concstats is a small package that helps you to calculate the
structure, concentration or diversity measures of a given
market.
You can reach that goal in different ways:
a) calculating an individual measure, e.g. the Herfindahl Hirschman
Index (HHI) or its dual.
b) calculating a group of measures, e.g. structural measures, or
c) a set of pre-selected measures in a one-step procedure.
You can install concstats directly from CRAN
install.packages("concstats") # Market Structure, Concentration, and Inequality
# Measures
library(concstats)You can install the development versions from
r-universe
install.packages(“concstats”, repos = “https://ropensci.r-universe.dev”)
github (requires remotes or
devtools)
remotes::install_github(“ropensci/concstats”
Measures of concentration and competition are important and give a
first insight of a given market structure in a particular market.
They are important to determine public policies and strategic
corporate decisions. However, in research and in practice the
most commonly used measure is the Herfindahl Hirschman Index. The
concstats package offers a set of alternative
measures.
concstats allows you to calculate quickly a
particular measure or a group of measures to give you a better overview
of a given market situation and therefore reducing uncertainty.
It can be used by practitioners and academics
alike.
concstats should be used by practitioners and academics
who are concerned about structure, concentration, diversity or
inequality in general or on a regular basis. A single
standard measure like the Herfindahl Hirschman Index (HHI) may lead to
erroneous conclusions. The concstats package
offers a straightforward way to calculate standard and
alternative measures given a data set of market participants
and their participation (in relative values) in a particular market at a
given point of time or over time. concstats provides currently the
following basic functions:
concstats_concstats() calculates eight
pre-selected measures in a one-step procedure to provide a first insight
of the market. The resulting data frame contains eight measures, which
are: number of firms with market share, numbers equivalent, the
cumulative share of the top (top 3 and top 5) firm(s) in percentage, the
hhi index, the entropy index, and the palma ratio.concstats_mstruct() is a wrapper for
the following measures: firm, nrs_eq
(Numbers equivalent), top, top 3 and
top 5 market share, and all calculates
all measures as a group. Each of the measures within a group can be
accessed directly using the prefix concstats_, e.g.
concstats_firm. In practice, firm ranking might be of
interest, and the user might prefer the
concstats_top_df functions. In general, the user should
provide individual markets shares, however, the helper function
concstats_shares can be used.concstats_comp() is a group wrapper
for the following concentration measures: hhi, the
dual of the hhi, the min. of the hhi,
the dominance index, the stenbacka
index, and finally all which calculates all
measures as a group.concstats_inequ() is a wrapper for
inequality and diversity measures and contains:
entropy, gini coefficient,
simpson index, the palma ratio and the
alternative grs measure, all
calculates the group measures.