Vincent Vandenberghe & Stephane Robin Alice Ballabio

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Presentation transcript:

Vincent Vandenberghe & Stephane Robin Alice Ballabio Does (Private) Education Matter? Recent Evidence from International OECD data Vincent Vandenberghe & Stephane Robin Alice Ballabio

Plan of presentation Introduction First section: Theoretical framework Second section: Data set and estimation strategy Third section: Results and Analysis Conclusion

Introduction The aim of this study is to estimate private vs. public sector schools relating to the effect on academic achievements. In order to do that, the authors used a research of PISA, which is a Programme for International Student Assessment sponsored by OECD “Organization for Economic Co-operation and Development”. This survey, carried out in 2000, is aimed at testing the competencies in Maths, Sciences and Reading of representative samples of 15 year-old students across OECD and non-OECD countries.

List of countries Australia, Austria, Belgium (French-Speaking), Belgium (Dutch-Speaking), Brazil, Canada, China, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Hong Kong China, Korea, Latvia, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Russian Federation, Spain, Sweden, Switzerland, United Kingdom, United States.

Defining Public and Private School Public school  is a school managed directly or indirectly by a public education authority, a government agency, or governing board appointed by government. Private school  is a school managed directly or indirectly by a non-government organization (for instance, a church, trade unions, businesses, or other private institutions).

First Section: Theoretical Framework Education production function Different categories of variables and biases that must be accounted for in order to isolate a true private/public differential effectiveness Empirical strategy used to estimate these models

Education production function The academic achievement A, at any time period t, is a function of monetary school resources, of the student’s peers and of the student’s individual characteristics. A = f (R, SC, P) A = student’s achievement R = school monetary resources or proxies SC = student’s characteristics (including family and social background) P = some characterization of the group of peers

Education production function Student i’s achievement (Aij) in country j can be explained by a linear model of the following form: i = student index j = country index Aij = Rij j + SCij j + Pij j + j PRIVij + ij

Education production function Where:  = controls the effect of the monetary resources on the level of A  = controls the effect of the individual characteristics on A  = controls the effect of the group of peers on A The main important variable, which makes a difference is the coefficient  which controls the effect on the variable PRIV The estimated value (PRIV) for the coefficient  will capture the differential effectiveness between private and public schools

Sample Selection Bias of Heckman The sample is not randomly chosen. There may be a number of unobserved variables or variable that are imperfectly measured that could determine the choice to attend or not to attend the private school. Because of motivation, ability, selection or self-selection are unobserved, the relative effectiveness of private and public schools could be confused with the background of their students. In this way, there is the insertion of the BIAS.

“Treatment effect” model, inspired by “Two-steps” correction model of Heckman To eliminate Selection Bias: - The first step, which indicates a choice within each j country, to attend or not to attend the private school is given by; PRIV* ij = Zijj + ij Where: PRIV* = indicates the choice to attend or not to attend the private school. Z = represents the probability that a student decides to attend a private school on the base of some controlled factors related on the private/public dummy variable, which are: (you can see it looking at the database) GIRL = gender NSIB = number of siblings BRTHORD = the birth order of student MISCED = highest degree of mother FISCED = highest degree of father FATHIM = immigration status of father HISEI = highest socio-economic index of the two parents HEDRES = cultural resources

“Treatment effect” model, inspired by “Two-steps” correction model of Heckman The choice equation regresses the set of individual characteristics on the private/public dummy variable (PRIV). The choice to attend or not to attend the private school is made according to the rule: PRIV = 1 if PRIV* ij >0, PRIV = 0 otherwise For the estimation of this equation they used the probit model which hypothesizes that the choice between public or private school is given by the propensity to attend private school or the public one. This model linked the linear expression Zijj + ij to the probability of attending a private school.

“Treatment effect” model, inspired by “Two-steps” correction model of Heckman - The Second step, which indicates the achievement; The achievement in private school (Aij  PRIVij = 1) is only observed when the unobserved variable of the choice model is positive (PRIV*>0). Algebraically, this means that: E (Aij  PRIVij = 1) = E (Aij PRIV*ij >0) = E (Aij ij > - Zij j) = Rij j + SCij j + Pij j + j +    ( Zijj) /  (Zijj)  if (ij, ij)  bivariate normal 0,0,1, ,  Where:  = is the probability density function  = is the cumulative distribution function of the standard normal distribution  = is the correlation coefficient between ij and ij

“Treatment effect” model, inspired by “Two-steps” correction model of Heckman The achievement equation regresses the whole set of variable on achievement A, which are (looking at our database): X = Z + STRATIO = student/teacher ratio SCHSIZE = size of the school (school total enrolment) PRBUILD = school with poor buildings LCTMAT = lack of teaching materials PHISEI = socio-economic status of the peer group The two equations contain the same set of individual variable; Choice equation = Z Achievement equation = X + Z (so X that contains also Z) In order to avoid identification problems, the authors add to the equation a variable that operates like an instrument which is not related to A, that is PERCPUBL, which indicates the percentage of a school’s total resources that are of a public origin

“Treatment effect” model, inspired by “Two-steps” correction model of Heckman Finally, the expected achievement of students who choose public school is E(Aij│PRIVij=0) = Rjjaj +SCijbj + Pjjcj + ρσε [(Zijζj )/1-(Zijζj )] And the difference between two types of schools in country j is E(Aij│PRIVij=1) - E(Aij│PRIVij=0) = dj + ρσε [ (Zijζj )/1-(Zijζj )]

Second Section: Data set and estimation strategy Presentation of the PISA programme Presentation of the data set through some main tables Presentation of the estimation strategy

What is PISA? PISA is an internationally standardized assessment developed jointly by the participating countries. PISA aims to assess competences in Maths, Reading and Science, not so much to evaluate the comprehension of the scholastic programme, but rather to evaluate the capacity to develop these competences also in the lifestyle. In particular, they aim to evaluate the understanding of concepts and the ability to apply them in different areas and situations. The assessment is via written examination which can be through multiple choice and through open questions. Also the head teachers have to answer to a questionnaire in order to provide information about the scholastic institution in which students belong. It is important to underline that the evaluation occurs every three years.

What is PISA? Through this tool emerge: - The outline of knowledge and skills of students - Context indicators which relate the characteristics of schools and students - Trend indicators that show changes in performance over time Mathematical Literacy: It implies the ability of an individual to identify and to apply the role of maths in the real world. It is important that a student compare themselves with Maths in order to satisfy needs that life as a citizen requires. Reading Literacy: It implies the ability of an individual to understand und utilize texts in order to reflect on their content. In this way it is possible that a student develops own skills and potentials and therefore they are able to perform an active role in the society. Scientific Literacy: It implies the ability to use scientific competences in order to understand the natural world around them and the changes that science brings to human activity and therefore makes decisions on them.

Through this instrument emerges other context information as: What is PISA? Through this instrument emerges other context information as: Family origin of students Socio-economic background of students and families Habits and attitudes of students in school and families Characteristics of schools as; quality of human resources and materials, public or private funding, teacher recruitment. Educational context; institutional structures, class sizes, parental involvement. Teaching strategies Learning methods Motivation and involvement of students

The data set To carry out the analysis the authors selected countries for which the number of students sampled and attending private school is above a 10% threshold. This lead to a subset of countries containing: Netherlands, Belgium, Mexico, Ireland, Spain, France, Denmark, Austria and Brazil. The authors make a restriction to the states on which make inquiries concerning the analysis. Justification for this restriction are twofold: 1)It makes no sense, statistically speaking, to assess a private school effect in a particular country using test scores of just of few dozen students. 2)Policy makers who currently discuss the opportunity to expand the private sector (for example using vouchers) are interested in knowing whether private schools make a difference when attended by a large and heterogeneous population.

Main Tables

Main Tables

Main Tables

Main Tables

Estimation strategy Finally, I would like just to say some words about the estimation strategy used by the authors in the regression; the authors used scores that have been standardized by countries (for instance, each country mean score = 0 and standard deviation = 1) in order to measure gross differentials. In this way they want to compare the average values of maths, science and reading test scores of students for each type of school. Then, they used the traditional OLS model to get a first estimate of the net private school effect (for instance controlling for level of resources, socio-economic status and peer endowments). In the last step they used to estimate a real “treatment effect” model and contrary to OLS approach, this should produce unbiased estimates of private school effect, controlling for selection bias

Third section: Results and Analysis Reading the results using tables: Looking at these tables we could see three results of interest: - the gross score differential between private and public students - the coefficient associated to the PRIV dummy () in an OLS regression model without control for selection biases - the coefficient associated to the PRIV dummy () in the treatment model

Main Tables

Main Tables

Main Tables

Main Tables

Conclusion Even when selection biases are taken into account, the type of school (private of public) attended can have a significant effect on 15 year-olds' academic achievement. We conclude to the absence of systematic advantage to private schools. Yet the conclusion is slightly different if one looks at the results from a country perspective How come that the advantage to private schools holds only for some countries? Conversely, how can one explains that in some other countries privately run schools seem to deliver less than public ones? 1) The “organizational” interpretation of achievement difference. Following this line of reasoning, private school in Brazil, Ireland or Belgium could possibly perform better because they are granted more autonomy. And maybe private schools have less autonomy than public ones in the Netherlands or Austria. 2) The “cultural” interpretation of private/public school difference. Rather than talking about “private schools” effects, it might make more sense – at least in some countries like Ireland or Belgium - to talk about “religious” schools effect. Indeed, a majority of private schools are, by religiously affiliated boards (the author focuses on the example of Catholic Schools). According to this cultural interpretation, the (marginally) better training received in private schools could be explained by religious values. In fact, the main religions existing today enhance values such as hard work, effort and dedication to a task.