Millennium Challenge Corporation MCA-Burkina Faso Rural Land

Millennium Challenge Corporation

MCA-Burkina Faso Rural Land Governance Phase II: Data Quality Review Report

Contract No: Task Order No. MCC-10-0111-CON-20 TO02

August 19, 2014

Submitted to: Submitted by:

Jack Molyneaux Laurence Dessein

Project Officer: Jennifer Witriol IMPAQ International, LLC Millennium Challenge Corporation 10420 Little Patuxent Parkway 875 15th Street, NW Suite 300 Washington, DC 20005 Columbia, MD 21044 www.impaqint.com

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TABLE OF CONTENTS

1. INTRODUCTION ...... 1 2. STUDY ZONES ...... 4 3. HOUSEHOLD SURVEY ...... 8 3.1 Sampling Frame ...... 8 3.2 Household Sampling ...... 9 3.3 Data Collection ...... 10 3.4 Data Editing and Entry ...... 11 3.5 Survey Instruments ...... 11 3.6 Distribution of Key Variables ...... 11 3.7 Data Issues Encountered...... 13 4. FIELD MANAGER SURVEY ...... 15 4.1 Sampling Frame ...... 15 4.2 Survey Instruments ...... 16 4.3 Distribution of Key Variables ...... 17 4.4 Data Issues Encountered...... 20 5. VILLAGE SURVEY ...... 23 5.1 Sampling ...... 23 5.2 Survey Instruments ...... 24 5.3 Distribution of Key Variables ...... 24 5.4 Data Issues Encountered...... 26 6. COMMUNE SURVEY ...... 28 6.1 Number of Interviewed Individuals ...... 28 6.2 Survey Instruments ...... 28 6.3 Distribution of Key Variables ...... 29 6.4 Data Issues Encountered...... 30 7. CONCLUSION...... 31 REFERENCES ...... 32 APPENDIX 1: FINAL STATE OF DATA COLLECTION ...... 33 APPENDIX 2: BASIC DESCRIPTIVE STATISTICS ...... 43 1. Village Questionnaire ...... 43

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2. Household Questionnaire ...... 48 2.1 Household Living Conditions ...... 48 2.2 Land Transfers ...... 55 3. Field Manager Questionnaire ...... 59 3.1 Types of land fields ...... 59 3.2 Perception of Land Security and land conflict on the fields ...... 61 3.3 Commercialization of Agricultural Production...... 67 3.4 Perception of gender inequality in access to land ...... 69 APPENDIX 3: DATA QUALITY CHECKS ...... 74

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Exhibit 1: Map of Burkina Faso Intervention Areas ...... 5 Exhibit 2: List of RLG Phase I Treatment and Comparison Communes...... 5 Exhibit 3: List of RLG Phase II Treatment and Comparison Communes ...... 6 Exhibit 4: Map of Intervention and Comparison Communes ...... 7 Exhibit 5: Village Sampling Results...... 9 Exhibit 6: Sample of the Household Survey ...... 10 Exhibit 7: Survey Modules ...... 11 Exhibit 8: Household Characteristics ...... 12 Exhibit 9: Home Characteristics ...... 12 Exhibit 10: Percent of Households Owning Durable Goods ...... 12 Exhibit 11: Field Managers ...... 13 Exhibit 12: Discrepancies Between 2006 Census and 2013 Enumeration ...... 14 Exhibit 13: Sample of the Field Manager Survey ...... 16 Exhibit 14: Survey Modules...... 16 Exhibit 15: Distribution of Field Managers by Age and Gender ...... 17 Exhibit 16: Field Characteristics ...... 17 Exhibit 17: Percent of households that made investments and used inputs in the last 12 months ...... 18 Exhibit 18: Land Conflict: Experiences and Perceptions ...... 18 Exhibit 19: Percent of Households that Perceive the Following as Highly Problematic ...... 19 Exhibit 20: Top 10 Agricultural Crops (Number of Fields) ...... 19 Exhibit 21: Total Household Agricultural Production (in Kg) ...... 20 Exhibit 22: Livestock in the last 12 Months (Number of Households): ...... 20 Exhibit 23: Counts of Missing Values for Surface Areas ...... 22 Exhibit 24: Sample of the Village Survey ...... 23 Exhibit 25: Survey Modules...... 24 Exhibit 26: Percent of Villages with Village Authorities and Institutions ...... 25 Exhibit 27: Total Number of Land Conflicts across All Authorities ...... 25 Exhibit 28: Average Number of Land Disputes Presented to the Village Authorities ...... 26 Exhibit 29: Average Number of Resolved Land Disputes by the Village Authorities ...... 26 Exhibit 30: Sample of the Commune Survey ...... 28 Exhibit 31: Survey Modules...... 29 Exhibit 32: Commune Characteristics ...... 29

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1. INTRODUCTION

This report reviews the quality of the Rural Land Governance Project Phase II baseline (pre- intervention) data collected by the Bureau d'Etudes et de Recherche pour le Développement (BERD) in Burkina Faso. The data collection was contracted by the Millennium Challenge Account – Burkina Faso (MCA-BF) for the evaluation of the Millennium Challenge Corporation’s Rural Land Governance Project in the country.

In 2008, the government of Burkina Faso and the Millennium Challenge Corporation (MCC) signed a USD 480.9 million five-year compact over 2009–2014 to finance a poverty-reduction program in Burkina Faso. The overall objective of the Compact is to contribute to poverty reduction in the country via economic growth. The Compact includes the following four projects:

. Agricultural Development Project,

. Rural Land Governance Project,

. Roads Rehabilitation Project and

. Burkinabé Response to Improve Girls’ Chances to Succeed (BRIGHT II) Schools Project.

The Rural Land Governance Project (RLG) was launched in September. The RLG represents a substantial investment in land issues and is structured around three components:

. Legal and Procedural Change and Communication This Project Activity supported the Government’s efforts to improve rural land laws and the regulatory and procedural framework to implement those laws. Most notably, the Project played a key role in the development of Law No. 34/2009 “On Rural Land Tenure” and its implementing regulations in 2009-2010, and Law No. 34/2012 “On Agrarian and Land Reform in Burkina Faso.” These efforts were complemented by a public outreach program to inform people about the new legislation and its expected benefits. This Activity was the first one implemented and set the framework for the other RLG activities, including decentralization of land administration and conflict resolution institutions, and issuance of rural land possession certificates (APFRs).

. Institutional Development and Capacity Building This Project Activity, in conjunction with the Legal and Procedural Change and Communication Project Activity, worked to improve institutional capacity to deliver land services in rural areas. Most notably, this activity supported extensive training of GOBF officials from various ministries, and the establishment and operations of commune-level rural land services offices (SFRs), village level land commissions (CFVs) that support SFR operations, and village level conflict resolution commissions (CCFVs) that mediate land conflicts. Implementation took place at the commune and village level in the Project’s 17 Phase 1 municipalities

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on a pilot basis, and expanded in 2013 to an additional 30 Phase 2 communes based on certain targets reached during Phase 1.

. Site-Specific Land Tenure Interventions This Project Activity supported a variety of site-specific land rights formalization interventions. Activities included: o Preparation of land titles and land leases for recipients of farmland in the new Di Irrigation Perimeter (the Perimeter was developed under the Agriculture Development Project) in 2014; o Preparation of leases for users of land in existing irrigation perimeters near the Di Perimeter in 2014; o Preparation of rural land possession certificates (APFRs) for non-irrigated land in the Project’s 47 implementation communes in 2013-2014; o Provision of APFR-like certificates to households in Ganzourgou Province in 2010; and o Working with local populations to develop participatory land and natural resource use plans.”

The RLG activities aim to make land legislation and administration procedures more user- friendly and accessible, to improve public land services in rural areas, and to facilitate participatory land-use management, registration of land rights, and conflict resolution. The expected results of the project are to improve land tenure security, reduce land conflicts, encourage productive land investments, and promote economic growth and reduce poverty in the intervention zones.

The impact evaluation of the RLG project will address four research questions: 1. Do project activities lead to an improved perception of land security? 2. Is there a reduction in the number of land conflicts? 3. Does improved land tenure security act as an incentive for producers’ investments? 4. Does land tenure improve for vulnerable groups (for example, women)?

The RLG project is being implemented in a phased approach consisting of a pilot phase (Phase I) and an extension phase (Phase II). Phase I provided the following activities in years 1 and 2: legal reform and institutional strengthening in 17 communes. These activities were followed by APFRs and other formalization activities in year 3. Phase II provided similar activities in 30 additional communes. It is important to note that in Phase II, there was no national level legislative assistance since the main legal changes were completed at the national level as part of Phase I.

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The purpose of the data reviewed in this report was to establish a baseline for the RLG Phase II intervention. This baseline data was designed to be used subsequently for the impact evaluation. In September–December 2013, BERD conducted the following surveys:

. household survey

. field manager (parcel owner) survey

. village survey

. commune survey

The impact analysis will incorporate information from all four surveys. In this review of the data, we review all four survey data sets. The focus of the report, however, is on the two main surveys: 1. the household survey and 2. the field manager survey.

These two surveys contain essential data necessary for the impact analysis, as our evaluation design consists of econometric models using individual and household level data. Since the two other surveys – the village survey and the commune survey – are less critical to the impact evaluation, we briefly described these surveys as well.

For each survey, we present the sampling frame, sampling coverage, survey instruments, descriptive statistics of key variables and any data issues encountered. The rest of the report is organized as follows: 2) Study zones 3) Household survey 4) Field manager survey 5) Village survey 6) Commune survey and 7) Conclusion.

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2. STUDY ZONES

Burkina Faso is located in a vast plateau south of the bend of the Niger River. Most of the country is flat and there is relatively low rainfall. Burkina Faso is home to an important hydrographic network which comprises three basins: the Volta, the Comoé and the Niger. The RLG Phase I was implemented in 17 communes and the RLG Phase II was implemented in 30 communes in various regions along these basins (See Exhibit 1 for the location of the communes). The 17 communes in Phase I (dark green in the map) and the 30 intervention communes in Phase II (light green in the map).

Based on limited documentation and discussions with from MCA-BF, IMPAQ understands that the RLG intervention communes were were selected based on the following criteria:

. Significant land tenure issues or disputes;

. Located near or within the Agricultural Development Project (ADP) new perimeter;

. Located in or near another irrigation perimeter;

. Contains important infrastructure such as a livestock market;

. Located near Compact road investments.

Furthermore, there was an effort to cluster communes, so that a concentration of several rural communes could facilitate the coordination of MCA programs.1

In Phase I, the 17 treatment and 17 comparison communes were selectd by MCA-BF prior to IMPAQ’s involvement in the project. In Phase II, 30 tretament communes were selected by MCA-DF based on the above criteria. IMPAQ collaborated with MCA-BF to select 29 comparison communes for Phase II. A list of the intervention and comparison areas for Phase I is presented in Exhibit 2 and for Phase II in Exhibit 3. The location of the intervention and comparison communes is presented in Exhibit 4.

The comparison communes in Phase II were collaboratively selected by IMPAQ and MCA-BF using a purposive rather than a probabilistic sampling procedure. For each treatment commune, the team identified a comparison commune that satisfied the following criteria:

. It is located in the same province as the treatment commune (assuming that location in the same province means sharing similar administrative structures).

. It is located in a zone aménagée (irrigation infrastructure) and is relatively similar in size to the intervention commune.

. It has a similar presence of gold mines, as in the treatment commune.

. It is geographically close to the treatment commune.

1 See document MCA proposal for final selection of CRs oct 2007_vOct16.doc.

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. No other land-related interventions are being implemented in the commune.

. It has a similar population size as the treatment commune (based on 2006 Census data).

. It has a similar socio-rural area (based on documentation received from MCA-BF).2

Exhibit 1: Map of Burkina Faso Intervention Areas

Exhibit 2: List of RLG Phase I Treatment and Comparison Communes

Treatment Comparison BAMA BEREGADOUGOU BANFORA BIEHA BOUDRY BOMBOROKUY DI BOUROUM DJIBO DANDE GUIBA GAONGO KAMPTI GOURCY KONGOUSSI KOMPIENGA LEO MEGUET

2 According to Cartographie des Zones Socio-Rurales, AgWater Solutions report (2010), Burkina Faso can be divided into 16 zones that are homogenous in terms of climate conditions, natural resources and other socio- economic characteristics (e.g. access to markets and main economic activities).

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Treatment Comparison LOUMBILA NOBERE MOGTEDO PABRE OUAHIGOUYA RAMONGO OUARGAYE SABCE PAMA TONGOMAYEL SABOU YE SONO YONDE ZAM ZOUNGOU Source: RLG Phase I Baseline Survey, 2010

Exhibit 3: List of RLG Phase II Treatment and Comparison Communes

Treatment Comparison N° Commune Province N° Commune Province 1 Gassan Nayala 1 Kougni Nayala 2 Moussoudougou Comoé 2 Samogohiri Kénédougou 3 NiangoloKo Comoé 3 Soubakaniedougou Comoé 4 Sideradougou Comoé 4 Mangodara Comoé 5 Douna Leraba 5 Dakoro Leraba 6 Koubri Kadiogo 6 Pabre Kadiogo 7 Saaba Kadiogo 7 Komsilga Kadiogo 8 Bittou Boulogou 8 Zabre Boulogou 9 Lalgaye Koupelogo 9 Komin-yanga Koupelogo 10 Zimtenga Bam 10 Nasséré Bam 11 Kokologho Boulkimiende 11 Nanoro Boulkimiende 12 Poa Boulkimiende 12 Kindi Boulkimiende 13 Tenado Sangie 13 Pouni Sanguie 14 Cassou Ziro 14 Bakata Ziro 15 Bere Zoundwego 15 Gomboussougou Zoundwego 16 Binde Zoundwego 16 Gogo Zoundwego 17 Tansarga Tapoa 17 Tampaga Tapoa 18 Padema Houet 18 Satiri Houet 19 Samorouguan Kenedougou 19 Sindo Kenedougou 20 Lanfiera Sorou 20 Yaba Nayala 21 Kassoum Sorou 22 Sapouy Ziro 21 Guiaro Nahouri 23 Banzon Kenedougou 22 Kourouma Kenedougou 24 Tangaye Yatenga 23 Thiou Yatenga 25 Pobe Mengao Soum 24 Baraboulé Soum 26 Bourasso Kossi 25 Dokui Kossi 27 Didyr Sanguié 26 Godyr Sanguié 28 Toussiana Houet 27 Péni Houet 29 Djigouè Poni 28 Gbomblora Poni 30 Rollo Bam 29 Tikare Bam IMPAQ International, LLC Page 6 RLG Phase II - Data Quality Review Report

Exhibit 4: Map of Intervention and Comparison Communes

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3. HOUSEHOLD SURVEY

The household survey provides information on housing, possession of durables, land transfers and major household events. This survey also provides an enumeration of all household members who manage fields or plots of land necessary for the next survey. The household survey data was collected in both the intervention and comparison zones.

To understand the sampling for the survey, it is important to keep in mind the evaluation design IMPAQ developed. IMPAQ plans to implement a difference-in-differences (DD) methodology. Based on this method, we have determined the necessary sample size and how to draw the households in the sample from the population of interest. The evaluation design can be summarized as follows: 1. The treatment group includes a sample of households located in villages from intervention communes where the RLG Phase II program has been rolled out. 2. The comparison group includes a sample of households located in villages from comparison communes where the RLG Phase II program has not been implemented. 3. Applying DD methodology, we will compare the changes in outcomes over time between the treatment and comparison groups.

Additional details on the sampling frame, sampling and data collection are presented in the following sections.

3.1 Sampling Frame

Given the finalized study zones (30 treatment and 29 comparison communes in 20 provinces and 12 regions), the IMPAQ team performed power analysis to determine the necessary sample size – the total number of villages within each commune and the total number of households within each village to be sampled. We used two-stage sampling to account for the household clustering in villages – first-stage is sampling at the village level and second-stage is sampling at the household level. Our power analysis calculations indicated that a total of 4,000 households will be a sufficient sample to detect a 12% change in agricultural income.3 At 8 households per village, this required approximately 250 villages in treatment communes and 250 villages in comparison communes.

IMPAQ used the most recent census of the population in Burkina Faso (2006) to obtain the list of villages in each commune and the total number of households in each village. From the compiled list of villages, the IMPAQ team then drew a group of villages to be sampled.

3 We calculated the minimum sample size to be 2,000 treatment and 2,000 comparison households under the assumption of 80% power and 5% significance level. Income data come from the PNGT2, a rural household survey conducted in Burkina in 2005.

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Within each commune, IMPAQ sampled villages with probability proportional to size of the village (i.e., the household population of the village). From a total of 623 villages in treatment areas, 178 were selected to be sampled (See Exhibit 5). In the comparison areas, 179 out of 672 villages were selected to be sampled. The total number of villages in the sample is 357 in 59 communes.

Exhibit 5: Village Sampling Results

Treatment Comparison Total Total number of villages 623 672 1,295 Number of villages sampled 178 179 357 Total number of sampled households 2,008 2,008 4,016

Since we used probability proportional to size sampling techniques with replacement, some villages were selected more than once into the sample (48 out of the 178 treated villages were sampled more than once).4 Each time a village was drawn into the sample, we selected 8 households. Thus, for example, Yorgo village in Bere commune was drawn twice. Therefore, we sampled and interviewed 16 households in Yorgo.

3.2 Household Sampling

IMPAQ supplied BERD with a list of treatment and comparison villages with the associated number of households to be sampled within each selected village. In the field, BERD enumerators traveled from village to village and from neighborhood to neighborhood to conduct an exhaustive enumeration of all households in the sampled villages. The enumeration data was collected to serve two purposes: (i) to facilitate the random draw of the necessary number of households within each village from an enumeration list of all households and (ii) to allow the calculation of population weights in case there were big population discrepancies between 2006 and 2013.5

With enumeration lists at hand, BERD data collectors randomly selected the designated number of households for each village. A total of 4,016 households (2,008 treatment and 2,008 control) were interviewed, thus reaching the target number of households (See Exhibit 6). There are a total of 32,595 household members across the total sample of 4,016 households. Among all household members, 8,096 were identified as field managers (4,076

4 Consistent with probability proportional to size sampling, the sampled villages with larger populations have a higher probability of being drawn. The sample of households in these larger villages was determined to be a multiple of 8. 5 IMPAQ has not received the enumeration data. The data, if of high quality, would provide up-to-date population figures in the sampled villages that would allow us to construct population weights.

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treatment and 4,020 control).6 See Appendix 1 for summary results of the data collection by village and communes.

Exhibit 6: Sample of the Household Survey

Treatment Comparison Total Communes 30 29 59 Villages 178 179 357 Households 2,008 2,008 4,016 Household members 16,620 15,974 32,594 Plot managers 4,076 4,020 8,096

3.3 Data Collection

The data collection was conducted in September and October of 2013 by 50 teams of enumerators hired by BERD. Each team was composed of 4 enumerators and 1 controller. Eleven supervisors oversaw 11 groups of teams organized by zones of communes. MCA provided some additional supervision.

All enumerators, controllers and supervisors were trained by BERD prior to the implementation of the survey (September 2-16, 2013). The training included plenary and small group work sessions each training day. In addition, there was a debriefing session at the beginning and end of each training day. IMPAQ observed the training which was very effective. However, there were some logistic and organizational difficulties in implementing the survey. For example,

. local officials were not informed of the upcoming survey in their community and, as a result, there were issues in obtaining timely access to respondents; . there was a shortage of GPS devices; and . there were some difficulties in reaching respondents who lived in distant hamlets outside the villages.

IMPAQ identified these issues and suggested corrective actions to MCA-BF and the survey firm. It appears that survey firm took some corrective issues (e.g., provided enumerators with more GPS units), but some of issues persisted (reaching respondents in distant hamlets).

A review of the difficulties encountered in the field by IMPAQ suggests that while these issues can present problems for data quality, in general, they affect only a small proportion of the

6 Field managers are members of the household who make most of the decisions concerning crops/trees to plant, input use and the planning of activities related to crop/livestock/pasture, the commercialization of agricultural production/products derived from animals, and investment in the field. For commercial or residential fields, this includes commercial and family decisions. The field manager can be the owner of the field or only have rights to use it. There may be more than one field manager per household.

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sample. As a result, we are reasonably confident that the collected survey data is adequate for the impact evaluation.

3.4 Data Editing and Entry

Field supervisors checked the questionnaires before the data were sent to the survey firm for data entry. Data entry was then conducted by BERD. After receiving the original data set from MCA-BF on March 17, 2014 IMPAQ began a data quality review. On May 8, 2014, IMPAQ received from MCA the revised by BERD data sets and proceeded to review the data quality of these files.

3.5 Survey Instruments

The household survey used a questionnaire composed of seven modules, each focused on a different area of interest (See Exhibit 7). Importantly, the household survey was used to enumerate all household members who manage fields that will be surveyed in the Field manager survey.

Exhibit 7: Survey Modules

1. Identification of the household 2. Housing characteristics 3. Land transfers 4. Characteristics of household members 5. Durable goods 6. Characteristics of field managers 7. Household events during last 24 months

3.6 Distribution of Key Variables

Exhibit 8 presents key household characteristics. Among all households in the sample, 7.3% were headed by women and 70.5% had an illiterate head of household. On average, households included 8.1 members.

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Exhibit 8: Household Characteristics

Treatment Comparison Total

Percent of households with female heads 6.1% 8.4% 7.3%

Percent of households with illiterate heads 68.9% 72.1% 70.5%

Average household size 8.0 8.3 8.1

Less than a third (31.9%) of all households lived in their current home between 0 and 5 years, while over two-thirds (68.1%) have been at the same home 6 years or more (See Exhibit 9). On average, there were 1.7 rooms per household.

Exhibit 9: Home Characteristics

Treatment Comparison Total

Percent of households living 0–5 years in current home 32.4% 31.3% 31.9% Percent of households living 6 or more years in current 67.6% 68.7% 68.1% home Average number of rooms per home 1.7 1.8 1.7

Exhibit 10 presents the percent of households that owned durable goods: bicycles (91.8%), mobile or landline phones (82.6%), radios (55.2%), televisions (9.5%) and fans (2.3%).

Exhibit 10: Percent of Households Owning Durable Goods

Treatment Comparison Total

Bicycle 91.8% 91.8% 91.8%

Phone 84.0% 81.2% 82.6%

Radio 57.1% 53.3% 55.2%

TV 11.4% 7.6% 9.5%

Fan 2.9% 1.7% 2.3%

There were a total of 8,096 field managers (i.e., household members who managed a field) identified. Specifically, there were 4,076 field managers in the treatment group and 4,020 in comparison group (See Exhibit 11). On average, there were two field managers per household.

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Exhibit 11: Field Managers

Treatment Comparison Total

Total number of field managers 4,076 4,020 8,096

Average number of managers per household 2.0 2.0 2.0 Percent of households with land transfer in last 4.6% 4.9% 4.7% 2 years

As indicated in Exhibit 10, few households (less than 5%) experienced a land transfer in the last two years.

3.7 Data Issues Encountered

In the data quality review, we did not identify any major data issues that would affect the overall quality of the analysis. We found the overall quality of the household survey to be adequate and we believe the data are suitable for the impact evaluation analysis. In the rest of this section, we list a few issues that are worth mentioning.

There were occasional gaps in the total number of households from the enumeration relative to the latest 2006 General Population Census. During the enumeration phase, BERD data collectors documented differences in household sizes between the 2006 Census and the enumeration conducted in 2013. For the most part, the changes in population are related to natural population growth during these years. Some of these differences may also be due to the use of a slightly different household definitions. This resulted in enumerated households being smaller and more numerous. The implication of the this discrepancy for the impact analysis is that the our sample design was based on data from the 2006 census. If these numbers are no longer valid, then the sample selection may be affected.

While it may not be surprising to observe changes in population over a seven year period, BERD looked into some of the discrepancies and identified reasons for the changes. Some of the changes between 2006 and 2013 are listed in Exhibit 12 with BERD’s assessment of the changes are presented following the exhibit. 7

7 Rapport Technique sur les Activités de Terrain: Enquête de base sur les ménages et l’agriculture. BERD. January 2014.

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Exhibit 12: Discrepancies Between 2006 Census and 2013 Enumeration

Village Commune 2006 Census 2013 Enumeration

Rimini Niangologo 504 887

Nianaba Toussiana 527 376

Wempeall Toussiana 121 81

Didri Koubri 601 539

. In the village of Rimini, Niangologo commune, 887 households were enumerated in 2013 against 504 in the 2006 Census. The reason for this remarkable increase was attributed to an influx of new households in the locality after the discovery of a vein of gold that turned the village into a mining site.

. In the villages of Nianaba and WempeaII, Toussiana commune, household populations decreased respectively from 527 and 121 (during the 2006 Census) to 376 and 81 households (during the enumeration survey of 2013). According to the authorities of Toussiana, the 2006 count included displaced populations from Côte d’Ivoire who returned to their country after the end of the civil war.

. In the village of Didri, Koubri commune, 539 households were listed in 2013 as compared to 601 in 2006. According to the village chef and the Village Development Council (Conseil Villageois de Développement, CVD), this is attributed to the fact that the population of the Kuinig-Banka section is now claimed to belong to a neighboring village.

Despite these observed changes in population from 2006, the original sampling design was maintained and BERD selected and interviewed the appropriate number of households in each village. BERD enumerators selected a random sample of households in each selected village and successfully collected data from almost 100% of the selected households.

In summary, while there were minor issues in the survey implementation, the issues encountered in the field seem not significant. IMPAQ believes that the issues identified above should not have a detrimental effect on the data quality and its usability for the impact evaluation.

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4. FIELD MANAGER SURVEY

Following the household survey, BERD enumerators proceeded with an individual questionnaire to all household members who were identified as field managers. The administration of this survey served two purposes: 1. to collect detailed information about each field or plot of land used by households and 2. to collect detailed information about the plot managers who make the decisions about these plots.

4.1 Sampling Frame

For all households in the sample, BERD interviewers established two enumerations: (1) an enumeration of all fields and (2) an enumeration of all field managers. Boxes 1 and 2 provide the definitions used in both enumerations.

Field definition:

A field is defined as a piece of land owned by one person or a group of members of a family. A field can be enclosed by natural borders and can contain one or more parcels. The natural boundary of a field can be a road, a river, or a field belonging to someone else.

Field manager definition: A field manager is a member of the household who takes most of the decisions concerning crops/trees to plant, use of agricultural inputs, the planning of activities related to crop/livestock/pasture, the commercialization of agricultural production and products derived from livestock, and decisions concerning investments in the field. For fields that are used for commercial or residential purposes, this also includes decisions related to commercial and household activities. The field manager can be the owner of the field or have only user rights on it.

For fields that are rented out to members outside the household, even if the tenant decides how to use the land, the field manager is the household member who owns the field or the member who decides about the appointment of a tenant. Therefore, the field manager is typically the person best placed to provide information on this particular field.

For fields used as primary residence of the household, the field manager can be the head of household or another member of the household who is regarded as being responsible for this field.

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The household survey identified 8,096 field managers (4,076 treatment and 4,020 control). They managed 16,370 land fields (8,422 treatment and 7,948 control). A field manager can manage multiple fields (See Exhibit 13).

Exhibit 13: Sample of the Field Manager Survey

Treatment Comparison Total

Households 2,008 2,008 4,016

Household members 16,620 15,974 32,594

Field managers 4,076 4,020 8,096

Fields 8,422 7,948 16,370

4.2 Survey Instruments

The field manager survey used a questionnaire composed of thirteen modules, each focused on a different area of interest (See Exhibit 14).

Exhibit 14: Survey Modules

1. Identification of fields 2. Ownership and acquisition of fields 3. Land rights of use 4. Field investments and use of inputs 5. Revenues from fields used for commercial purposes 6. Perceptions of and actual land conflicts 7. Agricultural production 8. Commercialization of agricultural production 9. Livestock 10. Employment 11. Transfers, rents and other revenues during last 12 months 12. General perceptions of land security 13. Gender inequality: perceptions of land access

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4.3 Distribution of Key Variables

There is an approximately equal distribution of male and female field managers – 4,073 men vs. 4,023 women (See Exhibit 15). However, female field managers tend to be younger, with 32% of them aged 30 or less. This percentage is only 19% among male field managers. Similarly, among those aged 65 and above, only 5% are women vs. 12% men.

Exhibit 15: Distribution of Field Managers by Age and Gender

Gender Age range Male Female Total N Percentage N Percentage N Percentage Younger than 30 765 19% 1,280 32% 2,045 25%

30–64 2,835 70% 2,541 63% 5,376 66%

Older than 64 473 12% 202 5% 675 8%

Total 4,073 100% 4,023 100% 8,096 100%

Exhibit 16 presents field characteristics for the households. There are a total of 16,370 enumerated fields among all households: 8,422 in treatment and 7,948 in comparison groups. Households reported four fields on average, with some owned and others in use. For the most part, households own at least one of the fields they reported (88.6%), while less than half of the surveyed use fields that belong to others (41.4%).

Exhibit 16: Field Characteristics

Treatment Comparison Total

Total number of fields 8,422 7,948 16,370

Average number of fields per household 4.2 4.0 4.1

Percent of households who own at least 1 field 87.2% 90.0% 88.6%

Percent of households who use fields of others 43.7% 39.0% 41.4%

Exhibit 17 represents the percentage of households who made field-related investments and used agricultural inputs in the past 12 months. The questionnaire asked about whether the household has made certain investments and if not why. For illustrative purposes, we list five reasons (out of 14 surveyed): to build a new construction (27.0%), to plant permanent crops (29.1%), to buy a tractor (1.0%), to use fertilizer (71.9%) and to use seeds (68.5%).

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Exhibit 17: Percent of households that made investments and used inputs in the last 12 months

Treatment Comparison Total

To build new constructions 27.0% 27.1% 27.0%

To plant permanent crops (trees) 28.8% 29.4% 29.1%

To buy a tractor 1.3% 0.8% 1.0%

To use fertilizer 71.4% 72.4% 71.9%

To use seeds 68.5% 68.6% 68.5%

In 7.9% of households, at least on field manager reported that they or another member of the household has ever experienced a land conflict, with an average number of 2.8 conflicts per household (See Exhibit 18). Similar proportions of treatment and comparison households experienced land conflicts (7.6% treatment and 8.2% comparison); however, the average number of conflicts for treatment households was 3.3 and the average for comparison households was 2.2. This discrepancy in average number of conflicts per household suggests that the treatment areas were prone to more land conflicts than the comparison areas. At this stage, we do not have an explanation for the observed difference in land conflicts. We will investigate the discrepancy more thoroughly in the analysis. IMPAQ does not believe that this discrepancy will have a significantly affect the impact analysis since our analysis will control for initial condition in the treatment and comparison areas.

Exhibit 18: Land Conflict: Experiences and Perceptions

Treatment Comparison Total

Percent of households experiencing land conflict 7.6% 8.2% 7.9%

Average number of conflicts per household 3.3 2.2 2.8

Percent of households fearing future conflicts 45.1% 43.1% 44.1%

Respondents also indicated the factors that may lead to land conflicts. In Exhibit 19, we present some of the most frequent reasons that were cited by respondents as highly problematic. We report percent of households where at least one field manager perceive these to be of most concern, in general:

. the arrival in the village of outsiders looking for farmland (55.9% of households) . the delay and cost to obtain legal property rights (55.1% of households), and

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. land disputes in their village (60.7% of households).8 There does not appear to be significant differences between the treatment and comparison group responses.

Exhibit 19: Percent of Households that Perceive the Following as Highly Problematic

Treatment Comparison Total

Arrival of outsiders looking for farmland 57.9% 53.8% 55.9%

Delay and cost to obtain property rights 53.6% 56.7% 55.1%

Land disputes in their village 63.4% 58.1% 60.7%

Respondents were also asked about the crops that they planted in their fields. Respondents were specifically asked about 32 different types of crops. As indicated in Exhibit 20, sorghum was planted in 2,040 treatment fields and 2,356 comparison fields. Note households can plant the same crop in multiple fields. Exhibit 19 lists the top 10 crops that were planted by households.

Exhibit 20: Top 10 Agricultural Crops (Number of Fields)

Treatment Comparison Total

1. Sorghum 2,040 2,356 4,396

2. Millet 2,017 1,769 3,786

3. Maize 1,658 1,582 3,240

4. Peanuts 1,537 1,524 3,061

5. Cowpeas 1,445 1,595 3,040

6. Sesame 663 733 1,396

7. Rice 540 717 1,257

8. Cotton 587 543 1,130

9. Gombos 502 556 1,058

10. Groundnuts 419 322 741

8 Field managers were asked whether, in general, land disputes were are a major problem, minor problem, or not a problem at all in their village.

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In Exhibit 21, we present the quantity amounts and standard deviation of total household production during the past 12 months of the three mostly planted crops. Among households who reported agricultural production, the mean total household production in the treatment area was 1,043 kg for sorghum, 937 kg for millet and 2,113 kg for maize. Note that not all households grow these cereals (1,127 out of 2,008 households in the treatment area grow sorghum, for example). In the comparison area, the average total household production was of similar magnitudes – 1,126 kg for sorghum, 936 kg for millet and 2,260 kg for maize.

Exhibit 21: Total Household Agricultural Production (in Kg)

Treatment Comparison Total household production Total household production Crop N N (kg) (kg) Sorghum 1,043 (1,892) 1,127 1,126 (2,414) 1,195

Millet 937 (1,627) 1,000 936 (1,116) 917

Maize 2,113 (3,819) 1,215 2,260 (10,326) 1,199

In addition to questions on crops, the questionnaire also asked about livestock. As indicated in Exhibit 22, a total of 3,337 households in the sample raised some livestock during the last 12 months. Of those households that raised livestock, chickens were the most prevalent (2,943) followed by sheep and goats (2,804). A relatively small number of households raised pigs (657). The distribution of type of animal raised is similar for treatment and comparison households.

Exhibit 22: Livestock in the last 12 Months (Number of Households):

Treatment Comparison Total

All livestock 1,663 1,674 3,337

Chickens 1,481 1,462 2,943

Sheep and goats 1,383 1,421 2,804

Cows 979 1,087 2,066

Pigs 274 383 657

4.4 Data Issues Encountered

The data quality review did not identify any major data issues that would affect the overall quality of the analysis. We find that the overall quality of the field manager survey is good and IMPAQ International, LLC Page 20 RLG Phase II - Data Quality Review Report

we believe this data to be suitable for an impact evaluation analysis. However, there were some issues that were identified, investigated, and corrected by BERD. Below, we describe these issues and how BERD corrected the problems identified.

BERD’s technical report9 of field activities identified two issues in the field:

i) underreporting of female field managers, and ii) enumerators’ understanding of the definition of ‘field manager’.

Specifically, data collection controllers noticed that, in some villages, households systematically underreported female field managers while in others villages controllers believed that certain household member should be listed as field managers. Following this discovery, BERD enumerators re-visited the problem villages to address the issues that were identified:

. Underreporting. In total, 175 households in 27 villages were identified as possibly underreporting female managers and required verification. To correct the problem, eight investigators returned to the field from 19–26 November 2013, in order to review the data accuracy of these problematic surveys and confirmed that 75 households were indeed without female field managers. Following the review, BERD sent eight controllers back into the field from 20–26 December 2013 to re-administer the questionable surveys to the remaining 100 households to collect data from their female field managers. The corrected surveys were then entered into the analysis file.

. Understanding. In some villages, BERD identified an issue with interviewers’ understanding of the definition of ‘field manage’ based on the low number of female field managers. This issue was discovered in 10 villages (two in Tangaye and eight in Thiou) and involved a total of 120 households. To correct this problem, two teams (2 controllers, 8 investigators) were deployed to the Thiou and Tangaye communes for a new data collection. This new data collection took place from 19–28 November, 2013. The corrected surveys were then entered into the analysis file.

In addition to the two main issues identified by BERD, IMPAQ identified some minor issues in the files. For example, 8,474 out of 16,376 (51.8%) did not provide values for their field surface size (see Exhibit 23). However, respondents who were not able to self-report the exact field surface area were asked to report the approximate size in hectare intervals. Nearly all respondents were able to provide an interval response to the surface area question.

In response to the surface area used for various agricultural products, the same issue was encountered. That is, when field managers were asked to report the exact surface area that

9 Rapport Technique sur les Activités de Terrain: Enquête de base sur les ménages et l’agriculture. BERD. January 2014.

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was used for various crops, 13,391 out of 24,826 (53.9%) responses had missing values. When asked to respond in intervals, nearly all field managers were able to respond (only 2.0% missing). Not having exact field and area sizes will prevent computing exact crop yields. However, we believe that using the approximate areas will allow the computation of reasonable accurate crop yield ranges.

Exhibit 23: Counts of Missing Values for Surface Areas

Section H: Identification of the Fields Section N: Agricultural Production

Area in Ha Area in Ha N % N % (values) (values) Missing 8,474 51.8 Missing 13,391 53.9 Total 16,376 100 Total 24,826 100

Area in Ha Area in Ha N % N % (intervals) (intervals) Missing 13 0.2 Missing 266 2.0 Total 8,474 100 Total 13,443 100

Despite the issues identified, we believe the data collected by BERD is of reasonable quality and suitable for the impact analysis. BERD took the initiative to identify and correct the problem. Once correct data was gathered, BERD entered the corrected data into the analysis file. As a result of BERD’s actions, we believe that the final data set is suitable for the impact analysis.

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5. VILLAGE SURVEY

The purpose of the village survey was to collect information on population, infrastructure, land use and ownership arrangements, as well as on prices of agricultural and livestock products, and perceptions of tenure security at the village level.

5.1 Sampling

This survey covers the same villages as those selected for the survey of households (178 treatment and 179 control villages). This questionnaire was administered simultaneously with the household questionnaire. Enumerators administered the questionnaire to a small group (3–5 people) of knowledgeable residents in each village. The profile of respondents included village chief, wife of the village chief, director of the local school, teacher, government officials, assistant land agronomist, religious leaders, merchants, workers in the sector of health, and long-term residents who are well informed. Each of the respondents in the group had lived in the village for several years.

Since the goal of this survey was to collect information from authorities responsible for resolving land conflicts at the village level, the interviewers made an effort to include representatives of the following authorities: 1. Village Development Council (CVD) 2. Village Land Conciliation Commission (CCFV) 3. Village Counselors

Enumerators selected two groups for this survey: (1) men and (2) women. There were a total of 3,121 male and female village resident responders (See Exhibit 24). There were up to 15 respondents per village. The groups gathered in a meeting room and were asked to reach a consensus before answering each question. Enumerators noted the disagreements within the group when they were unable to reach a consensus. Groups of men and women were interviewed separately and two responses were collected for each question. There were 1,491 women and 1,630 men.

Exhibit 24: Sample of the Village Survey

Treatment Comparison Total

Villages 179 178 357

Male respondents 845 785 1,630

Female respondents 786 705 1,491

Total respondents 1,631 1,490 3,121

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5.2 Survey Instruments

The village survey used a questionnaire composed of thirteen modules, each focused on a different area of interest (See Exhibit 25).

Exhibit 25: Survey Modules

1. Identification of the village 2. Characteristics of individual respondents 3. Characteristics of village populations 4. Village infrastructure 5. Land use 6. Land ownership arrangements 7. Village resource management 8. Perceptions of land security 9. Perceptions of gender equity in land access 10. Administration of land conflicts at the village level 11. Village organizations 12. Prices of agricultural products 13. Prices of livestock products

5.3 Distribution of Key Variables

Exhibit 26 presents the percent of villages with authorities and institutions responsible for addressing land conflicts. As indicated, 82.9% of the villages reported the presence of a Chef de terre (land ownership chief) and 94.4% reported the presence of a City Council. There is a Village Development Council (Conseil Villageois de Développement, CVD) in practically all villages (98.3%). Only 51.3% of villages had a Village Land Conciliation Commission (Commission de Conciliation Foncière Villageoise, CCFV), with a large difference across treatment (82.1%) and comparison (19.5%) groups.

The responses in Exhibit 26 on the number of CCFVs in the treatment and comparison areas are very puzzling and lead us to suspect the data quality of the village survey. Our understanding is that, at the time of the baseline survey, CCFVs were in process of being established and were not operational until after the baseline survey. Therefore, we do not understand how the respondents could have known about the CCFVs. While the 82.1% reported in the treatment areas is surprising, even more surprising is the reported CCFVs in the comparison areas. While MCA explained that some control communes could have set-up their own CCFVs, such a large proportion of CCFVs (19.5%) reported in the control communes remains surprising and puzzeling.

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These issues suggest a problem with the village survey which will require a more detailed investigation during the evaluation. In a recent conference call with MCA-BF and MCC, MCA- BF promised to send documentation with detailed information on when CCFVs were established and began operation in each commune. With this documentation, IMPAQ will be able to better assess the validity of the village survey data. 10

Exhibit 26: Percent of Villages with Village Authorities and Institutions11

Treatment Comparison Total

Chef de terre 86.1% 79.6% 82.9%

City Council 97.2% 91.5% 94.4%

Village Development Council (CVD) 98.3% 98.3% 98.3%

Village Land Conciliation Commission (CCFV) 82.1% 19.5% 51.3%

As indicated in Exhibit 27, a total of 1,980 land conflicts were identified in the treatment and comparison areas during the past 12 months. Specifically, 1,276 land conflicts were reported in villages in the treatment areas and 704 land conflicts were reported in villages in the comparison areas. During the same period, 1,515 were resolved. It is tempting to compare these results with the results reported in Exhibit 18 from the household survey; however, the samples are different and, therefore, the results may not be comparable. As we indicated earlier, the difference in number of land conflicts between the treatment and comparison areas is not a serious data quality issue in measuring the program impacts since the evaluation will control for initial conditions in the two areas.

Exhibit 27: Total Number of Land Conflicts across All Authorities

Treatment Comparison Total

Total number of identified conflicts 1,276 704 1,980

Total number of resolved conflicts 889 626 1,515

The average number of land disputes presented to various village authorities is depicted in Exhibit 28. As indicated in the exhibit, an average of 2.1 land disputes were presented to the Chef de terre, 1.8 to the City Council, 1.7 to the Village Development Council and 0.7 to the Village Land Conciliation Commission. There low number of land disputes presented to the CCFVs may partly be explained by the issue discussed above. Another issue with the data

10 See conference call notes: MCC_MCA_IMPAQ_MeetingNotes_2014.07.31.docx 11 Only male responses are reported.

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presented in Exhibit 28 is that land disputes may have been presented to multiple authorities and, therefore, there is probably some double counting involved in the data. All of these issues will need to be investigated more fully to determine the accuracy of the village data.

Exhibit 28: Average Number of Land Disputes Presented to the Village Authorities

Treatment Comparison Total

Chef de terre 2.5 1.7 2.1

City Council 2.2 1.3 1.8

Village Development Council (CVD) 2.1 1.3 1.7

Village Land Conciliation Commission (CCFV) 0.8 0.4 0.7

The average number of resolved land disputes at the separate village authorities is presented in Exhibit 29. An average of 2.3 land disputes were resolved by the Chef de terre, 1.6 by the City Council, 2.0 by the Village Development Council and 0.8 by the Village Land Conciliation Commission.

A comparison of the results in Exhibit 28 and 29 suggests that, for some village authorities, the responses suggest that more land disputes resolved (Exhibit 28) than were presented (Exhibit 27). For example, Exhibit 29 indicates that CVDs, on average resolved 2.3 land disputes while they were presented 2.1 land disputes, on average (Exhibit 28). This result is puzzling and raises issue on the accuracy of the data.

Exhibit 29: Average Number of Resolved Land Disputes by the Village Authorities

Treatment Comparison Total

Chef de terre 2.5 2.1 2.3

City Council 1.8 1.4 1.6

Village Development Council (CVD) 2.3 1.7 2.0

Village Land Conciliation Commission (CCFV) 1.0 0.4 0.8

5.4 Data Issues Encountered

Although we are not aware of specific data collection issues in the field, a review of the data suggests that there are a number of data issues that could affect the quality of the data sets for analysis. Some of the specific issues are discussed below.

One of the serious problems identified is the reported number of CCFVs at baseline in treatment and comparison areas. As explained above, although both treatment and

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comparison communes might have set-up their own CCFVs at baseline, it is unclear whether they were operational at the time of the baseline survey, yet the data indicates that they were in place.

More disturbing is the fact that the data indicates that CCFVs in both treatment and comparison areas were resolving land disputes. If CCFVs were not in operation at the time of the baseline, how could this be? Given these serious data issues, we suspect that the data might not be usable for the impact analysis.

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6. COMMUNE SURVEY

The purpose of this survey was to collect information on the characteristics of communes, land conflict administration, and total land surface area. This survey covers all 59 rural communes in both the treatment and comparison areas. The information collected in the questionnaire seeks to complement the information from the household and village questionnaires.

6.1 Number of Interviewed Individuals

The commune-level data was collected from 204 male and female community leaders occupying various community positions, such as municipal counsel and religious chiefs (See Exhibit 30). There were up to five individual respondents per commune and one response was collected for each commune question. There were 33 women among the 204 respondents.

Interviewers administered the questionnaire to a group of representatives of the commune and/or commune staff. Informants were required to have worked in the commune for a number of years. The groups gathered in a meeting room and had to reach a consensus before answering each question. Enumerators reported disagreements when the group was unable to reach a consensus.

Exhibit 30: Sample of the Commune Survey

Treatment Comparison Total

Communes 30 29 59

Male respondents 89 82 171

Female respondents 19 14 33

Total respondents 108 96 204

6.2 Survey Instruments

The commune survey used a questionnaire composed of five modules, each focused on a different area of interest (See Exhibit 31).

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Exhibit 31: Survey Modules

1. Identification of the commune 2. Characteristics of individual respondents 3. Activities in the commune in the past 12 months 4. Administration of land conflicts and services at the commune level 5. Total land area

6.3 Distribution of Key Variables

Household Land conflicts were identified in 47 out of 59 communes (See Exhibit 32). Specifically, 26 communes in the treatment areas and 21 communes in the comparison areas had land conflicts. There were a total of 734 land conflicts reported in the last 12 months (431 in treatment communes and 303 in comparison communes). Over the same period, 441 were resolved (227 in treatment and 214 in comparison communes). On average, 16.0 land conflicts were reported per commune and 10.5 were resolved.

The responses also indicated that 40 communes had access to land ownership services (services fonciers ruraux, SFR), with large differences across treatment (30) and comparison (10) groups. This last result appears questionable. Although control communes might set-up their own SFRs, the large number of control communes (33%) listing a SFR at baseline is puzzling since SFRs may not have been operational at the time of the baseline. Thus, this remains a potential data quality issue that will be investigated further upon receipt of documentation about detailed implementation dates of SFRs in the various communes.

Exhibit 32: Commune Characteristics

Treatment Comparison Total

Total number of communes 30 29 59

Communes with identified conflicts 26 21 47

Total number of identified conflicts 431 303 734

Total number of resolved conflicts 227 214 441

Average number of identified conflicts 16.6 15.2 16.0

Average number of resolved conflicts 9.5 11.9 10.5

Communes with SFR 30 10 40

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6.4 Data Issues Encountered

IMPAQ identified some data issues that could affect the overall quality of the data sets for analysis. As described above one data issue is the number of SFRs reported in the treatment and comparison communes.

Another issue is the significant number of missing values in important variables. For example, the village land surfaces area was to be collected as part of the commune survey. An examination of the data, however, reveals that the data for many villages are missing. Section E of the questionnaire lists the surface area of all villages in the sample, but many of the entries are missing. Specifically, only 177 villages out of the total 357 villages in all communes are listed and only 40 of these 177 villages have values for the total land surface varaiable. BERD has attributed the missing observations to the lack of official documentation at the commune level to confirm actual surfaces. Interviewers had been instructed to record data after reviewing the available official administrative records and registers.

The issues raised above regarding the presence of SFRs and the large number of missing data may present a problem for the usability of the data for the impact analysis. It may be possible to correct the missing data issues since the land area data can still be collected from official records (if they exist). However, such an effort will require additional time and resources to correct.

As a result of these issue, it is not clear if the commune survey data is usable for the impact analysis.

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7. CONCLUSION

A review of the household and field manger data, suggest that there were some difficulties encountered in the field. However, IMPAQ believes that, in general, the issues were identified and appear to have been corrected by BERD. Furthermore, these issues most likely affected only a small proportion of the sample. As a result, we are confident that the collected household and field manager survey data is adequate for the impact evaluation.

On the other hand, the village and commune data may not be of sufficient quality for the impact evaluation. Upon receipt of additional documentation about the various implementation dates of the land institutions, we will be able to investigate these data further. If the village and commune data prove to be “erroneous”, we might not be able to use them for the impact evaluation analysis.

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REFERENCES

For the preparation of the report, IMPAQ reviewed the following documents:

Méthodologie et Plan du Travail. BERD. September 2013.

Compte Rendu de Réunion du 02 Octobre sur l’Etat de l’Enquête de Base sur le Foncier Phase II. BERD. October 2013.

Rapport Technique sur les Activités de Terrain: Enquête de base sur les ménages et l’agriculture. BERD. January 2014.

Rapport de BERD sur la Collecte de Données de Terrain dans le Cadre de la Phase 2 du PSF. BERD. June 2014.

Impact Evaluation of MCC Projects in Burkina Faso: Findings from IMPAQ Mission. IMPAQ. February 2012.

Preliminary Evaluation Design Report Impact of the Agricultural Development Project and Rural Land Governance Project. IMPAQ. August 2012.

Sabo, T. Rapport sur le Contrôle de l’Exécution et des Résultats de l’Enquête Test sur le Foncier – Phase II 2013. September 2013.

Memos and emails exchanged between IMPAQ and MCA/MCC over the life of the evaluation project, including: Comments on Baseline and Follow-up Data Rural Land Governance (RLG) Burkina Faso. IMPAQ. August 16, 2012. Sampling Phase II Rural Land Goverance Project (RLG) Burkina Faso. IMPAQ. October 17, 2012. Phase II Rural Land Governance Project (RLG) Comparison Commune Selection Burkina Faso. IMPAQ. November 5, 2012. Phase II Rural Land Governance Project (RLG) Comparison Commune Selection – Revision Burkina Faso. IMPAQ. December 3, 2012. Phase II Rural Land Governance Project (RLG) Comparison Commune Selection, Questionnaires and Sampling Burkina Faso. IMPAQ. December 21, 2012. Phase II RLG Project Village Sampling Burkina Faso. IMPAQ. February 17, 2013. BERD RLG 2 data files [Stata format].

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APPENDIX 1: FINAL STATE OF DATA COLLECTION

TREATED VILLAGES

Number of Number of Village Commune households to households sample sampled BANZON Banzon 24 24 KOUNSENI Banzon 8 8 YORGO Bere 16 16 BOUNOMTORE Bere 8 8 GOGHIN Bere 8 8 MAZOARA Bere 24 24 KAIBO-SUD V1 Binde 8 8 SONDRE-EST Binde 8 8 LILGOMDE Binde 8 8 TIGRE Binde 8 8 SINIKIERE Binde 8 8 KAIBO-CENTRE Binde 16 16 TOEYOKO Binde 8 8 KOAKIN Binde 16 16 KANKAMOGRE-PEULH Bittou 8 8 ZEKEZE Bittou 8 8 MOGANDE Bittou 16 16 KANYIRE Bittou 8 8 MOGANDE-PEULH Bittou 8 8 LOABA Bittou 16 16 GNAGDIN Bittou 8 8 KANKAMOGRE Bittou 8 8 FOTTIGUE Bittou 8 8 SAWENGA Bittou 16 16 BIRON-MARKA Bourasso 16 16 KAMIANKORO Bourasso 8 8 LEKUY Bourasso 8 8 KASSOLO-TIABONA Cassou 8 8 NEVRY Cassou 8 8 CASSOU Cassou 16 16 OUPON Cassou 8 8 GUILLAN Cassou 8 8 NIESSAN Cassou 8 8 BAZAWARA Cassou 8 8

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Number of Number of Village Commune households to households sample sampled KADAPRA Cassou 8 8 OUAYOU Cassou 8 8 KYA Didyr 8 8 POUNI-NORD Didyr 8 8 IMOUGOU Didyr 8 8 LADIANA Didyr 8 8 DIDYR Didyr 16 16 MOUZOUMOU Didyr 16 16 DJIGOUE Djigoue 8 8 BAWE-DARA Djigoue 24 24 GONGOMBOULO Djigoue 8 8 DOUNA Douna 16 16 MONSARA Douna 8 8 TERI-SAMO Gassan 8 8 DJIN Gassan 8 8 SONI Gassan 8 8 DJIMBARA Gassan 8 8 GASSAN Gassan 16 16 WAROU Gassan 8 8 MOARA-GRAND Gassan 8 8 LERY Gassan 8 8 MARA-GRAND Kassoum 8 8 BAN Kassoum 8 8 TOUNGOUROU Kassoum 8 8 BOURGOU Kassoum 8 8 DOUBAN Kassoum 8 8 PINI Kassoum 8 8 SAKOINSE Kokologho 8 8 PITMOAGA Kokologho 8 8 DOURE Kokologho 8 8 GOULOURE Kokologho 8 8 KOKOLOGHO Kokologho 48 48 TANVI Koubri 8 8 TANSABLOGO Koubri 8 8 MOINCE Koubri 8 8 PEELE Koubri 16 16 KOUBRI Koubri 32 32 PIKIEKO Koubri 8 8 IMPAQ International, LLC Page 34 RLG Phase II - Data Quality Review Report

Number of Number of Village Commune households to households sample sampled NAPAGTING-GOUNGHIN Koubri 8 8 DIDRI Koubri 8 8 SABLOGO Lalgaye 8 8 DIBLI Lalgaye 24 24 GOURAN Lanfiera 8 8 KOUMBARA Lanfiera 16 16 GUIEDOUGOU Lanfiera 16 16 MOUSSODOUGOU Moussoudogou 16 16 MONDON Moussoudogou 8 8 TIMPERBA Niangaloko 16 16 DANGOUINDOUGOU Niangaloko 8 8 KIMINI Niangaloko 16 16 NOFESSO Niangaloko 8 8 KARABOROSSO Niangaloko 8 8 OUANGOLODOUGOU Niangaloko 8 8 LAHIRASSO Padema 16 16 KOLEDOUGOU Padema 16 16 KIMINI Padema 8 8 DJIGOUEMA Padema 16 16 BANWALI Padema 8 8 SOMA Padema 8 8 BANKOUMA Padema 8 8 ZONGOMA Padema 16 16 LOAGA Poa 16 16 YARGUIN Poa 8 8 POA Poa 24 24 MENTAO Pobe-Mengao 8 8 CISSE Pobe-Mengao 8 8 GASKINDE Pobe-Mengao 8 8 BOUI-BOUI Pobe-Mengao 24 24 POBE-MENGAO Pobe-Mengao 8 8 ROLLO Rollo 24 24 POGORO Rollo 8 8 GONDEKOUBE Rollo 8 8 POGORO-FOULBE Rollo 8 8 KANGARE Rollo 8 8 BOUDTENGA PEULH Saaba 8 8 TANSOBENTINGA Saaba 16 16 IMPAQ International, LLC Page 35 RLG Phase II - Data Quality Review Report

Number of Number of Village Commune households to households sample sampled BAROGO Saaba 8 8 NIOKO I Saaba 48 48 KOALA Saaba 8 8 BADNOGO 2 Saaba 8 8 SAABA Saaba 40 40 BOUDTENGA Saaba 8 8 SIKORLA-DIERIKANDOUGOU Samorougan 8 8 KORKORLA Samorougan 8 8 SAMOROGOUAN Samorougan 24 24 SANA Samorougan 8 8 ZOUMAHIRI Samorougan 8 8 KONGOLIKORO Samorougan 8 8 N'GANA Samorougan 16 16 SANTIO Sapouy 8 8 BORO Sapouy 8 8 NABILPAGA-YORGA Sapouy 16 16 TIABIEN Sapouy 8 8 BAOUIGA Sapouy 8 8 LADIGA Sapouy 8 8 NEKROU Sapouy 8 8 LATIAN Sapouy 8 8 POUN Sapouy 8 8 KOUTERA Sapouy 8 8 BATE Sideradougou 8 8 GOUIN-GOUIN Sideradougou 8 8 KOUENDI Sideradougou 8 8 DEGUE-DEGUE Sideradougou 16 16 GOUANDOUGOU Sideradougou 24 24 KAPONGOUAN Sideradougou 8 8 KOUERE Sideradougou 16 16 SAMPOBIN Sideradougou 16 16 DANDOUGOU Sideradougou 8 8 DJANGA Sideradougou 8 8 DOUTIE Sideradougou 8 8 DEREGOUE I Sideradougou 8 8 BADE Sideradougou 16 16 SIDERADOUGOU Sideradougou 8 8 KELEGUERIMA Tangaye 8 8 IMPAQ International, LLC Page 36 RLG Phase II - Data Quality Review Report

Number of Number of Village Commune households to households sample sampled BOUNDOUKAMBA Tangaye 8 8 DOUMA Tangaye 16 16 LOUBRE Tangaye 8 8 MERA Tangaye 8 8 NAMSIGUIA Tangaye 8 8 RASSANDOGO Tangaye 8 8 TOPTIAGOU Tansarga 8 8 TANSARGA Tansarga 24 24 BODIAGA Tansarga 8 8 KOBDARI Tansarga 8 8 DIAFOUANOU Tansarga 8 8 BOBOMONDI Tansarga 8 8 POUN Tenado 8 8 TENADO Tenado 8 8 TIEBO Tenado 8 8 TIOGO Tenado 8 8 BATONDO Tenado 8 8 TIALGO Tenado 16 16 KOUKOULDI Tenado 24 24 KABORO Tenado 8 8 DOUDOU Tenado 8 8 TOUSSIANA Toussiana 8 8 NIANABA Toussiana 24 24 WEMPEA II Toussiana 8 8 GASDONKA Zimtenga 8 8 KALAGRE-MOSSI Zimtenga 8 8 KALAGRE-RIMAIBE Zimtenga 8 8 BANGRIN Zimtenga 8 8 MINIMA Zimtenga 8 8 BATANGA Zimtenga 8 8 TOTAL NUMBER OF INTERVIEWS 2008 2008

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CONTROL VILLAGES