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Non-Response Bias in Income Data Mari Toomse University of Essex Research topic • Non-response bias in annual income measures: – – – – Sources and mechanism of bias Predicting bias from survey data Relationship with measurement error Cumulative bias in a panel study Data • Estonian EU-SILC 2007 (Statistics on Income and Living Conditions) • Panel study on income • Comes with call record data • Linked on individual level to Tax and Customs Board register – Respondents AND – Non-respondent Research design I • Non-response bias – variable specific • Response process as a sequence of events – – – – – Case issued Address known Contact achieved Co-operation achieved Item response Research design II • Mechanisms causing these events are different • Assess the net effect of each processes • Annual salary data from the regiser • Linked to the outcome of the whole of the selected sample – New cases – Panel cases Mean salary 90,000 88,000 86,000 84,000 EEK 82,000 80,000 78,000 76,000 74,000 72,000 70,000 Total sample, frame error excluded Issued First year Address known Second year Contact made Third and fourth year HH interview completed Responded to the salary question Probability of contact, 1st year Intercept Salary Type of settlement Rural Area Northern Western Central Northeastern Gender Male Age Model 1 2.117** 0.000** Model 2 2.109** 0.000 Model 3 1.407** 0.000 0.090 0.092 -0.726** 0.640 1.724** -0.021 -0.744** 0.652 1.735 -0.027 -0.111 0.019** Probability of item response, 1st year Intercept Salary Type of settlement Rural Area Northern Western Central Northeastern Gender Male Age Model 1 3.449** 0.000** Model 2 3.458** 0.000** Model 3 3.251** 0.000** 0.383 0.833 0.346 -0.453 1.157 -0.565 0.307 -0.482 1.141 -0.556 -0.433 0.003 Quintile distribution, 1st year 25.0 20.0 % 15.0 10.0 5.0 0.0 Total sample, frame error excluded Issued Address known Contact made Lowest quintile Highest quintile HH interview completed Responded to the salary question Conclusions • There is a substantial negative net bias in annual salary estimates • Bias accumulates over the course of a panel • Main sources of bias are non-contact and item non-response • Bias due to non-contact is largerly explained away by basic grographical variables Thank you for your attention!