About xyz0505

xyz0505 · ‎05-26-2020

If you want to run regular panel model with a really big dataset, you can try SAS viya PROC CPANEL. It saves data parallel which compute the data much faster. But even for regular SAS it can still process large data. Once I tried PROC PANEL with 10 GB data it ran fine. Have you tried to use PROC PANEL with your data?

xyz0505 · ‎03-23-2020

PROC PANEL drop the redundant dummies for you.

xyz0505 · ‎03-18-2020

This is a system error, can you check your SAS and whether it has the ETS license? By the way I just noticed your industry id has duplicated time sequence. Proc Panel suppose you id time look like: id time 1 1 1 2 1 3 1 4 2 1 2 2 2 3 2 4 … … If you have duplicated time periods in one industry I suggest you use dummy directly. Also in proc panel the id statement requires cross section id comes first and then time id: data testdat; input company_name $ year industry_code y x1 x2 x3; datalines; 20_Microns_Ltd 2011 1 956.5 69.8 610.1 542.7 20_Microns_Ltd 2012 1 82.3 5.1 142.8 281.8 20_Microns_Ltd 2013 1 -25.3 -38.2 -98.7 123 20_Microns_Ltd 2014 1 413.7 26.1 130.4 65.8 7Seas_Entertai 2011 2 -121.2 100.9 -96.5 88 7Seas_Entertai 2012 2 -20.9 -80.7 18.6 246 7Seas_Entertai 2013 2 -20.9 -80.7 18.6 246 7Seas_Entertai 2014 2 -2.8 -21.8 -104.8 41.4 7Seas_Entertai 2015 2 7871.9 1086.5 5092.9 5177.8 A_B_B_India_Ltd. 2011 3 -5687.4 -686 -4771.1 1111.3 A_B_B_India_Ltd. 2012 3 678.6 -263.9 -134.7 657.5 A_B_B_India_Ltd. 2013 3 3450.1 26.3 1066.3 1654.9 A_B_B_India_Ltd. 2014 3 1010.7 -41.6 1379.2 41.8 A_B_B_India_Ltd. 2015 3 4309.7 88.4 -2329.2 6173.1 3I_Infotech_Ltd. 2011 1 4309.7 88.4 -2329.2 6173.1 3I_Infotech_Ltd. 2012 1 39.2 -636 -20 235.2 3I_Infotech_Ltd. 2013 1 1056.3 32.1 611.9 555.8 3I_Infotech_Ltd. 2014 1 887.9 56.9 992.2 3359.1 3I_Infotech_Ltd. 2015 1 -174.9 1.2 -519.6 232.9 3I_Infotech_Ltd. 2016 1 -828.7 542.1 -1084.5 2738.2 run; proc sort data=testdat; by company_name year; run; proc panel data=testdat; id company_name year; class industry_code year; model y = x1 x2 year industry_code/ pooled; run;

xyz0505 · ‎03-11-2020

The error indicate you may need to sort the data first. proc sort data=your_data; by industry year; run; PROC PANEL assumes you've already sorted data by cross section first then time.

xyz0505 · ‎03-06-2020

There's a trick you can use to cluster on variable that is not ID using proc panel. If you have an ID variable (maybe firm), time variable, and an ID2 variable you want to cluster on (let's say industry, for example). First sort the data according to id2 variable, and create a new variable called time2. time2 variable give sequence for each observation in each id2 group. Example looks like: id t id2 t2 1 1 1 1 1 2 1 2 1 3 1 3 1 4 1 4 1 5 1 5 1 6 1 6 2 1 1 7 2 2 1 8 2 3 1 9 2 4 1 10 2 5 1 11 2 6 1 12 3 1 2 1 3 2 2 2 3 3 2 3 3 4 2 4 3 5 2 5 3 6 2 6 4 1 2 7 4 2 2 8 4 3 2 9 4 4 2 10 4 5 2 11 4 6 2 12 Then sort the data according to id2 and time2. Then run: proc panel data = panel_example3 ; Id id2 t2; class id; model y = x1 x2 id / pooled hccme=0 cluster; run; should give you fixone model with fixed effects on id but clustering on id2.

xyz0505 · ‎03-06-2020

PANEL and CPANEL can do that, proc panel data = Electricity; id firm year; model cost = production iv/ hccme=0 cluster; run; will give clustered s.e clustering on firm.

xyz0505 · ‎03-06-2020

I'm not sure what you want, for cross section, you just want industry fix effect only or you want both industry and company effect??? For the first one you can do: proc panel data=your_data_name; id industry year; model y = x1 x2 x3 / fixtwo; run; For the second one there's no built in model, you can add all dummies to the pooled model: proc panel data=your_data_name; id company_name year; class company_name year industry; model y = x1 x2 x3 company_name year industry/ pooled; run;

xyz0505 · ‎11-25-2019

Hi, From the PANEL related procs side, there's no other solution as far as I know.

xyz0505 · ‎11-18-2019

Hi, If you have sas viya 3.4 you can try PROC CPANEL. For example, if you have a panel data with id and time to be firm and year, dependent variable to be cost, independent variable to be production (endogenous) and iv, instrumental variable to be iv2, the code is following: proc cpanel data = Electricity; id firm year; endogenous production ; instruments iv2; model cost = production iv/ ivfixtwo printfixed robust; run; should be able to give you the heteroskedasticity robust standard error with twoway fixed effects.

xyz0505 · ‎09-27-2019

Hi, Right now PROC PANEL only provides cluster s.e by id variable.

xyz0505 · ‎06-03-2019

Hi, First of all, I don't think you are estimating a dynamic panel model with your code. To do dynamic GMM, the very first thing is to do first difference to the model and run GMM on the differenced equation. You can find reference in PANEL's user manual detail section for the equations and instrument matrix. Your code seems run everything on raw data. Try the following code: proc panel data=work.panel; id indip year; model Y=A1 A2 A3 A4 A5 B1 B2 C1 C2 D1 / dyndiff; run; DYNDIFF takes care of everything for you. Second, I notice that you only have N=5, and T=20. When T is large it means instruments increase quadratically, and too many instruments bias the estimators. The asymptotic properties is coming from large N. So you can try to limit the number of IVs by using "maxband" option. At last, GMM=1 or 2 doesn't affect the consistency of the estimators, it's just the matter of efficiency or not. I feel like if you are in a large T and small N scenario, it won't be efficient anyway, so it doesn't matter if you are using gmm1 or gmm2.

xyz0505 · ‎03-11-2019

Hi, I mean OLDER VERSION does not support DYNDIFF and DYNSYS, NEW VERSION support. SAS ETS package start to support DYNDIFF and DYNSYS since SAS/ETS 14.3. You are using SAS/ETS 14.2.

xyz0505 · ‎03-05-2019

Hi, The earlier release of SAS 9.4 (with SAS/ETS 13.1) does not support DYNDIFF and DYNSYS. It would be more helpful if you can provide the log file and I can tell which version it is.

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