{"id":111,"date":"2018-08-03T20:51:13","date_gmt":"2018-08-04T01:51:13","guid":{"rendered":"https:\/\/dcsh.izt.uam.mx\/proyectos\/r\/?page_id=111"},"modified":"2018-11-15T21:15:23","modified_gmt":"2018-11-16T03:15:23","slug":"capitulo-4-wooldridge","status":"publish","type":"page","link":"https:\/\/dcsh.izt.uam.mx\/proyectos\/r\/?page_id=111","title":{"rendered":"Cap\u00edtulo 6 Wooldridge"},"content":{"rendered":"
\n

<\/h2>\n

Cap\u00edtulo 6: Regresi\u00f3n m\u00faltiple: otros problemas<\/h2>\n

Example 6.1:<\/code>\u00a0Efectos de la contaminaci\u00f3n en los precios de la vivienda, estandarizados.<\/strong><\/p>\n

p\u00a0<\/span>r\u00a0<\/span>i\u00a0<\/span>c\u00a0<\/span>e\u00a0<\/span>=\u00a0<\/span>\u03b2<\/span>0<\/span><\/span>+\u00a0<\/span>\u03b2<\/span>1<\/span><\/span>n\u00a0<\/span>o\u00a0<\/span>x\u00a0<\/span>+\u00a0<\/span>\u03b2<\/span>2<\/span><\/span>c\u00a0<\/span>r\u00a0<\/span>i\u00a0<\/span>m\u00a0<\/span>e\u00a0<\/span>+\u00a0<\/span>\u03b2<\/span>3<\/span><\/span>r\u00a0<\/span>o\u00a0<\/span>o\u00a0<\/span>m\u00a0<\/span>s\u00a0<\/span>+\u00a0<\/span>\u03b2<\/span>4<\/span><\/span>re<\/span>yo\u00a0<\/span>s\u00a0<\/span>t\u00a0<\/span>+\u00a0<\/span>\u03b2<\/span>5<\/span><\/span>s\u00a0<\/span>t\u00a0<\/span>r\u00a0<\/span>a\u00a0<\/span>t\u00a0<\/span>i\u00a0<\/span>o\u00a0<\/span>+\u00a0<\/span>\u03bc<\/span><\/span><\/span>pagryodomi=\u03b20+\u03b21norteoX+\u03b22doryometromi+\u03b23roometros+\u03b24reyost+\u03b25struntyoo+\u03bc<\/span><\/span><\/div>\n

p\u00a0<\/span>r\u00a0<\/span>i\u00a0<\/span>c\u00a0<\/span>e<\/span><\/span><\/span>pagryodomi<\/span><\/span><\/span>: precio medio de la vivienda.<\/p>\n

n\u00a0<\/span>o\u00a0<\/span>x<\/span><\/span><\/span>norteoX<\/span><\/span><\/span>: Concentraci\u00f3n de \u00f3xido nitroso;\u00a0partes por mill\u00f3n.<\/p>\n

c\u00a0<\/span>r\u00a0<\/span>i\u00a0<\/span>m\u00a0<\/span>e<\/span><\/span><\/span>doryometromi<\/span><\/span><\/span>: n\u00famero de cr\u00edmenes reportados per capita.<\/p>\n

r\u00a0<\/span>o\u00a0<\/span>o\u00a0<\/span>m\u00a0<\/span>s<\/span><\/span><\/span>roometros<\/span><\/span><\/span>: n\u00famero promedio de habitaciones en casas en la comunidad.<\/p>\n

re<\/span>i\u00a0<\/span>s\u00a0<\/span>t<\/span><\/span><\/span>reyost<\/span><\/span><\/span>: distancia ponderada de la comunidad a 5 centros de empleo.<\/p>\n

s\u00a0<\/span>t\u00a0<\/span>r\u00a0<\/span>a\u00a0<\/span>t\u00a0<\/span>i\u00a0<\/span>o<\/span><\/span><\/span>struntyoo<\/span><\/span><\/span>: proporci\u00f3n promedio de alumnos por maestro en las escuelas de la comunidad.<\/p>\n

z<\/span>p\u00a0<\/span>r\u00a0<\/span>i\u00a0<\/span>c\u00a0<\/span>e<\/span><\/span>1.<\/span><\/span><\/span><\/span>=\u00a0<\/span>\u03b2<\/span>1<\/span><\/span>z<\/span>n\u00a0<\/span>o\u00a0<\/span>x\u00a0<\/span>+\u00a0<\/span>\u03b2<\/span>2<\/span><\/span>z<\/span>c\u00a0<\/span>r\u00a0<\/span>i\u00a0<\/span>m\u00a0<\/span>e\u00a0<\/span>+\u00a0<\/span>\u03b2<\/span>3<\/span><\/span>z<\/span>r\u00a0<\/span>o\u00a0<\/span>o\u00a0<\/span>m\u00a0<\/span>s\u00a0<\/span>+\u00a0<\/span>\u03b2<\/span>4<\/span><\/span>z<\/span>re<\/span>yo\u00a0<\/span>s\u00a0<\/span>t\u00a0<\/span>+\u00a0<\/span>\u03b2<\/span>5<\/span><\/span>z<\/span>s\u00a0<\/span>t\u00a0<\/span>r\u00a0<\/span>a\u00a0<\/span>t\u00a0<\/span>i\u00a0<\/span>o<\/span><\/span><\/span>zpagryodomi^=\u03b21znorteoX+\u03b22zdoryometromi+\u03b23zroometros+\u03b24zreyost+\u03b25zstruntyoo<\/span><\/span><\/div>\n

Cargue los\u00a0hprice2<\/code>datos y vea la documentaci\u00f3n.<\/p>\n

\n
data<\/span>(\"hprice2\"<\/span>)\r\n?hprice2<\/code><\/pre>\n<\/div>\n
Datos de\u00a0Hedonic Housing Prices y Demand for Clean Air<\/em>\u00a0, por Harrison, D. y DLRubinfeld, Journal of Environmental Economics and Management 5, 81-102.\u00a0Diego Garc\u00eda, un ex Ph.D.\u00a0estudiante de econom\u00eda en el MIT, amablemente proporcion\u00f3 estos datos, que obtuvo del libro Regression Diagnostics: Identifying Influential Data and Sources of Collinearity, por DA Belsey, E. Kuh, y R. Welsch, 1990. Nueva York: Wiley.<\/p>\n
Estime el coeficiente con el\u00a0lm<\/code>modelo de regresi\u00f3n\u00a0habitual\u00a0, pero esta vez, coeficientes estandarizados envolviendo cada variable con la\u00a0scale<\/code>funci\u00f3n\u00a0de R\u00a0:<\/p>\n
\n
housing_standard <- lm<\/span>(scale<\/span>(price) ~<\/span> 0<\/span> +<\/span> scale<\/span>(nox) +<\/span> scale<\/span>(crime) +<\/span> scale<\/span>(rooms) +<\/span> \r\n    scale<\/span>(dist) +<\/span> scale<\/span>(stratio), data =<\/span> hprice2)<\/code><\/pre>\n<\/div>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/td>\n<\/tr>\n
<\/td>\nVariable dependiente:<\/em><\/td>\n<\/tr>\n
<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nescala (precio)<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
escala (nox)<\/td>\n-0.340\u00a0***<\/sup>\u00a0(0.044)<\/td>\n<\/tr>\n
escala (crimen)<\/td>\n-0.143\u00a0***<\/sup>\u00a0(\u00a00.031\u00a0)<\/td>\n<\/tr>\n
escala (habitaciones)<\/td>\n0.514\u00a0***<\/sup>\u00a0(0.030)<\/td>\n<\/tr>\n
escala (dist)<\/td>\n-0.235\u00a0***<\/sup>\u00a0(0.043)<\/td>\n<\/tr>\n
escala (stratio)<\/td>\n-0.270\u00a0***<\/sup>\u00a0(0.030)<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
Observaciones<\/td>\n506<\/td>\n<\/tr>\n
R\u00a02<\/sup><\/td>\n0.636<\/td>\n<\/tr>\n
R\u00a02<\/sup>\u00a0ajustado<\/td>\n0.632<\/td>\n<\/tr>\n
Residual Std.\u00a0Error<\/td>\n0.606 (df = 501)<\/td>\n<\/tr>\n
Estad\u00edstica F<\/td>\n174.822\u00a0***<\/sup>\u00a0(df \u200b\u200b= 5; 501)<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
Nota:<\/em><\/td>\np <0.1;\u00a0p <0.05;\u00a0<\/strong><\/em>p <0.01<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Example 6.2:<\/code>\u00a0Efectos de la contaminaci\u00f3n en los precios de la vivienda, t\u00e9rmino interactivo cuadr\u00e1tico<\/strong><\/p>\n
Modificar el modelo de vivienda, agregando un t\u00e9rmino cuadr\u00e1tico en las\u00a0habitaciones<\/em>\u00a0:<\/p>\n
l\u00a0<\/span>o\u00a0<\/span>g<\/span>(\u00a0<\/span>p\u00a0<\/span>r\u00a0<\/span>i\u00a0<\/span>c\u00a0<\/span>e\u00a0<\/span>)\u00a0<\/span>=\u00a0<\/span>\u03b2<\/span>0<\/span><\/span>+\u00a0<\/span>\u03b2<\/span>1<\/span><\/span>l\u00a0<\/span>o\u00a0<\/span>g<\/span>(\u00a0<\/span>n\u00a0<\/span>o\u00a0<\/span>x\u00a0<\/span>)\u00a0<\/span>+\u00a0<\/span>\u03b2<\/span>2<\/span><\/span>l\u00a0<\/span>o\u00a0<\/span>g<\/span>(\u00a0<\/span>d<\/span>i\u00a0<\/span>s\u00a0<\/span>t\u00a0<\/span>)\u00a0<\/span>+\u00a0<\/span>\u03b2<\/span>3<\/span><\/span>r\u00a0<\/span>o\u00a0<\/span>o\u00a0<\/span>m\u00a0<\/span>s\u00a0<\/span>+\u00a0<\/span>\u03b2<\/span>4<\/span><\/span>r\u00a0<\/span>o\u00a0<\/span>o\u00a0<\/span>m\u00a0<\/span>s<\/span>2<\/span><\/span>+\u00a0<\/span>\u03b2<\/span>5<\/span><\/span>s\u00a0<\/span>t\u00a0<\/span>r\u00a0<\/span>a\u00a0<\/span>t\u00a0<\/span>i\u00a0<\/span>o\u00a0<\/span>+\u00a0<\/span>\u03bc<\/span><\/span><\/span>logramo(pagryodomi)=\u03b20+\u03b21logramo(norteoX)+\u03b22logramo(reyost)+\u03b23roometros+\u03b24roometros2+\u03b25struntyoo+\u03bc<\/span><\/span><\/div>\n
\n
housing_interactive <- lm<\/span>(lprice ~<\/span> lnox +<\/span> log<\/span>(dist) +<\/span> rooms+<\/span>I<\/span>(rooms^<\/span>2<\/span>) +<\/span> stratio, data =<\/span> hprice2)<\/code><\/pre>\n<\/div>\n
Compare los resultados con el modelo de\u00a0example 6.1<\/code>.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/td>\n<\/tr>\n
<\/td>\nVariable dependiente:<\/em><\/td>\n<\/tr>\n
<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nescala (precio)<\/td>\nlprice<\/td>\n<\/tr>\n
<\/td>\n(1)<\/td>\n(2)<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
escala (nox)<\/td>\n-0.340\u00a0***<\/sup>\u00a0(0.044)<\/td>\n<\/td>\n<\/tr>\n
escala (crimen)<\/td>\n-0.143\u00a0***<\/sup>\u00a0(\u00a00.031\u00a0)<\/td>\n<\/td>\n<\/tr>\n
escala (habitaciones)<\/td>\n0.514\u00a0***<\/sup>\u00a0(0.030)<\/td>\n<\/td>\n<\/tr>\n
escala (dist)<\/td>\n-0.235\u00a0***<\/sup>\u00a0(0.043)<\/td>\n<\/td>\n<\/tr>\n
escala (stratio)<\/td>\n-0.270\u00a0***<\/sup>\u00a0(0.030)<\/td>\n<\/td>\n<\/tr>\n
lnox<\/td>\n<\/td>\n-0.902\u00a0***<\/sup>\u00a0(\u00a00.115\u00a0)<\/td>\n<\/tr>\n
log (dist)<\/td>\n<\/td>\n-0.087\u00a0**<\/sup>\u00a0(0.043)<\/td>\n<\/tr>\n
habitaciones<\/td>\n<\/td>\n-0.545\u00a0***<\/sup>\u00a0(0.165)<\/td>\n<\/tr>\n
Yo (habitaciones2)<\/td>\n<\/td>\n0.062\u00a0***<\/sup>\u00a0(0.013)<\/td>\n<\/tr>\n
stratio<\/td>\n<\/td>\n-0.048\u00a0***<\/sup>\u00a0(0.006)<\/td>\n<\/tr>\n
Constante<\/td>\n<\/td>\n13.385\u00a0***<\/sup>\u00a0(0.566)<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
Observaciones<\/td>\n506<\/td>\n506<\/td>\n<\/tr>\n
R\u00a02<\/sup><\/td>\n0.636<\/td>\n0.603<\/td>\n<\/tr>\n
R\u00a02<\/sup>\u00a0ajustado<\/td>\n0.632<\/td>\n0.599<\/td>\n<\/tr>\n
Residual Std.\u00a0Error<\/td>\n0.606 (df = 501)<\/td>\n0,259 (df = 500)<\/td>\n<\/tr>\n
Estad\u00edstica F<\/td>\n174.822\u00a0***<\/sup>\u00a0(df \u200b\u200b= 5; 501)<\/td>\n151.770\u00a0***<\/sup>\u00a0(df \u200b\u200b= 5; 500)<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
Nota:<\/em><\/td>\np <0.1;\u00a0p <0.05;\u00a0<\/strong><\/em>p <0.01<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
<\/div>\n
\n\n\n\n\n\n\n\n
<\/td>\n0.587<\/td>\n<\/tr>\n
Residual Std.\u00a0Error<\/td>\n1.843 (df = 53)<\/td>\n<\/tr>\n
Estad\u00edstica F<\/td>\n40.094\u00a0***<\/sup>\u00a0(df \u200b\u200b= 2; 53)<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
Nota:<\/em><\/td>\np <0.1;\u00a0p <0.05;\u00a0<\/strong><\/em>p <0.01<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Example 10.11:<\/code>\u00a0Efectos estacionales de las presentaciones antidumping<\/strong><\/p>\n
CM Krupp y PS Pollard (1999),\u00a0Las respuestas del mercado a las leyes antidumping: algunas pruebas de la industria qu\u00edmica de los Estados Unidos<\/em>\u00a0, Canadian Journal of Economics 29, 199-227.\u00a0El Dr. Krupp amablemente proporcion\u00f3 los datos.\u00a0Son datos mensuales que abarcan desde febrero de 1978 hasta diciembre de 1988.<\/p>\n
\n
data<\/span>(\"barium\"<\/span>)\r\n?barium<\/code><\/pre>\n<\/div>\n
\n
barium_imports <- lm<\/span>(lchnimp ~<\/span> lchempi +<\/span> lgas +<\/span> lrtwex +<\/span> befile6 +<\/span> affile6 +<\/span> \r\n    afdec6, data =<\/span> barium)<\/code><\/pre>\n<\/div>\n
Estime un nuevo modelo,\u00a0barium_seasonal<\/code>que tenga en cuenta la estacionalidad mediante la adici\u00f3n de variables ficticias contenidas en los datos.\u00a0Calcule el\u00a0anova<\/code>entre los dos modelos.<\/p>\n
\n
barium_seasonal <- lm<\/span>(lchnimp ~<\/span> lchempi +<\/span> lgas +<\/span> lrtwex +<\/span> befile6 +<\/span> affile6 +<\/span> \r\n    afdec6 +<\/span> feb +<\/span> mar +<\/span> apr +<\/span> may +<\/span> jun +<\/span> jul +<\/span> aug +<\/span> sep +<\/span> oct +<\/span> nov +<\/span> dec, \r\n    data =<\/span> barium)\r\nbarium_anova <- anova<\/span>(barium_imports, barium_seasonal)<\/code><\/pre>\n<\/div>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/td>\n<\/tr>\n
<\/td>\nVariable dependiente:<\/em><\/td>\n<\/tr>\n
<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nlchnimp<\/td>\n<\/tr>\n
<\/td>\n(1)<\/td>\n(2)<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
lchempi<\/td>\n3.117\u00a0***<\/sup>\u00a0(0.479)<\/td>\n3.265\u00a0***<\/sup>\u00a0(0.493)<\/td>\n<\/tr>\n
lgas<\/td>\n0.196 (0.907)<\/td>\n-1.278 (1.389)<\/td>\n<\/tr>\n
lrtwex<\/td>\n0,983\u00a0**<\/sup>\u00a0(0,400)<\/td>\n0,663 (0,471)<\/td>\n<\/tr>\n
befile6<\/td>\n0.060 (0.261)<\/td>\n0.140 (0.267)<\/td>\n<\/tr>\n
affile6<\/td>\n-0.032 (0.264)<\/td>\n0.013 (0.279)<\/td>\n<\/tr>\n
afdec6<\/td>\n-0.565\u00a0*<\/sup>\u00a0(0.286)<\/td>\n-0.521\u00a0*<\/sup>\u00a0(0.302)<\/td>\n<\/tr>\n
feb<\/td>\n<\/td>\n-0.418 (0.304)<\/td>\n<\/tr>\n
mar<\/td>\n<\/td>\n0.059 (0.265)<\/td>\n<\/tr>\n
abr<\/td>\n<\/td>\n-0.451\u00a0*<\/sup>\u00a0(0.268)<\/td>\n<\/tr>\n
mayo<\/td>\n<\/td>\n0.033 (0.269)<\/td>\n<\/tr>\n
jun<\/td>\n<\/td>\n-0.206 (0.269)<\/td>\n<\/tr>\n
jul<\/td>\n<\/td>\n0.004 (0.279)<\/td>\n<\/tr>\n
ago<\/td>\n<\/td>\n-0.157 (0.278)<\/td>\n<\/tr>\n
sep<\/td>\n<\/td>\n-0.134 (0.268)<\/td>\n<\/tr>\n
oct<\/td>\n<\/td>\n0.052 (0.267)<\/td>\n<\/tr>\n
nov<\/td>\n<\/td>\n-0.246 (0.263)<\/td>\n<\/tr>\n
dic<\/td>\n<\/td>\n0.133 (0.271)<\/td>\n<\/tr>\n
Constante<\/td>\n-17.803 (21.045)<\/td>\n16.779 (32.429)<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
Observaciones<\/td>\n131<\/td>\n131<\/td>\n<\/tr>\n
R\u00a02<\/sup><\/td>\n0.305<\/td>\n0.358<\/td>\n<\/tr>\n
R\u00a02<\/sup>\u00a0ajustado<\/td>\n0.271<\/td>\n0.262<\/td>\n<\/tr>\n
Residual Std.\u00a0Error<\/td>\n0.597 (df = 124)<\/td>\n0.601 (df = 113)<\/td>\n<\/tr>\n
Estad\u00edstica F<\/td>\n9.064\u00a0***<\/sup>\u00a0(df \u200b\u200b= 6; 124)<\/td>\n3.712\u00a0***<\/sup>\u00a0(df \u200b\u200b= 17; 113)<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
Nota:<\/em><\/td>\np <0.1;\u00a0p <0.05;\u00a0<\/strong><\/em>p <0.01<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/td>\n<\/tr>\n
Estad\u00edstica<\/td>\nnorte<\/td>\nMedia<\/td>\nSt. Dev.<\/td>\nMin.<\/td>\nMax<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
Res.Df<\/td>\n2<\/td>\n118.500<\/td>\n7.778<\/td>\n113<\/td>\n124<\/td>\n<\/tr>\n
RSS<\/td>\n2<\/td>\n42.545<\/td>\n2.406<\/td>\n40.844<\/td>\n44.247<\/td>\n<\/tr>\n
Df<\/td>\n1<\/td>\n11,000<\/td>\n<\/td>\n11<\/td>\n11<\/td>\n<\/tr>\n
Suma de Sq<\/td>\n1<\/td>\n3.403<\/td>\n<\/td>\n3.403<\/td>\n3.403<\/td>\n<\/tr>\n
F<\/td>\n1<\/td>\n0.856<\/td>\n<\/td>\n0.856<\/td>\n0.856<\/td>\n<\/tr>\n
Pr (> F)<\/td>\n1<\/td>\n0.585<\/td>\n<\/td>\n0.585<\/td>\n0.585<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
<\/div>\n
<\/div>\n
<\/div>\n
\n
\n
Econometr\u00eda Aplicada con R<\/h3>\n
es mi proyecto registrado en el Consejo Divisional de la DCSH.<\/p>\n
Este proyecto presenta\u00a0 los m\u00e9todos de la\u00a0 econometr\u00eda aplicada que utiliza el sistema R para computaci\u00f3n y gr\u00e1ficos estad\u00edsticos.\u00a0Presenta ejemplos pr\u00e1cticos para una amplia gama de modelos econom\u00e9tricos, desde modelos de regresi\u00f3n lineal cl\u00e1sicos para secciones transversales, series de tiempo o datos de panel y los modelos comunes no lineales de microeconometr\u00eda, como modelos logit, probit y tobit, hasta modelos semiparam\u00e9tricos recientes. extensiones\u00a0Adem\u00e1s, proporciona un cap\u00edtulo sobre programaci\u00f3n, que incluye simulaciones, optimizaci\u00f3n y una introducci\u00f3n a las herramientas R que permite una investigaci\u00f3n econom\u00e9trica reproducible.\u00a0Un paquete R que acompa\u00f1a a este libro, AER, est\u00e1 disponible en la Red Integral de Archivos R (CRAN) en\u00a0https:\/\/CRAN.R-project.org\/package=AER<\/a>\u00a0.<\/p><\/blockquote>\n
 <\/p>\n<\/div>\n
\n
Bibliograf\u00eda<\/h2>\n
Yves Croissant, Giovanni Millo (2008).\u00a0Econometr\u00eda de datos de panel en R: El paquete de plm<\/em>\u00a0.\u00a0Journal of Statistical Software 27 (2).\u00a0URL www.jstatsoft.org\/v27\/i02\/.<\/p>\n
Marek Hlavac (2015).\u00a0stargazer: Regresi\u00f3n con formato correcto y tablas de estad\u00edsticas de resumen<\/em>\u00a0.\u00a0Paquete R versi\u00f3n 5.2.\u00a0https:\/\/CRAN.R-project.org\/package=stargazer<\/a><\/p>\n
Christian Kleiber y Achim Zeileis (2008).\u00a0Econometr\u00eda Aplicada con R<\/em>\u00a0.\u00a0Nueva York: Springer-Verlag.\u00a0ISBN 978-0-387-77316-2.\u00a0URL\u00a0https:\/\/CRAN.R-project.org\/package=AER<\/a><\/p>\n
Franz Mohr (2015).\u00a0prais: Prais-Winsten Procedimiento de estimaci\u00f3n para AR (1) Correlaci\u00f3n en serie<\/em>\u00a0.\u00a0Versi\u00f3n del paquete R 0.1.1.\u00a0https:\/\/CRAN.R-project.org\/package=prais<\/a><\/p>\n
R Core Team (2018).\u00a0R: Un lenguaje y entorno para la inform\u00e1tica estad\u00edstica<\/em>\u00a0.\u00a0R Foundation for Statistical Computing, Viena, Austria.\u00a0URL\u00a0https:\/\/www.R-project.org\/<\/a>\u00a0.<\/p>\n
Hadley Wickham y Winston Chang (2016).\u00a0devtools: herramientas para hacer que los paquetes R en desarrollo sean m\u00e1s f\u00e1ciles<\/em>\u00a0.\u00a0Paquete R versi\u00f3n 1.12.0.\u00a0https:\/\/CRAN.R-project.org\/package=devtools<\/a><\/p>\n
Hadley Wickham.\u00a0prueba de que: comience con las pruebas<\/em>\u00a0.\u00a0Paquete R versi\u00f3n 1.0.2.\u00a0https:\/\/CRAN.R-project.org\/package=testthat<\/a><\/p>\n
 <\/p>\n
EL LIBRO DE WOOLDRIDGE, ES UN CLASICO. YA VAMOS EN LA 4ta. edici\u00f3n en espa\u00f1ol y la 6ta en ingl\u00e9s.<\/p>\n
Jeffrey M. Wooldridge (2016).\u00a0Econometr\u00eda introductoria: un enfoque moderno<\/em>\u00a0.\u00a0Mason, Ohio: South-Western Cengage Learning.<\/p>\n
 <\/p>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"
Cap\u00edtulo 6: Regresi\u00f3n m\u00faltiple: otros problemas Example 6.1:\u00a0Efectos de la contaminaci\u00f3n en los precios de la vivienda, estandarizados. p\u00a0r\u00a0i\u00a0c\u00a0e\u00a0=\u00a0\u03b20+\u00a0\u03b21n\u00a0o\u00a0x\u00a0+\u00a0\u03b22c\u00a0r\u00a0i\u00a0m\u00a0e\u00a0+\u00a0\u03b23r\u00a0o\u00a0o\u00a0m\u00a0s\u00a0+\u00a0\u03b24reyo\u00a0s\u00a0t\u00a0+\u00a0\u03b25s\u00a0t\u00a0r\u00a0a\u00a0t\u00a0i\u00a0o\u00a0+\u00a0\u03bcpagryodomi=\u03b20+\u03b21norteoX+\u03b22doryometromi+\u03b23roometros+\u03b24reyost+\u03b25struntyoo+\u03bc p\u00a0r\u00a0i\u00a0c\u00a0epagryodomi: precio medio de la vivienda. n\u00a0o\u00a0xnorteoX: Concentraci\u00f3n de \u00f3xido nitroso;\u00a0partes por mill\u00f3n. c\u00a0r\u00a0i\u00a0m\u00a0edoryometromi: n\u00famero de cr\u00edmenes reportados per capita. r\u00a0o\u00a0o\u00a0m\u00a0sroometros: n\u00famero promedio de habitaciones en casas en la comunidad. rei\u00a0s\u00a0treyost: distancia ponderada de la comunidad … Seguir leyendo Cap\u00edtulo 6 Wooldridge<\/span> →<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"","meta":{"footnotes":""},"class_list":["post-111","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/dcsh.izt.uam.mx\/proyectos\/r\/index.php?rest_route=\/wp\/v2\/pages\/111","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dcsh.izt.uam.mx\/proyectos\/r\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/dcsh.izt.uam.mx\/proyectos\/r\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/dcsh.izt.uam.mx\/proyectos\/r\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dcsh.izt.uam.mx\/proyectos\/r\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=111"}],"version-history":[{"count":3,"href":"https:\/\/dcsh.izt.uam.mx\/proyectos\/r\/index.php?rest_route=\/wp\/v2\/pages\/111\/revisions"}],"predecessor-version":[{"id":173,"href":"https:\/\/dcsh.izt.uam.mx\/proyectos\/r\/index.php?rest_route=\/wp\/v2\/pages\/111\/revisions\/173"}],"wp:attachment":[{"href":"https:\/\/dcsh.izt.uam.mx\/proyectos\/r\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=111"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}