MOMENT-BASED INFERENCE WITH STRATIFIED DATA

B-Tier
Journal: Econometric Theory
Year: 2011
Volume: 27
Issue: 1
Pages: 47-73

Score contribution per author:

2.011 = (α=2.01 / 1 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Many data sets used by economists and other social scientists are collected by stratified sampling. The sampling scheme used to collect the data induces a probability distribution on the observed sample that differs from the target or underlying distribution for which inference is to be made. If this effect is not taken into account, subsequent statistical inference can be seriously biased. This paper shows how to do efficient semiparametric inference in moment restriction models when data from the target population are collected by three widely used sampling schemes: variable probability sampling, multinomial sampling, and standard stratified sampling.

Technical Details

RePEc Handle
repec:cup:etheor:v:27:y:2011:i:01:p:47-73_00
Journal Field
Econometrics
Author Count
1
Added to Database
2026-01-29