Peyman Firouzi-Naeim
University of Technology Sydney
Centre for Health Economics and Evaluation (CHERE)
I am an Economist with a keen interest in diverse policy analyses and econometric methods. While my primary focus lies in Health Economics, I also find excitement in exploring questions related to labor, retirement, gender disparities, and education. My approach to methods is flexible, adapting to the specific needs of each inquiry. This has led me to employ various techniques such as Structural estimation, causal analysis, Bayesian methods, and more.
The Effect of changing the Medicare Eligibility Age on the Health of the Near-Retirement Population
Raising the eligibility age for Medicare, the third largest program in the federal budget, could lead to a large reduction in the federal budget deficit; however, the effect of this change on the health of the near-retirement population is unclear. Using Health and Retirement Study (HRS) dataset, I measure the effect of a change in Medicare eligibility age on the health of the elderly population by estimating a dynamic discrete choice model of health and retirement that endogenizes the health investment decisions. Using Forward Simulation and Conditional Choice Probability estimator (CCP), I incorporate a large, multidimensional state space consisting fixed, unobserved heterogeneity that helps me to employ a detailed model to address the health and welfare concerns of the change in the eligibility age of the Medicare. I find that labor supply, life expectancy, and mental health will be affected positively in response to an increase in the Medicare eligibility age. The welfare effect, however, is negative and there is some evidence of cost transfers from Medicare to the Social Security Program.
Labor Unions and Covid-19: Beyond the Workplace
Person-to-person transmission in the workplace is thought to play a crucial role in the spread of COVID-19. Labor unions are among the largest institutions in the United States, and their role in regulating employee-employer relations is hard to ignore. Costly efforts to contain the virus combined with the monopoly and collective voice faces of unions emphasize the role of unions in shaping the workforce’s response to the pandemic, where the effects can be amplified by the further transmission of the virus beyond the workplace. We utilize state-level data and a dynamic spatial probability model to quantify the total effect of both economic activities and union membership. We find that increasing economic activity by recruiting 1,000 new employees from unemployed individuals would lead to 368 more COVID-19 cases by November 2020 and before the vaccine rollout. However, increasing the union size by 1,000 while keeping the employment level constant would lead to 111 fewer COVID-19 cases in the same period. Paper
Measuring Health in HRS dataset using Bayesian Approach
This paper provides a measure of the physical health for the near retirement people based on the binary responses of individuals to the sets of questions, regarding the objective aspects of their health. Using three sets of questions: Activities of daily living (ADL), Lower Body Mobility (LBM) and Upper Body Agility (UBA), I employ the Item Response Theory and using Bayesian approach estimate the individual distribution of health for each individual in the Health and Retirement Survey (HRS) sample of 2008. The Analysis of 17,217 sets of individual responses shows that LBM and UBA affect the combined health index (Full Index) more strongly and ADL has a weak effect on the health index. While the correlation between the full measure of functional limitation and LBM and UBA is 0.92 and 0.84 respectively, the correlation between functional limitation and ADL is only 0.5.