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

Transcription

1 World Bank Annual Conference on Land and Poverty, April 19-20, 2011 Securing Rural Land Rights: Experimental Evidence from the Plans Fonciers Ruraux in Benin Harris Selod (team leader) Klaus Deininger Markus Goldstein Kenneth Houngbedji Déo-Gracias Houndolo Florence Kondylis Michael O Sullivan This work has been undertaken in collaboration with MCC & MCA Benin. 1 Funding from AADAPT/DIME, BPRP/LPRP, BNPP and GAP is also gratefully acknowledged.

2 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) 2

3 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 3

4 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 4

5 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 5

6 Example of a PFR 6

7 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? 7

8 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) 8

9 PFR locations 9

10 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 villages EMICoV panel wave Treatment villages Control villages TOTAL 2006 & only Total Total with withincommune matched pairs

11 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 11

12 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 landholdings with agricultural parcels. 12

13 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) 13

14 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 14

15 Balance test: Community, EMICoV 2010 Variables Sample size T-test Treated Primary school Local market microfinance Power supply Water network Water pump Paved road Laterite road Land line Cell phone OLS Treated (1)-(0) Significance Significance * p < 0:10, ** p < 0:05, *** p <

16 Balance test: Individuals, EMICoV 2010 Variables Sample size T-test Treated Age 23, Ethnicity: Adja 23, Ethnicity: Bariba 23, *** Ethnicity: Fon 23, *** Ethnicity: Peulh 23, *** Ethnicity: Yoruba 23, *** Can write French 23, *** Illiterate 23, *** Relig. indig 23, ** Christian 23, *** Muslim 23, Migrant 23, Primary education 23, Poverty 23, *** ** OLS Treated (1)-(0) Significance Significance * p < 0:10, ** p < 0:05, *** p <

17 Balance test: Plots, EMICoV 2010 T-test OLS Variables Sample size Treated Treated (1)-(0) Significance Significance Land-use agreement 5, ** Land title 5, Land lease 5, Land permit 5, ** Land-sales agreement 5, ** Can rent out 5, * Can sell 5, Can mortgage 5, ** Can bequeath 5, * Land bought 5, ** Land inherited 5, ** Land under conflict 5, * p < 0:10, ** p < 0:05, *** p <

18 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? 18

19 Annex 1: Land right types 19

20 Annex 2: Example of a socio-legal inquiry card 20

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22 Annex 3: Example of a CFR (full document) 22

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28 Annex 4: Rental contract template 28

29 Annex 5: Balance test: Individuals, EMICoV 2006 Variables Sample size T-test Treated female age * eth_adja eth_bariba *** eth_fon *** eth_peulh *** eth_yoruba *** relig_indig relig_christ relig_musli Migrant OLS Treated (1)-(0) Significance Significance edu_primar edu_middle edu_high edu_unive * * 29

30 Balance test: Plots, EMICoV 2006 Variables Sample size T-test Treated lndtitle duraccess lndbought lndinheri *** lndshcropin *** lndrentin ** lndrentout lndfallow ** lndshcropout * lndconfl conflsetl customsetl OLS Treated (1)-(0) Significance Significance 30