Welfare measurements with heterogeneous agents

Marcin Dec () and Marek Weretka

No 50, GRAPE Working Papers from GRAPE Group for Research in Applied Economics

Abstract: The canonical infinite horizon framework with heterogeneous consumers, used in macro and financial literature, lacks a preference-based welfare index that produces consistent normative predictions for different policies. In particular, the classic preference-based indices, such as equivalent or compensating variations, do not aggregate and they are not additive on the set of policies. This paper offers a positive result. We show that for arbitrary heterogeneous von Neumann Morgenstern preferences with common discount factor, an equivalent (compensating) variation is nearly additive and admits a representative agent representation, as long as consumers are patient. Therefore, this index generates consistent quantitative comparisons of welfare effects in a wide variety of problems studied in the macro and finance literature. These problems include, among others, predictions regarding welfare impacts of fiscal or monetary policies, costs of real business cycles, or welfare costs of policies implemented in financial markets.

Keywords: Preference-based welfare; additivity; aggregation (search for similar items in EconPapers)
JEL-codes: D43 D53 G11 G12 L13 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://grape.org.pl/WP/50_DecWeretka_website.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fme:wpaper:50

Access Statistics for this paper

More papers in GRAPE Working Papers from GRAPE Group for Research in Applied Economics Contact information at EDIRC.
Bibliographic data for series maintained by Jan Hagemejer ().