How to Adjust for Nonignorable Nonresponse: Calibration, Heckit or FIML?

Fredrik Johansson
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Fredrik Johansson: Department of Economics, Postal: Uppsala University, P.O. Box 513, SE-751 20 Uppsala, Sweden

No 2007:22, Working Paper Series from Uppsala University, Department of Economics

Abstract: When a survey response mechanism depends on the variable of interest measured within the same survey and observed for only part of the sample, the situation is one of nonignorable nonresponse. Ignoring the nonresponse is likely to generate significant bias in the estimates. To solve this, one option is the joint modelling of the response mechanism and the variable of interest. Another option is to calibrate each observation with weights constructed from auxiliary data. In an application where earnings equations are estimated these approaches are compared to reference estimates based on large a Swedish register based data set without nonresponse.

Keywords: Earning equations; Nonignorable response mechanism; Calibration; Selection; Full-information maximum likelihood (search for similar items in EconPapers)
JEL-codes: C15 C24 C34 C42 J31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2007-08-22
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