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Re: st: re: Troubleshooting 'not sorted' and 'not regularly spaced' errors

From   Michael Hanson <>
Subject   Re: st: re: Troubleshooting 'not sorted' and 'not regularly spaced' errors
Date   Mon, 13 Oct 2008 14:19:31 -0400


Kit is, of course, correct that one can use -ivreg2- (from SSC; runs in Stata 9) or -ivregress- (Stata 10 only) to mimic the -newey- and - newey2- estimators, as all allow you to get Newey-West style heteroskedasticity and autocorrelation consistent (HAC) standard errors. There are a few additional points worth noting in order to make sure these various Stata commands are delivering the HAC estimator that you have in mind. And when you have time series with "gaps" and use lagged regressors, you may need to pay close attention to whether you -tsset- or -xtset- to a Stata date variable (with gaps) or a linear time trend (without gaps).

1. If m is the number of lags you would specify in -newey- or - newey2-, then use m for the -ivregress, vce(hac nw m)- command, but n=m+1 for the -ivreg2, bw(n)- command. As you point out, it takes some effort or experimentation to extract this information from the - ivreg2- help file.

2. To match the HAC SE estimates of -newey- or -newey2-, you will need to add the options -robust small- to an -ivreg2- estimation and the option -small- to an -ivregress- estimation.

3. If you -tsset- (or -xtset-) your data to a Stata date variable with gaps, you may not get the same HAC SE estimates from -newey2, force- as from -ivreg2- or -ivregress- when lagged regressors are included. You can modify my earlier example program to demonstrate that fact (left as an exercise). This problem may or may not occur in your dataset.

4. If you instead -tsset- (or -xtset-) to a sequential linear time trend (-gen t = _n-), then you will get the same results for all three commands -- but you will have, in effect, told Stata that there are no gaps in your data. Indeed, you likely will have included a larger set of observations in your regressions, so both the coefficient estimates and the SE estimates are likely to differ from those in (3).

Which of (3) or (4) above is preferable depends on how you think the "gaps" should be handled. Stata constructs lags by strictly using the prior observation at the frequency specified. For example, if you have business daily data (as in the example program in my prior message) and -tsset- to a daily Stata date variable, Stata will not construct any lags for a Monday, as the prior daily observation (Sunday) is missing in that financial data set. However, you may well want Stata to treat Friday as the prior observation -- which will require you to pay close attention to the construction of your data and then to -tsset- to a time trend. (Other statistical packages that specialize in time series estimation, such as RATS and (IIRC) EViews, have an explicit "business daily" frequency as this problem arises regularly in applications with financial data. One still has to think about how to handle holidays in that case.) If instead you have data with regular gaps -- such as every two or every five years of annual data -- you can use the -delta- option of - tsset- or -xtset- to have Stata treat the prior two- or five-year observation as the lagged value.


On Oct 13, 2008, at 12:27 PM, Thomas Jacobs wrote:


Thanks for introducing me to ivregress and ivreg2 for use in newey
west estimation.  I was unfamiliar with both commands.  I confirmed
they run just as you indicated with both the examples Michael Hanson
provided as well as the questions from my original post.  No problems
with either time series commands or gaps.

Is the translation between newey west lags and bartlett kernel
bandwidth simply bandwidth = lags +1 as it appears?  I was unsure from
the ivreg2 help file.  Thanks again.


On Sat, Oct 11, 2008 at 3:07 PM, Kit Baum <> wrote:
< >
Re Michael Hanson's comments on David Roodman's -newey2-: David has on more than one occasion suggested that those wanting to calculate Newey- West standard errors in an OLS regression should just use -ivreg2- of Baum, Schaffer, Stillman. Despite its name it is happy to estimate OLS models without any instruments, and it can estimate Newey-West standard errors as
well as a variety of other HAC models. E.g.

ivreg2 irx t, robust bw(9)

Notice that it reports the presence of gaps but does not choke on them.
-ivreg2- requires Stata 9.2.

In fact, contradictory to its syntax diagram, -ivregress- can do this as
well. The -ivregress- syntax states that the (varlist2 = varlist_iv)
 component is mandatory, but the program does not enforce this:

ivregress 2sls irx t, vce(hac bartlett 8)

works, making no mention of gaps.  -ivregress- requires Stata 10.

Kit Baum, Boston College Economics and DIW Berlin
An Introduction to Modern Econometrics Using Stata:
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