inst/tests/arguments_for_StepByStepFunctionChecksEducData.R

In pdynmc: Moment Condition Based Estimation of Linear Dynamic Panel Data Models

rm(list = ls())


#	install.packages("pdynmc")
library(pdynmc)


data(cigDemand, package = "pdynmc")
dat <- cigDemand


dat$y			<- log(dat$packpc)				# response variable log(Q^Cigarettes)
dat$x			<- log(dat$avgprs/dat$cpi)			# endogenous variable log(P^Cigarettes)
dat$z1		<- (dat$taxs - dat$tax)/dat$cpi		# instrument 1 SalesTax
dat$z2		<- dat$tax/dat$cpi				# instrument 2 CigTax
dat$w			<- log((dat$income/dat$pop)/dat$cpi)	# exogenous variable log(rincome)






dat = dat
varname.i = "state"
varname.t = "year"

use.mc.diff = FALSE
use.mc.lev = TRUE
use.mc.nonlin = FALSE
use.mc.nonlinAS = NULL
inst.stata = FALSE

include.y = FALSE
varname.y = "y"
lagTerms.y = 1
maxLags.y = 4

include.x = TRUE
varname.reg.end = NULL
lagTerms.reg.end = NULL
maxLags.reg.end = NULL
varname.reg.pre = NULL
lagTerms.reg.pre = NULL
maxLags.reg.pre = NULL
varname.reg.ex = c("z1")
lagTerms.reg.ex = c(0)
maxLags.reg.ex = c(2)
include.x.instr = TRUE
varname.reg.instr = c("z1")
inst.reg.ex.expand = FALSE
include.x.toInstr = TRUE
varname.reg.toInstr = "x"

fur.con = TRUE
fur.con.diff = TRUE
fur.con.lev = FALSE
varname.reg.fur = "w"
lagTerms.reg.fur = 0

include.dum = FALSE
dum.diff = NULL
dum.lev = NULL
varname.dum = NULL

col_tol = 0.65
w.mat = "iid.err"
w.mat.stata = FALSE

std.err = "corrected"
estimation = "twostep"
max.iter = 4
iter.tol = 0.01
inst.thresh = NULL
opt.meth = "none"
hessian = FALSE
optCtrl = list(kkt = FALSE, kkttol = .Machine$double.eps^(1/3), kkt2tol =
    .Machine$double.eps^(1/3), starttests = TRUE, dowarn = TRUE, badval = (0.25) *
    .Machine$double.xmax, usenumDeriv = FALSE, reltol = 1e-12, maxit = 200, trace = TRUE,
    follow.on = FALSE, save.failures = TRUE, maximize = FALSE, factr = 1e+07, pgtol = 0,
    all.methods = FALSE)
custom.start.val = FALSE
start.val = NULL
start.val.lo = -1
start.val.up = 1
seed.input = 2