prices

Prices, quantities, identities and time periods
adopted to demonstrate the computation of price indexes.

datasets

Decomposing value added growth into explanatory factors.
A cost constrained value added function is defined to specify the
production frontier. Industry estimates can also be aggregated using
a weighted average approach.
Details about the methodology and data can be found in Diewert and Fox (2018)
<doi:10.1093/oxfordhb/9780190226718.013.19>
and Zeng, Parsons, Diewert and Fox (2018)
<https://www.business.unsw.edu.au/research-site/centreforappliedeconomicresearch-site/Documents/emg2018-6_SZeng_EMG-Slides.pdf>.

Shipei Zeng

dfvad

Diewert and Fox's Method of Value Added Growth Decomposition

prices function

A list of data frames with the following columns:<dl class="dl-horizontal">
<dt>t</dt><dd>A time period column.</dd>
<dt>id</dt><dd>An identity column.</dd>
<dt>p</dt><dd>A price column.</dd>
<dt>q</dt><dd>A quantity column.</dd>
</dl>These data frames are produced with different elasticities
that can be specified by the sub-list names.

Format

Sample Data for Price Indexes — prices

A list of data frames with the following columns:<dl class='dl-horizontal'>
<dt>t</dt><dd>A time period column.</dd>
<dt>id</dt><dd>An identity column.</dd>
<dt>p</dt><dd>A price column.</dd>
<dt>q</dt><dd>A quantity column.</dd>
</dl>These data frames are produced with different elasticities
that can be specified by the sub-list names.

prices: Sample Data for Price Indexes

Description

Usage

Arguments

Format

References