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Formalizing Rural Land Rights in West Africa: Early Evidence from a Randomized Impact Evaluation in Benin Markus Goldstein* Kenneth Houngbedji + Florence.

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Presentation on theme: "Formalizing Rural Land Rights in West Africa: Early Evidence from a Randomized Impact Evaluation in Benin Markus Goldstein* Kenneth Houngbedji + Florence."— Presentation transcript:

1 Formalizing Rural Land Rights in West Africa: Early Evidence from a Randomized Impact Evaluation in Benin Markus Goldstein* Kenneth Houngbedji + Florence Kondylis* Michael O’Sullivan* (presenter) Harris Selod* * The World Bank, + Paris School of Economics World Bank Land and Poverty Conference 2016 March 14-18, 2016

2  Tenure insecurity can lead to under-investment and low productivity (Goldstein & Udry, 2008)  Shift in policy response in Sub-Saharan Africa from individual titling toward “better integration of customary tenure with the formal legal system” (Udry 2012)  Need for rigorous evidence of impact at key stages of the formalization process to understand the mechanisms and inform policy  Land demarcation constitutes a key step in the process  Also need evidence on the gender differences in impact, given existing differences in customary tenure Motivation

3  The Plan Foncier Rural  A participatory process to document & formalize customary rights at the village level  Led by the Millennium Challenge Corporation/MCA-Benin, the program (which scaled up in 2009/10) aimed to improve tenure security & stimulate agricultural investment in 40 of Benin’s 77 communes (districts)  Two key PFR steps in each village:  Systematic land demarcation, with identification of rights-holders and planting of cornerstones within village boundaries  Land certificate issuance [had not taken place at survey date]  Impact estimates presented here capture the effect of demarcation (11 months after their completion, on average) prior to certification Benin’s Plans Fonciers Ruraux (PFR)

4 PFR intervention: Systematic demarcation

5 IE overview: Randomized lotteries to select PFR villages & measure impact

6  2006 household survey (EMICoV) to establish village-level balance prior to the intervention  2011 household survey (3,500 HHs) + community survey to estimate impact on:  Villages  Households  Parcels/landholdings  Farm plots  Individual spouses  Project administrative data to establish village lottery and treatment status IE overview: Data

7  A theoretical framework of cultivation and investment decisions (building on Besley 1995 and Besley and Ghatak 2010)  We focus on three decisions:  cultivation (i.e., cultivating land or leaving it fallow)  choice of crop mix (i.e., long-term and short-term crops)  relative investments across plots (i.e., investments on inside- and outside-village plots)  We discuss how these decisions are affected by PFR demarcation activities (modelled as an improvement in property rights within – but not outside the village) A model What does theory tell us? (I)

8  Following demarcation:  Households are likely to invest more in long-term crops (as “guarding labor” becomes more efficiently spent on long-term investments)  Women are more likely than men to switch to a long-term crop (their greater gain in tenure security frees up more labor for long-term crops)  Plots – particularly those controlled by individuals with lower initial property rights – are more likely to be left fallow (as there is less risk associated with leaving land fallow)  Labor may be shifted to plots outside the village for households with initially weaker property rights (as these plots become in greater relative need of “guard labor”) What does theory tell us? (II) Model predictions

9 What does theory tell us? (III)

10 What does theory tell us? (IV)

11 What does theory tell us? (V)

12  Following demarcation:  Households are likely to invest more in long-term crops (as “guarding labor” becomes more efficiently spent on long-term investments)  Women are more likely than men to switch to a long-term crop (their greater gain in tenure security frees up more labor for long-term crops)  Plots – particularly those controlled by individuals with lower initial property rights – are more likely to be left fallow (as there is less risk associated with leaving land fallow)  Labor may be shifted to plots outside the village for households with initially weaker property rights (as these plots become in greater relative need of “guard labor”) Model predictions

13 Results: Impact on crop choice

14  Following demarcation:  Households are likely to invest more in long-term crops (as “guarding labor” becomes more efficiently spent on long-term investments)  Women are more likely than men to switch to a long-term crop (their greater gain in tenure security frees up more labor for long-term crops)  Plots – particularly those controlled by individuals with lower initial property rights – are more likely to be left fallow (as there is less risk associated with leaving land fallow)  Labor may be shifted to plots outside the village for households with initially weaker property rights (as these plots become in greater relative need of “guard labor”) Model predictions

15 Results: Differences in impact on crop choice by gender

16  Following demarcation:  Households are likely to invest more in long-term crops (as “guarding labor” becomes more efficiently spent on long-term investments)  Women are more likely than men to switch to a long-term crop (their greater gain in tenure security frees up more labor for long-term crops)  Plots – particularly those controlled by individuals with lower initial property rights – are more likely to be left fallow (as there is less risk associated with leaving land fallow)  Labor may be shifted to plots outside the village for households with initially weaker property rights (as these plots become in greater relative need of “guard labor”) Model predictions

17 Results: Impact on fallowing Average impact Gender difference in impact

18  Following demarcation:  Households are likely to invest more in long-term crops (as “guarding labor” becomes more efficiently spent on long-term investments)  Women are more likely than men to switch to a long-term crop (their greater gain in tenure security frees up more labor for long-term crops)  Plots – particularly those controlled by individuals with lower initial property rights – are more likely to be left fallow (as there is less risk associated with leaving land fallow)  Labor may be shifted to plots outside the village for households with initially weaker property rights (as these plots become in greater relative need of “guard labor”) Model predictions

19 Results: Differences in impact on farm labor by gender

20 Results: Differences in impact on farm labor by gender & parcel location

21 Results: Differences in impact on agricultural production by gender & parcel location

22  First large-scale RCT of a land formalization program  Short-term effects, following demarcation  Results:  36 percent increase in perennial cash crop investments  Closing of the gender gap in fallowing  For female-headed households, shift towards cultivation of relatively less secure parcels outside of the village Results summary

23  Important questions remain:  What about the medium-term effects?  What about the impact of certificate delivery?  Follow-up household survey was carried out in 2015 with the same households (panel data)  Analysis is underway / results coming soon! Going forward…

24 Questions? Download the paper here: http://goo.gl/xz5RNU Thank you


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