svars (version 1.3.11)

chow.test: Chow Test for Structural Break

Description

The Chow test for structural change is implemented as sample-split and break-point test (see Luetkepohl and Kraetzig, 2004, p. 135). An estimated VAR model and the presupposed structural break need to be provided.

Usage

chow.test(
  x,
  SB,
  nboot = 500,
  start = NULL,
  end = NULL,
  frequency = NULL,
  format = NULL,
  dateVector = NULL
)

Value

A list of class "chow" with elements

lambda_bp

Test statistic of the Chow test with break point

testcrit_bp

Critical value of the test statistic lambda_bp

p.value_bp

p-value of the test statistic lambda_bp

lambda_sp

Test statistic of the Chow test with sample split

testcrit_sp

Critical value of the test statistic lambda_sp

p.value_sp

p-value of the test statistic lambda_sp

SB

Structural break tested

SBcharacter

Structural break tested as character

p

Number of lags used

Arguments

x

An object of class 'vars', 'vec2var', 'nlVar'. Estimated VAR object. Or an object of class 'chowpretest' from stability()

SB

Integer, vector or date character. The structural break is specified either by an integer (number of observations in the pre-break period), a vector of ts() frequencies if a ts object is used in the VAR or a date character. If a date character is provided, either a date vector containing the whole time line in the corresponding format or common time parameters need to be provided

nboot

Integer. Number of bootstrap iterations to calculate quantiles and p-values

start

Character. Start of the time series (only if dateVector is empty)

end

Character. End of the time series (only if dateVector is empty)

frequency

Character. Frequency of the time series (only if dateVector is empty)

format

Character. Date format (only if dateVector is empty)

dateVector

Vector. Vector of time periods containing SB in corresponding format

References

Luetkepohl, H., 2005. New introduction to multiple time series analysis, Springer-Verlag, Berlin.
Luetkepohl, H., Kraetzig, M., 2004. Applied time series econometrics, Cambridge University Press, Cambridge.

See Also

stability

Examples

# \donttest{
# Testing for structural break in USA data
#' # data contains quartlery observations from 1965Q1 to 2008Q2
# assumed structural break in 1979Q3
# x = output gap
# pi = inflation
# i = interest rates
set.seed(23211)
v1 <- vars::VAR(USA, lag.max = 10, ic = "AIC" )
z1 <- chow.test(v1, SB = 59)
summary(z1)

#Using stability() to find potential break point and sample split
x1 <- stability(v1, type = "mv-chow-test")
plot(x1)
z1.1 <- chow.test(x1)
summary(z1.1)
#Or using sample split as benchmark
x1$break_point <- FALSE
z1.1 <- chow.test(x1)
summary(z1.1)

#Structural brake via Dates
#given that time series vector with dates is available
dateVector <- seq(as.Date("1965/1/1"), as.Date("2008/7/1"), "quarter")
z2 <- chow.test(v1, SB = "1979-07-01", format = "%Y-%m-%d", dateVector = dateVector)
summary(z2)

# alternatively pass sequence arguments directly
z3 <- chow.test(v1, SB = "1979-07-01", format = "%Y-%m-%d",
                start = "1965-01-01", end = "2008-07-01",
                frequency = "quarter")
summary(z3)

# or provide ts date format (For quarterly, monthly, weekly and daily frequencies only)
z4 <- chow.test(v1, SB = c(1979,3))
summary(z4)
# }