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    <title>topic Re: Serial Autocorrelation Tobit in SAS Forecasting and Econometrics</title>
    <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/388837#M2602</link>
    <description>&lt;P&gt;Hi,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You can estimate random-effects tobit models in PROC QLIM using the new RANDOM statement. A simple example, based on your model,&amp;nbsp;for the syntax would be&lt;/P&gt;
&lt;P&gt;PROC QLIM;&lt;/P&gt;
&lt;P&gt;MODEL Y = X / censored(lb=0);&lt;/P&gt;
&lt;P&gt;RANDOM INT / SUBJECT=id METHOD=HERMITE(QPOINTS=12);&lt;/P&gt;
&lt;P&gt;RUN;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Currently, PROC QLIM does not offer an option for obtaining robust standard errors for heteroskedasticity and serial correlation.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Please note that xttobit does not have the “robust” option, either.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;If you are willing to specify the nature of the standard errors, then you&amp;nbsp;might estimate your model with PROC NLMIXED by modeling the standard errors explicitly.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Best regards,&lt;/P&gt;
&lt;P&gt;Gunce&lt;/P&gt;</description>
    <pubDate>Thu, 17 Aug 2017 14:59:46 GMT</pubDate>
    <dc:creator>gunce_sas</dc:creator>
    <dc:date>2017-08-17T14:59:46Z</dc:date>
    <item>
      <title>Serial Autocorrelation Tobit</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/388436#M2597</link>
      <description>&lt;P&gt;I have a panel data, and I am running my model like this:&lt;/P&gt;&lt;P&gt;Y = B0 + B1X + error&lt;/P&gt;&lt;P&gt;I ran the model using QLIM procedure, and I need to include the serial autocorrelation to it. The DW test using Proc Autoreg shows significant P-Value as in this examample:&lt;/P&gt;&lt;P&gt;&lt;A href="http://support.sas.com/documentation/cdl/en/etsug/60372/HTML/default/viewer.htm#etsug_autoreg_sect005.htm" target="_blank"&gt;http://support.sas.com/documentation/cdl/en/etsug/60372/HTML/default/viewer.htm#etsug_autoreg_sect005.htm&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I am a STATA geek, and this can be done in STATA in one line as follows (after setting my time variable):&lt;/P&gt;&lt;P&gt;xttobit Y X, robust&lt;/P&gt;&lt;P&gt;Can you please let me know how this should be done in SAS?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks&lt;/P&gt;</description>
      <pubDate>Wed, 16 Aug 2017 12:59:36 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/388436#M2597</guid>
      <dc:creator>altijani</dc:creator>
      <dc:date>2017-08-16T12:59:36Z</dc:date>
    </item>
    <item>
      <title>Re: Serial Autocorrelation Tobit</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/388837#M2602</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You can estimate random-effects tobit models in PROC QLIM using the new RANDOM statement. A simple example, based on your model,&amp;nbsp;for the syntax would be&lt;/P&gt;
&lt;P&gt;PROC QLIM;&lt;/P&gt;
&lt;P&gt;MODEL Y = X / censored(lb=0);&lt;/P&gt;
&lt;P&gt;RANDOM INT / SUBJECT=id METHOD=HERMITE(QPOINTS=12);&lt;/P&gt;
&lt;P&gt;RUN;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Currently, PROC QLIM does not offer an option for obtaining robust standard errors for heteroskedasticity and serial correlation.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Please note that xttobit does not have the “robust” option, either.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;If you are willing to specify the nature of the standard errors, then you&amp;nbsp;might estimate your model with PROC NLMIXED by modeling the standard errors explicitly.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Best regards,&lt;/P&gt;
&lt;P&gt;Gunce&lt;/P&gt;</description>
      <pubDate>Thu, 17 Aug 2017 14:59:46 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/388837#M2602</guid>
      <dc:creator>gunce_sas</dc:creator>
      <dc:date>2017-08-17T14:59:46Z</dc:date>
    </item>
    <item>
      <title>Re: Serial Autocorrelation Tobit</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/388908#M2605</link>
      <description>Thanks Gunce for your post.&lt;BR /&gt;&lt;BR /&gt;Are you sure about the code? I tried it and it gave me this error in red:&lt;BR /&gt;ERROR 180-322: Statement is not valid or it is used out of proper order.</description>
      <pubDate>Thu, 17 Aug 2017 17:46:28 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/388908#M2605</guid>
      <dc:creator>altijani</dc:creator>
      <dc:date>2017-08-17T17:46:28Z</dc:date>
    </item>
    <item>
      <title>Re: Serial Autocorrelation Tobit</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/389114#M2607</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You must have an older version of SAS/ETS. PROC QLIM started supporting the&amp;nbsp;RANDOM statement starting from version 14.1.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Gunce&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Fri, 18 Aug 2017 14:03:23 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/389114#M2607</guid>
      <dc:creator>gunce_sas</dc:creator>
      <dc:date>2017-08-18T14:03:23Z</dc:date>
    </item>
    <item>
      <title>Re: Serial Autocorrelation Tobit</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/389126#M2608</link>
      <description>That is right. Any other solution that you might suggest?&lt;BR /&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;BR /&gt;Thanks.&lt;BR /&gt;&lt;BR /&gt;&lt;BR /&gt;</description>
      <pubDate>Fri, 18 Aug 2017 15:04:01 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/389126#M2608</guid>
      <dc:creator>altijani</dc:creator>
      <dc:date>2017-08-18T15:04:01Z</dc:date>
    </item>
    <item>
      <title>Re: Serial Autocorrelation Tobit</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/389222#M2609</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;
&lt;P&gt;As I mentioned before,&amp;nbsp;you can use PROC NLMIXED and specify the nature of the standard errors.&lt;/P&gt;
&lt;P&gt;Best regards,&lt;/P&gt;
&lt;P&gt;Gunce&lt;/P&gt;</description>
      <pubDate>Fri, 18 Aug 2017 20:14:46 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Serial-Autocorrelation-Tobit/m-p/389222#M2609</guid>
      <dc:creator>gunce_sas</dc:creator>
      <dc:date>2017-08-18T20:14:46Z</dc:date>
    </item>
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