Choosing the Future: Economic Preferences for Higher Education Using Discrete Choice Experiment Method

Abstract

This study illustrates how respondents' stated choices (the discrete choice experiment method) combined with the random utility framework can be used to model preferences for higher education. The flexibility offered by stated preference data circumvents limitations of other approaches, and allows quantifying young people' preferences for selected attributes of higher education programs that are typically highly correlated in revealed preference data. The empirical study presented here is based on a survey of 20,000 Polish respondents aged 18-30, who stated their preferences for higher education programs in carefully prepared hypothetical choice situations. The attributes considered include tuition fee, expected salary after graduation, quality of institution, interest in the field of study, distance from home, and mode of study. Using random parameters and latent class mixed multinomial logit models, young peoples' preferences are formally described, and the financial trade-offs they are willing to make are identified (willingness to pay for specific attribute levels in terms of increased tuition fees or expected salary after graduation). Accounting for respondents' observed and unobserved preference heterogeneity addresses a few research questions related to, for example, distinct preferences of students with parents who never attained tertiary education, students from lower socioeconomic groups, or students of a particular gender. Overall, the usefulness of stated preference methods as a tool for exploring economic preferences is demonstrated, allowing for better understanding the determinants of choices, forecasting, and designing the services offered by higher education institutions in an optimal way.

An attribute-based framework for students' motivation to join an HEI: a self-determination theory perspective

“…Thus, the students need financial assistance for their studies in the form of scholarships, part-time job opportunities and support from financial institutes. These facilities are external motivators for students since the lower cost enhances the value-for-money perception (Aungamuthu and Vigar-Ellis, 2017; Cosentino et al , 2019; Czajkowski et al , 2019). The last factor, social influence in the form of appreciation from friends, colleagues, family and siblings serves as an external motivation (Ahmad and Buchanan, 2017).…”

“…Czajkowski et al (2019), Daniel and Johnstone (2017) and Perez-Encinas et al (2020) suggested that students’ selection of institutes/universities is a complex multidimensional process. Thus, the current work aims to (1) develop an integrative multidimensional attribute-based framework for students' motivation to join an HEI and (2) measure the effect of such motivations on the students’ engagement intention.…”

First-year Students’ University and Programme Selection at a South African University:

“…To make the calculation, a prospective student weighs the costs and benefits (Vrontis, Thrasai, and Melanthial, 2007). It is thus assumed that prospective students are capable of evaluating factors such as fees in making their choices (Czajkowski et al, 2019).…”

Estimating Social Preferences Using Stated Satisfaction: Novel Support for Inequity Aversion

“…Charness and Grosskopf (2001) point out that mainstream economic analyses have typically used self-reported data from unemployment and Census surveys. 6 Our approach, making use of an inequity list, contributes to the large body of research on stated preferences applied both specifically to distributive preferences (Kuziemko, Norton, Saez, & Stantcheva, 2015;Norton & Ariely, 2011), and more broadly to a set of topics as diverse as education (e.g., Czajkowski, Gajderowicz, Giergiczny, Grotkowska, & Sztandar-Sztanderska, 2020), environmental issues (e.g., Hanley et al, 2017, Alberini, 2019), health (e.g., de Bekker-Grob, Ryan, & Gerard, 2012, savings decisions (e.g., Ameriks, Briggs, Caplin, Shapiro, & Tonetti, 2020), and labor market decisions (Doiron & Yoo, 2020).…”