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RGAP
View on CRAN: Click
here
Download and install RGAP package within the R console
Install from CRAN:
install.packages("RGAP")
Install from Github:
library("remotes")
install_github("cran/RGAP")
Install by package version:
library("remotes")
install_version("RGAP", "0.1.1")
Attach the package and use:
library("RGAP")
Maintained by
Sina Streicher
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.RGAP . RGAP citation info . RGAP results . RGAP.pdf . RGAP_0.1.1.tar.gz . RGAP_0.1.1.zip . RGAP_0.1.1.zip . RGAP_0.1.1.zip . RGAP_0.1.1.tgz . RGAP_0.1.1.tgz . RGAP_0.1.1.tgz . RGAP_0.1.1.tgz . RGAP_0.1.1.tgz . RGAP_0.1.1.tgz . RGAP archive . https://CRAN.R-project.org/package=RGAP .
First Published: 2023-06-01
Latest Update: 2023-11-02
Description:
The output gap indicates the percentage difference between the actual output of an economy and its potential. Since potential output is a latent process, the estimation of the output gap poses a challenge and numerous filtering techniques have been proposed. 'RGAP' facilitates the estimation of a Cobb-Douglas production function type output gap, as suggested by the European Commission (Havik et al. 2014) . To that end, the non-accelerating wage rate of unemployment (NAWRU) and the trend of total factor productivity (TFP) can be estimated in two bivariate unobserved component models by means of Kalman filtering and smoothing. 'RGAP' features a flexible modeling framework for the appropriate state-space models and offers frequentist as well as Bayesian estimation techniques. Additional functionalities include direct access to the 'AMECO' database and automated model selection procedures. See the paper by Streicher (2022) for details.
How to cite:
Sina Streicher (2023). RGAP: Production Function Output Gap Estimation. R package version 0.1.1, https://cran.r-project.org/web/packages/RGAP. Accessed 02 Apr. 2025.
Previous versions and publish date:
0.1.0 (2023-06-01 14:50)
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