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Add wealth_tax lecture: estimating wealth tax revenue - #852
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Compare the weighted 2022 SCF estimate of revenue from a modified Warren wealth tax with a Pareto-tail estimate fitted by weighted MLE above $10M, and check the fitted tail against the 2022 Forbes 400. Add the lecture to the Estimation section, point heavy_tails at it, and add bibliography entries. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Tighten the overview and tax schedule exposition, simplify h, rename the survey weights to lambda, spell out the Forbes 400 tax calculation using h, and drop the threshold sensitivity figure. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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This was referenced Oct 6, 2026
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Adds a new lecture,
wealth_tax, to the Estimation section, aftermle. It applies maximum likelihood to a policy question: how much revenue would a wealth tax on the very rich raise?Contents
The tax: a modification of Senator Warren's 2019 proposal, with marginal rates of 1% on $10M–$50M, 2% on $50M–$1B and 6% above $1B.
Survey estimate: a weighted sum over the 2022 Survey of Consumer Finances. It also explains survey weights and the oversampling of wealthy households.
The missing rich: the SCF excludes the Forbes 400 by design, and the public file stops just below the $2.7B Forbes cutoff. Under the schedule, the Forbes 400 alone would owe $224B a year.
Pareto model: motivated by the weighted counter-CDF, which is roughly linear on log-log axes above $10M. The tail index is estimated by weighted MLE (α̂ ≈ 1.56, in line with published estimates of about 1.5).
Pareto revenue estimate: in closed form. The comparison by bracket:
Out-of-sample check: the model predicts 339 households worth $2.5T above $2.7B, against the Forbes 400's 400 households worth $4.0T.
Sensitivity to α, and a caveat about behavioral responses.
Exercises:
Other changes
wealth_taxto_toc.ymlaftermle.heavy_tails: the "Fiscal policy" link about tax revenue now points towealth_tax, sincemleno longer contains a tax example.Data
Reads
us_household_net_worth_2022.csvfrom QuantEcon/data-lectures, added in QuantEcon/data-lectures#144 (merged). A follow-up there will mark the dataset as repointed inmigration.ymlonce this PR merges.Builds locally with no warnings.
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