## TESTING FOR STRUCTURAL CHANGE ---- ## There appears to be structural differences in valuation during the 1920's and 1930's and then again in the last 60's ## and early 70's. Run a version of the Chow Test with dummy variables to determine if there were structural breaks. ## Define dummy variables for 20's & 30's and 60's & 70's separately. We are creating two dummy variables as we don't ## know if the nature of the structural change is the same or different for the two time periods. df.3$D1 <- NA df.3$D2 <- NA for(i in 1:length(df.3$Dates)){ if(df.3$Dates[i] < 1940){ df.3$D1[i] <- 1 } else { df.3$D1[i] <- 0 } if(df.3$Dates[i] > 1965 & df.3$Dates[i] < 1975){ df.3$D2[i] <- 1 } else { df.3$D2[i] <- 0 } } ## Create Interaction terms between dummy variables and CAPE Ratio. df.3$I1 <- df.3$CAPE*df.3$D1 df.3$I2 <- df.3$CAPE*df.3$D2 ## Chow Test Model chow_model <- lm(df.3$Annualized ~., data = df.3[ ,c(-2,-3)]) summary(chow_model)