This section describes the methodology and data sources used to conduct the impact analysis in Chapter 2.
The direct economic impacts presented in the report are based on public financial data for the CSU and/or from calculations based on assumptions discussed in the following sections. The direct economic impacts included annual CSU operational expenditures, four-year average capital expenditures, auxiliary expenditures, and student expenditures.
The total economic impacts, including total spending, total job, and total tax impacts, were calculated using the IMPLAN economic impact software package. Within a defined study region, IMPLAN uses average expenditure data from the industries that originate the impact on supplier industries to trace and calculate the multiple rounds of secondary indirect and induced impacts that remain in the region (as opposed to “leaking out” to other areas). IMPLAN then uses this total impact to calculate total job and tax impacts.
Despite an increase in the magnitude of the CSU’s impact, the total number of supported jobs that is reported is fewer than what was reported in the 2004 analysis due to national, economy-wide increases in worker productivity. The 2004 analysis used the IMPLAN model, version 2, which relied on the most recently available data from 2001. The model used the 2001 data and industry trade flows to create industry multipliers that were used to estimate the direct job impacts associated with direct spending. The current (2010) analysis uses version 3 of the IMPLAN model, which relies on 2008 data (also the most recently available). The difference in direct employment generated by the model can be explained by changes in the underlying data that is not related to CSU specifically, but to economy-wide, increased productivity. Worker productivity increased substantially over the past decade. According to the IMPLAN model, 2003 US output per worker for the higher education sector was $58,450. In 2008, the output per worker for this sector jumped to $75,500. This change in output per worker (worker productivity) means that for each dollar invested, more worker output is produced, but by fewer employees and thus equivalent levels of direct investment generates fewer jobs (but more labor income and industry activity).
In this study, IMPLAN runs were made using California as the study region, and separately for each of the eight sub-regions defined in the report. The current (version 3) of the IMPLAN model allows for the assessment of regional interaction, and therefore can account for impact that spending in one region has on surrounding regions. Because of this enhanced capability, ICF calculated the regional impact, calibrating the model to take into account only those dollars that would be spent locally, as well as the impact on other regions and the state as a whole. All of the CSU’s direct impacts were modeled as originating in the Higher Education industry (sector #392 in IMPLAN, NAICS # 6112-3).
This study used CSU financial statements provided by each campus and the Chancellor’s Office to estimate annual CSU expenditures systemwide as well as at the campus level. Because campus capital expenditures vary significantly from year-to-year, four years of financial statements were used to calculate an average annual capital expenditure for each campus.
Information regarding the impact of auxiliary organizations also came from internal CSU financial reports. Because the data were not broken down by the type of auxiliary enterprise; i.e., retail store, food service area, research institute, etc. The following assumptions were made regarding expenditures in each IMPLAN sector:
A significant portion of CSU student expenditures occur at auxiliary organizations (e.g., campus housing, bookstores, campus food services and parking) which are incorporated in the auxiliary organization spending as noted above.
A full accounting of student expenditures attributable to CSU operations required an estimate of off-campus student expenditures. First, it was assumed that since many students would be working in California and their region and making similar expenditures whether or not they were attending a CSU campus, the conservative assumption (i.e., an assumption that underestimates student spending impacts compared to many traditional impact calculations) was made to exclude these expenditures from the total student spending.
Only out-of-state students were counted in the statewide analysis, and only students who came from outside of the region where they attended a CSU campus were counted in the regional analysis.
In order to create these estimates, the following calculations were made:
Alumni impacts are treated differently than the other spending impacts in IMPLAN because they are not expenditures by the CSU but by CSU graduates. Thus, instead of treating the direct impact as originating from the Higher Education sector, these expenditures were assumed to originate from the Household Expenditure sector.
The method used to assess the direct impact of alumni consisted of the following steps:
Location |
Bachelors Degrees Granted |
Masters Degrees Granted |
Bachelors Graduates Remaining |
Masters Graduates Remaining |
Bachelors Graduates Lost |
Masters Graduates Lost |
Bakersfield |
27,394 |
7,220 |
22,587 |
5,943 |
4,807 |
1,277 |
Channel Islands |
2,873 |
139 |
2,768 |
136 |
105 |
3 |
Chico |
103,323 |
10,484 |
80,412 |
8,241 |
22,911 |
2,243 |
Dominguez Hills |
49,200 |
21,803 |
39,649 |
18,055 |
9,551 |
3,748 |
Fresno |
109,865 |
19,875 |
85,506 |
15,767 |
24,359 |
4,108 |
Fullerton |
155,122 |
32,493 |
124,071 |
25,903 |
31,051 |
6,590 |
Hayward |
76,894 |
25,033 |
60,347 |
20,538 |
16,547 |
4,495 |
Humboldt |
47,045 |
5,360 |
36,591 |
4,167 |
10,454 |
1,193 |
Long Beach |
179,333 |
38,438 |
139,765 |
30,448 |
39,568 |
7,990 |
Los Angeles |
100,610 |
34,227 |
76,627 |
26,278 |
23,983 |
7,949 |
CSU Maritime Academy |
1,369 |
0 |
1,265 |
0 |
104 |
0 |
Monterey Bay |
5,360 |
376 |
4,983 |
356 |
377 |
20 |
Northridge |
157,187 |
32,518 |
124,251 |
25,914 |
32,936 |
6,604 |
Pomona |
98,041 |
10,888 |
77,698 |
8,718 |
20,343 |
2,170 |
Sacramento |
142,416 |
30,674 |
112,335 |
24,307 |
30,081 |
6,367 |
San Bernardino |
55,262 |
16,664 |
46,018 |
14,045 |
9,244 |
2,619 |
San Diego |
198,174 |
50,790 |
154,793 |
40,520 |
43,381 |
10,270 |
San Francisco |
146,683 |
47,391 |
115,719 |
37,100 |
30,964 |
10,291 |
San José |
155,312 |
51,768 |
119,612 |
41,758 |
35,700 |
10,010 |
San Luis Obispo |
114,920 |
10,742 |
90,582 |
8,449 |
24,338 |
2,293 |
San Marcos |
17,420 |
1,816 |
15,850 |
1,672 |
1,570 |
144 |
Sonoma |
46,655 |
6,913 |
36,895 |
5,400 |
9,760 |
1,513 |
Stanislaus |
34,175 |
4,331 |
27,833 |
3,563 |
6,342 |
768 |
Entire CSU |
2,024,633 |
459,943 |
1,596,156 |
367,280 |
428,477 |
92,663 |
Age Cohort |
Educational Attainment |
|||
High School |
Some College, No Degree |
Bachelor's Degree |
Master's Degree |
|
25-34 |
$28,224 |
$31,956 |
$48,445 |
$55,635 |
35-44 |
$36,917 |
$42,558 |
$70,054 |
$84,491 |
45-54 |
$35,338 |
$41,742 |
$64,810 |
$72,603 |
55-64 |
$27,533 |
$32,218 |
$43,378 |
$45,805 |
1 Source: U.S. Census Bureau, Current Population Survey, Annual Social and Economic Supplements, Table P-28, Educational Attainment—Workers 18 Years Old and Over by Mean Earnings, Age, and Sex: 1991 to 2008
2 The weights for the weighted average earnings calculations were the number of male and female workers in each age cohort earning sex-specific mean earnings.