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</o:shapelayout></xml><![endif]--></head><body lang=ES link=blue vlink=purple><div class=WordSection1><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Hello everybody:<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>I am trying to estimate a spatial error model, but I am facing to several problems<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoListParagraph style='text-indent:-18.0pt;mso-list:l0 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><span style='mso-list:Ignore'>1)<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Running errorsarlm function the following message appears:<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Warning messages:<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>1: In errorsarlm(y ~ z1 + z2 + z3 + z4 + z5 + z6 + z7 + z8 + :<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'> inversion of asymptotic covariance matrix failed for tol.solve = 1e-10 <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'> número de condición recíproco = 3.80991e-16 - using numerical Hessian.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>2: In sqrt(fdHess[1, 1]) : Se han producido NaNs<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Getting the following results:<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Approximate (numerical Hessian) standard error: NaN<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'> z-value: NaN, p-value: NA<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Wald statistic: NaN, p-value: NA<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>This can be easily “solved” changing tol.solve from 1.0e-10 to, for example, 1.0e-20. Doing this I get the following results<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Asymptotic standard error: 14.053<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'> z-value: -44.177, p-value: < 2.22e-16<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Wald statistic: 1951.6, p-value: < 2.22e-16<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoListParagraph style='text-indent:-18.0pt;mso-list:l0 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><span style='mso-list:Ignore'>2)<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>However, I have a more serious problema: the estimate of lambda does not make any sense<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Lambda: -620.82, LR test value: 333.5, p-value: < 2.22e-16<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Any idea about what it is happening? I am using a big dataset with 2800 observations (houses), 14 variables, and the spatial weight matrix has been constructed “by hand” with the inverse of the inter-areas distances . Moreover, several observations belong to the same area (in total we have only 10 areas). As the intra-area distance is unknown but cannot be considered zero, I calculate it as 1/(0.1*dist_min), being dist_min the distance between the corresponding area and the nearest one (idea borrowed from Pattanayak and Butry (2005) “<i>Spatial complementarity of forest and farms: accounting for ecosystem services</i>”, American Journal of Agricultural Economics). Could be due to my particular spatial weight matrix? Any alternative? </span><o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Cheers<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:16.0pt;font-family:"Trebuchet MS","sans-serif";color:black'>Javi<o:p></o:p></span></p><p class=MsoNormal><o:p> </o:p></p><table class=MsoNormalTable border=0 cellspacing=3 cellpadding=0 width="86%" style='width:86.58%;background:white'><tr><td style='padding:3.75pt 3.75pt 3.75pt 3.75pt'></td></tr><tr><td width="99%" style='width:99.04%;background:black;padding:3.75pt 3.75pt 3.75pt 3.75pt'><table class=MsoNormalTable border=0 cellspacing=3 cellpadding=0 width="100%" style='width:100.0%'><tr><td width="55%" style='width:55.0%;padding:.75pt .75pt .75pt .75pt'><p class=MsoNormal><b><span style='font-size:8.5pt;font-family:"Verdana","sans-serif";color:white;mso-fareast-language:ES'>JAVIER GARCÍA </span></b><b><span style='font-size:8.5pt;font-family:"Verdana","sans-serif";color:white;mso-fareast-language:ES'><o:p></o:p></span></b></p><p class=MsoNormal><b><span style='font-size:8.5pt;font-family:"Verdana","sans-serif";color:white;mso-fareast-language:ES'><o:p> </o:p></span></b></p><p class=MsoNormal><b><span style='font-size:8.5pt;font-family:"Verdana","sans-serif";color:white;mso-fareast-language:ES'>Departamento de Economía Aplicada III (Econometría y Estadística)<o:p></o:p></span></b></p><p class=MsoNormal><b><span style='font-size:8.5pt;font-family:"Verdana","sans-serif";color:white;mso-fareast-language:ES'>Facultad de Economía y Empresa (Sección Sarriko)</span></b><span style='color:#1F497D;mso-fareast-language:ES'><br></span><span style='font-size:7.0pt;font-family:"Verdana","sans-serif";color:white;mso-fareast-language:ES'>Avda. Lehendakari Aguirre 83</span><span style='font-size:7.0pt;color:#1F497D;mso-fareast-language:ES'><o:p></o:p></span></p><p class=MsoNormal><span style='font-size:7.0pt;font-family:"Verdana","sans-serif";color:white;mso-fareast-language:ES'>48015 BILBAO<br><b>T.: +34 601 7126</b> <b>F.: +34 601 3754</b><br></span><span style='color:#1F497D;mso-fareast-language:ES'><a href="http://www.ehu.es/"><b><span style='font-size:7.0pt;font-family:"Verdana","sans-serif";color:white'>www.ehu.es</span></b></a> </span><span style='font-size:12.0pt;color:#1F497D;mso-fareast-language:ES'><o:p></o:p></span></p></td><td width="45%" valign=top style='width:45.0%;padding:.75pt .75pt .75pt .75pt'><p class=MsoNormal align=right style='text-align:right'><span style='color:#1F497D;mso-fareast-language:ES'><img border=0 width=482 height=74 id="Imagen_x0020_1" src="cid:image001.gif@01D30BFB.1B7B5240" alt="http://www.unibertsitate-hedakuntza.ehu.es/p268-content/es/contenidos/informacion/manual_id_corp/es_manual/images/firma_email_upv_euskampus_bilingue.gif"></span><span style='font-size:12.0pt;color:#1F497D;mso-fareast-language:ES'><o:p></o:p></span></p></td></tr></table></td></tr></table><p class=MsoNormal><span style='mso-fareast-language:ES'><o:p> </o:p></span></p><p class=MsoNormal><o:p> </o:p></p></div></body></html>