Research in Higher Education

, Volume 60, Issue 1, pp 111–133 | Cite as

Time to the Doctorate and Research Career: Some Evidence from Spain

  • Antonio Caparrós-RuizEmail author


Education and research are considered as the cornerstones of the economic growth and the job creation for the Lisbon Strategy proposed by the European Union. Therefore, understanding the transmission channels of the educational investments to the society is important to inform policymakers and students about the benefits and opportunities associated with the acquisition of human capital. In this context, PhD programs play a significant role to reach the European research goals. The current study contributes to shed empirical evidence about the determinants of the time to the doctorate in Spain and its influence on the probability of carrying out an innovate activity (for example, working as a researcher), in both cases the PhD program’s academic field is included as regressors. One of the main hypothesis to verify is whether a prolonged time to complete the doctoral studies is a negative signal about the individual’s capacity to develop research skills. If this is the case, longer time to doctorate would imply less probability of working as a researcher. The methodology applied consists in estimating a Cox model to analyse the determinants of the time to the doctorate, and a probit model to examine the probability of being a researcher considering time to the doctorate as an endogenous regressor. Data used in this study come from the 2009 Survey on Human Resources in Science and Technology, provided by the Spanish National Institute of Statistics (INE in 2009 survey on human resources in science and technology, INE, Madrid, 2010).


PhD program Research career Endogenous regressor 


  1. Altonji, J. G., Blom, E., & Meghir, C. (2012). Heterogeneity in human capital investments: high school curriculum, college major, and careers. Annual Review of Economics, 4(September), 185–223.Google Scholar
  2. Amemiya, T. (1978). The estimation of a simultaneous equation generalized probit model. Econometrica, 46(5), 1193–1205.Google Scholar
  3. Auriol, L., Misu, M., & Freeman, R. A. (2013). Careers of doctorate holders: Analysis of labour market and mobility indicators. OECD science, technology and industry working papers, 2013/04. Paris: OECD.Google Scholar
  4. Behrman, J., & Rosenzweig, M. (2002). Does increasing women’s schooling raise the schooling of the next generation? American Economic Review, 91(1), 323–334.Google Scholar
  5. Bormann, L., & Enders, J. (2004). Social origin and gender of doctoral degree holders. Scientometrics, 61(1), 19–41.Google Scholar
  6. Breslow, N. (1974). Covariance analysis of censured survival data. Biometrics, 30(1), 89–99.Google Scholar
  7. Brooks, R., & Everett, G. (2008). The impact of higher education on lifelong learning. International Journal of Lifelong Learning, 27(3), 239–254.Google Scholar
  8. Canal, J. F. (2013). Ingresos y satisfacción laboral de los trabajadores españoles con título de doctor. Revista Española de Investigaciones Sociológicas, 144(octubre), 49–72.Google Scholar
  9. Canal, J. F., & Rodríguez, C. (2013). Wage differences among PhDs by area of knowledge: are science areas better paid than humanities and social ones? The Spanish case. Journal of Education and Work, 26(2), 187–218.Google Scholar
  10. Canal, J. F., & Rodríguez, C. (2016). Doctoral training and labour market needs. Evidence in Spain. Research Evaluation, 25(1), 79–93.Google Scholar
  11. Canal, J. F., & Wall, A. (2014). Factors determining the career success of doctorate holders: evidence from the Spanish case. Studies in Higher Education, 39(10), 1750–1773.Google Scholar
  12. Caparrós, A. (2014). Geographical mobility and potential wage gain of immigrants within Spain. Regional Studies, 48(4), 680–690.Google Scholar
  13. Caparrós, A. (2016). The impact of education on intergenerational occupational mobility. Journal of Vocational Behavior, 92(February), 94–104.Google Scholar
  14. Commission, European. (2016). Horizon 2020—Work Programme 2016–2017–3. Marie Sklodowska-Curie Actions. Report No.: C(2016)1349. Brussels: European Commission.Google Scholar
  15. Cox, D. R. (1972). Regression models and life-tables. Journal of Royal Statistical Society, Series B, 34(2), 187–220.Google Scholar
  16. Cryer, P. (1998). Transferable skills, marketability and lifelong learning: The particular case of postgraduate research students. Studies in Higher Education, 23(2), 207–216.Google Scholar
  17. Ehrenberg, R., & Mavros, P. (1995). Do doctoral students’ financial support patterns affect their times to degree and completion probabilities? The Journal of Human Resources, 30(3), 581–609.Google Scholar
  18. European Commission. (2005). i2010—a European information society for growth and employment. COM (2005) 229 final. Brussels: European Commission.Google Scholar
  19. European Commission. (2011). Report of mapping exercise on doctoral training in Europe “Towards a common approach”. Brussels: European Commission.Google Scholar
  20. Evangelauf, J. (1989). Lengthening of time to earn a doctorate causes concern. Chronicle of Higher Education, 35, 13–14.Google Scholar
  21. Fox, M., & Stephan, P. (2001). Careers of young scientists: preferences, prospects and realities by gender and field. Social Studies of Science, 31(1), 109–122.Google Scholar
  22. García-Quevedo, J., Mas-Verdú, F., & Polo-Otero, J. (2012). Which firms want PhDs? An analysis of the determinants of the demand. Higher Education, 63(5), 607–620.Google Scholar
  23. Golde, C. M. (2005). The role of the department and discipline in doctoral student attrition: Lessons from four department. The Journal of Higher Education, 76(6), 669–700.Google Scholar
  24. Grambsch, P. M., & Therneau, T. M. (1994). Proportional hazards tests and diagnostics based on weighted residuals. Biometrika, 81, 515–526.Google Scholar
  25. Guan, W. (2003). From the help desk: Bootstrapped standard errors. The Stata Journal, 3(1), 71–80.Google Scholar
  26. INE (Instituto Nacional de Estadística). (2007). 2006 survey on human resources in science and technology. Madrid: INE.Google Scholar
  27. INE (Instituto Nacional de Estadística). (2010). 2009 survey on human resources in science and technology. Madrid: INE.Google Scholar
  28. King, M. F. (2008). PhD completion and attrition: analysis of baseline demographic data from the PhD completion project. Washington, DC: Council of Graduate Schools.Google Scholar
  29. Lassibille, G., & Navarro, L. (2011). How long does it take to earn a higher education degree in Spain? Research in Higher Education, 52(1), 63–80.Google Scholar
  30. Lawless, J. (1982). Statistical models and methods for lifetime data. New York: Wiley.Google Scholar
  31. Lee, L. (1992). Amemiya’s generalized least squares and tests of overidentification in simultaneous equations models with qualitative or limited dependent variables. Econometric Reviews, 11(3), 319–328.Google Scholar
  32. Lee, H., Miozzo, M., & Laredo, P. (2010). Career pattern and competence of PhDs in science and engineering in the knowledge economy: The case of graduates from a UK research-based university. Research Policy, 39, 869–881.Google Scholar
  33. McCormick, B. (1997). Regional unemployment and labour mobility in the UK. European Economic Review, 41(3–5), 581–589.Google Scholar
  34. Newey, W. (1987). Efficient estimation of limited dependent variable models with endogenous explanatory variables. Journal of Econometrics, 36(3), 231–250.Google Scholar
  35. OECD (Organization for Economic Co-operation and Development). (2013). Panorama de la Educación, Indicadores de la OCDE 2013. Informe español. Madrid: Ministerio de Educación, Cultura y Deporte.Google Scholar
  36. OECD (Organization for Economic Co-operation and Development). (2014). Panorama de la Educación, Indicadores de la OCDE 2014. Informe español. Madrid: Ministerio de Educación, Cultura y Deporte.Google Scholar
  37. OECD (Organization for Economic Co-operation and Development) (2016). Main science and technology indicators full database. Retrieved from
  38. OECD (Organization for Economic Co-operation and Development) (2018). Education at a glance: Educational attaintment and labour-force status. OECD Education Statistics (database).Google Scholar
  39. Robin, S., & Cahuzac, E. (2003). Knocking on academia’s doors: an inquiry into the early careers of doctors in life science. Labour, 17(1), 1–23.Google Scholar
  40. Seagram, B. C., Gould, J., & Pyke, W. (1998). An investigation of gender and other variables on time to completion of doctoral degrees. Research in Higher Education, 39(3), 319–335.Google Scholar
  41. Sheridan, P. M., & Pyke, S. W. (1994). Predictors of time to completion of graduate degrees. Canadian Journal of Higher Education, XXIV-2, 68–87.Google Scholar
  42. Siegfried, J. J., & Stock, W. A. (2001). So you want to earn a Ph.D. in Economics: How long do you think it will take? Journal of Human Resources, 36(2), 364–378.Google Scholar
  43. Spence, M. A. (1973). Job market signalling. Quarterly Journal of Economics, 87(3), 355–374.Google Scholar
  44. Thune, T. (2009). Doctoral students on the university-industry interface: A review of the literature. Higher Education, 58, 637–651.Google Scholar
  45. Tinto, V. (1975). Dropout from Higher Education: A theoretical synthesis of recent research. Review of Educational Research, 45(1), 89–125.Google Scholar
  46. Tuckman, H., Coyle, S., & Bae, Y. (1990). On time to the Doctorate: A study of the increased time to complete doctorates in Science and Engineering. Washington, DC: National Academy Press.Google Scholar
  47. UNESCO (United Nations Educational, Scientific and Cultural Organization). (2015). UNESCO science report: Towards 2030. Paris: UNESCO.Google Scholar
  48. Walker, I., & Zhu, Y. (2008). The college wage premium and the expansion of higher education in the UK. The Scandinavian Journal of Economics, 110(4), 695–709.Google Scholar
  49. Wao, H. O. (2010). Time to the doctorate: Multilevel discrete-time hazard analysis. Educational Assessment. Evaluation and Accountability, 22(3), 227–247.Google Scholar
  50. Wooldrige, J. (2002). Econometric analysis of cross section and panel data. Cambridge: MIT Press.Google Scholar
  51. World Bank. (2013). World development indicators 2013. Washington, DC: World Bank.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Facultad de Ciencias Económicas y Empresariales, Departamento de Estadística y EconometríaUniversity of MálagaMálagaSpain

Personalised recommendations