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## ECO 343 - Week 2 Notes

by: Alexa Sweeney

17

0

3

# ECO 343 - Week 2 Notes ECO 343

Alexa Sweeney
GVSU
GPA 3.73

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These notes cover the lecture from Wednesday, 9/7 and Friday, 9/9. We discussed what factors affect the MEC curve, the production function for health, and a hypothetical regression model for life e...
COURSE
Health economics
PROF.
Muller, Leslie
TYPE
Class Notes
PAGES
3
WORDS
CONCEPTS
health, care, wage, age, rate, return, Education, Depreciation
KARMA
25 ?

## Popular in Economic Sciences

This 3 page Class Notes was uploaded by Alexa Sweeney on Sunday September 11, 2016. The Class Notes belongs to ECO 343 at Grand Valley State University taught by Muller, Leslie in Fall 2016. Since its upload, it has received 17 views. For similar materials see Health economics in Economic Sciences at Grand Valley State University.

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Date Created: 09/11/16
Health Economics Notes – Week 2 9/2 There is an inverse relationship between H and (r + δ). r = rate of return δ = depreciation Things that affect the MEC curve: 1. Education – if education goes up, what happens to health? a. The more educated are more aware of the benefits of the things that affect health (ex. Preventative care) b. They follow doctor’s orders c. They are assertive with their health (ex. Seeking a second opinion) If you are more educated, the MEC curve would increase (shift to the right) 2. Wage – if you are wealthier… a. You can afford better health care/preventative visits b. Provides future value because to work and make a higher wage, you must be healthy c. When your wage goes up, your opportunity cost of not being healthy also goes up An increase in wage causes an increase of the MEC curve (shift to the right) 3. Age – as age increases, depreciation increases. This causes and increase in (r + δ) a. An increase in age raises (r + δ) until we eventually get to H mindealth) b. As you move right along the x-axis, we see old age to a young age 4. Rate of Return a. Increase in return causes an increase in (r + δ), which then causes an H* decrease (H* is where the MEC curve intersects the (r + δ) line) 9/9 Production Function for Health: Y = f(education, age, income, environment, genes, lifestyle, medical care, etc.) There are diminishing marginal returns to medical care. Hypothetical Regression Model for Life Expectancy LEx = H +oβ (m1dical care) + β (inc2me) + β (educa3ion) + β4(cigarettes) 1.1 0.5 2.1 -1.5 (.9) (0.6) (0.1) (0.5) The numbers in parenthesis represent standard error. If standard error times 2.5 is less than the coefficient estimate, then it is statistically significant.  LEx is in years  Medical care is in # of visits  Income is in the 1000s  Education is in college degree = 1, no degree = 0  Cigarettes is in # of packs per day Looking at medical care… 1.1 < (0.9)2.5  Not statistically significant so  medical care doesn’t affect life expectancy Looking at income… 0.5 < (0.6)2.5  Not statistically significant so  income doesn’t affect life expectancy Looking at education… 2.1 > (0.1)2.5  Statistically significant  Those who are educated live 2.1 more years than those who are not Looking at cigarettes… 1.5 > (0.5)2.5  Statistically significant  For every pack you smoke a day, you lose a year off of your life **The negative sign only refers to how it affects your life expectancy Other factors besides medical care  changes will shift the production function Looking at the curve with Life Expectancy on the y-axis and Medical Care on the x-axis, where will specific countries be? Developing countries will be far to the left, where the slope is increasing a lot. The flu alone can kill people. The U.S. is either very far to the right where there is very little increase or at the very top where there is no slope. Its currently being debated whether or not we receive small or no benefits from health care.

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