The McKinsey Metric Applied to Cali Cities: It’s Not Pretty

The McKinsey Global Institute produced a fantastic study on how to solve California’s housing crisis.  Embedded in the study is this fantastic and illustrative figure:

McKinzee1

I decided to explore what it would look like to apply the final metric on the far right hand side to our cities in California.  It’s the ratio of new housing units relative to new population, per 1,000 people.  Let’s call this “the McKinsey ratio” for now.

Because American Community Survey estimates are unreliable for 2005 at a local scale, I get population data for the two years (2005 & 2014) from the Department of Finance’s Population Estimates tables for jurisdictions, and new housing data from Census permitting records.  They’re not perfect, but they work for this exercise.

First, I want to show you the distribution of “the McKinsey ratio” for the 157 jurisdictions that had adequate information and a population over 50,000 in 2005, with some of the state estimates in the figure above drawn over in dashed lines.  Communities of less than 50,000 are left out due to extreme results.

RealMckinzeeAdd

The first thing you notice is that the vast majority of California cities are on the smaller side of the state’s average as estimated by McKinsey.  A small but not insignificant amount of this is due to the data differences, I’m sure.  But regardless, just 24 of 157 jurisdictions score above the statewide average.  The first thing a Geographer notices is this variable might not be appropriate for jurisdictions, which can very dramatically in size (there are some with ratios above 1000 and below -1000 cut off for visual reasons).

But look at where other state’s stand.  Some folks are really pumping up Texas as the “Yes” state.  It’s ratio is actually somewhat close to California’s according to McKinsey.

But look at New York.  There are 14 sizable jurisdictions in our state producing as much as the New York average or more, and they are the first 14 ranked in the table below.  With only a couple of exceptions, they are all in southern California.  The table ranks jurisdictions in my dataset with over 50,000 residents by their “McKinsey Ratio” score.  Note that in areas that lost population, the ratios don’t really make sense.  But they are worth including to know where they are.  See anything interesting?

McKinsey Ratio Rank Jurisdiction McKinsey Ratio DOF Estimated Pop 2005
1 South Gate 2731 97,461
2 Rosemead 2570 54,677
3 Paramount 1150 55,606
4 Vacaville 906 93,954
5 Pasadena 764 137,501
6 Ontario 730 164,504
7 Arcadia 730 55,521
8 Pomona 696 152,106
9 Burbank 671 103,122
10 Gardena 642 59,277
11 Long Beach 622 470,781
12 Santa Ana 621 332,878
13 Torrance 605 143,738
14 Chino Hills 591 75,414
15 Fountain Valley 484 55,193
16 Encinitas 456 59,929
17 Lodi 439 61,431
18 Hawthorne 436 85,030
19 Downey 434 111,416
20 Lynwood 389 70,733
21 Newport Beach 331 81,678
22 Santa Monica 321 88,692
23 Los Angeles 317 3,769,131
24 Santa Barbara 312 88,854
25 Upland 308 72,216
STATEWIDE 308
26 Oceanside 289 166,958
27 Costa Mesa 289 109,030
28 Redding 281 87,152
29 Glendora 281 50,490
30 Garden Grove 276 168,219
31 Whittier 270 85,433
32 Laguna Niguel 257 63,310
33 Colton 257 51,522
34 San Buenaventura 245 103,374
35 La Habra 241 59,828
36 Orange 226 133,542
37 Vista 223 92,110
38 Anaheim 222 331,458
39 Thousand Oaks 219 124,169
40 Westminster 219 89,268
41 Highland 210 50,901
42 Walnut Creek 208 64,705
43 Inglewood 202 112,417
44 Redondo Beach 198 65,931
45 Oakland 198 389,937
46 Davis 196 63,889
47 San Diego 195 1,261,035
48 Buena Park 194 78,619
49 Modesto 190 201,980
50 Concord 189 122,373
51 Escondido 172 139,585
52 Fullerton 171 132,913
53 Oxnard 169 185,994
54 Mountain View 169 70,629
55 San Bernardino 169 201,295
56 San Clemente 167 62,286
57 San Leandro 162 81,802
58 El Cajon 161 97,364
59 San Francisco 159 780,187
60 Rialto 158 98,224
61 National City 155 55,948
62 Napa 154 74,499
63 Sacramento 153 442,662
64 Simi Valley 152 118,961
65 Livermore 147 78,019
66 Salinas 138 147,387
67 Petaluma 134 55,973
68 Pleasanton 132 66,890
69 Yorba Linda 131 62,574
70 Richmond 127 101,098
71 Woodland 124 52,474
72 Cupertino 124 53,632
73 Compton 123 96,133
74 Lake Forest 121 76,635
75 Stockton 120 277,485
76 Palo Alto 119 60,723
77 Daly City 119 100,379
78 Corona 116 144,719
79 Turlock 115 65,301
80 Santa Clara 112 107,058
81 San Jose 111 901,159
82 Union City 110 67,544
83 Santa Rosa 109 157,175
84 La Mesa 107 55,354
85 San Mateo 106 93,396
86 Rancho Cucamonga 105 156,854
87 Milpitas 105 62,177
88 South San Francisco 105 60,172
89 Riverside 104 284,715
90 Chino 99 74,463
91 Fremont 99 206,712
92 Fresno 96 457,786
93 Berkeley 95 105,880
94 Redwood City 95 74,621
95 Santee 95 52,110
96 Fairfield 89 102,553
97 Tustin 89 70,116
98 Folsom 85 66,362
99 Pittsburg 84 61,120
100 San Rafael 83 56,247
101 Camarillo 83 61,515
102 Santa Cruz 79 56,387
103 Chula Vista 73 219,939
104 Hayward 72 140,530
105 Merced 70 72,402
106 Santa Maria 69 91,313
107 Alameda 68 71,727
108 Sunnyvale 66 131,853
109 Lancaster 64 137,268
110 Carlsbad 57 94,161
111 Antioch 57 99,713
112 Yuba City 56 57,975
113 Manteca 56 60,598
114 Clovis 55 84,552
115 Tracy 54 78,228
116 San Marcos 51 72,564
117 Hemet 51 68,943
118 Roseville 49 104,105
119 Palmdale 49 135,179
120 Chico 49 72,459
121 Visalia 48 106,054
122 Rocklin 46 51,206
123 Madera 46 51,735
124 Bakersfield 44 299,363
125 Moreno Valley 44 167,262
126 Hesperia 36 76,548
127 Santa Clarita 35 165,431
128 Irvine 35 179,975
129 Temecula 35 78,808
130 Murrieta 32 85,769
131 Elk Grove 32 125,703
132 Rancho Cordova 31 55,476
133 Fontana 31 161,728
134 Victorville 23 87,813
135 Perris 23 50,650
136 Indio 21 62,024
137 San Ramon 10 53,923
138 Cerritos -62 51,674
139 Lakewood -85 81,040
140 Huntington Park -132 61,318
141 Carson -178 94,236
142 El Monte -210 118,295
143 Baldwin Park -223 77,383
144 Norwalk -282 106,921
145 Mission Viejo -518 95,427
146 Alhambra -548 86,541
147 West Covina -642 107,955
148 Pico Rivera -652 64,635
149 Vallejo -757 117,993
150 Monterey Park -884 61,647
151 Diamond Bar -925 56,703
152 Redlands -1030 68,471
153 Huntington Beach -1430 192,581
154 Montebello -2669 63,359
155 Citrus Heights -2890 85,153
156 Bellflower -3802 76,306
157 Glendale -5403 197,042

 

 

Published by mattdpalm

Doctoral Student UC Davis USDOT Graduate Eisenhower Fellow 2014-2015

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