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Moving forward in Zimbabwe Reducing poverty and promoting growth Figure 2.4: Extrapolated migration statistics to South Africa. Source: Makina, 2007. The problem of unemployment Unemployment has been a problem in the economy since independence. The rate reported for the 1980s is 11.6 per cent. It increased during the structural adjustment period to reach a peak of 21.8 per cent in 1992 before decreasing to 6 per cent in 1999 (CSO, 2004). The 1992 peak was partly a result of the drought that year. According to the 1999 labour force survey, unemployment in Harare and Bulawayo was 13 per cent and 14 per cent, and the average for other provinces ranged between 1 and 3 per cent, including communal farmers. Harare and Bulawayo are industrial satellites that attract labour from the rest of the country, and company closures due to economic crisis contributed to the concentration of unemployment. According to the most recent labour force survey, the unemployment rate for 2004 was 9 per cent (CSO, 2006a). Considering that economic reforms failed to stimulate significant employment growth, and that recession started from 1998, including that youth unemployment increased in the 1990s (Kanyenze, 1997), it is apparent that the 2004 unemployment statistic was a gross underestimation of the problem. Actually, the figure shows that there is something fundamentally wrong with the way unemployment is measured. The data collection process seems to be missing critical issues about unemployment and hence is disguising the problem. For this reason, unemployment figures in Zimbabwe are contestable, as shown by the summary of the sources and statistics in Table 2.5. The table shows that unemployment increased between 1986 and 1993. Thereafter different sources reported different rates. Under such circumstances, it may appear reasonable to give more credence to CSO figures as Potts (2000) stated, because it is the national institution mandated with data collection and compilation. However, as discussed below, use of the strict definition of unemployment biases the statistics downwards thereby grossly underestimating it. It is incredible that after economic contraction of over 40 per cent in successive years from 1998, the CSO published an unemployment rate of 9 per cent for 2004 (CSO, 2006a). This casts doubt over the reliability and hence usefulness of its previous statistics. However, it should be noted that there is no question about the accuracy of formal employment figures that are collected using an appropriate methodology. Notwithstanding this, one can conjecture that on the basis of employment dynamics examined above, unemployment increased in 1992, 1995 and from 1998 onwards at the very least. Generally unemployment statistics for developing countries are unreliable. In some countries, the statistics are scarce because of the high cost of collection. In others, the statistics are unreliable because they are ‘massaged’ to present a good image in order to protect politicians against a possible political backlash. Both these conditions hold for Zimbabwe, especially from 2000. 7 The controversies surrounding the statistics make their reliability Table 2.5: Unemployment estimates. Year Source Unemployment estimates Definition used and reference period 1986 Central Statistical Office 11.6% Strict, 7 days 1990 1991 Ministry of Public Service, Labour and Social Welfare Government of Zimbabwe, Framework for Economic Reform 37.2% 1993 Rakodi (1994) 40% 1993 Ministry of Public Service, Labour and Social Welfare 26-37% Strict 44% 1993 Central Statistical Office (1994) 7.9% national; 2.4% rural; 15.9% urban Strict, 7 days 1996 Economic Intelligence Unit (1996) 50% 1996 US Department of State >45% 1996 Ministry of Public Service, Labour and Social Welfare annual report 22.4% in 1994 including unpaid family workers 1997 Kanyenze (1997) 35-50% total, of which 62% were youths 1999 Central Statistical Office (2000) 6% national; 1.4% rural; 15.5% urban Strict, 7 days 2004 Central Statistical Office (2006) 9% national Strict, 7 days 2005 US Department of State 80% 2006 Kanyenze (2006) Over 70% 2008 Bird and Prowse (2008) Over 80% Source: Adapted from Potts (2000) and modified using Indicator Monitoring – Labour Force Surveys for 1999 and 2004 and other sources. 28
Moving forward in Zimbabwe Reducing poverty and promoting growth The decline in numbers of professional and skilled workers is cause for concern given the importance of skilled labour in economic growth and development (Photo © Tsvangirayi Mukwazhi). doubtful. An example of such a controversy arose in 1999 when the Ministry of Labour estimated unemployment at 45 per cent while the CSO’s labour force survey reported unemployment of 6 per cent. At one point the Ministry of Finance also quoted unemployment figures well above the ones published by the CSO. This indicated that there was doubt even within government circles about the relevance of unemployment figures in relation to prevailing conditions. What really makes unemployment figures contestable is the definition used, which may result in counter-intuitive figures, as evidenced by the official statistics record of falling unemployment during economic recession. A closer look reveals that whatever statistics are published are dependent on the definition used. The CSO mainly uses the strict definition of unemployment which classifies a person as unemployed if he/she is aged 15 years or older and during the reference period was without work, was available for work, and was actively seeking employment. 8 This definition has two problematic issues: first, what constitutes work? Is it any economic activity that an individual engages in, or any form of paid activity? Using productive economic activity to define unemployment can be problematic because often people engage in many types of activities, some of them survivalist in nature, but would still prefer to be employed. Thus, using the strict definition, very few people will be officially regarded as unemployed. This is supported by Serneels (2004) and Krishnan et al (1998)’s assertion that unemployment in Africa may be restricted to wealthier households whose members can afford to stay away from any economic activity while looking for suitable employment. The important questions arising from this discussion are: how useful for policy are (African) unemployment statistics, even the ones based on a broader definition? When we look at the measurement of unemployment, some categories into which respondents are classified (own account worker and unpaid family worker) pose a serious problem in calculating unemployment statistics since they are likely to hide people who may otherwise be unemployed. Further, the condition that the respondent must have been seeking employment during the reference period can also be problematic, especially since job search is not necessarily a continuous process. This is particularly so in the rural sector where infrastructure is poor, production seasonal, and the dominant type of employment casual. In consequence, some unemployed persons may be wrongly classified as discouraged workers, especially if the reference period is short. For policy purposes, it may be useful to collect statistics of discouraged workers, but unfortunately these are not available. Distinguishing between unemployed and discouraged workers, short-term and long-term unemployed, and the level of unemployment using the strict and broad definitions over varying reference periods is a crucial approach that can generate appropriate data to shed more light into the state of the labour market. Suitable concepts that can indicate the hardships faced in the labour market are underemployment and whether or not existing jobs can be called decent work. As reported by the UN Economic Commission for Africa (UNECA) (2005), there are many people disguised as employed in the informal economy who are in fact under-employed, and are striving to make ends meet. Underemployment and decent work are complicated to measure. Decent work implies safe work in a healthy environment with guaranteed income and employment security, a concept very important for the improvement of conditions in the informal economy. Underemployment is defined as the proportion of employees working part-time – that is, those working for hours less than a given limit, usually less than 20 hours 29
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