Reference no: EM131710181

Environmental Economics Assignment

1. A student  named  Bertha at  the  UCLA Institute  of  the  Environment is interested in studying whether exposure to pollution causes sickness. She collects some data for people named "A", "B", and "C".

Person	Days sick during 2013	Polluted days the person is exposed to
A	8	2
B	14	12
C	18	16

a) Graph these data putting sick days on the vertical axis and pollution exposure on the horizontal axis. Use your knowledge of intercepts and slopes to provide your best estimate of a and b in the following linear equation Sick Days = a + b*(Day of Polluted Air)

b) In three sentences or less, how do you interpret "a" and "b"? Under what assumptions would your estimate of "b" represent the causal effect of pollution on sick days? (hint: what is a causal effect?)

c) If "Days of Polluted Air" rises to 50, what is your best guess of the number of sick days the average person would experience?

2. Another student named Jane at the UCLA Institute of the Environment is interested in studying whether exposure to pollution causes sickness. She collects the following data for person called "D" tracking his sickness and pollution exposure over time

Person	Year	Days sick during the year	Polluted days the person is exposed to
D	2011	8	2
D	2012	14	12
D	2013	18	16

Who has the better experimental design? Why?

3. Here are some ambient pollution data for cities in the United States over time. The units are days where the pollution level exceeded the World Health Organization's recommended level. Days pollution exceeds the recommended level = 0 represents the best air quality and hence the worst air quality is represented by 365 which means that every day in a given year is dirty.

Year	Chicago	Los Angeles	NYC	Miami
1970	95	114	88	44
1975	96	82	78	22
1980	88	66	75	21
1985	80	55	74	17
1990	66	44	34	8

a) You know that the Clean Air Act is introduced in 1970 and that its intent is to reduce urban air pollution. Since Miami had low pollution in 1970, the Clean Air Act is not enforced there while it is enforced in the other cities. From these data what do we learn about the causal impact of this regulation on ambient air quality in the United States? What assumptions must you make to infer causal effects based on these data?

b) Suppose that Chicago always has 2 million people who live there. 50% are young and 50% are old. Each young person has a days sick production function = 3 + .2*Dirty Days while each old person has a days sick production function = 5 + .8*Dirty Days. If each person is willing to pay $12 not to be sick, how much in aggregate are the people in Chicago willing to pay for the pollution reduction that took place in their city between 1970 and 1990?