Author(s)

Makram EL-SHAGI


Abstract

In this paper, we demonstrate that using finite sample correction bootstrapping techniques is advisable in samples that cover less than two complete business cycles, even when high-frequency data seemingly provide a sufficient number of observations to overcome the small sample bias. This is particularly relevant in the current research environment. Because the recent financial crisis is considered as a structural break, research on current problems is often conducted using post-crisis data. That is, the available samples cover only a few years of data, often spanning only one business cycle or even less. We provide ample simulation-based evidence that samples of daily or monthly dynamic data covering periods of this magnitude are prone to a fairly substantial bias. Moreover, we are able to show that standard bootstrap-based bias correction techniques still work in those cases.

Keywords

Finite sample, Short period
 

Get Full Article

El-Shagi, M.: Dealing with Small Sample Bias in Post-Crisis Samples, Economic Modelling, Vol. 65 (September 2017), pp. 1-8


 
 

 

 


 

GET IN TOUCH

Address: Dongliuzhai Building, 85 Minglun Street
Henan University, Minglun Campus
Shunhe, Kaifeng, Henan
475004 China

E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

 Web: http://cfds.henuecon.education

 

 

 

 QUICK LINKS

People

Working Paper Series

Events

Contact Us


© Copyright 2018 CFDS at Henan University