1)
Input the following data into Excel.
Or, you may open the Regression Homework Q1 data Excel file
Assume that Q = quantity of pizza, Price = price of pizza (in cents), Tuition = tuition (in thousands of dollars), Price of Soft Drink = price of soft drinks (in cents):
Q Price Tuition Price of Soft Drink
10 100 14 120
12 100 16 95
13 90 8 110
14 95 7 90
9 110 11 100
8 125 5 100
4 125 12 125
3 150 10 150
15 80 18 100
12 80 12 90
13 90 6 80
15 100 5 75
12 110 13 100
10 110 10 125
10 125 14 130
12 110 15 80
11 150 16 90
12 100 12 95
10 150 12 100
8 160 10 90
9 150 13 95
10 135 15 100
11 125 16 95
12 100 17 100
13 75 10 100
10 100 12 110
9 110 6 125
8 125 10 90
8 150 5 80
4 100 10 95
a) Estimate the linear demand function with Q as the dependent variable and Price as the independent
variable. Comment fully on the results and discuss the identification problem.
) Estimate the linear demand function with Q as the dependent variable and Price, Tuition, Price of Soft
Drinks, as the independent variables. Comment fully on the results.
c) Take the natural logarithm of all the variables and estimate the new demand function. Comment fully on
the results. What is the value of the price elasticity of demand? What is the value of the cross-price
elasticity of demand?
2)
Input the following data into Excel.
Regression Homework Q2 data Excel file
Assume we have the following time series data on variable Y below:
YEAR/Time Y=Output
1953 482
1954 312
1955 1221
1956 1800
1957 2419
1958 2958
1959 3454
1960 3897
1961 4317
1962 4705
1963 5056
1964 5378
1965 5681
1966 5964
1967 6216
1968 6425
1969 6632
1970 6836
1971 7003
1972 7170
1973 7315
1974 7456
1975 7595
1976 7715
1977 7815
1978 7918
1979 7995
1980 8079
1981 8164
1982 8239
1983 8292
1984 8355
1985 8402
1986 8461
1987 8493
1988 8539
1989 8561
1990 8609
1991 8649
1992 8660
1993 8680
1994 8726
1995 8740
1996 8760
1997 8783
1998 8805
1999 8812
2000 8854
2001 8841
2002 8869
2003 8893
2004 8883
2005 8888
2006 8904
2007 8913
2008 8913
2009 8923
2010 8948
2011 8962
a) Fit a simple trend model to the time series data and discuss the findings.
) Fit a quadratic trend model to the time series and discuss the findings: (square time).
c) Compare your results in part (b) to part (a) and use the best of the two models to forecast 2012 and 2013
values of Y.