Introduction to Time Series Homework: 1. Autocorrelation causes problems for ordinary least squares regression. Explain the autocorrelation problem in a simple way as you would to a friend who doesn't know much about econometrics. 2. Autocorrelation, if left unchecked, can be particularly dangerous for a researcher who has found statistically significant results. Explain why this is so. 3. Conduct a Durbin-Watson test of a 5% error level for each case given. Is the null hypothesis of no first-order autocorrelation rejected, not rejected, or is the test inconclusive? Use the appropriate one-sided test for each Durbin-Watson statistic given. a. D.W. = 1.27, N = 40, k = 2 (dj=1.39) b. D.W. = 1.27, N = 25, k = 2 (dj =1.21, du=1.55) c. D.W. = 2.45, N = 80, k = 5 (4-dj=4-1.51=2.49, 4-du=4-1.77=2.23) d. D.W. = 2.45, N = 80, k = 1 (4-dj=4-1.61=2.39, 4-du=4-1.66=2.34) 4. What is the distinction between adding missing variables to treat the "illness" of autocorrelation, and using a generalized difference equation to treat the "symptoms"