reinsdorf-balk transformation and additive decomposition of indexes
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Reinsdorf-Balk Transformation and Additive Decomposition of Indexes. I. Introduction II. Reinsdorf-Balk Transformation III. Additive Decompositions of Fisher Index IV. Additive Decomposition of Chain Indexes V. Numerical Illustrations (skip) VI. Concluding Remarks. - PowerPoint PPT PresentationTRANSCRIPT
Reinsdorf-Balk Transformationand Additive Decomposition of Indexes
Ki-Hong Choi(NPRI) and Hak K. Pyo(SNU)
I. Introduction
II. Reinsdorf-Balk Transformation
III. Additive Decompositions of Fisher Index
IV. Additive Decomposition of Chain Indexes
V. Numerical Illustrations (skip)
VI. Concluding Remarks
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I. Introduction
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arithmetic mean index
geometric mean index
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decomposition in %-change
decomposition in log-change
• Arithmetic mean index and decomposition of growth rate
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• Geometric mean index and decomposition of growth rate
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II. Reinsdorf-Balk Transformation
• Literature
Reinsdorf(1997, 2002), Balk(1999, 2004)
Kohli(2007), “Truly remarkable”
• Some need for improvements
– Reinsdorf’s proof is hard to follow.– Though Balk’s proof is easy and clear, there
is a better alternative.
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Balk’s Identity: from A index to G index
Reinsdorf’s Identity: from G index to A index
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III. Additive Decompositions of Fisher III. Additive Decompositions of Fisher IndexIndex
• Conventional Decompositions
– Decomposition in % changes
van IJzeren(1952)=Dumagan(2002)=Ehemann
et al(2002)
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– Decomposition in log-changes
Reinsdorf(1997), Reinsdorf et al(2002), Balk(2004)
Less satisfactory decomposition by Vartia(1976)
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• New Decompositions Decomposition in % changes
Reinsdorf et al.(2002), applying Reinsdorf identity to the geometric mean version of Fisher index.
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– Decomposition in log-changes
• Applying Balk’s identity to the van IJzeren form of Fisher index
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IV. Additive Decomposition of Chain Indexes
• Difficulty with additive decomposition of cumulative (compound) growth rates of chain indexes
– Cumulative growth rates is decomposable in log-changes
– But decomposition in log-change is not good since it deviates from %-changes
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• R-B transformation gives solution to this dilemma
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VI. Concluding remarks
• R-B transformation is interesting since it makes arithmetic mean and geometric mean indexes interchangeable.
• R-B transformation is useful since it can provide an additive decomposition of cumulative growth rates by chain indexes.
Thank you!