Selection Bias: More than a Female Phenomenon

Advances in Econometrics and Modelling, Kluwer Academic Publishers, 1989

University of Alberta School of Business Research Paper No. 2013-269

Posted: 28 May 2013 Last revised: 30 May 2013

See all articles by Alice Orcutt Nakamura

Alice Orcutt Nakamura

University of Alberta - School of Business

Masao Nakamura

University of British Columbia (UBC) - Sauder School of Business

Date Written: October 3, 1988

Abstract

When a regression model is estimated using a censored subset of observations, coefficient estimates may be biased. Censored regression models have a long history in biometrics, engineering and other areas of applied statistics. The interest of economists in these models was stimulated by Tobin’s work on durable goods consumption in the late 1950s. It was Heckman’s publication of a simple two-step procedure for estimating censored regression models, however, that led to their widespread usage in applied econometric studies. Although this is not necessarily the best method for estimating all censored regression models, it has certain attractive properties. An understanding of this method is vital to the proper interpretation of the wealth of applied studies based on this approach. Also, valuable insights into the basic nature of sample selection problems can be gained from the formulation of the censored regression model popularized by Heckman.

We begin by exploring the estimation problems resulting from censoring and from certain properties of Heckman’s two-step estimation method. Procedures are developed for assessing the nature and extent of problems resulting from censoring; these procedures are then applied in an empirical analysis of the wage rates and hours of work of individuals in 10 different demographic groups using data from the Panel Study of Income Dynamics. One of our findings is that estimation using censored data can lead to bias and other related problems even when the degree of censoring is slight.

Suggested Citation

Nakamura, Alice Orcutt and Nakamura, Masao, Selection Bias: More than a Female Phenomenon (October 3, 1988). Advances in Econometrics and Modelling, Kluwer Academic Publishers, 1989, University of Alberta School of Business Research Paper No. 2013-269, Available at SSRN: https://ssrn.com/abstract=2270774

Alice Orcutt Nakamura (Contact Author)

University of Alberta - School of Business ( email )

2-32C Business Building
Edmonton, Alberta T6G 2R6
Canada

Masao Nakamura

University of British Columbia (UBC) - Sauder School of Business ( email )

2053 Main Mall
Vancouver, BC V6T 1Z2
Canada
604-822-8434 (Phone)
604-822-8477 (Fax)

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