Summary & conclusions 1 On the model

1.The model performed well in the actual Sri Lankan situation as a tool to assist in the upgrading of skills (data analysis, micro-computer processing, presentation of results to management) of Sri Lankan social scientists engaged in human resource analytical issues. The model continues to be used in Sri Lanka for baseline projections and to assist in data consistency checks.

2. The model can provide insights into labour market analysis. It goes much further than a traditional

"manpower requirements" approach but, in its reduced form (i.e. without using the labour flexibility option), can imitate the manpower requirements approach and this is useful in providing baseline projections of manpower.

3. A number of policy issues of crucial concern to Sri Lanka may be examined with the model. This could be further enhanced through increasing its flexibility in a number of areas. Three main areas where improvements would be useful are:

a.Parameter changes. The model currently allows changes in a number of parameters that then impact on the major dynamics of the model. These can be entered in the base year and changed again after 10 years. Nevertheless, it would be desirable to be able to intervene in intermediate years as well even at the risk of complicating data entry into the model. This would then, for example, allow stochastic variables to be entered such as interruptions in agriculture production because of drought that occurs randomly in Sri Lanka but has short term devastating effects. The following variables need to be amenable to change in this way:

total fertility rate, life expectancy, international migration, school repetition rates, school dropout rates, investment ratio over GDP, economic growth rates by economic sector, and the retirement of the labour force by education level.

b.Model changes. Three areas of possible improvements were considered - including an input-output structure, better specification of labour demand in the labour market and including wages. None of these changes present simple adaptations of the model. An input

output structure could help in examining indirect effects of investment but would considerably complicate the model. It was thought better to introduce investment changes that had already taken account of indirect effects (see the description of the scenario where investment was changed). Second, although the current labour market specification is simple it can allow behavioural labour market mechanisms to be introduced through changes in exogenous inputs. On the other hand, not enough is known about labour market mechanisms in Sri Lanka to provide new model specifications and new research is required that examines the different labour market segments to increase understanding of the complexities involved.

Third, wages are already included in the model, or rather relative wages since prices are exogenous to the model to give signals to labour movements between occupation levels and skills. This option was not used in the Sri Lanka application because of the problems of data.

If one could estimate the elasticity of response of wages with respect to the labour balance between different workers with different educational levels changes., this would enhance the interest of the model. However, wage data is not available in Sri Lanka to allow this to be done.

c.Scenario analysis. The exogenous changes introduced for each of the six scenarios presented were introduced on a "back of the envelope" basis. It would be desirable to put more work into alternative future scenario paths. For example, scenario 4 simulated a "NIC"

expansion path. The coefficients for investment, growth, education, technology etc. were guessed. However, data exist for these parameters for NIC and nearly NIC countries such as South Korea, Taiwan, Singapore, Hong Kong, Thailand and Malaysia. Some further research is required to obtain these coefficients which could then be relayed into a vastly improved

"NIC" scenario and re-run through the model.

7.2 On the economy

There is not much that can be said about training and occupation mismatches because the aggregation of data available from censuses and surveys are inappropriate, even to the extent of being useless for manpower analysis purposes. It would be desirable to have a data base that measured the skill level of workers that not only took into account their education, length of time working and occupation but also their quality. In the meantime it would be useful to re-calibrate the model with occupational classifications that identified critical skills or, if that concept proves to be elusive, something that can allow Sri Lanka to measure and develop its "comparative advantage" in human resources.

There are major inconsistencies between available education data and the labour force. The numbers in school and leaving to join the labour force, as implied by Ministry of Education data (for school attendance, dropout, repetition and graduation rates) are inconsistent with the changing pattern of the labour force by level of education. It was not possible to judge whether the fault lay in the education or the labour force data. The inescapable conclusion is that the education statistics are incompatible with the labour force statistics. Clearly, consistency checks of flows of educated people by age and grade out of the education system are not matched with flows into the labour pool and labour force.

Population growth rate uncertainties (i.e. will it be higher or lower than trend) make very little difference to unemployment by the year 2000 simply because the newly born take up to 15 years to enter the labour force and with the gradually increasing length of education in Sri Lanka this period will be even longer than before.

Changing the pattern of investment away from agriculture toward more capital intensive sectors like

manufacturing increases unemployment.

The high growth scenario aimed at, at that time, by the Government, will reduce unemployment but not totally eliminate it because a)there is a mismatch between type of educated supply and demand, b) new investment, although assumed more productive, is capital intensive in nature. It may well be, and further experimentation within this scenario could explore these limits, that there will be shortages of skilled labour and not unskilled labour if the Government's high growth strategy succeeds.

A worse case scenario whereby the Government's high growth strategy fails could lead to unemployment rates of the order of 19.3% by the year 2000 compared with the trend (in the base scenario) of 9.9%.

The comparison between ‘actual’ values of some key variables and the base scenario forecasts for the year 2000 showed mixed results. The demographic projections were excellent but the economic forecasts were too optimistic in terms of economic growth. The results do not question the validity of the model as much as its political context – a forecasting exercise is best done by an independent group that is allowed by the Government to have access to available data.

Chapter VI: Labour Market Signalling through Survey Analysis – an Alternative