The goal of FAVAR is to estimate a FAVAR model by Bernanke et al. (2005).
You can install the package FAVAR from CRAN:
install.packages('FAVAR')You can install the development version of FAVAR from GitHub with:
# install.packages("devtools")
devtools::install_github("common2016/FAVAR")This is a basic example which shows you how to estimate a FAVAR model:
library(FAVAR)
## basic example code
data('regdata')
fit <- FAVAR(Y = regdata[,c("Inflation","Unemployment","Fed_funds")],
X = regdata[,1:115], slowcode = slowcode,fctmethod = 'BBE',
factorprior = list(b0 = 0, vb0 = NULL, c0 = 0.01, d0 = 0.01),
varprior = list(b0 = 0,vb0 = 10, nu0 = 0, s0 = 0),
nrep = 500, nburn = 100, K = 2, plag = 2)
# print FAVAR estimation results
summary(fit,xvar = c(3,5))
#> Estimation VAR results for equation factor1
#> -------------
#> Estimate se q025 q975
#> factor1.1 0.7236 0.0035 0.5651 0.8700
#> factor2.1 0.1463 0.0026 0.0344 0.2603
#> Inflation.1 0.0268 0.0041 -0.1336 0.2166
#> Unemployment.1 -0.1733 0.0034 -0.3215 -0.0221
#> Fed_funds.1 0.0592 0.0019 -0.0211 0.1427
#> factor1.2 0.1954 0.0038 0.0359 0.3667
#> factor2.2 -0.0400 0.0024 -0.1465 0.0616
#> Inflation.2 -0.0335 0.0037 -0.1926 0.1194
#> Unemployment.2 0.1168 0.0033 -0.0237 0.2606
#> Fed_funds.2 -0.0106 0.0018 -0.0916 0.0681
#> --------------
#> Estimation VAR results for equation factor2
#> -------------
#> Estimate se q025 q975
#> factor1.1 -0.5147 0.0051 -0.7437 -0.2973
#> factor2.1 0.8002 0.0037 0.6343 0.9516
#> Inflation.1 -0.0076 0.0060 -0.2751 0.2370
#> Unemployment.1 0.3294 0.0042 0.1295 0.5041
#> Fed_funds.1 -0.0894 0.0027 -0.2132 0.0213
#> factor1.2 0.0127 0.0054 -0.2186 0.2711
#> factor2.2 0.0202 0.0031 -0.1077 0.1615
#> Inflation.2 0.1378 0.0053 -0.0847 0.3757
#> Unemployment.2 -0.3043 0.0041 -0.4742 -0.1103
#> Fed_funds.2 0.0180 0.0026 -0.0907 0.1372
#> --------------
#> Estimation VAR results for equation Inflation
#> -------------
#> Estimate se q025 q975
#> factor1.1 0.2308 0.0028 0.1127 0.3677
#> factor2.1 0.2765 0.0022 0.1826 0.3718
#> Inflation.1 0.9731 0.0034 0.8121 1.1173
#> Unemployment.1 -0.0320 0.0027 -0.1458 0.0795
#> Fed_funds.1 -0.0580 0.0014 -0.1192 0.0037
#> factor1.2 0.2515 0.0031 0.1115 0.3866
#> factor2.2 0.0792 0.0018 -0.0087 0.1597
#> Inflation.2 -0.1338 0.0029 -0.2663 0.0030
#> Unemployment.2 0.0323 0.0026 -0.0748 0.1478
#> Fed_funds.2 0.0415 0.0014 -0.0156 0.0982
#> --------------
#> Estimation VAR results for equation Unemployment
#> -------------
#> Estimate se q025 q975
#> factor1.1 0.2806 0.0037 0.1172 0.4362
#> factor2.1 -0.3049 0.0028 -0.4272 -0.1945
#> Inflation.1 -0.0208 0.0044 -0.2263 0.1565
#> Unemployment.1 0.7705 0.0035 0.6228 0.9287
#> Fed_funds.1 -0.0110 0.0018 -0.0830 0.0690
#> factor1.2 0.1685 0.0042 -0.0046 0.3616
#> factor2.2 0.1293 0.0024 0.0150 0.2378
#> Inflation.2 0.0186 0.0037 -0.1384 0.1889
#> Unemployment.2 0.1744 0.0034 0.0301 0.3208
#> Fed_funds.2 0.0270 0.0018 -0.0575 0.1045
#> --------------
#> Estimation VAR results for equation Fed_funds
#> -------------
#> Estimate se q025 q975
#> factor1.1 -0.0826 0.0055 -0.3069 0.1667
#> factor2.1 0.6031 0.0043 0.4049 0.7826
#> Inflation.1 0.1715 0.0062 -0.0811 0.4602
#> Unemployment.1 0.0654 0.0053 -0.1575 0.2950
#> Fed_funds.1 0.7489 0.0029 0.6216 0.8723
#> factor1.2 0.0518 0.0062 -0.2181 0.3232
#> factor2.2 -0.2942 0.0037 -0.4427 -0.1254
#> Inflation.2 -0.1307 0.0055 -0.3806 0.1026
#> Unemployment.2 -0.0881 0.0053 -0.3171 0.1353
#> Fed_funds.2 0.1904 0.0029 0.0703 0.3254
#> --------------
#>
#> =================================================================================
#> Estimation results for the 3th equation in X = FY
#> ------------
#> loading loading_se q025 q975
#> factor1 -1.68390725 0.011857036 -2.13008865 -1.08789590
#> factor2 0.57351588 0.007049173 0.28645862 0.88920757
#> Inflation 0.17500014 0.004882530 -0.03514514 0.36357533
#> Unemployment 0.05065144 0.002760542 -0.06667948 0.18144093
#> Fed_funds -0.14186086 0.003393773 -0.28570561 0.01174437
#> -------------
#> Estimation results for the 5th equation in X = FY
#> ------------
#> loading loading_se q025 q975
#> factor1 -0.5431962 0.012825894 -1.04440858 0.06499368
#> factor2 0.7660636 0.007873015 0.43876128 1.11441043
#> Inflation 0.1760928 0.005413527 -0.06253258 0.38725944
#> Unemployment 0.2045756 0.003149414 0.06955185 0.35321617
#> Fed_funds -0.3872807 0.003923484 -0.55207957 -0.21091164
#> -------------
#> NULL
# plot impulse response figure
library(patchwork)
ans <- irf(fit,resvar = c(2,9,10), tcode = tcode, nhor = 21, showplot = T)
- Bernanke, B.S., J. Boivin and P. Eliasz, Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach. Quarterly Journal of Economics, 2005. 120(1): p. 387-422.