EconPapers    
Economics at your fingertips  
 

An Introduction to Understanding and Teaching Within-Cluster Correlation in Complex Surveys

Humberto Barreto () and Manu Raghav ()

Eastern Economic Journal, 2017, vol. 43, issue 4, No 10, 727-728

Abstract: Abstract This econometrics pedagogy note points to online material that demonstrates the importance of using cluster standard errors (SEs) with data generated from complex surveys. Simulation is used to show that both classic ordinary least squares and robust SEs perform poorly in the presence of within-cluster correlated errors, while cluster SEs perform much better. We take advantage of Excel’s spreadsheet interface to produce clear and intuitive visuals of the data generation process and explain key results. Customizable Stata and R implementations, which help in further analysis by taking advantage of the unique different capabilities of Stata and R, are also provided. We conclude with suggestions for how to use these files in the classroom.

Keywords: complex survey; simulation; cluster sampling; estimation; survey regression; A22; C80; C83 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1057/eej.2015.55 Abstract (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:pal:easeco:v:43:y:2017:i:4:d:10.1057_eej.2015.55

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/41302

DOI: 10.1057/eej.2015.55

Access Statistics for this article

Eastern Economic Journal is currently edited by Allan Zebedee and Cynthia Bansak

More articles in Eastern Economic Journal from Palgrave Macmillan, Eastern Economic Association Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-19
Handle: RePEc:pal:easeco:v:43:y:2017:i:4:d:10.1057_eej.2015.55