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The
theoretical framework of this study is based on the Theory of the Allocation of
Time1
which has various approaches such as the changes in hours and leisure. This
theory is an augmentation of utility maximization in consumer theory in which
includes the cost of time and the cost of market goods on the same established
position.

Following
the paper of Becker (1965), the individual’s utility function while developing
this theory is similar with this equation:

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U=
f(C, L).                                                                                          (1)

According
to the basic model of utility maximization, individuals want to optimize their
utility (U) by consumption of goods (C) in the marketplace and spending time
for leisure activities (L). Furthermore, C and L are both economic goods, thus,
whatever economic measures they correspond to, we conclude more of any
particular good is preferred to less. In order to maximize the utility, the
individual is bound by two constraints. The first constraint is  the availability of time which is day’s time
and the second one is the purchase of consumption of goods by working
(Nicholson, 2005).2

Time
constraint could be written as follows:

L
+ H=T                                                                                              (2)

An
individual must allocate his/her time (T) per given day either for working with
pay (H) or to leisure (L).

For
income constraint:

(W*H)
+ V = C                                                                                   (3)

This
condition is related to the income that an individual needs to purchase goods
and services in the marketplace. The individual’s income are the sum of his/her
the wage rate (W*H) and non-labor incomes (V).
This equation implies that the individual consumption expenditures is
equal to the total income. We can rewrite equations (2) and (3) as follows:

W(T-L)
+ V = C                                                                                 (4)

The
invidual’s utility maximization problem becomes:

Max
U (C,L) subject to C = W(T-L) + V                                           (5)

The
first order conditions solution yield the following equations:

MaxUC=

(6)

MaxUL=

W                                                                                        (7)

Hence,
the following principle was derived:

W=
MRS (UL
for UC)                                                                         (8)

In
order to maximize utility, given the real wage (W) the individual should select
to work that number of hours for which the marginal rate of substitution of
leisure for consumption is equal to real wage (Nicholson,
2005)
.

Moreover,
based on consumer theory, Ackah et al (2009)3
argue that,  if an individual maximizes
his/her utility (U) function for consumption of items (C) and leisure (L), the
model can be expressed as

U= U (C, L, X)                                                                                   (9)

where
X, distinguishes the individual and household attributes such as age, marital
status, ethinicity etc. This utility maximisation is subject to income and time
constraints:

C
+WL=Y +WT ,                                                                                (10)

where
W is the wage rate, Y is non-labor income and T is the the total time
available. We can also rewrite this as in equation (4),

W(T-L)
+ V = C,                                                                                (11)

The
solutions for maximization problem derived the following equation which are
familiar in the first order conditions,

Uc
(WH + V, T-H, X) =

Ul
(WH + V, T-H, X)?

(12)

where
? is the marginal utility of income. Equation (12) involves the demand function
for the consumption of  commodities, and
the topmost allocation of time between leisure and market activities. According
to Ackah et al (2009), if the inequality in equation (12) holds strictly, then
the individual is not participating in the labor market and L=T. The wage Wr,
such that Ul (WH + V, T-H,  X)?

is the reservation wage below in which an individual will not likely to
join the labor force. In other words, if the expected market wage is greater
than the reservation wage, the individual is likely to participate in the labor
market.

Data and Proposed Methdology

In
our efforts to determine the factors that influence the labor force
participation among TVET graduates, we will use survey data from Technical
Education and Skills Development Authority (TESDA) and secondary data from
Philippine Statistics Authority (PSA). We will evaluate the socio-economic and
demographic profiles of graduates from the  cross-sectional data of 2014 Study on the Employability of TVET Graduates. This national
survey data has an estimated of 10,000 TVET graduates in 2013. Furthermore, to
enrich our analyses, we will also use the secondary data from PSA, pertaining
to data of regional measures such as Regional Gross Domestic Product Per Capita
(RGDPPC)  and minimum wage rate by
non-agriculture sector, while level of urbanization, population growth and
poverty rate are included under the provincial, municipalities/cities
dimensions.

Most
studies on labor force participation use either Probit or Logistic models which
are non-linear models. These probability models are most capable in
interpreting dichotomous dependent variables (Pampel, 2000). Furthermore, both
logistic and probit models are similar, thus, in this study, we will employ
probit regression analysis.

1 For more
information on Theory of the Allocation of Time, see Becker (1965)

2  Theory of Allocation of Time is briefly
discussed in Chapter 22, Labor Supply; Microeconomic Theory: Basic Principles
and Extensions 8th edition, see Nicholson (2005)

3   This study would like to assess the
determinants of socio-economic and demographic factors of the labor force
participation, thus,  we will adopt the
extension of utility maximisation theory in which Ackah et al (2009) included
the  variable
X which represents individual characteristics  such as age, marital status etc.

For
more details on the derivation of utility optimization, see Ackah et al (2009).

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