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Buiding A Model of the Demand for Water in Los Angeles

Instruction:

1. Your goal is to build a model of the demand for water in Los Angeles County as a function of population, rainfall and other variables.

2. Carefully take into consideration issues like specification bias, multicolinearity, autocorrelation, or heteroskadasticity in the modeling.

3. Give out estimation results of the final model you chose and your explanation of the model in Word file.

4. Send the file to me as attachment in email by Dec. 16th.

Data Description:

W - Consumption of water in Los Angeles county in year t (hundreds of millions of gallons)
POP - Population in Glendale, CA in year t (thousands of people)
T - Average annual temperature at the Los Angeles civic center in year t (degrees F)
R - Inches of rainfall at the Los Angeles civic center in year t.
P - average price of a gallon of water in Los Angeles in year t. (dollars)
CO - A dummy variable to measure the conservation efforts undertaken in the last two years in the sample, when there was a
severe drought in Northern California (the source of much of L.A.'s water) even though no such drought took place in
Southern California.
Y- Total personal income for LA county in year t (in billions of dollars)

Note:

1. Population data for LA county were unavailable for the entire sample when the data were collected, so population in Glendale
was used as a proxy.

2. Conservation efforts took place only during the last two years in the sample, so if conservation efforts have an effect but with a lag,
we'd be forced to use a "one-time dummy".

3. Thus there are reasons to be concerned that population and conservation are not accurately measured in the sample.

Year W POP T R P Y
1 53.385 108.7 63.6 26.21 0.23 9.5345
2 60.311 110.78 64.6 9.46 0.22 10.783
3 60.064 113.34 64.9 11.99 0.22 11.991
4 58.939 114.79 63.7 11.94 0.23 13.019
5 62.33 115.78 64.8 16 0.22 14.288
6 62.361 117.11 65.7 9.54 0.23 15.428
7 65.409 118.26 67.1 21.13 0.25 15.876
8 71.914 118.38 67.3 5.58 0.25 17.327
9 70.417 119.44 65.7 8.18 0.26 18.002
10 73.549 121.88 65.3 4.83 0.26 18.888
11 69.093 123.12 62.3 18.79 0.27 20.342
12 67.479 126.77 65.1 8.38 0.26 21.581
13 73.277 129.83 63.2 7.93 0.26 22.979
14 68.947 132.44 64.3 13.69 0.26 24.228
15 73.437 135.79 66 20.44 0.26 26.099
16 72.34 137.05 66.5 22 0.28 27.924
17 76.044 137.27 66.2 16.58 0.3 29.908
18 75.155 137.92 65.4 27.47 0.34 32.407
19 81.664 132.66 66.1 7.77 0.37 34.098
20 80.544 132.75 65.1 12.32 0.39 34.314
21 81.418 133.11 66.5 6.54 0.43 37.116
22 76.707 132.7 65 17.45 0.44 39.191
23 80.615 136.51 65.3 16.69 0.47 43.784
24 80.062 138.01 63 10.7 0.51 47.822
25 81.467 139.26 65.2 11.01 0.6 53.334
26 69.315 133.92 65.9 14.97 0.75 59.267

Microeconomics, Economics

  • Category:- Microeconomics
  • Reference No.:- M91574792

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