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I need help interpreting a stata output
I am trying to find how the implementation of the equal pay act affects the gender pay gap.
Variable:
GRSSWK - weekly pay
SEX - gender 1 being male 2 being female
ACT - 1 for observation after the act 0 for before
SEXACT- SEX*ACT

I used a regression framework to try and calculate the differences-in-differneces
I used the command
reg GRSSWK SEX ACT SEXACT

reg GRSSWK SEX ACT SEXACT Number of obs1,078 19.50 0.0000 0.0516 Adj R-squared 0.0490 344.45 Source df MS F(3, 1074) Model 6939659.45 3 2313219.82Prob SF 1,074 118643.665 R-squared Total1343629561,077 124756.691Root MSE GRSSWK p>It! [95% Conf. Interval] SEX-165.9008 24.03571-6.90 0.000-213.063+118.7385 ACT -50.50852 81.37736-0.62 0.535-210.1852109.1681 0.46 0.648-75.45547121.2739 657.208 39.2058416.760.000580.2793734.1368 SEXACT 22.90921 50.13043 cons I need help interpreting this
math   Statistics-And-Probability   
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Answer #1


Answer Date: 10/01/2019 The estimated regression equation line Stata output is = 657 .21-165 .90 x1-50 .51 x, + 22.90 x, x x 12 From the Stata output, the slop of sex is significant due to significance p-value in terms of t-statistics is less than 0.05 which is 0.000. From the Stata output, the slop of ACT is not significant due to significance p-value in terms oft-statistics is higher than 0.05 which is 0.535. From the Stata output, the slop of Sex multiply ACT is not significant due to significance p-value in terms of t-statistics is higher than 0.05 which is 0.648. To test the hypothesis is that the overall regression model is significant at 5% level of significance. The null and alternative hypothesis is,Ha: at least one p, is unequal. The F-test statistics is, From the Stata output, the F-test statistics is 19.501 Thep-value for this test is From the Stata output, the p-value for this test is 0.000 Decision The conclusion is that p-value in this context is less than 0.05 which is 0.000, so the null hypothesis is rejected at 5% level of significance. There is sufficient evidence to indicate that the overall regression model is significant. The result is statistically significant. Interpretation of coefficient of determination R. 0.052. 5.2% of sample variation in weekly pay 0) can be explained by the model containing Sex, ACT and Sex multiply ACT.Interpretation of intercept o 657.21. This is y-intercept and there is no other meaning. Interpretation of slop p165.90. For each unit increase in Sex, the mean weekly pay is estimated to decreases 165.90, holding other independent variable are ACT and Sex multiply ACT. =-50.51. For each unit increase in ACT, the mean weekly pay is estimated to decreases 50.51, holding other independent variable are Sex and Sex multiply ACI constant =22.91 . For each unit increase in Sex multiply ACT, the mean weekly pay is estimated to increases 22.91, holding other independent variable are Sex and ACT constant.

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