levels. The evidence from Nepal suggests that education does have an effect
independent of family background and that increased productivity is related to
improvements in farmers numerical skills giving some clue as to why the observed
correlations exist.
A provocative study by Mingat and Tan (1988) suggests that Project Related Training
(PRT) yields high rates of return in both agricultural and non-agricultural development.
This study is based on an analysis of 115 World Bank projects taking the success of the
project, rather than direct measures of earnings, as a criteria. However, high returns are
concentrated heavily in countries where the general educational base is well
established. Where illiteracy rates are high and educational participation rates are low
PRT does not appear to be an effective investment. This may arise both because
individuals with low levels of formal education are handicapped in absorbing training
inputs and because countries where educational infra-structure is weak may also be
those where management capacity is least developed and organisational capabilities are
most limited. In countries where more than half the population are literate rates of
return for PRT are more strongly positive for agricultural rather than non-agricultural
projects. This may be the result of diminishing returns to training (nonagricultural
projects tended to have more than four times as much training associated with them)
and because agricultural projects tend to have greater dependence on people and skills
and less on capital than many nonagricultural projects (Mingat and Tan 1988:238). The
conclusions of this work argue that changes are need in PRT where its effectiveness
appear very low for reasons associated with poor infrastructure and low educational
endowments in the population as a whole. In these conditions institution building and
support for improvements in basic education are a priority. Under other circumstances
PRT appears very cost effective.
Studies of productivity in urban areas and in industry are much more common in
developed countries than in developing countries. Much of this literature has addressed
the debate between human capital proponents (who argue that education increases
productivity which is rewarded by higher earnings) and screening theorists (who
attribute the higher earnings of the more educated to factors other than the cognitive
changes which are associated with studying to higher educational levels). The evidence
does not conclusively favour one or the other approach (Winkler 1987:287). Part of the
reason lies in the difficulty of measuring the dependent variable - productivity. If
simple output measures are not available e.g. piecework production under standardised
conditions, comparison is difficult between workers with different educational levels.
Supervisor and peer group ratings can be used though these may not have high
reliability. Comparison between jobs with different characteristics is problematic - the
relative productivity of lawyers and plumbers cannot simply be assumed to be reflected
in their earnings for a long list of reasons. And in any case the occupational mobility of
urban workers is often high, resulting in situations where additional educational inputs
may be reflected in increased productivity in subsequent not current jobs.