Package: EWS 0.2.0
Quentin Lajaunie
EWS: Early Warning System
The purpose of Early Warning Systems (EWS) is to detect accurately the occurrence of a crisis, which is represented by a binary variable which takes the value of one when the event occurs, and the value of zero otherwise. EWS are a toolbox for policymakers to prevent or attenuate the impact of economic downturns. Modern EWS are based on the econometric framework of Kauppi and Saikkonen (2008) <doi:10.1162/rest.90.4.777>. Specifically, this framework includes four dichotomous models, relying on a logit approach to model the relationship between yield spreads and future recessions, controlling for recession risk factors. These models can be estimated in a univariate or a balanced panel framework as in Candelon, Dumitrescu and Hurlin (2014) <doi:10.1016/j.ijforecast.2014.03.015>. This package provides both methods for estimating these models and a dataset covering 13 OECD countries over a period of 45 years. In addition, this package also provides methods for the analysis of the propagation mechanisms of an exogenous shock, as well as robust confidence intervals for these response functions using a block-bootstrap method as in Lajaunie (2021). This package constitutes a useful toolbox (data and functions) for scholars as well as policymakers.
Authors:
EWS_0.2.0.tar.gz
EWS_0.2.0.tar.gz(r-4.5-noble)EWS_0.2.0.tar.gz(r-4.4-noble)
EWS_0.2.0.tgz(r-4.4-emscripten)EWS_0.2.0.tgz(r-4.3-emscripten)
EWS.pdf |EWS.html✨
EWS/json (API)
| # Install 'EWS' in R: |
| install.packages('EWS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- data_USA - Historical data for the United States
- data_panel - Historical data for 13 OECD countries
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:e08f14a3fd. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 12 2024 |
| R-4.5-linux | OK | Sep 12 2024 |
Exports:BlockBootstrappEWS_AM_CriterionEWS_CSA_CriterionEWS_NSR_CriterionGIRF_DichoGIRF_Index_CIGIRF_Proba_CILogistic_EstimationMatrix_lagSimul_GIRFVector_ErrorVector_lag
Dependencies:numDeriv
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Block Bootstrapp | BlockBootstrapp |
| Historical data for 13 OECD countries | data_panel |
| Historical data for the United States | data_USA |
| AM Threshold - optimal cut-off | EWS_AM_Criterion |
| CSA Threshold - optimal cut-off | EWS_CSA_Criterion |
| NSR Threshold - optimal cut-off | EWS_NSR_Criterion |
| GIRF for Dichotomous models | GIRF_Dicho |
| Confidence Intervals for the Index - GIRF Analysis | GIRF_Index_CI |
| Confidence Intervals for the Probability - GIRF Analysis | GIRF_Proba_CI |
| Logistic Estimation for Dichotomous Analysis | Logistic_Estimation |
| Matrix Lag - data processing | Matrix_lag |
| GIRF Simulations | Simul_GIRF |
| Vector of Errors | Vector_Error |
| Vector lag - data processing | Vector_lag |