topic Re: Lagged variables for DiD analysis in SAS Forecasting and Econometrics

Lagged variables for DiD analysis

EmanuelS — Wed, 23 Oct 2013 14:25:39 GMT

Hello,

I have data in the following style:

Group	Date	NumberObservations	Numb. Obs. Last Year
M1XM	01/2008	2	.
M1XM	01/2009	221	2
M1XM	02/2009	452	2
M1XM	03/2009	132	2
M1XM	05/2009	45	2
M1XM	01/2010	2	221
M3GL	01/2008	4	.
M3GL	01/2009	15	4
M3GL	02/2009	45	4
M3GL	03/2009	13	4
M3GL	05/2009	12	4
M3GL	08/2009	1265	4
M3GL	10/2009	985	4
M3GL	12/2009	451	4
M3GL	01/2010	352	15
M3GL	02/2010	41	45
M3GL	03/2010	7	13
M3GL	04/2010	45	.
M3GL	05/2010	62	12

Additional Informations: I need the data "Numb. Obs. Last Year". The data of the year 2008 does not contain a month, nevertheless are the data formated as date (mm/yyyy). For 2008 there are always 01/2008. I need the lagged observations from the month in the previous year. For 2009 I want to use for every month 01/2008. The Dataset is very large.

I tried it with lag function LAG<n>(argument), but my n differs. I'm able to calculate for each observation the n with a macro, but then I fail.

It would be great if anybody can provide me a solution or an approach of solving the problem.

Thank you very much in advance!

Emanuel

Re: Lagged variables for DiD analysis

snoopy369 — Wed, 23 Oct 2013 14:45:12 GMT

SQL Join is probably your best bet - you could do this in a data step merge also, if you set things up ahead of time with a variable for 'desired lag date'.

data have;

input group $ date :anydtdte. numobs desiredlag;

datalines;

M1XM 01/2008 2 .

M1XM 01/2009 221 2

M1XM 02/2009 452 2

M1XM 03/2009 132 2

M1XM 05/2009 45 2

M1XM 01/2010 2 221

M3GL 01/2008 4 .

M3GL 01/2009 15 4

M3GL 02/2009 45 4

M3GL 03/2009 13 4

M3GL 05/2009 12 4

M3GL 08/2009 1265 4

M3GL 10/2009 985 4

M3GL 12/2009 451 4

M3GL 01/2010 352 15

M3GL 02/2010 41 45

M3GL 03/2010 7 13

M3GL 04/2010 45 .

M3GL 05/2010 62 12

;;;;

run;

proc sql;

create table want as

select H.*, L.numobs as lyobs from

have H

left join

have L

on (H.group=L.group) and ((H.date = intnx('YEAR',l.date,1,'s'))

or (year(H.date)=2009 and year(L.date)=2008))

order by H.group, H.date;

quit;

Re: Lagged variables for DiD analysis

Jennifer_beeman — Tue, 29 Oct 2013 19:49:37 GMT

I would do this using PROC TIMEDATA as follows. This will also add in the months that are missing.

If you don't wish to have those months listed, then you can simply say

outarray=outarray(where=(numobs)); thus only printing output where numobs is nonzero and non-missing....

The reason i suggest this over sql is that you are going to have more flexibility in your timeseries analysis in general,

proc timedata data=have outarray=outarray;

by group;

id date interval=month format=date9.;

var numobs;

outarray lagobs;

do t=1 to dim(numobs);

if year(date)=2008 then do;

lagobs=.;

end;

if year(date)=2009 then do;

count=intck('month','01JAN2008'd,date);

lagobs=numobs[t-count];

end;

if year(date)>2009 then do;

previousyear=intnx('year',date,-1,'s');

count=intck('month',previousyear,date);

lagobs=numobs[t-count];

end;

run;

proc print data=outarray;run;

Re: Lagged variables for DiD analysis

EmanuelS — Fri, 01 Nov 2013 10:13:27 GMT

I tried it, but I haven't the PROC TIMEDATA. I have SAS Enterprise Guide 4.3.

Re: Lagged variables for DiD analysis

EmanuelS — Mon, 18 Nov 2013 14:49:05 GMT

Hi all,

I solved the problem by using proc panel.

Here creating lags is very easy.

Kind regards,

Emanuel