ECN/PUB 480/580 Assignment #7 Using Stata

User Generated

fgnprlynzoreg1

Economics

ECN PUB 480 580

U of M

Description

Hi I have an assignment that requires the usage of Stata software for data analysis for a masters level economics course. The documents are attached. I am looking for someone to complete the entire assignment.


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Assignment 7 wage educ age 13 exper marr female 12 41 15 1 0 12.8 14 53 4 0 0 24.33 14 36 18 0 1 6 13 18 9 0 0 8.55 12 29 17 1 0 5.4 11 58 7 1 1 5.25 12 47 4 0 0 6.35 8 40 8 1 1 10.2 11 44 1 0 0 6.2 12 27 30 1 0 5.15 12 29 6 1 1 12 12 46 24 1 0 6 14 23 2 0 0 9 16 30 3 1 1 9.45 13 34 3 1 1 14.33 12 28 3 1 0 6.75 12 24 3 1 1 5.6 12 30 13 1 1 6.5 12 46 8 1 1 45 16 51 8 1 0 15.89 8 48 5 1 0 9 10 50 10 1 1 14.85 13 46 4 1 0 27.97 13 45 4 1 0 8 13 22 3 0 0 6 14 22 6 0 1 10 12 37 11 1 1 7 13 68 4 1 0 6.5 11 36 6 0 1 8.5 14 28 4 1 0 6 8 36 3 0 1 5.5 10 24 1 0 1 7.7 12 41 12 1 1 13.42 13 47 14 1 0 6 12 45 14 1 1 5.4 13 20 2 0 1 8.5 13 28 6 1 0 6.75 13 25 6 0 1 5 12 62 6 0 1 9.72 12 28 7 1 1 6.45 14 27 3 1 1 8.5 13 29 8 1 0 7 12 32 4 0 0 4.5 12 49 5 1 0 7 14 45 2 1 1 9.75 12 44 9 1 1 5.15 10 16 8 0 0 10 11 29 8 1 0 7 11 28 6 1 1 5.5 12 36 6 1 1 11.5 10 33 7 1 0 7 14 53 1 0 1 15.27 12 26 42 1 0 11 12 64 4 1 1 9.5 12 28 4 1 0 15 12 42 2 1 1 10 11 71 4 1 0 7 12 32 4 1 0 8 13 38 8 1 1 11 13 43 6 1 1 6 6 52 11 1 1 7.5 12 26 6 1 0 19.13 16 24 8 1 1 5.25 13 25 1 0 0 9 13 25 13 1 1 12 16 45 6 1 1 12 13 25 7 1 1 7 13 35 1 1 1 9 16 23 8 0 1 20 12 49 1 0 1 26 13 40 3 0 0 9 14 26 3 1 1 11.6 13 26 4 1 0 7.6 13 23 2 0 0 12 12 29 11 1 1 10 12 39 9 1 0 6.5 12 27 10 1 1 11.5 13 36 46 1 1 13.5 13 21 6 0 1 8.5 13 50 2 1 1 5.65 13 27 6 0 1 8 12 22 34 0 1 7.5 12 22 4 0 1 21 13 54 19 1 1 21 13 32 2 1 1 7 13 42 2 1 0 8.5 13 20 3 0 1 8 10 21 8 0 0 14 12 49 21 1 1 10 13 18 2 0 1 15.03 12 47 5 1 1 6.5 12 43 7 1 1 15.54 16 47 6 1 0 12.35 16 45 24 1 1 25.44 13 43 15 1 0 8 13 18 2 0 0 8 11 17 24 0 1 8 11 17 2 0 0 20 13 26 2 0 0 15 13 29 12 0 1 9.5 12 26 18 1 1 19 12 45 2 1 0 30.3 12 36 9 1 0 11.52 12 45 2 1 0 11 12 45 2 1 1 9 13 25 4 0 1 9 9 24 2 0 0 8.5 11 20 2 0 1 10.45 14 28 2 1 1 12.03 12 41 4 0 1 12.45 16 26 6 1 0 18.1 16 24 11 1 1 9 13 51 10 1 0 11.18 11 49 5 1 1 11 16 24 9 0 0 16 16 37 3 1 1 15.2 13 29 6 1 0 8.83 12 31 1 1 1 10.53 12 32 1 1 1 14 49 2 0 1 13 5.3 16 29 3 0 0 19 13 53 5 1 0 9 12 38 5 0 1 23.75 12 42 38 1 1 25.5 12 40 24 1 0 38 13 40 5 1 0 24 14 39 24 1 1 28.28 12 39 4 1 0 18.04 12 22 2 0 1 18 13 23 30 0 1 15 12 24 2 0 1 12.83 14 43 22 1 1 14.75 8 48 12 0 1 5.3 14 30 5 0 0 5.5 18 28 37 0 0 12 16 41 8 0 1 18 13 47 10 1 0 12 12 40 8 1 1 7 12 24 15 1 0 17.41 16 41 4 1 1 12 13 29 12 0 1 12.98 16 29 5 1 1 5 13 47 18 1 1 7.5 8 36 40 1 0 8 9 33 2 0 1 5.25 16 40 5 1 1 7.5 11 67 3 0 1 21.85 13 39 52 0 1 7.5 13 29 4 0 0 18.32 21 43 14 1 1 12.3 16 43 5 1 0 8.77 13 56 6 0 1 18.9 14 51 16 1 1 5.5 13 31 3 1 1 14 12 27 8 1 0 22 12 51 22 1 0 11 13 20 11 0 0 5.5 9 16 2 0 0 6.5 11 25 3 0 1 6.25 12 24 2 0 0 6 6 53 1 1 1 6 13 61 5 1 0 15 12 40 18 1 0 10.5 12 45 16 1 1 7.3 12 46 5 0 1 13 12 28 3 0 0 8.3 11 24 2 0 0 14.62 12 41 15 1 1 8.31 12 21 7 0 1 6.5 18 5 0 0 13 6.5 13 18 5 0 0 8.32 12 31 1 0 0 7.5 44 14 0 1 8.31 13 22 1 1 1 7 11 48 4 0 0 12 12 54 4 0 0 6 6 29 7 1 0 4 9 20 3 1 1 12 16 36 3 1 1 21 14 33 5 0 1 9.3 14 32 3 0 1 7.46 12 62 6 0 1 13 10 58 3 1 0 8 8 31 12 0 1 7.5 6 34 18 0 0 15 13 31 8 0 0 10 13 19 3 0 1 6 8 16 3 0 0 5.5 11 18 10 0 0 19.75 12 42 6 1 1 5 12 25 4 1 1 7 10 28 1 1 0 5 12 40 4 1 1 7.25 12 42 5 0 1 7 21 5 1 1 8 13 7.5 10 22 2 0 0 5.5 11 52 2 1 1 5.25 14 59 1 0 1 9.69 13 58 30 1 0 10.69 13 49 28 1 1 7.5 13 47 3 1 0 10 12 44 5 1 1 2.35 12 23 4 0 0 21.9 14 41 9 1 0 8.5 12 35 3 1 0 8.38 13 37 6 1 1 8.63 12 54 6 1 1 10.66 16 29 2 0 1 12 16 22 7 0 1 8.37 12 49 4 0 0 15 12 47 25 1 0 13 14 43 10 1 1 10 13 20 8 0 0 8 13 26 3 0 0 14 11 33 8 1 0 7.75 12 33 24 1 1 13.87 14 35 7 1 0 10 9 52 10 1 0 10 12 40 4 0 0 10 12 30 5 0 1 5.5 9 16 8 0 0 8 13 48 18 1 0 8 13 46 5 1 1 14.62 12 41 18 1 1 7 13 21 2 0 1 6 11 18 5 0 0 6 10 17 2 0 1 8 13 20 5 1 1 10 12 37 15 1 1 5.35 12 21 3 0 1 13 10 57 17 1 0 5 12 44 16 1 1 6 12 21 5 0 0 9.5 9 31 66 1 0 9 12 24 60 1 1 7.41 13 28 2 1 0 5.15 12 36 6 1 1 5.15 10 16 6 0 0 18 21 27 1 0 1 5.25 13 28 7 1 1 5.15 12 25 7 1 1 7.25 12 42 2 0 1 7.43 14 51 6 1 1 7 12 39 10 0 0 6 12 38 1 0 0 7 12 45 4 1 1 7.5 12 30 2 0 1 7.5 12 30 3 0 0 6.7 9 38 3 1 1 7 8 40 3 1 0 6.25 9 28 3 1 0 9 12 55 5 1 0 31 16 52 30 1 1 6.5 13 21 6 0 0 10.5 12 40 14 1 0 8.6 12 44 9 1 1 7.25 13 19 7 0 1 7.25 13 22 3 0 1 5.25 12 25 3 0 0 6 11 17 1 0 0 13 13 29 4 1 1 6 16 22 7 0 1 8.6 12 54 3 0 1 10 13 37 2 1 1 11.35 12 51 2 1 1 19.44 13 36 3 0 1 9.5 26 2 0 0 8.03 8 42 9 1 1 5.15 12 19 3 0 0 7.55 12 33 9 1 0 12 8 8 51 20 1 0 5.15 12 24 3 0 1 6.25 12 30 3 1 0 7.56 12 33 15 0 1 11.7 13 42 14 0 1 15 13 40 10 0 0 5.15 13 29 4 1 1 18 12 70 11 0 0 12 13 33 1 1 0 18 14 34 8 1 0 10.35 13 34 1 1 1 5.95 12 31 1 1 1 12.09 12 35 3 1 0 15 14 48 2 0 0 9 12 23 4 0 1 5.5 12 73 20 0 1 7 13 30 6 1 0 5.15 12 33 12 1 1 8.5 9 22 2 1 0 14 14 37 15 1 1 10 12 53 5 1 1 15 16 58 20 1 0 15 14 41 12 1 1 6.5 13 25 5 0 0 6 12 23 10 1 1 6 12 23 4 1 0 6.37 13 57 9 1 1 13.25 12 34 6 1 0 28 16 30 11 0 1 11 13 28 2 0 0 8.63 13 48 18 1 1 5.5 13 20 18 0 0 24 16 53 15 1 0 16.5 12 57 34 1 1 6 12 22 6 0 0 11.25 16 31 4 0 0 16 16 34 3 0 0 13 13 34 2 0 1 18 13 37 17 1 0 13.47 16 39 18 1 1 26 13 49 41 0 1 10 12 24 1 0 0 9 12 24 2 0 0 21.99 13 46 20 1 0 14.55 12 23 6 0 0 12 13 20 3 1 1 12 10 40 12 0 0 13.5 16 35 4 0 0 5.5 14 22 1 0 0 6.75 13 21 5 0 0 5.75 13 21 8 0 0 5.75 13 21 24 0 0 6.25 12 55 5 1 1 6 12 27 4 0 1 11.52 14 49 6 0 0 8 12 21 2 0 0 16.97 14 42 6 1 0 14.37 14 29 1 1 1 5 12 31 6 1 1 6.75 16 52 1 1 1 14.67 13 48 8 0 1 18 12 34 5 0 0 10.45 14 62 9 1 0 12.25 11 39 7 1 0 11.93 12 36 9 1 1 40 21 36 5 1 0 11.69 12 42 18 1 1 7 13 46 10 1 1 5.5 12 29 8 0 1 12 11 32 5 1 1 5.15 6 26 2 1 0 6.5 13 21 36 0 1 6.5 13 19 12 0 0 20.78 13 36 6 1 0 8.65 12 31 3 1 1 7.99 13 47 6 1 1 12 11 20 12 1 0 13.75 13 31 10 1 1 19.16 13 43 27 1 1 7.75 12 28 11 0 0 7 11 48 5 1 1 6 13 21 2 1 1 21.9 12 50 10 0 0 8.52 12 35 4 1 1 12 12 52 8 1 0 6.4 13 47 18 1 1 11.08 14 39 6 1 1 12.11 12 58 15 0 1 20 16 35 3 0 0 13.74 13 41 5 1 1 7.5 12 44 7 1 0 7.5 13 19 1 0 0 10 13 19 3 0 0 15 8 33 12 1 0 16 14 36 3 1 1 10 11 58 4 1 0 5.5 11 17 9 0 1 7 13 43 1 0 1 14 13 45 4 0 0 5 10 16 3 0 1 12.5 13 25 3 0 0 7 13 50 6 1 1 10.81 12 31 3 1 0 12 13 29 3 1 1 5 11 44 2 1 0 33 21 37 7 1 0 15.7 14 44 7 1 0 14 10 47 5 1 1 16.5 16 42 18 0 1 16.5 16 34 10 0 0 37 18 49 4 0 0 28 16 53 3 1 1 8 16 24 1 0 1 40 16 45 8 1 0 7 9 15 1 0 1 20 13 49 30 1 0 18 13 38 3 1 0 17 14 38 10 1 1 7.63 14 24 3 0 0 11 12 63 3 1 0 9 10 31 7 1 0 12 16 30 3 1 0 13 14 28 1 1 1 10 14 30 8 1 0 14 18 37 9 1 1 6 4 32 7 1 0 6 6 31 3 1 0 5.15 11 19 4 0 1 9 32 2 1 0 7.38 11 61 7 0 1 7 23 1 0 1 5.15 8 27 16 1 0 5.15 6 29 18 1 0 7 14 70 3 0 1 7 12 27 2 0 0 8 9 27 2 1 1 8.5 14 58 8 1 0 5.15 13 37 13 1 0 13 16 28 4 0 1 20 16 45 10 0 1 27 13 35 9 1 0 14.33 4 48 13 0 0 9 16 26 4 0 1 5.41 12 18 1 0 1 10 18 36 4 0 1 6.8 13 25 3 0 1 5 6 29 10 1 0 18 12 35 12 1 0 13 16 28 30 1 1 12.25 16 27 6 0 0 6 13 13.5 16 28 8 1 0 10 13 23 1 1 1 8.75 14 24 4 1 0 6 13 23 6 1 1 18.75 12 36 7 0 0 9.5 12 36 2 0 1 6.95 13 24 2 0 0 9.1 13 25 5 0 1 14 9 35 18 0 0 9.75 12 34 6 1 0 25 18 40 10 1 0 23 16 37 10 1 1 26 16 37 10 1 0 6 11 17 8 0 0 22.5 16 38 3 1 1 21.5 13 41 4 1 0 12.5 21 31 1 0 0 6 4 34 1 1 0 9 6 33 13 1 1 7 11 52 5 0 1 5 1 30 3 1 0 5 1 28 2 1 0 5 1 24 3 1 1 5 4 54 4 1 0 5 8 23 6 0 1 6 6 40 5 1 0 8 13 35 1 0 1 6 12 30 5 1 1 7 12 40 1 1 0 5.41 12 18 1 0 1 5.5 13 19 1 0 0 5.41 13 21 2 0 1 5.5 13 29 1 1 1 10 16 45 16 0 1 7.5 13 19 3 0 1 12.5 12 45 2 0 1 5.25 12 33 3 1 0 6 11 18 3 0 1 12 18 31 6 1 1 5.5 13 20 1 0 1 5 11 52 25 0 0 5.15 12 52 2 0 1 8 13 30 11 1 0 7 16 27 9 1 1 23.5 21 40 8 0 0 6 8 26 1 1 0 11 12 29 4 0 0 12 12 39 6 1 1 8 14 28 9 0 1 8 13 26 5 1 1 7.9 6 64 4 1 0 7.9 4 59 15 1 1 10.05 6 45 4 0 1 6 12 19 4 0 0 10 12 21 1 1 0 10.25 18 67 4 0 0 6.3 16 52 1 0 0 9 16 52 6 0 1 12.12 16 41 20 1 0 22.5 16 63 7 0 1 10.15 14 47 7 0 1 6 12 18 1 0 1 7.75 12 25 6 1 1 15 46 6 0 1 9.36 6 28 9 1 1 6 11 28 5 1 0 7 6 21 3 0 0 20.17 13 50 20 1 0 6 12 22 10 0 0 7.5 13 21 4 0 1 10.74 12 37 6 1 0 10.54 12 25 2 0 0 8.76 12 32 8 1 1 9.56 12 38 9 1 0 5.15 12 39 7 0 0 16 6 14 53 2 1 1 13 13 30 6 0 0 28 21 32 3 0 0 11.5 13 30 5 0 1 9.5 14 40 6 0 1 9.5 14 53 15 0 1 25.44 12 44 16 1 0 10 11 50 29 1 1 9 12 45 12 1 1 7 13 24 6 0 1 18.13 13 48 11 1 1 8 13 20 3 0 1 5.25 10 17 1 0 1 15 16 33 4 0 0 13.62 13 35 5 0 1 13 13 31 3 0 1 5.25 13 24 2 1 0 9.85 14 27 4 1 1 6 4 25 4 0 0 5.5 4 21 24 0 0 6 1 24 12 0 0 6 1 23 30 0 0 6 11 18 12 0 0 13.25 16 48 5 0 1 6.5 18 3 0 0 11 7 13 23 1 0 0 8 6 36 3 0 1 15 12 36 3 0 0 7.31 11 42 1 0 1 20 16 34 5 0 1 14 12 27 4 1 0 7 13 24 3 0 1 16 13 36 10 1 0 18 12 48 20 1 0 6 12 20 3 0 1 7 12 18 3 0 1 10 12 20 3 0 0 8 16 47 56 0 1 19 14 37 15 0 1 20.96 14 43 7 0 1 12 16 33 8 0 0 6 4 25 2 1 1 6 6 32 10 1 1 11 12 26 2 0 0 10 13 21 3 0 1 10.25 12 22 18 0 1 10 12 37 4 0 1 5.15 11 18 2 0 0 9 14 51 3 1 1 5.5 11 18 2 0 1 10 12 44 2 1 1 6 11 17 11 0 0 5.75 13 18 6 0 0 14 13 29 4 1 0 33 18 34 4 1 0 11 14 31 3 1 1 11 14 55 10 0 0 7.42 6 42 8 1 1 5.25 11 18 78 0 0 10 13 26 3 1 1 17 14 48 2 1 1 8 12 41 10 1 1 7 14 31 3 1 1 16.75 14 35 2 1 0 5.25 13 20 3 0 1 5.25 12 36 7 0 1 25 18 34 10 1 1 9 13 30 3 1 1 5.5 4 43 8 1 1 13 12 33 4 1 0 3.25 13 20 1 0 1 8.5 13 27 3 0 1 10.87 14 39 11 1 1 41 16 55 3 1 0 9.5 13 47 2 0 0 5.5 12 35 15 1 1 11.5 9 37 7 1 0 6 11 18 8 0 0 5.25 16 25 3 0 1 5.25 14 22 2 0 1 23 21 42 3 1 1 5.5 13 40 10 1 0 7.5 13 41 1 1 1 11.78 13 51 9 1 0 10.6 13 49 13 1 1 8 13 34 3 0 1 5.15 13 22 9 0 0 5.5 12 38 4 0 1 22 14 60 10 1 0 12.98 16 56 20 1 1 22 12 47 1 1 0 8.25 12 43 2 1 1 5.25 11 18 3 0 1 11 13 24 7 1 0 8 13 59 8 0 1 8.63 14 47 5 1 1 7.92 16 45 27 1 0 13 12 21 1 1 0 5.25 12 19 4 1 1 7.25 12 32 9 0 1 9 12 40 2 0 0 5.5 10 20 3 0 0 5.25 14 29 1 0 0 6 12 19 4 0 0 9 13 20 5 0 0 6 13 20 1 0 0 8.65 8 67 31 1 0 11 6 39 7 0 1 6 12 30 5 1 1 8 12 21 2 0 0 13 13 34 1 0 0 5 14 22 1 0 1 7 16 31 3 0 0 13 16 25 4 0 1 12 11 34 5 1 0 6 13 20 2 0 0 14.74 16 33 7 0 1 8.65 16 31 1 1 1 28.64 14 60 10 1 1 27 16 51 25 0 0 13 12 25 14 1 1 5.25 13 67 1 1 0 10 16 35 3 1 1 8 12 41 18 1 0 5.55 12 48 3 1 1 31 18 47 10 1 1 14.78 12 41 9 1 0 14 12 46 29 1 1 17.62 13 57 28 0 0 12.42 13 39 3 1 1 25 13 34 3 1 0 31 16 43 15 0 0 25.96 16 26 37 1 0 21 16 26 18 1 1 16 16 26 42 1 0 5.15 13 23 1 0 0 6.5 12 22 4 0 0 6.5 13 21 2 0 1 6 13 20 17 0 1 7 13 22 2 0 0 14.78 12 38 1 1 0 5.35 8 36 6 1 1 7.25 12 28 4 0 1 6.5 13 23 1 1 1 40 16 55 18 0 1 9.25 12 70 2 0 1 23 13 46 8 1 0 10 13 19 6 0 1 9.05 14 22 3 0 1 7.5 18 3 0 1 13 8 13 23 1 0 1 5.5 13 25 7 0 1 14 4 47 7 1 0 7 4 42 30 1 1 14 11 26 4 0 0 5 9 16 5 0 0 25 13 37 8 1 0 8 14 37 3 1 1 17.1 14 34 4 1 0 10.5 14 35 10 1 1 19.84 13 41 18 1 0 12.5 13 40 5 0 1 6 16 9 0 0 5.15 8 15 9 0 1 30 12 39 2 1 0 6 12 37 10 1 1 6.5 12 18 1 0 0 20.97 21 48 8 1 0 6.21 11 17 10 0 0 9 14 48 7 1 1 8.91 13 44 12 1 0 6 13 21 18 0 0 6.75 13 19 30 0 0 14.75 13 49 12 0 1 7.25 13 32 2 1 1 10 8.5 8 31 10 1 0 16.5 14 44 2 1 0 12.75 14 51 8 1 1 19 16 44 1 1 1 6.25 13 17 1 0 1 17.5 12 45 23 0 1 16.25 12 42 13 0 0 8.65 12 41 2 0 1 14.35 12 31 5 1 0 8.5 18 54 18 1 1 18 13 34 10 1 0 14.78 14 39 2 1 0 5.5 6 41 25 1 0 40 16 62 8 1 0 9.62 12 43 4 0 1 6 12 30 3 0 1 6 13 21 3 0 1 6 14 34 4 0 1 5.5 4 50 9 0 0 11.7 12 51 4 1 0 27.5 14 40 19 0 0 30 12 47 4 1 1 5.5 12 18 4 0 1 11.2 13 34 2 1 1 14.5 13 39 3 1 1 10 13 54 9 1 0 11.8 13 54 19 1 1 21 14 48 16 1 0 11 12 54 6 1 1 8 8 37 18 1 0 10 11 26 5 0 0 6 11 17 3 0 0 5.65 12 18 2 0 0 21 16 49 24 1 0 5.25 13 18 5 0 0 8 16 35 8 1 0 9.58 12 21 4 1 0 5.25 11 65 18 0 1 16.25 12 47 27 1 0 30 12 47 20 1 1 6.5 12 23 3 1 1 12 12 25 14 1 1 5.5 12 17 4 0 1 10 13 25 5 0 1 8.45 13 40 3 1 1 11.5 13 56 14 1 1 12.69 14 44 4 0 0 9.27 18 55 5 1 0 10 13 46 8 1 1 7 16 25 6 0 0 8.5 12 22 1 1 0 10 13 24 10 1 1 6 12 22 1 1 1 9.75 12 44 3 1 0 9.56 12 43 3 1 0 5 9 15 12 0 0 8 13 32 11 0 1 13.5 13 45 3 1 0 23 13 44 11 1 1 11 13 66 17 0 1 8 13 19 3 0 0 10 14 45 5 1 1 22.75 13 49 26 1 0 9.31 18 27 19 0 1 11.39 11 42 11 1 0 6.15 21 47 3 1 0 18 14 29 5 1 0 16.42 16 27 3 1 1 30 13 29 2 0 0 15 12 68 7 1 0 25 12 44 10 0 0 22 18 53 1 0 1 13.65 12 62 8 1 0 10.26 12 58 5 1 1 16 48 4 0 0 12 9 12 20 6 0 0 7 12 41 6 0 1 4.35 13 23 6 0 0 5.65 13 24 4 0 1 37 13 52 23 1 0 7 13 20 1 0 0 9 11 69 14 1 0 25.22 13 42 21 1 0 12 13 32 4 1 1 21 12 41 18 1 0 38.48 16 38 9 1 1 16.23 14 51 11 1 0 10 12 41 4 1 1 18.5 16 61 31 0 0 22 16 55 20 1 0 6 13 19 3 1 0 8.25 12 24 23 0 1 9 13 44 6 0 1 5.5 11 18 3 0 1 8 12 20 5 0 1 11 16 29 4 0 1 15 13 31 18 0 0 6.83 13 23 1 0 0 7 16 24 2 1 0 10.5 18 25 3 0 0 5.4 12 19 4 0 1 19 16 50 11 1 1 10 12 52 13 1 1 4.57 12 32 5 0 0 5 8 37 5 0 0 5 11 40 5 0 0 10 12 34 3 0 0 10 16 29 3 1 0 8.5 13 22 3 1 1 9.5 13 45 3 0 1 12.5 12 36 1 0 0 7.25 12 29 3 0 1 17 13 38 1 1 1 9 12 42 5 1 1 5.15 12 21 9 0 0 7 12 23 7 0 1 9.23 12 27 5 0 1 7 11 44 9 1 1 5.25 11 18 2 0 0 9.5 6 42 3 1 0 9.5 12 21 3 0 1 6.45 12 67 4 0 1 7.5 13 49 15 1 1 11.5 16 24 2 1 0 12.5 14 25 2 1 1 11.48 12 49 22 0 1 15.5 12 44 7 0 0 9.3 13 25 4 1 1 10 12 28 4 1 0 8 16 34 4 1 1 11 13 25 6 0 1 7 13 20 3 0 1 6.05 10 17 8 0 0 7.5 12 39 8 0 1 5.25 10 17 3 0 1 14 16 45 12 0 1 22 12 38 14 1 0 13.5 13 41 20 0 0 7 12 40 2 1 1 9 12 48 3 1 0 5.4 13 21 6 0 1 9.29 12 49 3 0 1 10.05 12 42 16 0 0 6.25 12 70 15 0 1 6 13 21 6 0 0 15.73 10 61 24 0 0 20 11 60 23 0 1 10.25 12 53 3 1 1 11 12 55 10 1 1 10 21 60 12 1 1 21.55 12 37 12 1 0 18 13 31 16 1 0 7.5 12 51 8 1 1 13 14 66 17 1 0 12 14 29 1 0 1 9 12 27 1 0 1 6 12 19 6 0 0 9.1 14 30 1 0 0 21 12 56 29 0 1 10 14 22 2 0 0 23.5 14 35 11 1 1 37 12 51 34 1 0 10 11 34 3 0 0 32.5 16 57 10 1 1 20.95 12 49 20 0 0 7.65 12 40 1 0 1 9 13 19 1 0 1 7 13 71 23 1 1 30 18 40 6 1 1 7 12 23 3 1 0 6 8 31 2 0 1 10 12 42 7 1 1 17 13 43 12 1 0 6.95 13 19 4 0 1 10.82 13 20 1 0 0 8.5 12 41 4 1 0 8 14 42 2 1 1 11.17 13 28 42 1 0 12.17 12 33 9 1 1 15 12 43 13 0 0 18 12 49 18 0 1 5.5 12 55 9 1 1 10 12 25 2 0 0 9.62 12 42 4 1 1 6 11 17 1 0 1 6 12 26 3 0 1 15.26 16 27 5 1 1 15.4 13 28 1 1 0 6.25 11 28 4 1 1 9.5 14 45 4 1 1 10 13 18 6 0 1 13.5 12 26 3 0 0 7.5 11 17 8 0 1 14 13 42 8 1 0 8 13 39 1 1 0 11.05 12 26 3 0 0 7.25 12 29 18 1 1 7.8 12 46 5 1 1 6.4 13 46 3 1 1 8 14 20 3 0 0 8.5 14 27 3 0 1 10 13 30 3 0 0 13 16 23 1 1 0 10.32 14 22 1 1 1 14 12 36 14 0 0 13.86 13 40 2 1 0 9 12 28 2 1 1 11.64 13 29 4 1 1 8 12 19 6 0 0 7 12 18 3 0 1 6 13 40 8 1 1 6 10 26 18 0 0 6.1 13 20 2 1 1 16 16 36 6 1 0 12 13 34 14 1 1 12 12 54 11 0 1 6.5 13 19 2 0 0 8 13 46 3 0 1 6 12 36 1 1 1 7 16 23 8 0 1 6.5 12 45 10 1 1 20 13 45 5 0 1 10 14 24 2 1 1 17.5 14 39 13 1 0 15 38 4 1 1 12 20.63 13 35 12 1 0 15.82 16 31 7 1 1 8 14 40 2 1 1 6 10 17 3 0 0 6.5 13 19 2 0 0 9 16 46 11 1 1 20 16 32 11 1 1 15.8 13 33 11 1 0 20.27 14 29 10 1 0 14.76 14 29 30 1 1 15 13 32 11 0 1 10 12 53 6 1 1 10 11 51 11 0 1 7.35 12 50 25 1 1 6.25 13 41 9 1 1 11.52 14 32 11 0 1 12 14 38 18 1 1 9.5 13 33 17 1 0 7 12 34 10 1 0 6.8 12 32 7 1 1 10.9 10 65 17 1 1 12 13 32 5 1 0 15.96 12 53 33 0 1 20 14 28 4 0 1 10 13 38 6 1 0 7.5 13 36 2 1 1 6 12 22 2 0 1 8 13 34 10 0 0 15.81 13 43 5 0 1 15 12 27 4 0 0 14.5 18 47 11 0 1 12.4 12 47 10 0 0 8.5 14 54 4 0 0 12.5 13 54 4 0 1 6 12 63 9 0 0 9 12 31 6 0 1 12 14 31 7 1 0 12 16 32 6 1 1 12.09 12 22 1 0 0 12 12 49 15 1 1 14 13 49 20 1 1 10 12 59 28 0 1 5.25 12 40 1 0 0 8 12 29 3 1 1 10.1 16 47 2 1 1 10.75 12 43 13 0 0 7.5 13 22 2 0 1 15 14 36 2 1 0 10 12 27 1 0 1 15 12 31 5 0 0 12 14 45 2 0 0 5.15 14 23 3 0 0 5.25 16 21 2 0 1 7.5 12 41 1 0 0 5.9 13 35 4 0 1 6.19 14 35 4 0 1 10.5 14 41 8 1 0 8.67 16 41 9 1 1 5.5 12 32 2 0 1 5.15 12 55 9 0 1 12 12 28 3 0 1 9.5 16 34 6 1 1 6.5 12 19 3 0 0 8.25 13 23 7 0 1 8.5 12 46 3 1 1 6.5 13 19 2 0 0 36 18 33 6 1 0 13 12 42 17 1 0 15 11 36 14 1 1 5.25 11 18 1 0 1 10 18 54 3 0 1 8.5 13 19 6 0 0 12 12 23 6 0 0 25 16 40 3 1 0 8.5 13 22 5 0 1 6.25 13 37 13 1 1 15.64 12 30 6 0 1 18.54 12 53 10 1 0 2.01 11 32 3 0 0 8 11 35 3 0 1 10 12 28 1 1 1 16 14 45 5 0 0 7 13 26 6 0 1 5.55 16 73 1 1 0 6.75 12 66 3 1 1 5.25 9 16 6 0 0 5.15 8 66 4 1 0 5.9 10 61 4 1 1 9.5 14 44 25 0 1 6.5 13 21 1 0 0 6 10 20 2 0 1 17 12 41 6 1 0 5.25 9 16 2 0 0 5.5 13 25 2 1 1 11.86 14 52 10 0 0 2.13 14 25 3 1 1 10.75 14 42 5 0 1 5.75 11 37 1 1 1 6.75 21 48 18 1 0 6 48 3 1 1 12 12 12 50 18 1 0 15 12 55 20 0 0 9.85 13 38 10 1 0 8 14 33 4 1 1 9 12 32 3 1 1 ECN/PUB 480/580 Assignment #7 Due: Friday, April 20th, 2017, 5:30pm Directions: Completely answer all the questions. You can integrate the Stata output within the questions using the techniques previously discussed. Please do not print out or turn in any of the original raw data!! Be sure to clearly indicate the units for all numbers ($, %, years, etc). Please staple all the pages together (no folders). Due by Monday, April 24th, either by personal delivery to 220 French Hall or by email of a MS Word file. Please turn in your assignment by the final deadline, even if it is incomplete (so I can compute final grades). Assignments that are submitted late (defined as starting at 5:31pm on April 20th) will be penalized by 10% per day that they are late. Read the questions and the directions carefully!!! The material needed to answer the questions is contained in the course notes. Your notes contain both the underlying statistical procedures behind the questions, as well as several examples that are very similar. You may also want to refer back to Assignments 4, 5, and 6 to refresh your memory on some of the things you will be doing. _______________________________________________________________________ Go to Blackboard to download the Assignment #7 exam data set. How to download: -Go to the “Assignments” section of Blackboard. -Right-click on the file. Select “Save Target As”. -Save the file on your computer in an easy-to-find place, such as The Desktop. -Open Stata. Select “File”, then “Open” and browse for where you stored the data set. -Double-click the data set to open it in Stata. BEFORE ANSWERING EACH QUESTION, MAKE SURE TO READ THE QUESTION CAREFULLY AND DO WHAT THE QUESTION ASKS! 1 The data set is a Stata data set containing labor market data for 1000 randomly selected individuals (unit of analysis) from the February, 1998 U.S. Census Current Population Survey. The data set includes the following variables: wage: average hourly earnings, in dollars, for each individual educ: number of years of education for each individual age: age of each individual, in years exper: number of years of work experience for each individual marr: dummy variable taking the value of 1 if the individual is married, 0 otherwise female: dummy variable taking the value of 1 if the individual is female, 0 otherwise Start by opening the data set in Stata and generate 5 new variables using the gen command. To help you out, I give the command you need to use in parentheses. a) the natural logarithm of wages (gen lwage = log(wage)) b) experience squared (gen expersq = exper^2) c) a new dummy variable for male, which takes on the value of 1 if the individual is a male and 0 otherwise (gen male = 1-female) d) a new interaction dummy variable marrfe taking on the value of 1 if the individual is a married female, and 0 otherwise (gen marrfe = marr*female) e) a new interaction dummy variable that will be equal to 1 if the individual is a married male, and 0 otherwise (gen marrma = marr*male) The point of this assignment is to conduct a regression analysis to see if the “wage gap” between male and female workers persists after we start controlling for other variables, namely education and experience. 1. Create a table in MS Word (with a title and description) that summarizes the data by gender. That is, give the average wage, average education, average experience, and average age separately for men and women. You can use the sum command along with an if statement to do this (no commas). For example, if female == 1 means only females. Use proper units for the variables in your summary statistics and round to two places past the decimal. Do NOT use the Stata output as your table! (4 points) 2. Calculate difference-of-means tests and report the t-statistics for the null hypothesis that the average wage for male workers is the same as the average wage for female workers. Use a 5% level of significance. Since you have a large sample, you can use the z-critical value. Either do the calculations by hand (show your work), or you can do the test in Stata using the ttest command. Hint: Refer to Assignment 4 to refresh your memory of this test. If you want to do the test in Stata, refer to the example handed out in class regarding the Stata command for the test (example is also 2 available on Blackboard, in case you lost it). If you choose to do the test in Stata, you still have to indicate whether you are accepting or rejecting the null hypothesis by comparing the test statistic to the critical value. In other words, simply copying-and-pasting the Stata output is not sufficient. What does the difference-of-means test tell you regarding average male and female wages? (4 points) 3. Consider the following two regressions: Regression A: wage   0  1educ   2exper  3expersq   4 female  ui Regression B: lwage  0  1educ   2exper  3expersq   4 female  ui Regression A is just your typical linear multiple regression. Regression B is a log-linear regression. Refer to the course notes and handout (also available on Blackboard) regarding log-linear regressions. Estimate both equations using Stata’s reg command. Include your output along with the command used to generate it. 4. a. Interpret the coefficients β1 and β2 from each equation. Based on the coefficients, how is the independent variable related to the dependent variable? In particular, how will the dependent variable change if the independent variable increases by 1 unit? Be specific and use specific units!! (6 points) b. Explain the signs on the coefficients β2 and β3 for Regression A. What do the signs indicate about the relationship between the independent and dependent variables? Hint: refer to the section on quadratics in your notes or the handout on quadratics. Is the relationship between wage and experience a straight linear relationship or does the relationship taper over time? Why do you think this is the case? (3 points) c. For each regression, interpret β4, which is the estimated coefficient on the female dummy variable. Recall that the estimated coefficients on dummy variables have an “if-then” interpretation. In other words, if the dummy variable equals 1, then the dependent variable changes by the associated β. β4 would thus be the “wage gap,” since it says how much more or less someone earns if that particular person is female. (3 points) a. In both regressions, which of the estimated coefficients (that is, the βs) are significant and why? Explain your answer referring to the t-statistics, critical values, and use a 5% level of significance. You can either use the t-statistics in the Stata output or calculate them yourself. You can ignore the constant (β0). Use a two-tailed test. (6 points) b. Explain what the R2 and F-statistics mean for these specific equations. That is, for the F-statistic, do you accept or reject the H0 for the F-test? (4 points) 3 5. Estimate Regressions A and B for only single people. Do this by including the statement if marr == 0 at the end of the reg command (no commas). Is the wage gap (as given by the coefficient on the variable female) statistically significant? Compare the estimated coefficient for female in this case to that in question 3. Is the “wage gap” for single women more or less than for women in general? How much more or less? Why do you think this is? Hint: compare the size and significance on the β associated with female in this case compared to what you found in question 3. (5 points) 6. Estimate regressions A and B for only people who are single and less than 30 years old. Do this by including the statement if marr == 0 & age < 30 at the end of the reg command (no commas). Given how young this subsample is, do not include the variable expersq. Include the variable female in both equations and interpret the results as you did in question 5. Is the wage gap statistically significant in this case? Is the “wage gap” for single women more or less than for single women in general? For women in general? How much more or less? Why do you think this is? Hint: Compare the size and significance of β in this case to what you found in questions #3 and #5. Why do you think they are different? (5 points) 1 point extra credit: Refer to the statement “Given how young this subsample is, do not include the variable expersq” from question 11. What do I mean by this statement? That is, why would including the square of experience be inappropriate here? You can answer this in just one or two sentences. 7. Summarize your results. What do your results suggest regarding the “wage gap” between male and female workers? Compare your results for the difference of means tests, Regressions A and B for all workers, for single workers, and for single young workers. Can we say anything about where the wage-gap is coming from? (5 points) You are done!!! Have a good summer! ☺ 4
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Explanation & Answer

Attached.

Question 1
Table 1: Descriptive statistics by gender.
Females
Variable
Wage
Education
Experience
Age

Mean
10.26
12.79
7.73
36.21

Minimum
2.13
1.00
1.00
15.00

Maximum
40.00
21.00
60.00
73.00

2.01
1.00
1.00
12.69

45.00
21.00
78.00
73.00

Males
Wage
Education
Experience
Age

11.95
12.34
8.24
34.78

Discussion
From table 1 above on descriptive statistics of the average wage, education, age, experience
of females and males are outlined. As indicated the output for females, the average wage is
10.26 dollars, the average number of years of education for the females is 12.79 years, the
average number of years of the females is 36.21 years and lastly the average number of work
experience of each female individual is 7.73 years. For males, the average income is 11.95
dollars, on average each male has 12.34 years of education, 8.24 years of working experience
and the average age for males is 37.78 years.
Question 2
Hypothesis
H0: There is no difference between the average wage for male workers and female workers.
H1: There is a difference between the average wage for male workers and female workers.

Two-sample t test with equal variances
Group

Obs

Mean

0
1

466
534

combined

1000

diff

Std. Err.

Std. Dev.

[95% Conf. Interval]

11.95082
10.26152

.3315513
.2301349

7.157209
5.318058

11.29929
9.809434

12.60234
10.7136

11.04873

.1991077

6.296338

10.65801

11.43945

1.689299

.3957427

.9127153

2.465882

diff = mean(0) - mean(1)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
degrees of freedom =
Ha: diff != 0
Pr(|T| > |t|) = 0.0000

4.2687
998

Ha: diff > 0
Pr(T > t) = 0.0000

Explanation
From the Stata output above, the corresponding test statistic for the difference of
means test is 4.2687 and the corresponding critical value from the normal tables is 1.96.
Since the test statistic is greater than the critical value (4.2687 > 1.96) we reject the null
hypothesis and conclude that there is a significance difference between the average wage for
males and that of the females. The difference in the average wage indicate that the males earn
a significant higher amount than the females since the difference is positive.
Question 3
Interpretation of Regression A
From the output below the interpretation of the coefficients of β1 is 0.9566839.
This implies that education and wage have a positive relationship. A unit increase
in number of years of e...


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