GENDER AND ETHNO-RACIAL INEQUALITIES IN LABOR MARKET OUTCOMES AMONG THE SECOND GENERATION IN TORONTO

Transcription

1 GENDER AND ETHNO-RACIAL INEQUALITIES IN LABOR MARKET OUTCOMES AMONG THE SECOND GENERATION IN TORONTO Brian Ray, University of Ottawa Valerie Preston, York University We gratefully acknowledge funding from SSHRC and York University and access to the data through COOL RDC and the York RDC.

2 Second Generation Theories Straight-line assimilation Social mobility occurs across generations due to changes in: Language proficiency Education Social networks Acculturation Associated with spatial assimilation Segmented assimilation Upward & downward Depends on: Resources and culture of immigrant parents Social capital of ethno-racial group Segregation & neighbourhood effects New second generation Racialised hierarchy of 2 nd generation success

3 PURPOSE Investigate how race and gender influence the labour market experiences of 2 nd generation adults Empirical study of Toronto CMA Document occupational, industry, and earnings differences within 2 nd generation due to: Ethno-racial background Sex Compare how social characteristics affect earnings across ethno-racial groups of 2 nd generation disaggregated by gender

4 Second Generation in Canada Mainly Europeans, 30% racial minorities Doing better than their parents Doing better than 3+ generation On all indicators (education, occupation, income) BUT Racial minorities have earnings gap Racial minorities are alienated Racial minorities experience discrimination Gender differences considered rarely Place matters thevarsity.ca

5 Place Matters: Toronto CMA Large urban region (approximately 5.9 million) Approximately 78% 1st and 2 nd generation Racially and ethnically diverse urban region Diverse and large job market

6 Caveats about the analysis Only the 2 nd generation At least one foreign-born parent or came to Canada before age 13 Examining only one age cohort: years old Separate analysis for women and men Five ethno-racial groups Black, Chinese, South Asian, Southern European, N/W European Analysis of National Household Survey, 2011 Presentation focuses on occupation & industry, but we have investigated educational attainment

7 Labor force participation & unemployment rates Very few differences in labor force participation between groups: 84.9% % Black & Chinese women 86.1% % Black & Southern European men Unemployment rates Lowest: S. European men ~ 5.0% Highest: Black men ~ 10.4%

8 Leading occupations of employment Women Men In most occupations, men under-represented All groups in senior management underrepresented relative to W. Europeans

9 Median employment earnings for women & men Black Chinese South Asian Southern European N/W European Total Visible Minority Non- Visible Minority Women - Men Income Ratio

10 Earnings for women by occupation and ethno-racial group Median employment earnings compared to white West/North European women Lower earnings in most occupations for most groups Higher earnings only in Intermediate Sales & Service Incomes relatively on par in Professional occupations except for Blacks Black Chinese South Southern Asian European Non Vis Min Vis Min Total Senior & specialized middle managers -13.9% -5.9% -22.1% -10.1% -5.9% -16.2% -10.0% Professional -6.0% 1.6% -0.7% 2.4% -1.4% -7.8% -4.5% Administrators & senior clerical -9.3% -7.2% -2.7% -3.0% -3.1% -9.3% -5.8% Technical occup. & semi-professionals -5.1% 6.5% 8.1% 1.1% -1.5% -11.3% -7.1% Intermediate sales & service 12.5% 3.0% 12.2% 23.9% 7.0% -7.3% -0.3%

11 Earnings for men by occupation and ethno-racial group Median employment earnings compared to white West/North European men Lower earnings for men except some Southern Europeans Biggest differences in earnings for Black men Earnings gap is lower for professional occupations Black Chinese South Southern Asian European Non Vis Min Vis Min Total Senior & specialized middle managers -32.1% -11.3% -15.0% -8.9% -4.4% -18.4% -10.6% Middle managers -26.7% -32.6% -13.5% -10.9% -8.2% -26.5% -13.3% Professional -26.6% -4.2% -7.7% 1.0% -0.6% -9.2% -5.0% Technical occup. & semi-professionals -28.5% -17.4% -15.6% -4.0% -3.0% -19.2% -10.2% Skilled crafts & trades -32.8% -34.0% -22.2% 0.0% -0.9% -24.3% -7.9% Intermediate sales & service -22.0% -26.0% -23.2% 11.9% 2.3% -23.8% -12.3%

12 Differences in employment income, Women vs Men Median employment income Lower earnings for women Earnings differences especially marked among N/W Europeans Gender differences less marked among Black individuals Ratio: Female-Male Median Employment Income South N/W Southern Nonvisible Visible Black Chinese Asian Europeans Europeans Others Total minority minority Senior & specialized middle managers Middle managers Professional Administrators & senior clerical Technical occup. & semi-professionals Intermediate sales & service Total

13 WOMEN β Standard error t value Age Groups ** ** ** Marital Status Single *** Seperated, Divorced, Widowed Married & Common Law Household Type Married/Common-lw w'out children *** Lone Parent Non-Family Alone *** Non-Family Other Married/Common-lw with children Highest Level of Educational Attainment Less than high school *** High School *** Post-secondary training *** Bachelor's degree *** Professional degree, Master's, PhD Ethno-racial identity Black ** Chinese ** South Asian Southern European * Other Northern/Western European Mother Tongue Other ** English or French Employment status Part-time Full-time Regression Analysis (Women), Employment earnings Lower earnings for younger Lower earnings for singles Married without children increases earnings Living alone increases earnings Lower levels of education have strongly negative influence on earnings Ethno-racial status: Black lowers earnings Chinese & Southern European modestly increases earnings Non-official language mother tongue has a negative influence Constant N (unweighted) 44,085 N (weighted) 227,145 Part-time employment lowers earnings F statistic R-sq *** = p > ** = p > * = p > 0.05

14 MEN β Standard error t value Age Groups *** *** *** 40 Similar - 44 effects women & men: Age Marital Status Single *** Seperated, Education Divorced, Widowed *** Married & Common Law Employment status Mother tongue Household Type Married/Common-lw w'out children *** Lone Parent * Black racial status Non-Family Alone *** Non-Family Other * Married/Common-lw with children Highest Level of Educational Attainment Less than high school *** High School *** Post-secondary training *** Bachelor's degree *** Professional degree, Master's, PhD Ethno-racial identity Black *** Chinese South Asian * Southern Household European type * Other * Northern/Western European Different effects women & men: Marital status South Asian and Other status associated with lower incomes for me Mother Tongue Other ** English or French Employment status Part-time ** Full-time Constant N (unweighted) 45,900 N (weighted) F statistic R-sq *** = p > ** = p > * = p > 0.05 Employment earnings for Men: Demographic effects Lower earnings for younger Lower earnings for singles, not married Lower earnings for separated, divorced Married without children lowers earnings Lone parent lowers earnings Living alone increases earnings Living non-family (other) increases earnings Lower levels of education have strongly negative influence on earnings Ethno-racial status: Black, South Asian, & Other significantly lowers earnings Southern European modestly increases earnings Non-official language mother tongue has a negative influence Part-time employment lowers earnings

15 WOMEN β Standard error t value Age Groups *** *** *** Marital Status Single Seperated, Divorced, Widowed Married & Common Law Household Type Married/Common-law w'out children *** Lone Parent Non-Family Alone *** Non-Family Other Married/Common-lw with children Highest Level of Educational Attainment Less than high school *** High School *** Post-secondary training *** Bachelor's degree *** Professional degree, Master's, PhD Ethno-racial identity Black ** Chinese South Asian Southern European Other Northern/Western European Mother Tongue Other ** English or French Employment status Part-time *** Full-time Regression Analysis (Women), including Occupation & Industry in relation to Employment earnings Occupations Senior & specialized middle manage *** Middle managers *** Supervisors *** Administrators & senior clerical *** Clerical & office support (semi-skilled) *** Technical & semi-professionals *** Skilled crafts & trades ** Semi-skilled manual *** Other manual *** Skilled sales & service *** Inter. sales & service *** Other sales & service *** Professional Industry of employment Primary & utilities *** Construction Manufacturing Transport & warehousing Wholesaling *** Retailing *** Information & culture FIRE & Management *** Admin. & support, waste man. services *** Education *** Health & social assistance Arts, entertain. & recreation *** Accommodation & food *** Other services (except public admin) *** Public administration *** Professional, science & technical Constant N (unweighted) 43,950 N (weighted) 226,420 F statistic R-sq *** = p > ** = p > * = p > 0.05 Although magnitude changes, demographic effects remain & are consistent Several occupations & industries have significant influence on earnings Industry less influential However, cultural characteristics remain important: Black Mother tongue

16 MEN β Standard error t value Age Groups *** *** *** Marital Status Single *** Seperated, Divorced, Widowed *** Married & Common Law Household Type Married/Common-law w'out children *** Lone Parent Non-Family Alone *** Non-Family Other * Married/Common-lw with children Highest Level of Educational Attainment Less than high school *** High School *** Post-secondary training *** Bachelor's degree *** Professional degree, Master's, PhD Ethno-racial identity Black *** Chinese * South Asian ** Southern European *** Other * Northern/Western European Mother Tongue Other *** English or French Employment status Part-time *** Full-time Regression Analysis (Men), including Occupation & Industry in relation to Employment earnings Occupations Senior & specialized middle manage *** Middle managers ** Supervisors *** Administrators & senior clerical *** Clerical & office support (semi-skilled) *** Technical & semi-professionals *** Skilled crafts & trades *** Semi-skilled manual *** Other manual *** Skilled sales & service *** Inter. sales & service *** Other sales & service *** Professional Industry of employment Primary & utilities *** Construction * Manufacturing Transport & warehousing Wholesaling *** Retailing ** Information & culture FIRE & Management *** Admin. & support, waste man. services *** Education *** Health & social assistance Arts, entertain. & recreation *** Accommodation & food *** Other services (except public admin) *** Public administration *** Professional, science & technical Constant N (unweighted) 45,770 N (weighted) 240,935 F statistic R-sq *** = p > ** = p > * = p > 0.05 Most demographic effects remain & are consistent Lone parent effect no longer significant Occupation & industry effects similar to those for women Significantly lower earnings for those in low-skill services, manual occup s, & clerical jobs Cultural effects Significantly lower incomes for Blacks, Chinese, South Asians & Others Earnings higher only for Southern Europeans Mother tongue

17 Second Generation Lessons Diverse experiences between Ethnoracial groups Men and women Gender and ethnoracial group affect earnings Even for people with similar occupations Examine role of discrimination in disparate employment outcomes Address discrimination through active enforcement Economic restructuring matters Alters occupations and industries