PISA: What makes the difference?

The large difference in the level and variance of student performance in the 2000 PISA study between Finland and Germany motivates this paper. It analyses why Finnish students showed a significantly higher performance by estimating educational production functions for both countries, using a unique micro-level dataset with imputed data and added school type information. The difference in reading proficiency scores is assigned to different effects, using Oaxaca–Blinder and Juhn–Murphy–Pierce decomposition methods. The analysis shows that German students and schools have on average more favorable characteristics except for the lowest deciles, but experience much lower returns to these characteristics in terms of test scores than Finnish students. The role of school types remains ambiguous. Overall, the observable characteristics explain more of the variation in test scores in Germany than in Finland.      

The Use of Course Evaluation Scores to Influence Teaching and Research Activities

The issue of course and teacher evaluations is one which continues to engender great interest. In this article, Paul Kipps comments on the Hansen-Kelley model as presented in the Fall 1973 issue of this journal, and then presents his own modifications and extensions of the model. These modifications deal mainly with the shape of the indifference curves and the slope of the output possibilities curve. The Kipps analysis casts doubts on the effectiveness of efforts to make significant improvements in the teaching output of research-oriented professors, and in the research work of teaching-oriented faculty members through voluntary incentive systems.     

Does grade retention affect students’ achievement? Some evidence from Spain

Grade retention practices are at the forefront of the educational debate. In this article, we measure the effect of grade retention on Spanish students’ achievement by using data from Programme for International Student Assessment (PISA). We find that grade retention has a negative impact on educational outcomes, but we confirm the importance of endogenous selection which makes observed differences between repeaters and nonrepeaters appear about 14% lower than they actually are. The effect on scores of repeating is much smaller (–10% of nonrepeaters’ average) than the counterfactual reduction that nonrepeaters would suffer had they been retained as repeaters (–24% of their average). Furthermore, those who repeated a grade during primary education suffered more than those who repeated a grade in secondary school, although the effect of repeating at both times is, as expected, larger.     

A Meta-analysis of the Gender Gap in Performance in Collegiate Economics Courses

The conventional wisdom has been that men outperform otherwise equivalent women in collegiate economics courses. Recent work in science, technology, engineering, and mathematics (STEM) fields documenting gains by women suggests that it is time to reevaluate the gender performance gap in economics. Surveying 68 studies containing 235 distinct regressions published since 1980, we find that 68.4% of regressions report men outperform women, though this is only statistically significant in 30.7% of regressions. Although the literature points to numerous reasons for this gap, our focus is on the effects of study design and the impact of broad socio-cultural changes over time. Using meta-regression analysis, we find that the likelihood of observing a statistically significant gap has declined noticeably, by almost 3% annually. Although the drop may not be as large as in some STEM fields, the result is highly robust to the specification of the time trend and the model.     

Private or public school advantage? Evidence from 40 countries using PISA 2012-Mathematics

It is known that in most countries, private school students outperform students in public schools in international assessments. However, the empirical literature recognizes that assessing the true effect of private school attendance requires addressing selection and sorting issues on both observabland unobservables. The existing empirical evidence on the private school effect mostly covers OECD and Latin American countries, with little evidence on other parts of the world. There is recent emerging country-specific evidence doubting the existence of a private school advantage. I use PISA 2012 data for Mathematics and two different methodologies to derive baseline and bias-corrected estimates of the private-dependent and independent school effect for 40 countries. A robust private school advantage is found only in a handful of countries. Public schools generally perform as well as private subsidized schools and outperform independent schools. Accounting for both peer effects and selection is necessary when evaluating school effectiveness, especially in the case of independent schools.     

School composition effects in Denmark: quantile regression evidence from PISA 2000

Data from the first wave of the OECD PISA study are combined with register data for Denmark to estimate the effect of the socioeconomic mix of schools on students’ test scores. A major disadvantage of the PISA design for the analysis of school composition effects is the small students-per-school samples. Adding family background data from administrative registers for all same-aged schoolmates of the PISA students helps overcome this. To compensate for endogeneity in the school composition variable, the results are conditioned on a rich set of family and school variables from the PISA data. Quantile regression results suggest differential school composition effects across the conditional reading score distribution, with students in the lower quantiles achieving the largest test score gains. Mathematics results suggest that high- and low-ability students benefit equally from attending schools with a better student intake, and most results for science are only marginally significant. These results imply that mixing students of different home backgrounds could improve equity of achievement for both reading and mathematics; however, the average skill level would improve only for reading literacy. In mathematics, mixing students would not raise average outcomes, because the detrimental effect on students in the higher quantiles would offset positive effects on those in the lower quantiles. I thank Amelie Constant, Bernd Fitzenberger, Eskil Heinesen, Peter Jensen, Craig Riddell, Michael Rosholm, Nina Smith, Robert Wright and participants at the ESPE and EALE 2003 conferences and at AKF seminars, and two anonymous referees for helpful comments and suggestions. Financial support provided by the Danish Social Science Research Council is gratefully acknowledged.     

The Effect of Information Technology on Economic Education

The author evaluated the effect on student performance of using a new information technology (IT) enhancement that permits students to participate in the recording of lectures that can be downloaded later from the Internet. The author compared two sections of the same Intermediate Microeconomics class and observed the sample students to be representative; the empirical model accounted for any differences in student characteristics between the comparison and test groups. Model results show that students exposed to the IT enhancement performed about 2 percentage points better on their final exam than did the comparison students; however, the difference was not statistically different from zero. The author concluded that the use of IT appears to not have any substantive influence on student performance.     

DOES TEACHER QUALITY AFFECT STUDENT PERFORMANCE? EVIDENCE FROM AN ITALIAN UNIVERSITY

In this paper, we analyse whether the characteristics of university teaching staff matter with regard to students' performance and interest in the discipline. We use data on about 1000 students enrolled on the first-level degree course in business and economics at a medium-sized Italian university. Thanks to the random assignment of students to different teaching classes during their first year, we are able to analyse the effect that teachers with different characteristics, in terms of experience and research productivity, produce both on students' performance, measured in terms of the grades obtained at subsequent examinations, and on courses chosen. Our results suggest that teacher quality has statistically significant effects on students' grades in subsequent courses. These effects are also robust after controlling for unobserved individual characteristics. On the other hand, we find less clear evidence when relating teacher quality to student involvement with a subject. It emerges that research productivity does not produce a statistically significant effect on the probability of a student undertaking additional courses in a subject, while more experienced teachers have a negative impact. However, also this effect does not become statistically significant when we run separate regressions for different disciplines.     

A new international database on education quality: 1965–2010

The aim of this article is to propose a new database allowing a comparative evaluation of the relative performance of schooling systems around the world. We measure this performance through pupils’ achievement in standardized tests. We merge all existing regional and international student achievement tests by using a specific methodology. When compared with other existing databases, our approach innovates in several ways, especially by including regional student achievement tests and intertemporal comparable indicators. We provide a data set of indicators of quality of student achievement for 103 countries/areas in primary education and 111 countries/areas in secondary education between 1965 and 2010.     

Does data matter? Statewide longitudinal data systems and student performance in the U.S.

Although many industries have benefited from advances in data-driven technology, education is making small steps in capitalizing on the huge potential of data systems. Since 2005, the U.S. Federal Government has been making large grants to help states build statewide longitudinal data systems (SLDS) with the goal of improving programme and teacher evaluation and engage in data-driven decision-making. We analyse whether the introduction of SLDSs improved student performance, measured using test scores for math and reading tests for 4th and 8th graders, as well as high school graduation rates. We find no effects of SLDSs on student performance up to 10 years from implementation. However, we find suggestive evidence that these systems may have long-run effects, emphasizing the long-run nature of educational data collection and policy analysis.     

Selecting successful students? Undergraduate grades as an admission criterion

In Europe’s reformed education system, universities may be forced by law to consider undergraduate grade point average (UGPA) as the primary admission criterion in the selection of graduate students. In this article, we investigate whether UGPA predicts graduate student performance in order to discuss its usefulness as an admission criterion. In our theoretical framework, we show that undergraduate students may choose slower study progress in favour of receiving higher grades and conclude that UGPA is a relatively good (weak) predictor for graduate grade point average (study progress). Having data from a cohort of students whose selection was in clear conflict with the legal requirement, we empirically confirm our theoretical predictions by exploiting a unique opportunity for assessing educational policies. Discussion of our findings leads to some important conclusions concerning the Bologna reforms and the lawmakers’ idea of giving some independence to universities, but not too much of it.     

Long term trends in fair and unfair inequality in the United States

This article analyses the microeconomic sources of wage inequality in the United States from 1967–2012. Decomposing inequality into factors categorized by degree of personal responsibility, education explains over twice as much of inequality today as 45 years ago. However, neither hours worked nor education, industry, marital status, or geographical location can explain the rise in income inequality. In fact, ‘unfair’ inequality (income disparity derived from non-responsibility factors) has risen faster than ‘fair’ inequality (income disparity derived from responsibility factors), regardless of the set of variables chosen as fair sources of inequality. We further examine income inequalities within gender and racial groups, finding substantial heterogeneity. Overall, using micro data to understand the sources of inequality and how these changes over time can provide better information for policymakers motivated to combat rising inequality.