Labor-mismatch-in-the-philippines-jasa.pdf 405b63

UNIVERSITY OF SANTO TOMAS 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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UNIVERSITY OF SANTO TOMAS

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

OF EXAMINEES Approved by the of____________.

Committee

on

Oral

Examination

with

the

grade

_________________________ Emmanuel Lopez, Ph.D. Chairman

__________________ Alvin Ang, Ph.D. Member

_______________________ Carlos Manapat, Ph.D. Member

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UNIVERSITY OF SANTO TOMAS 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, istrative 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 as well as for helping them to coordinate with NSO. Engr. and Mrs. Rodel Jasa (Daddy and Mommy) for the financial 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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UNIVERSITY OF SANTO TOMAS ABSTRACT Title: Labor Mismatch in the Philippines: Analysis of the Impact of EducationOccupation 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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UNIVERSITY OF SANTO TOMAS 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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UNIVERSITY OF SANTO TOMAS 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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UNIVERSITY OF SANTO TOMAS 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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UNIVERSITY OF SANTO TOMAS 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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UNIVERSITY OF SANTO TOMAS 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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UNIVERSITY OF SANTO TOMAS 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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UNIVERSITY OF SANTO TOMAS VII.

Definition of

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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UNIVERSITY OF SANTO TOMAS 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 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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UNIVERSITY OF SANTO TOMAS 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: , 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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UNIVERSITY OF SANTO TOMAS 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 ed 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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UNIVERSITY OF SANTO TOMAS 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 costeffective 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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UNIVERSITY OF SANTO TOMAS 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 ing 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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UNIVERSITY OF SANTO TOMAS 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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UNIVERSITY OF SANTO TOMAS 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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UNIVERSITY OF SANTO TOMAS 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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UNIVERSITY OF SANTO TOMAS 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 + 𝑑𝑋 2 + 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

unemployment rate (Shimer, 2005).

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the

vacancy

rate

and

the


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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UNIVERSITY OF SANTO TOMAS 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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UNIVERSITY OF SANTO TOMAS 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 ment 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 (S) 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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UNIVERSITY OF SANTO TOMAS IV.

CONCEPTUAL FRAMEWORK

A. The Model used by the Researchers in the Analysis of EducationOccupation 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

Education Occupation

Matched or Unmatche d

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Effect

Wage

UNIVERSITY OF SANTO TOMAS 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.

Job- vacancy rate

Unemployment rate

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UNIVERSITY OF SANTO TOMAS CHAPTER 3: DATA AND METHODOLOGY

A. The Model used by the Researchers in the Analysis of EducationOccupation 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 s 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 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

27

UNIVERSITY OF SANTO TOMAS 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.

28

UNIVERSITY OF SANTO TOMAS 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

29

UNIVERSITY OF SANTO TOMAS 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

30

UNIVERSITY OF SANTO TOMAS 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.

31


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.

32


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

33

UNIVERSITY OF SANTO TOMAS 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.

HOURLY WAGE/ EARNINGS 350 300 250 200

HOURLY WAGE/ EARNINGS

150 100 50 0 0

10

20

30

LOG OF HOURLY EARNINGS 7 6 5 4 LOG OF HOURLY EARNINGS

3 2 1 0 0

10

20

30

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.

34

UNIVERSITY OF SANTO TOMAS 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.

35

UNIVERSITY OF SANTO TOMAS 2. Social Sciences, Business and Law Under the Field of Social Sciences, Business and Law (63), the regression model is: log of hourly wages= 4.270 + 0.662MATCH

This presents that on the average,

for every unit increase in the MATCH

variable, the log of hourly earnings would be increasing by 0.662 peso.



36

UNIVERSITY OF SANTO TOMAS 3. Services

Under the Field of Services (68), the regression model is: log of hourly wages= 4.282 + 0.653MATCH




37


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 ed 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.

38

UNIVERSITY OF SANTO TOMAS 4. Humanities and Arts

Under the Field of Humanities and Arts (62), the regression model is: log of hourly wages= 4.437 - 0.010MATCH

This presents that on the average, for every unit increase in the MATCH variable, the log of hourly earnings would be decreasing by 0.010 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= 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 Study pursues with the occupation related to his/her field of study can earn lower wages rather than having occupation not related to his/ her field of study.

39

UNIVERSITY OF SANTO TOMAS 5. Science

Under the Field of Science (64), the regression model is: log of hourly wages= 4.479 + 0.051MATCH


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= 0.197020752163872


40

UNIVERSITY OF SANTO TOMAS 6. Engineering, Manufacturing and Construction

Under the Field of Engineering, Manufacturing and Construction (65), the regression model is: log of hourly wages= 4.851- 0.193MATCH




41

UNIVERSITY OF SANTO TOMAS 7. Agriculture

Under the Field of Agriculture (66), the regression model is: log of hourly wages= 4.447- 0.243MATCH


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= 29- 1-1 =27 T critical= 1.703 T-stat= -0.913513876447283


42


8. Health and Welfare

Under the Field of Health and Welfare (67), the regression model is: log of hourly wages= 4.694- 0.468MATCH




43


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. Jobvacancy Unemployment Year

Rate

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

44


Correlation of Unemployment rates and Job-vacancy rates Unemployment Job-vacancy rate

rate

Job-vacancy rate

1

Unemployment rate

0.768721874

1

Table 3. Correlation between job-vacancy and unemployment rates

The correlation coefficient between the jobvacancy 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

45

UNIVERSITY OF SANTO TOMAS 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 ed 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.

46


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 ed 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.

47

UNIVERSITY OF SANTO TOMAS 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 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

48

UNIVERSITY OF SANTO TOMAS 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.

49

UNIVERSITY OF SANTO TOMAS 

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

50

UNIVERSITY OF SANTO TOMAS 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.

51

UNIVERSITY OF SANTO TOMAS BIBLIOGRAPHY Books: 

Gujarati. 2004. Basic Econometrics, Fourth Edition. The McGraw−Hill Companies, 2004.



Mincer, J.

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

Samson, J. et. Al. 2003. The Impact of Occupational Mismatch and Education on Wages. University of the Philippines. School of Economics.

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

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(BITS

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from

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National Statistics Office’s First Stage of Tertiary/ Baccalaurate Education.



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52


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Ahola, S. 1999. The Matching Of Educational And Occupational Structures In Sweden And Finland.



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

Allen, J. & van der Velden, R. 2001. Educational Mismatches Versus Skill Mismatches: Effects on Wages, Job Satisfaction and On-theJob Search. Oxford Economic Papers 3 (2001), 432-452. Oxford University

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

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

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

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

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

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55


http://www.investopedia.com//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



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

http://www.thefreedictionary.com/



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

56

UNIVERSITY OF SANTO TOMAS 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 61401 61401 61401 61401 61401 61404 61404 61404 61404 61404 61404 61404 61404 61404 61404 61404 61404 61404 61404 61408 61408

TEACHER TRAINING AND EDUCATION SCIENCES PROGRAMS Programs in General Teacher Training Bachelor of Elementary Education Bachelor of Secondary Education Bachelor of Science in Elementary and Secondary Education Bachelor of Science in Pedagogy Programs in Teacher Training with Specialization in Nonvocational Subjects Bachelor of Home Economics and Livelihood Education for Teachers Bachelor of Physical Education Bachelor of Sports Science Bachelor of Technology and Home Economics for Teachers Bachelor of Arts in Language Education for Teachers Bachelor of Science in Chemistry for Teachers Bachelor of Science in English Education as Secondary Language Bachelor of Science in Language Education for Teachers Bachelor of Science in Mathematics for Teachers Bachelor of Science in Music Education Bachelor of Science in Physical Education Bachelor of Science in Physics for Teachers Bachelor of Science in Religious Education Programs in Teacher Training for Teaching Practical or Vocational Subjects Bachelor of Science in Industrial Education

61408 61412 61412 61412 61416 61422 61422 61472 61472 61499 61499 61499 61499 61499 61499 61499 61499

Bachelor of Science in Technician Teacher Education Programs in Teacher Training for Teaching Preschool or Kindergarten Bachelor of Science in Early Childhood Education Bachelor of Science in Kindergarten/Preschool Education Programs in Teacher Training for Teachers in Adult Education Programs in Teacher Training for Teachers in Special Education Bachelor of Special Education Programs in Education Science in of Teaching Bachelor of Science in Guidance and Counseling Other Programs in Teacher Training and Education Sciences Bachelor of Science in Agricultural Education Bachelor of Science in Business/Commercial Education Bachelor of Science in Extension Education Bachelor of Science in Fishery Education Bachelor of Science in Nursing Education Bachelor of Science in Nutrition and Dietetics for Teachers Bachelor of Science in Secretarial Education HUMANITIES AND ARTS

621 62101 62101 62101 62104 62108 62122 62122 62122 62132 62132 62132 62132 62132 62132 62152 62152 62199

ARTS PROGRAMS General Programs in Art Studies Bachelor of Digital Arts Bachelor of Science in Fine Arts/Bachelor of Fine Arts Programs in Drawing and Painting Programs in Sculpturing Programs in Music Bachelor of Music Liturgy Bachelor of Science in Music/Bachelor of Music Programs in Drama Bachelor of Performing Arts Bachelor of Arts in Speech and Drama Bachelor of Arts in Speech and Theater Arts Bachelor of Arts in Theater Arts Bachelor of Science in Speech and Drama Programs in Interior Design Bachelor of Science in Interior Design Other Programs in Arts

62199

Bachelor of Arts in Film and Audio-Visual Communication

622 62201

HUMANITIES PROGRAMS General Programs in Humanities

57

UNIVERSITY OF SANTO TOMAS 62201 62211 62211 62211 62211 62211 62215 62215 62221 62231 62231 62241 62241 62241 62251 62251 62251 62261 62271 62271 62271 62281 62281 62281 62281 62281 62281 62299

Bachelor of Arts in Humanities Programs in the Current or Vernacular Language and Its Literature Bachelor of Arts in English Bachelor of Arts in English Literature Bachelor of Arts in Filipino Bachelor of Arts in Philippine Literature Programs in Other Living Languages and Their Literature Bachelor of Arts in European Languages Programs in "Dead" Languages and Their Literature Programs in Linguistics Bachelor of Arts in Linguistics Programs in Comparative Literature Bachelor of Arts in Comparative Literature Bachelor of Arts in Literature Programs in History Bachelor of Arts in Development Studies Bachelor of Arts in History Programs in Archeology Programs in Philosophy Bachelor of Arts in Classical/Philosophy/Bachelor of Classical/Philosophy Bachelor of Arts in Philosophy/Bachelor of Philosophy Programs in Religion and Theology Bachelor of Evangelical Ministry Bachelor of Arts in Religion Bachelor of Arts in Religious Studies Bachelor of Arts in Divinity/Bachelor of Divinity Bachelor of Arts in Theology/Bachelor of Theology Other Programs in Humanities SOCIAL SCIENCES, BUSINESS, AND LAW

631 63101 63101

SOCIAL AND BEHAVIORAL SCIENCE PROGRAMS General Programs in Social and Behavioral Sciences Bachelor of Arts in Behavioral Science

63101 63101

Bachelor of Arts in Social Science Bachelor of Arts in Human Behavior Technology/Bachelor of Human Behavior Technology Bachelor of Science in Behavioral Science Bachelor of Science in Human Behavior Technology Programs in Economics Bachelor of Arts in Economics Bachelor of Arts in Applied Economics/Bachelor of Applied Economics Bachelor of Science in Applied Economics Bachelor of Science in Business Economics Bachelor of Science in Economics Programs in Political Science Bachelor of Arts in Political Science/Bachelor in Political Science Bachelor of Science in Foreign Service Bachelor of Science in International Relations Bachelor of Science in Political Economy Programs in Sociology Bachelor of Arts in Applied Sociology Bachelor of Arts in Sociology Bachelor of Science in Sociology Programs in Demography Bachelor of Science in Demography Programs in Anthropology Bachelor of Arts in Anthropology Programs in Psychology Bachelor of Arts in Applied Psychology Bachelor of Science in Clinical Psychology Bachelor of Science in Industrial and Organizational Psychology Bachelor of Science in Psychology Programs in Geography Bachelor of Science in Geography Programs in Studies of Regional Cultures Bachelor of Arts in Arabic/Islamic Studies Bachelor of Arts in International Studies Bachelor of Arts in Philippine Arts Bachelor of Arts in Philippine Studies Other Programs in Social and Behavioral Sciences

63101 63101 63112 63112 63112 63112 63112 63112 63122 63122 63122 63122 63122 63132 63132 63132 63132 63133 63133 63142 63142 63152 63152 63152 63152 63152 63162 63162 63172 63172 63172 63172 63172 63199

58

UNIVERSITY OF SANTO TOMAS 632 63201 63201 63201 63202 63202 63202 63202 63202 63204 63204 63204 63207 63207 63222 63222 63222 63229 63229 63229 63229 63229 634 63401 63401 63401 63401 63401 63401 63401 63401 63401 63401 63404 63404 63404 63404 63404 63432 63432 63432 63432 63432 63434 63434 63434 63434 63436 63436 63436 63436 63439 63439 63439 63439 63439 63439 63439 63439 63439 63439 63439 63439 63439 63439 63439

JOURNALISM AND INFORMATION PROGRAMS Programs in General Communication Arts Bachelor of Arts in Communication Bachelor of Arts in Media Studies Programs in Journalism Bachelor of Arts in Business Journalism/Bachelor in Business Journalism Bachelor of Arts in Journalism/Bachelor in Journalism Bachelor of Science in Business Journalism Bachelor of Science in Journalism Programs in Radio and Television Broadcasting Bachelor of Arts in Broadcast Communication Bachelor of Science in Broadcast Communication Programs in Public Relations Bachelor of Arts in Public Relations Programs in Library Science Bachelor of Arts in Library and Information Science/Bachelor of Library and Information Science Bachelor of Arts in Library Science/Bachelor of Library Science Other Programs in Journalism and Information Bachelor of Arts in Communication Arts/Mass Communication Bachelor of Arts in Communication Research Bachelor of Arts in Organizational Communication Bachelor of Science in Mass Communication BUSINESS AND ISTRATION PROGRAMS General Programs in Business istration/Commerce Bachelor of Arts in Business istration/Bachelor in Business istration Bachelor of Arts in Entrepreneurial Management/Bachelor in Entrepreneurial Management Bachelor of Arts in Business Management/Bachelor of Business Management Bachelor of Arts in Management and Social Work /Bachelor of Management and Social Work Bachelor of Science in istration Bachelor of Science in Business istration Bachelor of Science in Business Management Bachelor of Science in Commerce Bachelor of Science in Management Programs in Secretarial Bachelor of Science in Airline Secretarial/istration Bachelor of Science in Computer Secretarial Bachelor of Science in Office istration/Technology Bachelor of Science in Secretarial istration Programs in Business istration with Specialization in ancy Bachelor of Science in ancy Bachelor of Science in Business istration and ancy Bachelor of Science in Computer ing and Management Bachelor of Science in Management and ancy Programs in Business istration with Specialization in Marketing Bachelor of Arts in Advertising/Bachelor of Advertising Bachelor of Arts in Advertising and Public Relations/Bachelor of Advertising and Public Relations Bachelor of Science in Marketing Programs in Business istration with Specialization in Finance and Investment Bachelor of Science in Finance Bachelor of Science in Real Estate Bachelor of Science in Banking and Finance/Bachelor in Banking and Finance Programs in Business istration with Other Specialization Bachelor of Arts in Legal Management Bachelor of Arts in Business Engineering/Bachelor in Business Engineering Bachelor of Arts in Agricultural Entrepreneurship/Bachelor of Agricultural Enterpreneurship Bachelor of Arts in Business Distributive Arts/Bachelor of Business Distributive Arts Bachelor of Arts in Computer Management/Bachelor of Computer Management Bachelor of Arts in Industrial Management/Bachelor of Industrial Management Bachelor of Arts in Transportation Management/Bachelor of Transportation Management Bachelor of Science in Agri-Business Management Bachelor of Science in Business Enterpreneurship Bachelor of Science in Business Technology Bachelor of Science in Economics and Cooperatives Bachelor of Science in Fishery Business Management Bachelor of Science in Home Arts and Enterpreneurship Bachelor of Science in Industrial Management

59

UNIVERSITY OF SANTO TOMAS 63452 63452 63452

Programs in Public istration Bachelor of Arts in Public istration/Bachelor of Public istration Bachelor of Science in Public istration

63462 63462 63462 63462 63462 63462 63462 63462 63462 63462 63499 63499 63499 63499 63499 63499 63499

Programs in Institutional istration/Management Bachelor of Arts in Port istration/Bachelor of Port istration Bachelor of Science in Airline Business istration/Management Bachelor of Science in Airline Management Bachelor of Science in Airline Management and ancy Bachelor of Science in Customs istration Bachelor of Science in Food Service istration Bachelor of Science in Hospital istration Bachelor of Science in Postal Management Bachelor of Science in Shipping Management Other Programs in Business istration/Management Bachelor of Arts in Legal and Indigenous Studies Bachelor of Arts in Cooperatives/Bachelor of Cooperatives Bachelor of Science in Cooperative Management Bachelor of Science in Maritime Management Bachelor of Science in Recreation Management Bachelor of Science in Supply Management

638 63801 63801 63801

LAW PROGRAMS General Programs in Law Bachelor of Laws (LL.B.)/Juris Doctor (J.D.) Bachelor of Science in Jurisprudence SCIENCE

642 64202 64202 64202 64202 64202 64202 64202 64202 64202 64202 64202 64202

LIFE SCIENCES PROGRAMS Programs in Biological Science Bachelor of Science in Applied Biology Bachelor of Science in Biochemistry Bachelor of Science in Biological Science Bachelor of Science in Biology Bachelor of Science in Botany Bachelor of Science in Entomology Bachelor of Science in Human Biology Bachelor of Science in Marine Biology Bachelor of Science in Microbiology Bachelor of Science in Molecular Biology and Biotechnology Bachelor of Science in Pharmacology

64202 64202 64202 64209 64209 64209 64209

Bachelor of Science in Physiology Bachelor of Science in Plant Science Bachelor of Science in Zoology Other Programs in Life Sciences Bachelor of Arts in Applied Science/Bachelor of Applied Science Bachelor of Science in General Science Bachelor of Science in Natural Science

644 64412 64412 64412 64412 64412 64422 64422 64422 64432 64432 64432 64432 64432 64442 64442 64452 64452 64462 64462 64462

PHYSICAL SCIENCES PROGRAMS Programs in Chemistry Bachelor of Science in Chemical Research Bachelor of Science in Chemical Technology Bachelor of Science in Chemistry Bachelor of Science in Industrial Chemistry Programs in Geological Science Bachelor of Science in Geology Bachelor of Science in Volcanology Programs in Physics Bachelor of Science in Applied Physics Bachelor of Science in Metallurgy Bachelor of Science in Physics Bachelor of Science in Physics-Mathematics Programs in Astronomy Bachelor of Science in Astronomy Programs in Meteorology Bachelor of Science in Meteorology Programs in Oceanography Bachelor of Science in Marine Science Bachelor of Science in Oceanography

646

MATHEMATICS AND STATISTICS PROGRAMS

60

UNIVERSITY OF SANTO TOMAS 64601 64601 64611 64611 64611 64611 64621

General Programs in Mathematics Bachelor of Science in Mathematics Programs in Statistics Bachelor of Science in Applied Statistics Bachelor of Science in Experimental Statistics Bachelor of Science in Statistics Programs in Actuarial Science

64621 64699 64699

Bachelor of Science in Actuarial Science Other Programs in Mathematics Bachelor of Science in Applied Mathematics

648 64841 64841 64841 64841 64841 64841 64841 64841 64841 64841 64841 64841 64844 64844 64844

COMPUTING/INFORMATION TECHNOLOGY PROGRAMS Programs in Computer Science and Information Technology Bachelor of Arts in Information Technology/Bachelor in Information Technology Bachelor of Science in Business Computer Applications Bachelor of Science in Computer Applications Bachelor of Science in Computer Data Processing Management Bachelor of Science in Computer Science Bachelor of Science in Computer Studies Bachelor of Science in Information and Computer Science Bachelor of Science in Information System/Management Bachelor of Science in Information Technology Bachelor of Science in Management Information System Bachelor of Science in Software Technology Programs in Electronic Data Processing Bachelor of Science in Computer Data Processing and Information Management Bachelor of Science in Data Processing ENGINEERING, MANUFACTURING, AND CONSTRUCTION

652 65204 65204 65204 65204 65204 65204 65204 65204 65204 65204 65204 65204 65204 65212 65212

ENGINEERING AND ENGINEERING TRADES PROGRAMS Programs in Aeronautical Engineering Bachelor of Science in Aeronautical Engineering Bachelor of Science in Aerospace Engineering Bachelor of Science in Air Transportation Bachelor of Science in Aircraft Maintenance Engineering Bachelor of Science in Aircraft Maintenance Technology Bachelor of Science in Aircraft Technology Bachelor of Science in Aviation Bachelor of Science in Aviation Electronics Engineering Bachelor of Science in Avionics Engineering Bachelor of Science in Avionics Technology Bachelor of Science in Electrical Engineering Avionics Bachelor of Science in Flying Technology Programs in Chemical Engineering Bachelor of Science in Ceramics Engineering

65212 65212 65212 65216 65216 65216 65218 65218 65222 65222 65222 65222 65222 65222 65222 65222 65222 65222 65222 65226 65226 65226 65226 65226 65226 65226

Bachelor of Science in Chemical Engineering Bachelor of Science in Chemical Engineering Technology Bachelor of Science in Textile Engineering Programs in Civil Engineering Bachelor of Science in Civil Engineering Bachelor of Science in Construction Technology Programs in Geodetic Engineering Bachelor of Science in Geodetic Engineering Programs in Electrical, Electronics and Computer Engineering Bachelor of Science in Communications Engineering Bachelor of Science in Computer Engineering Bachelor of Science in Computer Technology Bachelor of Science in Electrical Engineering Bachelor of Science in Electrical Engineering Technology Bachelor of Science in Electrical Technology Bachelor of Science in Electronics and Communications Engineering Bachelor of Science in Electronics Engineering Bachelor of Science in Electronics Technology Bachelor of Science in Instrumentation and Control Engineering Programs in Industrial Engineering Bachelor of Science in Industrial and Management Engineering Bachelor of Science in Industrial Design Bachelor of Science in Industrial Engineering Bachelor of Science in Industrial Technology Bachelor of Science in Management Engineering Bachelor of Science in Manufacturing Engineering

61

UNIVERSITY OF SANTO TOMAS 65232 65232 65236 65236 65242 65242 65242 65242 65242 65250 65250 65250

Programs in Metallurgical Engineering Bachelor of Science in Metallurgical Engineering Programs in Mining Engineering Bachelor of Science in Mining Engineering Programs in Mechanical Engineering Bachelor of Science in Automotive Technology Bachelor of Science in Geothermal Engineering Bachelor of Science in Mechanical Engineering Bachelor of Science in Mechanical Technology Programs in Sanitary Engineering Bachelor of Science in Environmental and Sanitary Engineering Bachelor of Science in Environmental Engineering

65250 65253 65253 65253 65263 65263 65281 65281 65281 65299 65299 65299 65299 65299

Bachelor of Science in Sanitary Engineering Programs in Agricultural Engineering Bachelor of Science in Agricultural Engineering Bachelor of Science in Aquatic Resource Engineering Programs in Forestry Engineering Bachelor of Science in Forest Products Engineering Programs in Marine Engineering Bachelor of Science in Marine Engineering Bachelor of Science in Naval Architecture and Marine Engineering Other Programs in Engineering Bachelor of Arts in Technology/Bachelor of Technology Bachelor of Science in Electronics and Computer Technology Bachelor of Science in Food Engineering Bachelor of Science in Petroleum Engineering

654 65476 65476 65476

MANUFACTURING AND PROCESSING PROGRAMS Programs in Clothing and Related Trades Bachelor of Science in Clothing Technology Bachelor of Science in Garment/Textile Technology

658 65801 65801 65812 65812 65822 65822

ARCHITECTURE AND BUILDING PROGRAMS General Programs in Architecture and Town Planning Bachelor of Science in Architecture Programs in Landscape Architecture Bachelor of Science in Landscape Architecture Programs in Town Planning Bachelor of Science in Town and Country Planning AGRICULTURE

662 66201 66201 66203 66203 66203 66203 66206 66206 66206 66208 66208 66212 66212 66222 66222 66226 66249 66249 66249 66249 66249 66249 66249 66262 66262 66262 66262

AGRICULTURE, FORESTRY, AND FISHERY PROGRAMS General Programs in Agriculture Bachelor of Arts in Agricultural Technology/Bachelor of Agricultural Technology Bachelor of Science in Agriculture Programs in Animal Husbandry Bachelor of Science in Animal Husbandry Bachelor of Science in Animal Science Bachelor of Science in Animal Technology Programs in Horticulture Bachelor of Arts in Horticulture Management/Bachelor of Technology in Horticulture Management Bachelor of Science in Horticulture Programs in Agronomy Bachelor of Science in Agronomy Programs in Agricultural Economics Bachelor of Science in Agricultural Economics Programs in Food Science and Technology Bachelor of Science in Food Technology Programs in Soil and Water Sciences Other Programs in Agriculture Bachelor of Science in Agricultural istration Bachelor of Science in Agricultural Chemistry Bachelor of Science in Agricultural Development Bachelor of Science in Agricultural Management Bachelor of Science in Rice Technology Bachelor of Science in Sugar Technology Programs in Forestry Bachelor of Arts in Agro-Forestry Technology/Bachelor in Agro-Forestry Technology Bachelor of Science in Agro-Forestry Bachelor of Science in Forestry

62

UNIVERSITY OF SANTO TOMAS 66272 66272 66272 66272 66272 66272

Programs in Fishery Science and Technology Bachelor of Science in Aquaculture Bachelor of Science in Aquatic Resource Management and Technology Bachelor of Science in Fisheries Bachelor of Science in Fishing Technology Bachelor of Science in Inland Fisheries

664 66432 66432

VETERINARY PROGRAMS Programs in Veterinary Medicine Bachelor of Science in Veterinary Technology HEALTH AND WELFARE

672 67202 67202 67202

HEALTH PROGRAMS Programs in Hygiene Bachelor of Science in Community/Public Health Bachelor of Science in Sanitary Science

67206 67206 67206 67208 67208 67208 67208 67208 67212 67212 67217 67217 67230 67230 67242 67242 67252 67252 67252 67252 67262 67262 67272 67272 67299 67299 67299

Programs in Medicine Bachelor of Arts in Basic Medical Sciences Doctor of Medicine Programs in Rehabilitation Medicine Bachelor of Science in Occupational Therapy Bachelor of Science in Physical Therapy Bachelor of Science in Respiratory Therapy Bachelor of Science in Speech Pathology Programs in Nursing Bachelor of Science in Nursing Programs in Medical X-Ray Techniques Bachelor of Science in Radiologic Technology Programs in Medical Technology Bachelor of Science in Medical Technology Programs in Dentistry Doctor of Dental Medicine Programs in Pharmacy Bachelor of Science in Industrial Pharmacy Bachelor of Science in Pharmaceutical Chemistry Bachelor of Science in Pharmacy Programs in Optometry Doctor of Optometry Programs in Nutrition and Dietetics Bachelor of Science in Nutrition and Dietetics Other Programs in Medical Diagnostic and Treatment Bachelor of Science in Paramedics Bachelor of Science in Rural Medicine

676 67632 67632 67632 67652 67652 67652 67652

SOCIAL SERVICES PROGRAMS Programs in Social Welfare Bachelor of Arts in Social Services/Social Work Bachelor of Science in Social Services/Social Work Programs in Community Development Bachelor of Science in Community Development Bachelor of Science in Development of Multi-Cultural Communities Bachelor of Science in Rural Development Management

SERVICES 681 68101 68101 68101 68101 68132 68134 68134 68172 68172 68182 68182 68182 68182 68182

PERSONAL SERVICES PROGRAMS General Programs in Home Economics (Domestic Science) Bachelor of Science in Family and Child Development Bachelor of Science in Home Economics Bachelor of Science in Human Ecology Programs in Home Economics with Emphasis on Household Arts Other Programs in Home Economics Bachelor of Science in Home Technology Programs in Hotel and Restaurant Trades Bachelor of Science in Hotel and Restaurant Management Programs in Tourism Bachelor of Arts in Tourism Bachelor of Science in Tourism Bachelor of Science in Tourism and Hotel and Restaurant Management Bachelor of Science in Tourism and Travel Management

63

UNIVERSITY OF SANTO TOMAS 684 68404 68404 68404

TRANSPORT SERVICES PROGRAMS Programs in Nautical Science Bachelor of Science in Marine Transportation Bachelor of Science in Nautical Science

685 68552 68552

68552 68552

ENVIRONMENTAL PROTECTION PROGRAMS Programs in Environmental Studies Bachelor of Arts in Technology in Environmental Management/Bachelor of Technology in Environmental Management Bachelor of Science in Coastal Resource Management Bachelor of Science in Ecology Bachelor of Science in Environmental Development/Environmental Hygiene/Environmental Science Bachelor of Science in Environmental Management Bachelor of Science in Environmental Planning

686 68613 68613 68613 68613

SECURITY SERVICES PROGRAMS Programs in Criminal Justice Education Bachelor of Science in Criminal Justice/Criminology Bachelor of Science in Forensic Science Bachelor of Science in Industrial Security Management

68613 68617 68619 68619 68619

Bachelor of Science in Police/Law Enforcement istration Programs in Military Other Programs in Civil Security Bachelor of Arts in Peace and Security Studies Bachelor of Science in Peace and Security Studies

68552 68552 68552

64


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

Officials of Government and Special-Interest

(63)

Organizations,

Corporate

Executives

and

Specialized Managers, General Managers or Managing-Proprietors, Supervisors, Teaching Professionals, Other Professionals, Related Associate Customer

Professionals, Services

Office

Clerks,

Clerks, Models,

Salespersons and Demonstrators, Other Craft and Related Trades Workers, Sales and Services. Science (64)

Physicists,

Life

Professionals,

Science Teaching

and

Health

Professionals,

Physical Science and Engineering Associate Professionals,

Life

Science

and

Health

Associate Professionals. Engineering,

Manufacturing

and Corporate

65

Executives

and

Specialized

UNIVERSITY OF SANTO TOMAS Construction (65)

Managers, General Managers or ManagingProprietors, 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.

66

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

67

UNIVERSITY OF SANTO TOMAS APPENDIX 4: Regression Results for the 8 Fields of Study

1. Education Coefficients

a

Standardized Unstandardized Coefficients

Coefficients

B

Std. Error

Beta

(Constant)

4.482

.129

MATCH

.965

.380

Model 1

a.

.461

t

Sig.

34.765

.000

2.542

.018

t

Sig.

34.143

.000

3.530

.002

t

Sig.

30.246

.000

2.259

.034

Dependent Variable: LOG OF HOURLY EARNINGS

2. Social Sciences, Business and Law Coefficients

a


Coefficients

B

Std. Error

Beta

(Constant)

4.270

.125

MATCH

.662

.188

Model 1

a.

.577


3. Services Coefficients

a


Coefficients

B

Std. Error

Beta

(Constant)

4.282

.142

MATCH

.653

.289

Model 1

.426

a. Dependent Variable: LOG OF HOURLY EARNINGS

68


4. Humanities and Arts Coefficients

a


Coefficients

B

Std. Error

Beta

(Constant)

4.437

.119

MATCH

-.010

.212

Model 1

-.012

t

Sig.

37.201

.000

-.049

.962

5. Science Coefficients

a


Coefficients

B

Std. Error

Beta

(Constant)

4.479

.114

MATCH

.051

.259

Model 1

.040

t

Sig.

39.402

.000

.197

.845


6. Engineering, Manufacturing and Construction Coefficients

a


Coefficients

B

Std. Error

Beta

(Constant)

4.851

.167

MATCH

-.193

.275

Model 1

a.

-.139


69

t

Sig.

28.988

.000

-.703

.488

UNIVERSITY OF SANTO TOMAS 7. Agriculture Coefficients

a


Coefficients

B

Std. Error

Beta

(Constant)

4.447

.148

MATCH

-.243

.266

Model 1

-.173

t

Sig.

29.997

.000

-.914

.369


8. Health and Welfare Coefficients

a


Coefficients

B

Std. Error

Beta

(Constant)

4.694

.140

MATCH

-.468

.296

Model 1

-.367


70

t

Sig.

33.625

.000

-1.580

.134

UNIVERSITY OF SANTO TOMAS APPENDIX 5: DATA FOR EDUCATION (61) TOTAL NO. OF HOURS

NORMAL

WORKED

WORKING

DURING

HOURS WORKING

DURING

HOURLY

LOG OF

BASIC

PAST

HOURS

THE PAST

WAGE/

HOURLY

PAY

WEEK

PER DAY

WEEK

EARNINGS

EARNINGS

OCCUPATION

THE

Officials of Government and Special-Interest Organizations

1499

48

8

6

249.833333

5.520794

Corporate Executives and Specialized Managers

1499

48

8

6

249.833333

5.520794

Supervisors

1499

48

8

6

249.833333

5.520794

699

48

8

6

116.5

4.757891

1499

48

8

6

249.833333

5.520794

899

48

8

6

149.833333

5.009524

Physicists Mathematical and Engineering Science Professionals Life Science and Health Professionals Teaching Professionals Other Professionals

1499

48

8

6

249.833333

5.520794

Physical Science and Engineering Associate Professionals

399

48

8

6

66.5

4.197202

Life Science and Health Associate Professionals

599

48

8

6

99.8333333

4.603502

1999

48

8

6

333.166667

5.808643

Related Associate Professionals

599

48

8

6

99.8333333

4.603502

Office Clerks

399

48

8

6

66.5

4.197202

Customer Services Clerks

299

48

8

6

49.8333333

3.908684

Personal and Protective Service Workers

1499

48

8

6

249.833333

5.520794

Models Salespersons and Demonstrators

299

48

8

6

49.8333333

3.908684

Mining Construction and Related Trade Workers

299

39

8

4.875

61.3333333

4.116323

Metal Machinery and Related Trades Workers

199

48

8

6

33.1666667

3.501545

Precision Handicraft Printing and Related Trades Workers

299

39

8

4.875

61.3333333

4.116323

Other Craft and Related Trades Workers

399

48

8

6

66.5

4.197202

Stationary Plant and Related Operators

399

48

8

6

66.5

4.197202

Machine Operators and Assemblers

399

48

8

6

66.5

4.197202

Drivers and Mobile Plant Operators

499

48

8

6

83.1666667

4.420847

Sales and Services Elementary Occupations

199

19

8

2.375

83.7894737

4.428307

Agricultural Forestry Fishery and Related Laborers

199

48

8

6

33.1666667

3.501545

Laborers in Mining Construction Manufacturing and Transport

399

48

8

6

66.5

4.197202

Armed Forces

499

48

8

6

83.1666667

4.420847

Teaching Associate Professionals

71

M

UNIVERSITY OF SANTO TOMAS APPENDIX 6: DATA FOR HUMANITIES AND ARTS (62) TOTAL NO. OF HOURS

NORMAL

WORKED

WORKING

DURING

OCCUPATION

HOURS

THE

WORKING

DURING

HOURLY

LOG OF

BASIC

PAST

HOURS

THE PAST

WAGE/

HOURLY

PAY

WEEK

PER DAY

WEEK

EARNINGS

EARNINGS


499

48

8

6

83.16667

4.420847


599

58

8

7.25

82.62069

4.41426

1499

48

8

6

249.8333

5.520794

Physicists Mathematical and Engineering Science Professionals

799

48

8

6

133.1667

4.891601

Life Science and Health Professionals

899

48

8

6

149.8333

5.009524

Teaching Professionals

499

48

8

6

83.16667

4.420847

Other Professionals

699

58

8

7.25

96.41379

4.568649


399

48

8

6

66.5

4.197202


299

19

8

2.375

125.8947

4.835446

Office Clerks

299

48

8

6

49.83333

3.908684


399

48

8

6

66.5

4.197202


399

58

8

7.25

55.03448

4.00796


499

48

8

6

83.16667

4.420847


499

39

8

4.875

102.359

4.628486


299

39

8

4.875

61.33333

4.116323


199

29

8

3.625

54.89655

4.005451


399

48

8

6

66.5

4.197202


299

48

8

6

49.83333

3.908684

Armed Forces

699

58

8

7.25

96.41379

4.568649

Supervisors

72

M

UNIVERSITY OF SANTO TOMAS APPENDIX 7: DATA FOR SOCIAL SCIENCES, BUSINESS & LAW (63) TOTAL NO. OF HOURS

NORMAL

WORKED

WORKING

DURING

OCCUPATION

HOURS

THE

WORKING

DURING

HOURLY

LOG OF

BASIC

PAST

HOURS

THE PAST

WAGE/

HOURLY

PAY

WEEK

PER DAY

WEEK

EARNINGS

EARNINGS


1499

48

8

6

249.8333333

5.520794


1499

48

8

6

249.8333333

5.520794

General Managers or Managing-Proprietors

1499

58

8

7.25

206.7586207

5.331552

Supervisors

1499

48

8

6

249.8333333

5.520794


499

48

8

6

83.16666667

4.4208466


299

48

8

6

49.83333333

3.9086841


1499

48

8

6

249.8333333

5.520794

Other Professionals

1499

48

8

6

249.8333333

5.520794


399

48

8

6

66.5

4.1972019


699

48

8

6

116.5

4.7578913


199

19

8

2.375

83.78947368

4.4283074


499

48

8

6

83.16666667

4.4208466

Office Clerks

399

48

8

6

66.5

4.1972019


599

48

8

6

99.83333333

4.6035021


499

48

8

6

83.16666667

4.4208466


499

48

8

6

83.16666667

4.4208466


499

48

8

6

83.16666667

4.4208466


299

48

8

6

49.83333333

3.9086841


599

48

8

6

99.83333333

4.6035021


399

29

8

3.625

110.0689655

4.7011071


399

48

8

6

66.5

4.1972019


399

48

8

6

66.5

4.1972019


499

48

8

6

83.16666667

4.4208466


299

48

8

6

49.83333333

3.9086841


199

48

8

6

33.16666667

3.5015454


299

48

8

6

49.83333333

3.9086841

Armed Forces

699

48

8

6

116.5

4.7578913

73

MA

UNIVERSITY OF SANTO TOMAS APPENDIX 8: DATA FOR SCIENCE (64) TOTAL NO. OF HOURS

NORMAL

WORKED

WORKING

DURING

OCCUPATION

HOURS

THE

WORKING

DURING

HOURLY

LOG OF

BASIC

PAST

HOURS

THE PAST

WAGE/

HOURLY

PAY

WEEK

PER DAY

WEEK

EARNINGS

EARNINGS


1499

48

8

6

249.833

5.520794


1499

48

8

6

249.833

5.520794

399

48

8

6

66.5

4.1972019

1499

48

8

6

249.833

5.520794


399

48

8

6

66.5

4.1972019


299

48

8

6

49.8333

3.9086841

1499

48

8

6

249.833

5.520794


499

48

8

6

83.1667

4.4208466


599

48

8

6

99.8333

4.6035021


599

48

8

6

99.8333

4.6035021


799

48

8

6

133.167

4.8916015

Office Clerks

499

48

8

6

83.1667

4.4208466


599

48

8

6

99.8333

4.6035021


499

48

8

6

83.1667

4.4208466


299

48

8

6

49.8333

3.9086841


399

48

8

6

66.5

4.1972019


399

48

8

6

66.5

4.1972019


299

48

8

6

49.8333

3.9086841


399

48

8

6

66.5

4.1972019


399

48

8

6

66.5

4.1972019


399

48

8

6

66.5

4.1972019


499

48

8

6

83.1667

4.4208466


199

19

8

2.375

83.7895

4.4283074


299

48

8

6

49.8333

3.9086841

Armed Forces

399

48

8

6

66.5

4.1972019

Other Occupations Not Classifiable

599

48

8

6

99.8333

4.6035021

Supervisors Physicists Mathematical and Engineering Science Professionals

Other Professionals

74

MA

UNIVERSITY OF SANTO TOMAS APPENDIX 9: DATA FOR Engineering, Manufacturing and Construction (65) TOTAL NO. OF HOURS

NORMAL

WORKED

WORKING

DURING

OCCUPATION

HOURS

THE

WORKING

DURING

HOURLY

LOG OF

BASIC

PAST

HOURS

THE PAST

WAGE/

HOURLY

PAY

WEEK

PER DAY

WEEK

EARNINGS

EARNINGS


1499

19

8

2.375

631.1579

6.4475561


1499

48

8

6

249.8333

5.520794


1499

48

8

6

249.8333

5.520794

Supervisors

1499

48

8

6

249.8333

5.520794


1499

48

8

6

249.8333

5.520794


1499

48

8

6

249.8333

5.520794


1499

48

8

6

249.8333

5.520794

Other Professionals

1499

48

8

6

249.8333

5.520794


799

48

8

6

133.1667

4.8916015


399

48

8

6

66.5

4.1972019


399

29

8

3.625

110.069

4.7011071


599

48

8

6

99.83333

4.6035021

Office Clerks

399

48

8

6

66.5

4.1972019


699

48

8

6

116.5

4.7578913


699

48

8

6

116.5

4.7578913


399

48

8

6

66.5

4.1972019


399

48

8

6

66.5

4.1972019


399

48

8

6

66.5

4.1972019


499

48

8

6

83.16667

4.4208466


699

48

8

6

116.5

4.7578913


499

48

8

6

83.16667

4.4208466


399

48

8

6

66.5

4.1972019


399

48

8

6

66.5

4.1972019


299

48

8

6

49.83333

3.9086841


299

48

8

6

49.83333

3.9086841


299

48

8

6

49.83333

3.9086841

1499

48

8

6

249.8333

5.520794

Armed Forces

75

M


APPENDIX 10: DATA FOR AGRICULTURE (66) TOTAL NO. OF HOURS

NORMAL

WORKED

WORKING

DURING

OCCUPATION Officials of Government and Special-Interest Organizations Corporate Executives and Specialized Managers

HOURS

THE

WORKING

DURING

HOURLY

LOG OF

BASIC

PAST

HOURS

THE PAST

WAGE/

HOURLY

PAY

WEEK

PER DAY

WEEK

EARNINGS

EARNINGS

6

249.833333

5.520794

1499

48

8

599

48

8

6

99.8333333

4.603502


1499

58

8

7.25

206.758621

5.331552

Supervisors

1499

48

8

6

249.833333

5.520794

899

48

8

6

149.833333

5.009524

1499

48

8

6

249.833333

5.520794


799

48

8

6

133.166667

4.891601

Other Professionals

799

48

8

6

133.166667

4.891601


599

48

8

6

99.8333333

4.603502


299

48

8

6

49.8333333

3.908684


499

48

8

6

83.1666667

4.420847

Office Clerks

299

48

8

6

49.8333333

3.908684


399

48

8

6

66.5

4.197202


299

48

8

6

49.8333333

3.908684


299

48

8

6

49.8333333

3.908684

Farmers and Other Plant Growers

199

19

8

2.375

83.7894737

4.428307

Animal Producers

199

48

8

6

33.1666667

3.501545

Forestry and Related Workers

199

39

8

4.875

40.8205128

3.709185

Fishermen

199

39

8

4.875

40.8205128

3.709185

Hunters and Trappers

199

39

8

4.875

40.8205128

3.709185


499

48

8

6

83.1666667

4.420847


299

48

8

6

49.8333333

3.908684


399

48

8

6

66.5

4.197202


399

39

8

4.875

81.8461538

4.404841


399

48

8

6

66.5

4.197202


199

48

8

6

33.1666667

3.501545


299

48

8

6

49.8333333

3.908684

1499

48

8

6

249.833333

5.520794

199

48

8

6

33.1666667

3.501545

Physicists Mathematical and Engineering Science Professionals Life Science and Health Professionals

Armed Forces Other Occupations Not Classifiable

76

MA


APPENDIX 11: DATA FOR HEALTH & WELFARE (67) TOTAL NO. OF HOURS

NORMAL

WORKED

WORKING

DURING

OCCUPATION

HOURS

THE

WORKING

DURING

HOURLY

LOG OF

BASIC

PAST

HOURS

THE PAST

WAGE/

HOURLY

PAY

WEEK

PER DAY

WEEK

EARNINGS

EARNINGS


1499

48

8

6

249.83333

5.52079403


1499

48

8

6

249.83333

5.52079403

Supervisors

1499

48

8

6

249.83333

5.52079403


599

48

8

6

99.833333

4.60350213


399

48

8

6

66.5

4.19720195


699

48

8

6

116.5

4.75789127

Other Professionals

899

48

8

6

149.83333

5.00952357


399

48

8

6

66.5

4.19720195


599

48

8

6

99.833333

4.60350213

Office Clerks

499

48

8

6

83.166667

4.42084663


499

48

8

6

83.166667

4.42084663


299

48

8

6

49.833333

3.9086841


299

48

8

6

49.833333

3.9086841


599

29

8

3.625

165.24138

5.10740731


399

39

8

4.875

81.846154

4.40484131


499

48

8

6

83.166667

4.42084663


299

48

8

6

49.833333

3.9086841


399

48

8

6

66.5

4.19720195

77

MAT


APPENDIX 12: DATA FOR SERVICES (68) TOTAL NO. OF HOURS

NORMAL

WORKED

WORKING

DURING

OCCUPATION Officials of Government and Special-Interest Organizations

HOURS

THE

WORKING

DURING

HOURLY

LOG OF

BASIC

PAST

HOURS

THE PAST

WAGE/

HOURLY

PAY

WEEK

PER DAY

WEEK

EARNINGS

EARNINGS 6.44756

1499

19

8

2.375

631.16


799

48

8

6

133.17

4.8916

Supervisors

499

48

8

6

83.167

4.42085


699

48

8

6

116.5

4.75789


499

48

8

6

83.167

4.42085

1499

48

8

6

249.83

5.52079

Other Professionals

599

48

8

6

99.833

4.6035


399

48

8

6

66.5

4.1972


399

48

8

6

66.5

4.1972


799

48

8

6

133.17

4.8916


499

48

8

6

83.167

4.42085

Office Clerks

499

48

8

6

83.167

4.42085


299

48

8

6

49.833

3.90868


1499

48

8

6

249.83

5.52079


299

48

8

6

49.833

3.90868


399

48

8

6

66.5

4.1972


499

48

8

6

83.167

4.42085


199

48

8

6

33.167

3.50155


199

48

8

6

33.167

3.50155


399

58

8

7.25

55.034

4.00796


399

48

8

6

66.5

4.1972


299

48

8

6

49.833

3.90868


299

48

8

6

49.833

3.90868


299

48

8

6

49.833

3.90868

Armed Forces

799

48

8

6

133.17

4.8916


78

M

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