Human capital linkages to labour productivity: implications from Thai manufacturers

Abstract

Human capital investment is a necessary condition for improving labour market outcomes in most countries. Empirical studies to investigate human capital and its linkages on the labour demand side are, however, relatively scarce due to limitations of firm-level data-sets. Using firm-level data from the Thai manufacturing sector, this paper aims to investigate the effects of skill and human capital on labour productivity. Costs and benefits of human capital improvement are compared indicating that hiring workers who have higher education as well as providing them with in-service training has a statistically and significantly positive impact on an increase in labour productivity. However, hiring workers who have higher education yields less benefit than costs which come from higher average wage expenditures. However, providing training should contribute more benefit than cost. Besides education and training measures, we also measure workers’ skill levels into cognitive skills and non-cognitive skills and find that skill in information technology is found to be the most important cognitive skill for increasing labour productivity among Thai manufacturers. Non-cognitive skills such as those in leadership, time-management and communication are also important and seem to have positive relationship to labour productivity among Thai manufacturers.

Keywords:

• human capital
• skills
• labour productivity
• manufacturing firm-level data
• Thailand

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The Productivity and Investment Climate Survey (PICS) was carried out by the Foundation for Thailand Productivity Institute (FTPI) under the supervision of the Ministry of Industry, with technical assistance from the World Bank on survey design and implementation. Technical Advisory Committees were composed of representatives from the World Bank, the Ministry of Industry, the National Economic and Social Development Board, the Bank of Thailand, the National Statistics Office and other agencies.

2. (1) ‘Managers’are persons making management decisions (excluding supervisors). (2) ‘Professionals’ are trained and certified specialists outside of management such as engineers, accountants, lawyers, chemists, scientists and software programmers. Generally,professionals hold a university-level degree. (3) ‘Skilled production workers’ are technicians involved directly in the production process or who serve at a supervisory position and who management considers to be skilled. (4) ‘Unskilled production workers’ are persons involved in the production process and who management considers to be unskilled. (5) ‘Non-production workers’are support, administrative and sales workers not included in management or professional categories.

3. Pholphirul (2013a) finds that Thai firms having job vacancies in either skilled or unskilled positions and losing production days due to slowdowns and work stoppages will tend to employ more immigrant workers in order to fill those vacancies and smooth out production. The impacts of job vacancies on the demand for immigrant workers were found to be stronger among firms located in non-border areas, where immigrants tend to move as they move away from bordering provinces to larger (non-border) provinces where there are better job opportunities.

4. Due to characteristics of the data-set, which is cross-sectional, cost and benefit comparison of human capital in this case must be explained only in short-term basics. Longer term effects of cost benefit cannot therefore be investigated in this context.

5. Not shown in the table, firms in the Eastern region, where several industrial estates are located, have the highest productivity – higher than labour productivity in Bangkok by around 23–25%. Firms in the southern region are discovered to have lowest average wage – approximately 8% lower as compared to firms in Bangkok and the Metropolitan Region. Classified by industry, labour productivity of the electrical appliance industry is the highest among all industries – higher than food-processing industry by about 24%. Additionally, the average wage in the electrical appliance industry is higher than that in food processing by around 18–19%.

6. This result is consistent when we use labour supply data to analyse return on education. Achieving higher education (or college) degree is found to contribute the most to wage earning output of those Thai labourers, compared to other education levels.

7. Since the data on the ratio of workers who receive vocational education is not collected in this survey, the analysis of this group of labourers is not included in this study. Subsequently, it is not possible to determine the benefits of hiring workers with vocational education for a manufacturing firm.

8. During the 1980s, the Thai government promoted universal primary education in order to reduce the adult illiteracy rate. Through this effort, the gross enrolment rate (GER) rose to 104.83% in 2008 (or around 5.37 million students, a slight increase from 103.14% in 2000). Universal primary education also increased access to higher educational levels. For lower secondary education, the GER increased substantially to 95.62% (or around 2.8 million students) from 82.7% in 2000. For upper secondary/vocational education, the GER increased to 68.14% (1.97 million students) from 54.7% in 2000. The largest improvement in education access appears to be in higher education, where the GER increased from 39.03% in 2000 to 60.47% in 2008 (Pholphirul 2013b).

9. In the same way, a study by Fletcher, by comparing behavioural skills of siblings (Sibling Effects) with different level of success at work, exposes that good behaviours cause a positive effect on success at work. The result of the study claims that giving the same level of education and family base, siblings who have better behavioural skills are more likely to achieve career success than the others.

10. Pholphirul (2013b) and World Bank (2008) find that there is clearly a mismatch between demand and supply in a labour market in which there is an oversupply of social science graduates, but a shortage of graduates in the strategic fields of science, technology and health sciences, which are all critical fields for teaching the technical skills needed in the labour market and contributing to the nation’s transition towards a knowledge economy. Mismatches between academic training and the skills demanded by industries are also indicated by the fact that the highest rate of unemployment is among people who have obtained college degrees, including degrees in science and technology, even though 80% of Thai firms ranked the lack of basic and technical skills as the reason for not being able to fill job vacancies.

11. The study of Skilled-Biased Technology Change has been widespread since the early 2000s. Several case studies have been examined using data from various sources. Some research papers use firm-level data, for example, a study of small and medium enterprises by Sandulli, Baker, Lopez-Sanchez (2013) and a study of a Turkish case by Bresnahan, Brynjolfsson, and Hitt (2011), which explains that investment in innovation causes firms to demand more skilled labourers. Analysis of data from the Thai manufacturing sector corresponds with previous studies.

12. For example, studies by Charlot, Decreuse, and Granier (2005) and Amah and Baridam (2012) on adaptability find that workers’ high adaptability has a positive influence on labour productivity and contributes to higher social return.

Additional information

Funding

This work was supported by International Institute for Trade and Development (ITD).