Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/244313 
Year of Publication: 
2021
Series/Report no.: 
Working Paper No. 2021-10
Publisher: 
Federal Reserve Bank of Atlanta, Atlanta, GA
Abstract: 
Researchers interested in studying the frequency of events or behaviors among a population must rely on count data provided by sampled individuals. Often, this involves a decision between live event counting, such as a behavioral diary, and recalled aggregate counts. Diaries are generally more accurate, but their greater cost and respondent burden generally yield less data. The choice of survey mode, therefore, involves a potential tradeoff between bias and variance of estimators. I use a case study comparing inferences about payment instrument use based on different survey designs to illustrate this dilemma. I then use a simulation study to show how and under what conditions a hybrid survey design can improve efficiency of estimation, in terms of mean-squared error. Overall, this work suggests that such a hybrid design can have considerable benefits as long as there is nontrivial overlap in the diary and recall samples.
Subjects: 
recall surveys
diaries
bias
mean-squared error
multi-level models
JEL: 
C15
C81
C83
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
441.27 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.