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    <title>topic Proc glm for panel data in SAS Forecasting and Econometrics</title>
    <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Proc-glm-for-panel-data/m-p/354366#M2301</link>
    <description>&lt;P&gt;Hi everybody&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I am using an unbalanced panel data set over individuals and want to estimate pooled ols(POLS), fixed effect (FE) and random effect (RE). Furthermore, I would like to make a hausman test, in order to see which of the FE or RE is preferred.&lt;/P&gt;&lt;P&gt;I cannot use the proc panel command, as my dataset is too big (error says insufficient memory). So far I have used proc glm, but I am not sure about its ability to produce robust standard errors from and it does not seem possible to perform a hausman test using this statement. Are there any better solutions for these estimations?&lt;/P&gt;&lt;P&gt;My current code looks like this:&lt;/P&gt;&lt;P&gt;POLS&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;Proc Glm data=merged;
Class year edu municipal;
Model Lnw= age lnedens lnfsize edu year municipal /solution;
Run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;FE&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;Proc Glm data=merged;
Absorb id;
Class year edu municipal;
Model Lnw= age lnedens lnfsize edu year municipal /solution;
Run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;RE&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;Proc Glm data=merged;
Class year edu municipal;
Model Lnw= age lnedens lnfsize edu year municipal /solution;
Random age lnedens lnfsize edu year municipal;
Run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;The RE gives me the same as POLS, but with the error statement saying only class variables are allowed in random statement. When I try this, I do not get any estimates.&lt;/P&gt;&lt;P&gt;Any suggestions as to how I can perform these estimations in a better way?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you&lt;/P&gt;</description>
    <pubDate>Fri, 28 Apr 2017 09:03:22 GMT</pubDate>
    <dc:creator>msj</dc:creator>
    <dc:date>2017-04-28T09:03:22Z</dc:date>
    <item>
      <title>Proc glm for panel data</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Proc-glm-for-panel-data/m-p/354366#M2301</link>
      <description>&lt;P&gt;Hi everybody&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I am using an unbalanced panel data set over individuals and want to estimate pooled ols(POLS), fixed effect (FE) and random effect (RE). Furthermore, I would like to make a hausman test, in order to see which of the FE or RE is preferred.&lt;/P&gt;&lt;P&gt;I cannot use the proc panel command, as my dataset is too big (error says insufficient memory). So far I have used proc glm, but I am not sure about its ability to produce robust standard errors from and it does not seem possible to perform a hausman test using this statement. Are there any better solutions for these estimations?&lt;/P&gt;&lt;P&gt;My current code looks like this:&lt;/P&gt;&lt;P&gt;POLS&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;Proc Glm data=merged;
Class year edu municipal;
Model Lnw= age lnedens lnfsize edu year municipal /solution;
Run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;FE&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;Proc Glm data=merged;
Absorb id;
Class year edu municipal;
Model Lnw= age lnedens lnfsize edu year municipal /solution;
Run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;RE&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;Proc Glm data=merged;
Class year edu municipal;
Model Lnw= age lnedens lnfsize edu year municipal /solution;
Random age lnedens lnfsize edu year municipal;
Run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;The RE gives me the same as POLS, but with the error statement saying only class variables are allowed in random statement. When I try this, I do not get any estimates.&lt;/P&gt;&lt;P&gt;Any suggestions as to how I can perform these estimations in a better way?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you&lt;/P&gt;</description>
      <pubDate>Fri, 28 Apr 2017 09:03:22 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Proc-glm-for-panel-data/m-p/354366#M2301</guid>
      <dc:creator>msj</dc:creator>
      <dc:date>2017-04-28T09:03:22Z</dc:date>
    </item>
    <item>
      <title>Re: Proc glm for panel data</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Proc-glm-for-panel-data/m-p/354493#M2302</link>
      <description>&lt;P&gt;Because you would like a Hausman test, you could try the following to get PROC PANEL to work.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;1. Increase the memory footprint so that the dataset may fit. &amp;nbsp;See the following link for the MEMSIZE system option:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="http://support.sas.com/documentation/cdl/en/hostwin/69955/HTML/default/viewer.htm#n0srij4mcdpzv2n1vtphltb00xjw.htm" target="_blank"&gt;http://support.sas.com/documentation/cdl/en/hostwin/69955/HTML/default/viewer.htm#n0srij4mcdpzv2n1vtphltb00xjw.htm&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;2. Consider using the high-performance version of PROC PANEL: PROC HPPANEL. &amp;nbsp;See&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="http://support.sas.com/documentation/cdl/en/etshpug/68149/HTML/default/viewer.htm#etshpug_hppanel_toc.htm" target="_blank"&gt;http://support.sas.com/documentation/cdl/en/etshpug/68149/HTML/default/viewer.htm#etshpug_hppanel_toc.htm&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Finally, we continuously make performance improvements to our panel-data procedures in SAS/ETS. &amp;nbsp;If you would like to email me at Bobby.Gutierrez@sas.com and let me know the version of SAS/ETS you are using, and how big of a dataset we're dealing with, I'd be glad to provide more specific advice.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;--bobby&lt;/P&gt;</description>
      <pubDate>Fri, 28 Apr 2017 14:45:03 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Proc-glm-for-panel-data/m-p/354493#M2302</guid>
      <dc:creator>bobby_sas</dc:creator>
      <dc:date>2017-04-28T14:45:03Z</dc:date>
    </item>
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