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:

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).