Wage premium in Singapore.

• Main Authors: Tan, Ruo Hui., Tan, Yan Yu., Lee, Wai Meng.
• Other Authors: Chia Wai Mun
• Format: Final Year Project
• Language: English
• Published: 2010
• Subjects: DRNTU::Social sciences::Economic development::Singapore
• Online Access: http://hdl.handle.net/10356/40016
• Institution: Nanyang Technological University

For several years, many economic literatures have been dedicated to estimate the wage-risk premium of workers which give insights to the attitudes of workers towards occupational risk. In a broader picture, wage-risk premiums could also be used to derive the value of a statistical life, which till today is widely debated and is a highly controversial topic. However, a large part of the existing literature was focused on western countries such as the United Kingdom, United States and Canada, and a minority on Asian countries such as Taiwan and Japan. To date, there are no such studies conducted in Singapore. This presented an interesting opportunity for us to attempt to conduct such a study in a Singapore context. During our review of the available literature, we found two predominant methods used to investigate wage-risk premium values; the revealed preference method and the contingent valuation method. (i) The revealed preference method relies on actual market data to obtain the market risk premium. The most commonly used market data has been in the labour market. By regressing wages with the risk of death associated with the respective occupations, the wage premium could be estimated. Although this method offers the advantage of using observable data in actual behaviour, several articles counter argued the disadvantages of this method. Firstly, marginal safety values were found to be widely divergent. Secondly, this method failed to capture the fact that workers make decision based on their perception of the jobs’ associated risk and not the objectively measured level of risk. (ii) The contingent valuation method, on the other hand, uses hypothetical situations to elicit contingent values. Because this method allows us to tailor our study to specific scenarios, the workers’ preference for safety can be measured directly. Furthermore, the fact that we could obtain directly the values that we desired, we could draw direct relationships between the variables that we wish to investigate. Of the contingent valuation studies that we reviewed, we found that there were several ways to carry out the survey. One approach was the use of mail surveys sent to pre-specified target groups. However, this method presented a response bias as higher educated individuals had higher tendencies to return the surveys. Another approach, which we eventually decided upon, was to perform face-to-face interviews. This method allows us to explain and clarify for any complexities involved in our survey questionnaire. We carried out our survey over 200 Singaporeans and Singapore Permanent Residents between the ages of 20 to 59 based on the demographic of Singapore. This sample size allows us to properly execute both the Ordinary Least Squares and Tobit and Probit methods to draw the relationships between the variables. We eventually used the former method as it provided us with more significant variables. We have identified several important leads that aid us in our study. (i) The monthly willingness to pay and willingness to accept a higher job risk are S$668.50 and S$1868.70 respectively. (ii) The value of statistical life of a Singaporeans and Singapore Permanent Residents was estimated to be in the range of S$18 million to S$23.4 million, which was greater than what was found in some western countries due to environmental and cultural differences. (iii) We also drew some relationships between certain factors and the willingness to pay and accept values. The following variables that were found to have significant impact: a) Respondents who were themselves, or have family members and close friends being severely injured, sick or killed due to job-related accidents reported higher values, b) respondents who were covered by life and accident insurance reported higher values, c) respondents with higher monthly income before taxes tended to report higher values and d) respondents who received higher education levels reported lower values. The findings of our study give interesting insights to the attitudes towards occupational risk within the Singapore context. As this is the first ever study to be conducted in Singapore, we feel that there are opportunities for further development in this topic. We also hope that our study will arouse the interest of future research efforts that would be dedicated to uncover the policy implications.