sctest.formula: Structural Change Tests in Linear Regression Models

Description

Performs tests for structural change in linear regression models.

Usage

# S3 method for formula
sctest(formula, type = , h = 0.15,
    alt.boundary = FALSE, functional = c("max", "range",
    "maxL2", "meanL2"), from = 0.15, to = NULL, point = 0.5,
    asymptotic = FALSE, data, ...)

Value

An object of class "htest" containing:

statistic: the test statistic,
p.value: the corresponding p value,
method: a character string with the method used,
data.name: a character string with the data name.

Arguments

formula: a formula describing the model to be tested.
type: a character string specifying the structural change test that is to be performed, the default is "Rec-CUSUM". Besides the test types described in efp and sctest.Fstats the Chow test and the Nyblom-Hansen test can be performed by setting type to "Chow" or "Nyblom-Hansen", respectively.
h: numeric from interval (0,1) specifying the bandwidth. Determines the size of the data window relative to the sample size (for MOSUM and ME tests only).
alt.boundary: logical. If set to TRUE alternative boundaries (instead of the standard linear boundaries) will be used (for CUSUM processes only).
functional: indicates which functional should be used to aggregate the empirical fluctuation processes to a test statistic.
from, to: numeric. If from is smaller than 1 they are interpreted as percentages of data and by default to is taken to be the 1 - from. F statistics will be calculated for the observations (n*from):(n*to), when n is the number of observations in the model. If from is greater than 1 it is interpreted to be the index and to defaults to n - from. (for F tests only)
point: parameter of the Chow test for the potential change point. Interpreted analogous to the from parameter. By default taken to be floor(n*0.5) if n is the number of observations in the model.
asymptotic: logical. If TRUE the asymptotic (chi-square) distribution instead of the exact (F) distribution will be used to compute the p value (for Chow test only).
data: an optional data frame containing the variables in the model. By default the variables are taken from the environment which sctest is called from.
...: further arguments passed to efp or Fstats.

Details

sctest.formula is a convenience interface for performing structural change tests in linear regression models based on efp and Fstats. It is mainly a wrapper for sctest.efp and sctest.Fstats as it fits an empirical fluctuation process first or computes the F statistics respectively and subsequently performs the corresponding test. The Chow test and the Nyblom-Hansen test are available explicitly here.

An alternative convenience interface for performing structural change tests in general parametric models (based on gefp) is available in sctest.default.

Examples

Run this code

## Example 7.4 from Greene (1993), "Econometric Analysis"
## Chow test on Longley data
data("longley")
sctest(Employed ~ Year + GNP.deflator + GNP + Armed.Forces, data = longley,
  type = "Chow", point = 7)

## which is equivalent to segmenting the regression via
fac <- factor(c(rep(1, 7), rep(2, 9)))
fm0 <- lm(Employed ~ Year + GNP.deflator + GNP + Armed.Forces, data = longley)
fm1 <- lm(Employed ~ fac/(Year + GNP.deflator + GNP + Armed.Forces), data = longley)
anova(fm0, fm1)

## estimates from Table 7.5 in Greene (1993)
summary(fm0)
summary(fm1)