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) 
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 ().