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1.Ricardian Model Example ECON 451 United States EU Peanut Butter 12 hrs per unit 6 hrs per unit Jelly |4 hrs per unit 5 hrs per unit Given 10 days, (240 hours): Peanut Butter Jelly United States |240 hrs/2 hrs per unit 240 hrs/4 hrs per unit EU 1240 hrs/6 hrs per unit 240 hrs/5 hrs per unit Given 10 days, (240 hours): Peanut Butter United States 120 units EU 40 units Jelly 60 units 48 units Does one country have an absolute advantage in PB? Jelly? Does the U.S. have a comparative advantage in PB or Jelly? What about the EU?
If the U.S. and the EU decide to open to trade, which good should each country produce? Please graph the PPFs of the two countries. Now suppose the terms of trade is 30 PB for 30 Jelly. Then plot the trade deal and explain how trade is beneficial to each country. Graph of PPFs for U.S. & EU 140 120 100 80 Peanut Butter 60 40 20 0 0 20 40 60 80 100 120 Jelly.
2.Kevin Brown is the management accountant at Boehm and Sons Bank. Some of his colleagues attended a conference recently where they learned that machine learning can be used to accu- rately predict loan performance. Excited by the possibilities, they asked Kevin to work with the data science team to develop a machine learning model that predicts whether a loan will repay or default. Kevin knows that defaulting loans have significantly hurt Boehm and Sons' profitability Kevin tells the data science team that his colleagues will appreciate a model that is interpretable and easy to understand, so they decide to use a decision tree. The team selects a random sample of eight loans (three loans that defaulted and five loans that repaid) from Boehm and Sons' internal loan database and begins the analysis. Repay • Default 800 . 750 . 200 . Credit Score . 650 600 50 55 40 550 25 30 35 45 Annual Income (5000s) F 1. Use your ruler to identify two possible places to make the first cut. Visually, is one of these cuts better than the other at separating the data? 2 For each potential cut, calculate the Gini impurity and the information gain. Based on these calcula tions, which cut should be used to form the first node of the decision tree? Is this consistent with your visual intuition from requirement 1? 3. How could Kevin use the decision tree analysis to help senior managers at Boehm and Sons improve profitability? th it management accountant at Donnelly Bank, which has recently thout do not fully understand the risk
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