The table below shows the relative risk of cardiovascular diseases among female nurses who were born at low birth weights compared to the average birth weight. For example, the risk of cardiovascular disease was 23% higher for those who were born at low birth weight compared to those born at average birth weight. Describe the data in light of what you know about the thrifty phenotype hypothesis.

Average birth weight

(3.2 - 3.9 kg)

Low birth weight

(2.5 - 3.2 kg)

Very low birth weight

(2.3 - 2.5 kg)

Extremely low birth weight

<2.3 kg

All cardiovascular diseases

100%

123%

129%

127%

Source: Data from Table 1 in Rich-Edwards et al. (2005)

Question 2:

Joe used to have a higher income. However, he developed an illness which led to fewer work hours and lower income.As his income fell, he needed to cut costs and began to eat inexpensive fast food.This led to a pre-diabetic condition and even further loss of income.At this point he needed to sell his car and began to skip doctor appointments due to transportation problems.Which of the theories discussed in lecture could explain this situation, and why?

Question 3:

Bart and Lisa are identical in every way except that Bart is impatient (that is, he has a low discount factor ) and Lisa is patient (that is, she has a high discount factor ). According to the time preference (or Fuchs) hypothesis, who is more likely to have a better health outcome and why?

Question 4:

In year 1, the price of health care is $100 and the price of other goods is $200. At the year 1 prices, you demand 30 units of health care and 35 units of other goods. In year 2, health care becomes more expensive at $150, while other good become cheaper at $150. Calculate the Laspeyres price index for the price changes from year 1 to year 2 and interpret your findings in terms of what happened to prices overall.

Question 5:

For this question, please download from Blackboard the excel file "Medicare claims and mortality data.xlsx", which contains data on claims-based Medicare reimbursement per enrollee (which is a measure of health care spending) and mortality rates in 2015 for all hospital service areas (HSAs) in the U.S. who have non-missing mortality data. An HSA is a collection of zip codes whose residents receive most of their hospitalizations from the hospitals in that area. The data have been assembled from Dartmouth Atlas website (https://atlasdata.dartmouth.edu/).

a)Sort data by Medicare claims reimbursement. Fill out the table below with the 10 HSAs that had the highest levels of claim-based Medicare reimbursements per enrollee in 2015 and what are the 10 HSAs that had the lowest levels of claim-based Medicare reimbursements per enrollee in 2015.

Name and state of HSA

Name and state of HSA

HSA with highest spending (1)

HSA with lowest spending (1)

HAS with second highest spending (2)

HAS with second lowest spending (2)

(3)

(3)

(4)

(4)

(5)

(5)

(6)

(6)

(7)

(7)

(8)

(8)

HSA with ninth highest spending (9)

HSA with ninth lowest spending (9)

HSA with tenth highest spending (10)

HSA with tenth lowest spending (10)

b)One way to measure the quality of care received in an HSA is by the mortality rate. Add a column to the table you completed in part a that includes the mortality rate of the 10 HSAs that had the highest levels of Medicare spending per enrollee and the mortality rate of the 10 HSAs that had the lowest levels of Medicare spending per enrollee.

Name and state of HSA

Mortality rate

Name and state of HSA

Mortality rate

HSA with highest spending (1)

HSA with lowest spending (1)

HAS with second highest spending (2)

HAS with second lowest spending (2)

(3)

(3)

(4)

(4)

(5)

(5)

(6)

(6)

(7)

(7)

(8)

(8)

HSA with ninth highest spending (9)

HSA with ninth lowest spending (9)

HSA with tenth highest spending (10)

HSA with tenth lowest spending (10)

c)Create a scatter plot of the Medicare reimbursement and mortality rate for the HSAs found in part a, either by hand or using excel. Put Medicare reimbursement on the x axis and the mortality rate on the y axis. Do you see any relationship between the ranking by Medicare reimbursement and mortality rate?

d)Your findings from parts a through c should provide evidence that additional spending does not necessarily translate to improved health status. One possible explanation is that the counties with the highest Medicare reimbursement have different health production functions than counties that have the lowest Medicare reimbursement.

List two reasons why the highest-spending HSAs may have a different health production function than other HSAs and how this prevents their higher spending from producing better health outcomes.