FRED_light: FRED-MD (December 2021 vintage) data set with light...
In juhokalle/rmfd4dfm: Estimation of DFMs using RMFD-E parametrization
FRED_light R Documentation
FRED-MD (December 2021 vintage) data set with light transformations
Description
This data is taken from FRED-MD database, with the sample span corresponding to
that of FG_data, i.e. March 1973 to November 2007. The database consists
of 127 variables, out of which two are discarded due to many missing variables, and
the corresponding variable names can be accessed by FRED_light$discarded.
The data is transformed differenly to the dataset FRED_heavy such that
the transformations would correspond more closely to those given in Forni and Gambetti (2010).
The method of obtaining this data set from the raw data and the transformation
codes are described in the script data-raw/DATASET.R.
Usage
FRED_light
Format
A list with the following elements
- discarded
data frame listing the discarded variables and the number of
missing values under the time span under consideration
- df
T x n data frame where T is the time-series dimension,
and n is the cross-sectional dimension
- data
Date variable giving the time span of the data
- trans_ix
Variable transformation codes with the interpretation as in
McCracken and Ng (2016)
Source
https://files.stlouisfed.org/files/htdocs/fred-md/monthly/2021-12.csv
References
Forni, M., & Gambetti, L. (2010). The dynamic effects of monetary policy:
A structural factor model approach. Journal of Monetary Economics, 57(2), 203-216.
McCracken, M. W., & Ng, S. (2016). FRED-MD: A monthly database for macroeconomic research.
Journal of Business & Economic Statistics, 34(4), 574-589.
juhokalle/rmfd4dfm documentation built on July 18, 2024, 10:19 p.m.
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| FRED_light | R Documentation |
FRED-MD (December 2021 vintage) data set with light transformations
Description
This data is taken from FRED-MD database, with the sample span corresponding to
that of FG_data, i.e. March 1973 to November 2007. The database consists
of 127 variables, out of which two are discarded due to many missing variables, and
the corresponding variable names can be accessed by FRED_light$discarded.
The data is transformed differenly to the dataset FRED_heavy such that
the transformations would correspond more closely to those given in Forni and Gambetti (2010).
The method of obtaining this data set from the raw data and the transformation
codes are described in the script data-raw/DATASET.R.
Usage
FRED_light
Format
A list with the following elements
- discarded
data frame listing the discarded variables and the number of missing values under the time span under consideration
- df
T x ndata frame whereTis the time-series dimension, andnis the cross-sectional dimension- data
Datevariable giving the time span of the data- trans_ix
Variable transformation codes with the interpretation as in McCracken and Ng (2016)
Source
https://files.stlouisfed.org/files/htdocs/fred-md/monthly/2021-12.csv
References
Forni, M., & Gambetti, L. (2010). The dynamic effects of monetary policy: A structural factor model approach. Journal of Monetary Economics, 57(2), 203-216.
McCracken, M. W., & Ng, S. (2016). FRED-MD: A monthly database for macroeconomic research. Journal of Business & Economic Statistics, 34(4), 574-589.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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