How to Adjust for Nonignorable Nonresponse: Calibration, Heckit or FIML?
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.
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- Daniel S. Hamermesh & Stephen G. Donald, 2004. "The Effect of College Curriculum on Earnings: Accounting for Non-Ignorable Non-Response Bias," NBER Working Papers 10809, National Bureau of Economic Research, Inc.
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Oxford University Press, vol. 70(1), pages 33-58.
- Mitali Das & Whitney K. Newey & Francis Vella, 2003. "Nonparametric Estimation of Sample Selection Models," Review of Economic Studies, Wiley Blackwell, vol. 70(1), pages 33-58, January.
- Johansson, Fredrik & Klevmarken, Anders, 2006. "Explaining the size and nature of response in a survey on health status and economic standard," Working Paper Series 2006:2, Uppsala University, Department of Economics.
- Edin, Per-Anders & Fredriksson, Peter, 2000.
"LINDA - Longitudinal INdividual DAta for Sweden,"
Working Paper Series
2000:19, Uppsala University, Department of Economics.
- Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
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