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# Appendix 1: Sensitivity Analysis

Sensitivity analysis measures the extent to which a model’s outputs are affected by hypothetical changes in the background data and assumptions. This is especially important when those variables are inherently uncertain. This analysis allows us to identify a plausible range of potential results that would occur if the value of any of the variables is in fact different from what was expected. In this chapter we test the sensitivity of the model to the following input factors: 1) the labor import effect variable and 2) the retained student variable.

### Labor import effect variable

The labor import effect variable only affects the alumni impact calculation in Table 2.10. In the model we assume a labor import effect variable of 50%, which means that 50% of the region’s labor demands would have been satisfied with- out the presence of UHV. In other words, businesses that hired UHV students could have substituted some of these workers with equally-qualified people from outside the region had there been no UHV students to hire. Therefore, we attribute only the remaining 50% of the initial labor income generated by increased alumni productivity to the university.

Table A1.1 presents the results of the sensitivity analysis for the labor import effect variable. As explained earlier, the assumption increases and decreases relative to the base case of 50% by the increments indicated in the table. Alumni productivity impacts attributable to UHV, for example, in FY 2018-19 range from a high of \$371.2 million at a -50% variation to a low of \$123.7 million at a +50% variation from the base case assumption. This means that if the labor import effect variable increases, the impact that we claim as attributable to alumni decreases. Even under the most conservative assumptions, the alumni impact on the Coastal Bend economy still remains sizeable.

TABLE A1.1: SENSITIVITY ANALYSIS OF LABOR IMPORT EFFECT VARIABLE

TABLE A1.1: SENSITIVITY ANALYSIS OF LABOR IMPORT EFFECT VARIABLE
% variation in assumption-50%-25%-10%Base Case10%25%50%
Labor import effect variable 25% 38% 45% 50% 55% 63% 75%
Alumni impact (millions), FY 2018-19 \$371 \$309 \$272 \$247 \$223 \$186 \$124
Alumni impact (millions), FY 2028-29 \$582 \$485 \$427 \$388 \$349 \$291 \$194

### Retained student variable

The retained student variable only affects the student spending impact calculation in Table 2.8. For this analysis, we assume a retained student variable of 10%, which means that 10% of UHV’s students who originated from the Coastal Bend would have left the region for other opportunities, whether that be education or employment, if UHV did not exist. The money these retained students spent in the region for accommodation and other personal and household expenses is attributable to UHV.

Table A1.2 presents the results of the sensitivity analysis for the retained student variable. The assumption increases and decreases relative to the base case of 10% by the increments indicated in the table. The student spending impact is recalculated at each value of the assumption, holding all else constant. Student spending impacts attributable to UHV in FY 2018-19 range from a high of \$11.8 million when the retained student variable is 15% to a low of \$7 million when the retained student variable is 5%. This means as the retained student variable decreases, the student spending attributable to UHV decreases. Even under the most conservative assumptions, the student spending impact on the Coastal Bend economy remains substantial.

TABLE A1.2: SENSITIVITY ANALYSIS OF RETAINED STUDENT VARIABLE

ABLE A1.2: SENSITIVITY ANALYSIS OF RETAINED STUDENT VARIABLE
% variation in assumption-50%-25%-10%Base Case10%25%50%
Retained student variable 5% 8% 9% 10% 11% 13% 15%
Student spending impact (thousands), FY 2018-19 \$6,959 \$8,157 \$8,876 \$9,355 \$9,834 \$10,553 \$11,752
Student spending impact (thousands), FY 2028-29 \$13,002 \$15,292 \$16,666 \$17,582 \$18,498 \$19,872 \$22,162