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Table B1

Descriptive Statistics of Variables by Birthplace Groups, Adult, Full-time Employed Males, Australia, 2001

Variable

Mean

Standard Deviation

Australian Born:

Log Hourly Earnings

2.882

0.562

Years of Education

12.072

2.396

Years of Experience

21.761

11.505

Marital Status (Married = 1)

0.708

0.455

Government Sector

0.164

0.371

Occupation







Managers and Administrators

0.144

0.351

Professionals

0.174

0.379

Associate Professionals

0.134

0.341

Tradespersons

0.213


0.409

Advanced Clerical

0.008

0.087

Intermediate Clerical

0.092

0.289

Production Workers

0.125

0.331

Elementary Clerical

0.039

0.194

Labourers

0.071

0.256










English-Speaking Developed Countries:

Log Hourly Earnings

3.004

0.542

Years of Education

12.594

2.495

Years of Experience (EXPER)

25.430

10.753

Years of Arrival:

Arrived 2000-2001

Arrived 1998-1999

Arrived 1996-1997

Arrived 1991-1995

Arrived 1986-1990

Arrived Before 1986


0.046

0.056

0.043

0.068

0.125

0.661


0.210

0.230

0.203


0.253

0.331

0.473


Marital Status (Married = 1)

0.790

0.407

Government Sector

0.151

0.358

Occupation







Managers and Administrators

0.154

0.361

Professionals

0.216

0.412

Associate Professionals

0.130

0.336

Tradespersons

0.204

0.403

Advanced Clerical

0.007

0.082

Intermediate Clerical

0.090

0.286

Production Workers

0.105

0.307

Elementary Clerical

0.037

0.188

Labourers

0.058

0.233








Non-English-Speaking Countries:

Log Hourly Earnings

2.883

0.562

Years of Education

12.673

3.067

Years of Experience (EXPER)

25.067

11.467

English Proficiency:

Very Well

Well

Not Well

Not at All


0.408

0.231

0.072

0.004


0.491

0.421

0.258

0.061

Years of Arrival:

Arrived 2000-2001

Arrived 1998-1999

Arrived 1996-1997

Arrived 1991-1995

Arrived 1986-1990

Arrived Before 1986


0.028

0.039

0.037

0.107

0.183

0.606


0.165

0.193

0.190

0.310

0.387

0.489

Marital Status (Married = 1)

0.780

0.414

Government Sector

0.124

0.330

Occupation






Managers and Administrators


0.112

0.315

Professionals

0.218

0.413

Associate Professionals

0.129

0.336

Tradespersons

0.180

0.384

Advanced Clerical

0.007

0.083

Intermediate Clerical

0.067

0.250

Production Workers

0.148

0.355

Elementary Clerical

0.035

0.185

Labourers

0.104

0.305




1 Positive selectivity can arise from the supply side (incentives for migration) or the demand side (criteria for allocating visas) of the market for immigrants.

2 For an application for the US unrelated to immigration see Sicherman and Golar (1990).

3 The RADL is an on-line database query system, under which microdata are held on a server at the Australian Bureau of Statistics (ABS) in Canberra. Registered users are able to submit programs (e.g., SAS, SPSS) to analyze the data.

4 Due to the 15-fold difference in population size, this level of detail is less than that utilised in the research for the US by Chiswick and Miller (2007), where the aggregate-level analysis was based on 23 occupational categories, and the more disaggregated analysis on over 500 occupations.


(a) For an analysis of the apparent decline in earnings with duration of residence among immigrants from the English-speaking developed countries, see Chiswick and Miller (2008).

5 To ascertain whether these relationships are due to immigrant occupational crowding, the difference in the occupational fixed effects between the Australian born and immigrants from English-speaking countries was related to the proportional representation of immigrants from English-speaking countries in each occupation and to differences in the proportional representation of the Australian born and immigrants from English-speaking countries. The findings did not support this possibility. This is also the case for the occupational fixed effects for immigrants from non-English-speaking countries (Figure 2).

6 There are, however, three occupations (Other Intermediate Production and Transport Workers, Farmers and Farm Managers, and Intermediate Production and Transport Workers n.f.d.) for immigrants from English-speaking countries that do no follow closely the pattern for the Australian born. Similarly, there are three occupations (Labourer and Related Workers n.f.d., Farmer and Farm Managers, and Secretaries and Personal Assistant) for immigrants from non-English-speaking countries where the earnings fixed effects diverge from the respective fixed effects for the Australian born. These occupations, however, are of relatively minor importance, accounting for less than five percent of the respective immigrant group’s employment. When the atypical occupations are removed from the analysis, these correlation coefficients rise to 0.904 and 0.898, respectively.

7 Status attainment models involve first characterizing occupations by a measure of “status,” and using this measure as the dependent variable in a linear regression. Nickell (1982) uses the mean earnings for each occupation. Evans (1987) uses a status attainment score. While status attainment scores are usually viewed as being more encompassing than mean occupational earnings (see Duncan, 1961), although they are based in part on earnings, which is a focus of this paper.

(a) These results are not presented here, as the information content is broadly the same as Table 4. The results are available from the authors upon request.


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