• Medientyp: E-Book
  • Titel: Nonparametric identification and estimation with non-classical errors-in-variables
  • Beteiligte: Evdokimov, Kirill S. [VerfasserIn]; Zeleneev, Andrei [VerfasserIn]
  • Erschienen: [London]: Cemmap, Centre for Microdata Methods and Practice, The Institute for Fiscal Studies, Department of Economics, UCL, [2024]
  • Erschienen in: Centre for Microdata Methods and Practice: CEMMAP working papers ; 2024,6
  • Ausgabe: This version: December, 2023
  • Umfang: 1 Online-Ressource (circa 41 Seiten)
  • Sprache: Englisch
  • DOI: 10.47004/wp.cem.2024.0624
  • Identifikator:
  • Schlagwörter: Nichtparametrisches Verfahren ; Statistischer Fehler ; Regressionsanalyse ; Schätztheorie ; Graue Literatur
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: This paper considers nonparametric identification and estimation of the regression function when a covariate is mismeasured. The measurement error need not be classical. Employing the small measurement error approximation, we establish nonparametric identification under weak and easy-to-interpret conditions on the instrumental variable. The paper also provides nonparametric estimators of the regression function and derives their rates of convergence.
  • Zugangsstatus: Freier Zugang