A binary choice model with partial observability for panel data

Author:

Batalova Ekaterina1,Furmanov Kirill1,Shelkova Ekaterina2

Affiliation:

1. The National Research University Higher School of Economics, Moscow, Russia

2. Deloitte, Risk Advisory Department Moscow, Russia

Abstract

We consider a panel model with a binary response variable that is a product of two unobservable factors, each determined by a separate binary choice equation. One of these factors is assumed to be time-invariant and may be interpreted as a latent class indicator. A simulation study shows that maximum likelihood estimates from even the shortest panel are much more reliable than those obtained from a cross-section. As an illustrative example, the model is applied to Russian Longitudinal Monitoring Survey data to estimate a proportion of the non-employed population who are participating in job search.

Publisher

IOS Press

Subject

Applied Mathematics,Modelling and Simulation,Statistics and Probability

Reference21 articles.

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2. Statistical analysis of variable-structure models;Aivazian;Applied Econometrics,2015

3. Nonparametric methods for multivariate classification: Binary case;Aivazian;In Proceeding of IX International Workshop “Multivariate Statistics and Econometrics”,2016

4. Job search in Russia: A split-population model;Batalova;HSE Economic Journal,2018

5. The Split Population Logit (SPopLogit): Modeling Measurement Bias in Binary Data

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