Description Details Author(s) References Examples
Allows you to create an evidence factor (EX analysis) in an instrumental variables regression model. Additionally, performs Sensitivity analysis for OLS analysis, 2SLS analysis and EX analysis with interpretable plotting and printing features.
Index: This package was not yet installed at build time.
Bikram Karmakar
Maintainer: Bikram Karmakar <bikramk@wharton.upenn.edu>
~~ Literature or other references for background information ~~
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | data("CigarettesSW", package = "AER")
CigarettesSW$rprice <- with(CigarettesSW, price/cpi)
CigarettesSW$rincome <- with(CigarettesSW, income/population/cpi)
CigarettesSW$tdiff <- with(CigarettesSW, (taxs - tax)/cpi)
########################
lmfit <- lm(log(packs) ~ log(rprice) + log(rincome), data = CigarettesSW, subset = year == "1995")
z <- senslm(lmfit, variable = 'log(rprice)')
z
plot(z)
######################
library(AER)
fm1 <- ivreg(log(packs) ~ log(rprice) + log(rincome) | tdiff + log(rincome),
data = CigarettesSW, subset = year == "1995", x=TRUE)
z <- sensIvreg(fm1, variable = 'log(rprice)')
z
plot(z)
######################
fm2 <- ivreg.EX(log(packs) ~ log(rprice) + log(rincome) | tdiff + log(rincome),
data = CigarettesSW, subset = year == "1995")
lmfit <- lm(log(packs) ~ log(rprice) + log(rincome), data = CigarettesSW,
subset = year == "1995")
res = coeftestIV(fm2, lmfit, 'log(rprice)')
z <- sensIvreg(fm2, res, 'log(rprice)', effect = c(-.1, 0, .1, .15, .17))
z
plot(z)
###################
x = CigarettesSW[CigarettesSW[,'year'] == "1995", c('rprice', 'rincome')]
y = CigarettesSW[CigarettesSW[,'year'] == "1995", c('packs')]
z = CigarettesSW[CigarettesSW[,'year'] == "1995", c('tdiff', 'rincome')]
fm3 <- ivreg.fit.EX(as.matrix(x), y, z)
lmfit <- lm(packs ~ rprice + rincome, data = CigarettesSW, subset = year == "1995")
res = coeftestIV(fm3, lmfit, 'rprice')
z <- sensIvreg(fm3, res, 'rprice', effect = c(-.1, 0, .1, .15, .17))
z
plot(z)
##################
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