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ADMISSIBLE CLUSTERING OF AGGREGATOR COMPONENTS: A NECESSARY AND SUFFICIENT STOCHASTIC SEMINONPARAMETRIC TEST FOR WEAK SEPARABILITY

Published online by Cambridge University Press:  15 September 2009

William A. Barnett  and
Philippe de Peretti
William A. Barnett
Affiliation:
Kansas University
Philippe de Peretti*
Affiliation:
Université Paris1 Panthéon-Sorbonne
*
Address correspondence to: Philippe de Peretti, Centre d'Economie de la Sorbonne (CES), Université Paris1 Panthéon-Sorbonne, Maison des Sciences Economiques, 106–112 Boulevard de l'Hôpital, 75647 Paris cedex 13, France; e-mail: philippe.de-peretti@univ-paris1.fr.
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Abstract

In aggregation theory, the admissibility condition for clustering components to be aggregated is blockwise weak separability, which also is the condition needed to separate out sectors of the economy. Although weak separability is thereby of central importance in aggregation and index number theory and in econometrics, prior attempts to produce statistical tests of weak separability have performed poorly in Monte Carlo studies. This paper introduces a new class of weak separability tests, which is seminonparametric. Such tests are both based on a necessary and sufficient condition and are fully stochastic, allowing to take into account measurement error. Simulations show that the tests perform well, even for large measurement errors.

Keywords

Weak separabilitySeminonparametric tests
Type
Articles
Information
Macroeconomic Dynamics , Volume 13 , Supplement S2: Measurement with Theory , September 2009 , pp. 317 - 334
Copyright
Copyright © Cambridge University Press 2009

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