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


From   "Mark Schaffer" <[email protected]>
To   [email protected]
Subject   Re: st: Re: -newey2- vs. -ivreg2-
Date   Thu, 13 Jan 2005 09:58:49 -0000

Clive,

Try adding the -robust- option to ivreg2.  I think the problem is 
that you are requesting from ivreg2 standard errors that are robust 
to autocorrelation but not heteroskedasticity.  ivreg2 can provide 
standard errors with and without heteroskedasticity-robustness, but 
newey and newey2 standard errors are always the robust type.

Cheers,
Mark

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

> 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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Prof. Mark E. Schaffer
Director
Centre for Economic Reform and Transformation
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS  UK
44-131-451-3494 direct
44-131-451-3296 fax
44-131-451-3485 CERT administrator
http://www.sml.hw.ac.uk/cert

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