Working Paper

Improved Estimation of Poisson Rate Distributions through a Multi-Mode Survey Design

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.

Keywords: recall surveys; diaries; bias; mean-squared error; multi-level models;

JEL Classification: C15; C81; C83;

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Bibliographic Information

Provider: Federal Reserve Bank of Atlanta

Part of Series: FRB Atlanta Working Paper

Publication Date: 2021-02-03

Number: 2021-10