EconPapers    
Economics at your fingertips  
 

Even Count Estimation

Laszlo Balazsi, Felix Chan and Laszlo Matyas ()

No 2018_2, CEU Working Papers from Department of Economics, Central European University

Abstract: This paper proposes a new estimation procedure called Event Count Estimator (ECE). The estimator is straightforward to implement and it is robust against outliers, censoring and excess zeros in the data. The paper establishes asymptotic properties of the new estimator and the theoretical results are supported by several Monte Carlo experiments. These also show that the estimator has reasonable properties in moderate to large samples. As such, the cost of inefficiency for robustness is negligible from an applied viewpoint. The practical usefulness of the new estimator is demonstrated via an empirical application of the Gravity Model of trade.

Date: 2018-04-11
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ceu-economics-and-business.github.io/RePEc/pdf/2018_2.pdf Full text (application/pdf)

Related works:
Journal Article: Event count estimation (2022) Downloads
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:ceu:econwp:2018_2

Access Statistics for this paper

More papers in CEU Working Papers from Department of Economics, Central European University Contact information at EDIRC.
Bibliographic data for series maintained by Anita Apor ().

 
Page updated 2025-03-22
Handle: RePEc:ceu:econwp:2018_2