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

Probability of contact, 1st year Model 1 Model 2 Model 3 Intercept 2.117** 2.109** 1.407** Salary 0.000** 0.000 0.000 Type of settlement Rural 0.090 0.092 Area Northern -0.726** -0.744** Western 0.640 0.652 Central 1.724** 1.735 Northeastern -0.021 -0.027 Gender Male -0.111 Age 0.019**

Probability of item response, 1st year Model 1 Model 2 Model 3 Intercept 3.449** 3.458** 3.251** Salary 0.000** 0.000** 0.000** Type of settlement Rural 0.383 0.833 Area Northern 0.346 0.307 Western -0.453 -0.482 Central 1.157 1.141 Northeastern -0.565 -0.556 Gender Male -0.433 Age 0.003

Quintile distribution, 1st year

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

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