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The Historical Evolution of the Wealth Distribution : a Quantitative-Theoretic Investigation

Author: Joachim Hubmer; Per Krusell; A A Smith; National Bureau of Economic Research.
Publisher: Cambridge, Mass. National Bureau of Economic Research 2016.
Series: Working paper series (National Bureau of Economic Research), no. w23011.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This paper employs the benchmark heterogeneous-agent model used in macroeconomics to examine drivers of the rise in wealth inequality in the U.S. over the last thirty years. Several plausible candidates are formulated, calibrated to data, and examined through the lens of the model. There is one main finding: by far the most important driver is the significant drop in tax progressivity that started in the late 1970s,  Read more...
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Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Joachim Hubmer; Per Krusell; A A Smith; National Bureau of Economic Research.
OCLC Number: 1008875479
Notes: December 2016.
Description: 1 online resource
Series Title: Working paper series (National Bureau of Economic Research), no. w23011.
Responsibility: Joachim Hubmer, Per Krusell, Anthony A. Smith, Jr.

Abstract:

This paper employs the benchmark heterogeneous-agent model used in macroeconomics to examine drivers of the rise in wealth inequality in the U.S. over the last thirty years. Several plausible candidates are formulated, calibrated to data, and examined through the lens of the model. There is one main finding: by far the most important driver is the significant drop in tax progressivity that started in the late 1970s, intensified during the Reagan years, and then subsequently flattened out, with only a minor bounce back. The sharp observed increases in earnings inequality, the falling labor share over the recent decades, and potential mechanisms underlying changes in the gap between the interest rate and the growth rate (Piketty's r-g story) all fall far short of accounting for the data.

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