EconPapers    
Economics at your fingertips  
 

Discrete Poisson kernel density estimation-with an application to wildcat coal strikes

Lawrence Marsh and Kajal Mukhopadhyay

Applied Economics Letters, 1999, vol. 6, issue 6, 393-396

Abstract: This paper proposes a nonparametric Poisson kernel density estimation technique for discrete distributions. Economists have been using continuous kernels to approximate discrete distributions. This work introduces a discrete kernel as more appropriate for approximating discrete distributions. Simulation results are presented to compare with standard parametric approaches. We apply our discrete Poisson kernel estimator to approximate the distribution of coal mine wildcat strikes in the United States.

Date: 1999
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.informaworld.com/openurl?genre=article& ... 40C6AD35DC6213A474B5 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:apeclt:v:6:y:1999:i:6:p:393-396

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20

DOI: 10.1080/135048599353168

Access Statistics for this article

Applied Economics Letters is currently edited by Anita Phillips

More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:apeclt:v:6:y:1999:i:6:p:393-396