Redistribution for Realists
67 Pages Posted: 25 Feb 2021 Last revised: 8 Feb 2022
Date Written: January 2022
Inequality is a defining issue of our time. Nevertheless, the longstanding economic orthodoxy for addressing inequality is that we should redistribute solely through tax and transfer policies because those are the most efficient means for doing so.
While the orthodoxy holds in theory, it fails in practice because of the public’s psychology about redistribution. New evidence shows that individuals silo their policy views: many are reluctant to redistribute through taxes and transfers but are willing to do so in other policy domains, like provision of necessities such as transportation, food, and housing. The orthodoxy thus restricts redistribution efforts to a policy domain where the public resists redistribution while neglecting the many policy domains where the public embraces redistributive policies. The current orthodoxy may be more efficient, but it is also a prescription for widespread inequality.
We need to flip the old economic orthodoxy on its head by spreading our redistribution efforts across many policy domains, but doing so modestly in each domain. This “thousand points of equity” approach has the virtue of redistributing where it can be achieved, by allowing policymakers to seek modest and attainable redistribution in many domains rather than pushing for massive redistribution in a single domain where it is difficult to attain. This approach would allow us to make substantial inroads on inequality while doing the most good at the least cost. The approach does so by retaining the traditional economic goal of efficiency, but combining it with data-driven behavioral insights about what redistribution is politically realistic. The Article illustrates how the approach would apply to areas across the law, including regulatory cost-benefit analysis, labor law, tax law, social insurance, tort law, and housing law.
Keywords: inequality, law and economics, taxation, transfers, redistribution, cost-benefit analysis
JEL Classification: D63, H23, H21, K10, K23, K34
Suggested Citation: Suggested Citation