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Question 3 (Autocorrelation) Given the following U.S. manufacturing data on inventories and sales, in millions of dollars, as below: Year Sales Inventories Year Sales Inventories 1952 44,840 72,377 1970 108,352 178,594 1953 47,987 76,122 1971 117,023 188,991 1954 46,443 73,175 1972 131,227 203,227 1955 51,694 79,516 1973 153,881 234.406 1956 54,063 87,304 1974 178,201 287,144 1957 55,879 89,052 1975 182,412 288,992 1958 54,201 87,055 1976 204,386 318,345 1959 59,729 92,097 1977 229,786 350,706 1960 60,827 94,719 1978 260,755 400,929 1961 61,159 95,580 1979 298,328 452,636 1962 65,662 101,049 1980 328,112 510,124 1963 68,995 105,463 1981 356,909 547,169 1964 73,682 111,504 1982 348,771 575,486 1965 80,283 120,929 1983 370,501 591,858 1966 87,187 136,824 1984 411,427 651,527 1967 90,918 145,681 1985 423,940 665,837 1968 98,794 156,611 1986 431,786 664,654 1969 105,812 170,400 1987 459,107 711,745 1990 540,788 835,985 1988 496,334 767,387 1991 533,838 828,184 1989 522,344 813,018 a. Estimate the regression; Sales = f (inventories) b. Test the existence of autocorrelation of the estimated model (a) using graphical approach c. Test the existence of autocorrelation of the estimated model (a) using Durbin-Watson test d. Test the existence of autocorrelation of the estimated model (a) using Breusch-Godfrey test e. Use the FGLS to solve the autocorrelation problem in the estimated model (a). Compare the results. Any noticeable differences