MétaCan
Menu
Retour à la cohorte
Enregistrement W2290962505

Wage premium in Singapore.

2010· article· en· W2290962505 sur OpenAlexaboutno aff
Ruo Hui. Tan, Yan Tan, Wai Meng. Lee

Notice bibliographique

RevueDR-NTU (Nanyang Technological University) · 2010
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueLabor Movements and Unions
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWageLabour economicsEconomicsBusiness
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

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.
\nDuring 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.
\n(i)\tThe 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.
\nAlthough 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.
\n(ii)\tThe 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.
\nOf 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.
\nWe 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.
\n 
\nWe have identified several important leads that aid us in our study.
\n(i)\tThe monthly willingness to pay and willingness to accept a higher job risk are S$668.50 and S$1868.70 respectively.
\n(ii)\tThe 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.
\n(iii)\tWe 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:
\na)\tRespondents who were themselves, or have family members and close friends being severely injured, sick or killed due to job-related accidents reported higher values,
\nb)\trespondents who were covered by life and accident insurance reported higher values,
\nc)\trespondents with higher monthly income before taxes tended to report higher values and 
\nd)\trespondents who received higher education levels reported lower values.
\nThe 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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,972
Score d'incertitude au seuil0,533

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,236
Écart entre enseignants0,224 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2010
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueDR-NTU (Nanyang Technological University)Même sujetLabor Movements and UnionsTravaux en français237 207