Main Article Content

Abstract

Purpose—The purpose of this article is to try to look at the risk aversion determination factors that encourage the behavior of the educated workforce using or not using insurance products. The indicators used are income, education level, number of Dependents, Gender, employment status, place of residence, generation group, insurance product information


Method—The analysis model used is probit regression. Primary data obtained through a survey of 111 respondents and only 93 educated workers in Aceh Province met the specifications and filled in completely.


Research Results—The results show that only employment status has a positive and significant effect on labor preferences for insurance products, while other factors are not significant.


Limitations — This research is still limited in samples, factors that are used as objects of research and less in-depth about the role of information affecting people's behavior. This is a suggestion for researchers to further conduct more comprehensive research.


Practical Implications—The results of this study can be used as a reference for the government and companies must synergize with each other in planning insurance programs. High-income workers are expected to join insurance programs, mutual care is an important social capital to maintain the economy. The government or insurance company must increase the socialization of information on the importance of insurance programs to deal with the uncertainty of future risks.

Keywords

Insurance, Behavior, Risk Aversion, Income, Employment Status

Article Details

References

  1. Altonji, J., Contractor, Z., Finamor, L., Haygood, R., Lindenlaub, I., Meghir, C., O’dea, C., Scott, D., Wang, L., & Washington, E. (2020). Employment Effects of Unemployment Insurance Generosity During the Pandemic. Yale University, July, 1–24. https://tobin.yale.edu/sites/default/files/files/C-19 Articles/CARES-UI_identification_vF(1). pdf%0Ahttps://tobin.yale.edu/ sites/default/files/files/C-19 Articles/CARES- UI_identification_vF(1) .pdf%0Ahttps://news.yale.edu/2020/07/27/yale-study-finds-expande
  2. Andersen, T. M., Kristoffersen, M. S., & Svarer, M. (2018). Benefit reentitlement conditions in unemployment insurance schemes. Labour Economics, 52, 27–39. https://doi.org/10.1016/j.labeco.2018.03.001
  3. Auray, S., Fuller, D. L., & Lkhagvasuren, D. (2019). Unemployment insurance take-up rates in an equilibrium search model. European Economic Review, 112, 1–31. https://doi.org/10.1016/j.euroecorev.2018.11.005
  4. Aziz, Y. A., & Chok, N. V. (2013). The Role of Halal Awareness, Halal Certification, and Marketing Components in Determining Halal Purchase Intention Among Non-Muslims in Malaysia: A Structural Equation Modeling Approach. Journal of International Food and Agribusiness Marketing, 25(1), 1–23. https://doi.org/10.1080/08974438.2013.723997
  5. Bardóczy, B. (2020). Spousal Insurance and the Amplification of Business Cycles. Working Paper, May, 1–46.
  6. Bousmah, M. al Q., Boyer, S., Lalou, R., & Ventelou, B. (2021). Reassessing the demand for community-based health insurance in rural Senegal: Geographic distance and awareness. SSM - Population Health, 16(November). https://doi.org/10.1016/j.ssmph.2021.100974
  7. Corcos, A., Montmarquette, C., & Pannequin, F. (2020). How the demand for insurance became behavioral. Journal of Economic Behavior and Organization, 180(xxxx), 590–595. https://doi.org/10.1016/j.jebo.2020.09.001
  8. Devos, E., & Rahman, S. (2018). Labor unemployment insurance and firm cash holdings. Journal of Corporate Finance, 49, 15–31. https://doi.org/10.1016/j.jcorpfin.2017.12.019
  9. Duman, A. (2010). Risks in the labor market and social insurance preferences: Germany and the USA. International Journal of Social Economics, 37(2), 150–164. https://doi.org/10.1108/03068291011007264
  10. Ellieroth, K. (2019). Spousal Insurance, Precautionary Labor Supply, and the Business Cycle-A Quantitative Analysis. 1–33.
  11. Fu, W., & Liu, F. (2019). Unemployment insurance and cigarette smoking. Journal of Health Economics, 63, 34–51. https://doi.org/10.1016/j.jhealeco.2018.10.004
  12. Gangopadhyaya, A., Karpman, M., & Aarons, J. (2020). As the COVID-19 Recession Extended into the Summer of 2020, More Than 3 Million Adults Lost Employer-Sponsored Health Insurance Coverage and 2 Million Became Uninsured; Evidence from the Household Pulse Survey , April 23–July 21, 2020. Urban Institute, 1–12. https://www.urban.org/sites/default/files/publication/102852/as-the-covid-19-recession-extended-into-the-summer-of-2020-more-than-3-million-adults-lost-employer-sponsored-health-insurance-coverage-and-2-million-became-uninsured.pdf
  13. Garcia-Mandicó, S., Reichert, A., & Strupat, C. (2021). The Social Value of Health Insurance: Results from Ghana. Journal of Public Economics, 194. https://doi.org/10.1016/j.jpubeco.2020.104314
  14. Hairault, J. O., Langot, F., Ménard, S., & Sopraseuth, T. (2012). Optimal unemployment insurance for older workers. Journal of Public Economics, 96(5–6), 509–519. https://doi.org/10.1016/j.jpubeco.2012.02.002
  15. He, A. J., Ratigan, K., & Qian, J. (2020). Attitudinal Feedback towards Sub-national Social Policy: A Comparison of Popular Support for Social Health Insurance in Urban China. Journal of Comparative Policy Analysis: Research and Practice, 00(00), 1–22. https://doi.org/10.1080/13876988. 2020.1780126
  16. Hedin, T. J., Schnorr, G., & Wachter, T. Von. (2020). An Analysis of Unemployment Insurance Claims in California During the COVID-19 Pandemic. April, 1–18.
  17. Isengard, B. (2003). Youth unemployment: Individual risk factors and institutional determinants. A case study of Germany and the United Kingdom. Journal of Youth Studies, 6(4), 357–376. https://doi.org/10.1080 /13676260320001 62096
  18. Jalaluddin. (2019). Respon Masyarakat Aceh Terhadap Wakaf Asuransi Jiwa Syariah. EKOBIS: JURNAL EKONOMI DAN BISNIS SYARIAH, 3(1), 40–54.
  19. Jang, B. G., Park, S., & Zhao, H. (2020). Optimal retirement with borrowing constraints and forced unemployment risk. Insurance: Mathematics and Economics, 94, 25–39. https://doi.org/10.1016/j.insmatheco.2020.06.002
  20. Lee, Y. W. (2012). Asymmetric information and the demand for private health insurance in Korea. Economics Letters, 116(3), 284–287. https://doi.org/10.1016/j.econlet.2012.03.021
  21. Li, X., & Tian, L. (2020). The effect of non-employment-based health insurance program on firm’s offering of health insurance: Evidence from the social health insurance system in China. Journal of Comparative Economics, 48(4), 997–1010. https://doi.org/10.1016/j.jce.2020.05.005
  22. Lin, C., Hsiao, Y. J., & Yeh, C. Y. (2017). Financial literacy, financial advisors, and information sources on demand for life insurance. Pacific Basin Finance Journal, 43, 218–237. https://doi.org/10.1016/j.pacfin.2017.04.002
  23. Mitman, K., & Rabinovich, S. (2021). Whether, when and how to extend unemployment benefits: Theory and application to COVID-19. Journal of Public Economics, 200, 104447. https://doi.org/10.1016/j.jpubeco.2021.104447
  24. Nicholson, W., & Snyder, C. (2012). Microeconomic Theory: Basic Principles and Extensions (Eleventh E). South-Western Cengage Learning.
  25. Pindyck, R. S., & Rubinfeld, D. L. (2013). Microeconomics (8Th ed.). Pearson Education, Inc.
  26. Sugiyono. (2017). Metode Penelitian Kuantitatif Kualitatif dan R & D. Alfabeta Bandung.
  27. Wulandari, E. (2010). FAKTOR-FAKTOR YANG MEMPENGARUHI JUMLAH PENDERITA Estimasi Parameter Regresi Probit dengan Metode Maximum Likelihood. Matematika, Jurusan Pengetahuan, Ilmu Surabaya, Negeri, 1–6.