Abstract
The over-representation of certain ethnic minority and immigrant groups in self-employment is, in common with other developed countries, a notable feature of the UK labour market. Compared to the substantial growth in self-employment in the 1980s, the 1990s saw overall self-employment rates plateau. Despite this, some minority groups experienced continued growth whilst others, particularly Chinese and Indian males and Pakistani, Bangladeshi and Chinese females, saw their self-employment rates decline. In this paper we use microdata samples from the 1991 and 2001 Censuses to investigate the dynamic and spatial patterns of ethnic entrepreneurship. Using decomposition methods we find that, for males from the Asian groups, changes in observable characteristics associated with an increasing proportion of second-generation individuals explain much of the decline in self-employment. This, which is also true of Chinese females, reflects in part the age structure and educational experiences of the second generation. The dynamics of Black male and Pakistani/Bangladeshi male and female entrepreneurship are less easy to explain. We also find that, while there is no evidence of self-employment being an “enclave” phenomenon, local economic conditions do affect rates of entrepreneurship for some groups, notably Pakistanis and Bangladeshis.
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Notes
See Platt et al. (2005) and ONS (2006) for justification for using these groups. Clark and Drinkwater (2005) provide more detail on the issues involved in matching the data between the two Census data sets and deriving the relevant variables. Note that we also consider only Great Britain in what follows as the Census collected different ethnicity information from Northern Ireland than in the rest of the UK.
Borooah and Hart (1999) also use SARs data to examine the factors affecting the low self-employment rates of Black Caribbean males relative to Indians. Interestingly, Fairlie (2004) finds that Asian males have similar self-employment rates to Whites in the US, with Blacks experiencing far lower self-employment rates, whilst for females, Asians have higher self-employment rates than Whites, and very low rates are observed for Blacks.
One potential caveat here is that entrepreneurship is often a family activity, and women (and indeed children) may play an important role in the operation of small firms which are “owned” by their male relative. See Metcalf, Modood and Virdee (1996) for a discussion of this in the context of the UK’s Asian population.
The nature of the work undertaken by entrepreneurs can be another source of ethnic diversity. Clark and Drinkwater (2006) analyse ethnic differences in hours of work and industrial sector for the self-employed and find no large changes in the relative ethnic positions between 1991 and 2001. Similarly, although ethnic variations are observed in the types of industry where the self-employed are located, the relative situation was similar in 2001 to that observed in 1991. In particular, although there is some evidence that the degree of concentration within particular sectors was reduced slightly between 1991 and 2001, this was by no means a steep decline, with Pakistani, Bangladeshi and Chinese males still concentrated within sectors such as restaurants, taxi-driving and retail.
See Fairlie (2005) for an alternative decomposition technique for logit and probit models.
In this paper we report results based on probit models. We have also estimated the models using a semi-nonparametric estimator (Gallant and Nychka 1987; Stewart 2004) and a linear probability model. The results, available on request, suggest that the magnitudes of the decomposition components are extremely similar across alternative estimators.
In fact there are some slight discrepancies in these changes over time compared to Table 1. This is due to the regression sample being slightly different to that used to compute the descriptive statistics.
An alternative method of decomposing the characteristics component into its constituent parts is proposed in Fairlie (2005). Unlike Even and McPherson’s method, which is based on a linear approximation, Fairlie’s approach is sensitive to a matching protocol used to match observations across the two samples being compared, and also to the order in which explanatory variables are listed in the regression. In the absence of compelling simulation evidence in the literature which compares the two methods, we experimented with both approaches and found that of Even and McPherson to be more appropriate in the current application.
See the ODPM (2005) for details of how the IMD has been constructed.
The Department of Trade and Industry’s targets or Public Service Agreement requirements are described at http://www.dti.gov.uk.
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Acknowledgements
We are grateful to David Blackaby, Angela Dale, Derek Leslie, Kathleen Kelly and Ludi Simpson for comments on an earlier draft of this paper, to two anonymous referees and to the Joseph Rowntree Foundation for financial support. Thanks are also due to participants at the 2nd IZA Migrant Ethnicity Meeting held in Bonn in May 2006, the SARS User Group, November 2006, and the WPEG Ethnicity workshop in February 2007. The support of the ONS, CCSR and ESRC/JISC Census of Population Programme is gratefully acknowledged. Census output is Crown copyright and is reproduced with the permission of the Controller of HMSO. The authors alone are responsible for the interpretation of the data.
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Clark, K., Drinkwater, S. Patterns of ethnic self-employment in time and space: evidence from British Census microdata. Small Bus Econ 34, 323–338 (2010). https://doi.org/10.1007/s11187-008-9122-1
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DOI: https://doi.org/10.1007/s11187-008-9122-1