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Classification and aggregation: An application to industrial classification in cps data
Author(s) -
Cotterman R.,
Peracchi F.
Publication year - 1992
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.3950070105
Subject(s) - aggregate (composite) , sequence (biology) , set (abstract data type) , function (biology) , data aggregator , data set , aggregation problem , wage , econometrics , computer science , agrégation , mathematics , mathematical economics , economics , artificial intelligence , chemistry , materials science , computer network , platelet , wireless sensor network , evolutionary biology , immunology , market economy , composite material , biology , biochemistry , programming language
In this paper we offer a method for deciding how to aggregate a set of elementary industries. The method is then applied to the problem of estimating a wage equation that allows for industry‐specific effects. Our method explicitly formalizes the trade‐off between goodness‐of‐fit and parsimony implicit in an aggregation problem. By varying the parameter of the assumed loss function, one obtains a whole sequence of aggregation levels. Further, the resulting sequence is consistent; that is, groupings formed at one level of aggregation will never be undone when one aggregates further.