Identification in dynamic binary choice models

This paper studies identification in a binary choice panel data model with choice probabilities depending on a lagged outcome, additional observed regressors and an unobserved unit-specific effect. It is shown that with two consecutive periods of data identification is not possible (in a neighborhood of zero), even in the logistic case.

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Year of publication:	2023
Authors:	Chamberlain, Gary
Publisher:	London : Centre for Microdata Methods and Practice (cemmap)
Subject:	Panel Data \| Binary Choice \| Feedback \| Identification

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Series:	cemmap working paper ; CWP16/23
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	10.47004/wp.cem.2023.1623 [DOI] 1854017276 [GVK] hdl:10419/284140 [Handle]
Classification:	C23 - Models with Panel Data ; C33 - Models with Panel Data
Source:	EconStor

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014480457