accumulation and economic growth, by influencing retirement decisions<sup>8</sup> and therefore labor force participation rates for individuals with different skill levels.<sup>9</sup> _The model – from skill formation to human capital_ The model developed here projects the labor force by gender, age and education level. Assuming a competitive environment we characterize the human capital of individuals with the marginal product of their labor, an equivalent value to their wages if they are employed. These are approximated by standard wage functions which we describe in the next section.<sup>10</sup> Clearly this definition of human capital may be counterintuitive to some as total human capital, a stock accumulated through a long period, is practically represented by the total wage bill under full employment of the labor force, i.e. the share of economic output attributable to labor effort during a year, a short period compared to the overall timeframe of human capital accumulation.

The fist step is to project the total population by age and gender on the basis of expectations about future fertility and mortality rates. Hence a vector Pop(g,a,t) is computed where g=1 if male and g=2 if female, ‘a’ refers to age and ‘t’ refers to the time period.

The next step is to project the supply of skills by the education sector. This supply is characterized by the vector Skill(s,g,a,e,t) where s=1 refers to “enrolled in an institution of the education system”, s=2 refers to those who are “not enrolled in the system of education”, while e<sup>∈</sup> {no education, 1st year of primary education, 2nd year of primary education, ...} is an element of the complete set of educational attainment categories. A particular type of school constitutes as many distinct educational attainment categories as many years are necessary to successfully complete its curriculum.

Entry to primary education is projected as follows: _Skill_ ( _s_ = ,1 _g_ , _a_ = ,6 _e_ = _P_ ,1 _t_ ) = _Pop_ ( _g_ , _a_ = ,6 _t_ ) * _SR_ ( _g_ , _a_ = ,6 _t_ ) _Skill_ ( _s_ = ,2 _g_ , _a_ = ,6 _e_ = _NoEd_ , _t_ ) = _Pop_ ( _g_ , _a_ = ,6 _t_ ) * [ 1 − _SR_ ( _g_ , _a_ = ,6 _t_ ) ] , (5) where SR(g, a=6, t) is the scholarization rate at the mandatory primary education entry age. (P1 refers to “1st year of primary education”, NoEd refers to “no education”.) Those who do not enter primary education are registered as “out of school” population without education.

> 8  The model could be used as well to assess the economic impact of the effect of the pension system on the age of entrance to the formal labor market.

> 9 In this paper the term human capital is used for the human capital actually offered for work, i.e. the human capital stock does not include the potentially highly productive, but inactive population.

> 10 The empirical analysis of the household survey presented in the following section includes the economic sector in the set of explanatory variables in determining wages. Since the labor force projection does not have a sector dimension the specification of the wage equation is somewhat simplified here, i.e. it omits economic sector from the set of right hand side variables.

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