# Re: st: Re: -newey2- vs. -ivreg2-

 From "Clive Nicholas" <[email protected]> To [email protected] Subject Re: st: Re: -newey2- vs. -ivreg2- Date Thu, 13 Jan 2005 03:56:13 -0000 (GMT)

```Kit Baum replied to Mark Schaffer:

> Indeed it can be confusing! Mark is absolutely right--you should ADD
> one to bw(), which starts counting from zero, to match lags(). Sorry
> for the added confusion!

I don't know if Jonathan A. Schwabish, who sent the original post, is now
satisfied, but I'm a bit puzzled. This is what I get when using Garrett
and Mitchell's (2001) infamous dataset, applying Kit and Mark's "for N
lags, add one to the bandwidth" formula:

. newey2 growthpc trade fdi unem left spend captax labtax, lag(1)

Regression with Newey-West standard errors        Number of obs  =       352
maximum lag : 1                                   F(  7,   344)  =      4.89
Prob > F       =    0.0000
----------------------------------------------------------------------------
|             Newey-West
growthpc |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------+----------------------------------------------------------------
trade |   .0051762   .0063955     0.81   0.419     -.007403    .0177555
fdi |   .1112711   .1114347     1.00   0.319     -.107908    .3304503
unem |  -.0917037   .0489144    -1.87   0.062    -.1879127    .0045053
left |  -.0011842   .0035009    -0.34   0.735    -.0080701    .0057017
spend |  -.0295982   .0455134    -0.65   0.516    -.1191177    .0599213
captax |  -.0620164   .0155124    -4.00   0.000    -.0925275   -.0315053
labtax |  -.0282463   .0348024    -0.81   0.418    -.0966986    .0402061
_cons |   6.832187   .9175741     7.45   0.000     5.027425    8.636949
----------------------------------------------------------------------------

. ivreg2 growthpc trade fdi unem left spend captax labtax, bw(2) small

Ordinary Least Squares (OLS) regression
---------------------------------------
Autocorrelation-consistent statistics
kernel=Bartlett; bandwidth=2
time variable (t):  year
group variable (i): nation
Number of obs =      352
F(  7,   344) =     7.30
Prob > F      =   0.0000
Total (centered) SS     =  2042.961127              Centered R2   =   0.1708
Total (uncentered) SS   =  4004.310028              Uncentered R2 =   0.5769
Residual SS             =  1694.045908              Root MSE      =      2.2
----------------------------------------------------------------------------
growthpc |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------+----------------------------------------------------------------
trade |   .0051762   .0073358     0.71   0.481    -.0092525     .019605
fdi |   .1112711   .1040054     1.07   0.285    -.0932954    .3158377
unem |  -.0917037   .0581893    -1.58   0.116    -.2061553     .022748
left |  -.0011842   .0041281    -0.29   0.774    -.0093037    .0069353
spend |  -.0295982   .0382442    -0.77   0.440      -.10482    .0456236
captax |  -.0620164   .0160886    -3.85   0.000    -.0936608    -.030372
labtax |  -.0282463   .0339707    -0.83   0.406    -.0950628    .0385703
_cons |   6.832187   .7036352     9.71   0.000     5.448218    8.216156
----------------------------------------------------------------------------

The coefficients are the same, but the standard errors most certainly
aren't. What's up here? Or, alternatively, what's up with me?

CLIVE NICHOLAS        |t: 0(044)7903 397793
Politics              |e: [email protected]
Newcastle University  |http://www.ncl.ac.uk/geps

References:

Garrett G and Mitchell D (2001) "Globalization, Government Spending and
Taxation in the OECD", EUR J POLIT RES 39(1): 145-77.

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