[R] HAC standard errors

[Achim Zeileis]

On Mon, 2 Jun 2014, Nick Pretnar wrote:

> Hello,
>
> I am having a great amount of difficulty running a simple linear regression model with entity and time fixed effects and HAC standard errors. I have a data set with 3 million observations and 30 variables. My data is structured as follows:
>
> NAME	STATE	YEAR	Y	X1	X2
> 1		1		2012	1	1	1
> 2		1		2012	1	2	7
> 3		1		2012	1	1	2
> 4		2		2012	2	4	5
>
> etc. ... For every state in every year, there are about 10,000 row 
> vectors corresponding to individual observations. This is not a 
> longitudinal dataset: an individual surveyed in year 2000 in state 1 is 
> never spoken to again. Nonetheless, I still wish to control for 
> geographical and time fixed effects. To do so, I run the following:

If you haven't got a longitudinal or time series data, then I wonder why 
you want to consider HAC standard errors (which explicitly try to adjust 
for autocorrelation). I guess that it would be more natural to simply use 
clustered standard errors, some of which are also robust against certain 
types of autocorrelation.

I would recommend that you use the "plm" package for your panel data. If 
you want to employ OLS estimation, you can use plm(..., model = "pooling") 
and adding certain id or time effects. And then plm has a number of vcov* 
functions for certain robust covariances: vcovBK, vcovHC, vcovSCC. See the 
corresponding manual pages for more details.

hth,
Z

>> load("data.frame.rda")
>> library(sandwich)
>> library(pcse)
>> model <- lm(data.frame$Y ~ data.frame$X1 + data.frame$X2 + as.factor(data.frame$state) + as.factor(data.frame$year))
>> vcovHAC(model, prewhite = FALSE, adjust = FALSE, sandwich = TRUE, ar.method = "ols")
>
> R will not return any results, yet acts as if it is computing the results. This goes on for 4 hours or more.
>
> I wanted to run the following:
>
>> library(pcse)
>> model <- lm(data.frame$Y ~ data.frame$X1 + data.frame$X2 + as.factor(data.frame$state) + as.factor(data.frame$year))
>> model.pcse <- pcse(model, groupN = data.frame$state, groupT = data.frame$year)
>
> But I get the error:
>> Error in pcse(model, groupN = BRFSS_OBESEBALANCED$X_STATE, groupT = BRFSS_OBESEBALANCED$YEAR) :
>  There cannot be more than nCS*nTS rows in the using data!
>
> If there are any workarounds for this problem, I would greatly appreciate learning about them.
>
> Thanks,
>
> Nicholas Pretnar
> University of Missouri, Economics
> npretnar at gmail.com
>
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