AER (version 1.2-9)

USMacroG: US Macroeconomic Data (1950--2000, Greene)

Description

Time series data on 12 US macroeconomic variables for 1950--2000.

Usage

data("USMacroG")

Format

A quarterly multiple time series from 1950(1) to 2000(4) with 12 variables.

gdp

Real gross domestic product (in billion USD),

consumption

Real consumption expenditures,

invest

Real investment by private sector,

government

Real government expenditures,

dpi

Real disposable personal income,

cpi

Consumer price index,

m1

Nominal money stock,

tbill

Quarterly average of month end 90 day treasury bill rate,

unemp

Unemployment rate,

population

Population (in million), interpolation of year end figures using constant growth rate per quarter,

inflation

Inflation rate,

interest

Ex post real interest rate (essentially, tbill - inflation).

References

Greene, W.H. (2003). Econometric Analysis, 5th edition. Upper Saddle River, NJ: Prentice Hall.

See Also

Greene2003, USMacroSW, USMacroSWQ, USMacroSWM, USMacroB

Examples

# NOT RUN {
## data and trend as used by Greene (2003)
data("USMacroG")
ltrend <- 1:nrow(USMacroG) - 1

## Example 6.1
## Table 6.1
library("dynlm")
fm6.1 <- dynlm(log(invest) ~ tbill + inflation + log(gdp) + ltrend, data = USMacroG)
fm6.3 <- dynlm(log(invest) ~ I(tbill - inflation) + log(gdp) + ltrend, data = USMacroG)
summary(fm6.1)
summary(fm6.3)
deviance(fm6.1)
deviance(fm6.3)
vcov(fm6.1)[2,3] 

## F test
linearHypothesis(fm6.1, "tbill + inflation = 0")
## alternatively
anova(fm6.1, fm6.3)
## t statistic
sqrt(anova(fm6.1, fm6.3)[2,5])
 
## Example 8.2
## Ct = b0 + b1*Yt + b2*Y(t-1) + v
fm1 <- dynlm(consumption ~ dpi + L(dpi), data = USMacroG)
## Ct = a0 + a1*Yt + a2*C(t-1) + u
fm2 <- dynlm(consumption ~ dpi + L(consumption), data = USMacroG)

## Cox test in both directions:
coxtest(fm1, fm2)
## ...and do the same for jtest() and encomptest().
## Notice that in this particular case two of them are coincident.
jtest(fm1, fm2)
encomptest(fm1, fm2)
## encomptest could also be performed `by hand' via
fmE <- dynlm(consumption ~ dpi + L(dpi) + L(consumption), data = USMacroG)
waldtest(fm1, fmE, fm2)

## More examples can be found in:
## help("Greene2003")
# }