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Big questions in this lecture

Stockholm Doctoral Course Program in Economics

Development Economics II — Lecture 1

Property Rights

Masayuki Kudamatsu

IIES, Stockholm University Motivations

Institutions matter for development

Property rights: often at the core of • this argument

Acemoglu-Johnson-Robinson (2001):

measure institutions with risk of
expropriation of assets by government Acemoglu-Johnson (2005): show
property rights, not contract enforcement, matter for development

Big questions in this lecture

1. How & When do secure

property rights promote development?

2. What makes property rights secure?

Conceptual issues

Two aspects of (private) property rights:

1. Protection against expropriation Conceptual issues

1. Protection against expropriation

Two aspects of (private) property rights:

2. Facilitating market transactions

Land rental markets
Credit markets

Conceptual issues

Two aspects of (private) property rights:

1. Protection against expropriation

Expropriation by whom?

2. Facilitating market transactions

Land rental markets
Credit markets

Conceptual issues

Two aspects of (private) property rights:

1. Protection against expropriation

Expropriation by whom?
Other private agents
Government

2. Facilitating market transactions

Land rental markets
Credit markets

Conceptual issues

Two aspects of (private) property rights:

1. Protection against expropriation

Expropriation by whom?
Other private agents
Government •

How different from taxation?

2. Facilitating market transactions

Land rental markets
Credit markets

4 mechanisms (Besley-Ghatak 2009a)

1. Expropriation risk ↓

⇒ Return to investment ↑

2. Guard labor ↓

⇒ Productive use of labor ↑

3. Trade of assets ↑

⇒ Asset manager’s productivity ↑

4. Assets used as collateral ↑

1-1 Expropriation risk

Property rights: how much of • investment return you actually receive

Including bribe payments out of profit

(Johnson-McMillan-Woodruff 2002) Conceptually same as sharecropping
Does secure property rights always
encourage investment via this mechanism?

Model 1

One producer-consumer • Endowed w/ 1 unit of land & ¯ e

units of time

≤ 1

√ Technology: y = A e

∗

A

≤ 2 assumed (so e ≤ 1)

Preference: u (c, l) = c + l where
l + e

≤ ¯e Model 1 (cont.)

Property rights w/ prob. τ , outputs/land • expropriated after e is sunk

τ affects the optimal How •

∗

investment level e ? Analysis

Agent solves √

(1 + ¯ max e e − τ)A − e

e ∈{0,¯e}

FOC: (1

− τ)A √

≥ 1 2 e Optimal investment level: _{!" # $}

2

(1 − τ)A

∗

= min , ¯ e e If interior solution, producer’s • _{" #}

2 (1−τ)A

indirect utility is also ₂

2 (1−τ)A

Output is given by

2

Impact of property rights

Secure property rights ⇒ Investment ↑ unless

∗

e

= ¯ e (e.g. imperfect labor market)

Lump-sum transfer available

⇒ For these 2 cases, impact is just distributional

1-2 Guard labor

Model 1 assumes protection • against expropriation by govt. Private agents can protect their

properties on their own Insecure property rights
⇒ Need to guard your property ⇒ Less time/resources for productive activities In what cases does this intuition •

2 cases to consider When insecure properties are used • for production When insecure properties are NOT • used for production (e.g. residential property)

2 cases: w/o & w/ complementarity

btw. income & utility from properties

Model 2A

e

1

∈ [0, 1]: productive labor

2

e

∈ [0, 1]: guard labor

e

₁

₂

Prob. of expropriation:

τ (1 − γ √ e

2 )

γ ∈ [0, 1]: effectiveness of guard labor
The rest: same as Model 1

Analysis

Agent solves √ √ max (1 e

2 ))A e 1 + ¯ e

1

2

− τ(1 − γ − e − e

e ₁ ,e ₂ ∗ ∗

e < ¯ Optimal effort levels (if e

e) are:

1

2 _{% &}

2

2 (1 − τ)A

∗

e =

1

2

4 − (τγA)

2 _{% &}

2

γτ (1 − τ)A

∗

= e

2

2

4 − (τγA)

Investment (e
Guard labor (e

): first ↑ & then ↓

:

2

2√e ₁

[1−τ(1−γ √ e ₂ )]A

1 & e 2 : complementary

⇐ e

2

∗

): ↑

1

∗

Impact of property rights As τ goes down from 1...

Marginal return to e 1 :

γτ A√e ₁ 2√e ₂

Marginal return to e

∗ ∗

If e + e

1 2 ≥ ¯e (say, due to labor market

imperfection): FOC: •

1 √

(1 e

2 )A = 1 + λ

− τ + τγ √ 2 e

1

1 √

τ γ A e = 1 + λ

1

√ 2 e

2

₊ _* which yields _'

₂

1

1

1 1 e ₂

e = ) + + ₂ With resource constraint binding, •

2

τ ↓ ⇒ e ↓ always Summary: Simple intuition holds • unless τ is close to 1 & resource constraint is not binding Evidence: Hornbeck (2009)

Late 19c American Plains • Marginal cost of e •

2

↓ by barbed wire This cost reduction: larger for • counties with less woodland DID estimation: compare changes • in outcomes btw. counties w/ less vs more woodland Results

Counties w/ less woodland: (1)

invest in land

↑, (2) land value ↑, (3) productivity ↑, (4) share of crops in need of protection

↑ Only during the period in which • barbed wire was gradually introduced (1880-1900) An interpretation

τ : Probability that other private

agents (cattle owners) “expropriate” your investment return

No formal right to compensation for

damages by cattle encroachment

Evidence for complementarity of e •

2

& e

1 Model 2B

Productive assets: no risk of • expropriation

e.g. Human capital

√ yields A e

1

1

⇒ e

h: Value of non-productive assets

facing risk of expropriation:

h = h > 0 if not expropriated

h = h = 0 if expropriated

Producer solves • √ max (1 e

2 ))h

− τ(1 − γ

e ₁ ,e ₂

√

A e + ¯ e

1

1

2

− e − e

∗

Not surprisingly, e unaffected by τ •

1

e

2 goes up with τ

If resource constraint binding, e •

1

goes down with τ Model 2B’

Suppose consumption & utility from • assets are complements

α β

u (c, h, l) = c h + l α + β < 1, α > 0, β > 0 where

In this case, if τ is small,

∂e

1

< 0 ∂τ Summary ∂e ₁

< 0 unless

∂τ

No binding resource constraint & • expropriation risk for non-productive assets

∂e ₂

> 0 unless

∂τ

No binding resource constraint, &

expropriation risk for productive assets & τ is large

Exploit phase-in nature of land

titling program of urban squatters in Lima, Peru Cross-sectional micro data & • estimate

′

y id = αS i + βT d + γS i d δ + ε id

x × T id

y : labor supply / indicator for

id

working away from home S : squatter indicator

i

γ: Program effect

Compare squatters between program

districts and non-program districts They are comparable in observables
Program covered all districts
eventually

Result: γ > 0 ˆ •

For subsample, 2-period panel data

available First-difference estimates give γ of ˆ
similar size ⇒ Bias due to individual unobservable:

Land titling on residential assets ⇒

Model 2B relevant Resource constraint binding (hard
to employ guard labor) Or complementarity between
residential assets & consumption (Model 2B’)

If you protect your property, thieves

target other people’s property

⇒ Guard labor has negative externality Same logic suggests γ was ˆ • overestimated in Field (2007)?

Non-program squatters more likely to

start business at home after the program started (Columns (3)-(4) in Table VI)

1-3 Barriers to trade

Secure property rights: encourage • sale/rental of assets ⇒ Assets managed by those who use them most productively ⇒ Investment & output ↑

Example: tenancy law in India

Model 3

A continuum of agents
δ of them: landed, 1 − δ: landless
Time: infinite

√ Technology: y = θA e (w/ land)

θ: agent’s productivity • θ = θ w/ prob. p

θ = θ w/ prob. 1

− p

≤ θ < θ ≤ 1
θ: i.i.d. across individuals & time
Alternatively, agents can always earn wage u

≥ 0

θ rents land out If landed agent w/ • to landless agent w/

θ, output ↑ Consider rental contracts where

Landless pays rent upfront
Contract duration: one period
Property rights: w/ prob. τ , rented
land won’t be returned to landed

√ max θA e + ¯ e − e

e

which yields (if interior solution)

2

(θA)

∗

e =

4 ₂

(θA) ∗

Denote the profit by π (θ) =

4 Assumptions

∗

(θ) > u

π
There’s gain from trade
(1

− p)(1 − δ) > pδ

Gain from trade accrues to landed

⇒ Rental price: r

∗

= π

∗

( θ) − u

Analysis

Compare the payoffs of a landowner from the following 2 strategies: When θ = θ, rent land to landless w/

θ. When θ = θ, cultivate on his own Irrespective of θ, cultivate on his
own

Denote the payoffs when θ = θ & θ = θ

under 1st strategy: V , W

′ ′ Payoff from renting land

V = π

∗

( θ) + β(1 − τ)[(1 − p)W + pV ]

W = π

∗

(θ) + β[(1 − p)W + pV ]

Solving for V yields V =

1 − βτ(1 − p)

1 − (1 − τp)β

π

∗

( θ) Payoff from not renting land ′ ∗ ′ ′

V = π (θ) + β[(1 + pV ] − p)W

′ ∗ ′ ′

W = π ( + pV ] θ) + β[(1 − p)W

′

Solving for V yields

∗ ∗

(1 (θ) + β(1 (θ) − β(1 − p))π − p)π

′

V =

1 − β Comparison

′

1
′

τ = 0 ⇒ V > V

, if β > τ = 1 ⇒ V < V

2 −p ′

V decreases w/ τ while V does not

depend on τ

′

if τ > ˆ τ ⇒ ∃ˆτ ∈ (0, 1), V < V

Insecure property rights reduce output

∗ ∗

by δp[π (θ) (θ)] − π

1-4 Collateralizability

de Soto (1989, 2000)’s “dead capital” Poor people do have assets

But they don’t formally register
them

⇐ Very costly do to so in LDCs

So they cannot use them as

collateral to borrow money & stay poor

When does this story hold true?

Model 4

(A simplified version of Besley-Ghatak 2009b)

Producer/borrower & lender
x

∈ {0, 1}: capital

√ e

Output: A (1 + ∆x)
Cost of capital: ρ
e: borrower’s private information Limited liability •

In case of default, borrowers don’t

need to repay more than their assets

w : value of borrower’s illiquid asset

Property rights: w/ prob. τ , lender
cannot foreclose assets in case of default

If producer has capital, then he solves √ max A (1 + ∆x) e

− e − ρx

e ,x A (1+∆)

which yields (assuming < 1 for

2

interior solution)

2

(A(1 + ∆x))

∗

e =

4 Assume x = 1 is profitable under

1st-best

2

2

(A(1 + ∆)) A − ρ >

4

4 Analysis: 2nd-best

Consider a debt contract (r , c) •

r : interest payment

c: collateral
Under this contract, borrower solves •

√ √ max e e )c {A(1 + ∆) − r} − (1 − − e

e

which yields

2

[A(1 + ∆) − (r − c)]

∗∗

e = Lender’s problem

√ √ max r e + c(1 e )) − − ρ

r ,c

subject to

∗∗

Incentive Compatibility (IC): e = e

Participation Constraint (PC):

_{2<√ √}

A

e e )c {A(1+∆)−r}−(1− −e >

4 Limited Liability (LL): c

≤ (1 − τ)w

_,

2

[A(1 + ∆) − (r − c)] max (r

− c)

r ,c

4

c

− ρ s.t. c ≤ (1 − τ)w which yields optimal loan contract A (1 + ∆)

∗

r = + (1 − τ)w

2

∗

∗ ∗

Under (r , c ), borrower’s effort is

2

2

[A(1 + ∆)] [A(1 + ∆)]

∗∗ ∗

e = < e =

16

4

∗∗

Notice τ does not affect e in this • case But do borrowers accept this loan • contract?

⇒ Now check if PC satisfied

∗ ∗

Borrower’s payoff under (r , c ):

2

[A(1 + ∆)] − w(1 − τ)

16 ₂ A which must be as large as ₂ ₂

4 (1+∆) A

[ ⇒ w(1 − τ) ≤ ω ≡ − 1]

4

4 Intuition in case of w (1

− τ) ≤ ω

PC not binding.

Cost of lowering r for borrowers w/
lower (1

− τ)w: outweighed by benefit of keeping borrower’s incentive to exert effort cf. As long as lender’s profit remains non-negative

⇒ Credit constraint for very low w (1 − τ) If w (1

− τ) > ω

∗

As w (1 must be lowered − τ) ↑, r

to satisfy PC, which yields

∗

r = A(1 + ∆) + w(1 _, − τ)

2 A

w(1 − 2 − τ)

₂

4 A

∗∗

with e = + w(1 − τ)

4

∗∗

Now τ affects e • When 1st-best achievable?

∗

r = c = (1 − τ)w will achieve

1st-best effort e This will be the case if •

∗

r ≤ (1 − τ)w or

2

w (1 [(1 + ∆) − τ) ≥ − 1] ≡ ω

4 Once 1st-best achieved, τ does not • ₂

(A(1+∆)) ∗∗ ∗

affect e = e =

4 Impact of τ ↑

1. If (1

− τ)w < ω, e

∗∗ not affected.

Borrower’s share of total surplus ↑

2. If (1 − τ)w ∈ [ω, ω], e

∗∗

↓. Marginal effect: larger

3. If (1 − τ)w > ω, 1st-best achieved irrespective of τ Impact of τ _ ↑

if (1 − τ)w < ω

∗∗ 

∂ e =

−w < 0 if (1 − τ)w ∈ [ω, ω] ∂τ _ if (1

− τ)w > ω ⇒ Impact of property rights: heterogenous across w

Average effect of secure property

rights will underestimate the impact

For countries with

(1) only very poor, (2) only very rich, (3) extremely unequal

property rights have little impact on aggregate investment If (1

total surplus

− τ)w < ω, borrower’s share of

↑ ⇒ Political institutions where poor borrowers have power Galiani-Schargrodsky (2005)

Evidence

Exploit variation in actual

implementation of the govt program to transfer land titles to urban squatters in Buenos Aires

Only some original landowners gave up land
Which has nothing to do w/
squatter/parcel characteristics
No impact on access to credit
By law, squatters cannot transfer

land titling program as Field (2007) Observe whether loan applicants
required to provide collateral (C i )
y i = αT i + βC i + γT i i + ε i

× C Approval rates on public sector • loans

↑ (ˆγ > 0) But no impact on approval rates on • Wang (2008) China after 1994: state employees

can buy their rented houses from the state at subsidized prices DID estimation w/ control group • being state employees living in private houses or private sector employees After reform, self-employment rate
doubles (2% to 4%)

1-5 Other evidence: Goldstein-Udry (2008)

Villages in southern Ghana • Fallowing: important investment in • land Land rights determined by • paramount chief Fallowing

ie. Prob. of expropriation increases w/ e

₁

⇒ Prob. of losing land ↑ Findings

Fallowing: longer for individuals

who hold powerful positions in local political hierarchy

conditional on household FE & plot

characteristics

Same individual fallows longer for • plots obtained via local political process

3 sources of insecure property rights Predatory states

Govt expropriates assets
Anarchic states
Govt cannot prevent private
expropriation

Ineffective states

Govt does not invest in legal
institutions for secure property rights

Theoretical frameworks for anarchic

states: will be covered in my lecture on conflict Ineffective states: take Political
Economics III or read Besley-Persson (2009)

2-1 Commitment problem

• In Model 1 above, govt commits to τ
• After producers choose e, however,

govt has incentive to set τ = 1

If govt cannot commit, producers

choose e = 0 by anticipating this

This is Pareto inferior.
Let producer choose e to maximize output
Then divide the surplus between govt & producer

3 ways to achieve τ < 1 w/o commitment

Reputation
Exit
Voice
See Besley-Ghatak (2009a) for 2 more ways: secrecy & public ownership

2-2 Reputation

If govt in power for a long time, • repeated interactions between govt & producers possible Producers can punish govt taking

τ = 1 by setting e = 0 from next period on

₂

(1−τ)A ∗

Let y (τ ) = = A e •

2

(expected output given τ ) and β

Govt’s deviation payoff: y (τ )

Govt’s equilibrium payoff:

τ y (τ )/(1

− β) Credible τ satisfies

τ y (τ )/(1

− β) ≥ y(τ) or τ ≥ 1 − β Govt solves •

2

(1 − τ)A

τ max τ s.t. τ ≥ 1 − β

2

∗

which yields τ = 1/2 if β ≥ 1/2 &

This mechanism to restrain

predatory state requires a stable government

cf. Olson (1993) "stationary bandit"

Empirically, however, long-lasting • govts appear be predatory

e.g. Mobutu in ex-Zaire (in power 1965-1997)

2-3 Exit

Suppose producers can hide

fraction µ

∈ (0, 1) of output from govt ⇒ τ ≤ 1 − µ in non-commitment case

This also reduces govt’s deviation • payoff in the reputation mechanism ⇒ Credible τ satisfies

τ y (τ )/(1 − β) ≥ (1 − µ)y(τ) ⇐⇒ τ ≥ (1 − µ)(1 − β)

2-4 Voice

Democracy supposed to be key for • secure property rights

North & Weingast (1989): the

Glorious Revolution in England in 1688 ⇒ Checks & balances against the King by Parliament ⇒ Secure property rights Acemoglu-Johnson-Robinson (2001):
Settler mortality ⇒ Checks & balances against executive ⇒ Secure property rights
Suppose political institutions (e.g.

elections) make govt put some positive weight on producer’s utility (λ

∈ (0, 1)) max

λ

τ

τ (1

− τ)A

2

2

[(1 − τ)A]

2

4

See Persson-Tabellini (2000) for how various political institutions result in
the govt’s objective function as a

1 − λ

∗

τ =

2 − λ

This decreases with λ • But λ < 1 suggests ex post govt •

= 1 has incentive to set τ Same logic as in the reputation • mechanism implies the lower bound of credible τ is

β

∗

τ ˆ = 1 −

1 − λ + βλ/2

This also decreases with λ • So λ

If λ = 1 (perfect democracy), τ = 0. •

↑ ⇒ τ ↓ for any given β Implication: A Theory of Democratization

This logic implies govt has an

incentive to increase λ when β is high so it cannot commit to τ = 1/2

Paltseva (2006) proposes a variant of

democratization theory of this type In her case, not high β but capital
accumulation (so marginal return to investment ↓) creates an incentive

2-5 Expropriation vs Taxation

Taxation: τ clearly specified ex ante

Why govt can commit then?
Expropriation: govt confiscates
assets to produce on its own

⇒ Lower bound of credible τ: higher

Empirically, taxation positively corr. • w/ protection against expropriation (Figure 3 of Besley-Ghatak 2009a)

References for the lecture on property rights _Economy

Acemoglu, Daron, and Simon Johnson. 2005. “Unbundling Institutions.” Journal of Political

Acemoglu, Daron, Simon Johnson, and James A. Robinson. 2001. “The Colonial Origins of

American Economic Review

Land Titling . Universidad Torcuato Di Tella. Available at: http://ideas.repec.org/p/udt/wpbsdt/ proprightspoor.html Wang, Shing-Yi. 2008. “Credit Constraints, Job Mobility and Entrepreneurship: Evidence ₃₀

from a Property Reform in China.” NYU Development Research Institute Working Paper No.

. Available at: http://homepages.nyu.edu/~syw3/entrep.pdf . !