Coming to Terms with Reality. Evaluation of the Belgian Debt Relief ...

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Annexes
the funds generated by HIPC debt forgiveness and set apart for projects administered by the
Comité Consultatif et de Suivi, but also for the general investment budget. Only the C2D
program, set up with the French Development Cooperation, seems on its way to perform
better. On the other hand private investment as a percentage of GDP had strongly increased
between 2000 and 2001, but thereafter it gradually decreased, from 18.1% in 2001 to 14.5%
in 2007. So if reaching the Decision Point had initially favorably affected the expectations of
investors, either because they expected a positive effect on public finance or because they
hoped for policy improvements, that effect was not sustained. As mentioned in subsection 5.7
there are a number of explanations for the rather weak private investments, including
deficient transport infrastructure, problems with electricity supply, and weak governance.
Summarizing, the available data do not allow us to pinpoint what exactly were the main
causes of Cameroon’s weak growth performance after the country reached the HIPC
Decision Point. We cannot exclude that the debt forgives starting in the year 2000 and the
expectation of more substantial debt forgiveness after reaching the Completion Point have
had a positive effect on economic growth, since we are not sure what would have
happened if the debt forgiveness under the HIPC Initiative had not taken place. But if there
was an effect, it has been swamped by other, negatively impacting decisions and events.
We cannot be exclude that new data will show that the debt cancellation upon reaching the
Completion Point has had a positive impact on growth performance. The effects of the debt
cancellation may take time to realize. We can only observe that the growth rate of GDP in
2007 was in line with the relatively low figures of the immediately preceding years.
6.2 Impact on poverty
We first discuss the possible impact of debt forgiveness on poverty by considering the
headcount ratio. We then analyze changes in a four social indicators linked to poverty;
these indicators belong to the fields of health and education.
6.2.1 Poverty headcount
The sources of information on poverty are the household surveys of 1996, 2001 and 2007,
implemented by the National Institute of Statistics (NIS). The survey of 1996 covered
1700 households, whereas those of 2001 and 2007 covered more than 10,000 households.
The first survey is therefore likely to imply larger margins of error than the later ones. A
national poverty line was computed by the NIS by considering food and non-food
expenditure; it was updated for inflation. In 2007 the poverty line was 738 FCFA (1.13 €)
per person per day.
The data in table 9 suggest that between 2001 and 2007 the percentage of people below the
poverty line has not substantially changed. This is in sharp contrast to the period 1996-
2001, when the overall poverty rate strongly decreased. This must have been the case even
if we take into account the larger margin of error in the 1996 survey. The decline of
poverty between 1996 and 2001 was observed both in urban and in rural areas, but it was
Coming to Terms with Reality
strongest in urban areas where the percentage of poor people in the population decreased
by more than half. After 2001 poverty continued to decline in urban areas, with a strong
decline in the two main cities, Douala and Yaoundé. But in rural areas the percentage of
poor people living in poor households did increase.
Table 9 Evolution of population under the poverty line (percentage of people living in
households with average income below the poverty line in total population):
1996 2001 2007
Global 53.3 40.2 39.9
Rural 59.6 52.1 55.0
Urban 41.4 17.9 12.2
Source: NIS (2008)
These observations are in line with our remarks on economic growth in the previous
subsection. Whereas over the period 1994-2000 the growth of value added in agriculture
was rather high, it was much lower after 2000. On the other hand after 2001 we observe a
strong growth of the service sector. Agricultural growth is of course linked to the evolution
of income in rural areas, whereas the service sector can be expected to have a stronger
impact on urban areas. More detailed figures suggest that especially households in the two
main cities, Douala and Yaoundé, did profit from the growth of the service sector.
Summarizing, the data do not provide indications that the debt alleviation resulting from the
HIPC and MDRI has reduced poverty. Apart from a lower overall growth rate, the nature of
economic growth after 2001 seems to have caused an increase in poverty incidence in rural
areas. We should again remark that we cannot exclude that in the absence of debt alleviation
poverty may have remained even more widespread than we observe in the data.
6.2.2 Social indicators
To study the evolution of welfare and of poverty, it is also interesting to consider the changes
in a number of social indicators. There is a long list of such indicators. In this subsection we
limit our analysis to four indicators, two in the field of health and two in the education sector.
We start with infant and child mortality. Data on this indicator are provided by the
Demographic and Health Surveys implemented by the National Institute of Statistics in the
years 1991, 1998 and 2004. The last survey may have been too early to register fully
possible improvements linked to HIPC debt alleviation.
Table 10 Infant and Child Mortality (deaths per thousand):
1990-1994 1995-1999 2000-2004
Infant mortality (birth to age one) 80 89 74
Child mortality (birth to age five) 133 152 144
Source : NIS (2004), table 11.1
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