Download 2016 Final Exam - Jacob LaRiviere

Economics
404
Spring 2016
Industrial Organization and Data Science Final Exam
Your Name:
Multiple Choice (2 points each, 20 points total)
1) The article by Paul Klemperer on the reading list extensively discussed examples of:
a. Timber auctions
b. Use car auctions
c. eBay auctions
d. Electromagnetic spectrum auctions
2) Collusion tends to be more common:
a. When bidder identify is revealed
b. In repeated auctions
c. In ascending auctions
d. All of the above
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept)
10.44751
0.01846 565.853 < 2e-16 ***
log(price)
-3.49702
0.02470 -141.608 < 2e-16 ***
log(lag1price)
1.00952
0.02536
39.803 < 2e-16 ***
log(lag2price)
0.09779
0.02440
4.008 6.13e-05 ***
brandminute.maid 0.65547
0.01415
46.319 < 2e-16 ***
brandtropicana
1.13475
0.01971
57.578 < 2e-16 ***
3) The coefficient on log(lag1price) tell us:
a. A 1% increase in the price last week leads to a 1% increase in the quantity sold this week.
b. A 1% increase in the price last week leads to a 1% decrease in the quantity sold this week
c. A 1% increase in the price last week leads to a 2.49% increase in the quantity sold this week
d. A 1% increase in the price last week leads to a 4.49% decrease in the quantity sold this week
4) One of the most important differences between freemium and traditional versioning is:
a. In freemium, there are only 2 versions of the product.
b. In freemium, users usually move to the higher version(s) from within the product, whereas
in traditional versioning this choice occurs at time of purchase.
c. Freemium is used by start-ups, traditional versioning is used by older companies
d. In freemium, the goal is to charge high value users a higher price
5) “Double marginalization”…
a. Can lead to higher prices in the downstream market to consumers
b. Occurs when upstream firms mark-up wholesale prices, which downstream firms
subsequently mark-up again.
c. Can be solved using two-part tariffs
d. All of the above
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Spring 2016
6) Lasso and Ridge regression are
a. Popular because the coefficient estimates are unbiased
b. Similar to regression trees in that they are non-parametric
c. A type of regression that shrinks coefficients to avoid overfitting
d. Estimated in R using the LM function
7) Alaska Airlines and Virgin America recently announced a proposed merger. Both airlines fly primarily
on the West Coast. This is an example of a:
a. Vertical merger
b. Horizontal merger
c. Two-part tariff
d. Foreclosure merger
8) Alaska Airlines and Virgin America recently announced a proposed merger. Both airlines fly primarily
on the West Coast. The airlines claim this merger will reduce operating costs due to operating
efficiency. If this is really true and there are no changes to the level of competition (perhaps not
realistic but assume that there is no change), then:
a.
b.
c.
d.
Prices are expected to rise over time
Prices are expected to fall over time
Prices are expected to remain constant over time
Not enough information given
9) Goods like clothing (e.g. stores in malls like Banana Republic) tend to have predictable sales at
certain points in the year where prices are 30-50% off (e.g. “Memorial Day Sale”). Goods like cars do
not tend to have predictable sales of this nature. What best explains this fact?
a. People expect car prices to go down over time
b. Clothing has very low storage costs
c. People tend to be more patient when buying expensive items such as cars
d. Clothing is a non-durable good
10) What is the optimal internal price to set for goods “sold” from one division of a firm to another
(internal transfer prices):
𝑃−𝑀𝐶
1
a. Set price to satisfy: 𝑃 = 𝑒𝑙𝑎𝑠𝑡𝑖𝑐𝑖𝑡𝑦
𝐹𝐶
b. 𝑀𝐶 +
(marginal cost + average fixed costs)
𝑇𝑜𝑡𝑎𝑙 𝑈𝑛𝑖𝑡𝑠
c. 𝑀𝐶
d. The best practice depends on the industry
Short Answer (3 points each, 36 points total)
1) Give 3 reasons to use an auction vs. setting a “take it or leave” posted price.
Economics
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Spring 2016
2) For most goods, is consumption in the future/past a substitute or complement to consumption
today? In one sentence, if I expect to the price to drop in the future, how will that affect my
consumption today?
3) Suppose you are running a second price, sealed bid auction (you are the auctioneer) and you value
the good at $20 (that is, you’d rather not sell it if you can’t get at least $20).
a. What should you set the reserve price to be (1 point)
b. Now suppose you change the format to a first price, sealed bid auction. Should you still set
the same reserve price (1 point)?
c.
If yes, why? If no, which direction should you move the reserve price (up/down) and in one
sentence why?
4) A friend tells you they want to sell a few items on eBay and is wondering if they should use “buy it
now” and set a price, or instead run an action with a low starting bid. For the following goods, what
is your recommendation and in one sentence why (1 point each)?
a. A new, popular smartphone they got as a gift but don’t want
b. Vintage disco platform shoes
c.
A used smartphone that is 2 years old
5) The following plot shows the true values of log(quantity) for a test set on the x-axis and the predicted
values on the y-axis:
Provide 3 insights you can obtain from examining model performance using this plot
a. (1 point)
b. (1 point)
c.
(1 point)
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6) What is the role of marginal costs in determining if a freemium strategy is viable?
7) If there are network externalities associated with a good should a firm charge lower or higher prices
than if there were no network externalities? In one or two sentences, why?
8) Why is it important to use train/test splits in evaluating model fit? What problem does this guard
against?
9) Suppose a firm did a “field experiment” in which they randomly selected certain regions to get a
price cut and then evaluated the impact of this price cut on revenue and profits. Is this primarily
done for causal inference or to improve a predictive model? In one sentence, why?
10) When looking at the results of a regression tree, are the variables that appear at the top of the tree
more or less important for predicting the dependent variable than ones that appear at the bottom?
Provide an example from the HW of a variable that tended to always be at the top.
11) Monopolies are undesirable because monopolists set lower quantities- and therefore have higher
prices- than is efficient. Does double marginalization make this problem worse or better? In one
sentence why?
12) Define "panel data" in one sentence.
Long Answer (10 points each, 50 points total)
1) [note the numbers are different than on the study guide] Suppose a firm offers a free trial for two
months and has acquisition rate of 0.3, a conversion rate of 0.5, nobody buys the premium version
direction (buy high rate=0), they make $10 per month if a customer converts, marginal costs per
month are $6 and the average customer lifetime is 12 months. Suppose there are 1 million
customers in their market. (2 points each)
a. What is their total revenue currently? (write the formula and provide the numerical answer)
b. What are total costs (assume FC=0)? (answer=$10.5 million)
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c.
Spring 2016
They are considering reducing the length of the free trial to 1 month. Their data science
team estimates the conversion rate will drop to 0.45 and the acquisition rate will drop to
0.28, what is the new revenue?
d. What are the new costs?
e. Should they make the change? In one sentence, why?
2) Suppose you are working for a grocery chain on inventory management and pricing. You propose
using historical data and a regression based approach, similar to our HW assignments. You put
log(quantity) on the left-hand-side of your regression:
a. (2 points) Based on the HW assignments, what variable is the single most important one to
include in this regression? In one sentence, why?
b. (3 points) Suppose your data has “week of year” numbered 1-52. You include
as.factor(week) in your regression, what does this do in terms of adding variables to the
model? What is the point of doing this?
c.
(3 points) Your model indicates that being featured increases price sensitivity (more
negative elasticity). Based on what you know of optimal pricing and this estimate, should
prices generally be lower or higher than normal when being featured? In one sentence,
why?
d. (2 points) Suppose you want to test if the relationship between being featured and price you
think should hold in (c) is in fact observed in the data currently. Write down a regression to
test your hypothesis.
3) You start a new job to price bags of whole bean coffee on starbucks.com. The previous person
working in your position was able to run pricing experiments, estimate own-price elasticities and
subsequently set prices. The previous employee found that own price elasticities are routinely
between –3 and –4 but had never estimated cross-price or intertemporal elasticities.
a. For instant coffee the own-price elasticities are consistently –2.5. Which product should
have a higher markup over cost? In one sentence, why? (2 points)
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b. You use R to estimate cross price elasticities (e.g., add additional RHS variables). They are
consistently positive and significant. What should you recommend to your boss about
Starbucks pricing for all whole bean coffee? In one sentence why? (3 points)
c.
You do the same for intertemporal elasticities and find positive and significant estimates
across all customer segments. What should you recommend to your boss about the
frequency of sales for whole bean coffee as compared to the case where intertemporal
elasticities are zero? In one sentence why? (3 points)
d. Now assume that for one customer segment (those with large own-price elasticities and
infrequent purchases) you observe the largest intertemporal elasticity. Should you offer a
targeted discount to this customer segment? Why or why not? (2 points)
4) Assume an upstream monopolist sells inputs that have a marginal cost of $2/unit to a downstream
firm. The downstream firm operates in a competitive market so that they price at MC. There is no
other input needed by the downstream firm. Assume the downstream firm faces using a demand
curve of Q = 10-P. Assume fixed costs are zero.
a. If the upstream firm charges $2 per unit, what are the profits for both the upstream and
downstream firm? (2 points)
b. Assume you cannot use a two-part tariff, what is the optimal per unit price to charge the
downstream firm? (2 points)
c.
Assume the upstream firms uses a two-part tariff and prices the input at $2, what would be
the maximum they could charge for the fixed fee? (2 points)
d. What does your observation in (c) tell you about how useful a two-part tariff is when the
downstream market is very competitive? (2 points)
e. If the downstream firm merges with other downstream firms to form a monopoly
downstream, now do you think you should use a two-part tariff? In one sentence, why?
(2 points)
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5) Consider the following table of header of a dataset for a firm’s sales by customer:
User
Product ID (SKU)
Date
Price
1
R2D2
5/1/16
$15
1
3CPO
5/1/16
$8
1
3CPO
5/1/16
$8
2
R2D2
6/1/16
$20
a. What type of data is this: cross section, panel or time series? (1 point)
b. If you wanted to quickly count the number of sales for each product by each date, what are
a couple of lines of code which would achieve this? (3 points)
c.
What does this data look like if reshaped to be "wide" so the unit of observation is Userdate? (write down what the data frame looks like, as above) (3 points)
d. Suppose the firm changed the price for R2D2 on June 1, 2016, but the price for 3CPO
remained the same. This change was not a part of an experiment. If you were interested in
identifying the causal impact of a price change how could use predictive models to
understand the impact of this change (hint: think about predicting what sales would have
been in June)? (3 points)