Arellano and Bond (1991) or Blundell and Bond (1998) in R estimation

Question

I have the following problem with the Arellano and Bond (1991) or Blundell and Bond (1998) estimators in R using the plm package. I receive the following problem when trying to run the needed regression:

The dataset could be found here: https://drive.google.com/file/d/1WUCrMCi7bJmhYbzZxNuXDpFIwXJTqdh3/view?usp=sharing

My code is the following, it seems that I do everything correctly, the formula I need to be estimated is the following:

remove(list=ls())

library(plm)
library(dplyr)
library(ggplot2)
library(prodest)
library(estprod)
library(broom)
library(pdynmc)

pckg<-c("plm","readxl","dplyr","ggplot2", "broom","prodest", "estprod")
#install.packages(c("plm","readxl","dplyr","ggplot2", "broom","prodest", "estprod"))
lapply(pckg, require, character.only = TRUE)

# Set the working directory
setwd("C:/Users/vadya/Desktop/baka")

# Downloading the survey data
Data <- read.csv("test.csv", header=TRUE, sep=",")
str(Data)

Data$ID<-as.numeric(as.factor(Data$ID))

summary(Data)

DataA11 <- Data %>% 
  filter(NACE == 'A' & Year < 2013) %>% 
  filter(VA > 0, L > 0, FA > 0, M > 0, Turn > 0, TA > 0) %>%
  mutate(ID = ID,
         Year = Year,
         l = log(L),
         va = log(VA),
         fa = log(FA),
         m = log(M),
         turn = log(Turn),
         ta = log(TA),
         ff1 = (LTD + STD)/TA,
         ff2 = lag(Cash),
         ff4 = FA/Sales,
         ff5 = TFA/TA)

####################################################################################

mod2LP <- prodest::prodestLP(DataA11$turn, fX = DataA11$l, sX = DataA11$fa, pX = DataA11$m, idvar = DataA11$ID, timevar = DataA11$Year, 
                             R = 100, cX = NULL, opt = "optim", theta0 = NULL, cluster = NULL, tol = 1e-100, exit = FALSE)  
mod2LP
omegaLP <- prodest::omega(mod2LP)
summary(mod2LP)
summary(omegaLP)

DataA11$omega <- prodest::omega(mod2LP) 

######################################################################################

DataA11 <- DataA11 %>%
  arrange(ID, Year) %>%
  group_by(ID) %>%
  mutate(domega = omega - dplyr::lag(omega),
         debt = LTD + STD,
         ddebt = debt - dplyr::lag(debt),
         dsales = Sales - dplyr::lag(Sales)) %>%
  ungroup

PDataA11 <- pdata.frame(DataA11, index = c("ID","Year"))

pdim(PData)
pvar(PData)

z1 <- pgmm(domega ~ lag(domega, 1:2) + ddebt + ff1 + ff1:ddebt + Age + ta + dsales | lag(domega, 2:99),
           data = PDataA11, effect = "twoways", model = "twosteps")
summary(z1, robust = TRUE)

ALSO! It would be perfect if you provide any information on that package and also what I do incorrectly + would be great if you said how to add fixed effects to this pgmm function.

Thanks a lot to each of you in advance!!!:)

UPDATE:

data("EmplUK", package = "plm")

## Arellano and Bond (1991), table 4 col. b 
emp.gmm <- pgmm(log(emp)~lag(log(emp), 1:2)+lag(log(wage), 0:1)+log(capital)+
                  lag(log(output), 0:1)|lag(log(emp), 2:99),
                data = EmplUK, effect = "twoways", model = "twosteps")
summary(emp.gmm)

I run this code, that is provided here: https://rdrr.io/cran/plm/man/pgmm.html

and I get the following message: