Dimitrakopoulos, S (2018) Accounting for persistence in panel count data models. An application to the number of patents awarded. Economics Letters, 171. pp. 245-248. ISSN 0165-1765
Abstract
We propose a Poisson regression model that controls for three potential sources of persistence in panel count data; dynamics, latent heterogeneity and serial correlation in the idiosyncratic errors. We also account for the initial conditions problem. For model estimation, we develop a Markov Chain Monte Carlo algorithm. The proposed methodology is illustrated by a real example on the number of patents granted.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2018 Elsevier B.V. All rights reserved. All rights reserved. This is an author produced version of a paper published in Economics Letters. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Dynamics; Initial conditions; Latent heterogeneity; Markov Chain Monte Carlo; Panel count data; Serial correlation |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Economics Division (LUBS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Jan 2019 10:41 |
Last Modified: | 14 Feb 2020 01:39 |
Status: | Published |
Publisher: | Elsevier BV |
Identification Number: | 10.1016/j.econlet.2018.08.004 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:141637 |