Description Usage Arguments Details Value References See Also Examples
Confidence intervals for estimated changes/breaks between exchange rate regimes.
1 2 |
object |
An object of class |
parm |
integer. Either |
level |
numeric. The confidence level to be used. |
breaks |
integer. The number of breaks to be extracted from |
meat. |
function. A function for extracting the meat of a sandwich estimator
from a |
... |
currently not used. |
As the breakpoints are integers (observation numbers) the corresponding
confidence intervals are also rounded to integers. The algorithm used
is essentially the same as described for confint.breakpointsfull
.
The same distribution function is used, just the variance components are
computed differently. Here, bread
and
meat
(or some of its HC/HAC counterparts) are
used. See Zeileis, Shah, Patnaik (2008) for more details.
An object of class "confint.fxregimes"
.
Zeileis A., Kleiber C., Krämer W., Hornik K. (2003), Testing and Dating of Structural Changes in Practice, Computational Statistics and Data Analysis, 44, 109–123.
Zeileis A., Shah A., Patnaik I. (2010), Testing, Monitoring, and Dating Structural Changes in Exchange Rate Regimes, Computational Statistics and Data Analysis, 54(6), 1696–1706. http://dx.doi.org/10.1016/j.csda.2009.12.005.
fxregimes
, refit
,
fxlm
, confint.breakpointsfull
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | ## load package and data
library("fxregime")
data("FXRatesCHF", package = "fxregime")
## compute returns for CNY (and explanatory currencies)
## for one year after abolishing fixed USD regime
cny <- fxreturns("CNY", frequency = "daily",
start = as.Date("2005-07-25"), end = as.Date("2006-07-24"),
other = c("USD", "JPY", "EUR", "GBP"))
## compute all segmented regression with minimal segment size of
## h = 20 and maximal number of breaks = 5.
reg <- fxregimes(CNY ~ USD + JPY + EUR + GBP,
data = cny, h = 20, breaks = 5, ic = "BIC")
summary(reg)
## minimum BIC is attained for 2-segment (1-break) model
plot(reg)
## two regimes
## 1: tight USD peg
## 2: slightly more relaxed USD peg
round(coef(reg), digits = 3)
sqrt(coef(reg)[, "(Variance)"])
## inspect associated confidence intervals
ci <- confint(reg, level = 0.9)
ci
breakdates(ci)
## plot LM statistics along with confidence interval
fm <- fxlm(CNY ~ USD + JPY + EUR + GBP, data = cny)
scus <- gefp(fm, fit = NULL)
plot(scus, functional = supLM(0.1))
lines(ci)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.