Restless minds: South African students and the brain drain

Figures & data

Table 1: 2002 final year South African tertiary population and sample

Type of student	2002 population	2002 population (per cent)	Unweighted 2003 sample (per cent)	Weighted 2003 sample (per cent)
Level of education
Undergraduate	97 285	62	62	59
Postgraduate	59 810	38	38	41
Total	157 095	100	100	100
Type of institution
University	100 118	64	63	63
Technikon	56 195	36	35	34
Nursing colleges	782	0.5	2	3
Total	157 095	100	100	100
Faculty
Commerce	42 500	27	35	26
Law	5750	4	3	3
Engineering	20 517	13	14	14
Science and technology	15 744	10	8	9
Humanities	19 820	13	8	12
Education	22 178	14	13	13
Health sciences	14 948	10	10	10
Management and IT	11 228	7	6	5
Medical/dentistry	1653	1	1	2
Theology	802	1	1	1
Architecture	1173	1	1	1
Nursing	782	0.5	2	3
Total	157 095	100	100	100
University background
Historically white	81 048	81	80	78
Historically black	19 070	19	20	22
Total	100 118	100	100	100
N			4784	2400
Note: Final-year student population data collected by authors from registrars.

Figure 1: Measuring emigration potential

Table 2: Statistics for emigration potential

	Mean (0–3 scale)	Standard deviation	Factor loading (structure matrix)
1. To what extent do you want to move to your MLD to live and work for a long period (longer than two years)?	1.67	1.10	0.79
2. How likely or unlikely is it that you would move to your MLD to live and work for a long period (two years or longer)?	1.47	1.08	0.77
3. How much consideration have you given to moving to another country to live and work?	1.82	1.10	0.49
4. How likely or unlikely is it that you would move from South Africa within five years after graduation?	1.34	1.10	0.38
5. How likely or unlikely is it that you would move from South Africa within two years after graduation?	1.32	1.03	0.35
N = 3907
Note: The unrotated factor has an eigenvalue of 2.37 and explains 47.3 per cent of common variance. Reliability (Cronbach's alpha)=0.72.

Figure 2: Emigration potential of final-year students and skilled adults

Figure 3: Most likely destination (all students)

Table 3: Most likely destination (by race) (%)

	Black	White	Coloured	Asian/Indian
Southern Africa	13	3	3	2
Elsewhere in Africa	1	< 1	0	0
Europe	46	44	50	32
North America	29	21	21	19
Australia/New Zealand	8	31	20	24
Asia	4	2	7	23
Total	100	100	100	100
Note: Totals may be more than 100% due to rounding.

Figure 4: Length of intended stay (by emigration potential)

Figure 5: Frequency of return and remittance (by emigration potential)

Figure 6: Willingness to give up assets in South Africa (by emigration potential)

Figure 7: Willingness to put down roots in new country (by emigration potential)

Figure 8: Emigration potential by race

Figure 9: Emigration potential by home language

Figure 10: Levels of patriotism and national identity among students

Table 4: OLS estimates of predictors of emigration potential

	r	B	SE	Beta	Adj. R^2 (Block)	Adj. R^2 (Cumul)
Constant		0.025	104
Social structure					0.000	0.000
National identity					0.078	0.078
Index of patriotism	− 0.258	− 0.093	0.015	− 0.098
National identity more important than quality of life	− 0.179	− 0.034	0.009	− 0.056
Economic evaluations					.152	0.198
Relative comparisons of family prospects	0.298	0.109	0.013	0.132
Believes emigrants do better	0.283	0.105	0.013	0.127
Believes emigrants skills optimised	0.189	0.136	0.021	0.095
Information and experience					0.059	0.223
International travel	0.099	0.067	0.021	0.047
Obtains information via internet	0.224	0.098	0.010	0.139
Logistics					0.209	0.308
Ease of leaving	0.249	0.070	.013	0.084
Family support	0.430	0.198	0.011	0.289
SE of estimate	.					0.6114
Adjusted R^2						0.308
Notes: All variables significant = / < 0.001.
N = 3386.
1. The dependent variable is the Index of Emigration Potential (an average score composed of six different indicators of emigration).
2. Ordinary least squares regression estimates.

Figure 11: Potential loss of state investments by type of bursary

Figure 12: Potential losses of state investments by course of study