Chapter

A Monte Carlo Comparison of OLS Estimation Errors and Design Efficiencies in a Two‐Stage Stratified Random Sampling Procedure for a Contingent Valuation Study

Kyeongae Choe, William R. Parke and Dale Whittington

in Valuing Environmental Preferences

Published in print November 2001 | ISBN: 9780199248919
Published online November 2003 | e-ISBN: 9780191595950 | DOI: http://dx.doi.org/10.1093/0199248915.003.0010
 A Monte Carlo Comparison of OLS Estimation Errors and Design Efficiencies in a Two‐Stage Stratified Random Sampling Procedure for a Contingent Valuation Study

More Like This

Show all results sharing this subject:

  • Economic Development and Growth

GO

Show Summary Details

Preview

In many settings, a random sample may not be cost‐inefficient, so that a two‐stage stratified random sample is adopted in contingent valuation (CV) studies. The first stage comprises identifying a number of enumeration areas from which to sample households in the second stage. The Monte Carlo simulation, from a CV case study, suggests that increasing the second‐stage sample size within a limited number of enumeration areas selected at the first stage of sampling will result in a greater return in statistical and sampling design efficiency than will increasing the number of enumeration areas with a limited second‐stage sampling size. In both approaches, the marginal return diminishes as the number of sampling units increases.

Keywords: Monte Carlo experiment; sample design efficiency; sampling distribution properties; standard error; statistical inference

Chapter.  8227 words.  Illustrated.

Subjects: Economic Development and Growth

Full text: subscription required

How to subscribe Recommend to my Librarian

Buy this work at Oxford University Press »

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.