chow[1] ------------------------------------------------------------------------------------------------------------------------log: C:\datos\docencia\econIccee\practicas2009\chow.log log type: text opened on: 17 Sep 2009, 17:58:52 . . use "$ruta\chow.dta", clear . . * crear variable logaritmo de 1+ingreso del hogar . g ling=ln(1+ing_tot) . . * crear variable logaritmo de 1+gasto en vivienda del hogar . g lviv=ln(1+gvivienda) . . * crear variable dummy "Montevideo" . . g Montevideo=(dpto==1) . . * crear una variable interacción Montevido-Ingreso . g lingMvdeo=ling*Montevideo . . . *Elasticidad ingreso del gasto en electricidad (Modelo Restringido) . reg lviv ling Source | SS df MS -------------+-----------------------------Model | 8233.4231 1 8233.4231 Residual | 7024.38039 20770 .338198382 -------------+-----------------------------Total | 15257.8035 20771 .734572408

Number of obs F( 1, 20770) Prob > F R-squared Adj R-squared Root MSE

= 20772 =24344.95 = 0.0000 = 0.5396 = 0.5396 = .58155

-----------------------------------------------------------------------------lviv | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------ling | .7635228 .0048935 156.03 0.000 .7539312 .7731144 _cons | .407958 .0473869 8.61 0.000 .315076 .5008399 -----------------------------------------------------------------------------. scalar SCR_restrin=e(rss) . scalar k=e(df_m)+1 . scalar Nobs=e(N) . . *Elasticidad ingreso del gasto en electricidad Montevideo . reg lviv ling if Montevideo==1 Source | SS df MS -------------+-----------------------------Model | 2976.04855 1 2976.04855 Residual | 2086.47157 7176 .290756908 -------------+-----------------------------Total | 5062.52012 7177 .705381095

Number of obs F( 1, 7176) Prob > F R-squared Adj R-squared Root MSE

= 7178 =10235.52 = 0.0000 = 0.5879 = 0.5878 = .53922

-----------------------------------------------------------------------------lviv | Coef. Std. Err. t P>|t| [95% Conf. Interval] Página 1

chow[1] -------------+---------------------------------------------------------------ling | .7299952 .0072155 101.17 0.000 .7158507 .7441396 _cons | 1.064812 .0726767 14.65 0.000 .9223438 1.207279 -----------------------------------------------------------------------------. scalar SCR_nrestrin_1=e(rss) . . . *Elasticidad ingreso del gasto en electricidad Montevideo . reg lviv ling if Montevideo==0 Source | SS df MS -------------+-----------------------------Model | 2444.99857 1 2444.99857 Residual | 3608.49385 13592 .265486599 -------------+-----------------------------Total | 6053.49242 13593 .445338955

Number of obs F( 1, 13592) Prob > F R-squared Adj R-squared Root MSE

= 13594 = 9209.50 = 0.0000 = 0.4039 = 0.4039 = .51525

-----------------------------------------------------------------------------lviv | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------ling | .5947658 .0061977 95.97 0.000 .5826176 .6069141 _cons | 1.832686 .0587044 31.22 0.000 1.717617 1.947755 -----------------------------------------------------------------------------. scalar SCR_nrestrin_2=e(rss) . . . * CONTRASTE DE CHOW . scalar CHOW1=(SCR_restrin-(SCR_nrestrin_1+SCR_nrestrin_2))/k/((SCR_nrestrin_1+SCR_nrestri n_2)/(Nobs-2*k)) . scalar p_valor=1-F(k,Nobs-2*k,CHOW1) . display p_valor 0 . . *Elasticidad ingreso del gasto para Montevideo e Interior: . *CONTRASTE ESTRUCTURAL DE CHOW UTILIZANDO VARIABLES DUMMY . reg lviv Montevideo ling lingMvdeo Source | SS df MS -------------+-----------------------------Model | 9562.83806 3 3187.61269 Residual | 5694.96542 20768 .274218289 -------------+-----------------------------Total | 15257.8035 20771 .734572408

Number of obs F( 3, 20768) Prob > F R-squared Adj R-squared Root MSE

= 20772 =11624.36 = 0.0000 = 0.6268 = 0.6267 = .52366

-----------------------------------------------------------------------------lviv | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------Montevideo | -.7678746 .0924176 -8.31 0.000 -.9490204 -.5867289 ling | .5947658 .0062988 94.43 0.000 .5824198 .6071119 lingMvdeo | .1352293 .0094221 14.35 0.000 .1167613 .1536974 _cons | 1.832686 .059662 30.72 0.000 1.715744 1.949628 -----------------------------------------------------------------------------. test Montevideo lingMvdeo ( 1)

Montevideo = 0 Página 2

chow[1] ( 2)

lingMvdeo = 0 F(

2, 20768) = 2424.01 Prob > F = 0.0000

. . *Calcular el estadìstico F del contraste por otra via: Usando (Rbeta_es-r)'{[RVar(beta_es)R']^-1}(Rbeta_es-r)/k . *Siendo Var(beta_es) la que se observa a continuación . matrix Varcovar=e(V) . matrix list Varcovar symmetric Varcovar[4,4] Montevideo ling Montevideo .00854101 ling .00037473 .00003967 lingMvdeo -.0008674 -.00003967 _cons -.00355955 -.00037473

lingMvdeo

_cons

.00008878 .00037473

.00355955

. . . . *ESTIMANDO OTRAS ESPECIFICACIONES . *Elasticidad ingreso del gasto en electricidad estimando un intercepto diferente para Montevideo e Interior . reg lviv Montevideo ling Source | SS df MS -------------+-----------------------------Model | 9506.35185 2 4753.17593 Residual | 5751.45163 20769 .276924822 -------------+-----------------------------Total | 15257.8035 20771 .734572408

Number of obs F( 2, 20769) Prob > F R-squared Adj R-squared Root MSE

= 20772 =17164.14 = 0.0000 = 0.6230 = 0.6230 = .52624

-----------------------------------------------------------------------------lviv | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------Montevideo | .5534025 .0081624 67.80 0.000 .5374034 .5694015 ling | .6552003 .0047075 139.18 0.000 .6459733 .6644274 _cons | 1.261873 .0446913 28.24 0.000 1.174275 1.349472 -----------------------------------------------------------------------------. . *Elasticidad ingreso del gasto en electricidad estimando una elasticidad diferente para Montevideo e Interior . reg lviv ling lingMvdeo Source | SS df MS -------------+-----------------------------Model | 9543.90732 2 4771.95366 Residual | 5713.89616 20769 .275116576 -------------+-----------------------------Total | 15257.8035 20771 .734572408

Number of obs F( 2, 20769) Prob > F R-squared Adj R-squared Root MSE

= 20772 =17345.21 = 0.0000 = 0.6255 = 0.6255 = .52452

-----------------------------------------------------------------------------lviv | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------ling | .6284557 .004828 130.17 0.000 .6189925 .6379189 lingMvdeo | .0572464 .0008295 69.02 0.000 .0556206 .0588722 _cons | 1.512667 .0456385 33.14 0.000 1.423212 1.602122 -----------------------------------------------------------------------------. Página 3

chow[1] . . *TEST DE RAMSEY en modelo no restringido . reg lviv Montevideo ling lingMvdeo Source | SS df MS -------------+-----------------------------Model | 9562.83806 3 3187.61269 Residual | 5694.96542 20768 .274218289 -------------+-----------------------------Total | 15257.8035 20771 .734572408

Number of obs F( 3, 20768) Prob > F R-squared Adj R-squared Root MSE

= 20772 =11624.36 = 0.0000 = 0.6268 = 0.6267 = .52366

-----------------------------------------------------------------------------lviv | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------Montevideo | -.7678746 .0924176 -8.31 0.000 -.9490204 -.5867289 ling | .5947658 .0062988 94.43 0.000 .5824198 .6071119 lingMvdeo | .1352293 .0094221 14.35 0.000 .1167613 .1536974 _cons | 1.832686 .059662 30.72 0.000 1.715744 1.949628 -----------------------------------------------------------------------------. . estat ovtest Ramsey RESET test using powers of the fitted values of lviv Ho: model has no omitted variables F(3, 20765) = 383.16 Prob > F = 0.0000 . predict plviv, xb . . g plviv2=plviv^2 . g plviv3=plviv^3 . g plviv4=plviv^4 . . reg lviv Montevideo ling lingMvdeo plviv2-plviv4 Source | SS df MS -------------+-----------------------------Model | 9861.5552 6 1643.59253 Residual | 5396.24828 20765 .259872298 -------------+-----------------------------Total | 15257.8035 20771 .734572408

Number of obs F( 6, 20765) Prob > F R-squared Adj R-squared Root MSE

= 20772 = 6324.62 = 0.0000 = 0.6463 = 0.6462 = .50978

-----------------------------------------------------------------------------lviv | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------Montevideo | -1.074234 .4191677 -2.56 0.010 -1.895836 -.2526328 ling | 2.172739 .3647315 5.96 0.000 1.457837 2.887641 lingMvdeo | .2993238 .0761617 3.93 0.000 .1500409 .4486067 plviv2 | -1.313952 .1646277 -7.98 0.000 -1.636635 -.991269 plviv3 | .1669429 .0177557 9.40 0.000 .1321403 .2017455 plviv4 | -.0065494 .0006709 -9.76 0.000 -.0078644 -.0052344 _cons | 10.96083 .5138965 21.33 0.000 9.953553 11.96811 -----------------------------------------------------------------------------. test plviv2 plviv3 plviv4 ( 1) ( 2) ( 3)

plviv2 = 0 plviv3 = 0 plviv4 = 0 Página 4

chow[1] F(

3, 20765) = Prob > F =

383.16 0.0000

. . *Calcular el estadìstico F del contraste por otra via: Usando (Rbeta_es-r)'{[RVar(beta_es)R']^-1}(Rbeta_es-r)/3 . *Notar que la matriz de Varcovar es la calculada màs arriba que se reproduce a continuación . matrix list Varcovar symmetric Varcovar[4,4] Montevideo ling Montevideo .00854101 ling .00037473 .00003967 lingMvdeo -.0008674 -.00003967 _cons -.00355955 -.00037473

lingMvdeo

_cons

.00008878 .00037473

.00355955

. . . log close log: C:\datos\docencia\econIccee\practicas2009\chow.log log type: text closed on: 17 Sep 2009, 17:58:53 -------------------------------------------------------------------------------------------------------------------------

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