Discussion of “Misreported Schooling, Multiple Measures and Returns to

Educational Qualifications” by Erich Battistin and Barbara Sianesi

Andreas Ammermueller

ZEW, Mannheim

Outline of discussion

• Contributions• Assumptions• Empirical application

Contributions

• General approach for correcting measurement error in treatment effects framework: extend measurement error correction (IV) to non-trivial categorical cases

• Can be extended to multiple treatments and heterogeneous invidual returns

• Application in a policy-relevant field, estimates of accuracy of qualification data for the UK

Assumptions

• Unconfoundedness: Few data sources provide sufficient information to be credible, even questionable in case of NCDS

• Non-differential misclassification given X: Even stronger than above; what drives missclassification and its direction?

• Independent reports of DA and DB: Difficult, regional/school level correlation in NCDS case

Empirical application: Returns to higher education, NCDS

• Distinguishing between only two groups invites no less criticism than using years of schooling: very heterogeneous groups, what is estimated?

• Restricted sample with full educational information: might trade measurement error against sample selection

• Biases have same direction but different size compared to OLS/years of schooling case

main story of application

Application continued

• Do assumptions for measurement error correction apply here?

• Test scores as controls for ability: imperfect measure, just another educational outcome

• Not convinced of control for ability bias: no classical approach

show control for ability bias in OLS case and test assumptions as far as possible