Human Capital Accumulation

Human Capital Accumulation Towards an Aging Society in Thailand 2008-2022 Kitti Limskul, Thoedsak Chomtohsuwan, Nuarpear Lekfuangfu Faculty of Economics, Chulalongkorn University, Phayathai Road, Pathumwan, Bangkok 10330, Thailand

Abstract Population demographic change of Thailand has shown trend towards an aging society in coming decade. The ratio of aged population will increase from 10.98% in 2008 to 18.02% in 2022, while the ratio of working population will decrease from 67.04% in 2008 to 63.40% in 2022 respectively. In other words, the ratio of aged population per working population will increase twice in two decades. This study applies labor and business surveyed data to project man power demand and supply. We have also estimated wage determination equation by occupation. The data used in this model was compiled with 15,000 employees and 170 companies via a job seeking website. The labor demand and supply was linked by education-occupation matrix, which derived from the Labor Force Survey. The study has estimated a human capital index and found that during 2008-2022 the Thai working population increase 2.08%. It is likely that the human capital accumulation will increase 45%. The human capital accumulation is mainly owing to rising average education level of labor. Accordingly, labor has higher productivity and higher wage. Nevertheless, the burden of working population also increases to take care of the aging. In this paper, we raise policy discussions and recommendations for government. Key words: Aging society; Population demographic change; Labor force; Human capital; Government policy JEL Classifications: J11; J18; J21; J22; J23; J24; J31

1. Introduction With reference to the World Development Report, Thailand has been within the global development patterns- diverging away from productions with labor intensive technology, for example textile and agriculture, towards skills& technology intensive technology. Historical data of Thailand suggest that the country has a long time been the net importer of knowledge-goods. This signifies that on the one hand, Thailand has been moving away from labor intensive production towards the higher skill knowledge intensive production. The path of development could not be easily

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achieved for lacking of knowledge creation, diffusion, utilization and commercialization. Thailand has quite low level of research & development intensity. The median age during 2008-2025 increases from 31.51 to 37.78 years old in 2025. However, it is expected that increase of the working age is slower than the average population. On the whole, Thailand is evolving towards rising dependency of aged population on the younger generations. In 2025, there would be 3 working-aged adults to 1 senior. In education, it is predicted that higher proportion of the Young would spend longer years in formal education rather than join the labor force. Here, a working person would have to spare 517.33 baht (3.51% of expected monthly income) in 2012 to support a senior person, in comparison to 896.51 baht (5.24%) in 2022. From the 2004 Thailand Socio-Economic Survey, it is found that senior population in Thailand (60 years old and above) spent on average 3,039.97 baths per month, with around 50% went into food expenses. The main objective of the study is to firstly analyze and evaluate circumstances surrounding the labor markets in Thailand in the next 10 years. The methodology follows closely the extent to which labor markets adjust to changes in fundamental economic structures, namely production technologies in manufacturing and service sectors, during to the epoch of economic development.

2. Labor Supply in Thailand: Trend of New Labor Pool and Labor Force Increasing number of populations spend more time in education system despite declining fertility and excess demand for primary labor in Thailand. Number of schools and teachers in primary education seems to be in excess supply. Quality of educational service is incomparable with international standard. Currently, government is considering strengthen her policy on education. Some would like to provide universal education for all as cited in the constitution. Others would like to change supply-sided financing to demand-side financing for higher education. In higher education, the education service can not provide sufficiently skilled and knowledge manpower to the market. Compatibility between supply and demand for skilled labor is unmatched. In Science& Technology, there has been severely mismatching between supply and demand in labor markets. This has resulted in unemployment or inferior positioning of Science &Technology employees. It also creates gap between employees’ required wage and labor productivity required by employers. This wage gap more often is cause of job-hopping. Applying a population, education and labor supply model we predict a declining trend of new entrant to labor pool by graduates with S&T proficiency (particularly vocational students who decide to continue a bachelor degree in S&T). It is predicted that labor market in Thailand would be affected as it will hard to fill up vacancy for this requirement. Thus, it is likely that future compensations for employees with S&T background will be notionally increased by employers. This notional demand for labor allows employers express their expected requirement or notional demand for labor according to jobs description and labor characteristics. We found that employees with vocational degree or higher would be notionally demanded with increasing trend. In contrast, those with only high school qualification or lower would face a decline trend in the notional demand from the market. By 2022, it is likely that employers will demand employees with upper-

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vocational qualification. As a matter of fact, employees with S&T background would be highly demanded in higher education. For vocational education, graduates with mechanics, machine operation and electronics are the first top three in row. Whist the lowest ranking from the bottom are graduates of construction and welding respectively. In addition, employees with bachelor degree in S&T are predicted to enjoy more than twice (2.4 times) the average trend of overall demand. In sum, those with degrees in IT, mechanical engineering& electrical engineering are most highly to get job. Whist graduates from agricultural, mathematics& statistics and chemical engineering seem to be less demanded. Predicted demands for technicians are amounted to 605,509 persons in 2008 and 928,524 persons in 2022. Demand for labor with degrees in Tourism, Health and Education are amounted to 1,810 in 2008 and 2,776 persons in 2022 respectively. The demand for graduates from managerial training is 28,661 in 2008 and 722,185 in 2022 respectively. The labor force in Thailand rises from 37.2 million persons at resent to 45.23 million persons in 2022 respectively. It should be noted that graduates with vocational education and bachelor degree would also increase during the next 15 years. On the contrary, labor force with lower education (primary school or lower) would continuously decline and share only 8.98 % of the total work force. The demand and supply gap will give rise to simultaneous vacancies and unemployment in labor markets as population tends to be in schools longer than before. Vacancy is not filled up. Unskilled labor may not find proper job either. Information from labor market indicates that employees with education qualification are looking for job. Of the total 19,611 samples, those who looked for job, 17,087 job-seekers have employment experiences, 2,287 job-seekers are recently graduated. The majority of those with S&T background have skills and knowledge of electronics and manufacturing operation. Graduates with master degree in S&T are in the field of environment related (4.77%), computer science (1.1%) and electrical engineering (1.1%). A large number of jobs-seekers are recent graduates in IT (7.84%), Environmental-related field, and Physics. The sample data implies that there is a rise in the proportion of Thai’s labor force with S&T proficiency.

3. The Notional Demand for Labor 3.1 Estimation of Notional Demand for Labor In our study, we have collected primary data at firms’ level to investigate both demand and supply aspect of the market. Employers are asked mainly about their expressed demand for occupational vacancy and position that is hard to fill up, training investment etc. While employees are asked how they would invest in their skill training, wage level etc. Notional Demand for Labor is hypothesized to be determined from company accumulation of wealth through profit taking behavior. Behavioral relationship of company is as follows: Profit (COMP_PROFIT) is determined by experiences of company represented by COMP_AGE, asset level (COMP_ASSET), revenue (COMP_REV), expenses (COMP_EXP), and additional labor requirement

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(LABOR_QUAN) respectively. Table 1 : Notional Demand for Labor as Perceived by Employers, Expressed by Profit Function

Source : Authors

It is partially hypothesized that company profit is negatively related with company asset and expenses. It is however, positively related with company revenue, experiences or age and additional labor quantity demanded. From the above profit function, we arrive at the additional labor requirement by firm or in short we call it “Notional demand for labor as perceived by employers”. We have also estimated the wage function as offered by employer. It is hypothesized that employer will offer higher wage for those job seekers who have higher education background (LABOR_EDU_EXP), having occupational or skills expressed by graduation field/subject on science and technology (LABOR_EDU_ST), having higher experiences represented by age of seeker; having an inhibited competency (LABOR_AGE_MIN), and rising company revenue (COMP_REV) respectively.

Table 2 : Wage Offered by Employers as Perceived from Notional Demand for Labor

Source : Authors

The result of estimation seems to confirm that labor market in Thailand is well behaved. We may use this equation to predict the notional demand for additional labor by employer. 3.2 Vacancy Survey of the Labor Market The vacancy survey in this study presents an important aspect of the dynamic equilibrium in the labor market. The level of vacancy and position with ‘Hard-to-Fill’ depicts strongly the situation of market disequilibrium. It may be causing by lags of adjustment between the demand and supply of the labor market. By our survey, we

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learnt that technicians and skilled trade workers are hard to fill as result of frictional market adjustment. Existing supply of workers in these occupations are lacking of necessary skills to perform proficient work quality. Employers expressed views that existing gap between demand and supply of labor was not caused from demand side, but rather because there are insufficient ‘effective’ labor supply in this category. The gap between demand and the supply of labor is not caused predominantly by the unattainable rise of the product market demand. The core problem in Thai labor market is not the lack of workers except in very low skill occupation. In general, it is the lack of ‘effective worker’ i.e. workers with sufficient skills and experience. The National Statistical Office conducted the survey in 2006, covered 31,565 establishments in the entire Thailand. The model estimation and findings are summarized as following 1 • The main cause of the disequilibrium in labor market is by labor supply side. The lack of work experience and practical skills are indicated to be the principle factor of the problem. Significantly, this lends a strong support to the case for the lack of effective labor in the Thai economy. • Workers with high school education are the group with highest demand. In term of age and experience, the NSO survey reported that the majority share of labor demanded (indicated vacant) is the workers with young age group. It consisted around 90% of the whole number of vacancy. This raises some concern because the high demand for young age, if persist, may not be sustainable, providing that Thai demography is moving away from a young economy to aging society. • By industry, of all 445,683 vacancies, the Electronic Sector is shown to have highest demand (29% of all vacancies) with Petro-Chemical Sector is with lowest demand. • The sector with most difficult to find replacement is Food Manufacturing Sector, which 40% of its vacancy were reported to have difficulty filling the post.

4. Coping with the Aging Society: Labor Market Adjustments There are a number of crucial implications for Thailand caused by the movement towards an Aging society. Principally, a strong structural change in the country’s demography would affect predominantly the dependency ratio of the entire population. In addition, this would present a further effect on the working-age group i.e. the labor market as a whole. As a result, necessary labor market adjustments should be considered to cope with these following incidents: • A demographic decline in younger generation would certainly affect the level of labor force in agricultural sectors, which are labor-intensive production. • The parallel phenomenon would also affect other industries-namely manufacturing as well as service sector, however with a somewhat different extent. That is to say, the lack of absolute quantity of labor force may not be as important as the lack of quality of labor. • Dependency ratio of the pre-school age may become less problematic, in the sense that there will be fewer children to one adult. However, Thai society would be facing a different generic of population dependency problem whereby a working1

This model is estimated by Nuaprae Lekfuengfu, Faculty of Economics, Chulalongkorn University.

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age adult would have more number of elderly to take care of. In short term, the direction of pubic policy on demographic changes should concentrate on how to deal with the deficit of the stock of human capital i.e. knowledge workers in the country, in order to satisfy the rising demand from the production sectors. At the same time, public policy would need to orient around the ways to raise and develop human resources to keep up with the ever-changing demand of the product markets.

5. Wage Determination: Differences of Opinion between Employers and Employees In our study, we also estimated the wage required by job seekers as well. Here, we would like to identify the determination of required wage function. In addition, we would like to understand the behavior of existing wage gap between wages offeredrequired. Wage function is as follows: Table 3 : Determination of Wage Required by Job Seekers

Source : Authors

Where Labor_Edu_Exp is the number of year in schooling or educational experience representing formal knowledge level, Dummy_Edu_ST is the dummy variable signifying whether job seeker graduated from field of science and technology (0 = S&T, 1 = Non S&T), Labor_Age is the age of labor signifying experiences of job seeker (year) , inhibited competency and/or maturity, Labor_Grad_Exp is the number of years after graduation, signifying competency as result of learning-by-doing, Dummy_Sex_Female is the dummy variable signifying gender (0 = male, 1 = female), signifying discrimination, and Dummy_Occ is the Dummy variables representing occupational difference or positioning in job post (OCC1 = Managers and Senior Officials; OCC2 = Professional; OCC3 = Associate Professional and Technical; OCC4 = Administrative and Secretarial; OCC5 = Skilled Trades; OCC6 = Personal

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Service; OCC7 = Sales and Customer Service; OCC8 = Process, Plant and Machine Operatives; OCC9 = Elementary). Table 4 : Wage Offer Discrimination as Perceived by Employers

Source : Authors

The study in this Report showed that employers are willing to provide attractive wage levels according to the level of job-seeker’s skills. Comparing among educational degrees, employers indicated to expect to pay 2,000 baht more to workers with S&T background. In addition, the gap between the offered wage (data from employer’ side) and the required wage (data from job-seeker’s side) would be increasing smaller with the level of knowledge and education. On employer side, it is quite clear that labor experience has positive relation with wage offered, as well as field of study like S&T and labor age of labor. It should be noted that the wage determination on the employer side is also discriminated against female as well. Although, employer does not have primarily strong gender’s discrimination, it seems to go against female significantly when come to recruitment. It may be the case that no matter what gender employee is, employer would like to recruit best productive one. Incidentally, female job seeker is less attractive as compared with male. Notice that employers in the sample group offered a comparatively higher wage to employees from Science& Technology backgrounds. Females receive less wage offer than their male counterparts. The trend in so-called wage discrimination becomes more neutralized by the increase of skill level. That is, for jobs with computer skill requirement, wage differentials among men and women had significantly diminished. Employers continue to use wage as a crucial tool to attract more employees. For gender-free jobs, potential employers made a wage offer of around 2,000 baht higher to jobs of S&T than the non-S&T jobs. Using forecasting method, with 2008 as base year, the rise of wage offer goes from 9.98% increase in 2012, to 22.26% (2017) and 32.85% (2022). 7

Executive, Senior Officers and Manager (OCC 1) is the group with highest wage offer, followed by Professional workers (OCC 2), and Technical workers (OCC 3). The lowest wage offer is made to Heath, Tourism, and Education Related workers (OCC 6), Retail and Customer Service (OCC 7), and Agricultural Businesses (OCC 9). The findings showed that the gap between the wage offered and wage required would be decreasing, due to the positive development trend of the country. An increase in labor productivity would encourage potential employers to bid for higher wage offers. Human capital accumulation will continue to be a necessary tool to bridge the gap of this current wage disparity as well as pay discrimination, through the accumulation of skills, experience and expertise.

6. Human Capital Accumulation Human Capital Index (HCI) is a universal indicator of the scale of country-wide human capital accumulation. The table below presents the trend of Thailand HCI since 1980, in relation to the level of gross national product (GDP). In the first 10 years, Thailand HCI increased significantly from 100 to 210. On the contrary, in the next 10 years, Thailand accumulated merely 20 more units. In the last 6 years (20002006), there was an increase of 30 unit index to 260. In our study, the Human Capital Accumulation as shown by ‘Human Capital Index’, HCI calculated from the wage series above 2008 - 2022 having 2008 as base year, given Occ(i) as occupation i-th and Edu_F as field of study comprising S&T and Non S&T.

Ht = ∑

∑ [W

t Occ , Edu _ F

t t * ρ Occ , Edu _ F * L

]

Occ Edu _ F

HCI = t

Ht H Base _ year

Where H t is the human capital at time t, W t is the wage at time t (Baht/month), HCI t is the human capital index at time t, ρ t is the share of labor in that Occ and

Edu_F at time t, Lt is the labor force at time t, Occ is the subscript for occupation group (1 to 9), and Edu _ F is the subscript for a science and technology major (S&T, Non S&T). The Study predicted that a rise in the level of Human Capital Index, a proxy indicates Human Capital Accumulation, would lead to a notable rise in the level of earnings. An increase in 45% in the next 15 years would reflect in a doubling of individual annual earning from 140,000 baht to 270,000 baht. A rise of Thailand’s HCI would be of increasing trend for the next 5 years, whilst it would be rising with decreasing trend in the following 10 years. If the country’s fertility rate would remain on the decline, Thailand would face a slowdown in the level of human capital accumulation. In the short run, Thailand might face the situation of excess demand for labor, resulted from the adjustment of the supply side with slower speed. Therefore, it is recommended that the policy makers must pay attention on the supply-side solutions. First of all, educational policy, with its aim to raise labor efficiency, is required. This encompasses formal education, vocational training/re-training and funding of 8

research& development. Alternative policy such as immigration could be considered. In the short run, certain industries would require a rapid and quick solution for their structural adjustments. Nevertheless, in the long run, other policies should enable the domestic labor market to function independent at its market equilibrium. In the case of Highly Skilled Immigrants, Thailand would remain dependent of the knowledge transfers from imported workforce of the high skill type. According to various studies, there are around 80,000 migrants workers came into the country, those of Business-and-High-End-Skills. In Medium term, the country should be prepared for making policies to facilitate this form of labor mobility.

7. State-Funded Training Program for Skill Development The study found evidences that a large number of employers were providing at least a form of training to their existing employees. However, the extent of training provision varies greatly by the types of establishment, in particular the size of the firm. We propose a government-finance training scheme with the sole objective to upgrade employee’s skills. The main hypothesis is that a rise in training funding would systematically lift up labor productivity. Hence employers would be more profitable thus have stronger incentives to hire. This implies that a rise in human capital accumulation would lead to the expansion of labor market opportunities i.e. employment. Given the forecasting trend of new labor supply of 2.0 percent per year, the Figure below shows the case II where an allocation of 0.01% of GDP to the Training Fund as compared to ‘no training effort’ case I, for new labor supply will affect labor force participation rates. In case of training is provided (case II), Labor force participation rate rise above the base case I, which is 72.2 percent. Without training effort (case I), unemployment will be as high as 0.7 million persons in 2020. After training provision, employment will grow on average 5 percent per year over the planning horizon, 2008-2020. Unemployment decreased to 0.15 million persons by 2020. The training provision has increased the labor force participation rate after wage and skills have increased simultaneously. We hypothesized that labor force participation rate would be the policy parameter, which would be adjustable by public policy on training provision. When the labor force accumulates more skills, the level of labor participation would increase. Both theoretical and empirical evidences show that decision to participate in the labor market (i.e. individual labor supply decision) varies across different age group and stock of wealth. That means it is endogenously determined. Now, we turn to the question that should Thailand need import of foreign guest labor or not? In our study we have tried to simulate the scenarios starting from base case scenario, case I, II, and III respectively. If the productivity increases as result of training, then wage and marginal productivity will rise simultaneously. That is to say, labor force would increase their provision of labor supply as shown above. Thus, the scenarios will give situation which employment increase together with moderate growth potential and excess demand for labor will be taken care by productivity increase, with higher level of labor supply provision simultaneously. This simulation confirms that in order to avoid import of guest labor in the medium run we may need to increase labor training fund and look for effective way to increase labor productivity.

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Given Base Case (Case 0) after reconcile survey data with I-O Table 2000, we assumed that the share of S&T labor force increases 5 percent per year, with share of education level of labor force increases 1 percent per year, under the GDP growth in real term of 5 percent per year. We do the following simulation experiments: • Case I : Same as Base Case with investment in human capital through training with fund allocation at 0.01 percent of GDP, productivity increase of 1.5 percent per year. Here in this case, employment is lower than base case, in the first 7 years. Thailand may not need to import foreign labor during first 7 years. The last 7 years, as GDP growth increased 5 percent per year, it is found that employment has exceeded the base case. Foreign labor may need to be invited • Case II : Same as case I but with productivity increase of 1.0 percent per year. Here in this case, GDP growth spurs demand for labor, and excess demand induces import of foreign labor as solution. • Case III : A rise in 2% of labor productivity resulted in a rather balanced labor market where excess supply prevails through out the planning horizon. Here, demand for labor is appropriately supported by the supply of domestic labor force. No import of foreign labor is necessary. This exercise implies clearly that productivity increment is necessary to lay policy foundation to immigration policy, if we would like to import guest labor of the type knowledge workers. Foreign knowledge can be substituted by local labor supply after training provision is effective. The productivity increment can be materialized by increment of labor force participation. The latter relies on the leisure-labor choice of household and individual.

8. Policy Discussions

8.1 Public Policy on Labor Migration of Knowledge Worker: Case Study-Singapore Singapore is another example of an aging society- with a serious problem of highly reduction in fertility rate. Giving the economic structure, which consists strongly of intra-firm linkages between the foreign and host firms; the labor market in Singapore has relied heavily on skilled workers. As a part of the main policy to upgrade the country’s competitiveness, immigration policy is also considered, by the Singaporean government as an important area of stimulus economic tool. As a result, the Singaporean government has concluded an agreement with the Indian counterpart, the Comprehensive Economic Cooperation Agreement, to prepare the country as a Knowledge-Based economy (KBE). Priorities are given to (1) formal education & skill upgrade (2) innovation: its role of the main driver of the economic growth (3) Business and Manufacture Restructuring (4) Product and Service realignment with higher-income consumers. (High-End products) The manufacturing sector is taken as a spearhead of the engine of the country’s development, with special interests paid to the electronic, science as well as biopharmaceutical industries. In addition, the Singaporean government places the service sector as the second most important engine, especially health, education and creative industries. Strong attention is paid to investment in ‘intellectual capital’, so as to substitute the need for vast land space and high quantity demand for labor force. Since 1975, Singapore began to face the prospect of ageing society, reflected in

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a significant reduction of fertility rate. Therefore, the country decided to bring in additional labor force from other countries, in particular, the communication, service, and bio-technology sectors. As a result, there has been a numerous change of production structure, evolving from labor-intensive towards capital, and technology-intensive methods of production. This had an implication on the factor market- the labor market in the way that the country’s occupational structure began to move towards jobs in management, technical, vocational, and technology. The share of these jobs increased from 11% in 1970 to 40% in 1999. On the supply side, a rise in the number of students in the S&T field is not sufficient to cope with a much more rapid rise of the demand. At 15% in 2000, the share of these students remains lower than the average in the developed world. Thereby, immigrants become a necessary solution. In 2000, it is estimated that there were around 600,000 immigrants (compared to 4 million Singaporean populations), made up of 30% of the total labor force. Of this, around 20% are high skill, working in manufacturing sector, and 33% in construction, and 25% in manufacturing, commerce and service sectors. Furthermore, the Singaporean has put a strong emphasis on investment in a number of key sectors, namely Communication& Technology, Banking, Healthcare, Education and R&D. The case of Singapore showed that the country decided to deploy the demand-side policy tools to deal with the approaching demographic threat.

8.2. Policy towards Immigration of Knowledge Worker into Thailand In the short run, Thailand might face the situation of excess demand for labor, resulted from the adjustment of the supply side with slower speed. Therefore, it is recommended that the policy makers must pay attention on the supply-side solutions. First of all, educational policy, with its aim to raise labor efficiency, is required. This encompasses formal education, vocational training/re-training and funding of research& development. Alternative policy such as immigration could be considered. In the short run, certain industries would require a rapid and quick solution for their structural adjustments. Nevertheless, in the long run, other policies should enable the domestic labor market to function independent at its market equilibrium. In the case of Highly Skilled Immigrants, Thailand would remain dependent of the knowledge transfers from imported workforce of the high skill type. According to various studies, there are around 80,000 migrants workers came into the country, those of Business-and-High-End-Skills. In Medium term, the country should be prepared for making policies to facilitate this form of labor mobility.

8.3 Estimation of the Necessary Demand for Immigration to Thai Labor Market: Labor-Intensive Sectors A study by Wongboonsin (2006: p.256) indicated that a majority of registered immigrant in labor-intensive production sectors are unskilled. This group of workers has a share of 10% of the entire Thai labor force. The forecast of labor supply of this type in Wongboonsin’s study concentrated on the undocumented migrant workers, excluded the agricultural sector. The future estimation by sector reveals the direction of the demand for labor in each of this sector, using crucially the wage gap (between the offered and the required) as the main signal of labor market disequilibrium.

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In sum, in the short run, the labor market in Thailand wound continue to rely on the easing effect from the influx of immigration. Nevertheless, the medium run, the country would need to produce a clear direction on all related policies, on how to soften the demand for immigration. In the longer run, sectors as Hi-Tech manufacturing, or professional occupations would need to become self-dependence. This could be done through the form of training, re-training and the reform of the formal education system.

9. Policy Recommendations

9.1 Challenges & Policy Solutions to future circumstances of labor markets in Thailand a) Agricultural Labor Force This group of labor force faces two distinctive problems. Firstly, there is a significant lack of these labors in harvesting seasonal whist similar excess of them off season. This results in an unpredictable level of supply, worsening by the increase in the trend of labor migration to manufacturing sectors. The current trend of the decline of stable labor supply but the rise in the demand, due to the production of ‘energy crops’ should be supported by the alternative use of machinery. b) Labor Force in Service and Manufacturing Sectors Global development pattern indicates a foreseeable growth in Service and Manufacturing sectors. Therefore, the labor market must be well prepared with both the quantity and the quality i.e. skill& proficiency of its workforce. Relevant trainings should

9.2 Declining Trends in Fertility Rate: Demographic Policy A policy recommendation should focus on encouraging the value of family, by employing tools of fiscal policy, in order to maintain a healthy level of fertility rate. Supports on working parents, as well as healthcare policy would be beneficial to both the condition of existing labor supply and the future labor supply.

9.3 Policy on Senior Population Policies should be working towards voluntary expansion of retirement age and prevention of potential age discrimination on employment. We need to encourage public understanding on the role of senior population in the working labor market. It may be the case that private sector may open up suitable jobs to senior population with government incentive.

9.4 Wage-Determination Policy The centrality of the principle of government intervention in this area should be made clearer. A wage policy, such as minimum wage setting under tripartite

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negotiation, should be reconsidered. Wage policies should be though of as a welfare policy i.e. Living Wage, as contrary to the benchmark to the market force. That means a wage would be set and offered to guaranteed quality of life of people in needs i.e. at the poverty or below. And the central government would be entitled to such expenses. On the other hand, wage levels in the labor markets should be left to the market force. This is to stimulate appropriate returns of skill, as well as incentive to invest in human capital. The role of central government in wage determination should ensure labor market flexibility, in particular the wage flexibility, in order to smooth the labor market transition for both the workers and employers.

9.5 Vocational Training and Standardization of Quality The direction of planning of vocational qualifications should be towards demand-side orientation. That is because the form of education must progress very closely to the rapid speed and direction of the economic development. In order to ensure the dynamic nature of the Qualification, consistent training and testing of skills composed in the qualification should be monitored regularly. A possible recommendation is the integration on dynamic market mechanism. In this, the use of labor wage at market price as the important signal, indicating a potential disequilibrium situation from either the demand or the supply side of the labor market. Wage adjustment should be a forceful indicator to pinpoint lack of or surplus of such skills in the labor at each time. Nonetheless, in the short run, the adjustment of the labor market in Thailand would rely strongly on some levels of government intervention. The serious disequilibrium in the skill markets of science& technology related field requires rapid injection on labor supply in the market. At the same time, wage adjustment on the demand side must also be looked after. The government needs to set up a Professional Quality Institute to act as the reliable institution capable of Accreditation, Testing& Qualifying and Training. In addition, it would be the main source to oversee competency demand and use, to serve the development dynamic of the economy. Most importantly, there must be a Qualification Certificate after the training. This is to reduce the problem of asymmetric information, as well as allow the market force to function most efficiently.

9.6 Reform of Formal Educational System and Management A public policy must introduce to encourage and support a continuous education from vocational graduation to higher level in line with the vocational quality path or as ‘Master of special skills’ rather than universal degree without special skills. This is to reduce the unnecessary loss of human capital in science & technology. Current evidence reveals a large number of vocational qualification graduates who abandon their practical skills, in order to pursue a ‘soft-skill’ university degree. In term of education financial support, public policy should establish such mechanism to allow the change from supply side financing as the main pillar, to the demand-side financing. A block grant would be the main policy tool to induce educational institutions to make use of the resources at the most effective and efficient nature possible. The reform of this education management would follow market mechanism in such a way that the least capable or most inefficient institutions would be fixed or worst case abolished.

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At university level, 1) the conduct of ‘industry scan’ every 2-3 years would be necessary to make human capital planning. Such planning would require partnership between the education institutions on the one end, and private sector on the other end. 2) In addition, this Report proposes an addition on budget on Research & Development from 0.026% of GDP to 1.00 % within the next 3 years, and 1.5% in 6 years time

9.7 Immigration Policy Immigration policy should be considered according to the actual requirement of labor factor in each adjustment state. That is the consideration of immigration policy would be different for the economic development in the short run, medium run and the long run. In order to increase labor productivity to 1.5% annual growth, the government may need to insert 0.01-0.05% of GDP to the human capital accumulation schemes. In the short run, additional labor force from overseas may be more necessary than the medium and the long run. • Level 1: Unskilled Sweat& Tear Labor Force: there must be lawfully restricted regulation, in particular, legal registration, is a necessary mechanism to ensure the temporary residence of this type of immigrants. Policy practical tools such as ‘pass book’ would allow the officials to control and limit the number of immigration in and out of the country. • Level 2: Skilled Labor: If proven insufficient supply of skills, employers should be able to bring in some addition overseas labor force, on a short-term basis. The wage level must not be below international standard, and income tax would be applicable as other domestic labor force in the country. • Level 3: Special skilled labor, Research& Development, Knowledge Workers: A free movement of labor force of this type should be encouraged. Wage levels must follow international standard. The side benefit of such wage setting is to converge upwards the earning levels of domestic labor force of similar skills. Transparent tax system would be the crucial tool to ensure positive contribution of immigration to the host country.

9.8 Industrial Policy Industrial policy would focus on the efficiency of market force in the labor market. That is to rely on wage-level, on each various occupation and sector, as the push-pull force, determining the equilibrium of demand for and supply of labor in the whole economy. It is expected that some of the significant industries in the future in Thailand are science-based sectors: biotechnology, nanotechnology, material science, information technology. Based on the Development Epoch, it could be seen, from the Report that Thailand is merely at the very beginning stage of the path. That means Thailand is in such need for further accumulation of human capital. Industries in Thailand should move to production techniques with more intensively use of high technology, rather than emphasizing of labor intensive methods of production. Necessary knowledge required for this developmental progress is that in Energy& Loss Control Process Simulation Material, Polymer Science, and Catalyst Development. Important practical skills are analytical & problem solving, knowledge

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application, team work, interpersonal leadership, and most importantly the Hands-On & Creativity. Returns to highly skill personnel are calculated to be approximately 60,000 baht per month for Research& Development Intensive industries, comparing to fewer than 7,000 baht for Sweat& Tear Service Industries.

9.9 Climate Change and Aging Society Global Warming is arguably an influential factor to the change of the economic progress, as well as development patterns. It leads to serious lacks of food and natural resources- implication of food and energy crisis on the global scale. Thailand must be prepared from such a global climate change, and ensure that its economy would be well-equipped for the foreseeable crisis. Therefore, with the effect of the aging economy- see in the future reduction of labor force, the country must focus its attention on how to elevate its existing labor force, and more importantly its human capital to face this phenomenon. A policy such as ‘Migrant U-turn’ is one of such policies with the objective to encourage a rise of labor force in local, agricultural economy. Government policies should pay more attention on how to induce a rise in human capital, as well as how to incorporate this with the increasing importance of one of the main sector in the country.

9.10 Paths of Human Capital Management under the Socio-Economic Structure of Thailand in the Era of Aging Society Goals and Plans for Improvement of Human Capital Management. The key principal of the planning of the improvement human capital management is to optimize social welfare of the country, under the constraint on social and economic structure. The focus of the development should be paid extensively on capital-deepening, with the preparation to minimize effects of externalities caused by the overconsumption on natural resources.

References

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European Economy Economic Papers, No. 300. Barker Terry and Peterson William (1987), “The Cambridge Multisectoral Dynamic Model of the British Economy”, Cambridge University Press. Becker, G. (1993), “Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education”, Third edition, University of Chicago Press. Briscoe and Wilson (2003), “Modeling UK Occupational Employment”, International Journal of Manpower 24(5), pp. 568-589. Charlotte H. (2002), “Policy Responses to Population Ageing and Population Decline in Germany”, Federal Institute for Population Research, Wiesbaden, Germany. Chenery and Syrquin (1975), Patterns of Development 1950-1970, World Bank, Published by Oxford University Press. Checchi, D. (2006), “The Economics of Education: Human Capital, Family Background and Inequality”, Cambridge University Press. David H. Autor, Frank Levy and Richard Murnane (2003), “The Skill Content of Recent Technological Change: An empirical exploration”, Quarterly Journal of Economics, November 2003, Vol. 118, No. 4, pp. 1279-1333. David H. Autor, Lawrence F. Katz and Alan B. Krueger (1998), "Computing Inequality: Have Computers Changed The Labor Market?," The Quarterly Journal of Economics, MIT Press, vol. 113(4), pp. 1169-1213. Eurostat (2005), “The Measurement of Scientific and Technological Activity”, Oslo Manual. Foray, D., and F. Gault (2003), “Measuring Knowledge Management in the Business Sector: First Steps”, Paris: OECD Foray, D. (2004), The Economics of Knowledge, Cambridge MA: MIT Press. Gault, F. (2006), “Measuring Knowledge and Its Economic Effects: The Role of Official Statistics”, in ed., Kahin., B. and Foray, D., Advancing Knowledge and the Knowledge Economy, The MIT Press. Hatzichronoglou, T. (1997), “Revision of the High-Technology Sector and Product Classification”, OECD STI Working Paper 1997/2, Paris, 59918. Herwig Birg (2002), “Demographic Ageing and Population Decline in Twenty-First – Century Germany: Consequences for the Systems of Social Insurance”, Institute for Population Research and Social Policy, University of Bielefeld, Germany. International Institute for Management Development (2004-2007), “World Competitiveness Yearbook various issues 2004-2007”, Switzerland: Lausanne. Kitti Limskul et.al., (2008), “Labor Market in Thailand under the Aging Society”, submiited to the NESDB, Thai Government. Lundvall (2000), “The Learning economic: Some implications for the knowledge base of knowledge to the learning economic in OECD” Machin, Stephen, and John Van Reenen (1998), “Technology and changes in skill structure: evidence of seven OECD countries”, Quarterly Journal of Economics (113). Magnus, G. (2008), “The Age of Aging: How Demographic are changing the Global Economy and our world”, John Wiley & Sons (Asia). Mincer, J. (1958), “Investment in Human Capital and Personal Income Distribution", The Journal of Political Economy 66(4): 281-302. Mowery, D. and Sampat, B. (2006), “The Bayh-Dole Act of 1980 and UniversityIndustry Technology Transfer: A Policy Model of Other Governments”, in ed., Kahin., B. and Foray, D., Advancing Knowledge and the Knowledge Economy, The MIT Press.

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Office of the Education Council, Ministry of Education, Kingdom of Thailand (2006), “Education in Thailand 2005/2006”, OEC Publication No. 77/2006. Organization for Economic Co-operation and Development (OECD) (1988), “Human Capital Investment: An International Comparison”, Center for Educational Research and Innovation, Paris. Organization for Economic Co-operation and Development (OECD) (2006), “PISA Report”, http://www.pisa.oecd.org Pitayanon and Limskul (1988), “Population education Manpower and Employment Forecasting Model for Thailand, Faculty of Economics”, Chulalongkorn University, Thailand. Pitchford, J.D. (1974), “The Economics of Population: An Introduction”, Australian National University Press, Canberra, pp. 305. Renner, M., Sweeney, S. and Kubit, J. (2008), “Green Jobs: Working for People and the Environment”, World watch Report 177, World watches Institute. Ronnachai Bunsuriyathum (2008), “The universities in Japan and Adaptation in present age”, Japan Watch Project, Vol.2 No.1, 2008. Ruttiya Bhula-or (2008), “Reexamine Measures of Human Capital: Value of Human Capital in Thailand”, A paper to be published, Faculty of Economics, Chulalongkorn University, Thailand. Schultz, T.W. (1961), “Investment in Human Capital”, American Economic Reviews, 51(1):1-17 Sen, A. (1988), “The Concept of Development” in ed., Chenery, H. and Srinivasan, T.N., Handbook of Development Economics, Vol. 1, North Holland. Sen , A., (2000), “Development as Freedom”, Anchor Books, New York. Schultz, T W. (1981), “Investing in People”, Berkeley, University of California Press. Syrquin, M. (1988), “Patterns of Structural Change”, in ed., Chenery and Srinivasan Handbook of Development Economics, Part 2, Structural Transformation, Vol. 1, North Holland. Tessaring, M. (1997), “Forecasting sectors, occupational activities and qualifications in the Federal Republic of Germany”, A Survey on Research Activities and Recent Findings, European Centre for the Development of Vocational Training. UNESCO (2000, 2006), “Institute for Statistic”, www.uis.unesco.org United Nations (1998, 2002), “World Population Prospects, volume I: comprehensive Tables”, UN, New York. Wilson, R., Woolard, I. and Lee, D. (2004), “Developing a National Skills Forecasting Tool for South Africa”, South African Department of Labour: Pretoria. Wilson (2006), “Working Futures 2004-2012 (Technical Report)”, Institute for Employment Research (England). World Bank (2006), “World Development Indicators 2006”, World Bank. Wongboonsin, P. (2006), “The State and Labor Migration Policies in Thailand”, in ed., Kaur, A. and Metcalfe, I. Mobility, Labor Migration and Border Controls in Asia, Palgrave Macmillan World Economic Forum (2007), The Global Competitiveness Report 2006. Wyckoff, A. and Schaaper, M. (2006), “The Changing Dynamics of the Global Market for the Highly Skilled”, in ed., Kahin, B. and Foray, D., Advancing Knowledge and the Knowledge Economy, The MIT Press.

(in Thai)

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Kua Wongboonsin et.al., (2003), “The forecasting for Population in Thailand 20002025: The Effect on Policy for Population in the Future”, College of Population Studies , Chulalongkorn University. Kua Wongboonsin and Suwanee Surasiengsunk (2004) , “The Desired Skill of Thai Labor in the Future”, The Thailand Research Fund (TDRI), Thailand. National Statistical Office of Thailand (1999), “International Standard Industrial Classification of All Economic Activities (ISIC)”, NSO, Thailand. Office of the Education Council (2000), “Education Graduation Forecasting Model for Thailand”, Ministry of Education, Thailand. Office of the Education Council (2006), “The Education Situation of Thailand in the world 2006”, Collected from 3 reports published in the Education Counts, Benchmarking Progress in 19 WEI Countries: World Education Indicators 2006 and Global Education Digest 2006, Comparing Education Statistics Across the World: Teachers and Educational Quality: Monitoring Global Needs for 2015, UNESCO Institute for Statistics (UIS), Ministry of Education, Thailand. Office of the Education Council (2006), “The research of the Education Reform for Knowledge-based Economy Society”, Ministry of Education, Thailand. Office of the Education Council (2008), “The Education capability of Thailand in the World 2007”, Ministry of Education, Thailand. Office of the Education Council (2008), “The Strategy and Policy for Driving Thailand to be the Knowledge-based Economy Society”, Ministry of Education, Thailand. Office of the National Economic and Social Development Board (2007), “Tread of Industrial Growth in Next 5 Year (2007-2012) and Development of Supporting Area”, NESDB, Thailand. Office of the National Economic and Social Development Board and The Thailand Development Research Institute (2004), “The Study of the Education for Human Resource Development for Increasing the Competitiveness of Industries”, NESDB, Thailand.

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Figure 1 : The Number of Labor taking care of one child and elder in Thailand during 2000-2025

Source : Authors, Derived from the data in “The forecasting for Population in Thailand 2000-2025: The Effect on Policy for Population in the Future”, Kua Wongboonsin et al., (2006)

Table 5 : The Forecasting of Labor Wage and Burden of Senior Citizen (at 2008’s Constant Price)

Source : Authors, Derived from the data in “Socio-Economic Survey”, National Statistic Office (2004)

19

Figure 2 : Employed Person by Education Level in Thailand during 2008-2022

100,000

Primary Level and Lower Lower Secondary Level Upper Secondary Level Vocational Certificate High Vocational Certificate Bachelor Degree Graduate Study

Employed work force (Thousand people)

10,000

1,000

Year

Source : Authors

20

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

100

Table 6 : The Forecasting of Required Wage by Job Seeker (at 2008’s Constant Price)

Source : Authors

21

Table 7 : The Forecasting of Offered Wage by Employer (at 2008’s Constant Price)

Source : Authors

22

Figure 3 : The Forecasting of Human Capital Accumulation during 2008-2022

Source : Authors

Figure 4 : Change in Employment with and without Training of New Labor Scenarios during 2008-2022

1,400 1,200 LPR = 72.2%

1,000

Case 1

800

Case 2 600 400 200 -

Year

Source : Authors

23

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

-200 2008

Change in Employees (in Thoudsan persons/Year)

1,600

Figure 5 : Change in Employment with Training Scenarios during 2008-2022

Employment (Million persons)

55

50

Case 0 (Base) Case I Case II

45

Case III

40

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

35

Year

Source : Authors

Table 8 : Snapshot of Change in Employment with Training Scenarios

Source : Authors

24

Table 9 : Registered Migrants as of 25 December 2003

Source : Wongboonsin. P. (2006), “The State and Labor Migration Policies in Thailand”, in ed., Kaur, A. and Metcalfe, I. Mobility, Labor Migration and Border Controls in Asia, Palgrave Macmillan

Table 10 :

Irregular Migrants Labor with Work Permit Extension between 24

February and 25 March 2002

Source : Ministry of Labor (2002b) ‘Irregular Immigrant Workers with Work Permit Extension’, Lien Registration, Office of Administration Commission on Irregular Immigrant Workers, 24 Dec. (in Thai) cited in Wongboonsin., P. (2006), “The State and Labor Migration Policies in Thailand”, in ed., Kaur., A. and Metcalfe, I. Mobility, Labor Migration and Border Controls in Asia, Palgrave Macmillan

25

Table 11 : Assessment of Demand for Foreign Guest Labor in year 2009-2023

Source : Authors Note : This scenario is assumed to be independent from short-term business cycle fluctuation. Economic crisis in 2008- will relax the tight labor demand for knowledge worker in USA, EU and Asia for certain time period, after economic recovery and business cycle up swing there will be higher demand for knowledge worker again as population structure in the world tends toward aging and declining birth rate in developing countries

26

Table 12 : Goals of Human Capital Accumulation: SWOT Analysis

Source : Authors

Table 13 : Structural Change in Physical Capital and Human Capital

Source : Authors

27

Table 14 : Policy by Labor Class

Source : Authors

Figure 6 : Structure

Source : Authors

28

Figure 7 : The Direction of Government Policy on Aging Society

Source : Authors

29

Figure 8 : Policy on Human Capital Investment and Human Capital Accumulation

Source : Authors

30