Overview of Datasets Included in the MultiATSM Package
Source:R/meta-documentation.R
MultiATSM_datasets.RdThe package includes several pre-processed datasets used for estimation and replication examples:
Details
- GlobalMacro
Global macro-financial risk factors, namely global economic activity and global inflation.
- GlobalMacro_covid
Global macro-financial risk factors, namely the output growth rate from the U.S. and China and the S&P 500 index.
- DomMacro
Domestic macroeconomic risk factors, namely economic activity and inflation.
- DomMacro_covid
Domestic macroeconomic risk factors, namely otput growth, inflation, CDS and the COVID-19 reproduction rate
- TradeFlows
Bilateral trade flow series used in GVAR examples as a proxy measure of cross-country conectdness.
- TradeFlows_covid
Bilateral trade flow series used in GVAR examples as a proxy measure of cross-country conectdness.
- Yields
Monthly series of bond yields by maturity for multiple economies.
- Yields_covid
Weekly series of sovereign bond yields by maturity for multiple economies.
- RiskFacFull
Full set of risk factors (global and domestic) data used throughout the package
- GVARFactors
List of risk factors used in the estimation of GVAR models.
- BR_jps_out
Replications of the JPS outputs by Bauer and Rudebusch (2017)
- InpForOutEx
List of inputs for an illustrative JPS model with Brazilian data
- ParaSetEx
List of set of parameterafter optimization for an illustrative JPS model with Brazilian data
- NumOutEx
List of numerical outputs for an illustrative JPS model with Brazilian data
- Out_Example
re-loaded examaple of a complete list of several model outputs. Used in the package vignette.
Each dataset is documented separately using `?GlobalMacro`, `?DomMacro`, `?TradeFlows`, `?Yields`, etc.
Datasets ending with the suffix _covid are based on those used in Candelon and Moura (2023) and cover Brazil, India, Mexico, and Russia.
The remaining datasets correspond to Candelon and Moura (2024) and include Brazil, China, Mexico, and Uruguay.