PhillipsCurve {strucchange} | R Documentation |
Macroeconomic time series from the United Kingdom with variables for estimating the Phillips curve equation.
data(PhillipsCurve)
A multivariate annual time series from 1857 to 1987 with the columns
p
,w
,u
u
,dp
.The data is available online in the data archive of the Journal of Applied Econometrics http://qed.econ.queensu.ca/jae/2003-v18.1/bai-perron/.
Alogoskoufis G.S., Smith R. (1991), The Phillips Curve, the Persistence of Inflation, and the Lucas Critique: Evidence from Exchange Rate Regimes, American Economic Review, 81, 1254-1275.
Bai J., Perron P. (2003), Computation and Analysis of Multiple Structural Change Models, Journal of Applied Econometrics, 18, 1-22.
## load and plot data data(PhillipsCurve) uk <- window(PhillipsCurve, start = 1948) plot(uk[, "dp"]) ## AR(1) inflation model ## estimate breakpoints bp.inf <- breakpoints(dp ~ dp1, data = uk, h = 8) plot(bp.inf) summary(bp.inf) ## fit segmented model with three breaks fac.inf <- breakfactor(bp.inf, breaks = 2, label = "seg") fm.inf <- lm(dp ~ 0 + fac.inf/dp1, data = uk) summary(fm.inf) ## Results from Table 2 in Bai & Perron (2003): ## coefficient estimates coef(bp.inf, breaks = 2) ## corresponding standard errors sqrt(sapply(vcov(bp.inf, breaks = 2), diag)) ## breakpoints and confidence intervals confint(bp.inf, breaks = 2) ## Phillips curve equation ## estimate breakpoints bp.pc <- breakpoints(dw ~ dp1 + du + u1, data = uk, h = 5, breaks = 5) ## look at RSS and BIC plot(bp.pc) summary(bp.pc) ## fit segmented model with three breaks fac.pc <- breakfactor(bp.pc, breaks = 2, label = "seg") fm.pc <- lm(dw ~ 0 + fac.pc/dp1 + du + u1, data = uk) summary(fm.pc) ## Results from Table 3 in Bai & Perron (2003): ## coefficient estimates coef(fm.pc) ## corresponding standard errors sqrt(diag(vcov(fm.pc))) ## breakpoints and confidence intervals confint(bp.pc, breaks = 2, het.err = FALSE)