This document analyzes the long-term effects of the 1832 Cherokee Land Lottery on wealth using census and other data. It finds that those who received land titles in the lottery on average had higher wealth levels in 1850 and 1860 compared to those who did not receive titles, even after controlling for other factors. The effects were larger for those matched to land closest to gold deposits discovered in the 1830s.

1. Hoyt Bleakley
Univ. of Chicago
Joseph Ferrie
Northwestern Univ.
June 2013
Up from Poverty?
Long-run effects of the 1832 Cherokee
Land Lottery on Wealth

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96. Rawlsian?

99. Eligibility
l The land in this area was made available to settlers of
European descent by the eviction of the Cherokees
in that area
l Every adult male who had been resident for at least
three years in Georgia by 1832 was eligible to one
draw in this lottery
l Widows and orphans were eligible for two draws, but
we drop them (can’t identify them in 1850)

100. Eligibility, part 2.
l Revolutionary War veterans were also eligible for
multiple draws, but we drop them as well (they
cannot be identified in 1850 when we create
treatment and control groups).
l But most were dead by 1850 anyway
l A group of highwaymen (members of “The Pony
Club”) were also excluded
l The Cherokee Land was surveyed and subdivided
l The lottery commences…

102. 1832 1850
Eligible man
[wife]
≥1 kids 1829-32
[post-lotto kids]
Wealth in
Real estate
Slaveholdings
Ga ✓
SC ✗
NC ✗

103. The Data: Georgia
l Smith (1838) lists winners, parcels.
l Full-count 1850 census.
l Sample of “eligibles”. (Widespread registration.)
l N = 14,375

104. Fig. 4 Josiah Spivey and Family in 1850

105. Fig. 4 Josiah Spivey and Family in 1850

106. Fig. 4 Josiah Spivey and Family in 1850

107. Specification Checks
l Is our sample more or less likely to have won a
parcel?
l For at least two counties (Columbia
Oglethorpe), lists of eligibles have survived.
l In our sample, 15.5% are (1/n) matched to the
Smith list. In Columbia Oglethorpe county,
16.0% of the eligible names were drawn

108. Did the non-winners actually register?
l 75.8K registered 1832 from
{WM; 18+ age; 3+yr in Ga}
l 78.0K in 1830 census
{WM; 15+age; currently in Ga}
l 97.2% registration rate

109. Specification Checks
l Placebo test with South Carolina
l Balancing tests on pre-lottery outcomes

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172. Analysis of Outcomes: Georgia Lottery
l Residence. (In old Cherokee county?)
l Real-estate wealth
l Slave wealth

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204. Analysis of Outcomes: Georgia Lottery
d variables, as seen in Section 3, casts doubt on t
We return to this issue in Section 8.3 with an alt
equation, which we generally estimate using O
ijk j ijk a k ijkY = T + BX + ⇥ + ⇥ + ⇤
jrest, T , is a binary variable that denotes treatm
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329. Quantile results
l Rank stability
l Quantile regressions
l Compare variables by quantile of treatment
distribution

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392. Rawls again

393. Rawls again
ay to vary the equity weight when
an aggregator with a constant elas
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s in our sample, j is an indicator fo

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.911.11.21.31.4
RatioofCESAggregators(Treatment/Control)
.35 1 3.25 10 30 90 270 825 2500
Elasticity of Substitution

425. Mechanisms?
1. Life cycle
2. Fixed cost
3. Interaction with ability
4. Risk

426. Life cycle of wealth in control sample

427. Mechanisms?
1. Life cycle
2. Fixed cost
3. Interaction with ability
4. Risk

428. Mechanisms?
1. Life cycle
2. Fixed cost
3. Interaction with ability
4. Risk

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460. Mechanisms?
1. Life cycle
2. Fixed cost
3. Interaction with ability
4. Risk

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492. Interactions?
l Own literacy
l Average characteristics of surname

495. Risk and churn
l Risk exposure
l Journalistic and semi-fictional work (Banerjee/Duflo,
Boo, Wilder, Mitchell)
l Safety first (Wright, 1975)
l Walk-away farming (Ransom, 2005)

496. Risk and churn
l Compare 1850 to 1860 wealth. Corr = 0.6

497. Risk and churn
l Compare 1850 to 1860 wealth. Corr = 0.6
0.1.2.3.4
Probabilityof1860WealthNoGreaterThanThreshold
.1 .25 .5 1 2.5 5 10 20 30 50
Natural Log of Total Wealth, 1850
Fraction holding no more than $100 in 1860
95% Conf. Int.
Prob. Density Function in 1850

498. Hoyt Bleakley
Univ. of Chicago
Joseph Ferrie
Northwestern Univ.
December 9, 2012
Up from Poverty?
Long-run effects of the 1832 Cherokee
Land Lottery on Wealth

499. Extensions / Related Work
l Placebo sample from South Carolina
l Relaxing the rank-invariance assumption in the
quantile analysis
l Intergenerational effects
l Importance of initial property allocation
(follow up the place rather than the person)

500. Mapping to returns?
l Rank invariance (quantile regs)
l Compute bounds for weaker assumptions,
using Markov matrix P:
l xt' = xc' P
l 1 = P 1
l 1 P 0
l Expected returns: Py or (P-I)y, net of starting yi
l Linear in P, with bounds.

501. Mapping to returns?
l Rewrite as
l A vec(P) = b
l A, b formed by Kronecker product of Identity
matrix with x’s and 1 vectors.
l 1vec(P)0
l Treatment effect Δ = C’vec(P); C = kron(y’,Im)’
l Compute bounds on elements of Δ

502. Mapping to returns?
l Linear programming
l Assumptions:
1. Bounds only
2. Ex post Pareto dominates to win (|yi)
3. FOSD to win (|yi)
4. Expected Δ positive for all yi
l Feasible?
l Bounds?

504. Shocking Behavior
The Cherokee Land Lottery of 1832
and Later Life Outcomes
Hoyt Bleakley
Univ. of Chicago
Joseph Ferrie
Northwestern Univ.
Spring 2013

505. Land Openings
on the Georgia
Frontier
and
the Coase
Theorem in the
Short- and
Long-Run
Hoyt Bleakley
(Univ. of Chicago)
Joseph Ferrie
(Northwestern Univ.)
Spring 2013

507. Summary
l Land Openings in “Lottery Zone” of Georgia
l Initial Parcel Sizes were...
l Quite sticky for c. 80 years (one for one)
l Unstuck by c. 150 years
l Misallocation cost c. 20% of 1880 land value

508. Diff-in-diff estimates of β, by decade

510. Average reduction in land value
−.3−.2−.10
1880 1890 1900 1910 1920 1930 1940 1950

511. Hoyt Bleakley
Univ. of Chicago
Joseph Ferrie
Northwestern Univ.
Up from Poverty?
Long-run effects of the 1832 Cherokee
Land Lottery on Wealth

512. Bonus: simulations
l Take a log-normal control distribution
l Perturb in various way to get simulated
treatment distribution

513. Control

514. Constant shift in logs (illustrative only)

515. Constant shift in levels

516. Constant shift in levels, 50% takeup

517. Higher return at the low end

518. Constant shift in levels

519. Higher return at the high end