Grade Inflation and the Interpretation of Labor Market Signals.

Autor/inn/en	Pu, Zhizhong; Abel, Martin; Carpenter, Jeffrey
Titel	Grade Inflation and the Interpretation of Labor Market Signals. Gefälligkeitsübersetzung: Noteninflation und die Interpretation von Signalen des Arbeitsmarktes.
Quelle	Bonn: IZA Network @ LISER (2026), 68 S. PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Reihe	IZA discussion paper / IZA Network @ LISER. 18654
Sprache	englisch
Dokumenttyp	online; Monografie
Schlagwörter	Kompetenz; Stereotyp; Psychischer Faktor; Verhalten; Vorurteil; Wahrnehmung; Mathematik; Einkommensunterschied; Skalierung; Personalauswahl; Bewerbungsverhalten; Stellenbesetzung; Studienerfolg; Auswirkung; Bewertung; Effizienz; Geschlechtsspezifik; Hochschulabsolvent; Arbeitgeber; Student; USA
Abstract	"We study how grading policies shape employers' interpretations of labor market signals embedded in academic credentials. In our experiment, hiring managers observe letter grades assigned to math tests taken by job candidates and make wage offers to match their beliefs about each candidate's underlying ability. We exogenously vary the coarseness of the grading scheme while holding candidate performance constant. As predicted, coarser grading leads managers to place less weight on grade signals and more on prior beliefs, reducing match efficiency. Departing from predictions, managers extract systematically higher signals from inflated grades, behaving as if candidates with As represent a positively selected pool. Furthermore, managers place greater decision weight on inflated As than on compressed Bs, creating a compounding wage advantage for candidates even though grade inflation is common knowledge. Considering the broader implications of our results, the shift toward prior-based evaluation under coarser grading falls disproportionately on female candidates, contributing to a wider gender wage gap among managers with gendered priors." (Author's abstract, IAB-Doku).
Erfasst von	Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg
Update	2026/4