QUIZ 1: Macro – Spring 2009
Name:
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T/Th 8:30-10:00 T/Th 10:00-11:30
T 6:00-9:00
Question 1
Answers will be graded on a partial credit scale. Perfect answers with the appropriate
documentation of your work will be given the complete score; answers with an intuitive attempt
at the correct procedure but a wrong answer will be given 50% credit; answers with a totally
incorrect procedure (even if the answer is correct) will be given either 0 or 1 point. This implies
that you must show your work to get full credit!!!! (Calculators are allowed.)
In today’s lecture, we are going to discuss historic changes in house prices at a variety of levels of
aggregation (country, U.S. state, U.S. metropolitan area (city), etc.). Below is actual data on
NOMINAL house prices as measured by OFHEO (an agency of the U.S. government) for three
U.S. cities. For each city, the OFHEO house price index is a NOMINAL index and is anchored
at 100 in the first quarter of 1995 (1995Q1).
Below is the OFHEO index for Boston, New York, and San Francisco for the first quarter of
1984, 1990, and 1997. In the last column, I give you the level of the consumer price index (CPI)
for that quarter (where the base year of the CPI is the first quarter of 1982). In this question, we
will use the CPI to convert all nominal variables into real variables.
Boston
53.8
111.2
108.7
1984Q1
1990Q1
1997Q1
New York City
51.7
107.2
104.7
San Francisco
50.1
112.2
103.3
CPI
1.021
1.275
1.594
a)
In 1990Q1 dollars, what was the real value of the 1984Q1 OFHEO price index for
Boston? Put your answer in the box below. Take your calculations to 2 digits. (4 points)
I am going to answer this question in two steps. Step 1 would be to convert the nominal
1984Q1 price index for Boston into a real 19841Q1 price index (measured in 1982Q1
dollars). Then I will convert the real measure in 1982 dollars into a real measure in 1990
dollars. The two steps are outlined below.
i)
Real price of Boston 1984Q1 house price index (measured in 1982 dollars):
=
=
=
1984Q1 Nominal Price Index/ 1984Q1 CPI
53.8/1.021
52.69
ii) Reall price of Boston 1984Q1 price index (measured in 1990Q1 dollars)
=
=
=
1984Q1 Real Price Index in 1982 dollars * 1990Q1 CPI
52.69 * 1.275
67.18
You could have computed this answer in one step (taking formula in (i) and multiplying it
through by 1990Q1 CPI). This is the way I did it in the supplemental notes
b)
Using the exact formula, what was the real change in the OFHEO house price index for
San Francisco between 1990Q1 and 1997Q1? Put your answer in the box below. Provide
answers to two decimal points (e.g., xx.xx%). (4 points)
To do this, you need to compute the real price of the nominal OFHEO price index in San
Francisco for both 1990Q1 and 1997Q1. You can convert the nominal housing price indices
into real prices anchored in any year (1982Q1, 1990Q1, etc.). As long as the real prices that
you are comparing are measured in the same year – that is all that is important.
I am going to report things in 1990Q1 prices. I do this for simplicity. In 1990Q1 prices, the
1990Q1 real variable (OFHEO housing price index) equals the 1990Q1 nominal variable
(that is by definition). This just saves me a calculation because I only have to worry about
converting the 1997 nominal variable into a real variable anchored in 1990 prices. The
procedure to convert the 1997 San Francisco nominal prices into a real price anchored in
1990 is exactly the same as the procedure we used for Boston above. After that, we just take
the growth rate between the two real variables (measured in 1990Q1 prices).
Step 1 – Compute Real 1997Q1 OFHEO House Price Index (measured in 1990Q1 prices)
1997Q1 Real OFHEO San Francisco House Price Index (in 1990Q1 prices)
= 1997Q1 Nominal House Price Index * (1990Q1 CPI / 1997Q1 CPI)
= 103.3 * (1.275 / 1.594)
= 82.63
Step 2 - Compute the growth rate in real prices between 1990Q1 and 1997Q1
Real growth rate in OFHEO house prices in San Fran between 1990Q1 and 1997Q1:
= [1997Q1 real price index – 1990Q1 real price index]/1990Q1 real price index
= [82.63 – 112.2] / 112.2
= -26.35%
Again, you could have computed the real prices in any year you wanted. As long as you
computed both the 1990Q1 and 1997Q1 nominal house price indices into real indices
anchored in the same year prices, you would have gotten the same answer (you should
prove this to yourself).
Question 2
In this question, circle all of the true statements to the following question stem. Note: All three
answers may be true answers or none of the answers may be true. You should view this as a
series of three separate true/false questions where you are suppose to circle whether or not the
statements is true (given the question stem). PLEASE CIRCLE ONLY TRUE STATEMENTS.
(6 points total – two points each).
According to the material we have covered in class so far, which of the following are true?
a.
In macroeconomic equilibrium, a 1% increase in aggregate expenditure always implies a
1% increase in disposable income (holding taxes (T) and transfers (Tr) constant).
False – this was the hardest question on the quiz.
Remember, in equilibrium, total expenditure = total production = total income (because
demand = supply). By definition (given in class), disposable income (Y d) equals Y – T + Tr.
So, a $1 increase in Y (total expenditure in equilibrium) will lead – by definition – to a $1
increase Yd (holding T and Tr constant).
However, it will not lead to the same PERCENTAGE increase. A one percent increase
total income will lead to a greater than 1% increase in Yd if T > Tr and it will lead to a less
than 1% increase if T < Tr.
The key is that the scaling factor of a $1 change in Y is not the same if T does not equal Tr
(or, put another way – the scaling factor is different if initially Y does not equal Yd). You
should prove this to yourself (just make up some numbers and compute the percentages).
This question may seem silly to you (testing levels versus percentages), but it is not. The
popular press often confuses levels and percent changes and they sometimes make a big
deal when the percentage change in two variables differs (even though the actual changes in
the variables are the same). In terms of interpretation, sometimes it is important to think in
levels and other times it is important to think in percent changes. That is why I am asking
this question. I want you to be reticent of the differences.
b.
Given what we learned about GDP accounting in class, a $100 purchase of Citibank stock
this year by U.S. consumers (i.e., the household sector) will be measured as a $100
increase in this year’s measured U.S. consumption (C).
False – this came directly from the slides. Buying stocks just transfers resources from
consumers to firms (we classify this type of transfer as being “saving”). This transaction
shows up nowhere in GDP accounting. Once the firm spends the money, it will show up as
investment (if the stock was an initial offering). If it was just bought on the exchange, it is
just a transfer of resources from one member of the household sector (the one buying the
stock) to another member (the one selling the stock).
Some people ask me “What if there were broker fees associated with the same of the stock?”
If that is the case, only the part of the $100 that comprised broker fees would show up in
consumption (the consumer would be paying for services that help them with their saving
decisions). The broker fees would be only a fraction of the $100.
c.
Given the model that we foreshadowed in class last week, large positive increases in
aggregate supply will imply growing GDP and falling inflation rates (price levels), all
else equal.
True – this also came directly from the slides (although we did the reverse). An increase in
aggregate supply holding aggregate demand constant (all else equal) will put downward
pressure on prices and cause Y to increase. Just like our micro class, increase in supply
reduce prices and increase output. This was the easiest question on the quiz (it was just like
questions on the two practice quizzes).
Question 3
Referring back to our discussion of the Great Moderation, what are two explanations that we
discussed in class as to why aggregate volatility in the U.S. was lower from 1982-2007 than it
was during the prior three decades. Each answer should not be more than 8 words each. Write
very clearly (or my TA will not be able to give credit). Also your answers should not be
repetitive – in other words, give 2 distinct answers. (2 points total – 1 point each)
This came directly from class. If you were in class, this was straight forward. Any two of
the following would work:
i.
ii.
iii.
iv.
Luck
Better inventory management by firms
Increase in credit card usage (and debt more generally) by households
Better implementation of macro policy by policy makers.
Question 4
In “Diagnosing Depression” (Economist 1/3/2009), the article discusses what constitutes an
economy being in a “depression”.
Although the article does not provide a formal definition, it
does suggest some principle criteria for distinguishing a depression from a normal recession.
Name any one of the criteria discussed in the article. Your answer should be brief (no more than
10 words or so) – I am just trying to get a sense of who read the articles and retrained some basic
information. (4 points)
Any one of the following would be fine:
i) A recession where real GDP declines by more than 10%
ii) A recession that lasts more than 3 years
There was another criteria outlined by the chief economist of ANZ bank which included
some of the following:
iii) A recession caused by a decline in asset prices or a credit crunch
iv) A recession that leads to deflation
v) A recession that needs to be fought with fiscal policy as opposed to monetary policy
Personally, I am not sure I have ever heard a debate about when something becomes a
depression as opposed to a recession. I would be inclined to use definitions i), ii) or iv)
myself. This will be interesting to see how this plays out in the academic community.
To be honest, I am less interested in such terms. Should I care any differently if U.S. GDP
fell by 9.999% than I would if it fell by 10.001%?
I care about actual economic
performance (as opposed to the words used to describe them).