> -----Original Message-----
> From: Babigumira Ronnie [mailto:[email protected]]
> Sent: Tuesday, June 25, 2002 10:23 AM
> To: [email protected]
> Subject: st: Missing values
>
>
> Hi Listers
> I have data on household expenditure. Households bought "x"
> kgs (quan) of
> food crops (exp) worth a certain amount of money (unitvalu).
> However, I
> have cases where the quantity bought is missing (either because the
> household couldn't recall or an error in data collection) however the
> amount spent by these households is known. The variables are
>
> lc1code housecode exp quan unitvalu
> 11233 112331 566 1 500
>
> I would like to replace the missing quantities purchased with
> community
> (lc1code) averages. If the lc1code, food item (exp), unitvalu
> are the same
> then we can deduce the quantity (quan) that can be purchased by that
> amount of money. What I now want to do is to replace all missing
> quantities with a value imputed from community averages. To
> make it more
> clear
>
> If we know that 500/= buys 1kg of cassava in a given community, then a
> respondent in the community who spends 500/= on cassava should
> automatically be purchasing 1kg.
>
> I want to write a code that would automatically execute this for all
> missing cases however, I can't figure out where to start. I would
> appreciate any help.
One way to go might be to create a dataset of mean community prices
using -collapse-, and then use -merge- to apply that data back to your
dataset.
. collapse unitvalu , by(lc1code exp)
. rename unitvalu meanprice
. sort lc1code exp
. save pricedata
. use <original dataset>
. save pricedata
. merge lc1code exp using pricedata
. generate estqty = <amtspent> / meanprice
As it stands, the -collapse- will calcuate the mean price for each
community-exp combination, based on a simple average of the prices in
the dataset. If you want it weighted based on quantity purchased, I
think this will do it:
. collapse (sum) unitvalue quan, by(lc1code exp)
. gen meanprice = unitvalue/quan
. drop unitvalue quan
--Nick Winter
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