# Chow Test for Structural Break 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. ```r chow.test( x, SB, nboot = 500, start = NULL, end = NULL, frequency = NULL, format = NULL, dateVector = NULL ) ``` ## 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 ## Returns 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 ## Examples ```r # 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) ``` ## 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`

chow.test function