may 2008 macartan humphreys columbia universitymh2245/drc/report.pdf · may 2008 macartan...

Community‐Driven Reconstruction in the Democratic Republic of Congo

Baseline Report

May 2008

Macartan Humphreys1

Columbia University

1 [email protected]. This report provides results from a baseline survey of communities in Eastern DR Congo. The survey was implemented by an IRC team led by Charles Lor with Patrick Milabyo and Vincent Witumbula. In addition we thank the Director of ISTM-Bukavu Prof. Chimanuka Bantuzeko and the students of ISTM-Bukavu, the Director of the Observatoire du Changement Urbain at Université de Lubumbashi, Professor Gabriel Kalaba, and the researchers of OCU-UNILU. Others at IRC also played a key role in the development of the survey instrument, Jana Frey, Lizanne McBride, Brian Sage, Adi Walker, and especially Jodi Nelson. Thanks also to Eric Mvukiyehe for help in testing the instrument and to Eric Mvukiyehe and Laura Paler for their help in drafting this report.

DRC TUUNGANE Evaluation Baseline Report [Revised May 2008]

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Executive Summary This report provides baseline information on demographics, welfare, and social and political attitudes of communities in Eastern DR Congo taking part in the IRC‐led TUUNGANE community derived reconstruction (CDR) program. The program is designed to support economic recovery, foster social cohesion, and improve the quality of governance. Built into the TUUNGANE program is a robust evaluation strategy designed to measure whether these objectives are in fact met. The evaluation strategy uses a first best method of randomized intervention which allows for the creation of a set of control communities that are similar to the TUUNGANE communities in every respect except for the presence of the program. A central component of the strategy is the comparison of outcomes between treated and control communities on a series of indicators before and after the intervention. Many of these indicators are drawn from the baseline survey described in this report. The baseline survey implemented by IRC is an extraordinary undertaking. In an area with little or no official data on welfare or governance indicators, the data produced by the survey provide an unprecedented opportunity to examine the conditions in the region. The survey contains information on close to 3000 respondents, along with their family members, drawn randomly from almost 600 villages throughout the areas of South Kivu, Maniema, and North and Haut Katanga. The data provide, in many cases for the first time, systematic information regarding the living conditions and attitudes of communities in Eastern DR Congo, including information on access to health and education, economic activity, levels of community cohesion and attitudes to governance and decision making. For each of these areas this report provides indicators of the present situation and a treatment of the variation in performance of different indicators across the region. The pattern that emerges is a nuanced one. The effects of the conflict have been extremely far reaching; across all regions our subjects suffered from the direct and indirect effects of violence. Perhaps the most dramatic measure is the fact that a full 61% of household members in the sample were reported as having been displaced at least once at some point during the period from 1996 to 2007; in addition many suffered directly from violence against them and family members. This violence corresponds to a decline in welfare conditions. The welfare indicators give a very clear message: conditions are very poor both as measured by outcomes and as measured by access to services. Housing conditions are basic with over 80% of the sample living in houses constructed of mud or (unbaked) mud bricks. The typical household has to walk 45 minutes to reach drinking water. 42% of the sample has had no access to education. 11% have suffered from severe sickness over the two weeks


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prior to survey implementation—although in these cases many respondents reported access to healthcare services. The results on social cohesion are more mixed. The vast majority of respondents report that they suffer no problems in terms of access to basic economic and social activities in their communities; they also report few problems for others. Nevertheless 10% report that new arrivals in villages make conditions harder and many report a resistance to welcoming new arrivals of particular sorts – notably ex‐combatants and foreigners. About one in five remarked on divisions in their villages based on wealth while others noted generational conflicts and conflicts based on place of origin. Finally there are clear, and somewhat surprising, results with respect to governance. Our respondents saw decision making power in their communities as being clearly vested in the hands of the village chief, and to a lesser extent in the hands of elders. Traditional chiefs from beyond the village are also influential. Community members and women and youth groups in particular play a relatively marginal role in the eyes of our respondents. This suggests in some ways a lack of a norm of public participation in decision making. Strikingly too, when asked who should play the biggest roles, the answers are similar: there is no evidence of a demand for more participatory decision making. Further exploration of political attitudes reveals however that while individuals believe that chiefs should be taking this prominent role, they also favor taking actions to hold chiefs accountable. Chiefs should be scrutinized and, for many, should face term limits. In addition many respondents take on these actions by attending meetings and meeting with chiefs and community members. With respect to development decisions however another pattern emerges from the data: for the allocation of funding and control over development projects a plurality of respondents prefers to see power being placed in the hands of development committees rather than in the hands of chiefs. These results provide a somewhat mixed position for the evaluation going forward. While the need for welfare improvements is clear, many of the attitudes that the CDR attitude hopes to promote are already strongly endorsed by many respondents. There is however substantial variation—indeed there is more variation that was found in the Liberia study—and this variation takes place both across regions and across individuals. Going forward the evaluation will examine both how aggregate levels change (does, for example, welfare improve on average) and how the variation between individuals and across regions vary (is there a rise or a decline in inequality? Do views become more cohesive in particular communities?).


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Contents

Executive Summary ...................................................................................................... 2

I Background ........................................................................................................... 7

II The Population .................................................................................................... 11

II.1 BASIC DEMOGRAPHICS ..................................................................................................................... 11 II.2 LINGUISTIC AND RELIGIOUS DEMOGRAPHY ........................................................................................ 14 II.3 EXPOSURE TO CONFLICT .................................................................................................................. 16

III Baseline Welfare ................................................................................................. 19

III.1 EDUCATION ................................................................................................................................. 19 III.2 HEALTH ....................................................................................................................................... 23 III.3 OCCUPATION ............................................................................................................................... 26 III.4 WEALTH ...................................................................................................................................... 27 III.5 ACCESS TO SERVICES AND AMENITIES ......................................................................................... 31 III.6 WELFARE PERCEPTIONS .............................................................................................................. 31

IV Social Cohesion and Divisions .............................................................................. 33

IV.1 ACCEPTANCE AND TRUST ............................................................................................................ 33 IV.2 DIVISIONS ................................................................................................................................... 36 IV.3 PARTICIPATION IN COLLECTIVE ACTION ........................................................................................ 36 IV.4 COHESION BETWEEN LOCALITIES ................................................................................................. 38

V Local Governance and Community Empowerment .............................................. 39

V.1 WHERE IS POWER LOCATED IN THE VILLAGES? ............................................................................. 39 V.2 POLITICAL ATTITUDES .................................................................................................................. 42 V.3 COMMUNITY ENGAGEMENT .......................................................................................................... 45 V.4 TRUST IN DECISION-MAKING BODIES ............................................................................................ 47

VI Conclusions ......................................................................................................... 49


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List of Tables Table 1: 2007 Household ................................................................................................................11 Table 2: 1996 Household ................................................................................................................12 Table 3: Language Demography by Region ....................................................................................14 Table 4: Religion .............................................................................................................................15 Table 5: Religion by Region ............................................................................................................15 Table 6: Injuries by Participation category ......................................................................................17 Table 7: Displacements by Region ..................................................................................................18 Table 8: Patterns of Participation by Region ...................................................................................19 Table 9: Educational Attainment by Time Period ............................................................................20 Table 10: Educational Attainment by Region (Percentage) .............................................................21 Table 11: Types of Sickness ...........................................................................................................24 Table 12: Reported Sickness by Region .........................................................................................25 Table 13: Access to Healthcare by Region .....................................................................................25 Table 14: Occupation by Region .....................................................................................................26 Table 15: Income Sources ..............................................................................................................27 Table 16: Asset Holdings ................................................................................................................28 Table 17: Median Asset Holdings: Regional Breakdown .................................................................29 Table 18: Wall Types ......................................................................................................................30 Table 19: Household Water Sources ..............................................................................................30 Table 20: Distance to Amenities ......................................................................................................31 Table 21: Perceptions of Economic Conditions in Village by Region ..............................................32 Table 22: Types of New Arrivals and Acceptance Levels ................................................................34 Table 23: Trust ................................................................................................................................35 Table 24: Who Can You Rely On? ..................................................................................................35 Table 25: Lines of Division within the Town ....................................................................................36 Table 26: Community Initiatives ......................................................................................................36 Table 27: Activity by Region ............................................................................................................37 Table 28: Who Contributes? ............................................................................................................37 Table 29: Committees Already in Place ..........................................................................................38 Table 30: Patterns of Political Access and Isolation ........................................................................39 Table 31: Who is Most Influential? ..................................................................................................41 Table 32: Who Should be Most Influential? .....................................................................................41 Table 33: Attitudes to Authority .......................................................................................................42 Table 34: Political Attitudes, Regional Breakdown ..........................................................................43 Table 35: Types of Political Access & Initiatives .............................................................................45 Table 36: Initiatives and Success Rates by Region ........................................................................47 Table 37: Median Shares of Project Funds by Region ....................................................................48 Table 38: Who should manage funds on behalf of the community? ................................................48


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List of Figures Figure 1: Regions Studied for Baseline ............................................................................................ 8 Figure 2: Cumulative Age distribution .............................................................................................13 Figure 3: Conflict Related Injuries ...................................................................................................17 Figure 4: Literacy rates by age and gender .....................................................................................20 Figure 5: Primary Education by Date of Birth ..................................................................................21 Figure 6: Primary Completion Rates by Region over Time .............................................................22 Figure 7: Sickness by Age ..............................................................................................................23


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I Background The International Rescue Committee (IRC), with its partner CARE International, is undertaking a major post‐conflict development initiative entitled TUUNGANE. Eastern Congo has been devastated by violent conflict for over a decade, resulting in massive loss of life and declines in welfare. With poverty being both a result and a predictor of violent conflict there is a real fear that Eastern DR Congo could be caught in a violence‐poverty trap. The goal of the initiative is to contribute to a response to these concerns. By establishing and strengthening participatory local governance committees at village, community, and regional levels, TUUNGANE aims to build stability by fostering social cohesion, improving governance, and strengthening citizens’ relationships with local government. The conduit to achieve these ends is village‐ and community‐level projects that contribute directly to socio‐economic recovery. The use of community driven reconstruction (CDR) projects in post conflict settings is a strategy that is increasingly used throughout the world. Major CDR projects have been implemented in Rwanda, Liberia, Sierra Leone, Indonesia and Afghanistan. They hold out the promise of creating change from the grassroots up. Yet, despite their growing popularity, there is little rigorous research describing whether and how effective they are.2 TUUNGANE has started, or plans to start, working in approximately 280 communities comprising approximately 1,400 villages in four of the country’s most war‐affected areas: South Kivu Province, Maniema Province, and Tanganyika and Haut Katanga Districts of Katanga Province (see Figure 1). These communities represent an estimated beneficiary population by project end of approximately 1,780,000 inhabitants. The program will deliver more than £12,300,000 worth of projects directly to the communities. This represents an average block grant of over £37,000 per community plus £1,250 per village, thus representing a contribution of £38 per household. Should the program follow the trend of similar projects—shown to have an average economic rate of return of 63%3‐‐TUUNGANE will put over £20 million into recipient local economies in the short run. If there is an average of two projects per village, TUUNGANE is similar in scale to 2,800 smaller initiatives currently targeting basic livelihoods for families through projects such as small scale rehabilitation and repair of communal infrastructure, village livestock or seed banks, and income generation for vulnerable groups. 2 For the case of Liberia a related evaluation of an IRC post conflict community-driven reconstruction (CDR) program is also underway, led by James Fearon and Jeremy Weinstein of Stanford University and Macartan Humphreys of Columbia University. 3 A review of economic recovery rates within Afghanistan’s National Solidarity CDR programmed is found in Morelli, Juan, “NSP Cost Effectiveness Study” (November 2005).


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The approach taken by the program is to mobilize communities to manage resources towards implementing their highest priority development projects in a way that builds both social cohesion and linkages with local government institutions. Through this process, the aim is to contribute to increased stability in the region and the development of the principles of good governance.

The core objectives of TUUNGANE are to foster:

1. Economic recovery: Increasing socio‐economic activity, access to utilities and services, and welfare levels.

2. Social cohesion: Enhancing the trust people have in each other and the extent to which social relations are characterized by tolerance and inclusiveness.

3. Good governance: Strengthening local governance institutions and adherence to principles that allow for transparent, inclusive decision‐making; providing communities with the means to hold their leaders accountable, make collective decisions about development, and resolve differences peacefully.

Figure 1: Regions Studied for Baseline

South Kivu

Maniema

Tanganyika

Haut Katanga


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Built into the program is a robust evaluation strategy employing the first best method of randomized intervention. For the purposes of the evaluation program, impact is defined here as the difference the program makes for people in the areas of socioeconomic recovery, social cohesion and governance. A central component of the evaluation is an assessment of baseline conditions prior to IRC intervention. This document provides the first results from this baseline assessment, using a large survey undertaken with a random sample of almost 3000 participants from throughout the zones of intervention.4 The data from this survey provide the basis for a rich description of the baseline conditions in Eastern DR Congo in four areas:

1. Basic demographics of the region 2. Welfare conditions 3. Social Cohesion 4. Local Governance

For each of these areas the report provides indicators of the present situation and a treatment of the variation in performance of different indicators across the region. The pattern that emerges is a nuanced one. The effects of the conflict have been extremely far reaching; across all regions our subjects suffered from the direct and indirect effects of violence. Perhaps the most dramatic measure is the fact that a full 61% of household members in the sample were reported as having been displaced at least once at some point during the period from 1996 to 2007. In addition many suffered directly from violence against them and family members. This violence corresponds to a decline in welfare conditions. The welfare indicators give a very clear message: conditions are poor both as measured by outcomes and as measured by access to services. Housing conditions are very basic with over 80% of the sample living in houses constructed of mud or (unbaked) mud bricks. The typical household has to walk 45 minutes to reach drinking water. 42% of the sample has had no access to education and 11% have suffered from severe sickness over the two weeks prior to survey implementation. The results on social cohesion are more mixed. The vast majority of respondents report that they suffer no problems in terms of access to basic economic and social activities in their communities; they also report few problems for others. Nevertheless 10% report that new arrivals in villages make conditions harder and many report a resistance to welcoming new arrivals of particular sorts – notably ex‐combatants and foreigners.

4 For technical details on the survey as well as the survey document and manual, see: http://www.columbia.edu/~mh2245/DRC/


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About one in five remarked on divisions in their villages based on wealth while others noted generational conflicts and conflicts based on place of origin. Finally there are clear, and somewhat surprising, results with respect to governance. Our respondents saw decision making power in their communities as being clearly vested in the hands of the village chief, and to a lesser extent in the hands of elders. Traditional chiefs from beyond the village are also influential. Community members (and women and youth groups in particular) play a relatively marginal role in the eyes of our respondents. This suggests in some ways a lack of a norm of public participation in decision making. Strikingly too, when asked who should play the biggest roles, the answers are similar: there is no evidence of a demand here for more participatory decision making. Further exploration of political attitudes reveals however that while individuals believe that chiefs should be taking this prominent role, they also favor taking actions to hold chiefs accountable. Chiefs should be scrutinized and, for many, should face term limits; in addition many take on these actions by attending meetings and meeting with chiefs and community members. With respect to development decisions however another pattern emerges from the data: for the allocation of funding and control over development projects a plurality of respondents prefers to see power being placed in the hands of development committees rather than in the hands of chiefs. These results provide somewhat mixed implications for the evaluation going forward. While the need for welfare improvements is clear, many of the attitudes that the CDR program hopes to promote are already strongly endorsed by many respondents. There is however substantial variation—indeed there is more variation that was found in the Liberia study—and this variation takes place both across regions and across individuals. Going forward the evaluation will examine both how aggregate levels change (does, for example, welfare improve on average) and how the variation between individuals and across regions vary (is there a rise or a decline in inequality? Do views become more cohesive in particular communities?).


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II The Population We begin by providing a description of the population of individuals that are covered by TUUNGANE. Since the survey sampled all individuals in beneficiary (and a set of control) communities with equal probability, and since the beneficiary communities are themselves selected with equal probability, our sample of subjects constitutes a representative sample of all program beneficiaries. The population is drawn from four of the most war‐affected regions of Eastern DRC—two provinces (Maniema and South Kivu) and two districts (Haut‐Katanga and Tanganyika).5 A battery of questions was designed to help collect data on the demographic, socio‐economic and political conditions in these areas as well as a range of background variables that might shape the outcomes of interest or impact the efficacy of the program. Respondents were asked to provide detailed information about their household, including information about occupation, education, and wealth of all household members. This information was collected both for the current household (2007) and the prewar household (1996).

II.1 Basic Demographics The household roster provides basic demographic information for about 2,906 households, comprising a total of 21,467 individuals.6 16,383 of these individuals (or 76% of the sample) are members of current households, while the remainder were members of the respondents’ households in 1996 but are no longer living with them.

Table 1: 2007 Household

Region N

Median Household

Size Share Male Average Age Share < 18 Female Headed

Haut Katanga 2,843 7 0.52 20.9 0.54 0.11 Maniema 5,209 9 0.52 20.9 0.50 0.04 Tanganyika 4,195 8 0.51 21.0 0.52 0.05 South Kivu 3,999 7 0.51 21.8 0.50 0.12

Total 16,246 8 0.52 21.1 0.51 0.08

5 Note that region here does not necessarily refer to province only. It also refers to other administrative units (in this case the two districts of Katanga province) that were selected for IRC’s CDR program.


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Table 1 reports key information on household structure for the 2007 households. We see that the median household is large with 8 members, a figure which is considerably larger than the 5.5 household members estimated at the start of the TUUNGANE program. The population is young: half of all household members are below 18 years of age; three quarters are 31 or younger (see Figure 2). The postwar household has rough gender parity although the data report a slightly larger male than female population. These measures are largely consistent across regions, although the Katanga regions have relatively small households compared to the other areas. 92% of households are headed by men, although there is important variation on this measure, with the greatest levels of female‐headed households arising in Haut Katanga and South Kivu. As can be seen from Table 2 there are a number of systematic differences between the 2007 sample and our estimates of the 1996 sample. Based on our data the 1996 household was smaller with 7 members, younger, and comprised of more male members (and, in particular, was more likely to be headed by a man).

Table 2: 1996 Household

Region N

Median Household

Size Share Male

Average Age (in 1996) Share < 18

Female Headed

Haut Katanga 3,124 6 0.53 18.5 0.57 0.09 Maniema 4,114 8 0.55 19.6 0.54 0.03 Tanganyika 3,508 7 0.52 19.5 0.52 0.04 South Kivu 3,856 7 0.56 19.2 0.56 0.08

Total 14,602 7 0.54 19.2 0.55 0.06 These differences in household demographics likely result in part from the conflict dynamics. As was found in the Liberia baseline, although women suffered directly and indirectly from conflict violence, the mortality rate is considerably higher among men. Of 14,455 household members in 1996 (for whom it is known whether or not they are still alive), 6.1% have died since, with death rates higher among men (6.3%) than among women (5.9%). As we will see below, men are more than ten times as likely to be reported as dying due directly to violence. Other conflict related features can also account for these patterns. For instance, war orphans taken in by relatives can expand household size. Also, tougher economic conditions might increase the average age by which adults leave their parents’ households to establish their own.


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The gender breakdown for the full set of individuals in the roster is 52% male and 48% female. This breakdown is similar in pre and postwar periods and across the four regions. The majority of women (60%) are reported as being single; 35% as being married; 3% as being widowed and 1% as being divorced or separated. The picture is nearly identical for males. However, the share of single males is slightly higher (65%), while the share of males married, divorced or widowed is slightly lower than corresponding shares for females. The roster also recorded a non‐negligible share of female head of households: 212 out of 2,353 in 2007 households. Of these female head of households, 101 (or 48%) reported being married; 33 (or 16%) were recorded as being divorced or separated; 54 (or 26%) said they were widowed; and 21 (or 10%) reported being single.

Figure 2: Cumulative Age distribution

0.2

.4.6

.81

shar

e

0 20 40 60 80 100AGE2007

Age in 2007


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II.2 Linguistic and Religious Demography Eastern DR Congo is an extremely diverse region. A standard measure of the degree of ethnic fragmentation is the “ethnolinguistic fragmentation index” (ELF) which records the probability that two randomly selected individuals from a community speak different (first) languages. The ELF measure ranges from 0 in homogenous societies to 1 in perfectly heterogeneous societies. The ELF measure for the sample of 2007 households recorded in the survey is 90%. If it were a country, Eastern DR Congo would be classified as the second most diverse in all of Africa, next to Tanzania. Examination of language demographics within regions (see Table 3) highlights three additional points. First, there is a high level of language fractionalization even within regions. That is, while of course in each region there is a language spoken by the plurality of people, in none of the regions is a language spoken by the majority of the population. Each region has 2 to 4 languages that encompass the bulk of the population and about a dozen other languages spoken by only a few people. The second point is that there is very little (if any) overlap between languages across regions. That is, the predominant languages in one region are typically not predominant in another region. As shown in the table, Lega is the only major language that spans two zones (Maniema and South Kivu); all other major languages are predominant in one region only.

Table 3: Language Demography by Region

Haut‐Katanga Maniema Tanganyika South Kivu

Name % Name % Name % Name % Largest group Sanga 30 Lega 38 Luba‐Katanga 35 Shi 47 Second largest Bemba 25 Bangubangu 26 Hemba 25 Lega 26 Third Largest Lamba 8 Kikusu 16 Taabwa 7 Havu 19 Finally, we note that this linguistic diversity persists, albeit to a smaller extent, at the village level. According to our data there is linguistic heterogeneity in at least a third of villages studied.7 The religious breakdown of individuals in the roster is reported below. Protestants (45%) and Catholics (37%) are the two largest religious groups, encompassing 82% of individuals in the sample. Representation of all other religions is very weak and well under 5% of individuals in the sample.

7 Note that the one third figure is a lower bound since only 5 individuals on average were surveyed in each village.


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Table 4: Religion

Percent (N)

Protestant 44.8

(9,366)

Catholic 36.9

(7,840)

Muslim 3.7 (796)

Jehovah Witness 1.3 (268)

Kimbanguiste 1.0 (220)

Anglican 0.9 (193)

No Religion 3.3 (678)

Other 7.9

(1,656) Table 5 shows the breakdown by region. As with language the aggregate heterogeneity is re‐produced at the regional level—in no one region is there a majority of the population affiliated with any one religion.

Table 5: Religion by Region

Haut‐Katanga Maniema Tanganyika South Kivu Catholic 39.1 33.7 27.9 48.5 Protestant 43.1 43.8 49.0 43.5 Muslim 0.6 8.1 3.7 0.8 Jehovah Witness 1.1 1.0 2.2 0.9 Kimbanguiste 1.1 1.2 1.6 0.3 Anglican 0.1 3.0 0.04 0.04 No Religion 7.1 1.4 3.2 2.3 Other 7.8 7.9 11.9 3.8 Total 100% 100% 100% 100% Protestants and Catholics occupy a predominant place in all four regions: 43% and 39% respectively in Haut‐Katanga; 44% and 34% in Maniema; 50% and 30% in Tanganyika;


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and 43% and 49% in South Kivu. However, while Protestants occupy the top spot in the first three regions, they trade places with Catholics in South Kivu. Furthermore, the margins between the top two religions vary considerably from anywhere as low as 4% (in Haut‐Katanga) to as high as 21% (in Tanganyika). Finally, the relative importance of smaller religions varies considerably. Muslims, for example, represent 8% of the population in Maniema while they are represented by less than one percent in Haut‐Katanga and South Kivu. As with ethnicity, there is more religious homogeneity levels at the village level; nevertheless, even here heterogeneity persists, indeed, based on our sample (of five households per village) only 50% of our town level samples have religiously homogenous populations.

II.3 Exposure to Conflict Since 1996, Eastern DR Congo has been ravaged by an intense and brutal conflict. To assess the extent to which different individuals, households and communities participating in TUUNGANE were affected by the war, the survey gathered basic data on exposure to the conflict through displacement, injury, and death. In addition, we collected basic data on participation in the fighting factions. These data will serve to provide estimates of the extent to which the CDR program is more effective in high conflict versus low conflict areas, and whether community cohesion is greater or less in communities with larger numbers of excombatants.

II.3.1 Injuries

The recorded data report that about 1.6% of household members in the sample suffered war related injuries at some point during the period from 1996 to 2007. On average this is equivalent to one war related injury in every eight households. About one third of these injuries were local in origin ‐‐ perpetrated by a fellow village member ‐‐ while the rest were perpetrated by individuals from outside the village, and likely belonging to armed groups. Looking over time these injuries occurred in two waves, the first at the height of the second Congo war (around 1998), the second in 2003, during a time at which peace deals were meant to be implemented and formal power sharing established among rival factions.


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Figure 3: Conflict Related Injuries

010

2030

40N

umbe

r of V

iole

nce

Rel

ated

Inju

ries

1995 2000 2005 2010Year

There are some important differences across regions. Haut‐Katanga has the lowest share of household members injured by either two of perpetrator (about 1/10th of a percent for each); while Maniema has the highest injury rates, totaling over 2%. Table 6 provides more insight into the pattern of these injuries. Most of the victims of injuries were civilians, not combatants. Nevertheless, it is not the case, according to our data, that life was safer inside the fighting factions. While the probability of sustaining an injury was 1% for civilians, it was 20% for combatants.

Table 6: Injuries by Participation category

. Not Injured Injured Total Civilian 17,741 208 17,949 Combatant 369 92 461 Total 18,110 300 18,410


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II.3.2 Displacements

The baseline survey gathered data about the number of displacements due to armed activities, the years in which these displacements (first) took place, the locations to which households fled, and when households returned (if at all). The data show extremely high levels of displacement. A full 61% of household members in the sample were reported as having fled at least once at some point during the period from 1996 to 2007 due to armed activities by organized armed groups or militias. The graph below presents the total number of (first) displacements by year.

Figure 3: Population Displacements by Year

010

0020

0030

00N

umbe

r of I

ndiv

idua

ls F

irst D

ispl

aced

1990 1995 2000 2005 2010Year

This figure reports the number of people in our sample displaced for the first time in each year

since 1990. For many the initial displacement took place early on in the conflict, between 1996 and 1998, reaching a peak in 1997. There was however substantial variation across regions. South Kivu suffered the most intense levels of displacement, with rates reaching 71%. Displacement occurred considerably later and with much lower rates in Haut Katanga.

Table 7: Displacements by Region

Share

displaced Median Year of

First displacement Median Year of

Return Haut‐Katanga 25 2004 2006 Maniema 66 1997 2003 Tanganyika 67 1998 2001 South Kivu 71 1998 2000


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II.3.3 Patterns of Participation in Armed Groups

Approximately 2% of household members are estimated to have participated in the conflict. Of these, less than one quarter are reported to have joined voluntarily and the rest are recorded as abductees. The median year for joining was 1999. The median joiner was 22 years old, although 25% of abductees were aged 15 or less at the time of their recruitment. There is again considerable variation on this measure. Haut Katanga has by far the lowest participation rate—with total participation rates totaling one fifth of one percent. The reported participation rates in Maniema are however very high, at 4.5%.

Table 8: Patterns of Participation by Region

Number of Excombatants

Joining Probability

Median Age at joining

Haut Katanga 9 0.2% 21 Maniema 286 4.5% 23 Tanganyika 96 1.9% 19.5 South Kivu 75 1.5% 22

Total 466 2.2% 22

III Baseline Welfare To generate estimates of baseline welfare conditions, the survey collected a series of measures of basic education and health levels, access to education and health services, and economic activity.

III.1 Education The roster records that about half of the people in our sample have basic literacy skills as reported by the respondents in their households. Figure 2 shows the breakdown by age and gender. The patterns reported by this figure are very informative. For all age groups, male literacy is higher than female literacy. This gap grows larger for individuals in older age cohorts. The graph thus provides evidence of a narrowing of a gender gap in this region over time. We note, however, that while much narrower among youths, gender gaps still persist: In the 15‐20 year old range, male literacy is 76% whereas female literacy is only 62%. Finally we note that the graph peaks late ‐‐ the highest rates arise for individuals in their very late teens or twenties. If literacy were to arise mostly from primary schooling, we


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would expect an earlier peak. This late peak could in part reflect a disruption in education due to the war.

Figure 4: Literacy rates by age and gender

0.2

5.5

.75

1Li

tera

cy R

ates

0 20 40 60 80 100Literacy by age

Note: the upper red line represents male literacy; the lower blue line represents female literacy.

Table 9 provides formal educational achievement rates broken down into four categories: (i) the none category encompasses individuals who were reported to have 0 years of formal schooling; (ii) some primary schooling includes individuals who were reported as having at least one year of formal schooling; (iv) some secondary schooling encompasses individuals who were reported to have between seven and 12 years of formal schooling; and (iv) post secondary schooling includes training both in university and in technical colleges. Overall achievements in formal education are very low. 77% of individuals in the sample have only some elementary schooling or no schooling at all. More specifically, 42% have no formal schooling and only 1% have received some post secondary education. In addition, as seen in Table 9, these rates represent a significant decline relative to the 1996 distribution.

Table 9: Educational Attainment by Time Period

Level of Education 1996 2007 None 32% 42% Some Primary School 38% 35% Some Secondary School 28% 22% Post secondary 1% 1% All 100% 100%


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Figure 5 provides an indication of the extent to which access to education depends on historical circumstances. The chart displays the share of individuals born in a given year that has attended at least one year of primary schooling, focusing on individuals aged under 50. The chart records a modest rise in average education rates over time, driven largely by increased access to education for girls. The gains, however, are halted and reversed in the 1980s. Girls born in 1990 – who were of school going age when the war broke out – are about 6 percentage points less likely to have achieved any primary schooling than girls born 10 years previously. The sharp decline at the tail of the graph can be in part accounted for by late start ages, the figures indicate that only 70% of ten year old girls (girls born in 1998) have received at least one year of primary school education.

Figure 5: Primary Education by Date of Birth

0.2

5.5

.75

1S

hare

with

at l

east

one

yea

r prim

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educ

atio

n

1960 1970 1980 1990 2000Primary Education by Date of Birth

Note: the upper red line represents male primary school access rates; the lower blue line represents female access to primary education.

Levels of educational attainment across the four surveyed regions were also examined. The table below summarizes findings and patterns.

Table 10: Educational Attainment by Region (Percentage)

Haut Katanga Maniema Tanganyika South Kivu Total

None 35 38 43 51 42 Some Primary School 50 33 34 28 35

Some Secondary 14 28 23 20 22 Post Secondary 1 1 1 1 1 Total 100 100 100 100 100


22

Tanganyika and South Kivu have the highest percentage of individuals who are reported to have had no formal education (43% and 51% respectively; corresponding figures for Haut‐Katanga and Maniema are 35% and 38%). Overall Haut Katanga has the highest rates of individuals receiving some formal education (65%). Strikingly, however, Haut Katanga also has the lowest rates of post primary education. The pattern then is one of broader basic education but less advanced education in this region. Educational attainment with respect to university and vocational schooling is almost non‐existent across the four regions. In none of these regions did the percentage of individuals reported having some college education or vocational training reach 1%.

Finally, in Figure 6 we provide a breakdown of primary school completion rates by region for all individuals born between 1975 and 1995. Note that under normal conditions individuals born in 1994 or 1995 would have completed primary school at the time of the survey. Individuals born in 1984 would have completed their primary education just before the start of the war; individuals born after 1984 would have had their primary education interrupted by the war.

Figure 6: Primary Completion Rates by Region over Time

0.2

.4.6

.8Sh

are

that

hav

e co

mpl

eted

prim

ary

scho

ol

1975 1980 1985 1990 1995Date of Birth

Haut Katanga ManiemaTanganika Sud Kivu

The figure shows that Haut Katanga has had the lowest completion rates in recent years with a decline setting in even prior to the onset of the war (that is for individuals born before 1984). A similar pattern holds for Maniema. In other regions the decline sets in around 1984, likely corresponding to interruptions due to the conflict. A number of factors may account for this decline across all four regions. Most obvious is that schools were closed down and individual students were displaced or in some cases


23

left to join fighting factions. But other dynamics may also be in operation. Notably families, facing greater hardship, may have been unable to support children in school or had a greater need for their labor.

III.2 Health The survey also records information regarding health conditions of current household members. For all individual household members the survey asked whether that individual had fallen ill over the previous two weeks to the point that he or she was not able to go to school or to work. Recorded responses indicate that sickness was common among household members in the sample, with 11% reported as being sick at some point two weeks prior to survey implementation. As indicated in Figure 7, sickness was most common among the very young, where it reached 20%; among older members sickness rates were close to 30%. Individuals in their late teens and early twenties had sickness rates of between 5 and 10%.

Figure 7: Sickness by Age

.05

.1.1

5.2

.25

.3Pr

obab

ility

sic

k

0 20 40 60Age

Table 11 shows the most prominent types of sicknesses. By far the most prominent are fever and malaria which together account for close to half of all reported illnesses. Rates of illness were high among young children and for these we collected more detailed data. Among young children (aged under 7), 23% were reported as having fevers, 19% of having coughs (and in half of these cases infants were reported as having


24

a shortness of breath) and 10% were reported as having diarrhea (of these, one third were reported as having blood in their stools). Although comparisons should be taken with caution since these data are collected at a single point in time, we note this incidence rate is consistent with data collected elsewhere in sub‐Saharan Africa.8

Table 11: Types of Sickness

% Fever 28.1 Malaria 15.5 Cold 3.9 Measles 11.0 Diarrhea 7.4 Tuberculosis 5.8 Other respiratory diseases 2.5 Skin diseases & infections 1.7 Eye diseases & infections 0.9 Handicapped 1.5 AIDS 1.0 Cholera 1.1 Typhoid 0.3 Meningitis 1.7 Accident or Injury 0.1 Malnutrition 0.8 Weakness 0.6 Other diseases 16.2

Disaggregation of recorded responses revealed no noticeable differences in levels of sickness (regardless of sickness types) across gender or regions. Men were as likely as women to suffer from sicknesses (10% of the former and 12% of the latter were reported as being sick). Three of the four regions displayed a similar share of individuals suffering from different sicknesses. Haut‐Katanga had the smallest share (7%), followed by Tanganyika and Maniema (11% each) and South Kivu (13 %).

8 See for example Child Health Research Project Special Report 1998. “Childhood Diarrhea in Sub‐Saharan Africa.”


25

Table 12: Reported Sickness by Region

Region Share Sick over the

past 2 weeks

Haut‐Katanga 7

(2722)

Maniema 11

(5095)

Tanganyika 11

(4086)

South Kivu 13

(3786) The four regions were also strikingly similar in the types of predominant diseases. Fever was the most common disease, reported by at least 25% of household members in each of the four regions. Malaria was the second most common disease and was reported by 20% of household members all the provinces except Tanganyika where diarrhea is the second most common disease (reported by nearly 16% of household members). Other types of illnesses were important to varying degrees across the four regions. Measles and tuberculosis, for example, were the third and fourth most common diseases and were reported by 6% to 7% of household members in Maniema and Tanganyika. Diarrhea and Tuberculosis occupied similar positions in Haut‐Katanga and South Kivu and were reported by 4% to 7% of household members. The survey also asked questions about access to healthcare as direct follow ups on the sickness question. Recorded responses show a surprisingly high level of access to healthcare professionals. 73% of those that suffered from serious sicknesses were reported as having consulted a healthcare professional after getting sick. This level of access to healthcare remained relatively high across regions as indicated by the table below.

Table 13: Access to Healthcare by Region

Haut Katanga Maniema Tanganyika

South Kivu Total

None 30 20 24 34 26 Doctor 9 9 5 7 7 Medical Assistant 3 6 17 7 9 Professional Nurse 44 46 39 38 42 Herbalist 4 4 3 3 4 Pharmacist 7 13 9 4 9 Other 3 2 3 4 3 All 100 100 100 100 100


26

Maniema has the highest level of access to health care (80%), followed by Tanganyika (76%) and Haut‐Katanga (70%). South Kivu has the lowest share of sick individuals who reported having consulted a healthcare professional (65%). While the level of access to healthcare across regions remained high overall, there is some variation in the types of healthcare sought in each region. Nurses were the most common type of healthcare professional consulted (57% of sick individuals were reported as having consulted a nurse); followed by pharmacists and assistant doctors (12% each) as well as trained doctors (10%). Traditional types of healthcare professionals are also represented, but in relatively small numbers. This stark difference between the employment of traditional and non‐traditional types is puzzling and we cannot rule out the possibility that there is a systematic underreporting of the usage of traditional healthcare providers.

III.3 Occupation Household members represented in the sample had a variety of occupations. Excluding the under 5 year olds from the sample, the three largest occupations comprise almost 90% of all household members. The largest share of household members in the sample (41%) corresponds to farmers, followed by students (37%) and unemployed (11%). All other occupations had very small shares (none surpassed a share of 3%).

Table 14: Occupation by Region

Haut Katanga Maniema Tanganyika South Kivu Total Farmer 45.8 38.8 37.4 43.6 40.8 Student 36.6 40.5 36.0 33.0 36.8 Unemployed 8.0 9.0 14.7 13.4 11.4 Trader 1.1 2.7 2.6 1.9 2.2 Teacher 0.9 2.0 1.6 1.7 1.6 Other Unskilled 1.6 1.2 1.9 1.8 1.6 Domestic worker 2.0 1.9 1.7 0.7 1.6 Fisher 1.0 0.5 1.6 0.4 0.9 Agro‐Pastoralist 0.9 0.5 0.2 1.2 0.7 Other Skilled 0.4 0.7 0.7 0.5 0.6 Public Office 0.5 0.7 0.7 0.5 0.6 Religious 0.1 0.7 0.3 0.5 0.5 Note: This sample excludes children under 5 years old. The broader occupational structure was similar for men and women, but men represented the biggest share of students (42% versus 31% for women), whereas women were more likely to be reported as farmers (48% versus 34% for men). The share of household members who were reported not having an occupation is virtually similar for women and men (12% and 10% respectively).


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As shown in Table 14, these patterns are broadly similar across regions. Differences exist however; Tanganyika for example has the highest reported unemployment rate, and Maniema the lowest, while South Kivu reported the lowest rates in education and among the highest rates in farming.

III.4 Wealth

III.4.1 Sources of Income

The post‐war economic structure is strikingly similar to the pre‐war economic structure with the sale of agricultural products being the most common source of income. In both periods, almost 50% of individuals in the sample drew their income from this source. Other important sources of income are sales of foodstuffs and income from small businesses (17% and 9%). In both periods, no other source garners more than 4%.

Table 15: Income Sources

Haut Katanga

Maniema Tanganyika

South Kivu All

Sale of Agricultural Products 64.7 44.4 34.8 46.6 47.9

Sale of other Foodstuff 6.7 27.8 14.6 16.9 16.4

Small Business 5.5 9.8 14.9 6.5 9.0

Salary /Government job 2.2 3.3 3.8 2.8 3.0

Sale of Fish 3.3 3.0 4.3 1.1 2.9

Casual Labor 2.5 1.0 1.2 3.6 2.1

Sale of Wood 4.5 0.5 1.0 1.5 1.9

Salary /Private Sector 1.3 1.0 0.5 0.8 0.9

III.4.2 Consumption: Meals

The extent of food consumption or security in a household is another way to gauge income. The standard question asked by the World Food Program (WFP) to evaluate food security—“how many meals did the household cook on the previous day”—provides a simple consumption measure. In the sample, 50% reported cooking two meals, while 45% reported cooking one meal. Less than 4% reported more than three meals, while three quarters of one percent reported no meal.


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III.4.3 Assets

We collected information on a number of household assets. In most cases asset holdings provide a proxy for wealth although in some cases assets were included if they were likely to indicate poverty. Bamboo beds, for example, are considered a poor substitute for wooden beds and straw mattresses are considered a poor substitute for foam mattresses. Information on the per capita distribution of small household assets in 1996 and 2007 households is given in Table 16.

Table 16: Asset Holdings

Asset 1996

Median 2007

Median 1996 Mean

2007 Mean

Difference in Means

Sheep 2 0 4.9 1.3 ‐3.63 Poultry 8 1 12.9 3.4 ‐9.52 Cows 0 0 0.6 0.1 ‐0.50 Pigs 0 0 1.6 0.5 ‐1.12 Rooms 2 2 2.6 2.3 ‐0.27 Chairs 3 1 3.2 1.9 ‐1.27 Wood Beds 0 0 1.2 0.7 ‐0.45 Sponge Mattresses 0 0 0.8 0.6 ‐0.26 Straw Mattresses 1 1 1.3 1.1 ‐0.24 Buckets 0 0 1.1 0.9 ‐0.23 Fans 0 0 0.1 0.1 ‐0.03 Oil lamps 1 0 1.0 0.6 ‐0.38 Radios 0 0 0.7 0.5 ‐0.25 Boats 0 0 0.1 0.1 ‐0.06 Bicycles 0 0 0.6 0.5 ‐0.13

The table shows a marked difference in asset ownership across the two periods. Across all measures the median holding is the same or lower in 2007 than in 1996. The average holdings are strictly lower across all measures (and in every case this difference is statistically significant at the 99% level). In this sense the survey documents a dramatic decline in asset ownership across the board. The types of assets hardest hit are livestock and poultries, which have decreased to as low as a quarter of 1996 levels. Other types of assets such as radios or bicycles also decreased from their 1996 levels, but not as dramatically. Several factors related to the civil war and subsequent insecurity between the two periods may help explain the difference in household asset ownership across the two periods. One is that armed groups operating in these areas may have looted these assets either as food rations or spoils of war. In addition, it may be possible that agricultural production decreased due


29

to armed activities or insecurity and thus people may have turned to livestock (which can be consumed directly) for food. A second observation is that in both periods, both the mean and median holdings of each type of asset are low in absolute terms. The median household ownership of straw mattress—considered a poor substitute for foam mattress— in both 1996 and 2007 while the median household ownership of a foam mattress across the two periods is 0. A final observation is that there is important variation across areas. As seen in Table 17, household asset holdings in Haut‐Katanga were lower than in all other areas in both periods and across all four asset types. Other rankings are less clear and there is no area that is wealthiest across all measures (although we note that Maniema had the greatest asset ownership in three of four measures).

Table 17: Median Asset Holdings: Regional Breakdown

Sheep Poultry Rooms Chairs 1996 2007 1996 2007 1996 2007 1996 2007

Haut Katanga 0 0 5 0 2 2 1 0 Maniema 4 0 12 3 3 3 2 1 Tanganyika 2 0 9 2 3 2 4 1 South Kivu 3 0 6 1 2 2 3 2

III.4.4 Housing

The survey also asked a series of questions designed to gauge levels of and changes in the the quality of housing. The results are given in Table 18. Overall, we see that the interregional variation in housing types is much more important than the inter‐temporal variation. While mud houses are most common in South Kivu, mud bricks are the dominant forms in all other areas. Baked bricks, cement and semi‐durable constructions are rare in all areas. Surprisingly, the shares associated with each type of material are virtually the same for both the 1996 and 2007 periods, although there appears to be slight deterioration from higher quality materials (baked bricks, stone, metal, semidurable and cement) to lower quality (mud, unbaked bricks, wood, plastic). This decline, from 7.6% to 5%, although substantively modest is significant at the 99% level. A somewhat similar pattern can be observed with roofing. Lower quality material such as straw comprised the primary roofing material reported for 1996 (75%) and 2007 (79%). However, in both periods, a non‐negligible portion of households (20% and 17% respectively) relied on metallic sheets, which is one of the high‐quality materials.


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Table 18: Wall Types

Haut Katanga Maniema Tanganyika

South Kivu

All (2007)

All (1996)

Mud 4.8 28.7 18.1 73.2 32.8 31.24 Plastic 0.8 0.5 1.5 0.3 0.7 0.49 Mud Bricks 84.0 63.4 74.8 13.7 57.2 56.37 Wood 7.3 0.5 1.8 6.4 4.2 4.38 Stones 0.0 0.0 0.5 0.8 0.3 0.34 Semi‐durable 0.5 0.3 0.2 3.9 1.3 1.66 Baked Bricks 2.4 6.3 2.5 1.2 3.0 4.95 Cement 0.3 0.3 0.7 0.1 0.3 0.45 Metal 0.0 0.0 0.0 0.4 0.1 0.11 Total 100 100 100 100 100

III.4.5 Water Sources

Households in our sample get water from a wide range of sources. The two common sources of drinking water are unprotected wells and rivers (accounting for approximately one third each in each period). Less common, but nonetheless important sources of drinking water in both periods are protected wells and public taps which together account for about one quarter of cases in 1996 but one third of cases in 2007. Across the board these figures suggest—surprisingly—that there was an improvement in the quality of the water sources available to households over the course of the conflict, a feature that could in part be due to a movement to more populated areas and to increased humanitarian assistance.

Table 19: Household Water Sources

Haut Katanga 2007

Maniema 2007

Tanganyika 2007

South Kivu 2007 All 2007 All 1996

Home tap 2.96 0.16 2.42 7.21 3.38 2.74 External tap 9.47 2.36 15.83 23.59 13.26 9.5 Protected well 14.94 25.98 9.85 27.39 19.9 15.39 Unprotected well 27.07 50.39 29.73 19.92 31.15 34.87 Rain water 0 0 0.81 0 0.19 0.19 Truck 0.3 0 0.16 0.26 0.19 0.04 River 45.27 21.1 41.2 21.63 31.93 37.27 Total 100 100 100 100 100 100


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III.5 Access to Services and Amenities Table 20 reports the distance in minutes walked to a range of services and amenities. The data show that average household is within an hour’s walk to the village chief, to water sources, and to a primary school. However, substantial walking is required to access a market, transport, hospital, police station, or secondary school. The amount of walking is also uneven across households. The median household walks half an hour for water, while 10% of households walk an hour and a half. The median household lives three quarters of an hour away from a secondary school while 10% of households have to walk for at least 3 hours.

Table 20: Distance to Amenities

Haut

Katanga Maniema Tanganyika

South Kivu

Total

Water 36 (20) 43 (30) 52 (40) 44 (30) 44 (30) Market 317 (60) 334 (60) 157 (60) 101 (60) 224 (60) Transport 396 (60) 702 (120) 360 (120) 131 (60) 386 (65) Primary School 92 (15) 50 (20) 45 (30) 37 (30) 56 (25) Secondary School 206 (60) 77 (30) 84 (54) 57 (45) 106 (45) Hospital 166 (60) 94 (40) 109 (60) 75 (45) 110 (50) Police Station 207 (90) 245 (90) 142 (90) 84 (60) 166 (60)

Groupement Chief 234 (120) 212 (60) 208 (120) 130 (80) 194 (90)

Village Chief 15 (5) 12 (5) 16 (10) 29 (5) 19 (5) Note: This table reports average time (median in parentheses), in minutes walking,

to the closest amenities of various types.

III.6 Welfare Perceptions Finally the survey gathered information about subject assessments of changes in welfare. How do individuals feel they fare relative to others? How do they feel economic conditions are compared to in the past? The results of these inquiries are shown in Table 21. The vast majority of respondents believed economic conditions in their village this year (2007) to be either identical (37%) or worse (48%) than they were last year. Only 8% of respondents reported current economic conditions in their village to be better than they were last year. The figures are more unbalanced for the question on comparisons with other villages. An overwhelming 68% of respondents reported that current economic conditions in their village were worse than those prevailing in other villages. Only 8.5% reported current conditions in their village to be better than those prevailing in other villages.


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Given the random sampling we note that if respondents had unbiased information and reported truthfully we would not expect to see more than 50% reporting that conditions are worse in their village than elsewhere. It is possible that the high numbers reporting poor conditions reflects a reporting bias, but it is also possible that this measure reflects a belief that things are especially bad locally; a perception that could have adverse implications for regional cohesion. While we cannot distinguish between these two accounts at this point, follow up data will allow us to examine whether participation in the program alters these perceptions. Finally, comparisons of individual perceptions of current economic conditions across regions suggest striking variation.

Table 21: Perceptions of Economic Conditions in Village by Region

Compared to Other Village Compared to Last Year Same Better Worse Same Better Worse

Haut‐Katanga 38.6 16.1 45.3 49.0 21.2 29.9 Maniema 29.1 7.9 62.9 45.6 14.4 40.0 Tanganyika 9.2 4.3 86.5 23.6 7.7 68.7 South Kivu 16.5 5.3 78.3 30.5 16.2 53.3 As seen in Table 21, the overall level of dissatisfaction with current economic conditions in villages is high, but some regions score better than others. With respect to the question asking respondents to make comparisons with other villages, for example, Tanganyika and South Kivu have the highest rate of dissatisfaction (87% and 78% respectively). The levels of dissatisfaction in Maniema are also high (63%), while Haut‐Katanga’s levels lie below 50%. A similar picture emerges with respect to the question asking respondents to make comparisons of current economic conditions with conditions that prevailed last year. Tanganyika again comes on top with 69% of respondents saying that current conditions are worse, followed by South Kivu with 53%. The shares of respondents with similar perceptions are more moderate in Maniema and Haut Katanga (40% and 30% respectively).


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IV Social Cohesion and Divisions A central goal of the CDR intervention is to strengthen social cohesion and provide channels for the resolution of conflict between groups. What are baseline levels of cohesion like in these areas? To answer the question the survey asked a set of questions aimed at identifying conflicts or tensions that may exist within and between communities as well as cleavages underlying them. Some questions focused specifically on sensitive issues such as the incorporation of returnees, new migrants, and ex‐combatants. Others inquired more generally about the nature of social tensions and the willingness of community members to cooperate with people of different backgrounds, including refugees from neighboring countries (such as from Rwanda and Burundi). The aim was to uncover some of the salient issues, differences, and tensions that may hinder the ability or willingness of community members to work together.

IV.1 Acceptance and Trust A direct measure of acceptance is constructed by asking respondents whether they have been refused access to social services or prohibited from undertaking economic activities by other community members. On this basic measure of cohesion the responses are overwhelmingly in the negative, with 98.5% of respondents claiming that no one has ever refused them access to social services or involvement in economic activities (in later analyses we will identify characteristics of those that do report such problems). Because individual respondents may be reluctant to report complaints of exclusion we also asked whether respondents knew of other individuals or categories of individuals (other than themselves) who were ever refused access to certain social services or prohibited from undertaking economic activities by some community members. The responses are strikingly similar to those given for the previous questions. For both questions, over 98% of respondents said that no one has been refused access to social services or involvement in economic activities. More variation was found on a number of more general questions on acceptance. In response to a more general question, 8% of respondents report that they felt they faced problems being accepted. In addition, 10% of respondents report that new arrivals (returnees or migrants) have worsened economic conditions in the village.


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To better understand the patterns of who is and is not accepted we asked a series of questions regarding the extent to which specific types of new arrivals would be made welcome or not in their communities. The results are shown in Table 22.

Table 22: Types of New Arrivals and Acceptance Levels

Type of Returnee Mean Returnees of One's Own Village

0.91 (2845)

Displaced from Other Villages 0.92 (2845)

Congolese Immigrants 0.93 (2845)

Non‐Congolese Migrants 0.44 (2845)

Former Combatants 0.74 (2845)

Members of Other Ethnic Groups

0.93 (2845)

Members of Other Churches 0.95 (2845)

Note: The question recorded 0 if the respondent felt the type of returnee would not be welcomed and 1 if they would be. The mean indicates the average score within this 0‐1 range.

The table uncovers clear patterns in the types of individuals that can or cannot gain acceptance easily in the communities of Eastern DR Congo. Respondents report a very high willingness to accept Congolese immigrants, whether originally from the respondent’s community or not and whether from the respondent’s ethnic groups or not. Two categories of individuals, however, receive low levels of acceptance: non‐Congolese migrants are considered welcome by only half of our respondents, and former combatants are considered welcome by only three quarters of respondents. Although in many post conflict societies there are concerns that former combatants have difficulties returning to their communities or settling in new ones, there is to date little direct evidence on the issue. The data from Eastern DR Congo provide a rare ability to assess this characteristic. The results are not encouraging, and suggest that reintegration attempts in Eastern DR Congo may face a substantial hurdle from receiving communities. Two other questions are used to assess trust within communities. The first asks hypothetically whether respondents would be willing to incur a financial risk on behalf of different sorts of people. The specific question generates a measure of trust by asking


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whether individuals would act as a guarantor for another for a loan. The results indicate that the likelihood of placing trust in others in this way declines rapidly with social distance. Individuals are ready to support family members, but only to support other villagers or co‐ethnics in two‐thirds of cases. Individuals support non‐co‐ethnics (from their village) approximately half the time but report a willingness to trust individuals from beyond their locality only two‐fifths of the time.

Table 23: Trust


My family 1.00 1.00 1.00 1.00 1.00 Other members of my village 0.73 0.58 0.69 0.58 0.64 Other members of my ethnic group 0.74 0.62 0.67 0.56 0.64 People from my locality 0.56 0.61 0.68 0.57 0.60 People from other ethnic groups 0.64 0.44 0.65 0.41 0.52 People from neighboring localities 0.40 0.38 0.54 0.38 0.42 Note: The question recorded 1 if the respondent reported that she would be willing to provide a loan to a person in each row category and 0 if not. The mean indicates the average score within this 0‐1 range. Similar patterns are found for a question that asks individuals from whom they feel they could borrow money in case of need. Three quarters feel that they could borrow from someone in their village, but only half feel they can borrow from individuals in neighboring communities. Again co‐ethnicity appears important here with 10% higher rates of reliance on co‐ethnics than on non‐co‐ethnics.

Table 24: Who Can You Rely On?


My family 0.93 0.91 0.98 0.93 0.94 Other members of my village 0.77 0.71 0.82 0.70 0.75 Other members of my ethnic group 0.73 0.75 0.74 0.61 0.70 People from my locality 0.63 0.74 0.77 0.66 0.70 People from other ethnic groups 0.67 0.60 0.71 0.46 0.60 People from neighboring localities 0.41 0.52 0.64 0.44 0.50 Note: The question recorded 0 if the respondent felt the type of returnee would not be welcomed and 1 if they would be. The mean indicates the average score within this 0‐1 range.


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IV.2 Divisions The survey asked a direct question to gauge the extent to which villages are divided along social, economic or other lines. The results provided in Table 25 suggest that the majority of respondents (68%) reported no divisive social or economic cleavage in their communities. In one third of cases however important cleavages were reported. 19% reported the existence of cleavages over wealth, while 8% reported intergenerational cleavages. There were also reports of cleavages over gender, religion, ethnicity and residency status, but these are considerably fewer. Religious divisions were mentioned by only 3% of respondents.

Table 25: Lines of Division within the Town

Region None Wealth Gender Generation Origin Religion Tribe Haut Katanga 76% 10% 11% 5% 3% 2% 2% Maniema 60% 25% 5% 18% 15% 3% 9% Tanganyika 89% 5% 1% 0% 3% 2% 1% South Kivu 50% 33% 6% 9% 14% 7% 10% All 68% 19% 6% 8% 9% 3% 6% Note: The table reports the percentage of individuals claiming that divisions of various types exist in the village to the extent that they inhibit the ability of groups to work together.

IV.3 Participation in Collective Action In the previous sections we focused especially on attitudinal data. Behavioral indicators can also be used however to estimate baseline cohesion rates. Our first measures record the share of communities that have worked together to invest in public goods of various times.

Table 26: Community Initiatives

In the past six months, has there been a community initiative to…

%

Rebuild a school or clinic 35.0 (2773)

Brush or clearing the road? 43.5 (2779)

Repair or widening the road? 35.0 (2755)

Dig or repair a well? 25.6 (2728)

Organize local defense? 10.3 (2675)

Increase agricultural productivity? 23.6 (2727)

Rebuild a school or mosque 0

(2113)


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We find that villages in our sample have been active in providing a range of goods, and have participated in building schools and clinics (35%), roads (35%) and wells (26%). In addition almost half of the communities have had recent initiatives in road clearing. There was however not a single report of a community action to rebuild a church or mosque. There is also here, as elsewhere, important regional variation. Road clearing – the most prominent activity globally – is undertaken by two‐thirds of Maniema’s communities but barely more than a quarter of the communities in Haut‐Katanga. Security provision is rare in all areas; it is reported by only 1 in 40 respondents in Haut Katanga but by 1 in 5 in South Kivu.

Table 27: Activity by Region

In the past six months, has there been a community initiative to… Brush or clearing the road? Provide security

Haut‐Katanga 27.1 (197)

2.4 (17)

Maniema 65.2 (432)

6.5 (40)

Tanganyika 36.4 (234)

20.8 (132)

South Kivu 46.6 (339)

12.1 (83)

Finally we examine who participates in collective action initiatives in general. We find that individual respondents place the village chief as the individual most likely to be active in providing public goods for the community. Following the chief they place themselves prominently as public good providers, marginally above the typical village member. Ethnic outgroup members are considered substantially less likely to contribute than ingroup members. People from outside the locality and ex‐combatants are considered the least likely to participate.

Table 28: Who Contributes?

How likely is… to contribute to provide public goods? The Respondent 0.68 Other Village Members 0.66 Individuals in neighboring villages 0.49 People from other ethnic groups 0.58 People from my locality 0.61 People from neighboring localities 0.48 Ex‐combatants in the village 0.52 The village chief 0.77 Note: A score of 0 corresponds to the response “not at all disposed” to

participate and a score of 1 corresponds to “fully disposed” to participate.


38

In many cases development initiatives such as these are led by development committees that are already active in these communities. Table 29 provides a profile of the types committees that exist along with basic information on their structures. The most prominent forms of pre‐existing committees are those oriented towards the development of education, health and agricultural productivity. These exist in at least a quarter of communities and, in the case of education, in nearly one half. In most cases—and in particular for the most common committees, these committees have been in existence for an extended period of time and overwhelmingly have an elected leadership, according to our respondents. These data then provide basic information about the development committee structure; qualitative evidence is needed, however, to determine in greater detail what the nature of these committees is.

Table 29: Committees Already in Place

Exists Meets

regularly

Has been in place for a year at least

Has an open membership

Has an elected

leadership Water 25% 88% 92% 88% 90% Roads 22% 90% 89% 89% 88% Erosion 8% 82% 88% 83% 80% Health 27% 89% 92% 86% 89% Education 46% 91% 96% 91% 93% Agriculture 28% 88% 90% 86% 88% Protection 11% 88% 90% 84% 78% Development 19% 90% 92% 85% 86%

IV.4 Cohesion Between Localities

We have seen above that willingness to trust and expectations of trust decline as one moves from the village to other localities. Individuals from other localities are not expected to be as ready to help one another out or to take part in the production of local public goods. Nevertheless there is no evidence of substantial divisions between localities, and respondents report a clear willingness to accept in‐migration from other localities. Table 30 reports relatively high rates of interaction with individuals beyond the respondent’s immediate communities, with about 50% of individuals engaging with others in some capacity over the previous month.


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Table 30: Patterns of Political Access and Isolation

During the last 30 Days has the respondent… Never 1 or 2 Times More

frequently Visited with someone from a 30 min walk village 34% 22% 45% Engaged in economic transactions with someone from a 30 min walk village 45% 16% 40% Visited with someone from a different locality 36% 19% 45% Did economic transactions with someone from a different locality 48% 14% 19%

To generate a direct measure of the extent of inter‐village cohesion we asked our respondents to consider the following hypothetical situation:

If this village received $1,000 from an NGO to spend on development projects, would you like to see the full amount spent in your community, or would you rather that there be two smaller projects, one for this community and the other in a neighboring community?

Respondents were split on this question, but overall the responses suggested a high level of intervillage cohesion. 52% reported that they would rather have two smaller projects, one for each community, while 47% reported that they would rather have one big project for their community. There was however substantial interregional variation: in Maniema 60% of respondents opted not to split the allocation while in South Kivu over 60% proposed a split.

V Local Governance and Community Empowerment

V.1 Where is Power Located in the Villages? The survey sought to assess beliefs about how local governing decisions are made and their beliefs and attitudes about how these decisions should be made. To study how decisions are made we examined what might be called positive and negative power – who can make things happen, and who can stop things from happening? Our interest lies in particular in understanding the extent to which individuals believe that community members are effective or whether they believe that decision making power is concentrated in the hands of a small number of individuals, such as the village chief or elders. To address the question we asked respondents to consider three hypothetical situations in which political decisions in the village would need to be made. Decision 1 involved two families in dispute over land rights—an issue of great material interest to individuals which in is often regulated by tradition; Decision 2 involves the distribution


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of private benefits to vulnerable social groups; and Decision 3 involves the selection of projects for public investment in the village. Decisions 2 and 3 most closely echo decisions at the heart of the CDR process. The CDR process formally places such decisions in the hands of community members. Here we ask who would normally control decisions of this form and who individuals think ought to control these decisions. For each decision individuals were asked to identify:

(i) the most powerful and second most powerful individual (or group of individuals) who can prevent a decision over land disputes from being made or once made, prevent its implementation;

(ii) the person who has the most influence and second most influence on how conflicts pertaining to these issues are resolved; and

(iii) the person who ought to be most influential and second most influential on how these issues are resolved.

Table 31 reports the results from the positive question: who is most influential? Overall, the results suggest a very large concentration of power in the hands of the village chief. Across issue areas the large majority of respondents indicated that village chiefs are the most powerful and most influential individuals across different types of issues. Elders came in second, with a healthy share of respondents perceiving them either as the most influential or second most influential individuals. Very few respondents perceived religious leaders as being the most powerful or influential, especially when it comes to preventing a decision from being made or implemented. However, a non‐negligible share of respondents perceive them to be (or believed they should be) the second most influential across the different types of issues. Community members, or community groups—such as women or youth groups—were generally not seen as central players in these decision making processes. Similar results (not reported here) obtain for the question on negative power, with the chief playing a clearly dominant role in decision making. Table 32 provides the responses to the normative question, who should be most influential. The striking finding here – consistent with similar results found in Liberia – is that the normative positions of the respondents are broadly consistent with their positive beliefs. Community members as well as women and youth groups are not only perceived to be marginally influential (in the sense that very few people believed they were among the most influential individuals), but also very few people believed they should be the most influential. This raises important normative questions since, based on the results for this question, there is no evident demand for a fundamental change to structures of power.


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Table 31: Who is Most Influential?

Land dispute

Identification of Beneficiaries Selection of Projects

#1 #1 or #2 #1 #1 or #2 #1 #1 or #2 Community members 3 6 5 12 5 10

Village chief 66 88 63 83 59 80

Elders 9 51 7 45 7 42 Religious leaders 4 16 12 32 12 29 Youth groups 1 2 2 4 2 6

Women's groups 0 1 0 2 1 3 Traditional chief (mwami/sultani)

8 19 5 10 7 14

State Representatives

7 13 4 7 5 9

None 1 4 2 5 3 7

Total 100% 100% 100% Note: This table reports the share of respondents who believe that individuals marked in the rows are among the most or second most influential in making decisions with respect to land disputes, the selection of beneficiaries and the selection of public projects.

Table 32: Who Should be Most Influential?

Land dispute Identification of Beneficiaries

Selection of Projects

#1 #1 or #2 #1 #1 or #2 #1 #1 or #2 Community members 3 8 5 11 6 14

Village chief 63 86 62 82 60 82 Elders 8 47 8 42 8 40 Religious leaders 7 21 14 36 12 32 Youth groups 1 3 2 6 2 7

Women's groups 0 1 1 3 1 5 Traditional chief (mwami/sultani)

10 19 4 8 6 10

State Representatives

6 12 3 6 3 6

None 1 3 1 4 1 4 Total 100% 100% 100% Note: This table reports the share of respondents who believe that individuals marked in the rows should be among the most or second most influential in making decisions with respect to land disputes, the selection of beneficiaries and the selection of public projects.


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V.2 Political Attitudes The survey also asked a series of questions with competing arguments concerning aspects of governance or political culture from which respondents were asked to choose one that was close to their own position as well as indicate the degree of agreement (either agree, agree strongly or no opinion) with the chosen position. One side (the left side of Table 33) presents “positive” statements, insofar as they are consistent with the philosophy of the CDR approach (for example, women and men should have equal rights as men or the use of violence should never be condoned), while the other side presents rival positions.

Table 33: Attitudes to Authority

Note: Questions in the table (although not in the survey) are given such that the A position is positive. Note that in every case the median position (marked in bold) corresponds to agreement with A. Almost all respondents were able to provide an opinion on one side or other and very few chose “neither” or “don’t know.” Overall, however, as seen in Table 33, survey responses tended to weight largely in favor of one or other option. Indeed, as seen in the table there is a very high level of agreement, across all questions, with positions that are likely to be normatively associated with the goals of the CDR program.

A (Positive Position) Strongly Agree with A

Agree with A

Neither Agree with B

Strongly agree with B

B (Alternative Position)

Scrutinize and question actions of the village chief

50 35 1 8 6 Defer to judgment of the

village chief without questioning

Scrutinize and question actions of national leaders

50 36 1 8 4 Defer to judgment of

national leaders without questioning

Scrutinize and question actions of provincial leaders

49 36 2 9 4 Defer to judgment of

provincial leaders without questioning

Nothing can justify the use of violence

38 34 6 13 9 Resort to violence if one's

concerns are not addressed

Never use position to favor family 46 29 2 14 8 One should use political position to favor family

members All people participate in economic decision‐making

26 26 2 20 26 Only the best informed

should participate There should be term limit for village chief

31 25 2 15 27 Village chief should stay

onto power for life Men and women should have equal rights and responsibilities

34 37 1 11 16 Women remain submissive

Women should have equal opportunity to take on socio‐administrative positions in the village.

40 40 1 10 9 Only men are capable of

governing and should take up such positions

Women should be eligible to preside over committees

41 32 1 13 12 Only men can preside over

projects committees


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Table 34: Political Attitudes, Regional Breakdown

Haut


South Kivu

All

Scrutinize and question actions of the village chief

0.6 0.7 0.6 0.6 0.6

Scrutinize and question actions of national leaders 0.7 0.6 0.5 0.6 0.6

Scrutinize and question actions of provincial leaders

0.7 0.6 0.5 0.5 0.6

Nothing can justify the use of violence 0.5 0.5 0.4 0.2 0.4 Never use position to favor family 0.7 0.5 0.3 0.4 0.5 All people participate in economic decision‐making

‐0.1 ‐0.2 0.2 0.2 0.0

There should be term limit for village chief

‐0.4 0.3 0.2 0.3 0.1

Men and women should have equal rights and responsibilities

0.2 0.4 0.5 0.2 0.3

Women should have equal opportunity to take on socio‐administrative positions in the village.

0.5 0.5 0.6 0.3 0.5

Women should be eligible to preside over committees

0.4 0.4 0.6 0.2 0.4

Note: This table shows the extent to which responses were in the direction of those consistent with CDR objectives. A value of 1 corresponds to a situation in which all respondents adopt such a position strongly and a value of ‐1 corresponds to a condition in which all respondents adopt the opposite position strongly. Thus a positive entry in this table implies that the average response supported position A. There is however important variation both across topic and across region. Although we saw that most respondents believe that chiefs should be among the most influential members of their communities, here we see that 85% also believe that community members should be more active in questioning and scrutinizing the actions of chiefs (the actual breakdown is 50% strongly agree and 35% agree with the statement). Only 6% strongly disagreed with this position, while 8% simply disagreed with the position. The overall percentage shares and breakdowns are fairly similar for statements scrutinizing national or provincial leaders. A large share of respondents also supported the position that violence, although relatively fewer “Strongly” agreed with this position. Again a large supported the position that one should never use their position to favor family members (72% and 75% respectively either agreed or strongly agreed with these statements). This result runs somewhat counter to the argument that there is a “moral economy” of corruption in which favoritism is broadly condoned. Favoritism may be condoned by beneficiaries but not by a cross section of the population. The questions that produced the greatest disagreement were with respect to the extent to the extent and forms of popular participation in decision making. Respondents were most divided on the question of popular participation in economic decision making with


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about half the respondents concerned that these issues are sufficiently technical that they should be left in the hands of experts. Although most respondents felt that there should be a term limit for village chiefs, over 25% strongly disagreed with the proposition. In contrast, responses about women rights, obligations and participation in all levels of governance are surprisingly high. The largest share of respondents (80%) either agreed or strongly agreed with the statement that women should have the same rights and obligations as men. 73% of respondents agreed with the statement that women should have equal opportunity to occupy socio‐economic positions in communities. Another 72% that women are as qualified and knowledgeable as men and should therefore be eligible to preside over committees that manage community projects. Examination across regions offers more nuanced patterns of responses; these patterns are summarized in Table 34. The questions regarding holding leaders produces little variation across regions; in all regions, nearly 50% of respondents strongly agreed with the normatively positive position, while another 35% to 40% simply agreed with the position. For two of these the responses were stronger in Haut Katanga than in other areas. Haut Katanga also has some of the most positive responses with respect to the use of force and the use of favoritism. In contrast there is a higher tolerance for the use of violence in South Kivu (where almost one third of respondents accepted the position that violence is sometimes needed to back up claims) and of favoritism in Tanganyika (where almost one third accepted the position that individuals should favor their family members when in office). Even in these cases however the majority supported the positive position. Differences across regions are more pronounced on the participation questions. While in Tanganyika and South Kivu most respondents supported broad participation in economic decision making this position was opposed by a majority of respondents in Haut Katanga and Maniema. Indeed in Haut Katanga 43% strongly opposed the position that there should be broad involvement of this form. Haut Katanga again stood out on the question of term limits with a majority strongly opposing the idea of placing limits on chief’s terms; in all other regions less than one in five strongly opposed the position and a majority supported it. The pattern in Haut Katanga – consistent with the global patterns we have been discovering – is of respondents who are supportive of a centralization of decision making in the hands of the chief but who nevertheless insist on holding the chief accountable (albeit not through the threat of replacement). Finally on the questions on gender equality broad majorities supported the positive positions in all areas. Responses to the three questions were in general highly correlated and patterns can be seen across regions. For all three questions Tanganyika reports the most positive answers. South Kivu reports the highest level of disagreement with the positive positions with over one third of respondents arguing that only men should preside over management committees in the village.


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V.3 Community Engagement A final section of the survey sought to investigate the degree of civic and political alertness (or access) as well as the level of community members’ involvement in the social, political and economic life of their communities. Several questions were used to measure the extent of political access, isolation or alertness including whether people knew the names of some national or local leaders, the extent of newspaper readership or radio listening and so forth. Recorded survey responses suggested a mixed picture of political access. While most respondents knew the name of the president (95%), only 49% of respondents knew the name of the prime minister. Only marginally more, 60%, knew the name of their representative to the national assembly. Most respondents (above 90%) knew the name of their more immediate local chiefs.

Table 35: Types of Political Access & Initiatives

Over the last six months have you… % (N)

Spoken at the meeting 67.8

(1,120)

Met with village chief 40.6

(1,134)

Met with committee members 29.0 (818)

Been consulted by committee members 21.5 (602)

Contacted the police or courts 13.6 (382)

Participated in a peaceful protest 9.2 (260)

Contacted the state 9.3 (264)

Contacted an NGO 19.1 (52)

This seeming lack of access to politics can also be seen in low levels of newspaper readership and radio listening. The large majority of respondents in the sample reported not having read a newspaper during the 30 days prior to survey implementation; 10% only once or twice; and 9% sometimes. Only 4% of respondents reported that they read newspapers quite often. The shares of radio listeners are higher; but even here almost 50% of respondents reported not having listened to Radio Okapi—one of the most popular radio stations in eastern DRC.


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The survey also asked more specific questions about individual initiatives such as whether the person met with a chief or a member of the project committee over the last six months to raise an issue. The table below presents aggregate responses.

The results indicate that the highest level of individual initiative was speaking at a community meeting—68% of respondents reported having done so. The next most common form of political action was meeting with a local chief (41%) and meeting with a member of a project committee (29%). Very few reported having contacted the police or courts (14%) or having participated in a peaceful protest (9%).

19% of respondents reported that their villages contacted an NGO to help start projects; only 9% reported that their villages approaches state institutions to help. There is some variation across regions with as many as one in five in Maniema and as few as one in twenty five in Tanganyika claiming to have contacted state representatives over the last 6 months; in Maniema one in three villages had contacted NGOs for support, in Tanganyika one in ten did. Across all regions however the broad pattern is one in which political action is taken locally through NGO rather than state channels; there is no evidence however that NGOs substitute for states in the sense that villages that contact NGOs are considerable more likely to also contact states (although we cannot attribute a causal effect to NGO contacts we note that the probability of contacting the state is .04 for villages that do not contact NGOs and .34 for those that do).

Respondents contacted the state or NGOs for support for a range of projects. The four main reasons for contacting a state were related to schools (27%); road construction and repairs (14%); clinics or health centers (11%); and water projects (10%). The reasons for contacting NGOs were largely similar: 14% of respondents contacted NGOs for school‐related projects; 12% for clinics or health centers; 11% for road construction and repairs; 16% for water projects; and 18% for seeds and equipments to increase agricultural production. In most cases these contacts did not lead to positive outcomes. Only 19% of respondents who contacted the state reported to have succeeded in getting their needs met, while 16% of those who contacted NGOs reported success. Because understanding the levels and patterns of individual initiatives are crucial for CDR programs, it may be useful to examine these patterns across the four regions. Table 36 presents the shares of respondents who reported having contacted the state or NGOs by region as well as the corresponding success rates.


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Table 36: Initiatives and Success Rates by Region

Took Initiative in Contacting… The State An NGO

N Percent Success rate

N Percent Success rate

Haut‐Katanga 45 6% 24% 63 9% 48% Maniema 126 18% 19% 225 33% 40% Tanganyika 28 4% 7% 55 9% 13% South Kivu 63 8% 20% 113 15% 30% The table shows that the success rates (or results) from these initiatives were much higher in Haut‐Katanga and Maniema (24% and 19% for state contact and 48% and 40% for NGO contact respectively). South Kivu came in close second with 20% success rates for state contacts and 30% for NGO contacts. Tanganyika was the worst performing region both in the levels of contacts initiated and in success rates.

V.4 Trust in Decision‐making Bodies We close our discussion of the baseline results with an examination of responses given by respondents to hypothetical scenarios in which individuals are asked to determine who they believe should make key allocation decisions in the community. Respondents were asked to consider a situation in which a certain amount of money ($1,000 in this case) is allocated to the village for developments projects. They are then asked what share they would like to be placed in the hands of individual citizens and what share would they entrust to some other entity such as the government or project committee for better results. Three questions were asked, in each case the respondents were asked to propose an allocation between how much should be held by villagers themselves and how much should be managed by (i) central government (ii) a community development committee and (iii) the village chief. Each question could be thought of as a (negative) taxation question in which individuals determine to what extent resources should be allocated privately and to what extent it should be allocated by various types of public bodies. As seen in Table 37 in all cases a large share of the resources were allocated to the public bodies with implicit preferred tax rates in the 30 – 40% range. Support for control by development committees is greatest, followed by control by the village chief and trailed by control by central government. The implicit tax rate for central government is however surprisingly high at 31% on average.


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Table 37: Median Shares of Project Funds by Region

Central Government Development Committee The Village Chief

Haut Katanga 29.6% 43.3% 34.8%

Maniema 43.0% 44.7% 43.9% Tanganyika 22.8% 27.5% 25.9%

South Kivu 30.0% 31.9% 27.8% All 31.4% 37.0% 33.1% A second question focuses more directly on this comparison across these different types of bodies. In this question respondents are asked to make a direct comparison to determine who they would like to see managing development funds in their communities. The results are given in Table 38. These figures provide a very clear ranking, consistent with the finding in Table 37: Citizens most trust village development committees to manage funds for their communities, with this trust strongest in Tanganyika. After development committees, villagers trust chiefs and after that NGOs. Only 1% of respondents claim that they would like to see central government managing these funds while 3% (driven largely by respondents in Haut Katanga) would trust Provincial government most.

Table 38: Who should manage funds on behalf of the community?

Haut


South Kivu

Total

The village Chief 38 26 33 30 32 A Development Committee 35 33 45 36 37 An NGO 15 30 17 23 22 Central Government 1 0 0 1 1 Provincial Government 7 1 1 1 3 Other 4 9 5 10 7

100 100 100 100 100 The overall picture is a divided one. While central government plays a weak role, our respondents are at present split down the middle on whether development decisions should be placed in the hands of traditional chiefs on the one hand or of community based development committees on the other. Consistent with previous findings, respondents are most likely to place trust in chiefs in Haut Katanga but in committees in other regions. In all cases while NGOs are trusted above central government they come a distant third relative to within village institutions.


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VI Conclusions The baseline data documents conditions in Eastern DRC prior to the beginning of the TUUNGANE program. The results confirm the dire welfare situation in the region: low levels of education, poor access to social services and amenities. It documents the severe effects of the conflict, high displacement rate and interruptions in investments in human capital as well as the consumption and destruction of physical capital. Beyond this the data provides rich information on the spatial distribution of these features across the zone. On measures of social cohesion and governance the data tell a more varied story. Key points of tension have been identified: individuals are relatively slow to welcome ex‐combatants and migrants from neighboring countries into their communities. They are less likely to trust individuals from other ethnic groups and from communities far from their own. However these features notwithstanding few report major tensions within their communities or problems of being accepted or participating in community activities. Although trust in government is weak, local trust appears stronger. Nevertheless considerable variation exists across communities in the extent of local cohesion and no questions admit no variation. This provides a relatively good basis for the evaluation as there is scope both to pick up improvements and to track deteriorations, should they occur. Finally on the measures of local governance and decision making a pattern emerges that is consistent with that found in the Liberia study but which may nevertheless be surprising for program designers. Across the board respondents already report a high level of agreement with normative positions that are consistent with the CDR approach—support for participatory decision making, support for women’s participation, support for dialogue rather than violence as a means to address problems. Again these beliefs vary across communities and across regions and so it should be possible to identify changes, if they occur. However the baseline is relatively high on these measures. With respect to decision‐making respondents reported that for a wide range of issues decision making not only is but should be concentrated in the person of the chief; although in most cases respondents asserted that chiefs; though they should be influential in decision making, should also be held to account. Although many respondents support term limits for chiefs we observe no broad calls for a change in power structures within villages. In many cases respondents village level development committees already exist and are already seen as legitimate groups for determining the use of development funds. Indeed, although respondents report faith in village chiefs, in a head‐to‐head decision about who should control development funds, in most regions most respondents support placing decision making power in the hands of community committees.

may 2008 macartan humphreys columbia universitymh2245/drc/report.pdf · may 2008 macartan...

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