University of Houston-Victoria

President

University spending impact

UHV professor teaching

The university spending impact consists of three sub-impacts stemming from the different types of UHV spending: 1) operations spending impact, 2) research spending impact, and 3) construction spending impact. The university spending impact is the sum of these three-sub impacts presented in the following section.

Operations spending impact

Faculty and staff payroll is part of the region’s total earnings, and the spending of employees for groceries, apparel and other household expenditures helps support regional businesses. The university itself purchases supplies and services, and many of its vendors are located in the Coastal Bend. These expenditures create a ripple effect that generates still more jobs and higher wages throughout the economy.

Table 2.1 presents FY 2018-19 university expenditures (not including research and construction) for the following three categories: 1) salaries, wages, and benefits, 2) operation and maintenance of plant, and 3) all other expenditures (including purchases for supplies and services). In this analysis, we exclude expenses for depreciation and interest due to the way those measures are calculated in the national input-output accounts, and because depreciation represents the devaluing of the university’s assets rather than an outflow of expenditures. 10

10 This aligns with the economic impact guidelines set by the Association of Public and Land-Grant Universities. Ultimately, excluding these measures results in more conservative and defensible estimates.

The first step in estimating the multiplier effects of the university’s operational expenditures is to map these categories of expenditures to the approximately 1,000 industries of the Emsi MR-SAM model. Assuming that the spending patterns of university personnel approximately match those of the average consumer, we map salaries, wages, and benefits to spending on industry outputs using national household expenditure coefficients provided by Emsi’s national SAM. Approximately 99% of UHV employees work in the Coastal Bend (see Table 1.1), and therefore we consider 99% of the salaries, wages, and benefits. For the other two expenditure categories (i.e., operation and maintenance of plant and all other expenditures), we assume the university’s spending patterns approximately match national averages and apply the national spending coefficients for NAICS 902612 (Colleges, Universities, and Professional Schools (State Government)).11

11 See Appendix 2 for a definition of NAICS.

Operation and maintenance of plant expenditures are mapped to the industries that relate to capital construction, maintenance, and support, while the university’s remaining expenditures are mapped to the remaining industries.                                                                                                  

TABLE 2.1: UHV EXPENSES BY FUNCTION (EXCLUDING DEPRECIATION & INTEREST), FY 2018-19
Expense category  In-region expenditures (thousands)  Out-of-region expenditures (thousands)  Total expenditures (thousands)  
Employee salaries, wages, and benefits   $34,012   $344   $34,355  
Operation and maintenance of plant   $2,105   $166   $2,270  
All other expenditures   $10,625   $11,353   $21,978  
Total   $46,741   $11,863   $58,604  

* This table does not include expenditures for research or construction activities, as they are presented separately in the following sections. Source: Data provided by UHV and the Emsi impact model.

We now have three vectors of expenditures for UHV: one for salaries, wages, and benefits; another for operation and maintenance of plant; and a third for the university’s purchases of supplies and services. The next step is to estimate the portion of these expenditures that occur inside the region. The expenditures occurring outside the region are known as leakages. We estimate in-region expenditures using regional purchase coefficients (RPCs), a measure of the overall demand for the commodities produced by each sector that is satisfied by regional suppliers, for each of the approximately 1,000 industries in the MR-SAM model.12 For example, if 40% of the demand for NAICS 541211 (Offices of Certified Public Accountants) is satisfied by regional suppliers, the RPC for that industry is 40%. The remaining 60% of the demand for NAICS 541211 is provided by suppliers located outside the region. The three vectors of expenditures are multiplied, industry by industry, by the corresponding RPC to arrive at the in-region expenditures associated with the university. See Table 2.1 for a break-out of the expenditures that occur in-region. Finally, in-region spending is entered, industry by industry, into the MR-SAM model’s multiplier matrix, which in turn provides an estimate of the associated multiplier effects on regional labor income, non-labor income, total income, sales, and jobs.

12 See Appendix 5 for a description of Emsi’s MR-SAM model.

Table 2.2 presents the economic impact of university operations spending in FY 2018-19. The people employed by UHV and their salaries, wages, and benefits comprise the initial effect, shown in the top row of the table in terms of labor income, non-labor income, total added income, sales, and jobs. The additional impacts created by the initial effect appear in the next four rows under the section labeled multiplier effect. Summing the initial and multiplier effects, the gross impacts are $52 million in labor income and $12.6 million in non-labor income. This sums to a total impact of $64.6 million in total added income associated with the spending of the university and its employees in the region. This is equivalent to supporting 817 jobs.                                                                                                                          

TABLE 2.2: OPERATIONS SPENDING IMPACT, FY 2018-19
 Labor income (thousands)  Non-labor income (thousands)  Total income  (thousands)  Sales (thousands)  Jobs supported  
Initial effect   $34,012   $0   $34,012   $58,260   504  
Multiplier effect            
Direct effect   $4,299   $2,577   $6,876   $12,729   55  
Indirect effect   $1,575   $666   $2,242   $4,390   20  
Induced effect   $12,112   $9,363   $21,475   $35,873   239  
Total multiplier effect   $17,986   $12,607   $30,593   $52,992   314  
Gross impact (initial + multiplier)   $51,998   $12,607   $64,605   $111,252   817  
Less alternative uses of funds   -$11,074   -$9,077   -$20,150   -$33,337   -240  
Net impact   $40,924   $3,530   $44,454   $77,915   577  

The $64.6 million in gross impact is often reported by researchers as the total impact. We go a step further to arrive at a net impact by applying a counterfactual scenario, i.e., what would have happened if a given event—in this case, the expenditure of in-region funds on UHV—had not occurred. UHV received an estimated 46% of its funding from sources within the Coastal Bend. These monies came from the tuition and fees paid by resident students, from the auxiliary revenue and donations from private sources located within the region, from state taxes, and from the financial aid issued to students by state government. We must account for the opportunity cost of this in-region funding. Had other industries received these monies rather than UHV, income impacts would have still been created in the economy. In economic analysis, impacts that occur under counterfactual conditions are used to offset the impacts that actually occur in order to derive the true impact of the event under analysis.

We estimate this counterfactual by simulating a scenario where in-region monies spent on the university are instead spent on consumer goods and savings. This simulates the in-region monies being returned to the taxpayers and being spent by the household sector. Our approach is to establish the total amount spent by in-region students and taxpayers on UHV, map this to the detailed industries of the MR-SAM model using national household expenditure coefficients, use the industry RPCs to estimate in-region spending, and run the in-region spending through the MR-SAM model’s multiplier matrix to derive multiplier effects. The results of this exercise are shown as negative values in the row labeled less alternative uses of funds in Table 2.2.

The total net impact of the university’s operations in FY 2018-19 is equal to the gross impact less the impact of the alternative use of funds—the opportunity cost of the regional money. As shown in the last row of Table 2.2, the total net impact is approximately $40.9 million in labor income and $3.5 million in non-labor income. This sums together to $44.5 million in total added income and is equivalent to supporting 577 jobs. These impacts represent new economic activity created in the regional economy in FY 2018-19 that are solely attributable to the operations of UHV.

The total net impact of the university's operations will increase from $44.5 million in FY 2018-19 to $66.2 million in FY 2028-29.

Table 2.3 presents the projected economic impact of university operations spending in FY 2028-29, the fiscal year when UHV expects to reach 6,000 FTEs. The total gross impact sums to $94.3 million in total added income associated with the spending of the university and its employees in the region. This is equivalent to supporting 1,169 jobs. The total net impact of the university’s operations is equal to the gross impact less the impact of the alternative use of funds, thus the total net impact is approximately $60.3 million in labor income and $5.9 million in non-labor income. This sums together to $66.2 million in total added income and is equivalent to supporting 833 jobs.

By serving 6,000 student FTEs, UHV is increasing its operations spending impact by almost 50%, with $44.4 million in added income in FY 2018-19 projected to grow to $66.2 million in added income in FY 2028-29. The jobs supported will increase from 577 jobs to 833 jobs.

                    

TABLE 2.3: OPERATIONS SPENDING IMPACT, FY 2028-29
 Labor income (thousands)Non-labor income (thousands)Total income (thousands)Sales (thousands)Jobs supported
Initial effect   $48,397   $0   $48,397   $86,279   697    
Multiplier effect              
Direct effect   $7,033   $3,996   $11,029   $20,458   91    
Indirect effect   $2,576   $1,046   $3,622   $7,085   33    
Induced effect   $17,757   $13,508   $31,265   $52,342   348    
Total multiplier effect   $27,366   $18,550   $45,916   $79,884   472    
Gross impact (initial + multiplier)   $75,762   $18,550   $94,313   $166,163   1,169    
Less alternative uses of funds   -$15,487   -$12,670   -$28,157   -$46,593   -336    
Net impact   $60,276   $5,880   $66,156   $119,570   833    

Research spending impact

Similar to the day-to-day operations of UHV, research activities impact the economy by employing people and requiring the purchase of equipment and other supplies and services. Figure 2.1 shows UHV’s research expenses by function—payroll, equipment, pass-throughs, and other—for the last four fiscal years. In FY 2018-19, UHV spent over $42.5 thousand on research and development activities. These expenses would not have been possible without funding from outside the region—UHV received around 52% of its research funding from federal sources and other sources.

We employ a methodology similar to the one used to estimate the impacts of operational expenses. We begin by mapping total research expenses to the industries of the MR-SAM model, removing the spending that occurs outside the region, and then running the in-region expenses through the multiplier matrix. As with the operations spending impact, we also adjust the gross impacts to account for the opportunity cost of monies withdrawn from the regional economy to support the research of UHV, whether through state-sponsored research awards or through private donations. Again, we refer to this adjustment as the alternative use of funds.

FIGURE 2.1: RESEARCH EXPENSES BY FUNCTION (THOUSANDS)

Mapping the research expenses by category to the industries of the MR-SAM model—the only difference from our previous methodology—requires some exposition. We asked UHV to provide information on expenditures by research and development field as they report to the National Science Foundation’s Higher Education Research and Development Survey (HERD).13 We map these fields of study to their respective industries in the MR-SAM model. The result is a distribution of research expenses to the various 1,000 industries that follows a weighted average of the fields of study reported by UHV.

13 The fields include environmental sciences and life sciences, as reported by UHV.

Initial, direct, indirect, and induced effects of UHV’s FY 2018-19 research expenses appear in Table 2.4. The university’s research expenses have a total gross impact of $10.8 thousand in labor income and $4.5 thousand in non-labor income. This sums together to $15.4 thousand in added income, equivalent to less than one job. Taking into account the impact of the alternative uses of funds, net research expenditure impacts of UHV are $7.5 thousand in labor income and $1.8 thousand in non-labor income. This sums together to $9.3 thousand in total added income and is equivalent to supporting less than one job.

TABLE 2.4: RESEARCH SPENDING IMPACT, FY 2018-19            

TABLE 2.4: RESEARCH SPENDING IMPACT, FY 2018-19
 Labor income (thousands)Non-labor income (thousands)Total income

(thousands)

Sales (thousands)
Initial effect   $7   $0   $7   $9   <1  
Multiplier effect            
Direct effect   $1   $0   $1   $1   <1  
Indirect effect   $1   $0   $1   $1   <1  
Induced effect   $3   $4   $7   $11   <1  
Total multiplier effect   $4   $5   $9   $14   0  
Gross impact (initial + multiplier)   $11   $5   $15   $22   <1  
Less alternative uses of funds   -$3   -$3   -$6   -$10   <1  
Net impact   $8   $2   $9   $13   <1  

In FY 2028-29, UHV expects its research spending will grow at the same rate as its operations spending. Thus, the impact from research spending will increase 48% from $9.3 thousand in added income in FY 2018-19 to $13.8 thousand in added income in FY 2028-29 (Table 2.5).                                                                    

TABLE 2.5: RESEARCH SPENDING IMPACT, FY 2028-29
 Labor income (thousands)Non-labor income (thousands)Total income(thousands)Sales (thousands)
Initial effect   $10   $0   $10   $13   <0  
Multiplier effect            
Direct effect   $1   $0   $1   $2   <1  
Indirect effect   $1   $0   $1   $2   <1  
Induced effect   $4   $6   $10   $16   <1  
Total multiplier effect   $6   $7   $13   $21   <1
Gross impact (initial + multiplier)   $16   $7   $23   $33   <1  
Less alternative uses of funds   -$5   -$4   -$9   -$15   <1  
Net impact   $11   $3   $14   $19   <1  

UHV’s research activities create an economic impact beyond spending. There are impacts created through the entrepreneurial and innovative activities stemming from UHV’s research. Research activities through UHV’s interdisciplinary and interdepartmental approach may, for example, lead to increased access to mental healthcare and have immense value in the regional economy. However, the full magnitude of this value is difficult to quantify. Some of this value may be captured in the alumni impacts, presented later in this chapter. The broader spillover effects, however, remain as additional value created beyond the scope of this analysis.

Construction spending impact

University Commons libraryIn this section, we estimate the economic impact of the construction spending of UHV. Because construction funding is separate from operations funding in the budgeting process, it is not captured in the operations spending impact estimated earlier. However, like operations spending, the construction spending creates subsequent rounds of spending and multiplier effects that generate still more jobs and income throughout the region. During FY 2018-19, UHV spent a total of $29.1 million on various construction projects.

Assuming UHV construction spending approximately matches national construction spending patterns of NAICS 902612 (Colleges, Universities, and Professional Schools (State Government)), we map UHV construction spending to the construction industries of the MR-SAM model. Next, we use the RPCs to estimate the portion of this spending that occurs in-region. Finally, the in-region spending is run through the multiplier matrix to estimate the direct, indirect, and induced effects. Because construction is so labor intensive, the non-labor income impact is relatively small.

To account for the opportunity cost of any in-region construction money, we estimate the impacts of a similar alternative uses of funds as found in the operations and research spending impacts. This is done by simulating a scenario where in-region monies spent on construction are instead spent on consumer goods. These impacts are then subtracted from the gross construction spending impacts. Again, since construction is so labor intensive, most of the added income stems from labor income as opposed to non-labor income.

During FY 2018-19, UHV spent a total of $29.1 million on various construction projects.

Table 2.6 presents the impacts of UHV construction spending during FY 2018-19. Note the initial effect is purely a sales effect, so there is no initial change in labor or non-labor income. The FY 2018-19 UHV construction spending creates a net total short-run impact of $19.1 million in added income—the equivalent of supporting 264 jobs in the Coastal Bend. For the purpose of this analysis, we assumed that construction spending did not change between FY 2018-19 and FY 2028-29. Thus, the impact from construction spending remains unchanged.                

TABLE 2.6: CONSTRUCTION SPENDING IMPACT, FY 2018-19
 Labor income (thousands)  Non-labor income (thousands)  Total income  (thousands)  Sales (thousands)  Jobs supported  
Initial effect  $0   $0   $0 $29,114   0
Multiplier effect            
Direct effect   $11,614   $2,508   $14,122   $27,300   187  
Indirect effect   $4,295   $928   $5,223   $10,096   69  
Induced effect   $6,390   $1,380   $7,769   $15,019   103  
Total multiplier effect   $22,299   $4,815   $27,115   $52,415   359  
Gross impact (initial + multiplier)   $22,299   $4,815   $27,115   $81,529   359  
Less alternative uses of funds   -$4,382   -$3,590   -$7,972   -$13,195   -95  
Net impact   $17,918   $1,225   $19,143   $68,335   264  

 

University Commons aerial view