Characterizing Selection Bias Using Experimental Data

“…12 For our analysis we use the inverse probability weighting estimator. 13 This procedure aims to obtain estimates of the average treatment e¤ ect for the treated (ATT), that is, the average e¤ect for those in schools that teach the course. 14 Given a set of covariates X, assumption (2) is testable, by comparing the distributions of the probability of participation in the program between the treatment group and the controls.…”

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confidence: 99%

Finance for All: The Impact of Financial Literacy Training in Compulsory Secondary Education in Spain

2015

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu We estimate the impact on objective measures of financial literacy of a 10-hours financial education program among 15-year old students in compulsory secondary schooling. We use a matched sample of students and teachers in Madrid and two different estimation strategies. Firstly, we use reweighting estimators to compare the performance in a test of financial knowledge of students in treatment and control schools. In another specification, we use school fixed-effect estimates of the effect of the course on change in the score in tests of financial knowledge. The program increased treated students' financial knowledge by between one fourth and one third of a standard deviation. We uncover heterogeneous effects, as students in private schools did not increase their knowledge much, possibly due to a less intensive implementation of the program. Secondly, we analyze the bias that arises because the set of schools that participate in financial literacy programs is not random. Such selection bias is estimated as the pre-program performance in financial PISA of students in applicant schools relative to a nationally representative sample of schools. We then study if estimators that condition on school and parental characteristics mitigate selection bias. Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E S

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“…Thus, the proper comparison of these states is in most cases not possible. Heckman et al 1998 developed a methodology to approximate this nonobservable ("counterfactual") state of a certain firm with the observable same state of another firm which is "structurally similar" to the first one according to a series of firm characteristics formally defined by a vector X. Thus, besides the group of firms which are KTT-active we need a pool of firms which are not KTT-active (control group) out of which "structurally similar" firms are selected according to a "proximity" criterion.…”

Section: Main Hypotheses Model Specification and Estimation Methodsmentioning

confidence: 99%

Is There Any Impact of University-Industry Knowledge Transfer on the Performance of Private Enterprises? An Empirical Analysis Based on Swiss Firm Data

Arvanitis

Sydow²,

Woerter

2005

SSRN Journal

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Characterizing Selection Bias Using Experimental Data

Cited by 636 publications

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Income transfer policies and the impacts on the immunization of children: the Bolsa Família Program

Income transfer policies and the impacts on the immunization of children: the Bolsa Família Program

Finance for All: The Impact of Financial Literacy Training in Compulsory Secondary Education in Spain

Is There Any Impact of University-Industry Knowledge Transfer on the Performance of Private Enterprises? An Empirical Analysis Based on Swiss Firm Data

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