NEED ANSWERED ASAP. Explain all steps used and attach excel data. Estimation. Us
ID: 3225431 • Letter: N
Question
NEED ANSWERED ASAP. Explain all steps used and attach excel data.
Estimation. Use OLS to estimate the linear and power forms of the demand function for beef:
Specification A : Qbeef = a + b1Pbeef+b2Ppork+b3Pchicken+b4I+b5T
Specification B: lnQbeef = a + b1lnPbeef+b2lnPpork+b3lnPchicken+b4lnI+b5T
where
Qbeef is per capita consumption of beef (pounds);
Pbeef is real retail price of beef (cents per lb. on a retail weight basis);
Ppork is real retail price of pork (cents per lb. on a retail weight basis);
Pchicken is real retail price of chicken (cents per lb. on a retail weight basis);
I is real per capita disposable personal income (dollars);
T is the year dummy (=1 for 1970, 2 for 1971, 3 for 1973, etc.).
Year Per capita consumption (pounds) Per capita consumption (pounds) Per capita consumption (pounds) Nominal retail price (cents per lb. on a retail weight basis) Nominal retail price (cents per lb. on a retail weight basis) Nominal retail price (cents per lb. on a retail weight basis) Annual, seasonally adjusted per capita nominal disposable income (dollars) Annual, seasonally adjusted CPI-U (index, 1982-84 = 100) Beef Pork Broilers Beef Pork Broilers 1970 84.6 55.8 36.6 99.9 77.4 40.8 3713 38.842 1971 83.9 60.5 36.5 106.2 69.8 41.1 3998 40.483 1972 85.3 54.7 38.1 116.6 82.7 41.4 4287 41.808 1973 80.5 48.7 36.7 139.7 109.2 59.6 4747 44.425 1974 85.6 52.7 36.6 143.8 107.8 56.0 5134 49.317 1975 88.2 42.9 36.3 152.2 134.6 63.3 5645 53.825 1976 94.3 45.5 39.4 145.7 134.0 59.7 6079 56.933 1977 91.8 47.0 40.2 145.8 125.4 60.1 6612 60.617 1978 87.3 47.0 42.5 178.8 143.6 66.5 7321 65.242 1979 78.1 53.3 46.0 222.4 152.5 67.7 8037 72.583 1980 76.6 57.3 45.8 233.6 147.5 70.9 8860 82.383 1981 77.3 54.7 46.9 234.7 161.2 73.2 9785 90.933 1982 77.0 49.1 47.0 238.4 185.6 71.4 10441 96.533 1983 78.6 51.8 47.4 234.1 179.7 72.5 11169 99.583 1984 78.4 51.5 49.2 235.5 171.4 81.0 12283 103.933 1985 79.2 51.9 51.0 228.6 171.4 76.3 12991 107.600 1986 78.8 49.0 52.0 226.8 188.8 83.5 13660 109.692 1987 73.9 49.2 55.1 238.4 199.4 78.5 14273 113.617 1988 72.6 52.5 55.3 250.3 194.0 85.4 15385 118.275 1989 69.0 52.0 56.6 265.7 193.5 92.7 16379 123.942 1990 67.7 49.7 59.5 281.0 224.9 89.9 17234 130.658 1991 66.6 50.2 61.9 288.3 224.2 88.0 17688 136.167 1992 66.1 52.7 65.5 284.6 209.5 86.9 18683 140.308 1993 64.6 51.9 67.9 293.4 209.1 89.0 19210 144.475 1994 66.3 52.5 68.8 282.9 209.5 90.1 19905 148.225 1995 66.6 51.7 67.9 284.4 206.1 91.7 20753 152.383 1996 67.1 48.3 69.2 280.2 233.7 97.3 21614 156.858 1997 65.7 47.8 71.4 279.5 245.0 100.2 22526 160.525 1998 66.7 51.5 72.0 277.1 242.7 104.4 23759 163.008 1999 67.5 52.6 76.3 287.8 241.5 105.6 24616 166.583 2000 67.8 51.2 77.0 306.4 258.2 107.1 26205 172.192 2001 66.3 50.4 76.8 337.7 269.4 110.5 27179 177.042 2002 67.8 51.6 80.7 331.5 265.7 107.4 28126 179.867 2003 65.0 51.9 81.8 374.6 265.8 103.4 29200 184.000 2004 66.2 51.5 84.5 406.5 279.2 107.0 30699 188.908 2005 65.6 50.1 86.0 409.1 282.7 105.6 31762 195.267 2006 65.9 49.5 86.7 397.0 280.8 104.9 33591 201.558 2007 65.3 50.8 85.3 415.8 287.1 111.5 34828 207.344 2008 62.5 49.5 83.5 432.5 293.7 120.7 36105 215.254 2009 61.1 50.2 79.8 426.0 292.0 128.1 35618 214.565 2010 59.6 47.8 82.4 439.5 311.4 126.3 36274 218.076 2011 57.3 45.7 82.9 482.7 343.4 129.1 37811 224.923 2012 57.3 45.9 80.4 498.6 346.7 133.5 39454 229.586 2013 56.3 46.8 81.8 528.9 364.4 149.0 39156 232.949 2014 54.1 46.4 83.3 597.1 402.0 153.0 40837 236.704 2015 53.9 49.7 88.9 628.9 385.3 148.0 42094 236.987 2016 estimated* 55.4 49.9 89.6 620.0 378.0 142.0 43431 240.009Explanation / Answer
First import data in excel
Go Data - Data Analysis- Regression
which variable is used as a explanatory variable, write in x range
dependnet variable write in y range
Specification A : Qbeef = a + b1Pbeef+b2Ppork+b3Pchicken+b4I+b5T
Specification B: lnQbeef = a + b1lnPbeef+b2lnPpork+b3lnPchicken+b4lnI+b5T
SUMMARY OUTPUT Regression Statistics Multiple R 0.944718 R Square 0.892492 Adjusted R Square 0.879381 Standard Error 3.592564 Observations 47 ANOVA df SS MS F Significance F Regression 5 4392.952 878.5903 68.07339 9.05E-19 Residual 41 529.1672 12.90652 Total 46 4922.119 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 89.24187 3.985625 22.39093 1.31E-24 81.19273 97.291 Pbeef -0.05192 0.023165 -2.24107 0.0305 -0.0987 -0.00513 Ppork 0.085937 0.058065 1.480025 0.14651 -0.03133 0.203201 Pchicken -0.07561 0.121785 -0.62081 0.538161 -0.32155 0.170344 I 0.001259 0.000506 2.49113 0.016874 0.000238 0.00228 T -1.70347 0.489644 -3.479 0.001207 -2.69233 -0.71461Related Questions
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