How to Adjust for Nonignorable Nonresponse: Calibration, Heckit or FIML?
AbstractWhen 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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Bibliographic InfoPaper provided by Uppsala University, Department of Economics in its series Working Paper Series with number 2007:22.
Length: 25 pages
Date of creation: 22 Aug 2007
Date of revision:
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Earning equations; Nonignorable response mechanism; Calibration; Selection; Full-information maximum likelihood;
Find related papers by JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
- C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
- C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
- J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
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- 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.
- Mitali Das & Whitney K. Newey & Francis Vella, 2003.
"Nonparametric Estimation of Sample Selection Models,"
Review of Economic Studies,
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.
- Edin, P.-A. & Fredriksson, P., 2000.
"LINDA - Longitudinal INdividual DAta for Sweden,"
2000:19, Uppsala - Working Paper Series.
- Edin, Per-Anders & Fredriksson, Peter, 2000. "LINDA - Longitudinal INdividual DAta for Sweden," Working Paper Series 2000:19, Uppsala University, Department of Economics.
- Edin, P.-A. & Fredriksson, P., 2000. "LINDA - Longitudinal INdividual DAta for Sweden," Papers 2000-19, Uppsala - Working Paper Series.
- Heckman, James J, 1979.
"Sample Selection Bias as a Specification Error,"
Econometric Society, vol. 47(1), pages 153-61, January.
- 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.
- 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.
- Adrián Rubli, 2012. "La importancia de corregir por el sesgo de selección en el análisis de las brechas salariales por género: un estudio para Argentina, Brasil y México," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 1-36, November.
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