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ABSTRACT
Analysing data from the 2006 Canadian census, the paper identifies various social characteristics that influence Bangladeshi immigrants’ employment status in Toronto, particularly their propensity to be self-employed and outside the paid labour force rather than paid employees. The analysis contributes to understanding why racialised immigrants take different paths to participating in the Canadian labour market. The results of regression analysis suggest that women are more likely to be out of the paid labour force and less likely to be self-employed or paid employees than their male counterparts. Young Bangladeshis with a university degree are least likely to withdraw from the paid labour force. Older Bangladeshis and those with longer length of residence in Canada are more likely to be self-employed. The likelihood of being out of the paid labour force increases as Bangladeshi immigrants age, and with less education and decreases for those with longer residence in Canada.
Acknowledgements
I am deeply thankful to Professor Valerie Preston, principal investigator of the partnership, for her constructive comments on the earlier versions of this paper. Her support and encouragement helped me improve the paper greatly.
Disclosure statement
No potential conflict of interest was reported by the author.
Notes on contributor
Marshia Akbar is a post-doctoral research fellow at York University in Toronto. She earned a doctorate degree in Geography from York University with a focus on migration and settlement. Her research broadly encompasses economic and social integration of South Asians in Canada.
Notes
1 In defined by the Employment Equity Act, as persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in color (Hou and Picot Citation2004, 1).
2 In 2011, the census was replaced by a voluntary survey, The National Household Survey (NHS), which has a global non-response rate of approximately 25 percent in the Toronto CMA. Due to concerns about the reliability of the data for specific social groups such as Bangladeshi immigrants, I used 2006 census data. These data were also available earlier than the 2011 NHS data.
3 A very small percentage (4.5%) of Bangladeshi born population who identified their ethnicity as European, African and West Asian were excluded from the analysis. Those who identify their ethnic identity as Bangladeshi, Bengali and East Indian are selected as Bangladeshi immigrants as these ethnic identities reflect the identities of Bangladeshis during pre-colonial, British colonial and post-colonial periods (Halder Citation2012).
4 The category ‘unpaid family workers’ does not include unpaid housework, childcare and senior care, and voluntary work.
5 The terms ‘not in the paid labour force’, ‘out of the paid labour force’, ‘non-participation in the paid labour force, and ‘withdrawal from the paid labour force’ are used synonymously in this study to indicate immigrants (aged 15 and over) who do not participate in the paid labour force.
6 The number of unpaid family workers among Bangladeshi immigrants did not comply with the data disclosure guidelines of the Research Data Centre at York University.
7 The comparative descriptive statistics included Bangladeshi, white and other visible minority immigrants aged 15 and over to focus on working age population.
8 Due to data confidentiality it was not possible to disaggregate the analysis among Bangladeshi immigrants by gender. Social factors may have different impacts on Bangladeshi men and women in shaping their engagement in businesses.
9 Educational attainment is grouped into three categories high school level/less education, college/University diploma and university degree. University degree represents a degree or certificate at the bachelor’s level or above.
10 Median income for census families after tax in 2005.
11 Total family income below the low income cut-offs after tax in 2005.
12 Odd ratios are based on a comparison of two probabilities by forming a ratio of the probabilities. If the probabilities are equal, the odds are 1.0. When the probabilities diverge, the odds diverge from 1.0. (Ray and Preston Citation2009, 224). For example, an odds ratio of 1.0 indicates that two groups such as, females and males have the same odds of engaging in self-employment. An odds ratio of 0.51 means that the probability of group A (e.g. females) to be engaged in self-employment is one half of the probability of the reference group (e.g. males).
13 In Ontario a child must be 6 years old to attend school, they can begin full day kindergarten program at 4.
14 Other types of housing include semi-detached or double house, row house, other single-attached house, mobile house and other mobile dwelling.