Skip to main content
Log in

FORECASTING CREDIT HOURS

  • Published:
Research in Higher Education Aims and scope Submit manuscript

Abstract

This paper employs Tobit to estimate retentionprobabilities and credit hours at two universities. Theinnovation is that this technique examines credit-hourchoice with the decision to depart the university treated as the choice of zero credit hours.Tobit is appropriate for this problem because itrecognizes the lower bound of zero on credit hours andincorporates this bound into the parameter estimates and forecasts. Models are estimated for credithours in a single year and cumulative hours over asix-year horizon.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

REFERENCES

  • Amemiya. Takeshi (1984). Tobit models: A survey. Journal of Econometrics24: 3±61.

    Google Scholar 

  • Bean, John P. (1980). Dropouts and turnover: The synthesis and test of a causal model of student attrition. Research in Higher Education12(2): 155±187.

    Google Scholar 

  • Bean, John P. (1983). The application of the turnover model in work organizations to the student attrition process. Review of Higher Education6(2): 129±148.

    Google Scholar 

  • Bean, John P. (1990). Why students leave: Insights from research. In Don Hossler and John P. Bean (eds.), The Strategic Management of College Enrollments(pp. 147±169). San Francisco: Jossey-Bass.

    Google Scholar 

  • Bean, John P., and Metzner, B. S. (1985). A conceptual model of nontraditional undergraduate student attrition. Review of Educational Research55(4): 485±540.

    Google Scholar 

  • Braxton, John M., Vesper, Nick, and Hossler, Don (1995). Expectations for college and student persistence. Research in Higher Education36(5): 595±612.

    Google Scholar 

  • Cabrera, Alberto F. (1994). Logistic regression analysis in higher education: An applied perspective. In John C. Smart (ed.), Higher Education: Handbook of Theory and Research, vol. 10 (pp. 225±256). New York: Agathon Press.

    Google Scholar 

  • Davidson, Russell, and MacKinnon, James G. (1993). Estimation and Inference in Econometrics. New York: Oxford University Press.

    Google Scholar 

  • Judge, George G., Griffiths, William E., Hill, R. Carter, and Lee, Tsoung-Chao (1980). The Theory and Practice of Econometrics. New York: John Wiley and Sons.

    Google Scholar 

  • Judge, George G., Hill, R. Carter, Griffiths, William E., Lütkepohl, Helmut, and Lee, Tsoung-Chao (1982). Introduction to the Theory and Practice of Econometrics. New York: John Wiley and Sons.

    Google Scholar 

  • Nora, Amaury, Cabrera, Alberto, Hagedorn, Linda Serra, and Pascarella, Ernest (1996). Differential impacts of academic and social experiences on college-related behavioral outcomes across different ethnic and gender groups at four-year institutions. Research in Higher Education37(4): 427±451.

    Google Scholar 

  • St. John, Edward P. (1990). Price response in persistence decisions: An analysis of the high school and beyond senior cohort. Research in Higher Education31(4): 387±403.

    Google Scholar 

  • St. John, Edward P., Kirshstein, Rita J., and Noell, Jay (1991). The effects of student financial aid on persistence: A sequential analysis. Review of Higher Education14(3): 383±406.

    Google Scholar 

  • Spady, W. (1970). Dropouts from higher education: An interdisciplinary review and synthesis. Interchange1:64±85.

    Google Scholar 

  • Tinto, Vincent (1975). Dropouts from higher education: A theoretical synthesis of recent research. Review of Educational Research45(1): 89±125.

    Google Scholar 

  • Tobin, James (1958). Estimation of relationships for limited dependent variables. Econometrica26(1): 24±36.

    Google Scholar 

Download references

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bivin, D., Rooney, P.M. FORECASTING CREDIT HOURS. Research in Higher Education 40, 613–632 (1999). https://doi.org/10.1023/A:1018704712802

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1018704712802

Keywords

Navigation