Friday, November 16, 2012

Identification of Panel Data Models With Attrition

Pierre Hoonhout
(ISEG, Technical University of Lisbon)

Abstract: Panel Surveys often suffer from a high degree of sample attrition between survey waves, a phenomenon that may have significant consequences for the representativeness of the panel. An unrepresentative panel leads to estimation results that suffer from selection bias. Selection bias can be avoided by using attrition models that are sufficiently unrestrictive to allow for a wide range of potential forms of selection. In this paper, I propose the Sequential Additively Nonignorable (SAN) attrition model. This model just-identifies the joint population distribution in Panel data with any number of waves. The identification requires the availability of refreshment samples. Just-identification means that the SAN model has no testable implications. In other words, less restrictive identified models do not exist.

Friday, November 16, 2012
Time: 11h00
Room: Sala Delta, Edificio Quelhas, ISEG