[gov3009-l] Applied Stats - 4/22 - Neil Shephard

Hi everyone! This week at the Applied Statistics Workshop we will be welcoming *Neil Shephard*, a Professor of Economics and Statistics at Harvard University. He will be presenting work entitled *Pricing each income contingent student loan using administrative data. Some statistical challenges*. Please find the abstract below and on the website. As usual, we will meet in CGIS Knafel Room 354 and lunch will be provided. See you all there! -- Anton Title: Pricing each income contingent student loan using administrative data. Some statistical challenges Abstract: Income student loans are used in many countries as the prime way for students to fund their tuition fees and maintenance. Repayments on the loans are a fraction of the former student’s income above some threshold. In England the fraction is 9% and the threshold is around $35,000. Interest is charged on the loans and any outstanding debt is forgiven after 30 years. The UK Government has offered to issue such loans to any qualified English student going to a UK university since 1998. How much are these loans worth to the Government or if the Government sold them? How does their worth vary with gender, university, subject and time? To answer these questions we have built a unique database out of administrative data the UK Government has given us access to. I will discuss this data, compare it to other sample survey sources and discuss the statistical challenges we face in pricing. Further, I will argue the approach I develop here provides a better definition of human capital than that traditionally used in labor economics.