Problem 4. (15pt) Suppose that Netflix is considering the design of its membership programs. There are three types of membership programs for customers: Basic, Standard, and Premium. You are the data scientist that helps the company to figure out the demand function. The company gives you following data sample Customer # 1 2 3 4 5 6 7 8 9 Basic Fee 70 61 55 65 59 64 68 69 68 Standard Fee 75 79 77 76 72 70 81 74 81 where WTP means willingness-to-pay. Premium Fee 90 100 98 96 95 92 90 101 90 Customers Choice B P N S BPP S P In the table, (B,S,P,N) means (Basic, Standard, Premium, No Purchase). Suppose that the customers' surplus for "No Purchase" is 0 and the surplus for choosing membership program "m" ("m" can be Basic, Standard and Premium) satisfies surplus = WTPm - am * pricem, (1) Assume that customers are homogeneous. Based on the dataset, what are the maximum likelihood estimators for customers' willingness-to-pay for each membership program and the impact of price am for each membership program. Hint: consider the optimization problem for maximum likelihood estimation.