random, severe bias attaches to wage equation coefficient estimates on attributes not matched in the earnings imputation hot deck. If nonresponse...
Persistent link: https://www.econbiz.de/10008758099
Earnings nonresponse in the Current Population Survey is roughly 30% in the monthly surveys and 20% in the annual March survey. Even if nonresponse is random, severe bias attaches to wage equation coefficient estimates on attributes not matched in the earnings imputation hot deck. If nonresponse...
Persistent link: https://www.econbiz.de/10009377090
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Earnings nonresponse in household surveys is widespread, yet there is limited knowledge of how nonresponse biases earnings measures. We examine the consequences of nonresponse on earnings gaps and inequality using Current Population Survey individual records linked to administrative earnings...
Persistent link: https://www.econbiz.de/10012912743
Earnings nonresponse in household surveys is widespread, yet there is limited knowledge of how nonresponse biases earnings measures. We examine the consequences of nonresponse on earnings gaps and inequality using Current Population Survey individual records linked to administrative earnings...
Persistent link: https://www.econbiz.de/10012906992
Earnings nonresponse in the Current Population Survey is roughly 30% in the monthly surveys and 20% in the annual March survey. Even if nonresponse is random, severe bias attaches to wage equation coefficient estimates on attributes not matched in the earnings imputation hot deck. If nonresponse...
Persistent link: https://www.econbiz.de/10013135391