Thank you for your advice, ill try to be more explicit now, i wasnt in the first mail because i thought it is a simple question to answer, so; i have a panel data which contains 48858 observations during 3 year therefore, there are 146574 observations in total, i have 22 different industries defined by 2-digit codes such as 11, 13,14,16...40 therefore, ind_2d contains 22 2-digit codes for example; i want to do a by-industry analysis and this requires to estimate the same model for all 22 industry! as i said total number of observations are 48858(each year), but the 11th industry has 9466 industries. i mean the code 11 corresponds to 9466 indsustries so i want to run the regression just for these firms ind_2d = is industry 2-digit codes in the dataset when i want to see the overall effect of the independent variables, i dont define any industry dummy but to see the effect of the independent variables on the 11th industry i defined a dummy variable such as: ind=(ind_2d==11)# this supposed to mean, ind is equal to 11th industry in other words just take into account the firms which has the code 11, am i mistaken here? and then run the regression, abc<-lm(lnQ~lnC+lnM+lnL+lnE+eco+inno+ind, data=ds)>> summary(abc) > > Call: > lm(formula = lnQ ~ lnC + lnM + lnL + lnE + eco + inno + ind, > data = ds) > > Residuals: > Min 1Q Median 3Q Max > -11.03392 -0.17647 -0.02301 0.14901 7.74957 > > Coefficients: > Estimate Std. Error t value Pr(>|t|) > (Intercept) 0.8980397 0.0050451 178.001 < 2e-16 *** > lnC 0.0672255 0.0006523 103.065 < 2e-16 *** > lnM 0.7990819 0.0006579 1214.596 < 2e-16 *** > lnL 0.0171633 0.0004004 42.870 < 2e-16 *** > lnE 0.0670030 0.0006716 99.770 < 2e-16 *** > ecoTRUE 0.0162249 0.0045672 3.552 0.000382 *** > innoTRUE 0.0966967 0.0030160 32.062 < 2e-16 *** > indTRUE -0.1251466 0.0031509 -39.717 < 2e-16 *** > --- > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > Residual standard error: 0.2924 on 146159 degrees of freedom > (407 observations deleted due to missingness) > Multiple R-squared: 0.9709, Adjusted R-squared: 0.9709 > F-statistic: 6.957e+05 on 7 and 146159 DF, p-value: < 2.2e-16but when i got the result, i see that the regression has been made for all the observations and not just for the industry which i defined with the dummy variable. so i want to know how to regress the same independent variables just for one industry but not on all the industries? Thank you again _________________________________________________________________ Yeni Windows 7: Size en uygun bilgisayarı bulun. Daha fazla bilgi edinin. http://windows.microsoft.com/shop [[alternative HTML version deleted]]
Thank you for your advice, ill try to be more explicit now, i wasnt in the first mail because i thought it is a simple question to answer, so; i have a panel data which contains 48858 observations during 3 year therefore, there are 146574 observations in total, i have 22 different industries defined by 2-digit codes such as 11, 13,14,16...40 therefore, ind_2d contains 22 2-digit codes for example; i want to do a by-industry analysis and this requires to estimate the same model for all 22 industry! as i said total number of observations are 48858(each year), but the 11th industry has 9466 industries. i mean the code 11 corresponds to 9466 indsustries so i want to run the regression just for these firms ind_2d = is industry 2-digit codes in the dataset when i want to see the overall effect of the independent variables, i dont define any industry dummy but to see the effect of the independent variables on the 11th industry i defined a dummy variable such as: ind=(ind_2d==11)# this supposed to mean, ind is equal to 11th industry in other words just take into account the firms which has the code 11, am i mistaken here? and then run the regression, abc<-lm(lnQ~lnC+lnM+lnL+lnE+eco+inno+ind, data=ds)>> summary(abc) > > Call: > lm(formula = lnQ ~ lnC + lnM + lnL + lnE + eco + inno + ind, > data = ds) > > Residuals: > Min 1Q Median 3Q Max > -11.03392 -0.17647 -0.02301 0.14901 7.74957 > > Coefficients: > Estimate Std. Error t value Pr(>|t|) > (Intercept) 0.8980397 0.0050451 178.001 < 2e-16 *** > lnC 0.0672255 0.0006523 103.065 < 2e-16 *** > lnM 0.7990819 0.0006579 1214.596 < 2e-16 *** > lnL 0.0171633 0.0004004 42.870 < 2e-16 *** > lnE 0.0670030 0.0006716 99.770 < 2e-16 *** > ecoTRUE 0.0162249 0.0045672 3.552 0.000382 *** > innoTRUE 0.0966967 0.0030160 32.062 < 2e-16 *** > indTRUE -0.1251466 0.0031509 -39.717 < 2e-16 *** > --- > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > Residual standard error: 0.2924 on 146159 degrees of freedom > (407 observations deleted due to missingness) > Multiple R-squared: 0.9709, Adjusted R-squared: 0.9709 > F-statistic: 6.957e+05 on 7 and 146159 DF, p-value: < 2.2e-16but when i got the result, i see that the regression has been made for all the observations and not just for the industry which i defined with the dummy variable. so i want to know how to regress the same independent variables just for one industry but not on all the industries? Thank you again _________________________________________________________________ Yeni Windows 7: Gündelik işlerinizi basitleştirin. Size en uygun bilgisayarı bulun. http://windows.microsoft.com/shop [[alternative HTML version deleted]]