Running lagged regressions with lapply and two arguments

Question

I am running multiple univariate regressions, like in this reproducible example:

require(dynlm)
data(USeconomic)
US<-USeconomic
vars<-colnames(US)[-2]
a<         


        

Answer 1

To construct R formula, you must paste it all together, not just the predictor side of it. So you need something like:

formula <- as.formula(
    paste("log(GNP)~",
        paste("L(",rep(vars,each=3),",",l,")",sep=""),
        sep = ""
    )
)

and then run

dynlm(formula, data = ...)

Answer 2

Here is an approach using plyr

library(plyr); library(dynlm); library(tseries)

# FUNCTION TO RUN A SINGLE REGRESSION
foo = function(x, l) dynlm(log(GNP) ~ L(get(as.character(x)), l), data = US)

# CREATE PARAMETER GRID
params = expand.grid(x = colnames(US)[-2], l = c(0, 1, 4))

# RUN REGRESSIONS
regressions = mlply(params, foo)

Each element of this list contains details on a single regression from which you can extract your desired output