Stata The Stata listserver
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

Re: st: Decimal precision, again


From   wgould@stata.com (William Gould, Stata)
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Decimal precision, again
Date   Mon, 28 Jul 2003 08:03:11 -0500

Sylvain Friederich <S.Friederich@bristol.ac.uk> has solved the problem 
with float rounding and promoted his float variable to double using 

        . gen double fixed = round(price*10,1)/10

About the data and the fix, Sylvain writes, 

> The variable I am considering is a share price. It will not take on very
> large values, and can have no more than two-digit decimal precision.  [...]
>
>       . list price in 1/6
>
>       417.8
>       418.68
>       418.9
>       419.28
>       425.35
>       426.55

The reason Sylvain wanted to promote price from float to double was 

> [...]although the Editor displays them as above, clicking on those cells
> shows that Stata really holds them as:

        417.7999
        418.67999
        418.89999
        419.28
        425.35001
        426.54999

Sylvain asks,

> For the sake of completeness, would my original intuition (coarse though it
> may have been) of outsheeting and re-insheeting the dataset right away with
> the "double" option have worked?

Yes it would have worked.  Displayed with the default %9.0g, the values were 
rounded in the desired way, so after -outfile-ing, -infile- would have 
seen 417.8, 418.68, 418.9, ...

If Sylvain's desire to promote the variable was based solely on a desire 
to have the editor show the full values as 417.8, 418.68, 418.9, ..., rather
than 417.7999, 418.67999, 418.89999, ..., then I have no qualm.  The error,
however, was never much.  Taking the 418.68 case, the float value stored
differed from the desired 418.68 by about 0.000007324219 (absolutely) and
0.000000017535 (relatively).  Relative error is what matters in statistical
calculations and there is not enough to matter.

All that said, we here at Stata have written do-files to do accounting
applications and, for those calculations, is is absolute error that matters.
Moreover, accountants, the IRS, etc., prefer sums be accurate to the penny.
When storing larger numbers, such as 418,680.02, the relative error remains
the same, approximately, but the absolute error grows, in this case to .01125,
which is too much for accountants.  In financial datasets, the best way to
store dollar amounts is in pennies as integers.  This abolishes round-off
error for addition and substraction and a -long- takes no more memory than a
-float-.  If amounts need to exceed $21 million, then use doubles (and still 
record pennies).

-- Bill
wgould@stata.com
*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/



© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index