repeated forecasts gives same values - r

Question

I have a monthly dataset of performance (in terms of %) of different sectors in a company in the form
Date |Sector |Value
2016-01-01 |Sect 1 |-20
2016-02-01 |Sect 1 |10
2016-01-01 |Sect 2 |23
2016-02-01 |Sect 1 |10
the data has 20 Sectors and monthly data till June 2018. Now I want to forecast Value for the next month. I used the below code:
combine_ts <- function(data, h=1, frequency= 12, start= c(2016,5),
end=c(2018,6))
{
results <- list()
sectgrowthsub <- data[!duplicated(sectgrowthdf2[,2]),]
sectgrowthts <- ts(sectgrowthsub[,3], frequency = frequency, start = start,
end = end)
for (i in 1:(nrow(sectgrowthsub))) {
results[[i]] <- data.frame(Date =
format(as.Date(time(forecast(auto.arima(sectgrowthts), h)$mean)), "%b-%y"),
SectorName = rep(sectgrowthsub[,2], h),
PointEstimate = forecast(auto.arima(sectgrowthts),
h=h)$mean[i])
}
return(data.table::rbindlist(results))
}
fore <- combine_ts(sectgrowthsub)
The problem in this case is that Value forecast is the same for all the Sectors.
Help is much appreciated

Answer 1

I took the liberty of simplifying the problem a little bit and removed the function to better show the process of modeling groups separately:
library(magrittr)
library(forecast)
dat <- data.frame(value = c(rnorm(36, 5),
rnorm(36, 50)),
group = rep(1:2, each = 36))
# make a list where each element is a group's timeseries
sect_list <- dat %>%
split(dat$group) %>%
lapply(function(x, frequency, start) {
ts(x[["value"]], frequency = 12, start = 1 ) })
# then forecast on each groups timeseries
fc <- lapply(sect_list, function(x) { data.frame(PointEstimate = forecast(x, h=1)$mean ) }) %>%
do.call(rbind, .) # turn into one big data.frame
fc
PointEstimate
1 5.120082
2 49.752510
Let me know if you get hung up on any parts of this.