Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/324443 
Erscheinungsjahr: 
2025
Schriftenreihe/Nr.: 
cemmap working paper No. CWP15/25
Verlag: 
Centre for Microdata Methods and Practice (cemmap), The Institute for Fiscal Studies (IFS), London
Zusammenfassung: 
This paper introduces a framework for selecting policies that maximize expected welfare under estimation uncertainty. The proposed method explicitly balances the size of the estimated welfare against the uncertainty inherent in its estimation, ensuring that chosen policies meet a reporting guarantee, namely, that actual welfare is guaranteed not to fall below the reported estimate with a pre-specified confidence level. We produce the efficient decision frontier, describing policies that offer maximum estimated welfare for a given acceptable level of estimation risk. We apply this approach to a variety of settings, including the selection of policy rules that allocate individuals to treatments and the allocation of limited budgets among competing social programs.
Schlagwörter: 
budget allocation
risk-aware policy learning
statistical decision theory
JEL: 
C14
C44
C52
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
654.5 kB





Publikationen in EconStor sind urheberrechtlich geschützt.