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UNIVERSITY OF SANTO TOMAS

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Labor Mismatch in the Philippines: Analysis of the Impact of

Education-Occupation Mismatch on Wage and Analysis of the Beveridge Curve

An Undergraduate Thesis Presented to the

Economics Department Faculty of Arts and Letters University of Santo Tomas

In Partial Fulfillment of the Requirements for the Degree

Bachelor of Arts Major in Economics

By Jasa, Mary Del A. Jasa, Mary Ann A. Corpuz, Edralyn L.

February 2013


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APPROVAL SHEET

This thesis entitled: Labor Mismatch in the Philippines: Analysis of the Impact of Education-Occupation Mismatch on Wage and Analysis of the Beveridge Curve, prepared and submitted by Mary Del A. Jasa, Mary Ann A. Jasa and Edralyn L. Corpuz has been approved and accepted in partial fulfillment of the requirements for the degree, BACHELOR OF ARTS IN ECONOMICS.

_________________________ Emmanuel Lopez, Ph.D.

Adviser

PANEL OF EXAMINEES

Approved by the Committee on Oral Examination with the grade of____________.

_________________________ Emmanuel Lopez, Ph.D. Chairman

__________________ _______________________ Alvin Ang, Ph.D. Carlos Manapat, Ph.D. Panel Member Panel Member


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ACKNOWLEDGEMENT

The researchers- Maan, Madel & Ral would like to express their sincerest appreciation and gratitude to the following persons who have greatly helped in the completion of this research: Dr. Alvin Ang for patiently helping them in accomplishing the initial works and first draft of their thesis. Dr. Emmanuel Lopez, their adviser, for his valuable suggestions and guidance. Ms. Rosario Abragan, Administrative Assistant II- Databank and Information Services Division of the National Statistics Office, for patiently helping them in acquiring and analyzing the data from NSO. Kuya RJ Angeles, Vice President and COO at Romar Commodities, Inc., Associate Director at Standard Chartered Bank and teaching fellow at University of the Philippines, for the assistance in suggesting data sources and methodology for their thesis.

Kuya Jeck Samson and Ate Rona Jasa for unconditionally sharing their time in imparting their knowledge and experience in doing their undergraduate thesis at the University of the Philippines; for supervising them in the completion of their thesis and inspiring them not to give up in the course of doing the research. Tita Mary Ann Mendoza, for giving them recommendations about their study. Mang Eseng for being their driver from University of Sto. Tomas to NSO, to NSCB, to University of the Philippines, to Makati and from UST to Bulacan in the course of doing the entire research. Mr. and Mrs. Edgardo Corpuz (Papa and Mama) for the moral and financial support as well as for helping them to coordinate with NSO. Engr. and Mrs. Rodel Jasa (Daddy and Mommy) for the financial support and for motivating them to believe in themselves and to be the best of who they can be. Their family, siblings, relatives, classmates and friends from 4ECO1 & 4ECO2 for all the prayers, love and sacrifices for the success of the thesis. And above all, to God Almighty for giving them strength, patience, knowledge and understanding for the very start up until the end and for making all of these success. To God be the glory!

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ABSTRACT Title: Labor Mismatch in the Philippines: Analysis of the Impact of Education-Occupation Mismatch on Wage and Analysis of the Beveridge Curve Researchers: Jasa, Mary Del A. Jasa, Mary Ann A. Corpuz, Edralyn L. School: University of Santo Tomas Degree: Bachelor of Arts Major: Economics Year: Fourth Year Adviser: Dr. Emmanuel Lopez In analyzing the education-occupation mismatch on wage, the researchers run a regression of the dummy variable: MATCH variable relating to the college graduates that were employed either in matched or unmatched occupations against the log of hourly wages. A matched individual is the one having the primary occupation in line with his/her field of study. An unmatched individual is the one having the primary occupation not in line with his/ her field of study. The college graduates under these 3 fields of study -Education, Social Sciences, Business and Law & Services who pursue with the occupation related to their field of study earn higher wages rather than having occupation not related to their field of study (lower wages). While, the college graduates under these 5 Fields of Study (Humanities and Art, Science, Engineering, Manufacturing and Construction, Agriculture, Health and Welfare) who pursue with the occupation related to their field of study (matched), earn lower wages; while if they pursue with the occupation not related to his/her field of study (unmatched), they could higher wages. Also, the Beveridge Curve showed a positive correlation (0.768721874) between the unemployment rate and job vacancy rate. From this point, the researchers conclude the existence of the education-occupation mismatch in the Philippines.


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CHAPTER 1: INTRODUCTION

I. Background of the Study

It is evident that the distribution of income in an economy is related to the

amount of education people have accumulated. The educational attainment of

a person will greatly reflect on the career and the job he will pursue that will

significantly amount the income fitted for his labor.

Mismatch exists in the labor market in the form of educational or skills

mismatch, education-job mismatches. According to Allen & van der Velden

(2001), these are reported to have serious effects on wages and associated

with negative labor market outcomes. The basic idea is that, although higher

education raises productivity in general, the actual level of productivity realized

is also determined by the match between educational and job level.

There are different kinds of mismatches. Spatial mismatch refers to the

disparity between where people who need jobs live and where jobs are

available. An example by Buchan & Calman (2004) is when health workers

typically prefer to live and work in larger cities that offer greater job

opportunities and infrastructure resulting in greater shortage in rural settings

and unemployment or underemployment in urban settings.

Skills mismatch refers to the situation where the workers‟ skills and

education are not adequate for the demands of jobs in the current economy.

There is a mismatch between the skills workers possess and what jobs require,

what economists call an imbalance between the supply of and demand for

human capital. Handel (2003) said that skills mismatch can describe situations

in which workers‟ skills exceed or lag behind those employers seek. An


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example of this in the Philippine setting is the oversupply of nurses and lack of

demand for them. The Filipino nurses may have difficulty entering the US labor

market until 2020 since the shortage of nurses in America ended in 2010 and

now, they have ample supply of US-educated nurses. The government is

pushing for new legislation that would establish a special local jobs plan for idle

Filipino nurses, now estimated at more than 300,000.

In line with these, the focus of this research is to specifically analyze the

education-occupation mismatch and its impact on wage. This research calls for

a need to look on the issues of mismatches since it affects the labor market. As

in the case of the Philippines, there is indeed a need to look and review labor

mismatch because this causes high unemployment rate. The evident reason

observed, is that college graduates‟ skills do not match with the available job

vacancies and the specific fields they should be placed on is already occupied,

therefore they will be left unemployed. The Department of Labor and

Employment said that many of the graduates do not satisfy what the economy

needs. They are either not ready for the jobs or they don‟t possess the needed

skills or knowledge needed for the work they applied for.

Mismatch can also be noticed when workers and jobs are randomly

assigned to labor markets. Each labor market clears at each instant but some

have more workers than jobs, hence unemployment, and some have more jobs

than workers, hence vacancies. According to Shimer (2005), as workers and

jobs move between labor markets, some unemployed workers find vacant jobs

and some employed workers lose or leave their job and become unemployed.

Thus, this research will focus also analyze the Beveridge Curve (ratio of

vacant jobs and unemployed workers) that will be important in understanding

the existence of mismatch on the Philippine labor market.


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II. Objectives of the Study

The objectives of the research are:

To be able to analyze the situation of the Philippine labor market

specifically the presence of the education-occupation mismatch and its

effect to wage

To be able to see the importance of a balanced labor market where job

vacancies can accommodate workers available for work

To provide possible information that would be important for the

government in solving certain issues in the labor market

III. Statement of the Problem

The research is intended to answer the following questions:

1. Does labor mismatch exist in the Philippines? To what extent?

2. How does education- occupation mismatch affect wage?

3. Which fields of study reflect the existence of the labor mismatch in the

Philippines?

4. What are the negative effects of the labor mismatch in the labor market?

5. Does the Beveridge Curve (unemployment rate and job vacancy rate

ratio) exist in the Philippines?

6. Does the Beveridge Curve reflect the positive relationship between the

unemployment rate and job vacancy rate signifying the occurrence of

labor mismatch?


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IV. Significance of the Study

The analysis of educational-occupational mismatch and the existence of

the Beveridge Curve in the Philippine labor market would be significant to the

following:

a. The Government- Mismatch worsens the employment circulation of

the labor market and brings negative effects to the workers in the

labor market who face occupational downgrading in their careers as

in the case of underemployment in which workers that are highly

skilled work in low paying and low-skilled jobs. The research could

help the government in addressing these problems.

The Department of Labor and Employment (DOLE) - The study

would be helpful for the DOLE to find possible solutions to address

the negative effects of the existence of labor mismatch such as

providing job opportunities and skills training that would augment the

mismatch experienced by the mismatched individuals in their line of

work.

Department of Education (DepEd), Commission on Higher Education

(CHED) and Technical Education and Skills Development Authority

(TESDA) - The study would be helpful to the following education

sectors as through the study, they can have knowledge on what field

of study they should give more focus and attention as according to

what the labor market demands in order to solve the problem of

underemployment and unemployment.


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b. The Students- The study would be beneficial to the high school students

as the study would provide information that can help them on their

choice of the field of study (course) that they would be taking in their

college. The study can also help the graduating college students in

choosing their path of careers.

c. Economy- The research would be significant for it can provide the basis

of the government in taking actions to properly utilize the labor force in

order for them to be productive and therefore be instruments in creating

a better economy.

d. The researchers- The research would be significant to the researchers

for this paper will enable them to apply what they have learned in the 4

years of study and this would enable them to learn and discover new

findings relevant to their field of study, Economics.

V. Scope and Limitation

The study will only cover the following parameters. The research

analyzed the impact of education- occupation mismatch on wage in the

Philippines through the use of the data from the National Statistics Office‟s

Labor Force Survey (LFS) October 2011 and the Philippine Standard

Occupational Classification (PSOC).The researchers used the CSPro or

Census and Survey Processing System which is a public domain statistical

package provided by NSO to obtain the necessary data to be used in the study.

The research does not deal on individual survey data.


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In making an empirical analysis of the existence of the Beveridge Curve

(unemployment-vacancies ratio), the researchers used the data of job vacancy

rates obtained from Bureau of Labor and Employment Statistics and the data of

unemployment rates was obtained from Philippine National Statistical

Coordination Board only for the years 1999 up to 2009.

VI. Hypotheses

There is no significant increase in wage when the education and occupation of

a college graduate is matched.

There is a significant increase in wage when the education and occupation of a

college graduate is matched.

This hypothesis will be tested in each of the 8 Major Classifications of the Field

of Study taken by the college graduates:

1. Education

2. Humanities and Arts

3. Social Sciences, Business and Law

4. Science

5. Engineering, Manufacturing and Construction

6. Agriculture

7. Health and Welfare

8. Services


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VII. Definition of Terms

a. Conceptual Definition

Education- is a powerful driver of development and one of the strongest

instruments for reducing poverty and improving health, gender equality,

peace, and stability (World Bank).

Occupation- refers to an activity in which one engages; the principal

business of one's life (Merriam Webster Dictionary)

Mismatch- refers to the situation where two objects or people do not go

together

Matched- refers to one that closely resembles or harmonizes with

another

Unmatched- refers to one that does not closely resembles or

harmonizes with another

Wage- refers to an employee's base pay is the pay they will receive at a

minimum, while extra forms of pay may or may increase the total pay

above this level (Investopedia)

Beveridge Curve- refers to the unemployment-vacancy ratio wherein the

negative/inverse relationship depicts a balanced cycle in the labor

market implying that the job matching process in the labor market is

functioning well while the positive relationship implies that there is a

mismatch in the labor market.


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b. Operational Definition

Education- refers to the field of study taken by the college graduates

Occupation- refers to the primary occupations provided by the National

Statistics Office‟s (NSO) regularly conducted Labor Force Survey‟s

(LFS) October 2011 (4th Quarter of 2011) public user file with wage data

Mismatch- refers to the situation when education (field of study taken by

college graduates) do not match with his/her occupation taken after

graduation

Matched- refers to the situation when an individual‟s occupation is in line

with his/her field of study

Unmatched- refers to the situation when an individual‟s occupation is not

in line with his/her field of study

Wage- refers to the log of hourly wages which can be obtained by

dividing the basic pay per day by normal working hours per day for the

past week

Beveridge Curve- refers to the unemployment-vacancy ratio wherein the

negative/inverse relationship depicts a balanced cycle in the labor

market implying that the job matching process in the labor market is

functioning well while the positive relationship implies that there is a

mismatch in the labor market.


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CHAPTER 2: REVIEW OF RELATED LITERATURE

The review of the related literature for this study focuses on the different studies

concerning the impact of education-occupation mismatch on wage differentials

and the Beveridge Curve.

I. Impact of Education-Occupation Mismatch on Wage

Education and Income Distribution

Tilak (1989) presented the following studies explaining the relation

between education and income distribution. Simon Kuznets (1955) predicted

that income distribution in capitalist countries would become more equal as the

labor force becomes more educated. As Knight and Sabot (1983) observed, the

change in educational composition of the labor force itself has an effect on

inequality. Whether it raises or lowers inequality, assuming all other factors are

held constant, depends on the relative sizes of different educational categories,

their relative mean wages, and their relative wage dispersions. The process of

education effecting income distribution can be simply explained as follows:

education creates a more skilled labor force. This will produce a shift from low

paid, unskilled employment to high paid, skilled employment. This shift

produces higher labor incomes, a reduction in skill differentials and an increase

in the share of wages in total output.

The Impact of Education and Mismatch on Wages

In the research study of Muysken and Hoppe (2002), The Impact of

Education and Mismatch on Wages: Germany, it is cited that in the study taken

in the Netherlands, Muysken and Ruholl traced that personal characteristics

which entails education and experience, and job characteristics which entails

the skills required are the two important determinants used to explain the wage


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differentials since the changes in personal characteristics explains about half of

the variation of wages and job characteristics explains at least thirty percent of

the variation of wages. This assumption was supported by the established

similar results in the United States.

In the estimation results of the study, it is figured out that variables used

in personal characteristics which pertains to age, working experience,

education received and number of hours worked, and job characteristics which

pertains to size of the firm and level of skills required, are significant in defining

the variation of wages, in fact as the job requires a higher level of skills the

earning wages yields higher. The experiences attained by a worker also

generate a positive impact towards defining wage. Job characteristics and

experience plays an important part in determining the wage differences of the

educational category of workers and the educational level is the one to define

the remaining part of it.

Education and Occupation Mismatch in the Labor Market

The educational market and the labor market are the two market

systems that facilitate the matching of education and occupations. Both are

systems of controlling demand and supply, and systems of evaluation and

allocation of positions and agents. As a rule, education qualifies mainly for the

labor market, not for the work or occupation itself (Masuda, T. & Muta, H.

1996).

Ahola et al. (1991) concluded that there are two dimensions of matching.

First is the level of education which is considered to be the primary dimension

of matching process that is related and connected to the segmentation of

structural classes and to the reproduction of social positions. And the


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secondary dimension is the field of study wherein it performs its act within the

different levels of education (Ahola, S. 1991)

The study, “The Matching of Educational and Occupational Structures in

Sweden and Finland” explains that apart from having a strong connection of

education and occupation in the professional fields, individuals who possess

different educational backgrounds can also have an easy way to get matched

up with various occupations in a relatively elastic way (Ahola et al. 1991).

Occupational domains are narrowing or sometimes widening in certain

fields. Narrowing occupational profiles can be found in the fields where

vocational/professional educational programmes have been developed to meet

the needs of specialized occupational tasks (Ahola et al. 1999).

Vocational Schooling as an Advantage Tool in the Labor Market

The study of Vocational Schooling Occupational Matching and Labor

Market Earnings in Israel concluded that vocational schooling is more cost-

effective than the general academic training in Israel. The students who came

from vocational programs and seek out for work that are related to their field of

study had earned more. In fact, their wages are generally higher by up to ten

percent a month than those who studied academic secondary schools but

found employment in occupations not related to their field (Neuman, S. &

Ziderman, A. 1991).

Productivity in Matched Occupation-Education

In the study of Patrick van Eijs and Hans Heijke (1996), The Relation

between the Wage, Job-related Training and the Quality of the Match between

Occupations and Types of Education, it is stated that efficiency and wages

depend on the matching of the demanded and attained abilities and therefore


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there will be a higher wages if there will be a match on these two that causes a

higher productiveness. This concludes that through the matching of the

laborer‟s specific education skills with the occupational job characteristics

which yields efficiency, the human capital of the labor force is being utilized well

and this paves a way to achieve the right and deserved wage for the rendered

skill.

Income Penalty of Mismatch

But in the labor market there are existing problems that hinders the right

allocation of deserved wages and this is due to the education-occupation

mismatch that creates an income penalty to the workers. A study supporting

this conclusion is the pioneering paper of Robst which had shown that in the

data wherein US college graduates who do not matched their occupation to the

major course they have taken had almost 11 percent lower annual income as to

be compared to the graduates who had a matched one.

Also in the study done by the 2006 Survey of Labour and Income

Dynamics (SLID) of Canada it is concluded in the survey results that those 58

percent workers reported who had matched their attained education closely

related to their present work and those 19 percent reported who had matched

their attained education somewhat related to their present work have a 35

percent higher wage given a $27 mean wage rate than those 23 percent

workers reported who did not found their attained education to be related to

their present work given $20 mean wage rate.

Reasons for having Occupations not related to the Field of Study

The general personal reasons for choosing the occupation even if it is not

related to the field of study are job security wherein the worker had found the

secureness, assurance and continuity of gainful employment to the said

occupation even if it is not inclined to his taken course, professional growth in


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which they had achieved the sense of fulfillment and usefulness of their

personal drive on the said occupation they have taken even if it is unmatched

to their field of study, pay, which pertains to monetary reason of earning a

higher compensation to the unmatched occupation than to the related one, and

quality of work life that refers to the benefits, environment and way of life that

the worker is attaining which provides him the sense of belongingness and

satisfaction (Edgewise.ph, 2010). Prejudiced situations is depicted in the

condition of the nurses who are under the health and welfare field of study in

way that nurses fail to pursue their careers not only because of financial

incapability of hospitals to give them a just compensation but worst is they

themselves are paying just to gain experience and after they will still not be

hired (Filipino Nurses Blog). And in the case of the agricultural workers they

had a greater tendency to prefer not to be in lined to their field of study because

of the existence of non-competitive salaries and incentives due to inefficient

utilization of our agricultural sector; therefore attaining an occupation

unmatched in this field would provide them a higher wage (Rwanda Skills

Survey 2012 Agriculture Sector Report).

II. Beveridge Curve

The Cyclical Behavior of Equilibrium Unemployment and Vacancies

This journal explains that with an increase in labor productivity

(interpreted as a technology or supply shock in one-sector model and referred

as the preference or demand shock changing the relative price of goods in

multi-sector model) in relation to the value of nonmarket activity (referred as

leisure) and to the cost of advertising a job vacancy makes unemployment

relatively expensive and vacancies relatively cheap. The market substitutes

toward vacancies, and the increased job-finding rate pulls down the

unemployment rate, resulting to a downward sloping Beveridge curve

(vacancy-unemployment ratio) (Shimer, 2005).


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This study presented that the increase in hiring, shortens unemployment

duration, increases workers‟ threat in wage bargaining, and increases also the

expected present value of wages in new jobs. Then, it can be said that higher

wages absorb most of the productivity increase, thus reducing the incentive for

the creation of vacancies. Therefore, the labor productivity shock results

primarily in higher wages, with little impact on the unemployment, vacancy, and

job-finding rates (Shimer, 2005).

This study presented that an increase in separations results to

decreasing employment duration, increasing unemployment rate and so

therefore increasing vacancies. As a result, fluctuations in the separation rate

or separation shocks generate an increase in both unemployment and

vacancies (Shimer, 2005).

According to search theory, unemployed workers have left their old job

and are actively searching for a new employer. It is a theory of former steel

workers moving to a new city to look for positions as nurses (Lucas and

Prescott 1974). In contrast, this study emphasizes the mismatch theory in

which unemployed workers are attached to an occupation and a geographic

location in which jobs are presently scarce. In here, it is a theory of former steel

workers choosing to remain near a closed plant in the hope that it reopens

(Shimer, 2005). These two theories are complementary and it is reasonable to

think that mismatch may be as important as search in understanding

equilibrium unemployment.

The Beveridge curve is part of the study since it reflects the efficiency of

the job matching process through depicting the state of the labor market using

the shifts along the curve that illustrates occurring regular changes in the


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demand and supply of labor. In the study of skills mismatches and labor

mobility of the European Union, they concluded that having an upturn shift in

curve reflects that there is a higher vacancies which shows that there is a

higher supply of jobs then definitely exemplifies lower unemployment and this

greatly explains that it indicates labor shortages while on the other hand the

downturn shift in curve reflects that there is a lower vacancies which shows that

there is a lower supply of jobs then definitely exemplifies lower unemployment

and this greatly explains that it indicates labor surplus (Shimer, 2005).

William Beveridge identified and implied the negative relationship

between unemployment and job vacancies that depicts a balanced cycle in the

labor market because a negative relationship between the two reflects that the

job matching process in the labor market is functioning well. Therefore if there

will be a positive relationship between them wherein a direct relationship

between them exists, mismatch in the labor market occurs (Shimer, 2005).

The conclusions made in this study was significantly discussed and

proven in the said research through the evaluation of the major skills challenge

of Europe wherein high levels of unemployment is still existing even if job

vacancies also started to increase which illustrates that mismatch in their labor

market exists which may be indicated by first, qualification mismatch that

pertains to the mismatch between educational qualifications a worker

possesses and the prerequisites of the job (Shimer, 2005). Situations involved

in this mismatch are over-education wherein a worker possesses more required

educational qualifications and under-education in which a worker possesses

fewer educational qualifications. Second is the structural unemployment that

pertains to the mismatch between labor demand and skills and the location of

the potential workers. Third, skills mismatch that pertains to incompatibility

between the skills possessed by the worker and the demanded skills of the job,


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and situation involves are skill deficit wherein the worker‟s skill didn‟t fit into the

job prerequisites and skill underutilization in which worker‟s skill went beyond

the job prerequisites. Fourth, Regional and sectoral mismatch which exists

when job openings in the locations and sectors are open but not well matched

with potential workers.

Labor Market Mismatches

Problems of matching between labor supply and labor demand in

Belgium are visible from the Beveridge curve, which shows the relationship

between the unemployment rate and the job vacancy rate. Belgium has both a

significant pool of unfilled job vacancies and persistent unemployment implying

that both unemployment rate and job vacancy rates move in the same

direction. This observation rises to the problem of labor mismatch or to the

question of how labor supply matches up with labor demand. The reasons for a

mismatch between the two can be cyclical, frictional or structural, for example

when the educational level of job-seekers does not correspond with the profiles

sought on the labor market, or when there is a lack of geographic mobility

(Zimmer, 2012).

2009-2010 Bureau of Labor and Employment Statistics (BLES)

Integrated Survey (BITS)

The 2009/2010 BITS results showed that from January 2009 to January

2010 the total number of job vacancies are at 276,940 while job applicants is

roughly 6 times higher at 1,969,976 for all occupations. Manufacturing, real

estate, renting and business activities, and education industries had the most

number of hard-to-fill vacancies. The most common problems in filling up

vacant positions include lack of competency, high expectations in wage/salary,

and lack of work experience.


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III. THEORETICAL FRAMEWORK

A. Impact of Education- Occupation Mismatch on Wage

Recent studies of education and wage determination are almost always

embedded in the framework of Mincer's (1974) human capital earnings function

(HCEF).

According to this model, the log of individual earnings (y) in a given time period

can be decomposed into an additive function of a linear education term:

𝑙𝑜𝑔𝑦 = 𝑎 + 𝑏𝑆 + 𝑐𝑋 + 𝑑𝑋2 + 𝑒

where S represents years of completed education, X represents the number of

years an individual has worked since completing schooling, and e is a statistical

residual. In the absence of direct information on experience Mincer proposed

the use of "potential experience": the number of years an individual of age A

could have worked, assuming he started school at age 6, finished S years of

schooling in exactly S years, and began working immediately thereafter: X =A -

S - 6.

B. Beveridge Curve

1. Skills Mismatches and Labor Mobility

A study done in the Member States of the European Union showed that the

unfilled job vacancies co-exist with high levels of unemployment. The so-called

Beveridge curve, which relates unemployment rates to job vacancies, typically

shows a negative relationship between the vacancy rate and the

unemployment rate (Shimer, 2005).


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The fact that unemployment was still rising when vacancies started to

increase reflects problems in the job matching process, which may be related

to mismatches in skills/educational qualifications required for a certain job and

regional/sectoral mismatches.

The Beveridge curve reflects the efficiency of the job matching

process.In the study, the curves of Member States are analyzed to help us

understand whether these structural changes are taking place.

- Shifts along the curve represent cyclical changes in the demand for labor

(higher vacancies and lower unemployment in upturns indicating labor

shortages; lower vacancies and higher unemployment in downturns indicating

an excess of labor)

- Shifts of the curve towards the left or right are indicative of structural changes.

Increases in long-term unemployment will push the curve away from the

starting position, pointing to potential mismatches in the labour market.

2. Mismatch by Shimer

The study conducted in the mismatch model of Shimer significantly showed

the negative correlation between unemployment and vacancy that pertains to

Beveridge curve and the positive correlation between rate wherein the

unemployed workers are able to discern jobs and the vacancy-unemployment

ratio.


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Theory

The unemployment and vacancy rates are dependent on the exogenous

number of workers per market M and the endogenous number of jobs per

market N.

The vacancy-unemployment (v-u) ratio is V (N)/U(N) and the unemployment

and vacancy rates are u(N) =U(N)/M and v(N) =V (N)/N.

Therefore unemployment and vacancies are being affected by productivity

shocks due to the unemployment and vacancies‟ impact on the number of jobs

per market.

The following proposition demonstrates how:

The unemployment rate u is increasing in the number of workers per labor

market M and decreasing in the number of jobs per labor market N.

The vacancy rate v is decreasing in the number of workers per labor market M

and increasing in the number of jobs per labor market N.

In this, there are a lot of implications. First, a higher productivity encourages

firms to produce more jobs, and therefore this would raise the number of jobs

per labor market N, and hence diminishes unemployment rate and upsurges

vacancy rate. Thus it presents to us that the impact of productivity shocks

cause a downward-sloping vacancy-un employment (v-u) locus movement.

Second, the unemployment and vacancy rates both decreases whenever there

is a proportional increase in both M and N.

Doubling M and N is equivalent to merging randomly selected pairs of labor

markets. If both markets have unemployment, this merger does not affect the


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unemployment or vacancy rates, and similarly if both markets have vacancies.

But merging a market with unemployment and a market with vacancies reduces

the unemployment and vacancy rate in both.

Measurement

In the United States, the Bureau of Labor Statistics (BLS) has measured job

vacancies using the JOLTS. The said measurement is the most reliable time

series for vacancies in the U.S.. In accordance to the prerequisites of job

openings, the BLS specified that job opening entails first, there is a specific slot

of position that occurs, second, within 30 days, the work could start, and third,

to fill in the vacant position, the employer is enthusiastically hiring outside the

institution itself. Wherein, active recruiting pertains to the commitment of the

institution in rendering contemporary efforts in fulfilling the opening through

advertisement and other methods of publicity. Also the time preferential such

as full-time, part-time, permanent, temporary, and short-term openings are

incorporated.

The vacancy rate is measured as the ratio of vacancies to vacancies plus

employment.

In order to measure the unemployment rate of each month, The Bureau of

Labor Statistics (BLS) uses the Current Population Survey (CPS) wherein it

entails a measurement procedure of using household questionnaire.

The unemployment rate is measured as the ratio of unemployment to the sum

of unemployment and employment.

The strong negative correlation between unemployment and vacancies over

this time period is shown by the empirical Beveridge curve.


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IV. CONCEPTUAL FRAMEWORK

A. The Model used by the Researchers in the Analysis of Education-

Occupation Mismatch effect on wage

This section provides a framework for the regression model to be estimated:

no formal model of wage determination is presented; the researchers draw

from the previous theoretical and empirical studies (Mincer‟s Model) in

analyzing the likely effects of certain variables on wages.

In this study regarding the impacts of education and occupation mismatch

on wages, the researchers will use Mincer‟s human capital earnings function as

the basis. The researchers will use this function:

𝐿𝑛 𝑊𝑖 = 𝛼 + 𝛽𝑀𝐴𝑇𝐶𝐻 + 𝑢

Where:

𝐿𝑛 𝑊𝑖 = log 𝑜𝑓 𝑕𝑜𝑢𝑟𝑙𝑦 𝑤𝑎𝑔𝑒𝑠 /𝑒𝑎𝑟𝑛𝑖𝑛𝑔𝑠

MATCH= field of study and occupation category 1=matched 0=not matched

Matched

or

Unmatche

d

Effect Wage Education

Occupation


26

B. Beveridge Curve

To analyze the mismatch between vacant jobs and unemployed workers in

the Philippines, the researchers will use Shimer’s measurement in obtaining the

Beveridge Curve.

The vacancy rate is measured as the ratio of vacancies to vacancies plus

employment.

The unemployment rate is measured as the ratio of unemployment to the sum

of unemployment and employment.

Unemployment

rate

Job- vacancy

rate


27

CHAPTER 3: DATA AND METHODOLOGY

A. The Model used by the Researchers in the Analysis of Education-

Occupation Mismatch effect on wage

1. Research Design

In the study, the researchers used a quantitative explanatory research

methodology which attempts to explain the functional relationship between the

variable to be estimated (dependent variable) and the variable that accounts for

the changes (independent variable). The researchers worked on the

educational and work-related variables across the country. The dependent

variable is the log of hourly wage. The independent variable that is used is a

dummy or binary variable: MATCH variables (being educationally and

occupationally matched or unmatched).

2. Sources of Data

The cross-sectional data the researchers used was sourced from the

National Statistics Office‟s (NSO) regularly conducted Labor Force Survey‟s

(LFS) October 2011 (4th Quarter of 2011) public user file with wage data. The

researchers used the CSPro or Census and Survey Processing System which

is a public domain statistical package provided by NSO to obtain the

necessary data to be used in the study.

3. Tools for Data Analysis

In doing the regression analysis, the researchers utilized the Statistical

Package for the Social Sciences (SPSS) 17.0. The researchers also did

hypothesis testing using the t test. According to Gujarati (2004), in the

language of significance tests, a statistic is said to be statistically significant if

the value of the test statistic lies in the critical region. In this case the null


28

hypothesis is rejected. By the same token, a test is said to be statistically

insignificant if the value of the test statistic lies in the acceptance region. In this

situation, the null hypothesis is not rejected.

4. Specific Methodology

With the objective to analyze the impact of education-occupation mismatch

on wage, the researchers used the LFS to obtain the total number of college

graduates. This was then classified according to the First Stage of Tertiary/

Baccalaurate Education provided also by the NSO thus arriving with the 8

Major Classifications of the Field of Study taken by the college graduates:

61-Education

62- Humanities and Arts

63-Social Sciences, Business and Law

64- Science

65- Engineering, Manufacturing and Construction

66-Agriculture

67- Health and Welfare

68-Services

For detailed sub-classifications of the 8 Major Classifications of the Field of

Study taken by the college graduates, see Appendix 1.

The researchers also obtained the Primary Occupations of the college

graduates for each of the 8 Major Classifications of the Field of Study.


29

Table 1: Primary Occupations

PRIMARY OCCUPATIONS

Officials of Government and Special-Interest Organizations

Corporate Executives and Specialized Managers

General Managers or Managing-Proprietors

Supervisors

Physicists Mathematical and Engineering Science Professionals

Life Science and Health Professionals

Teaching Professionals

Other Professionals

Physical Science and Engineering Associate Professionals

Life Science and Health Associate Professionals

Teaching Associate Professionals

Related Associate Professionals

Office Clerks

Customer Services Clerks

Personal and Protective Service Workers

Models Salespersons and Demonstrators

Farmers and Other Plant Growers

Animal Producers

Forestry and Related Workers

Fishermen

Hunters and Trappers

Mining Construction and Related Trade Workers

Metal Machinery and Related Trades Workers

Precision Handicraft Printing and Related Trades Workers

Other Craft and Related Trades Workers

Stationary Plant and Related Operators

Machine Operators and Assemblers

Drivers and Mobile Plant Operators

Sales and Services Elementary Occupations

Agricultural Forestry Fishery and Related Laborers

Laborers in Mining Construction Manufacturing and Transport

Armed Forces

Non-Gainful Occupations

Other Occupations Not Classifiable


30

The regression model to be estimated as presented here will be used for

each Major Classification of the Field of Study to determine the impact of

education-occupation mismatch on wage.

𝑳𝒏 𝑾𝒊 = 𝜶 + 𝜷𝑴𝑨𝑻𝑪𝑯 + 𝒖

Where:

𝐿𝑛 𝑊𝑖 = log 𝑜𝑓 𝑕𝑜𝑢𝑟𝑙𝑦 𝑤𝑎𝑔𝑒𝑠 /𝑒𝑎𝑟𝑛𝑖𝑛𝑔𝑠

MATCH= field of study and occupation category 1=matched 0=not matched

The dependent variable is the log of hourly wages and was obtained by

dividing the basic pay per day by normal working hours per day for the past

week. The reference period, being the „past week‟ or the past seven days

preceding the date of visit of the interviewer. The reason for taking the natural

logarithm of the wage variables is that they are highly skewed to the left. By

taking the log, the distribution becomes more symmetric (Neuman & Ziderman,

1991).

log 𝑜𝑓 𝑕𝑜𝑢𝑟𝑙𝑦 𝑤𝑎𝑔𝑒𝑠

= 𝑏𝑎𝑠𝑖𝑐 𝑝𝑎𝑦 𝑝𝑒𝑟 𝑑𝑎𝑦

/ 𝑛𝑜𝑟𝑚𝑎𝑙 𝑤𝑜𝑟𝑘𝑖𝑛𝑔 𝑕𝑜𝑢𝑟𝑠 𝑝𝑒𝑟 𝑑𝑎𝑦 𝑓𝑜𝑟 𝑡𝑕𝑒 𝑝𝑎𝑠𝑡 𝑤𝑒𝑒𝑘

The basic pay per day with the highest frequency was obtained from

each of the Primary Occupations under each Major Classification of the Field of

Study taken by the college graduates. This is to represent the basic pay per

day of the majority of the college graduates is receiving.

The normal working hours per day for the past week was obtained by

dividing the total number of hours worked during the past week by 8 hours


31

which is the normal working hours per day for an employee as specified in the

Philippine Labor Law (Art. 84, Labor Code). The total number of hours worked

during the past week with the highest frequency was obtained from each of the

Primary Occupations under each Major Classification of the Field of Study

taken by the college graduates.

𝑛𝑜𝑟𝑚𝑎𝑙 𝑤𝑜𝑟𝑘𝑖𝑛𝑔 𝑕𝑜𝑢𝑟𝑠 𝑝𝑒𝑟 𝑑𝑎𝑦 𝑓𝑜𝑟 𝑡𝑕𝑒 𝑝𝑎𝑠𝑡 𝑤𝑒𝑒𝑘

= 𝑡𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑕𝑜𝑢𝑟𝑠 𝑤𝑜𝑟𝑘𝑒𝑑 𝑑𝑢𝑟𝑖𝑛𝑔 𝑡𝑕𝑒 𝑝𝑎𝑠𝑡

/ 𝑛𝑜𝑟𝑚𝑎𝑙 𝑤𝑜𝑟𝑘𝑖𝑛𝑔 𝑕𝑜𝑢𝑟𝑠 𝑝𝑒𝑟 𝑑𝑎𝑦

The MATCH variable was obtained by doing cross tabulation of the

Primary Occupations and the Field of Study. The Primary Occupations under

each Major Classification of the Field of Study were classified as Matched=1

and Unmatched=0 which is based and patterned on the Philippine Standard

Occupational Classification 1992 (updated for the year 2002), see Appendix 2

and also on the First Stage of Tertiary/ Baccalaurate Education provided by the

NSO. A matched individual is the one having the primary occupation in line with

his/her field of study. An unmatched individual is the one having the primary

occupation not in line with his/ her field of study.


32

B. Beveridge Curve

1. Research Design

The researchers used correlational quantitative research design which

expresses the relationship between two variables numerically.

2. Sources of Data

In making an empirical analysis of the existence of the Beveridge Curve

in the Philippines, the researchers used the data of job vacancy rates obtained

from Bureau of Labor and Employment Statistics and the data of

unemployment rates was obtained from Philippine National Statistical

Coordination Board only for the years 1999 up to 2009.

3. Tools for Data Analysis

The researchers used the Statistical Package for the Social Sciences

(SPSS) 17.0 to analyze the vacancy-unemployment (v-u) ratio or the Beveridge

Curve.

4. Specific Methodology

The researchers obtained the correlation between the job vacancy rates

and unemployment rates to analyze the Beveridge Curve.


33

CHAPTER 4: RESULTS AND DISCUSSION

A. Education-Occupation Mismatch Impact on Wage

The statistical table (See Appendix 3) shows the total number of college

graduates per Field of Study and their corresponding Primary Occupations.

The following shows the percentage of each field of study‟s graduates to the

total number of college graduates:

Education (61)- 23.14 %

Humanities and Arts (62)- 1.33 %

Social Sciences, Business and Law (63) -32.35%

Science (64) -7.13%

Engineering, Manufacturing and Construction (65) - 22.69%

Agriculture (66) - 3.55%

Health and Welfare (67) - 1.33%

Services (68)- 8.47%

The highest proportion (32.35%) of the total number of college graduates

who had already found jobs/ occupations are coming from the Social Sciences,

Business and Law. The least proportion (1.33%) of the total number of college

graduates who had already found jobs/ occupations are coming from the

Humanities and Arts and Health and Welfare.

Regression Analysis

The researchers consider the log of hourly earnings as the dependent

variable as run against the MATCH variable as the independent variable. The

reason for taking the natural logarithm of the wage variables is that they are

highly skewed to the left. By taking the log, the distribution becomes more


34

symmetric (Neuman & Ziderman, 1991). By taking the natural logarithm of the

hourly wages shows that these become responsive to the changes in the

independent variable as shown in the two scatter diagram plots below. The

scatter plots presented here is only for Education field of study, since the

scatter plots for the other 7 fields of study also reflect the same pattern.

The results of the regression analysis (See Appendix 4) done for the 8 Major

Classifications of the Field of Study are explained on the next page.

0

50

100

150

200

250

300

350

0 10 20 30

HOURLY WAGE/ EARNINGS

HOURLY WAGE/ EARNINGS

0

1

2

3

4

5

6

7

0 10 20 30

LOG OF HOURLY EARNINGS

LOG OF HOURLY EARNINGS


35

1. Education

Under the Field of Education (61), the regression model is:

log of hourly wages= 4.482 + 0.965MATCH

This presents that on the average, for every unit increase in the MATCH

variable, the log of hourly earnings would be increasing by 0.965 peso.

Hypothesis Testing

H0: There is no significant increase in wage when the education and

occupation of a college graduate is matched.

H1: There is a significant increase in wage when the education and occupation

of a college graduate is matched.

α=0.05

Degrees of freedom= n-k-1

Degrees of freedom= 26- 1-1 = 24

T critical= 1.711

T-stat= 2.54224502580694

Reject H0. Accept H1.This implies that if a college graduate under this Field of

Study pursues with the occupation related to his/her field of study can earn

higher wages rather than having occupation not related to his/ her field of

study.


36


Under the Field of Social Sciences, Business and Law (63), the regression

model is:




Hypothesis Testing





α=0.05



T critical= 1.708

T-stat= 3.5304477880851




study.


37

3. Services

Under the Field of Services (68), the regression model is:




Hypothesis Testing





α=0.05



T critical= 1.714

T-stat= 2.25884756076435




study.


38

Based on the hypothesis testing conducted using t-test, the results show

that college graduates under these 3 fields of study (Education, Social

Sciences, Business and Law & Services) who pursue with the occupation

related to their field of study earn higher wages rather than having occupation

not related to their field of study. Thus, a college graduate earns higher wages

when his/her education and occupation is matched.

The result was supported by the study made by Patrick van Eijs and

Hans Heijke (1996) where it stated that efficiency and wages depend on the

matching of the demanded and attained abilities and therefore there will be a

higher wages if there will be a match on these two that causes a higher

productiveness. The study also concluded that through the matching of the

laborer‟s specific education skills with the occupational job characteristics

which yields efficiency, the human capital of the labor force is being utilized well

and this paves a way to achieve the right and deserved wage for the rendered

skill.


39


Under the Field of Humanities and Arts (62), the regression model is:

log of hourly wages= 4.437 - 0.010MATCH


variable, the log of hourly earnings would be decreasing by 0.010 peso.

Hypothesis Testing





α=0.05


Degrees of freedom= 19- 1-1 =17

T critical= 1.740

T-stat= -0.0486257070180501

Accept H0. Reject H1.This implies that if a college graduate under this Field of


lower wages rather than having occupation not related to his/ her field of study.


40

5. Science

Under the Field of Science (64), the regression model is:




Hypothesis Testing





α=0.05



T critical= 1.711

T-stat= 0.197020752163872





41


Under the Field of Engineering, Manufacturing and Construction (65), the

regression model is:

log of hourly wages= 4.851- 0.193MATCH



Hypothesis Testing





α=0.05



T critical= 1.708

T-stat= -0.703149759265872





42

7. Agriculture

Under the Field of Agriculture (66), the regression model is:




Hypothesis Testing





α=0.05



T critical= 1.703

T-stat= -0.913513876447283





43


Under the Field of Health and Welfare (67), the regression model is:




Hypothesis Testing





α=0.05



T critical= 1.746

T-stat= -1.57964542504616





44

Based on the hypothesis testing conducted using t-test, the results show

that college graduates under these 5 Fields of Study (Humanities and Art,

Science, Engineering, Manufacturing and Construction, Agriculture, Health and

Welfare) who pursue with the occupation related to their field of study

(matched), earn lower wages; while if they pursue with the occupation not

related to his/her field of study (unmatched), they earn higher wages.

B. Beveridge Curve

The data presented on Table 2 are used in analyzing the existence of the Beveridge curve in the Philippines.

Year

Job-

vacancy

Rate

Unemployment

Rate

2009 45.1 7.475

2008 52.5 7.4

2007 47.7 7.325

2006 47.9 8

2005 57.3 11.35

2004 62.3 11.825

2003 74.7 11.4

2002 70.9 11.4

2001 84.6 11.125

2000 68.5 11.175

1999 71.8 9.75

Table 2: Job-vacancy & unemployment rates


45

Correlation of Unemployment rates and Job-vacancy rates

Table 3. Correlation between job-vacancy and unemployment rates

The correlation coefficient between the job- vacancy rates and

unemployment rates resulted to a positive value of 0.768721874 which means

that there is a positive correlation. The two variables are associated; and they

move in the same direction in systematic way: as one gets larger, so does the

other; as one gets smaller, so does the other. The correlation coefficient of

0.768721874 is closer to 1 therefore implying strong positive correlation. This

positive correlation between the two variables greatly reflects that mismatch

occurs in the Philippine labor market as job vacancies increases, the

unemployment rate increases. This implies that as more jobs become available

for employment, more number of the labor force gets unemployed indicating

that there is no equilibrium in the labor market.

William Beveridge (1960) identified that the negative relationship

between unemployment and job vacancies depicts a balanced cycle in the

labor market implying that the job matching process in the labor market is

functioning well. Thus, the study‟s result showing a positive correlation implies

Job-vacancy rate

Unemployment

rate

Job-vacancy

rate 1

Unemployment

rate 0.768721874 1


46

that the job matching process in the labor market is not functioning well

mismatch, so the researchers could say that mismatch exists in the Philippines.

The result of the study showing that mismatch occurs in the Philippines

is also supported by Zimmer (2012) wherein in his study in Belgium, problems

of mismatch is also evident as it has both a significant pool of unfilled job

vacancies and persistent unemployment implying that both unemployment rate

and job vacancy rates move in the same direction.


47

CHAPTER 5: CONCLUSION AND RECOMMENDATIONS

I. CONCLUSION

A. Education-Occupation Mismatch

The research was able to analyze the impact of education- occupation

mismatch on wage. Through estimating the coefficient of the Match variable

(education-occupation) along with the log of hourly earnings/wage, the

researchers conclude that that college graduates under these 3 fields of study -

Education, Social Sciences, Business and Law & Services who pursue with the

occupation related to their field of study earn higher wages rather than having

occupation not related to their field of study (lower wages).

The result was supported by Van Eijs and Heijke (1996) where it stated

that the matching of the laborer‟s specific education skills with the occupational

job characteristics yields efficiency, the human capital of the labor force is

being utilized well and this paves a way to achieve the right and deserved wage

for the rendered skill. Samson (2003) also concluded in their study that

matched workers earn more than their unmatched counterparts verified by the

regression analysis.

The researchers also conclude that college graduates under these 5

Fields of Study (Humanities and Art, Science, Engineering, Manufacturing and

Construction, Agriculture, Health and Welfare) who pursue with the occupation

related to their field of study (matched), earn lower wages; while if they pursue

with the occupation not related to his/her field of study (unmatched), they could

higher wages.


48

These 5 out of 8 Major Classifications of the Fields of Study implied that

college graduates coming from these 5 Fields of study since they are earning

lower wages if they pursue with the occupation related to his/her field of study

(matched), tend to pursue occupations not related to his/her field of study

(unmatched) in order for them to earn higher wages. From, this point, the

researchers can conclude the existence of the education-occupation mismatch

in the Philippines.

Mismatch exists and causes underemployment, a situation in which a

worker is employed, but not in the desired capacity, whether in terms of

compensation, hours, or level of skills and experience (Lopez). Labor that falls

under the underemployment classification includes those workers that are

highly skilled but working in low paying jobs, workers that are highly skilled but

work in low skill jobs (Investopedia). Underemployment resulted from the

mismatch as can be seen in this research. In the 3 fields of study (Education,

Social Sciences, Business and Law & Services), underemployment can be

seen when unmatched individuals who are highly skilled work in a low paying

(lower wage) and low skill jobs. Moreover, in the 5 Fields of Study (Humanities

and Art, Science, Engineering, Manufacturing and Construction, Agriculture,

Health and Welfare), underemployment can be seen when unmatched

individuals who are highly skilled work but are working in low skill jobs.

B. Beveridge Curve

The researchers conclude that labor mismatch exists in the Philippine

labor market since the Beveridge Curve showed a positive correlation of

0.768721874 between the unemployment rate and job vacancy rate. This

presents the positive correlation between the two showing that mismatch exists

in the labor market (Beveridge. 1960). When the levels of unemployment and


49

job vacancies are both increasing, this illustrates that mismatch in the labor

market exists which is indicated by the qualification mismatch pertaining to the

mismatch between educational qualifications a worker possesses and the

prerequisites of the job (Shimer, 2005).

II. RECOMMENDATIONS

For the Government

Since one of the main problems that education-occupation mismatch

brings is underemployment, which reflects the occurrence of low quality jobs

that hinders the existence of good job opportunities, workers are not able to

earn appropriate income that compensates their rendered skill. Therefore this

problem should be seriously resolved, and to address such, the researchers

recommend the following:

The researchers recommend the strengthening of the coordination of

the three training and education institutions – Department of Education

(DepEd), Commission on Higher Education (CHED) and Technical

Education and Skills Development Authority (TESDA) so as to have a

harmonized education and human resource development program.

The researchers recommend the government to provide enough job

opportunities (labor demand) that would cater the unemployed

individuals (labor supply) through the enhancement of the labor supply

side through development of human resources, labor productivity, and

technological advancement as well as the improvement of the labor

demand side.


50

The researchers would also like to recommend the government in order

to attain a balanced labor market (where Beveridge Curve presents as

inverse relationship between unemployment rate and job vacancy rate),

to find solutions on how to fill the job vacancies by focusing on

increasing the workers‟ competencies and work experiences.

The researchers recommend the government to properly utilize the

Official Job Portal of the Philippines, Phil-JobNet, which is an

automated job and applicant matching system which aims to fast-track

jobseekers search for jobs and employers search for manpower.

Based on the results of the study, the researchers would like to

recommend the government to help in the improvement of the

Education, Social Sciences, Business and Law & Services fields of

study as well as the occupations related to these fields of study so as to

attain matched individuals earning higher wages. The researchers

recommend that the Senior high school students to take these Fields of

study and pursue jobs related to these after college graduation for them

to attain higher wages at the same time applying the skills they have

learned in college.

Based from the results of the study that if the college graduates from

Humanities and Art, Science, Engineering, Manufacturing and

Construction, Agriculture, Health and Welfare Fields of study are

matched, they will earn lower wages and/ or if they are unmatched, they

will earn higher wages. Thus, the researchers recommend that the

college graduates from these fields of study should be flexible in

adapting various job opportunities. In line with this, the researchers

would like to recommend the government to boost the job opportunities


51

by providing sufficient incentives, proper working conditions, and

satisfying salaries for these fields of study so that the college graduates

from these fields would be able to achieve better earnings and at the

same applying their learned skills making them educationally and

occupationally matched.

For Future Researchers

The researchers recommend to the future researchers to deal with the

gathered primary individual data of the LFS so as to have a clearer and

precise study of the Mincer model (Human Capital Earning function). In

this regard, it is recommended to deal with the sex, age and work

experience of each individual so as to analyze the effect of these three

personal and work related variables on wage differentials.


52

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55

Shimer, R. 2005. Mismatch. National Bureau of Economic Research

Working Paper Series: Working Paper 11888. Cambridge,

Massachusetts Avenue. Retrieved from

http://www.nber.org/papers/w11888

Tilak, J. 1989. Education and Its Relation to Economic Growth,

Poverty and Income Distribution. World Bank Discussion Papers. The

World Bank. Washington, D.C.

Van Ejis, P. & Heijke, H. 1996. The Relation between the Wage, Job-

related Training and the Quality of the Match between Occupations

and Types of Education.University of Limburg, Maastricht

Zimmer, H. 2012. Labour Market Mismatches. Economic Review

Journal. National Bank of Belgium.

Internet Articles:

http://filipinonurses.org/index.php/2011/11/being-a-volunteer-nurse-or-a-

call-center-agent-2/

http://www.edgewise.ph/2010/06/22/006-ask-edgewise/i-just-started-

this-job-but-i-received-a-better-offer-elsewhere/

N/A. 2010. Job Mismatch Causes High Unemployment

Rate.Retrieved from http://affleap.com/job-mismatch-causes-high-

employment-rate/

N/A. 2012. Pinoy Nurses Told Not To Expect US Hiring Till 2020.

Retrieved from http://mb.com.ph/node/357253/pinoy-nur

http://filipinonurses.org/index.php/2011/11/being-a-volunteer-nurse-or-a-call-center-agent-2/

http://filipinonurses.org/index.php/2011/11/being-a-volunteer-nurse-or-a-call-center-agent-2/

http://www.edgewise.ph/2010/06/22/006-ask-edgewise/i-just-started-this-job-but-i-received-a-better-offer-elsewhere/

http://www.edgewise.ph/2010/06/22/006-ask-edgewise/i-just-started-this-job-but-i-received-a-better-offer-elsewhere/


56

http://www.investopedia.com/terms/u/underemployment.asp

http://www.ble.dole.gov.ph/philjobnet.asp

http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTEDUCATIO

N/0,,menuPK:28291~pagePK:149018~piPK:149093~theSitePK:282386,

00.html

http://www.merriam-webster.com/dictionary/occupation

http://www.thefreedictionary.com/

http://www.investopedia.com/terms/b/base-pay.asp#ixzz2LOnGtWQL


57

APPENDIX 1: 8 Major Classifications of the Field of Study

FIRST STAGE OF TERTIARY/BACCALAUREATE EDUCATION (NOT LEADING DIRECTLY TO AN ADVANCED RESEARCH QUALIFICATION) EDUCATION 614 TEACHER TRAINING AND EDUCATION SCIENCES PROGRAMS 61401 Programs in General Teacher Training 61401 Bachelor of Elementary Education 61401 Bachelor of Secondary Education 61401 Bachelor of Science in Elementary and Secondary Education 61401 Bachelor of Science in Pedagogy 61404 Programs in Teacher Training with Specialization in Nonvocational Subjects 61404 Bachelor of Home Economics and Livelihood Education for Teachers 61404 Bachelor of Physical Education 61404 Bachelor of Sports Science 61404 Bachelor of Technology and Home Economics for Teachers 61404 Bachelor of Arts in Language Education for Teachers 61404 Bachelor of Science in Chemistry for Teachers 61404 Bachelor of Science in English Education as Secondary Language 61404 Bachelor of Science in Language Education for Teachers 61404 Bachelor of Science in Mathematics for Teachers 61404 Bachelor of Science in Music Education 61404 Bachelor of Science in Physical Education 61404 Bachelor of Science in Physics for Teachers 61404 Bachelor of Science in Religious Education 61408 Programs in Teacher Training for Teaching Practical or Vocational Subjects 61408 Bachelor of Science in Industrial Education 61408 Bachelor of Science in Technician Teacher Education 61412 Programs in Teacher Training for Teaching Preschool or Kindergarten 61412 Bachelor of Science in Early Childhood Education 61412 Bachelor of Science in Kindergarten/Preschool Education 61416 Programs in Teacher Training for Teachers in Adult Education 61422 Programs in Teacher Training for Teachers in Special Education 61422 Bachelor of Special Education 61472 Programs in Education Science in Support of Teaching 61472 Bachelor of Science in Guidance and Counseling 61499 Other Programs in Teacher Training and Education Sciences 61499 Bachelor of Science in Agricultural Education 61499 Bachelor of Science in Business/Commercial Education 61499 Bachelor of Science in Extension Education 61499 Bachelor of Science in Fishery Education 61499 Bachelor of Science in Nursing Education 61499 Bachelor of Science in Nutrition and Dietetics for Teachers 61499 Bachelor of Science in Secretarial Education HUMANITIES AND ARTS 621 ARTS PROGRAMS 62101 General Programs in Art Studies 62101 Bachelor of Digital Arts 62101 Bachelor of Science in Fine Arts/Bachelor of Fine Arts 62104 Programs in Drawing and Painting 62108 Programs in Sculpturing 62122 Programs in Music 62122 Bachelor of Music Liturgy 62122 Bachelor of Science in Music/Bachelor of Music 62132 Programs in Drama

62132 Bachelor of Performing Arts 62132 Bachelor of Arts in Speech and Drama 62132 Bachelor of Arts in Speech and Theater Arts 62132 Bachelor of Arts in Theater Arts 62132 Bachelor of Science in Speech and Drama 62152 Programs in Interior Design 62152 Bachelor of Science in Interior Design 62199 Other Programs in Arts 62199 Bachelor of Arts in Film and Audio-Visual Communication 622 HUMANITIES PROGRAMS 62201 General Programs in Humanities


58

62201 Bachelor of Arts in Humanities 62211 Programs in the Current or Vernacular Language and Its Literature 62211 Bachelor of Arts in English 62211 Bachelor of Arts in English Literature 62211 Bachelor of Arts in Filipino 62211 Bachelor of Arts in Philippine Literature 62215 Programs in Other Living Languages and Their Literature 62215 Bachelor of Arts in European Languages 62221 Programs in "Dead" Languages and Their Literature 62231 Programs in Linguistics 62231 Bachelor of Arts in Linguistics 62241 Programs in Comparative Literature 62241 Bachelor of Arts in Comparative Literature 62241 Bachelor of Arts in Literature 62251 Programs in History 62251 Bachelor of Arts in Development Studies 62251 Bachelor of Arts in History 62261 Programs in Archeology 62271 Programs in Philosophy 62271 Bachelor of Arts in Classical/Philosophy/Bachelor of Classical/Philosophy 62271 Bachelor of Arts in Philosophy/Bachelor of Philosophy 62281 Programs in Religion and Theology 62281 Bachelor of Evangelical Ministry 62281 Bachelor of Arts in Religion 62281 Bachelor of Arts in Religious Studies 62281 Bachelor of Arts in Divinity/Bachelor of Divinity 62281 Bachelor of Arts in Theology/Bachelor of Theology 62299 Other Programs in Humanities SOCIAL SCIENCES, BUSINESS, AND LAW 631 SOCIAL AND BEHAVIORAL SCIENCE PROGRAMS 63101 General Programs in Social and Behavioral Sciences 63101 Bachelor of Arts in Behavioral Science 63101 Bachelor of Arts in Social Science 63101 Bachelor of Arts in Human Behavior Technology/Bachelor of Human Behavior Technology 63101 Bachelor of Science in Behavioral Science 63101 Bachelor of Science in Human Behavior Technology 63112 Programs in Economics 63112 Bachelor of Arts in Economics 63112 Bachelor of Arts in Applied Economics/Bachelor of Applied Economics 63112 Bachelor of Science in Applied Economics 63112 Bachelor of Science in Business Economics 63112 Bachelor of Science in Economics 63122 Programs in Political Science 63122 Bachelor of Arts in Political Science/Bachelor in Political Science 63122 Bachelor of Science in Foreign Service 63122 Bachelor of Science in International Relations 63122 Bachelor of Science in Political Economy 63132 Programs in Sociology 63132 Bachelor of Arts in Applied Sociology 63132 Bachelor of Arts in Sociology 63132 Bachelor of Science in Sociology 63133 Programs in Demography 63133 Bachelor of Science in Demography 63142 Programs in Anthropology 63142 Bachelor of Arts in Anthropology 63152 Programs in Psychology 63152 Bachelor of Arts in Applied Psychology

63152 Bachelor of Science in Clinical Psychology 63152 Bachelor of Science in Industrial and Organizational Psychology 63152 Bachelor of Science in Psychology 63162 Programs in Geography 63162 Bachelor of Science in Geography 63172 Programs in Studies of Regional Cultures 63172 Bachelor of Arts in Arabic/Islamic Studies 63172 Bachelor of Arts in International Studies 63172 Bachelor of Arts in Philippine Arts 63172 Bachelor of Arts in Philippine Studies 63199 Other Programs in Social and Behavioral Sciences


59

632 JOURNALISM AND INFORMATION PROGRAMS 63201 Programs in General Communication Arts 63201 Bachelor of Arts in Communication 63201 Bachelor of Arts in Media Studies 63202 Programs in Journalism 63202 Bachelor of Arts in Business Journalism/Bachelor in Business Journalism 63202 Bachelor of Arts in Journalism/Bachelor in Journalism 63202 Bachelor of Science in Business Journalism 63202 Bachelor of Science in Journalism 63204 Programs in Radio and Television Broadcasting 63204 Bachelor of Arts in Broadcast Communication 63204 Bachelor of Science in Broadcast Communication 63207 Programs in Public Relations 63207 Bachelor of Arts in Public Relations 63222 Programs in Library Science 63222 Bachelor of Arts in Library and Information Science/Bachelor of Library and Information Science 63222 Bachelor of Arts in Library Science/Bachelor of Library Science 63229 Other Programs in Journalism and Information 63229 Bachelor of Arts in Communication Arts/Mass Communication 63229 Bachelor of Arts in Communication Research 63229 Bachelor of Arts in Organizational Communication 63229 Bachelor of Science in Mass Communication 634 BUSINESS AND ADMINISTRATION PROGRAMS 63401 General Programs in Business Administration/Commerce 63401 Bachelor of Arts in Business Administration/Bachelor in Business Administration 63401 Bachelor of Arts in Entrepreneurial Management/Bachelor in Entrepreneurial Management 63401 Bachelor of Arts in Business Management/Bachelor of Business Management 63401 Bachelor of Arts in Management and Social Work /Bachelor of Management and Social Work 63401 Bachelor of Science in Administration 63401 Bachelor of Science in Business Administration 63401 Bachelor of Science in Business Management 63401 Bachelor of Science in Commerce 63401 Bachelor of Science in Management 63404 Programs in Secretarial 63404 Bachelor of Science in Airline Secretarial/Administration 63404 Bachelor of Science in Computer Secretarial 63404 Bachelor of Science in Office Administration/Technology 63404 Bachelor of Science in Secretarial Administration 63432 Programs in Business Administration with Specialization in Accountancy 63432 Bachelor of Science in Accountancy 63432 Bachelor of Science in Business Administration and Accountancy 63432 Bachelor of Science in Computer Accounting and Management 63432 Bachelor of Science in Management and Accountancy 63434 Programs in Business Administration with Specialization in Marketing 63434 Bachelor of Arts in Advertising/Bachelor of Advertising 63434 Bachelor of Arts in Advertising and Public Relations/Bachelor of Advertising and Public Relations 63434 Bachelor of Science in Marketing 63436 Programs in Business Administration with Specialization in Finance and Investment 63436 Bachelor of Science in Finance 63436 Bachelor of Science in Real Estate 63436 Bachelor of Science in Banking and Finance/Bachelor in Banking and Finance 63439 Programs in Business Administration with Other Specialization 63439 Bachelor of Arts in Legal Management 63439 Bachelor of Arts in Business Engineering/Bachelor in Business Engineering 63439 Bachelor of Arts in Agricultural Entrepreneurship/Bachelor of Agricultural

Enterpreneurship 63439 Bachelor of Arts in Business Distributive Arts/Bachelor of Business Distributive Arts 63439 Bachelor of Arts in Computer Management/Bachelor of Computer Management 63439 Bachelor of Arts in Industrial Management/Bachelor of Industrial Management 63439 Bachelor of Arts in Transportation Management/Bachelor of Transportation Management 63439 Bachelor of Science in Agri-Business Management 63439 Bachelor of Science in Business Enterpreneurship 63439 Bachelor of Science in Business Technology 63439 Bachelor of Science in Economics and Cooperatives 63439 Bachelor of Science in Fishery Business Management 63439 Bachelor of Science in Home Arts and Enterpreneurship 63439 Bachelor of Science in Industrial Management


60

63452 Programs in Public Administration 63452 Bachelor of Arts in Public Administration/Bachelor of Public Administration 63452 Bachelor of Science in Public Administration 63462 Programs in Institutional Administration/Management 63462 Bachelor of Arts in Port Administration/Bachelor of Port Administration 63462 Bachelor of Science in Airline Business Administration/Management 63462 Bachelor of Science in Airline Management 63462 Bachelor of Science in Airline Management and Accountancy 63462 Bachelor of Science in Customs Administration 63462 Bachelor of Science in Food Service Administration 63462 Bachelor of Science in Hospital Administration 63462 Bachelor of Science in Postal Management 63462 Bachelor of Science in Shipping Management 63499 Other Programs in Business Administration/Management 63499 Bachelor of Arts in Legal and Indigenous Studies 63499 Bachelor of Arts in Cooperatives/Bachelor of Cooperatives 63499 Bachelor of Science in Cooperative Management 63499 Bachelor of Science in Maritime Management 63499 Bachelor of Science in Recreation Management 63499 Bachelor of Science in Supply Management 638 LAW PROGRAMS 63801 General Programs in Law 63801 Bachelor of Laws (LL.B.)/Juris Doctor (J.D.) 63801 Bachelor of Science in Jurisprudence SCIENCE 642 LIFE SCIENCES PROGRAMS 64202 Programs in Biological Science 64202 Bachelor of Science in Applied Biology 64202 Bachelor of Science in Biochemistry 64202 Bachelor of Science in Biological Science 64202 Bachelor of Science in Biology 64202 Bachelor of Science in Botany 64202 Bachelor of Science in Entomology 64202 Bachelor of Science in Human Biology 64202 Bachelor of Science in Marine Biology 64202 Bachelor of Science in Microbiology 64202 Bachelor of Science in Molecular Biology and Biotechnology 64202 Bachelor of Science in Pharmacology 64202 Bachelor of Science in Physiology 64202 Bachelor of Science in Plant Science 64202 Bachelor of Science in Zoology 64209 Other Programs in Life Sciences 64209 Bachelor of Arts in Applied Science/Bachelor of Applied Science 64209 Bachelor of Science in General Science 64209 Bachelor of Science in Natural Science 644 PHYSICAL SCIENCES PROGRAMS 64412 Programs in Chemistry 64412 Bachelor of Science in Chemical Research 64412 Bachelor of Science in Chemical Technology 64412 Bachelor of Science in Chemistry 64412 Bachelor of Science in Industrial Chemistry 64422 Programs in Geological Science 64422 Bachelor of Science in Geology 64422 Bachelor of Science in Volcanology 64432 Programs in Physics

64432 Bachelor of Science in Applied Physics 64432 Bachelor of Science in Metallurgy 64432 Bachelor of Science in Physics 64432 Bachelor of Science in Physics-Mathematics 64442 Programs in Astronomy 64442 Bachelor of Science in Astronomy 64452 Programs in Meteorology 64452 Bachelor of Science in Meteorology 64462 Programs in Oceanography 64462 Bachelor of Science in Marine Science 64462 Bachelor of Science in Oceanography 646 MATHEMATICS AND STATISTICS PROGRAMS


61

64601 General Programs in Mathematics 64601 Bachelor of Science in Mathematics 64611 Programs in Statistics 64611 Bachelor of Science in Applied Statistics 64611 Bachelor of Science in Experimental Statistics 64611 Bachelor of Science in Statistics 64621 Programs in Actuarial Science 64621 Bachelor of Science in Actuarial Science 64699 Other Programs in Mathematics 64699 Bachelor of Science in Applied Mathematics 648 COMPUTING/INFORMATION TECHNOLOGY PROGRAMS 64841 Programs in Computer Science and Information Technology 64841 Bachelor of Arts in Information Technology/Bachelor in Information Technology 64841 Bachelor of Science in Business Computer Applications 64841 Bachelor of Science in Computer Applications 64841 Bachelor of Science in Computer Data Processing Management 64841 Bachelor of Science in Computer Science 64841 Bachelor of Science in Computer Studies 64841 Bachelor of Science in Information and Computer Science 64841 Bachelor of Science in Information System/Management 64841 Bachelor of Science in Information Technology 64841 Bachelor of Science in Management Information System 64841 Bachelor of Science in Software Technology 64844 Programs in Electronic Data Processing 64844 Bachelor of Science in Computer Data Processing and Information Management 64844 Bachelor of Science in Data Processing ENGINEERING, MANUFACTURING, AND CONSTRUCTION 652 ENGINEERING AND ENGINEERING TRADES PROGRAMS 65204 Programs in Aeronautical Engineering 65204 Bachelor of Science in Aeronautical Engineering 65204 Bachelor of Science in Aerospace Engineering 65204 Bachelor of Science in Air Transportation 65204 Bachelor of Science in Aircraft Maintenance Engineering 65204 Bachelor of Science in Aircraft Maintenance Technology 65204 Bachelor of Science in Aircraft Technology 65204 Bachelor of Science in Aviation 65204 Bachelor of Science in Aviation Electronics Engineering 65204 Bachelor of Science in Avionics Engineering 65204 Bachelor of Science in Avionics Technology 65204 Bachelor of Science in Electrical Engineering Avionics 65204 Bachelor of Science in Flying Technology 65212 Programs in Chemical Engineering 65212 Bachelor of Science in Ceramics Engineering 65212 Bachelor of Science in Chemical Engineering 65212 Bachelor of Science in Chemical Engineering Technology 65212 Bachelor of Science in Textile Engineering 65216 Programs in Civil Engineering 65216 Bachelor of Science in Civil Engineering 65216 Bachelor of Science in Construction Technology 65218 Programs in Geodetic Engineering 65218 Bachelor of Science in Geodetic Engineering 65222 Programs in Electrical, Electronics and Computer Engineering 65222 Bachelor of Science in Communications Engineering 65222 Bachelor of Science in Computer Engineering 65222 Bachelor of Science in Computer Technology 65222 Bachelor of Science in Electrical Engineering

65222 Bachelor of Science in Electrical Engineering Technology 65222 Bachelor of Science in Electrical Technology 65222 Bachelor of Science in Electronics and Communications Engineering 65222 Bachelor of Science in Electronics Engineering 65222 Bachelor of Science in Electronics Technology 65222 Bachelor of Science in Instrumentation and Control Engineering 65226 Programs in Industrial Engineering 65226 Bachelor of Science in Industrial and Management Engineering 65226 Bachelor of Science in Industrial Design 65226 Bachelor of Science in Industrial Engineering 65226 Bachelor of Science in Industrial Technology 65226 Bachelor of Science in Management Engineering 65226 Bachelor of Science in Manufacturing Engineering


62

65232 Programs in Metallurgical Engineering 65232 Bachelor of Science in Metallurgical Engineering 65236 Programs in Mining Engineering 65236 Bachelor of Science in Mining Engineering 65242 Programs in Mechanical Engineering 65242 Bachelor of Science in Automotive Technology 65242 Bachelor of Science in Geothermal Engineering 65242 Bachelor of Science in Mechanical Engineering 65242 Bachelor of Science in Mechanical Technology 65250 Programs in Sanitary Engineering 65250 Bachelor of Science in Environmental and Sanitary Engineering 65250 Bachelor of Science in Environmental Engineering 65250 Bachelor of Science in Sanitary Engineering 65253 Programs in Agricultural Engineering 65253 Bachelor of Science in Agricultural Engineering 65253 Bachelor of Science in Aquatic Resource Engineering 65263 Programs in Forestry Engineering 65263 Bachelor of Science in Forest Products Engineering 65281 Programs in Marine Engineering 65281 Bachelor of Science in Marine Engineering 65281 Bachelor of Science in Naval Architecture and Marine Engineering 65299 Other Programs in Engineering 65299 Bachelor of Arts in Technology/Bachelor of Technology 65299 Bachelor of Science in Electronics and Computer Technology 65299 Bachelor of Science in Food Engineering 65299 Bachelor of Science in Petroleum Engineering 654 MANUFACTURING AND PROCESSING PROGRAMS 65476 Programs in Clothing and Related Trades 65476 Bachelor of Science in Clothing Technology 65476 Bachelor of Science in Garment/Textile Technology 658 ARCHITECTURE AND BUILDING PROGRAMS 65801 General Programs in Architecture and Town Planning 65801 Bachelor of Science in Architecture 65812 Programs in Landscape Architecture 65812 Bachelor of Science in Landscape Architecture 65822 Programs in Town Planning 65822 Bachelor of Science in Town and Country Planning AGRICULTURE 662 AGRICULTURE, FORESTRY, AND FISHERY PROGRAMS 66201 General Programs in Agriculture 66201 Bachelor of Arts in Agricultural Technology/Bachelor of Agricultural Technology Bachelor of Science in Agriculture 66203 Programs in Animal Husbandry 66203 Bachelor of Science in Animal Husbandry 66203 Bachelor of Science in Animal Science 66203 Bachelor of Science in Animal Technology 66206 Programs in Horticulture 66206 Bachelor of Arts in Horticulture Management/Bachelor of Technology in Horticulture Management 66206 Bachelor of Science in Horticulture 66208 Programs in Agronomy 66208 Bachelor of Science in Agronomy 66212 Programs in Agricultural Economics 66212 Bachelor of Science in Agricultural Economics 66222 Programs in Food Science and Technology

66222 Bachelor of Science in Food Technology 66226 Programs in Soil and Water Sciences 66249 Other Programs in Agriculture 66249 Bachelor of Science in Agricultural Administration 66249 Bachelor of Science in Agricultural Chemistry 66249 Bachelor of Science in Agricultural Development 66249 Bachelor of Science in Agricultural Management 66249 Bachelor of Science in Rice Technology 66249 Bachelor of Science in Sugar Technology 66262 Programs in Forestry 66262 Bachelor of Arts in Agro-Forestry Technology/Bachelor in Agro-Forestry Technology 66262 Bachelor of Science in Agro-Forestry 66262 Bachelor of Science in Forestry


63

66272 Programs in Fishery Science and Technology 66272 Bachelor of Science in Aquaculture 66272 Bachelor of Science in Aquatic Resource Management and Technology 66272 Bachelor of Science in Fisheries 66272 Bachelor of Science in Fishing Technology 66272 Bachelor of Science in Inland Fisheries 664 VETERINARY PROGRAMS 66432 Programs in Veterinary Medicine 66432 Bachelor of Science in Veterinary Technology HEALTH AND WELFARE 672 HEALTH PROGRAMS 67202 Programs in Hygiene 67202 Bachelor of Science in Community/Public Health 67202 Bachelor of Science in Sanitary Science 67206 Programs in Medicine 67206 Bachelor of Arts in Basic Medical Sciences 67206 Doctor of Medicine 67208 Programs in Rehabilitation Medicine 67208 Bachelor of Science in Occupational Therapy 67208 Bachelor of Science in Physical Therapy 67208 Bachelor of Science in Respiratory Therapy 67208 Bachelor of Science in Speech Pathology 67212 Programs in Nursing 67212 Bachelor of Science in Nursing 67217 Programs in Medical X-Ray Techniques 67217 Bachelor of Science in Radiologic Technology 67230 Programs in Medical Technology 67230 Bachelor of Science in Medical Technology 67242 Programs in Dentistry 67242 Doctor of Dental Medicine 67252 Programs in Pharmacy 67252 Bachelor of Science in Industrial Pharmacy 67252 Bachelor of Science in Pharmaceutical Chemistry 67252 Bachelor of Science in Pharmacy 67262 Programs in Optometry 67262 Doctor of Optometry 67272 Programs in Nutrition and Dietetics 67272 Bachelor of Science in Nutrition and Dietetics 67299 Other Programs in Medical Diagnostic and Treatment 67299 Bachelor of Science in Paramedics 67299 Bachelor of Science in Rural Medicine 676 SOCIAL SERVICES PROGRAMS 67632 Programs in Social Welfare 67632 Bachelor of Arts in Social Services/Social Work 67632 Bachelor of Science in Social Services/Social Work 67652 Programs in Community Development 67652 Bachelor of Science in Community Development 67652 Bachelor of Science in Development of Multi-Cultural Communities 67652 Bachelor of Science in Rural Development Management SERVICES 681 PERSONAL SERVICES PROGRAMS 68101 General Programs in Home Economics (Domestic Science)

68101 Bachelor of Science in Family and Child Development 68101 Bachelor of Science in Home Economics 68101 Bachelor of Science in Human Ecology 68132 Programs in Home Economics with Emphasis on Household Arts 68134 Other Programs in Home Economics 68134 Bachelor of Science in Home Technology 68172 Programs in Hotel and Restaurant Trades 68172 Bachelor of Science in Hotel and Restaurant Management 68182 Programs in Tourism 68182 Bachelor of Arts in Tourism 68182 Bachelor of Science in Tourism 68182 Bachelor of Science in Tourism and Hotel and Restaurant Management 68182 Bachelor of Science in Tourism and Travel Management


64

684 TRANSPORT SERVICES PROGRAMS 68404 Programs in Nautical Science 68404 Bachelor of Science in Marine Transportation 68404 Bachelor of Science in Nautical Science 685 ENVIRONMENTAL PROTECTION PROGRAMS 68552 Programs in Environmental Studies 68552 Bachelor of Arts in Technology in Environmental Management/Bachelor of Technology in Environmental Management 68552 Bachelor of Science in Coastal Resource Management 68552 Bachelor of Science in Ecology 68552 Bachelor of Science in Environmental Development/Environmental Hygiene/Environmental Science 68552 Bachelor of Science in Environmental Management 68552 Bachelor of Science in Environmental Planning 686 SECURITY SERVICES PROGRAMS 68613 Programs in Criminal Justice Education 68613 Bachelor of Science in Criminal Justice/Criminology 68613 Bachelor of Science in Forensic Science 68613 Bachelor of Science in Industrial Security Management 68613 Bachelor of Science in Police/Law Enforcement Administration 68617 Programs in Military 68619 Other Programs in Civil Security 68619 Bachelor of Arts in Peace and Security Studies 68619 Bachelor of Science in Peace and Security Studies


65

APPENDIX 2: Field of Study and Primary Occupations used for Matching

The following shows the Primary Occupations under each Major Classification

of the Field of Study which are considered to be matched which is based and

patterned on the Philippine Standard Occupational Classification 1992.

Education (61) Supervisors, Teaching Professionals, and

Teaching Associate Professionals.

Humanities and Arts (62) Teaching Professionals, Other Professionals,

Physical Science and Engineering Associate

Professionals, Related Associate

Professionals, Models, Salespersons and

Demonstrators, Precision, Handicraft, Printing

and Related Trades Workers.

Social Sciences, Business and Law

(63)

Officials of Government and Special-Interest

Organizations, Corporate Executives and

Specialized Managers, General Managers or

Managing-Proprietors, Supervisors, Teaching

Professionals, Other Professionals, Related

Associate Professionals, Office Clerks,

Customer Services Clerks, Models,

Salespersons and Demonstrators, Other Craft

and Related Trades Workers, Sales and

Services.

Science (64) Physicists, Life Science and Health

Professionals, Teaching Professionals,

Physical Science and Engineering Associate

Professionals, Life Science and Health

Associate Professionals.

Engineering, Manufacturing and Corporate Executives and Specialized


66

Construction (65) Managers, General Managers or Managing-

Proprietors, Physicists, Mathematical and

Engineering, Physical Science and

Engineering Associate, Mining, Construction

and Related Trade Workers, Metal, Machinery

and Related Trades Workers, Stationary Plant

and Related Operators, Machine Operators

and Assemblers, Drivers and Mobile Plant

Operators, Laborers.

Agriculture (66) General Managers or Managing-Proprietors,

Supervisors, Farmers and Other Plant

Growers, Animal Producers, Forestry and

Related Workers, Fishermen, Hunters and

Trappers, Metal, Machinery and Related

Trades Workers, Agricultural, Forestry,

Fishery and Related Laborers.

Health and Welfare (67) Life Science and Health Professionals, Life

Science and Health Associate Professionals,

Related Associate Professionals, Personal

and Protective Service Workers.

Services (68) Officials of Government and Special-Interest

Organizations, Supervisors, Related

Associate Professionals, Customer Services

Clerks, Personal and Protective Service

Workers, Armed Forces.


67

APPENDIX 3: Total Number of College Graduates per Field of Study and their corresponding Primary Occupations


68

APPENDIX 4: Regression Results for the 8 Fields of Study

1. Education

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 4.482 .129 34.765 .000

MATCH .965 .380 .461 2.542 .018

a. Dependent Variable: LOG OF HOURLY EARNINGS


Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 4.270 .125 34.143 .000

MATCH .662 .188 .577 3.530 .002


3. Services

Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 4.282 .142 30.246 .000

MATCH .653 .289 .426 2.259 .034



69


Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 4.437 .119 37.201 .000

MATCH -.010 .212 -.012 -.049 .962

5. Science

Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 4.479 .114 39.402 .000

MATCH .051 .259 .040 .197 .845



Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 4.851 .167 28.988 .000

MATCH -.193 .275 -.139 -.703 .488



70

7. Agriculture

Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 4.447 .148 29.997 .000

MATCH -.243 .266 -.173 -.914 .369



Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 4.694 .140 33.625 .000

MATCH -.468 .296 -.367 -1.580 .134



71

APPENDIX 5: DATA FOR EDUCATION (61)

OCCUPATION

BASIC

PAY

TOTAL

NO. OF

HOURS

WORKED

DURING

THE

PAST

WEEK

WORKING

HOURS

PER DAY

NORMAL

WORKING

HOURS

DURING

THE PAST

WEEK

HOURLY

WAGE/

EARNINGS

LOG OF

HOURLY

EARNINGS MATCH

Officials of Government and Special-Interest Organizations 1499 48 8 6 249.833333 5.520794 0

Corporate Executives and Specialized Managers 1499 48 8 6 249.833333 5.520794 0

Supervisors 1499 48 8 6 249.833333 5.520794 1

Physicists Mathematical and Engineering Science Professionals 699 48 8 6 116.5 4.757891 0

Life Science and Health Professionals 1499 48 8 6 249.833333 5.520794 0

Teaching Professionals 899 48 8 6 149.833333 5.009524 1

Other Professionals 1499 48 8 6 249.833333 5.520794 0

Physical Science and Engineering Associate Professionals 399 48 8 6 66.5 4.197202 0

Life Science and Health Associate Professionals 599 48 8 6 99.8333333 4.603502 0

Teaching Associate Professionals 1999 48 8 6 333.166667 5.808643 1

Related Associate Professionals 599 48 8 6 99.8333333 4.603502 0

Office Clerks 399 48 8 6 66.5 4.197202 0

Customer Services Clerks 299 48 8 6 49.8333333 3.908684 0

Personal and Protective Service Workers 1499 48 8 6 249.833333 5.520794 0

Models Salespersons and Demonstrators 299 48 8 6 49.8333333 3.908684 0

Mining Construction and Related Trade Workers 299 39 8 4.875 61.3333333 4.116323 0

Metal Machinery and Related Trades Workers 199 48 8 6 33.1666667 3.501545 0

Precision Handicraft Printing and Related Trades Workers 299 39 8 4.875 61.3333333 4.116323 0

Other Craft and Related Trades Workers 399 48 8 6 66.5 4.197202 0

Stationary Plant and Related Operators 399 48 8 6 66.5 4.197202 0

Machine Operators and Assemblers 399 48 8 6 66.5 4.197202 0

Drivers and Mobile Plant Operators 499 48 8 6 83.1666667 4.420847 0

Sales and Services Elementary Occupations 199 19 8 2.375 83.7894737 4.428307 0

Agricultural Forestry Fishery and Related Laborers 199 48 8 6 33.1666667 3.501545 0

Laborers in Mining Construction Manufacturing and Transport 399 48 8 6 66.5 4.197202 0

Armed Forces 499 48 8 6 83.1666667 4.420847 0


72

APPENDIX 6: DATA FOR HUMANITIES AND ARTS (62)

OCCUPATION

BASIC

PAY

TOTAL

NO. OF

HOURS

WORKED

DURING

THE

PAST

WEEK

WORKING

HOURS

PER DAY

NORMAL

WORKING

HOURS

DURING

THE PAST

WEEK

HOURLY

WAGE/

EARNINGS

LOG OF

HOURLY

EARNINGS MATCH


Corporate Executives and Specialized Managers 599 58 8 7.25 82.62069 4.41426 0

Supervisors 1499 48 8 6 249.8333 5.520794 0




Other Professionals 699 58 8 7.25 96.41379 4.568649 1


Related Associate Professionals 299 19 8 2.375 125.8947 4.835446 1

Office Clerks 299 48 8 6 49.83333 3.908684 0


Personal and Protective Service Workers 399 58 8 7.25 55.03448 4.00796 0


Mining Construction and Related Trade Workers 499 39 8 4.875 102.359 4.628486 0

Precision Handicraft Printing and Related Trades Workers 299 39 8 4.875 61.33333 4.116323 1

Sales and Services Elementary Occupations 199 29 8 3.625 54.89655 4.005451 0



Armed Forces 699 58 8 7.25 96.41379 4.568649 0


73

APPENDIX 7: DATA FOR SOCIAL SCIENCES, BUSINESS & LAW (63)

OCCUPATION

BASIC

PAY

TOTAL

NO. OF

HOURS

WORKED

DURING

THE

PAST

WEEK

WORKING

HOURS

PER DAY

NORMAL

WORKING

HOURS

DURING

THE PAST

WEEK

HOURLY

WAGE/

EARNINGS

LOG OF

HOURLY

EARNINGS MATCH



General Managers or Managing-Proprietors 1499 58 8 7.25 206.7586207 5.331552 1

Supervisors 1499 48 8 6 249.8333333 5.520794 1







Teaching Associate Professionals 199 19 8 2.375 83.78947368 4.4283074 0


Office Clerks 399 48 8 6 66.5 4.1972019 1




Mining Construction and Related Trade Workers 499 48 8 6 83.16666667 4.4208466 0


Precision Handicraft Printing and Related Trades Workers 599 48 8 6 99.83333333 4.6035021 0

Other Craft and Related Trades Workers 399 29 8 3.625 110.0689655 4.7011071 1




Sales and Services Elementary Occupations 299 48 8 6 49.83333333 3.9086841 1



Armed Forces 699 48 8 6 116.5 4.7578913 0


74

APPENDIX 8: DATA FOR SCIENCE (64)

OCCUPATION

BASIC

PAY

TOTAL

NO. OF

HOURS

WORKED

DURING

THE

PAST

WEEK

WORKING

HOURS

PER DAY

NORMAL

WORKING

HOURS

DURING

THE PAST

WEEK

HOURLY

WAGE/

EARNINGS

LOG OF

HOURLY

EARNINGS MATCH



Supervisors 399 48 8 6 66.5 4.1972019 0









Office Clerks 499 48 8 6 83.1667 4.4208466 0











Agricultural Forestry Fishery and Related Laborers 199 19 8 2.375 83.7895 4.4283074 0


Armed Forces 399 48 8 6 66.5 4.1972019 0

Other Occupations Not Classifiable 599 48 8 6 99.8333 4.6035021 0


75

APPENDIX 9: DATA FOR Engineering, Manufacturing and Construction (65)

OCCUPATION

BASIC

PAY

TOTAL

NO. OF

HOURS

WORKED

DURING

THE

PAST

WEEK

WORKING

HOURS

PER DAY

NORMAL

WORKING

HOURS

DURING

THE PAST

WEEK

HOURLY

WAGE/

EARNINGS

LOG OF

HOURLY

EARNINGS MATCH

Officials of Government and Special-Interest Organizations 1499 19 8 2.375 631.1579 6.4475561 0


General Managers or Managing-Proprietors 1499 48 8 6 249.8333 5.520794 1

Supervisors 1499 48 8 6 249.8333 5.520794 0







Teaching Associate Professionals 399 29 8 3.625 110.069 4.7011071 0


Office Clerks 399 48 8 6 66.5 4.1972019 0














Armed Forces 1499 48 8 6 249.8333 5.520794 0


76

APPENDIX 10: DATA FOR AGRICULTURE (66)

OCCUPATION

BASIC

PAY

TOTAL

NO. OF

HOURS

WORKED

DURING

THE

PAST

WEEK

WORKING

HOURS

PER DAY

NORMAL

WORKING

HOURS

DURING

THE PAST

WEEK

HOURLY

WAGE/

EARNINGS

LOG OF

HOURLY

EARNINGS MATCH



General Managers or Managing-Proprietors 1499 58 8 7.25 206.758621 5.331552 1

Supervisors 1499 48 8 6 249.833333 5.520794 1








Office Clerks 299 48 8 6 49.8333333 3.908684 0




Farmers and Other Plant Growers 199 19 8 2.375 83.7894737 4.428307 1

Animal Producers 199 48 8 6 33.1666667 3.501545 1

Forestry and Related Workers 199 39 8 4.875 40.8205128 3.709185 1

Fishermen 199 39 8 4.875 40.8205128 3.709185 1

Hunters and Trappers 199 39 8 4.875 40.8205128 3.709185 1




Drivers and Mobile Plant Operators 399 39 8 4.875 81.8461538 4.404841 0




Armed Forces 1499 48 8 6 249.833333 5.520794 0

Other Occupations Not Classifiable 199 48 8 6 33.1666667 3.501545 0


77

APPENDIX 11: DATA FOR HEALTH & WELFARE (67)

OCCUPATION

BASIC

PAY

TOTAL

NO. OF

HOURS

WORKED

DURING

THE

PAST

WEEK

WORKING

HOURS

PER DAY

NORMAL

WORKING

HOURS

DURING

THE PAST

WEEK

HOURLY

WAGE/

EARNINGS

LOG OF

HOURLY

EARNINGS MATCH



Supervisors 1499 48 8 6 249.83333 5.52079403 0







Office Clerks 499 48 8 6 83.166667 4.42084663 0




Metal Machinery and Related Trades Workers 599 29 8 3.625 165.24138 5.10740731 0

Drivers and Mobile Plant Operators 399 39 8 4.875 81.846154 4.40484131 0





78

APPENDIX 12: DATA FOR SERVICES (68)

OCCUPATION

BASIC

PAY

TOTAL

NO. OF

HOURS

WORKED

DURING

THE

PAST

WEEK

WORKING

HOURS

PER DAY

NORMAL

WORKING

HOURS

DURING

THE PAST

WEEK

HOURLY

WAGE/

EARNINGS

LOG OF

HOURLY

EARNINGS MATCH

Officials of Government and Special-Interest Organizations 1499 19 8 2.375 631.16 6.44756 1


Supervisors 499 48 8 6 83.167 4.42085 1









Office Clerks 499 48 8 6 83.167 4.42085 0








Machine Operators and Assemblers 399 58 8 7.25 55.034 4.00796 0





Armed Forces 799 48 8 6 133.17 4.8916 1

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