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Selecting Field Experiment Locations with Archival Data
Author(s) -
Leonhardt James M.,
Trafimow David,
Niculescu Mihai
Publication year - 2016
Publication title -
journal of consumer affairs
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.582
H-Index - 62
eISSN - 1745-6606
pISSN - 0022-0078
DOI - 10.1111/joca.12117
Subject(s) - field (mathematics) , computer science , parsing , selection (genetic algorithm) , control (management) , consumption (sociology) , data mining , operations research , statistics , econometrics , mathematical optimization , artificial intelligence , mathematics , social science , sociology , pure mathematics
The selection of field experiment locations often requires that the control location be comparable to the treatment location. Recently, a method that employs the mathematics of potential performance theory was proposed for comparing field experiment locations by parsing random versus systematic effects. Here, we apply this method to archival data (i.e., household electricity consumption). In doing so, we are able to assess the effectiveness of this method at handling real‐world data, absent user‐defined variables. In addition, we provide consumer researchers with a step‐by‐step example on how to apply this method to the problem of selecting optimal treatment and control locations for field experiments. Finally, we consider how this method could apply to policy assessment more generally.