Correcting for Truncation Bias Caused by a Latent Truncation Variable / David E. Bloom, Mark R. Killingsworth.

Format:

Book

Author/Creator:

Bloom, David E. (David Elliot), 1955-

Contributor:

National Bureau of Economic Research.

Killingsworth, Mark R., 1946-

Series:

Technical Working Paper Series (National Bureau of Economic Research) no. t0038.

NBER technical working paper series no. t0038

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 1984.

Summary:

We discuss estimation of the model Y[sub i] = X[sub i]b[sub y] + e[sub Yi] and T[sub i] =X[sub i]b[sub T] + e[sub Ti] when data on the continuous dependent variable Y and on the independent variables X are observed if the "truncation variable" T > 0 and when T is latent. This case is distinct from both (i) the "censored sample" case, in which Y data are available if T > 0, T is latent and X data are available for all observations, and (ii) the "observed truncation variable" case, in which both Y and X are observed if T > 0 and in which the actual value of T is observed whenever T > O. We derive a maximum-likelihood procedure for estimating this model and discuss identification and estimation.

Notes:

Print version record

June 1984.