ScholarLens Back to search
1995•Journal of Economic SurveysRequires access

RECENT DEVELOPMENTS IN COUNT DATA MODELLING: THEORY AND APPLICATION

Rainer Winkelmann, Klaus Zimmermann

Open publisher page 253 citations

Abstract

Abstract. This paper deals with statistical methods for modelling individual behavior when the endogenous variable is a nonnegative integer. Examples are the number of children, the number of job changes or the number of shopping trips in a given period. Several approaches—Poisson, robust Poisson, negative binomial (NEGBIN), NEGBINk, hurdle Poisson, truncated‐at‐zero Poisson—are discussed with a focus on specification, estimation, and testing. An application to labor mobility data illustrates the gain obtained by carefully taking into account the specific structure of the data.

About this research paper

What this paper is about

Abstract. This paper deals with statistical methods for modelling individual behavior when the endogenous variable is a nonnegative integer. Examples are the number of children, the number of job changes or the number of shopping trips in a given period. Several approaches—Poisson, robust Poisson, negative binomial (NEGBIN), NEGBINk, hurdle Poisson, truncated‐at‐zero Poisson—are discussed with a focus on specification, estimation, and testing. An application to labor mobility data illustrates the gain obtained by carefully taking into account the specific structure of the data.

Why it matters

OpenAlex reports 253 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Abstract. This paper deals with statistical methods for modelling individual behavior when the endogenous variable is a nonnegative integer. Examples are the number of children, the number of job changes or the number of shopping trips in a given period. Several approaches—Poisson, robust Poisson, negative binomial (NEGBIN), NEGBINk, hurdle Poisson, truncated‐at‐zero Poisson—are discussed with a focus on specification, estimation, and testing. An application to labor mobility data illustrates the gain obtained by carefully taking into account the specific structure of the data.

Key concepts: Count data, Negative binomial distribution, Poisson distribution, Quasi-likelihood, Econometrics, Poisson regression, Focus (optics), Mathematics

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
RECENT DEVELOPMENTS IN COUNT DATA MODELLING: THEORY AND APPLICATION — Research Paper | ScholarLens