nep-edu New Economics Papers
on Education
Issue of 2010‒11‒13
eleven papers chosen by
Joao Carlos Correia Leitao
University of Beira Interior and Technical University of Lisbon

  1. The Choice Between Fixed and Random Effects Models: Some Considerations for Educational Research By Clarke, Paul; Crawford, Claire; Steele, Fiona; Vignoles, Anna
  2. Determinants of Demand for Education in Tanzania: Costs, Returns and Preferences By Nerman, Måns; Owens, Trudy
  3. Performance of the Different Methods of Study Financing: A Measurement through the Data Envelopment Analysis Method By Valérie Vierstraete; Eric Yergeau
  4. How Much Do Educational Outcomes Matter in OECD Countries? By Eric A. Hanushek; Ludger Woessmann
  5. An analysis of the educational progress of children with special educational needs By Claire Crawford; Anna Vignoles
  6. Human Capital, Labour Productivity and Employment By Savita Bhat; N S Siddharthan
  7. Maintaining (Locus of) Control? Assessing the Impact of Locus of Control on Education Decisions and Wages By Piatek, Rémi; Pinger, Pia
  8. University Competition, Grading Standards and Grade Inflation By Popov, Sergey V.; Bernhardt, Dan
  9. Spreading the Word: Geography, Policy and University Knowledge Diffusion By Sharon Belenzon; Mark Schankerman
  10. The Concept of “Educational Campus” and its Application in Spanish Universities By Pablo Campos Calvo-Sotelo
  11. Investing in Aboriginal Education in Canada: An Economic Persepctive By Andrew Sharpe; Jean-François Arsenault

  1. By: Clarke, Paul (University of Bristol); Crawford, Claire (Institute for Fiscal Studies, London); Steele, Fiona (University of Bristol); Vignoles, Anna (Institute of Education, University of London)
    Abstract: We discuss fixed and random effects models in the context of educational research and set out the assumptions behind the two approaches. To illustrate the issues, we analyse the determinants of pupil achievement in primary school, using data from the Avon Longitudinal Study of Parents and Children. We conclude that a fixed effects approach will be preferable in scenarios where the primary interest is in policy-relevant inference of the effects of individual characteristics, but the process through which pupils are selected into schools is poorly understood or the data are too limited to adjust for the effects of selection. In this context, the robustness of the fixed effects approach to the random effects assumption is attractive, and educational researchers should consider using it, even if only to assess the robustness of estimates obtained from random effects models. When the selection mechanism is fairly well understood and the researcher has access to rich data, the random effects model should be preferred because it can produce policy-relevant estimates while allowing a wider range of research questions to be addressed. Moreover, random effects estimators of regression coefficients and shrinkage estimators of school effects are more statistically efficient than those for fixed effects.
    Keywords: fixed effects, random effects, multilevel modelling, education, pupil achievement
    JEL: C52 I21
    Date: 2010–10
  2. By: Nerman, Måns (Department of Economics, School of Business, Economics and Law, Göteborg University); Owens, Trudy (University of Nottingham)
    Abstract: This paper uses household data to test whether the determinants of demand for education have changed during the Tanzanian government’s push for Universal Primary Education (UPE) in the 2000s. Drawing on the existing theoretical and empirical literature, we test three main hypotheses. First, we test whether demand for education is driven by the direct and opportunity costs of education. We find that the abolition of school fees has led to an increase in enrolment within agricultural households. However, wealth is still a significant determinant of demand, indicating that structural differences in educational attainment have remained largely intact over the period. In line with other studies, we find opportunity costs of sending children to school to be important, yet their impact is modest. Second, the paper estimates returns to education which is then used as an explanatory factor in the demand for education estimations. The paper finds strong indications that returns do not determine demand. Third, we test the importance of preferences in determining demand and find that educational choices are affected by the views held by others within the community, which is supportive of the importance of social norms in determining educational choices. However, after the introduction of UPE, the size of this impact halves, suggesting that the push has reduced the influence of previous social norms on the demand for education.<p>
    Keywords: Education; household behaviour; Tanzania
    JEL: I21 O15
    Date: 2010–11–02
  3. By: Valérie Vierstraete (GREDI, Department of Economics, Université de Sherbrooke); Eric Yergeau (Department of Vocational Guidance, Université de Sherbrooke)
    Abstract: Financial hardship can significantly undermine post-secondary students’ ability to attain their academic goals: completing their training and obtaining degrees with good grades. This study considers which method of financing studies—loans and bursaries from the Government, student aid granted directly by universities, scholarships or on-campus jobs, off-campus jobs or parental financial contribution—will best help students attain academic success. For these purposes, we use a non-parametric data envelopment method, the Data Envelopment Analysis (DEA) which will enable us to determine a theoretically efficient production frontier against which the efficiency of students will be measured. Depending on the financing methods used, the conclusions of this study show efficiency differences.
    Keywords: Data Envelopment Analysis, efficiency, student aid, university
    JEL: I23 I28
    Date: 2010–10–12
  4. By: Eric A. Hanushek; Ludger Woessmann
    Abstract: Existing growth research provides little explanation for the very large differences in long-run growth performance across OECD countries. We show that cognitive skills can account for growth differences within the OECD, whereas a range of economic institutions and quantitative measures of tertiary education cannot. Under the growth model estimates and plausible projection parameters, school improvements falling within currently observed performance levels yield very large gains. The present value of OECD aggregate gains through 2090 could be as much as $275 trillion, or 13.8 percent of the discounted value of future GDP. Extensive sensitivity analyses indicate that, while differences between model frameworks and alternative parameter choices make a difference, the economic impact of improved educational outcomes remains enormous. Interestingly, the quantitative difference between an endogenous and neoclassical model framework – with improved skills affecting the long-run growth rate versus just the steady-state income level – matters less than academic discussions suggest. We close by discussing evidence on which education policy reforms may be able to bring about the simulated improvements in educational outcomes.
    JEL: H0 I2 J24 J48 O4
    Date: 2010–11
  5. By: Claire Crawford (Institute for Fiscal Studies, 7 Ridgmount Street, London, WC1E 7AE; Institute of Education, University of London, 20 Bedford Way, London WC1H 0AL, UK.); Anna Vignoles (Department of Quantitative Social Science, Institute of Education, University of London. 20 Bedford Way, London WC1H 0AL, UK.)
    Abstract: One in five children in England are recorded as having some kind of special educational need, meaning that they receive additional help in school; yet there is very little evidence of the effect of such assistance on pupil’s academic progress. This is at least partly because it is usually very difficult to define an appropriate control group for pupils with special educational needs. To overcome this issue, we make use of extremely rich data from the Avon Longitudinal Study of Parents and Children to assess the academic progress of pupils between Key Stages 1 and 2 (ages 7 and 11). Specifically, we compare the progress of children who have been formally identified by the SEN system as having non-statemented (less severe) needs with the progress of children who do not have SEN label, but whose class teacher reports that they exhibit behaviour which suggests that they might have special educational needs. Our results suggest that, despite our very similar control group, pupils with a SEN label still score about 0.3 standard deviations lower at Key Stage 2 than otherwise identical pupils without a SEN label. This is perhaps not an entirely unexpected result, given that there is no compulsion in the system for non-statemented SEN funding to be spent on children with special educational needs and in any case additional resources may not close the gap completely. Nonetheless, such a result clearly has significant policy implications: schools are provided with resources to help children with special educational needs and if these resources are not improving academic outcomes for these children, then this should be of concern to both parents and policymakers alike.
    Keywords: special educational needs, educational attainment, propensity score matching
    JEL: I2 H52
    Date: 2010–11–03
  6. By: Savita Bhat; N S Siddharthan
    Abstract: This paper analyses the importance of human capital in determining the inter-state differences in labour productivity and its growth in India. The paper also examines the impact of human capital differences on the growth of employment for a cross section of Indian states for the period 2003- 2007. It argues that the current technology is human capital and knowledge intensive and cannot be used in the absence of skill development. Due to the presence of skill bias in the new technology, persons with less education would become victims. The panel model results of Generalised Least Squares using cross section weights show that after controlling for other determinants, variables representing human capital emerge significant determinants of productivity. Furthermore, higher enrolments in high schools not only contribute to higher labour productivity but also to higher growth in productivity. In addition, states that have higher high school enrolment rates have been enjoying higher growth rates of employment. On the whole the results presented show strong skill bias in productivity and employment growths across states.
    Keywords: human capital, skill development, technology, education, high school enrollments, productivity, Economics, Labour Economics
    Date: 2010
  7. By: Piatek, Rémi (University of Konstanz); Pinger, Pia (University of Mannheim)
    Abstract: This paper demonstrates that locus of control, i.e. whether individuals believe that reinforcement in life comes from their own actions instead of being determined by luck or destiny, is an important predictor of the decision to obtain higher education. Furthermore, the authors find that premarket locus of control, defined as locus of control measured at the time of schooling – before the individual enters the labor market – does not significantly affect later wages after controlling for education decisions. In light of the existing literature, which finds mostly positive effects of contemporaneous locus of control measures on wages, this indicates that it is important to distinguish between premarket skills and those that are already influenced by labor market experience and age. Last, simulation of the model shows that moving individuals from the first to the last decile of the locus of control distribution significantly shifts the distribution of schooling choices, thus indirectly affecting later wages. The paper conveys important policy implications. If some personality traits, such as locus of control, influence the cost of education but not outcomes directly, these individual characteristics may keep individuals from studying who, once they reach the labor market, are no less successful than other individuals. If these individuals are at high risk of dropping out of school, early personality tests and targeted mentoring of students with an external locus of control are a means to countervail skill shortages in society.
    Keywords: data set combination, locus of control, wages, latent factor model
    JEL: C31 J24 J31
    Date: 2010–10
  8. By: Popov, Sergey V.; Bernhardt, Dan
    Abstract: We develop a model of strategic grade determination by universities distinguished by their distributions of student academic abilities. Universities choose grading standards to maximize total wages of graduates. Job placement and wages hinge on a firm’s productivity assessment given a student’s university, grade and productivity signal. We identify conditions under which better universities set lower grading standards, exploiting the fact that firms cannot distinguish between “good” and “bad” “A”s. In contrast, a social planner sets stricter standards at better universities. We show how increases in skilled jobs drive grade inflation, and determine when grading standards fall faster at better schools.
    Keywords: grading standards; grading inflation; information
    JEL: I21
    Date: 2010–11–04
  9. By: Sharon Belenzon; Mark Schankerman
    Abstract: Using new data on citations to university patents and scientific publications, and measures ofdistance based on Google maps, we study how geography affects university knowledgediffusion. We show that knowledge flows from patents are localized in two respects: theydecline sharply with distance up to about 100 miles, and they are strongly constrained bystate borders, controlling for distance. While distance also constrains knowledge spilloversfrom publications, the state border does not. We investigate how the strength of the stateborder effect varies with university and state characteristics. It is larger for patents frompublic, as compared to private, universities and this is partly explained by the localdevelopment policies of universities. The border effect is larger in states with stronger noncompetelaws that affect intra-state labor mobility, and those with greater reliance on in-stateeducated scientists and engineers. We confirm the impact of non-compete statutes bystudying a policy reform in Michigan that introduced such restrictions.
    Keywords: knowledge spillovers, diffusion, geography, university technology transfer,patents, scientific publications
    JEL: K41 L24 O31 O34
    Date: 2010–09
  10. By: Pablo Campos Calvo-Sotelo
    Abstract: A university campus should reflect a commitment to quality and be dedicated to the intellectual, psychological and social development of its students. The “Educational Campus” is an innovative concept which espouses this concept and is designed to stimulate a process of modernisation in universities and contribute to their excellence.
    Date: 2010–07
  11. By: Andrew Sharpe; Jean-François Arsenault
    Abstract: The objective of this paper is to summarize the research done by the Centre for the Study of Living Standards (CSLS) on the economic impacts of improving levels of Aboriginal education. Improving the social and economic well-being of the Aboriginal population is not only a moral imperative; it is a sound investment that will pay substantial dividends in the coming decades. In particular, Canada’s Aboriginal population could play a key role in mitigating the looming long-term labour shortage caused by Canada’s aging population and low birth rate. We estimate that complete closure of both the education and the labour market outcomes gaps by 2026 would lead to cumulative benefits of $400.5 billion (2006 dollars) in additional output and $115 billion in avoided government expenditures over the 2001-2026 period.
    Keywords: Aboriginal, Education, Canada, Forecast of economic growth, Equity and efficiency, well-being, labour market, unemployment
    JEL: J10 J11 I29 I28 E27 O11 O15 O47
    Date: 2010–02

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