Graduate Business Administration 509

MANAGERIAL DECISION MAKING

Fall 2003
 
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Assignment 1 - Demand Estimation

Data

The data represents the demand for single family housing in a metropolitan area from 1980 - 2001.  They are entered into an Excel spreadsheet that was sent to you as an e-mail attachment.  The data is also given in a table below, and are coded as follows:

! Population = population of the metropolitan area in thousands

! CPI = Consumer Price Index for the area

! Quantity = quantity of single family housing units sold in a year

! Price = average price of single family housing per square foot

! Income = median income in the area

! Rent = average rent for apartments in the area

Analysis

Use your data and a spreadsheet program to do to estimate the demand for single family housing in the metropolitan area.  Write a brief report which includes the following:

  1. Indicate the form of the model used, including the expected signs of the coefficients for each variable.

  2. Analyze the validity of the model, including a discussion of the R2, the F-test, and t-tests.

  3. Calculate the point elasticity for each of the variables, based on the data for the latest period. Use the estimated elasticities in your role as a consultant to a land development company to answer the following questions:

    a. What should the company do to the price of the houses to increase its revenue from their sale?

    b. How will a slowing in the local economy affect the demand for the housing?

    c. How significant are apartments as competition for single family housing?

Final Output

Please submit a copy of your analysis along with supporting computer output by Thursday, October 2. If the output is a hard copy, it should be typed on 8 ½ x 11 or A4 paper. Please do not submit the report in a special report cover; a stable in the upper left hand corner would be adequate. The output may also be submitted as an e-mail attachment.

Population CPI Quantity Price Income Rent
1980 875.5 79.4 23059 59.17 23.3 435
1981 887.5 90.1 20453 68.28 24.9 470
1982 903.8 96.2 20373 69.34 24.7 484
1983 929.1 99.0 20964 70.31 25.2 503
1984 957.6 104.8 18953 72.22 26.9 518
1985 979.3 110.4 19417 77.18 28.7 534
1986 1007.0 113.5 22913 84.13 30.1 609
1987 1031.8 117.5 23491 91.83 31.8 670
1988 1058.7 123.4 25876 105.12 33.7 690
1989 1087.8 130.6 24163 122.07 35.0 704
1990 1118.3 138.4 21949 128.79 36.5 760
1991 1130.0 143.4 19645 129.88 36.3 783
1992 1149.6 147.4 21024 125.81 35.5 744
1993 1171.6 150.6 18567 119.38 35.5 729
1994 1184.8 154.5 21879 119.38 35.9 758
1995 1197.7 156.8 24176 115.34 37.2 841
1996 1183.1 160.9 24686 116.87 40.2 866
1997 1190.2 163.7 27341 123.20 42.3 953
1998 1214.0 166.9 29462 139.44 44.7 1010
1999 1245.5 172.8 25476 159.54 47.1 1030
2000 1277.2 182.8 30375 183.99 53.1 1071
2001 1250.7 191.2 (X) 191.16 56.3 1082

In place of the (X) for quantity in 2001, use the number next to your name below:

Name (X)
Albano 28000
Alipour 28050
Arendale 28100
Austin 28150
Barrios 28200
Boyer 28250
Bui 28300
Carlson 28350
Cervantes 28400
Chavez 28450
Chen, Leo 28500
Chen, Tia 28550
Coleman 28600
Creighton 28650
Cugini 28700
Curry 28750
Dabrowski 28800
Diodosio 28850
Dorsey 28900
Felke 28950
Fenske 29000
Fernandez 29050
Flores 29100
Foerder 29150
Fullerton 29200
Geldern 29250
Gerhardt 29300
Gillen 29350
Gleason 29400
Grau 29450
Gupta 29500
Gutierrez 29550
Hawkins 29600
Huang 29650
Huszar 29700
Jimenez 29750
Kaloti 29800
Kim 29850
Lalinde 29900
Lanjewar 29950
Lee 30000
Leibham 30050
Levy 30100
Lopez 30150
Meiners 30200
Morga 30250
Nunes 30300
O'Donnell 30350
Osborne 30400
Otani 30450
Patel, Pramesh 30500
Patel, Roshni 30550
Peyre 30600
Richardson 30650
Ruiz 30700
Sevick 30750
Shah 30800
Smith 30850
Sorenson 30900
Stearrett 30950
Tanz 31000
Tatarian 31050
Tchang 31100
Vanderhoof 31150
Villani 31200
Wang 31250
Weller 31300
Zachry 31350