Hello !
it is my first time to post. Please, excuse my poor English writing.
Please, how to evaluate the wage differential between unionized firms (the presence of a union where the individual works) and non-unionized firms (the absence of a union where the individual works) with separate estimation of wage determination, using Quasi-maximum likelihood estimations (poisson; gamma; NLS) and OLS, for an individual with average characteristics for the entire sample; and get the results with *(**){***} significant coefficients at the 10% (5%){1%} level.
The formula of my union wage differential based on a separate estimation is : d = (Bu - Bn)X where X is the average characteristics for the entire sample.
My variable of interest is union presence (0 for unionized firms; and 1 for non-unionized firms). Below are means and standard errors for the variables I use (taking into account the command svy for complex survey data).
Thank you !
it is my first time to post. Please, excuse my poor English writing.
Please, how to evaluate the wage differential between unionized firms (the presence of a union where the individual works) and non-unionized firms (the absence of a union where the individual works) with separate estimation of wage determination, using Quasi-maximum likelihood estimations (poisson; gamma; NLS) and OLS, for an individual with average characteristics for the entire sample; and get the results with *(**){***} significant coefficients at the 10% (5%){1%} level.
The formula of my union wage differential based on a separate estimation is : d = (Bu - Bn)X where X is the average characteristics for the entire sample.
My variable of interest is union presence (0 for unionized firms; and 1 for non-unionized firms). Below are means and standard errors for the variables I use (taking into account the command svy for complex survey data).
| Education (%) | Higher Not in school Primary Secondary |
22.94 4.61 22.92 49.52 |
0.421 0.21 0.420 0.50 |
36.42 1.83 13.49 48.26 |
0.481 0.134 0.342 0.50 |
17.15 5.81 26.98 50.07 |
0.377 0.234 0.444 0.50 |
|||
| Job tenure | 5.46 | 6.626 | 7.340 | 7.837 | 4.657 | 5.851 | ||||
| Training (%) | No Yes |
75.49 24.51 |
0.430 0.430 |
63.55 36.45 |
0.482 0.482 |
80.62 19.38 |
0.395 0.395 |
|||
| Age (%) | 15 – 34 years (youth) 35 – 54 years (adult) 55 – 64 years (senior) |
57.77 38.67 3.57 |
0.494 0.487 0.185 |
46.81 47.69 5.50 |
0.499 0.500 0.228 |
62.47 34.79 2.74 |
0.484 0.476 0.163 |
|||
| Marital status (%) | Single Married Widow/separated Common-low marriage |
41.67 42.67 3.81 11.84 |
0.493 0.495 0.192 0.323 |
28.85 54.04 3.68 13.43 |
0.453 0.499 0.188 0.341 |
47.18 37.79 3.87 11.16 |
0.499 0.485 0.193 0.315 |
|||
| Gender (%) | Female Male |
26.37 73.63 |
0.440 0.440 |
25.61 74.39 |
0.437 0.437 |
26.70 73.30 |
0.442 0.442 |
|||
| Type of work (%) | Permanent Occasional |
92.79 7.21 |
0.259 0.259 |
97.91 2.09 |
0.143 0.143 |
90.58 9.42 |
0.292 0.292 |
|||
| Institutional sector (%) | Informal Public Formal private |
55.56 28.61 15.83 |
0.497 0.452 0.365 |
31.36 42.12 26.52 |
0.456 0.494 0.442 |
65.96 22.80 11.24 |
0.474 0.420 0.316 |
|||
| Industry sector (%) | Services Primary Manufacturing Trade |
67.14 4.96 18.90 8.99 |
0.470 0.217 0.392 0.286 |
70.61 2.90 21.15 5.35 |
0.458 0.168 0.409 0.225 |
65.65 5.85 17.94 10.56 |
0.475 0.235 0.384 0.307 |
|||
| Location (%) | Rural Urban |
30.71 69.29 |
0.461 0.461 |
28.45 71.55 |
0.451 0.451 |
31.68 68.32 |
0.465 0.465 |
|||
| Union presence (%) | Non-unionized firm Unionized firm |
69.94 30.06 |
0.459 0.459 |
|||||||
| Occupation (%) | Skilled worker Not skilled worker Semi-skilled worker Middle manager Senior executive |
23.95 23.85 27.67 14.98 9.56 |
0.427 0.426 0.447 0.357 0.294 |
26.78 12.23 21.49 21.80 17.71 |
0.443 0.328 0.411 0.413 0.382 |
22.73 28.84 30.33 12.05 6.05 |
0.419 0.453 0.460 0.326 0.238 |
|||
| N | 3658 | 1093 | 2565 |
