Score-driven dynamic patent count panel data models
type: Item
instance of: scholarly article
title: Score-driven dynamic patent count panel data models
zbMATH Open document ID: 1490.62422
author: Szabolcs Blazsek
author: Alvaro Escribano
published in: Economics Letters
publication date: 2018-08-29T00:00:00Z
full work available at URL: http://hdl.handle.net/10016/25168
Mathematics Subject Classification ID: 62P20
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62F12
zbMATH DE Number: 6928534
zbMATH Keywords: research and development
zbMATH Keywords: patent count panel data
zbMATH Keywords: dynamic conditional score
zbMATH Keywords: quasi-maximum likelihood
MaRDI profile type: Publication
OpenAlex ID: W2521081486
cites work: Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations
cites work: Knowledge spillovers in US patents: a dynamic patent intensity model with secret common innovation factors
cites work: Patent propensity, R\&D and market competition: dynamic spillovers of innovation leaders and followers
cites work: Individual effects and dynamics in count data models.
cites work: Efficiency Bounds for Semiparametric Regression
cites work: Observation-driven models for Poisson counts
cites work: Maximum likelihood estimation for an observation driven model for Poisson counts
cites work: Pseudo Maximum Likelihood Methods: Theory
cites work: Pseudo Maximum Likelihood Methods: Applications to Poisson Models
cites work: Q4840212
cites work: Dynamic models for volatility and heavy tails. With applications to financial and economic time series
cites work: Q2995585
DOI: 10.1016/J.ECONLET.2016.10.026
description: scientific article; zbMATH DE number 6928534