add standard TSLS standard errors

[remlapmot]

It's great that you have interfaced to the heteroskedasticity robust standard errors but would you mind adding the standard TSLS SEs. For the example you're using from the AER R package the default SEs from the ivreg() output are as follows:

library(Ecdat)
library(AER)
data(Cigarette)
attach(Cigarette)
y <- log(packpc)
x1 <- log(income/pop/cpi)
x2 <- log(avgprs/cpi)
z1 <- (taxs - tax)/cpi
z2 <- tax/cpi
iv <- ivreg(y ~ x1 + x2 | x1 + z1 + z2, subset=year==1995)
summary(iv)

Call:
ivreg(formula = y ~ x1 + x2 | x1 + z1 + z2, subset = year == 
    1995)

Residuals:
       Min         1Q     Median         3Q        Max 
-0.6006931 -0.0862222 -0.0009999  0.1164699  0.3734227 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   9.8950     1.0586   9.348 4.12e-12 ***
x1            0.2804     0.2386   1.175    0.246    
x2           -1.2774     0.2632  -4.853 1.50e-05 ***

---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.1879 on 45 degrees of freedom
Multiple R-Squared: 0.4294, Adjusted R-squared: 0.4041 
Wald test: 13.28 on 2 and 45 DF,  p-value: 2.931e-05 

cheers, Tom

[gragusa]

Thank you for pointing this out. Code for the homoskedastic standard errors was written by there was no way to call it. I have changed things so that the default show method gives these standard errors as default

using RDatasets
using DataFramesMeta
cig = dataset("Ecdat", "Cigarette")
cig[:lrincome] = @with(cig, log(:Income./:POP./:CPI));
cig[:lrprice] = @with(cig, log(:AvgPrs./:CPI));
cig[:tdiff] = @with(cig, (:Taxs - :Tax)./:CPI)
cig[:rtax] = @with(cig, :Tax./:CPI)
cig95 = @ix(cig, :Year .== 1995)
y = convert(Array, log(cig95[:PackPC]));
x = convert(Array, [ones(size(cig95,1)) cig95[:lrincome] cig95[:lrprice]])
z = convert(Array, [ones(size(cig95,1)) cig95[:lrincome] cig95[:tdiff] cig95[:rtax]])

iv = ivreg(x, z, y)

InstrumentalVariables.LinearIVModel{InstrumentalVariables.DenseIVPredChol{Float64,Base.LinAlg.Cholesky{Float64,Array{Float64,2}}}}:

Coefficients:
     Estimate Std.Error  t value Pr(>|t|)
x1    9.89496   1.05856  9.34756   <1e-99
x2   0.280405  0.238565  1.17538   0.0836
x3   -1.27742  0.263199 -4.85346   <1e-99

To get the HC1() standard errors --- the default in STATA when ,rob is used

coeftable(iv, HC1())