Improved Estimation of Poisson Rate Distributions through a Multi-Mode Survey Design
No 2021-10, FRB Atlanta Working Paper from Federal Reserve Bank of Atlanta
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.
Keywords: recall surveys; diaries; bias; mean-squared error; multi-level models (search for similar items in EconPapers)
JEL-codes: C15 C81 C83 (search for similar items in EconPapers)
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