A Q-Theory of Inequality
- Type of resource
- Text
- Presented
- Stanford (Calif.) : Stanford Institute for Theoretical Economics, 2020
- Language
- English
- Digital origin
- born digital
- Extent
- 1 online resource
- Form
- online resource
Digital content
Context
Item belongs to a collection
Stanford Institute for Theoretical Economics (SITE) Archives
Since 1989, Stanford University's Department of Economics has hosted a series of workshop sessions in economic theory and mathematical economics. This program is known as the Stanford Institute for Theoretical Economics (SITE). Its purpose is to advance economic science for the benefit of society and to support cutting-edge work of economic theorists within specialized areas of research. The SITE Archives documents the workshop proceedings over time. Access to the presented papers is available in cases where the original material was provided by the author(s). This portion of the archive includes records describing papers where a copy of the original material is preserved and accessible.
- Digital collection
- 3144 digital items
Description
Creators/Contributors
Abstract/Contents
We study the effect of interest rates on top wealth inequality. While lower rates decrease the average growth rate of existing fortunes, they increase the growth rate of new fortunes by making it cheaper to raise capital. We develop a sufficient statistic approach to express the effect of interest rates on the Pareto exponent of the wealth distribution: it depends on the average equity issuance and leverage of individuals reaching the top. Quantitatively, we find that the secular decline in real interest rates has been a major contributor to the rise in top wealth inequality in the U.S.
Subjects
Bibliographic information
- Note
- Presented at SITE on July 17, 2020
- Session series
- Asset Pricing, Macro Finance, and Computation
- Session
- Organizer of meeting:
- Judd, Kenneth, Pohl, Walter, Schmedders, Karl, Wilms, Ole
- Abstract:
- This session focuses on recent advances in asset pricing and macro finance as well as the use of computational techniques in these areas. Possible topics include but are not limited to the following: investor heterogeneity, learning and ambiguity, new preference structures for pricing models, or using machine learning to understand the cross-section of returns. As the analysis of such models often requires the use of computational methods, we encourage submissions that develop and make use of new numerical techniques.
- Repository
- Stanford Institute for Theoretical Economics
- Location
- https://purl.stanford.edu/mb286yj5502
Access conditions
- Use and reproduction
- This publication is open for research use. Copyright is retained by the author(s) or their heir(s).
