Boston Metropolitan Area
City
Abington
Acton
Amesbury
Andover
Arlington
Ashland
Avon
Bedford
Bellingham
Belmont
Beverly
Billerica
Bolton
Boston
Boxborough
Boxford
Braintree
Bridgewater
Brockton
Brookline
Burlington
Cambridge
Canton
Carlisle
Carver
Chelmsford
Chelsea
Cohasset
Concord
Danvers
Dedham
Dover
Duxbury
East Bridgewater
Easton
Essex
Everett
Foxborough
Land
Area
(sq.mi)
9,95
19,98
12,41
31,01
5,18
12,45
4,38
13,74
18,50
4,66
15,44
25,89
19,93
48,42
10,37
23,97
13,89
27,49
21,47
6,79
11,81
6,43
18,94
15,36
37,55
22,65
2,19
9,89
24,92
13,28
10,45
15,33
23,76
17,24
28,44
14,16
3,38
20,08
Distance
to CBD
18,496
21,436
35,667
21,1
6,268
21,726
15,786
14,347
28,4
6,615
16,589
17,482
28,485
0
25,588
21,182
9,914
25,846
19,144
3,653
12,278
3,327
14,525
18,916
36,245
22,262
2,669
15,396
16,373
16,374
9,746
13,832
29,57
23,068
23,368
23,62
3,473
22,919
1970
Population
12.334
14.770
11.388
23.695
53.524
8.882
5.295
13.513
13.967
28.285
38.348
31.648
1.905
641.071
1.451
4.032
36.050
11.829
89.040
58.689
21.980
100.361
17.100
2.871
2.420
31.432
30.625
6.954
16.148
26.151
26.938
4.529
7.636
8.347
12.157
2.670
42.485
14.218
1990
Population
13.817
17.872
14.997
29.151
44.630
12.066
4.558
12.996
14.877
24.720
38.195
37.609
3.134
574.283
3.343
6.266
33.836
21.249
92.788
54.718
23.302
95.802
18.530
4.333
10.590
32.383
28.710
7.075
17.076
24.174
23.782
4.915
13.895
11.104
19.807
3.260
35.701
14.637
Framingham
Franklin
Georgetown
Gloucester
Groveland
Halifax
Hamilton
Hanover
Hanson
Harvard
Haverhill
Hingham
Holbrook
Holliston
Hopedale
Hopkinton
Hudson
Hull
Ipswich
Kingston
Lakeville
Lawrence
Lexington
Lincoln
Littleton
Lowell
Lynn
Lynnfield
Malden
Manchester
Mansfield
Marblehead
Marlborough
Marshfield
Maynard
Medfield
Medford
Medway
Melrose
Merrimac
Methuen
Middleborough
Middleton
Milford
25,12
26,74
12,94
25,97
8,94
15,87
14,60
15,61
15,02
26,36
33,33
22,47
7,35
18,71
5,15
26,56
11,51
2,97
32,61
18,53
29,90
6,97
16,40
14,37
16,62
13,78
10,81
10,15
5,09
7,84
20,46
4,53
21,09
28,46
5,24
14,51
8,14
11,45
4,70
8,53
22,41
69,56
13,97
14,60
19,036
25,69
25,607
27,004
27,845
27,363
20,771
21,19
21,657
28,452
28,917
11,866
14,308
21,646
29,26
25,326
25,984
8,695
24,838
30,484
35,906
24,677
10,423
13,321
26,203
23,087
9,375
12,505
4,623
21,231
23,919
14,227
25,181
25,876
20,577
17,295
4,78
22,857
6,926
32,8
26,307
33,08
16,524
27,839
64.048
17.830
5.290
27.941
5.382
3537
6.373
10.107
7.148
12.536
46.120
18.845
11.775
12.069
4.292
5.981
16.084
9.961
10.750
5.999
4.376
66.915
31.886
7.567
6.380
94.239
90.294
10.826
56.127
5.151
9.939
21.295
27.936
15.223
9.710
9.821
64.397
7.938
33.180
4.245
35.456
13.607
4.044
19.352
64.989
22.095
6.384
28.716
5.214
6526
7.280
11.912
9.028
12.329
51.418
19.821
11.041
12.926
5.666
9.191
17.233
10.466
11.873
9.045
7.785
70.207
28.974
7.666
7.051
103.439
81.245
11.274
53.884
5.286
16.568
19.971
31.813
21.531
10.325
10.531
57.407
9.931
28.150
5.166
39.990
17.867
4.921
25.355
Millis
Milton
Nahant
Natick
Needham
Newbury
Newburyport
Newton
Norfolk
North Andover
North Reading
Norton
Norwell
Norwood
Peabody
Pembroke
Plymouth
Quincy
Randolph
Raynham
Reading
Revere
Rockland
Rockport
Rowley
Salem
Salisbury
Saugus
Scituate
Sharon
Sherborn
Somerville
Southborough
Stoneham
Stoughton
Stow
Sudbury
Swampscott
Taunton
Tewksbury
Topsfield
Wakefield
Walpole
Waltham
12,16
13,04
1,24
15,09
12,61
24,25
8,38
18,06
14,84
26,67
13,26
28,71
20,88
10,48
16,40
21,85
96,48
16,79
10,07
20,50
9,93
5,92
10,02
7,07
18,72
8,10
15,43
10,99
17,18
23,31
15,96
4,11
14,15
6,14
16,04
17,62
24,37
3,05
46,62
20,72
12,66
7,47
20,53
12,70
20,179
7,502
8,599
15,702
10,261
32,755
32,767
7,783
21,395
23,852
15,021
27,871
19,245
13,406
13,499
23,641
34,22
7,881
13,582
28,354
11,71
4,234
17,39
30,416
26,454
13,912
34,943
7,786
20,457
17,343
17,886
2,862
24,047
8,658
16,288
23,418
18,298
10,646
31,746
19,588
20,116
10,264
17,863
9,074
5.686
27.190
4.119
31.057
29.748
3.804
15.807
91.263
4.656
16.284
11.264
9.487
7.796
30.815
48.080
11.193
18.606
87.966
27.035
6.705
22.539
43.159
15.674
5.636
3.040
40.556
4.179
25.110
16.973
12.367
3.309
88.779
5.798
20.725
23.459
3.984
13.506
13.578
43.756
22.755
5.225
25.402
18.149
61.582
7.613
25.725
3.828
30.510
27.557
5.623
16.317
82.585
9.270
22.792
12.002
14.265
9.279
28.700
47.039
14.544
45.608
84.985
30.093
9.867
22.539
42.786
16.123
7.482
4.452
38.091
6.882
25.549
16.786
15.517
3.989
76.210
6.628
22.203
26.777
5.328
14.358
13.650
49.832
27.266
5.754
24.825
20.212
57.878
Wareham
Watertown
Wayland
Wellesley
Wenham
West Bridgewater
West Newbury
Westborough
Westford
Weston
Westwood
Weymouth
Whitman
Wilmington
Winchester
Winthrop
Woburn
Wrentham
35,79
4,11
15,24
10,18
7,72
15,74
13,52
20,52
30,61
17,02
10,97
17,01
6,96
17,14
6,04
1,99
12,68
22,20
44,73
6,349
15,424
12,654
34,326
23,634
30,858
29,121
24,61
12,452
13,074
11,323
20,243
14,25
7,599
4,098
9,602
24,418
11.492
39.307
13.461
28.051
3.849
7.152
2.254
12.594
10.368
10.870
12.750
54.610
13.059
17.102
22.269
20.335
37.406
7.315
19.232
33.284
11.874
26.615
4.212
6.389
3.421
14.133
16.392
10.200
12.557
54.063
13.240
17.651
20.267
18.127
35.943
9.006
Source:
2007 data come from the Massachusetts Government’s Dept of Health and Human Services, and the De
2000
Population
2007
Population
14.605
20.331
16.450
31.247
42.389
14.674
4.443
12.595
15.314
24.194
39.862
38.981
1.148
589.141
4.868
7.921
33.828
25.185
94.304
57.107
22.876
101.355
20.775
4.717
11.163
33.858
35.080
7.261
16.993
25.212
23.464
5.558
14.248
12.974
22.299
3.267
38.037
16.246
16.365
20.753
16.429
33.284
41.144
15.796
4.303
13.146
15.908
23.356
39.198
42.038
4.481
599.351
5.097
8.074
34.422
25.514
93.092
54.809
25.034
101.388
21.916
4.882
11.547
34.128
38.203
7.182
16.840
26.736
24.132
5.627
14.444
13.879
22.969
3.323
37.269
16.298
1967
Employment
2027
2356
3332
11123
6008
4555
1615
12198
1276
3905
10502
3621
440
372.306
120
171
12301
3113
30784
12560
10375
92475
5675
264
195
3855
10056
1186
6634
8873
9084
463
800
1736
1879
404
13515
5552
1990
Employment
3.306
9.395
4.399
24.873
9.153
4.075
4.975
24.620
2.949
6.877
15.406
20.009
1.471
537.664
2.286
695
29.610
5.061
38.584
18.123
33.103
103.278
19.068
649
1.299
15.065
9.670
2.024
11.643
22.291
14.050
620
2.256
3.377
5.855
1.089
12.086
8.506
2000
Employment
4.203
11.091
4.773
34.258
8.607
4.464
6.858
20.170
5.028
6.315
18.963
26.626
2.388
583.955
2.248
906
31.666
7.211
37.737
16.434
39.350
115.625
20.978
905
1.920
22.801
13.124
2.354
12.944
22.170
14.965
828
2.601
3.418
9.344
1.459
10.407
9.469
66.910
29.560
7.377
30.273
6.038
7.500
8.315
13.164
9.495
5.981
58.969
19.882
10.785
13.801
5.907
13.346
18.113
11.050
12.987
11.780
9.821
72.043
30.355
8.056
8.184
105.167
89.050
11.542
56.340
5.228
22.414
20.377
36.255
24.324
10.433
12.273
55.765
12.448
27.134
6.138
43.789
19.941
7.744
26.799
64.786
31.381
8.147
30.308
6.923
7.700
8.188
13.966
9.956
6.001
59.902
22.394
10.663
13.941
6.165
14.307
19.580
11.067
13.245
12.339
10.587
70.066
30.332
7.994
8.714
103.512
87.122
11.382
55.712
5.265
22.993
20.039
38.065
24.576
10.177
12.266
55.565
12.749
26.782
6.425
43.979
21.245
9.347
27.263
24925
2353
935
7915
418
197
721
2948
1370
445
15754
3873
1518
1459
3335
889
2870
1023
2330
983
503
30867
5680
635
1722
34955
43992
1615
15914
716
2042
2771
5690
1097
3918
1693
15918
994
6161
391
4582
3496
969
4620
39.047
7.156
1.483
11.268
822
683
1.237
6.569
1.706
1.004
17.378
9.730
3.035
4.209
1.526
3.900
8.381
1.085
3.082
4.656
1.940
23.417
19.411
1.671
5.342
40.116
29.682
3.337
19.076
1.266
8.771
4.498
20.531
4.201
7.403
3.509
19.513
1.796
6.082
718
13.482
6.612
2.489
11.181
45.892
15.794
2.434
12.383
1.095
1.098
1.399
7.118
1.839
1.039
19.160
11.727
2.782
5.146
1.726
5.983
9.647
1.320
3.927
5.318
2.960
23.626
21.513
1.875
6.189
34.694
25.214
5.055
17.515
1.584
12.340
5.109
28.869
4.890
4.962
3.483
20.270
2.750
6.545
957
14.170
7.731
4.927
13.772
7.902
26.062
3.632
32.170
28.911
6.717
17.189
83.829
10.460
27.202
13.837
18.036
9.765
28.587
48.129
16.927
51.701
88.025
30.963
11.739
23.708
47.283
17.670
5.606
5.500
40.407
7.827
26.078
17.863
17.408
4.200
77.478
8.781
22.219
27.149
5.902
16.841
14.412
55.976
28.851
6.141
24.804
22.824
59.226
7.927
25.691
3.519
31.975
28.263
6.926
17.144
83.271
10.646
27.637
14.021
19.222
10.271
28.172
51.441
18.595
55.188
91.622
30.168
13.641
23.129
55.341
17.780
7.633
5.839
40.922
8.521
27.192
17.881
17.033
4.217
74.405
9.484
21.508
26.951
6.327
17.159
13.994
55.783
29.607
6.067
24.706
23.086
59.758
1017
2807
292
13239
12365
306
3658
35398
885
13521
1249
1924
776
11738
14379
779
4280
38022
5155
1225
3559
5995
3729
997
529
19647
1005
5322
1497
1372
229
19745
932
5235
4771
307
3606
1814
14068
3168
926
9428
5670
43877
2.124
5.128
496
19.331
18.449
914
8.256
44.793
2.373
16.758
3.454
4.066
5.511
22.927
21.692
3.832
16.066
39.938
9.692
4.503
6.060
8.176
6.643
1.344
1.446
20.191
1.995
9.875
2.906
2.882
551
20.136
4.097
8.107
13.192
2.260
9.706
2.747
19.882
9.489
1.779
10.904
7.598
63.087
2.186
6.051
367
24.156
18.310
1.141
10.149
48.105
3.033
19.271
6.326
6.112
8.461
24.639
27.056
5.280
19.100
47.227
10.421
6.890
7.455
8.776
8.146
1.451
2.394
18.051
2.771
11.128
2.987
3.417
522
23.220
6.277
8.032
12.452
2.211
6.491
3.432
24.319
17.262
2.896
15.078
9.608
64.851
20.335
32.986
13.100
26.613
4.440
6.634
4.149
17.997
20.754
11.469
14.117
53.988
13.882
21.363
20.810
18.303
37.258
10.554
21.154
32.521
13.017
26.985
4.615
6.679
4.269
18.459
21.790
11.698
14.010
53.272
14.385
21.679
21.137
20.154
37.042
11.116
1891
18809
3983
6308
345
1054
356
4338
1845
1770
2215
7498
3362
6926
3923
1906
11234
3661
5.621
17.178
3.286
18.203
661
4.922
502
18.036
5.565
2.928
9.157
14.653
2.843
19.771
6.729
2.986
35.608
4.268
h and Human Services, and the Dept of Labor and Workforce Development
6.605
19.616
3.884
19.263
1.187
6.902
704
25.050
11.484
3.003
10.541
16.828
2.951
21.736
7.635
2.472
41.212
4.887
2007
Employment
4.023
10.089
4.709
32.440
7.997
4.994
5.420
18.135
5.636
6.394
21.129
22.867
1.527
562.720
3.834
947
28.204
7.757
38.026
14.279
38.146
107.730
23.451
768
2.777
21.229
13.348
2.499
12.808
25.289
14.869
812
2.871
2.720
9.669
1.282
12.761
10.333
45.646
16.227
2.351
10.838
1.175
1.326
1.468
7.063
1.624
1.064
18.207
11.955
2.741
5.337
1.668
8.934
10.405
1.338
4.233
5.761
3.341
23.274
19.161
1.759
5.018
33.353
23.024
5.757
15.261
1.680
11.193
5.027
30.387
5.518
5.130
2.896
18.123
3.429
6.278
688
15.214
8.895
4.601
15.264
2.216
5.402
508
23.588
19.831
1.520
10.638
47.480
2.859
13.718
7.825
6.211
8.433
24.803
24.665
6.235
23.042
46.826
8.008
8.623
6.063
9.384
8.073
1.389
2.721
18.426
2.772
10.584
3.307
3.665
655
21.451
7.105
7.771
13.628
2.336
8.141
3.505
25.887
15.628
2.248
14.599
10.533
54.404
8.462
19.079
3.248
17.645
1.410
5.956
753
24.811
11.879
3.667
9.436
18.592
3.192
19.289
8.518
1.985
38.837
6.337
University of Southern California
Sol Price School of Public Policy
red 362—Real Estate Development Fundamentals
Spring 2020
Assignment 2
Professor: Jorge De la Roca
Assignment due date is Thursday, February 27 at the beginning of class. All answers must be
clearly explained. Answers may be either hand-written or typed, as long as they are clear and
legible. Excel graphs should be as clear and descriptive as possible.
Short questions (21 points)
1. (3 points) Classify the following as contributing to either localization economies or urbanization economies (or both), and provide a brief explanation of your reasoning.
• Lots of good computer engineers in Silicon Valley
• Frequent flights between Newark Airport and Los Angeles
• A Kinko’s near University of Southern California
2. (4 points) Consider two cities, Flexville and Rigid City, that have the same equilibrium wage
and the same equilibrium total employment. The export industries in the two cities produce
the same good. In Flexville, export firms produce with variable factor proportions—that is,
they can easily adjust the amount of labor in response to changes in the wage, i.e., the price
of labor. In Rigid City, export firms produce with fixed (or less variable) factor proportions,
meaning it is quite difficult to change the amount of labor. Suppose that both cities find a
way to increase the quality of residential public services (e.g. public schools, parks, libraries)
without increasing taxes. Use two supply-demand graphs, one for each city, to show the
effects of the improvements in public services on
• equilibrium employment
• the equilibrium wage
3. (3 points) In a 1989 report, a consulting firm estimated the economic impacts of moving the
Los Angeles Raiders (a professional football team) to Sacramento. The authors predicted
that people would spend $28 million per year on the team (tickets, food, merchandise, and
parking). (You can assume this is a reasonable estimate.) The consulting firm then used
an economic multiplier of 2.2 to arrive at their estimate of the total economic impact of the
Raiders on the city of Sacramento—$61.6 million per year. What implicit assumptions have
they made in their analysis? Provide a brief assessment of their conclusion.
4. (2 points) Suppose you operate a small manufacturing firm in Santa Monica and you recently
developed a unique, new production process that will allow your shop to earn $500 more per
month in profit. Your landlord hears about this and smiles since she remembers from her real
estate class that all economic development benefits accrue to landowners. She says, “since
the supply of land is inelastic (e.g. very steep), you will now have to pay me $500 more per
month in rent.” Is your landlord correct? Explain.
5. (3 points) There is some evidence that people have become more sensitive to air pollution.
If this is true, what influence may it have on wages in different cities, and how will it likely
affect the location decisions of firms?
6. (4 points) How would you expect the division of land between office firms and manufacturing firms—and their relative locations—to change if per unit freight costs decline (that is, it
becomes cheaper to ship manufacturing goods)? Use a single bid-rent diagram to illustrate
your answer.
7. (2 points) Suppose a city restricts the heights of residential structures. The maximum height
is four stories, the height that would normally occur at a distance of five miles from the
city center. Draw two residential bid-rent curves on the same graph, one for the city in the
absence of height restrictions and one with height restrictions.
Analysis of suburbanization in Boston (14 points)
This exercise requires you to examine suburbanization patterns in the Boston metropolitan area.
Using real world data, you will study how the density of population and employment in Boston
area towns change as one moves away from the Boston central business district (cbd) and to
examine how these patterns changed between 1970 and 2007. The required data are posted on
Blackboard in an Excel file. The data set includes the population and employment of municipalities
in the Boston metropolitan area in 1970, 1990, 2000, 2007, as well as their land area and distance to
the cbd. (Note that the employment figures are for 1967, 1990, 2000, and 2007.)
• Calculate the population and employment density for each town in 2007 and plot these
densities against distance from the central business district (cbd).
Specifically, use Excel to create two different xy-scatterplot graphs (using the Excel Chart tab).
Distance to Boston (the cbd) should be on the x-axis and the density measure should be on
the y-axis (population density in 2007 and employment density in 2007). Note that density
is defined simply as (population divided by land area) and (employment divided by land
area).
Excel help: To create a scatterplot in Excel, the density data must be immediately to the right
of the “distance from cbd” column. First create new columns and calculate four density
measures for each town in the Boston metropolitan area. Then, you can add two columns for
the distance data—one immediately to the left of each density column. Then highlight the
data included in a single pair of distance-density columns and click on the Excel Chart tab
and then pick a type of scatterplot.
At the bottom of the assignment, I have included a sample graph for population in 1970 in
the Boston metro area to give you an idea of what the end product should look like.
• After producing these graphs, please answer the following questions:
1. (2 points) Do the graphs generally appear consistent with the predictions of location
theory, or the traditional urban model? Why or why not? (Again, take Boston to be the
cbd.)
2. (1 point) Why should population density be higher nearer to the cbd?
3. (1 point) Are there any notable outliers in the data? Be specific. What might explain
their unusual patterns?
2
• Population
4. (1 point) How many people lived in towns within 15 miles of Boston in 1970, 1990, 2000,
and 2007?
5. (1 point) How many people lived in towns more than 15 miles away from Boston during
these four years? (Creating a table like the one below may help.)
1970
1990
2000
2007
< 15 miles > 15 miles
Total
6. (1 point) What was the percentage change in the population living within 15 miles of
Boston during 1970-1990 and from 1990-2007?
7. (1 point) What was the percentage growth in the population living more than 15 miles
away from Boston during these two time periods?
• Employment
8. (2 points) In 1967, 1990, 2000, and 2007, how many jobs were there in towns within 5
miles of Boston, between 5–10 miles away, between 10–15 miles away, and beyond 15
miles?
1967
1990
2000
2007
< 5 miles 5–10 miles 10–15 miles > 15 miles
Total
9. (1 point) What was the percentage change in employment that occurred within each of
these four distance bands from 1967–1990, and from 1990–2007?
• (3 points) Analysis
– What can you say generally about suburbanization in Boston during these two time
periods?
– How do changes between 1967/1970 and 1990 compare to the changes that occurred
between 1990 and 2007?
– Is the pace of suburbanization similar during each time period?
3
Sample graph
4

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