Barnett, William A. and de Peretti, Philippe (2008): Admissible clustering of aggregator components: a necessary and sufficient stochastic semi-nonparametric test for weak separability.
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In aggregation theory, the admissibility condition for clustering together 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 deals with semi-nonparametric tests for weak separability. It introduces both a necessary and sufficient test, and a fully stochastic procedure allowing to take into account measurement error. Simulations show that the test performs well, even for large measurement errors.
|Item Type:||MPRA Paper|
|Original Title:||Admissible clustering of aggregator components: a necessary and sufficient stochastic semi-nonparametric test for weak separability|
|Keywords:||weak separability; quantity aggregation; clustering; sectors; index number theory; semi-nonparametrics|
|Subjects:||C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C43 - Index Numbers and Aggregation
D - Microeconomics > D1 - Household Behavior and Family Economics > D12 - Consumer Economics: Empirical Analysis
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General
|Depositing User:||William A. Barnett|
|Date Deposited:||05. Jan 2009 06:34|
|Last Modified:||20. May 2015 03:46|
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