Objectives. Most researchers who use survey data must grapple with the problem of how best to handle missing information. This article illustrates multiple imputation, a technique for estimating missing values in a multivariate setting. Methods. I use multiple imputation to estimate missing income data and update a recent study that examines the influence of parents’ standard of living on subjective well-being. Using data from the 1998 General Social Survey, two ordered probit models are estimated; one using complete cases only, and the other replacing missing income data with multiple imputation estimates. Results. The analysis produces two major findings: 1) parents’ standard of living is more important than suggested by the complete cases model, and 2) using multiple imputation can help to reduce standard errors. Conclusions. Multiple imputation allows a researcher to use more of the available data, thereby reducing biases that may occur when observations with missing data are simply deleted.
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Paper provided by Middle Tennessee State University, Department of Economics and Finance in its series Working Papers with number
200709.
Find related papers by JEL classification: A10 - General Economics and Teaching - - General Economics - - - General C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
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