Land Conflict and Agricultural Land Conflict and Agricultural Tenancy: The Impact on Land Use Tenancy: The Impact on Land Use

and Farm Sizeand Farm Size

  Lee J. Alston

University of ColoradoNBER

Bernardo MuellerUniversity of Brasilia

• In Brazil rentals account for about 11% of the farms

•For U.S. and OECD countries it’s close to 50%

•Missing market- millions of landless peasants and unused or under-utilized land•Tenancy associated with career

mobility•Too few rentals implies an inefficiency•Landless move to the frontier and

deforest

Figure 1 – Evolution of Tenancy over time in Brazil

Source: IBGE (2007). Data for 2006 from the 2006 Agricultural Census.

Insecure Property Rights, i.e., the threat of expropriation - fewer land rentals

de janvry and Sadoulet 1989• Land reforms of the 1960s and 1970s gave

incentives for landowners to modernize and expel tenants.

Conning and Robinson (2007)• “…the anticipation of future property rights

challenges by tenants lead landlords to defensively suppress tenancy as a costly mechanism to protect property rights.”

Land Statute, 1964 “… expropriation will be applied to: ...

areas with high incidence of renters, sharecroppers and squatters."

Rural Worker Statute, 1963

Land Reform- Land Conflict leads to expropriations (Alston, Libecap, Mueller, 1999, 2000, 2009)

Rented land may attract invasion Need instruments for land conflict Landless peasants and rural workers

became increasingly organized in 1970-1980s:

• Catholic Church –organized landless peasants from the early 70s until the mid-80s.

• Instrument: Priests per rural pop 1966

Security of Property rights affect contract choice (1996 Census data) –more conflict associated with fewer fixed rent and sharecrop contracts. - one std dev in conflict: decreases fixed rent from 4% to 3% and sharecrop from 2.5% to 1.25%

Rented farms “too small” and sharecropped farms “too large”- generating inefficiencies in agriculture .

• Net result: farm size increases

Land Conflict and Tenancy Land Conflict and Tenancy

Our results: land conflict pushes land use into marginal uses and lowers investment

Increase from 0 to 4.4 conflicts1000 farms: - natural pasture- 20% to 3% (target for invasions) - temporary crops- 18% to 15% (highly productive) - planted pasture – 26% to 37% (low productivity)

Total country wide impact in hectares= to the size of small countries, e.g. Greece, Honduras plus others

Land Conflict and Land Use Land Conflict and Land Use

Land conflict is the result of insecure property rights generated by government policies, e.g. land reform

Land Conflict Reduces Tenancy: • 1) hurts the landless;• 2) creates inefficiencies; and • 3) causes deforestation through migration to

the frontier.

Conflicts skew land uses to low productivity uses

Coase-like bargaining?

Urban constituents favor redistribution of land, affects credible commitment of Government

Belief in social inclusion (for now) prevents fixing the “missing market.”

Coase-like bargaining?

Brazilian Belief in Social Inclusion sustains misallocation

Urban constituents favor redistribution of land, affects credible commitment of Government

Land Conflicts and Land Reform

0

100

200

300

400

500

600

700

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Occ

up

atio

ns

0

20

40

60

80

100

120

140

160

Fam

ilies

Set

tled

(10

00)

Occupations Families Settled

Source: Ministério do Desenvovlvimento Agrário (2004: 20), MDA/INCRA Balanço de 2007 (2008).Comissão Pastoral da Terra (2004:13). Note: Data for number of families settled from 1988 to 1994 isthe average for each government; Sarney (1988-89), Collor (1990-91), Franco (1992-94).

In the 1970s the Catholic Church in Brazil made a ‘preferential option for the poor.’

It became “probably the most progressive Church in Latin America, if not the world.” (Bruneau, 1987: 271)

Pastoral Land Commission (CPT).

“The CPT (Pastoral Land Commission) was the practical application of the Theology of Liberation, which was an important contribution to the landless peasants’ struggle from the ideological point of view. The priests, pastoral agents and pastors discussed with the peasants the need for them to organize themselves. The Church stopped doing messianic work and saying to the peasant: ‘Wait and you will go to heaven.’ Now they started saying ‘You have to get organized and fight to solve your problems here on earth’”J.P. Stedile, main leader of the MST on the Church’s rolein the foundation of the MST in the early 1980s.

Land Conflicts: data collected by the Catholic Land Pastoral Commission.

Land Conflicts per farm by county 1986-1995 – aggregated to MCA.

Conflicts in 645 of the 3615 MCAs

Tobit estimation

Exclusion RestrictionExclusion Restriction

1970 1975 1980 1985 1990 1995

Pueblaconference

Conflictdata

Priestdata

Contractdata

Redemo-cratization

1966

Conservative shift of the Church.

Rise of the MST.Evangelical movement.

Medellinconference

Brazilian Bishopsconference

Directactive Church

participa-tion in

agrarian issues

Exclusion RestrictionsExclusion Restrictions

“In more recent years the Church has become increasingly confused with respect to support for societal transformation. Not only has the upper hierarchy become more fractious, a tendency toward conservatism has also become apparent. The Church as an institution has returned to previous modes of political influence and appears to be abandoning its support for grassroots movements in favor of direct pressure on political policy makers”. (pg. 148)

Hewitt, Warren E. 1990. “Religion and Consolidation of Democracy in Brazil: The Role of the Comunidades Eclesiais de Base (CEBs),” Sociological Analysis, 50:2, 139-152.

Dep. Variable: Priest per 1000 rural pop in 1985

I II III IV V Dep. Var: Opposition party†

VIOpp. 1982

VIIOpp. 1996

Priest / 1000 rural pop 1966 1.09***

(11.96)1.09***

(11.48)Oppo. Party (1982) 0.010*

(1.92)

Fixed rent % (1970) 23.763**

(2.42)3.109(0.40)

Fixed rent % 0.144***

(2.87)-0.012(-0.89)

Sharecrop % (1970) -14.756*

(-1.67)-10.553(-1.15)

Sharecrop % 0.213***

(3.30)0.053(1.63)

Occupied % (1970) -24.222***

(-5.14)-2.178(-0.78)

Occupied % -0.045(-1.28)

0.019(1.62)

Population growth 1970-80 3.151(1.04)

-0.012(-0.01)

Pop. growth 0.040***

(3.51)-0.001(-0.90)

GDP growth 1970-80 0.109(0.61)

0.063(0.42)

GDP growth -0.0003(-0.31)

-0.001***

(-2.76)

Income (1970) -0.0001**

(-2.29)-0.00001(-1.41)

Income -2.2e-7***

(-4.06)0.0000001**

*

(3.47)Schooling (1970) 12.017***

(9.66)1.453(1.53)

Schooling 0.082***

(12.26)0.014***

(8.46)

Distance to state capital -0.048***

(-7.52)-0.008**

(-2.41)Dist. to state capital -0.0002***

(-6.15)0.00004***

(3.95)

Frontier -1.411***

(-5.72)0.088(0.90)

Frontier 0.002*

(1.72)0.0004(1.24)

Latitude -1.036***

(-11.41)0.009(0.03)

Latitude -0.003(-1.11)

0.002***

(2.93)

Longitude 0.311***

(2.92)0.327(1.55)

Longitude 0.012***

(4.52)-0.004***

(-4.31)

Constant 0.805(0.75)

17.234***

(18.74)-0.165(-0.13)

-0.677(-0.17)

-23.517*

(-1.88)Constant -0.709***

(3.45)0.318***

(3.75)

Number of observations Total: 3631 Total: 3631 Total: 3631 Total: 3631 Total: 3631 Number observations Total: 3656 Total: 3656

State dummies (27 states) No No No No Yes State dummies (27 states)

Yes Yes

R2 adjusted 0.64 0.005 0.05 0.07 0.64 R2 adjusted 0.35 0.10

F(k, n-k) Prob>F

142.940.0000

13.500.0000

30.440.0000

37.130.0000

74.790.0000

F(k, n-k) Prob>F

84.070.0000

9.940.0000

Determinants of Priest Allocation and Opposition Determinants of Priest Allocation and Opposition Party StrengthParty Strength

Explanatory Variables:

1. Number of Priests /rural population

2. Frontierness – number of times a MCA subdivided

3. Priests interacted with Frontierness

4. Opposition Parties: MDB and PT % of seats

5. Distance to state capital

6. Latitude and Longitude

7. Population Density: more demand for land

8. Ag/GDP: More valuable land better defended

9. Land concentration: size of farms

10. Crop variables

11. State dummies.

Data:Land Conflict: (Pastoral Land Commission)- rural threats, murders, murder attempts and occupations by countyAg Variables: Agricultural Census; Priests: Catholic Hierarchy;.

11stst Stage Specification – Land Conflict Stage Specification – Land Conflict

Determinants of Rural Conflict – First Stage EquationDeterminants of Rural Conflict – First Stage EquationDep. Var.: Violence 1985-1996

Priests 1966No Opposition Parties

Priests 1966Opposition Parties

Priests per rural population -0.629***

(-10.47)-0.614***

(-10.26)Frontier 0.233***

(5.01)0.232***

(5.00)Interaction: Priest x Frontier 0.287***

(8.21)0.285***

(8.13)Political opposition 1982 (% seats in state assembly – MDB

6.680***

(3.52)Political opposition 1996 (% seats in state assembly – PT

15.803**

(2.30)Agricultural GDP growth 1985-1995. 2.683***

(4.68)2.810***

(4.91)Distance to state capital 0.004

(1.39)0.006**

(2.02)Latitude 0.195

(0.84)0.250(1.08)

Longitude -0.359(-1.35)

-0.423*

(-1.59)Cattle per hectare1995 -0.656

(-0.67)-0.668(-0.66)

Tractors per hectare1995 -1240.63***

(-8.57)-1241.46***

(-8.60)Rural/Urban Population (1995) -1.650***

(-4.28)-1.394***

(-3.59)Population growth 1985-1995 1.236***

(2.65)1.265***

(2.71)Constant 19.994

(1.10)20.930(1.15)

Number of observations Total: 3616Censored at 0: 2967Uncensored: 648

Total: 3616Censored at 0: 2967Uncensored: 648

State Dummies (27 states) Yes Yes

Pseudo R2 0.14 0.152(55)Prob>2

1131.910.0000

1150.370.0000

Tobit Estimation. t-stats in parentheses. Statistical significance: 1% ***. 5% **, 10% *. Weighted by the number of county subdivision from 1970-2000. Other controls not shown to save space.

Interaction of Priests and Frontier: Effect of Priests on ConflictsInteraction of Priests and Frontier: Effect of Priests on Conflicts ..

05

1015

20E

ffect

of P

ries

t per

hec

tare

pe

r C

atho

lic o

n V

iole

nce

0 10 20 30 40 50Frontier

95% confidence interval

Effect of Priest per hectare per Catholic on Violence

Determinants of Contract ChoiceDeterminants of Contract Choice

(Continues)

Fixed Rent (%) Sharecropper (%) Owner (%) Occupant (%)

Conflict per 1000 farms -0.008***

(-3.60)-0.006***

(-4.21)0.010***

(3.39)0.004**

(2.50)

Cotton, % of total farm area 0.428***

(4.21)0.181***

(2.61)-0.689***

(-4.99)0.080(1.05)

Rice, % of total farm area 0.275***

(5.97)0.227***

(7.19)-0.512***

(-8.18)0.011(0.30)

Coffee, % of total farm area -0.146***

(-4.14)0.042*

(1.73)0.124***

(2.60)-0.021(-0.78)

Cane, % of total farm area 0.187***

(17.77)0.068***

(9.47)-0.225***

(-15.73)-0.030***

(-3.83)Beans, % of total farm area -0.050

(-1.40)0.089***

(3.61)-0.167***

(-3.42)0.129***

(4.76)

Manioc, % of total farm area 0.062(1.21)

0.097***

(2.78)-0.695***

(-9.98)0.536***

(13.94)Corn, % of total farm area -0.042*

(-1.70)0.021(1.23)

0.019(0.57)

0.002(0.11)

Soy Beans, % total farm area 0.218***

(13.21)0.032***

(2.82)-0.219***

(-9.73)-0.032**

(-2.55)Frontier -0.0004**

(-2.28)0.00003(0.21)

0.0009***

(4.05)-0.0005***

(-4.05)

GDP growth 1985-1995 0.006**

(2.47)0.004**

(2.40)-0.013***

(-3.87)0.003**

(1.52)Latitude -0.004***

(-4.60)-0.0001(-0.15)

0.005***

(4.64)-0.001**

(-2.15)

Longitude -0.001(-0.93)

-0.0007(-1.01)

-0.003**

(-2.01)0.005***

(5.79)Distance to state capital -0.000002

(-0.19)0.00002***

(2.66)0.00001(0.58)

-0.00003***

(3.23)Transport cost to São Paulo 0.000003

(0.73)-0.0000002

(-0.10)-0.00001**

(-2.52)0.00001***

(3.68)Number of train stations 0.002***

(3.57)-0.0001(-0.21)

-0.003***

(-2.85)0.0003(0.60)

Determinants of Contract ChoiceDeterminants of Contract Choice(Continuation)

Fixed Rent (%) Sharecropper (%)

Owner (%) Occupant (%)

Population density 1995 0.00002**

(2.06)0.000001

(1.47)-0.00002**

(-1.96)-0.000003

(-0.52)Rural/Urban Population 1995 -0.002**

(-2.32)-0.0008(-1.56)

-0.00005(-0.05)

0.003***

(4.59)Population growth 1985-1996 0.003

(1.12)0.002(1.36)

-0.002(-0.62)

-0.003(-1.61)

Tractor /hectare growth 1985-1995

-0.243(-1.06)

0.512***

(3.26)-0.775**

(-2.48)0.507***

(2.94)Cattle per hectare1995 -0.002

(-0.65)0.0002(0.11)

0.007**

(2.06)-0.005***

(-2.96)Constant 0.077

(1.09)0.075(1.54)

1.100***

(11.42)-0.248***

(-4.68)Number of observations Total: 3616 Total: 3616 Total: 3616 Total: 3616State dummies (27 states) Yes Yes Yes YesPseudo R2 0.17 0.05 0.18 0.222(44) Prob>2

1757.510.0000

720.980.0000

1754.120.0000

1649.150.0000

Hausman-Wu Test

H0: Conflicts are exogenous.

Χ2(1)=25.06p-value= 0.0000

Χ2(1)=30.66p-value=0.0000

Χ2(1)=21.18p-value=0.0000

Χ2(1)=5.39p-value=0.0202

The impact of Violence on Tenancy and Sharecropping - Brazil

Determinants of Land UseDeterminants of Land Use

Natural Forest %

Planted Forest %

Perm. Crops %

Temp. Crops %

Nat. Pasture %

Plant. Pasture %

Fallow % Unused %

Conflict per 1000 farms 0.006**

(3.17)0.006***

(6.21)0.017***

(8.97)-0.007***

(-5.00)-0.038***

(-9.60)0.063***

(8.20)0.00003(0.06)

-0.008***

(-7.70)Cotton, % of total farm area -0.731***

(-4.65)-0.098(-1.19)

-0.097(-0.60)

0.815***

(6.59)-0.511(-1.45)

0.736***

(2.67)-0.015(-0.35)

-0.099(-1.03)

Rice, % of total farm area -0.356***

(-4.99)-0.063*

(-1.70)-0.111(-1.51)

0.531***

(9.48)-0.071(-0.45)

-0.099(-0.79)

0.155***

(7.75)0.013(0.31)

Coffee, % of total farm area -0.223***

(-4.10)-0.116***

(-4.08)1.056***

(18.79)-0.213***

(-4.97)-0.135(-1.11)

-0.319***

(-3.34)-0.018(-1.16)

-0.032(-0.96)

Cane, % of total farm area -0.157***

(-9.95)-0.053***

(-6.36)-0.034**

(-2.12)0.647***

(52.18)-0.162***

(-4.59)-0.244***

(-8.81)0.017***

(3.81)-0.014(-1.45)

Beans, % of total farm area -0.097*

(-1.83)0.047*

(1.68)-0.077(-1.41)

0.623***

(14.96)-0.123(-1.04)

-0.264***

(-2.84)0.021(1.39)

-0.129***

(-4.00)Manioc, % of total farm area -0.862***

(-10.78)-0.029(-0.70)

0.428***

(5.23)0.908***

(14.47)-0.573***

(-3.22)0.050(0.36)

0.024(1.06)

0.055(1.16)

Corn, % of total farm area -0.195***

(-5.07)-0.052***

(-2.61)0.023(0.60)

0.499***

(16.53)-0.299***

(-3.48)-0.096(-1.42)

0.088***

(8.19)0.031(1.32)

Soy Beans, % total farm area -0.075***

(-2.92)-0.039***

(-2.89)-0.092***

(-3.47)0.782***

(38.69)-0.081(-1.41)

-0.404***

(-8.96)-0.059***

(-8.17)-0.031**

(-2.02)Constant 0.532***

(5.02)1.096*

(1.74)-0.140(-1.29)

-0.155*

(1.87)1.681***

(7.11)-1.273***

(-6.88)0.00004(0.00)

0.215***

(3.39)Number of observations Total: 3616 Total: 3616 Total: 3616 Total: 3616 Total: 3616 Total: 3616 Total: 3616 Total: 3616State dummies (27 states) Yes Yes Yes Yes Yes Yes Yes YesR2 0.37 0.07 0.11 0.74 0.12 0.29 0.38 0.232(44) Prob>2

4904.520.0000

829.240.0000

993.450.0000

14975.280.0000

1225.010.0000

2787.730.0000

2421.120.0000

2340.630.0000

Estimated by Three Stage Least Squares. t-stats in parentheses. Statistical signif.: 1% ***. 5% **, 10% *. The coefficients for all eight equations are constrained to add up to 0 for every variable. A Hausman-Wu endogeneity test rejects exogeneity of conflicts in all of the equations at 1% (except Natural Forest at 5%) except Fallow.