1. Under current law, most Social Security recipients do not have to pay federal or state income taxes on their Social Security benefits. Suppose the government proposes to tax these benefits at the same rate as other types of income. What would be the impact of the proposed tax on the optimal retirement age?

2. Consider the following proposed changes to the current Social Security earnings test and determine if the changes lead to higher hours of work among retirees.

a. A change in the amount of exempt labor earnings, from $17,000 to $25,000.

b. An increase in the implicit tax rate from 33 to 50 percent.

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1. Using the formulation in Section 10.3, plot the bet size (m) as a function of the maximum predicted probability

2. Draw 10,000 random numbers from a uniform distribution with bounds

(a) Compute the bet sizes m for

(b) Assign 10,000 consecutive calendar days to the bet sizes.

(c) Draw 10,000 random numbers from a uniform distribution with bounds

(d) Form a pandas series indexed by the dates in 2.b, and with values equal to the index shifted forward the number of days in 2.c. This is a t1 object similar to the ones we used in Chapter 3.

(e) Compute the resulting average active bets, following Section 10.4.

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1. Using the function mp Sample TW, compute the average uniqueness of each label. What is the first-order serial correlation, AR(1), of this time series? Is it statistically significant? Why?

2. Fit a random forest to a financial dataset where

(a) What is the mean out-of-bag accuracy?

(b) What is the mean accuracy of k-fold cross-validation (without shuffling) on the same dataset?

(c) Why is out-of-bag accuracy so much higher than cross-validation accuracy? Which one is more correct / less biased? What is the source of this bias?

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1. Using the code presented in Section 8.6:

(a) Generate a dataset (X, y).

(b) Apply a PCA transformation on X, which we denote Ẋ.

(c) Compute MDI, MDA, and SFI feature importance on (Ẋ,y), where the base estimator is RF.

(d) Do the three methods agree on what features are important? Why?

2. From exercise, generate a new dataset (Ẍ,y), where Ẍ is a feature union of X and Ẋ .

(a) Compute MDI, MDA, and SFI feature importance on (Ẍ,y), where the base estimator is RF.

(b) Do the three methods agree on the important features? Why?

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1. What are teams and how are they formed? Consider this question in the context of your
group and the board of your Central Bank.
2. How successful is your team in deriving their recommendation? Is your team able to agree
on and manage their schedule? Are their different opinions and how are they resolved?
3. Assume that you are the chairman of the central bank board and your team mates are board
members. How would you handle different opinions and would you do things differently
compared to what your team did?
4. Now assume that you are board member and have a different recommendation to other
board members. Having gone through this process, how might you contribute to the
discussion differently in the future?

Attachments:

The-video-we-….mp4Mock-Central-…Marking-rubri….pdfIndividual-re….pdfGroup-meeting….pdf

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