HAC standard errors

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:

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