Securing Rural Land Rights: Experimental Evidence from the Plans Fonciers Ruraux in Benin

Harris Selod (team leader)Klaus Deininger

Markus GoldsteinKenneth Houngbedji

Déo-Gracias HoundoloFlorence KondylisMichael O’Sullivan

World Bank Annual Conference on Land and Poverty, April 19-20, 2011

This work has been undertaken in collaboration with MCC & MCA Benin.Funding from AADAPT/DIME, BPRP/LPRP, BNPP and GAP is also gratefully acknowledged.

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The PFR approach

Policy to consolidate land rights in rural areas Introduces written documentation of rights

(Certificat Foncier Rural - CFR) Stated objectives: improve tenure security of

landholdings and stimulate agricultural investment

Originality: recognizes existing customary land rights

Benin currently has two PFR programs Large one under MCC/MCA (implemented by GTZ-IS) Smaller one in the North (ProcGRN)

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The Benin context

Low investment in land

Tenure insecurity

Customary law typically holds sway

Thin rural credit markets

Emerging land markets

Conflicts over land– Farmers vs. pastoralists, farmers vs. farmers

– Inheritance

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The Benin context (cont.)

Unequal access to land

– Women often cannot inherit land and rely on husbands for access to land

– Evidence from other African countries suggests that insecure tenure limits women’s investment (Udry 1996), productivity (Goldstein & Udry 2008) and land market participation (Holden et al 2011)

– Marginalized groups (migrants and pastoralists) also face challenges

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The PFR process in Benin

Participatory process to establish written documentation of land rights with legal recognition

Main steps in each village:1. Information campaign

2. Preparation of village profiles

3. Socio-legal inquiry

4. Parcel surveying and mapping of land use plan

5. Temporary recording of rights and rights holders

6. Public review of village land use plan (60 days)

7. CFR delivery and facilitation of formal, written records of secondary land rights

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Example of a PFR

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Impact evaluation research topics

Effect on tenure security (reduction or reactivation of “conflits dormants”?)

Changes in land market participation & prices?

Effect on investments in land, production & yields?

Labor effects? (incl. off –farm activities)

Possible differential effects on men and women?

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Measuring program impact

300 village PFRs in 40 of Benin’s 77 communes Random selection of villages that submit a

proposal and meet eligibility criteria agricultural production, poverty but economic

opportunities, presence of land conflict, willingness to promote women’s access to land, rural

Villages are selected through commune-level lotteries, establishing clearly defined PFR “treatment” villages and non-PFR “control” villages

Phased-in implementation (ongoing)

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PFR locations

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The data: EMICoV

Nationally representative panel household and community survey (EMICoV 2006 and 2010) with a large intersection with PFR villages

EMICoV 2010 extended to more treatment and control villagesEMICoV panel wave Treatment

villagesControl villages TOTAL

2006 & 2010 98 71 169

2010 only 103 35 138

Total 201 106 307Total with within-

commune matched pairs 194 99 293 10

The data: WB survey

A 3,500 HH survey designed by the World Bank and linked to EMICoV (data collection just finished) + community survey

Justification

Pre-program data

Longitudinal data (effects take time)

“Baseline” for some villages (due to phased-in implementation)

Very detailed plot-level info on land and agriculture

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The data: WB survey (cont.)

Preliminary plot-level data from the World Bank 2011 household survey. Plots will be linked with administrative data to compare PFR land-holdings with agricultural parcels.

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Impact evaluation challenges

Several agro-climatic zones Complex and heterogeneous tenure situations

(Lavigne-Delville, 2010) Distinction between agricultural plots and land

parcels (and plot definitions across surveys) GPS measurements of plots (tracks and

waypoints) and linking to program data Identification of households (EMICoV sampled on

enumeration areas but program implemented at village level)

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Preliminary conclusions

EMICoV 2006 data suggest a pre-program balance across treatments and controls

EMICoV 2010 data reveal:

some observable differences between treatments and controls in simple mean comparisons

but 2010 differences tend to disappear when commune and EMICoV 2006 controls are included

Justifies follow-up survey waves

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Balance test:Community, EMICoV 2010

Variables

T-test OLS

Sample size

Treated (1)-(0) Signifi-cance

Treated Signifi-cance

Primaryschool 271 0.8644 0.013 -0.003Local market 271 0.2655 0.042 0.030microfinance 271 0.1017 0.038 0.040

Power supply 267 0.1314 -0.075 -0.044

Water network 271 0.0904 -0.005 0.001

Water pump 271 0.7627 0.039 0.026

Paved road 269 0.1143 -0.056 -0.033

Laterite road 269 0.7600 0.037 0.008

Land line 271 0.0226 -0.009 -0.004

Cell phone 271 0.9322 0.007 -0.014

* p < 0:10, ** p < 0:05, *** p < 0.001

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Balance test: Individuals, EMICoV 2010

Variables

T-test OLS

Sample size

Treated (1)-(0) Signifi-cance

Treated Signifi-cance

Age 23,853 20.7882 0.117 0.106

Ethnicity: Adja 23,855 0.1745 0.002 -0.030

Ethnicity: Bariba 23,855 0.1804 0.069*** 0.042

Ethnicity: Fon 23,855 0.3876 -0.067*** -0.012

Ethnicity: Peulh 23,855 0.0891 -0.025*** -0.040

Ethnicity: Yoruba 23,855 0.1351 0.021*** 0.034

Can write French 23,855 0.2763 -0.025*** -0.009

Illiterate 23,855 0.4740 0.024*** 0.014

Relig. indig 23,855 0.1823 0.012** 0.011

Christian 23,855 0.1682 -0.025*** -0.007

Muslim 23,855 0.1845 0.003 -0.013

Migrant 23,855 0.0822 -0.000 -0.000

Primary education 23,855 0.2653 -0.009 0.006

Poverty 23,855 0.4834 -0.069*** -0.108**

* p < 0:10, ** p < 0:05, *** p < 0.00116

Balance test: Plots, EMICoV 2010

Variables

T-test OLS

Sample size

Treated (1)-(0) Signifi-cance

Treated Signifi-cance

Land-use agreement 5,485 0.3977 -0.043 ** -0.059

Land title 5,485 0.0046 0.001 0.001

Land lease 5,485 0.0107 -0.003 0.005

Land permit 5,485 0.0008 -0.004 ** -0.005

Land-sales agreement 5,485 0.1108 0.024 ** 0.020

Can rent out 5,485 0.5181 0.027 * 0.036

Can sell 5,485 0.4426 0.016 0.032

Can mortgage 5,485 0.4354 0.034 ** 0.047

Can bequeath 5,485 0.7815 0.021 * 0.011

Land bought 5,485 0.1209 0.028 ** 0.021

Land inherited 5,485 0.6723 -0.040 ** -0.047

Land under conflict 5,485 0.0563 -0.001 -0.006

* p < 0:10, ** p < 0:05, *** p < 0.001

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Going forward

Forthcoming data analysis (plots, HH and communities)

Analysis can provide policy lessons for further scale-up (dialogue with authorities)

Need for further wave(s) of data collection to track the PFR effects over time (2012 or 2013 envisioned)

Possibility for experimentation of program variants?

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Annex 1: Land right types

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Annex 2:Example of a socio-legal inquiry card

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Annex 3: Example of a CFR(full document)

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Annex 4: Rental contract template

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Annex 5:Balance test: Individuals, EMICoV 2006

Variables

T-test OLS

Sample size

Treated (1)-(0) Signifi-cance

Treated Signifi-cance

female 12745 0.5129 0.001 0.008

age 12742 20.5177 0.554* 0.485

eth_Adja 12252 0.1841 0.001 -0.026

eth_Bariba 12745 0.1035 0.019*** 0.035

eth_Fon 12745 0.4725 -0.059*** -0.027

eth_Peulh 12745 0.0729 -0.018*** -0.024

eth_Yoruba 12745 0.1338 0.040*** 0.031

relig_Indig 12745 0.2603 -0.003 0.011

relig_Christ 12745 0.2719 0.013 0.014

relig_Musli 12745 0.1724 0.003 -0.007

Migrant 12745 0.1585 -0.010 -0.014

edu_primar 12745 0.2571 -0.002 -0.001

edu_middle 12745 0.0505 0.003 0.007

edu_high 12745 0.0086 0.001 0.002

edu_unive 12745 0.0004 -0.001* -0.001* 29

Balance test: Plots, EMICoV 2006

Variables

T-test OLS

Sample size

Treated (1)-(0) Signifi-cance

Treated Signifi-cance

lndtitle 3900 0.0103 -0.001 -0.003duraccess 3860 13.5358 -0.636 -1.046

lndbought 3900 0.1414 0.014 0.020lndinheri 3900 0.6152 0.062*** 0.048

lndshcropin 3900 0.0198 -0.024*** -0.017lndrentin 3900 0.0831 -0.019** -0.029

lndrentout 3900 0.0018 0.000 -0.001lndfallow 3900 0.0256 -0.014** -0.009lndshcropout 3900 0.0022 0.002* 0.003

lndconfl 3900 0.0162 0.002 0.003

conflsetl 3900 0.0157 0.005 0.005

customsetl 3900 0.0036 -0.002 -0.002

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