jocci: U.S. Macroeconomic Time Series

In lmtest: Testing Linear Regression Models

U.S. Macroeconomic Time Series

Description

Several macroeconomic time series from the U.S.

Usage

data(fyff)
data(gmdc)
data(ip)
data(jocci)
data(lhur)
data(pw561)

Format

All data sets are multivariate monthly time series from 1959(8) to 1993(12) (except 1993(10) for jocci) with variables

y

original time series,

dy

transformed times series (first differences or log first differences),

dy1

transformed series at lag 1,

dy2

transformed series at lag 2,

dy3

transformed series at lag 3,

dy4

transformed series at lag 4,

dy5

transformed series at lag 5,

dy6

transformed series at lag 6.

Details

The description from Stock & Watson (1996) for the time series (with the transformation used):

fyff

interest rate (first differences),

gmdc

pce, implicit price deflator: pce (1987 = 100) (log first differences),

ip

index of industrial production (log first differences),

jocci

department of commerce commodity price index (log first differences),

lhur

unemployment rate: all workers, 16 years & over (%, sa) (first differences),

pw561

producer price index: crude petroleum (82 = 100, nsa) (log first differences).

Stock & Watson (1996) fitted an AR(6) model to all transformed time series.

Source

Stock & Watson (1996) study the stability of 76 macroeconomic time series, which can be obtained from Mark W. Watson's homepage at http://www.princeton.edu/~mwatson/ddisk/bivtvp.zip.

References

J.H. Stock & M.W. Watson (1996), Evidence on Structural Instability in Macroeconomic Time Series Relations. Journal of Business & Economic Statistics 14, 11–30.

Examples

data(jocci)

dwtest(dy ~ 1, data = jocci)
bgtest(dy ~ 1, data = jocci)
ar6.model <- dy ~ dy1 + dy2 + dy3 + dy4 + dy5 +dy6
bgtest(ar6.model, data = jocci)

var.model <- ~ I(dy1^2) + I(dy2^2) + I(dy3^2) + I(dy4^2) + I(dy5^2) + I(dy6^2)
bptest(ar6.model, var.model, data = jocci)

lmtest documentation built on March 22, 2022, 1:06 a.m.