The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Stratified and Cluster Sampling

  • Jeffrey M. Wooldridge
Reference work entry
DOI: https://doi.org/10.1057/978-1-349-95189-5_2639

Abstract

The random sampling paradigm, typically introduced in basic statistics courses, ensures that a sample of data is, loosely speaking, ‘representative’ of the underlying population. When the population parameters are identified, many common estimation techniques, including least squares, maximum likelihood, and instrumental variables, have desirable statistical properties under random sampling. Unfortunately, while random sampling is convenient, it can be, and often intentionally is, violated when cross-sectional data and panel data are collected. Two important deviations from random sampling are stratified sampling and cluster sampling, or perhaps a combination.

Keywords

Cluster correlation Cluster sampling Exogenous sampling Heteroskedasticity Multinomial sampling Probability sampling Sampling Stratified sampling Survey sampling Two-stage sampling Unbiased estimators Variable probability sampling Variance Weighted least squares 

JEL Classifications

C81 
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Copyright information

© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Jeffrey M. Wooldridge
    • 1
  1. 1.