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THE FULL‐DISTRIBUTION APPROACH TO AGGREGATE REPRESENTATION IN THE INPUT‐OUTPUT MODELING FRAMEWORK *
Author(s) -
Jackson Randall W.
Publication year - 1986
Publication title -
journal of regional science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.171
H-Index - 79
eISSN - 1467-9787
pISSN - 0022-4146
DOI - 10.1111/j.1467-9787.1986.tb01057.x
Subject(s) - aggregate (composite) , probabilistic logic , representation (politics) , computer science , variation (astronomy) , specification , econometrics , identification (biology) , input/output , sampling (signal processing) , production (economics) , mathematics , economics , materials science , physics , botany , filter (signal processing) , artificial intelligence , politics , political science , astrophysics , computer vision , law , composite material , biology , operating system , macroeconomics
. This paper presents a probabilistic specification of coefficients in the input‐ output modeling framework. Although previous works on probabilistic input‐output models attribute uncertainty to measurement and sampling errors, this specification derives from systematic variation directly attributable to industrial, institutional, and location factors. Experiments with national input‐output data support the existence of such variation. Employing the specification not only yields a more flexible aggregate modeling framework capable of producing interval impact estimates, but also an alternative perspective on such issues as interregional differentiation and structural comparison, the identification of key industrial sectors, aggregation, and spatial variation in production.