pp_measures: Measures of interest of a policy portfolio

In PolicyPortfolios: Tools for Managing, Measuring and Visualizing Policy Portfolios

Measures of interest of a policy portfolio

Description

Calculate measures of interest of a policy portfolio.

Usage

pp_measures(D, id = NULL)

Arguments

D	Data frame in a tidy format with the following columns: "Country", "Sector", "Year", "Instrument", "Target" and "covered". "covered" is a binary identificator of whether the portfolio space is covered by policy intervention (1) or not (0). The remaining columns identify the case. Notice that "Year" is a numeric value, while the remaining 4 case identifiers are factors.
id	A list with up to two elements, namely "Country", and "Year" indicating the specific identification characteristics of the portfolio(s) that must be processed. Defaults to NULL to process all portfolios.

Value

A tidy dataset containing the portfolio identificators (Country, Sector and Year) plus the Measure identificators (Measure and Measure.label) and the value of the portfolio characteristic.

References

Fernández-i-Marín, X., Knill, C. & Steinebach, Y. (2021). Studying Policy Design Quality in Comparative Perspective. _American Political Science Review_, online first. For Average Instrument Diversity.

Adam, C., Knill, C. & Fernández-i-Marín, X. (2016). Rule growth and government effectiveness: why it takes the capacity to learn and coordinate to constrain rule growth. _Policy Sciences_, 50, 241–268. doi:10.1007/s11077-016-9265-x. For portfolio size.

See Also

diversity for Average Instrument Diversity, Gini, diversity configurations.

Examples

data(P.education)
m.education <- pp_measures(P.education)
m.education

# Calculate portfolio measures for a restricted set of portfolios defined by a list.
data(P.energy)
m.energy <- pp_measures(P.energy, id = list(Country = "Borduria", Year = 2022))
m.energy

PolicyPortfolios documentation built on March 18, 2022, 5:36 p.m.