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Using econometric modeling to increase Net tuition revenue. June 14, 2012. Introduction…. Tim Schuldt Camden High School ‘04 St. Lawrence University ‘08 (Go Saints!) Statistical Analyst – Scannell & Kurz Fun fact…. A Couple Questions…. 2 year institutions? 4 year institutions?
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Using econometric modeling to increase Net tuition revenue June 14, 2012
Introduction… Tim Schuldt Camden High School ‘04 St. Lawrence University ‘08 (Go Saints!) Statistical Analyst – Scannell & Kurz Fun fact…
A Couple Questions… • 2 year institutions? 4 year institutions? • Central NY? Western NY? North country? • Challenges with NTR? • Challenges with retention?
New Year, Same Questions… • How do we get them to come? • How do we get them to stay? • What factors contribute to a student making those decisions? • How big of an impact does grant have on those decisions?
Same Questions, New Answers… • Unlike table analysis, econometric modeling controls for the influence of multiple variables, holding other variables constant. • Each individual student will be assigned an estimated probability of enrollment/retention that is a function of individual student characteristics.
Elasticity Tells You Which Side Of The Peak You Are On Elastic Inelastic
Exploring Price Sensitivity • Econometric modeling can help an institution assess the tradeoffs between institutional enrollment goals by: • Providing information on the price sensitivity of different subpopulations • Assessing the maximum NTR that can be generated with the current applicant pool • Simulating how much NTR would need to be forgone in order to achieve institutional goals for quality, diversity, program mix, etc.
Same Year, More Questions… • Now that they are here, what can we do to get them to stay? • How can we target at-risk students? • Does grant drive their decision to retain as much as it does to enroll? (the answer might surprise you…)
A Different Approach • Retention analysis takes a slightly different path. • Table analysis provides a solid base for modeling. • Models are built based on first term grade point average. • Two models are built to look at overall retention as well as at-risk students.