Premium
Identification Problems in the Social Sciences and Everyday Life
Author(s) -
Manski Charles F.
Publication year - 2003
Publication title -
southern economic journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.762
H-Index - 58
eISSN - 2325-8012
pISSN - 0038-4038
DOI - 10.1002/j.2325-8012.2003.tb00553.x
Subject(s) - identification (biology) , statistical inference , inference , sampling (signal processing) , selection (genetic algorithm) , association (psychology) , sample (material) , everyday life , statistical analysis , econometrics , sample size determination , data science , sociology , computer science , psychology , economics , statistics , artificial intelligence , epistemology , mathematics , biology , botany , chemistry , filter (signal processing) , chromatography , psychotherapist , computer vision , philosophy
Econometricians have found it useful to separate the problem of empirical inference into statistical and identification components. Studies of identification determine the conclusions that could be drawn if a researcher were able to observe a data sample of unlimited size. Statistical inference seeks to characterize how sampling variability affects the conclusions that can be drawn from samples of limited size. This Association Lecture to the Southern Economic Association describes the broad themes of a research program on identification that I began in the late 1980s and continue today. I show how these themes have played out in my analysis of the selection problem , a fundamental and pervasive identification problem. I examine how the selection problem manifests itself in the econometric analysis of market demand.