OR We want to compare regression beta's coming from two different regressions. Well, you have the results of testing whether they are equal. I divide the sample into two subsamples: male and female, and estimate two models on these two subsamples separately. Below, we have a data file with 10 fictional females and 10 fictional males, along with their height in inches and their weight in pounds. As I said in #6, there is the option of applying a one-tailed test of sranklow = srankhigh. Dear Statalist, I am trying to get stata to test the equality of coefficient estimates following two xtabond arellano-bond regressions. Calculate and compare coefficient estimates from a regression interaction for each group. If you concluded that they are not equal, then it is obvious from inspection that sranklow is the bigger of the two. which tests the null hypothesis: Ho: B 1 = B 2 = B 3. Using the Base Model, again test the claim that the return to each additional year of schooling is nine percent, but this time do not use Stata's test … The regress command will be followed by the command: test age1ht age2ht. Test the claim that the gender differential is ten percent. whether I can just estimate the model using the combined sample of males and females. Here is how I code it. I am trying to use Suest to compare the coefficients of a regressor in two regressions ran on two different datasets. But then I want to test whether all the coefficients in the two models based on the two subsamples are the same, i.e. With two regular regressions I would use something like the following code in Stata to test a cross-equation restriction: sureg (y1 x ) (y2 x ) lincom [y1]x - [y2]x However Stata is explaining that this is not possible when I try to use xtreg. Normally I would run suest and lincom following two regressions but this doesn't work after xtabond because xtabond is is gmm estimation. We can now use age1 age2 height, age1ht and age2ht as predictors in the regression equation in the regress command below. Is there any method/creteria to standardize regression coefficients coming from different regressions. In Stata. test female=-0.10. 1. linearHypothesis() to test coefficients of terms enclosed in I(X) 0. For example, you might believe that the regression coefficient of height predicting weight would be higher for men than for women. Stata reports it has omitted all independent variables (11 in total, but 'ESG' is the variable of interest) due to collinearity (I assume that's supposed to happen) The coefficient for "which_outcome#c.ESG2" is statistically significant, but does not match the actual difference between both coefficients when I run the regressions separately. GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together. For number-1, you could analyze the whole dataset with both gender and add gender in the model. This test will have 2 df because it compares three regression coefficients. use sample_1, clear //Read dataset for the first regression regress nis switch_lead reppdr reppret reppdrret est store model1 Sometimes your research may predict that the size of a regression coefficient should be bigger for one group than for another. test age=age2=0. Dear all, I want to estimate a model with IV 2SLS method. See help qreg Editted: qreg is not probably suitable for nested data. The coefficeint for gender produced by the model is the test for equality of the coefficients between male and female. For number-2, have you considered Stata's quantile regression? xtreg y1 x i.z xtreg y2 x i.z I want to check whether the βs are significantly different. 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