| fred | R Documentation |
Function that fetches economic data from the FRED based on the series ids.
fred(
...,
key = NULL,
all = TRUE,
info = TRUE,
realtime_start = NULL,
realtime_end = NULL,
long = FALSE
)
... |
character vectors of series ids to search. Any names will be used to label the series in the resulting data.frame |
key |
32 character lower-cased alpha-numeric character string. If
|
all |
logical; should all observations be used? Defaults to |
info |
logical; should information about each series, such as units and title, be kept? If so, the information will be stored in a data.frame under the attribute |
realtime_start, realtime_end |
character date strings of format "YYY-MM-DD" used obtain information that was known during the specified time period. If empty, the latest update of the information is used. |
long |
logical; should the resulting data.frame be long or wide? Defaults to |
The fred function search for series ids from the FRED and returns the
values in a data.frame. Unless long=TRUE, a new column will be created
for each series. The dates for each observation will be included in the "date"
column and will be of class "Date". Each series will be a numeric value.
An API key is required. Request a free key at
https://fred.stlouisfed.org/docs/api/api_key.html and register it for the
session with set_fred_key, or pass it through key.
If a series id cannot be found, then it will be skipped and R will issue a
warning. If the FRED API itself cannot be reached, or returns a response that
cannot be parsed, an informative message is printed and no data are returned.
In either case the remaining series are still returned; if no series at all
could be retrieved, the function returns NULL.
To access ALFRED, or the archived Federal Reserve Economic Data, use the realtime_start
and realtime_end arguments to specify a time frame. More details about
real time periods can be found at https://fred.stlouisfed.org/docs/api/fred/realtime_period.html.
data.frame
## Not run:
api_key <- "abcdefghijklmnopqrstuvwxyz123456"
# Naive Phillips Curve Estimation
df <- fred(p = "CPIAUCSL", u = "u6rate", key=api_key)
head(df)
df$pi <- log(df$p) - log(c(NA, df$p[2:nrow(df)]))
reg_pc <- lm(pi ~ u, data = df)
summary(reg_pc)
# Different variations of the CPI
cpis <- c("CPIMEDSL", "CPIFABSL", "CPIHOSSL")
names(cpis) <- c("P_Med", "P_Food", "P_House")
df_cpi <- fred(cpis, key=api_key, long=TRUE)
head(df)
## End(Not run)
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