2. Cliff Avenue Utd FC, a Burnaby youth soccer club, was established in 1956. You can see many of its ads along the streets in North Burnaby, trying to attract new members. Suppose you believe that people usually remember the ads for about 4 years (as long as they have the kids of certain age) and the impact of the ads in any given year is declining during the subsequent 4 years. You want to build a distributed lag model to evaluate the impact of the ads spending ADI, AD-1, AD1-2, and so on, on membership (the number of families who join the club M in year t). Suppose in 1982-84 no ads were run. In 1971-76, 1988-90, and 1992-95, the ads were run but the data on the ads spending are missing (poor management and poor record-keeping). You have the data up to 2012. You also have the data on other things that you think are relevant, number of other clubs in Burnaby and New Westminster NCt, proportion of Burnaby families with European ethnic background ED, membership fee MFt, a dummy WC that is equal to 1 for the FIFA World Cup 1 years, and attendance at the FC Whitecaps games WAt (you do not believe that any of these variables have lagged effects; only AD does). a. How many degrees of freedom (for hypothesis testing on the slope coefficients) would you have in a distributed lag model? Explain. (2) b. Suppose your research leads you to believe that the distributed lag is really 6 years (rather than 4). How many ees of freedom (for hypothesis testing on the slope coefficients) would you have in a distributed lag model? Explain. (2) c. What is the problem that you are facing if you want to decide whether the ads matter and how much to spend on them (based on the data you have and the distributed lag model you are using? How would you try to fix it? (2)