Multivariate ordered discrete response models
Abstract:
We introduce multivariate ordered discrete response models with general rectangular structures, which allow for two different layers of dependence across decision dimensions. From the perspective of behavioral economics, these non-lattice models correspond to broad bracketing in decision making, whereas lattice models, which researchers typically estimate in practice, correspond to narrow bracketing. In these models, we specify latent processes as a sum of an index of covariates and an unobserved error, with unobservables for different latent processes potentially correlated. We provide conditions that are sufficient for identification under the independence of errors and covariates and outline an estimation approach. We present simulations and empirical examples, focusing on popular probit specifications. We argue that our models can be useful in disentangling adverse selection and moral hazard in discrete choice models of insurance choice and healthcare usage and present an application to support that.
About Tatiana Komarova:
Tatiana Komarova is a Professor of Econometrics at the University of Manchester. Her recent work focuses on econometric approaches in auctions either with multiple projects or multiple stages, discrete choice models in multivariate settings, and econometric methods under privacy constraints on the data release.
Language: English
This is a free seminar. Registration is mandatory.
Supported by the Luxembourg National Research Fund (FNR) 17931929