Importing libraries

library(dynlm) #for dynamic lag models
library(zoo) #for time series functions
library(readxl) #for reading excel file
library(tidyverse) #for data manuplation
library(lmtest) #for coeftest and bptest
library(TTR) #for time series functions
library(sandwich) #for variance covariance matrices
library(car) #for durbinwatson test and hccm robust standard errors
library(tseries) #for unit root test
library(urca) #for detailed ADF test
library(ecm) #for ECM model
library(forecast) #for forecasting models
library(pdfetch) #for importing financial data
library(knitr) #for presentations
library(modelr) #for adding residuals in datafile
library(astsa) #for applied statistical time series analysis
library(tsbox) #for time series graphs
library(vars) #for estimating VAR model

Importing data

df <- read_excel(“D:/UMT notes/MPhil – MS courses/Applied Econometrics/lectures applied econometrics/lecture 8/TIME SERIES r/logistics data.xlsx”)

library(ARDL)
library(nardl)

df <- df %>% mutate(AGRIAIR = AGRIAIR, AGRISEA = AGRISEA)
ardl <- ardl(LGDP ~ AGRI + AGRIAIR + AGRISEA, data = df, order = c(1,2,2,2))
summary(ardl)

model1 <- auto_ardl(LGDP ~ AGRI + AGRIAIR + AGRISEA, data = df, max_order = c(1,3,3,3), selection = “BIC”)
model1$top_orders

ardl <- ardl(LGDP ~ AGRI + AGRIAIR + AGRISEA, data = df, order = c(1,1,1,1))
summary(ardl)
bounds_t_test(ardl, case = 3)
bounds_f_test(ardl, case = 3)
ce2_ardl <- coint_eq(ardl, case = 3)
uecm <- uecm(ardl)
summary(uecm)

ce2_uecm <- coint_eq(uecm, case = 3)
recm <- recm(uecm, case = 3)
summary(recm)
ce2_recm <- coint_eq(recm)
identical(ce2_ardl, ce2_uecm, ce2_recm)

mult_ardl <- multipliers(ardl)
mult_ardl

mult_uecm <- multipliers(uecm)
mult_uecm