KEY GENDER INDICATORS AND BASELINE IN FOUR SECTORSgmo.gov.rw/fileadmin/user_upload/Researches and... · gender principles as well as to fight gender based injustice and violence

KEY GENDER INDICATORS AND BASELINE

IN FOUR SECTORS

Governance, Agriculture, Infrastructure, and Private Sector

REPUBLIC OF RWANDA

July 2011

1GMO / Gender Monitoring Office

Gender accountability for sustainable development

KEY GENDER INDICATORS AND BASELINE

IN FOUR SECTORS

Governance, Agriculture, Infrastructure, and Private Sector

REPUBLIC OF RWANDA

2 GMO / Gender Monitoring Office


TABLE OF CONTENTS TABLE OF CONTENTS ............................................................................................................................ 2

ACRONYMES AND ABREVIATIONS ........................................................................................................ 3

LIST OF TABLES .................................................................................................................................... 5

EXECUTIVE SUMMARY ......................................................................................................................... 6

INTRODUCTION ................................................................................................................................... 7

1. Background and Justification ........................................................................................................ 7

2. Objectives .................................................................................................................................... 9

3. Definition of Concepts .................................................................................................................. 9

4. Methodology and Research Methods ......................................................................................... 11

1. Introduction ............................................................................................................................... 13

2. Presentation of gender Indicators in governance sector ............................................................. 14

3. Conclusion .................................................................................................................................. 32

Chapter II ........................................................................................................................................... 33

GENDER BASELINE AND KEY INDICATORS IN AGRICULTURE ............................................................... 33

1. Introduction ............................................................................................................................... 33

2. Presentation of Agriculture Indicators ........................................................................................ 34

3. Conclusion .................................................................................................................................. 43

Chapter III .......................................................................................................................................... 44

GENDER BASELINE AND KEY INDICATORS IN INFRASTRUCTURE .......................................................... 44

1. Introduction ............................................................................................................................... 44

2. Presentation of infrastructure indicators .................................................................................... 44

2. Conclusion .................................................................................................................................. 53

Chapter IV: ......................................................................................................................................... 54

GENDER BASELINE AND INDICATORS IN PRIVATE SECTOR .................................................................. 54

1. Introduction ............................................................................................................................... 54

2. Presentation of Private Sector Indicators .................................................................................... 55

3. Conclusion .................................................................................................................................. 63

CONCLUSION AND RECOMMENDATIONS ........................................................................................... 64

1. Conclusion .................................................................................................................................. 64

2. Recommendations ..................................................................................................................... 64

REFERENCES ....................................................................................................................................... 66

Appendix ........................................................................................................................................... 68

List of Contacted persons ................................................................................................................... 68



ACRONYMES AND ABREVIATIONS BDS : Business Development Services BNR : Banque Nationale du Rwanda BPFA : Beijing Platform for Action BRD : Banque Rwandaise de Développement CEDAW : Convention on Elimination of all forms of Discriminations Against

Women CNF : Conseil National des Femmes COOPEDU : Coopérative d’Epargne Duterimbere CSO : Civil Society Organization DFID : Department Fund for International Development EDPRS : Economic Development and Poverty Reduction Strategy EICV : Enquête Intégrale sur les Conditions de Vie des Ménages FFRP : Forum des Femmes Rwandaises Parlementaires GDP : Gross Domestic Product GIS : Geographic Information System GIZ : German Development Cooperation GMO : Gender Monitoring Office GoR : Government of Rwanda HR : Human Resource ICT : Information and Communication Technology ISAE : Institute of Agriculture and Animal Husbandry ISAR : Institut des Sciences Agronomiques du Rwanda

(Rwanda Agricultural Research Institute) MDGs : Millennium Development Goals MIFOTRA : Ministry of Public Service and Labour MIGEPROF : Ministry of Gender and Family Promotion MINADEF : Ministry of Defence MINAFFET : Ministry of Foreign Affairs and Cooperation MINAGRI : Ministry of Agriculture and Animal Resources MINALOC : Ministry of Local Government MINECOFIN : Ministry of Finance and Economic Planning MINEDUC : Ministry of Education MINELA : Ministry of Environment and Land MINICOM : Ministry of Commerce MINIFOM : Ministry of Forestry and Mine MINIJUST : Ministry of Justice MININFRA : Ministry of Infrastructure MININTER : Ministry of Internal Security MINISANTE : Ministry of Health MINIYOUTH : Ministry of Youth NEC : National Electoral Commission NGP : National Gender Policy NISR : National Institute of Statistics of Rwanda NLC : National Land Centre NSS : National Statistical System



NWC : National Women Council OCIR- Café : Office for Rwanda Industrial Crops - Coffee OCIR- Thé : Office for Rwanda Industrial Crops - Thea OECD : Organization for Economic Cooperation and Development OGMR : Office General des Minerais du Rwanda PAIGELAC : Projet d’Appui à l’Aménagement Intégré et la Gestion des Lacs

Intérieurs PAPSTA : Projet d’Appui au Plan Stratégique pour la Transformation de

l’Agriculture PSF : Private Sector Federation PSTA : Strategic Plan for the Transformation of Agriculture RADA : Rwanda Agriculture Development Authority RALGA : Rwanda Association for Local Government Authority RARDA : Rwanda Animal Resources Development Authority RCA : Rwanda Cooperative Agency RDB/ORG : Rwanda Development Board REMA : Rwanda Environmental Management Authority RHA : Rwanda Housing Authority RHODA : Rwanda Horticulture Development Authority RIM : Réseau Interdiocésain de Microfinance RTDA : Rwanda Transport Development Agency RURA : Rwanda Utility Regulatory Agency SACCO : Saving and Credit Cooperative UNDP : United Nations for Development Programme UNESCO/GAB : United Nations Organization for Science and Culture UN WOMEN : United Nations Entity for Gender Equality and the Empowerment of Women UNIFEM : United Nations Development Fund for Women WB : World Bank WDA : Workforce Development Authority



LIST OF TABLES Table1: Executive governance organs..........................................................................................18 Table2: Executive high governance positions ..............................................................................20 Table3: Executive technical governance positions.......................................................................23 Table4: Legislative governance organs.........................................................................................25 Table5: Legislative high governance positions.............................................................................25 Table6: Judiciary high governance positions................................................................................26 Table7: Civil Society governance organs .....................................................................................29 Table8: High governance positions in Civil Society......................................................................30 Table9: Governance organs in Private sector..............................................................................30 Table10: High governance positions in Private sector ................................................................31 Table11: Private technical governance positions ........................................................................31 Table12: Qualitative indicators in governance....... .....................................................................32 Table 13: International indicators recommended at national level............................................37 Table14: National key indicators with baseline...........................................................................38 Table15: Key International quantitative indicators without baseline.........................................41 Table 16: Key National quantitative indicators without baseline ...............................................42 Table17: Key qualitative indicators without baseline..................................................................44 Table18: Key gender and ICT.......................................................................................................46 Table19: Key gender and transport indicators............................................................................46 Table20: Key gender and transport indicators............................................................................46 Table21: Key gender and urbanism and habitat indicators.........................................................46 Table22: Key gender and metrology indicators...........................................................................46 Table23: Internet and mobile phone access and use.................................................................47 Table24: Employment in infrastructure sub sectors...................................................................48 Table25: Education in ICT and sciences.......................................................................................50 Table26: Participation in telecommunication and ICT decision-making....................................50 Table27: Participation in ICT projects..........................................................................................50 Table28: Transport and Gender....................................................................................................51 Table29: Energy and Gender........................................................................................................51 Table30: Urbanism and Habitat....................................................................................................52 Table31: Metrology......................................................................................................................53 Table32: Qualitative indicators.....................................................................................................54 Table33: Key gender indicators in Private Sector with baseline ..................................................56 Table 34: Key gender indicators in Private Sector without baseline............................................60



EXECUTIVE SUMMARY

Equal access to opportunities that enhances empowerment of both men and women is a priority for the Government of Rwanda. The Government of Rwanda established in 2007 an autonomous body, “Gender Monitoring office” to monitor the implementation of gender principles and hold institutions accountable in regard to gender mainstreaming. The mandate of the Gender Monitoring Office is to ensure that fundamental principles of gender are respected in all government, private, non-governmental and religious organs. It also monitors the implementation of international agreements and programmes to ensure the respect of gender principles as well as to fight gender based injustice and violence.

To successfully fulfil this mandate, the Gender Monitoring Office needs to have a well developed, comprehensive and responsive gender monitoring and evaluation system with specific gender indicators for each sector of interest. It is in this regard that a gender baseline and key indicators for the four sectors, that are critical for economic growth social and justice, is developed. The four sectors covered in this report are Agriculture, Governance, Private Sector and Infrastructure. Gender indicators are a valuable tool for gender advocates, policy makers, and other actors working on gender-related issues.

To ensure that this balance is occurring in Rwanda there is a need for having indicators that will enable the government not only to observe how gender balance is being respected but also to do monitoring and evaluation.

This report discusses key indicators both national and international for the four sectors: governance, agriculture, infrastructure and private sector. Data on the indicators for the four sectors are not equally available. The sector that has a high number of indicators with data is governance, agriculture and private sector. The infrastructure sector has fewer indicators. For each indicator, institutions responsible for gathering data and the periodicity have been indicated. Some indicators will be collected annually or after a period of five years. Some will be from administrative data while others will come from surveys. The report highlights also recommendations that would enable GMO to get data disaggregated by sex for each indicator of the four sectors.



INTRODUCTION

1. Background and Justification

The Government of Rwanda recognizes the need of promoting gender equality as part of its

strategy for poverty reduction and realization of vision 2020. This political will was materialized

not only by ratifying of international conventions and agreements such as the CEDAW, MDGs

especially MDG 3 but also by putting in place various institutions such as Ministry of Gender

and Family Promotion, National Women Council and many other local NGOs for women

empowerment and advocacy. The GoR also developed policies and strategies for this purpose.

As illustrated in the Vision 2020, The Constitution of the Republic of Rwanda of 04 June 2003

and EDPRS, gender is a cross-cutting issue. This implies that gender need to be considered in all

sectors to ensure that gender equality is promoted. Rwanda has set a target of achieving equity

in education and having 50% of women in non-farming employment and 50% of women in the

parliament by 2015 (MDG Country Report, 2010). Education level equips both men and women

with more knowledge and increases equal chances of participating actively in the four sectors

(agriculture, governance, infrastructure and private sector). With regard to political

participation, the Government of Rwanda has made a huge step by becoming the first country

in the world to have more than 50% of women parliamentarians. The Constitution of the

Republic of Rwanda of 04 June 2003 also legislates for at least 30% of all members of the

cabinet, judges and members of public and private bodies to be women.

If there is a good progress in some areas such as those mentioned above, there remain

challenges to monitor the progress on gender equality in other critical socio-economic areas.

Agriculture, employment and private sector have been targeted by the strategic plan for the

implementation of the national gender policy to increase economic opportunities for both

women and men. Yet there is no baseline for monitoring the progress and the impact. This is

due to lack of a monitoring and evaluation system for accountability purposes across sectors.

To date, indicators disaggregated by sex are only available in social and demographic sectors.



To address this issue, the Government of Rwanda established in 2007 an autonomous body,

“Gender Monitoring office” to monitor the implementation of gender principles and hold

institutions accountable in regard to gender mainstreaming. The Gender Monitoring Office has

the mandate of ensuring that fundamental principles of gender are respected in all

government, private, non-governmental and religious organs. It also monitors the

implementation of international agreement and programmes to ensure the respect of gender

principles as well as fighting the gender based injustice and violence.

To successfully full-fill this mandate, the Gender Monitoring Office needs to have at its disposal

a well developed, comprehensive and responsive gender monitoring and evaluation system

with specific gender indicators for each sector of interest. It is in this regard that the GMO

needed to develop a gender baseline and key indicators for the four sectors that are critical for

economic growth social and justice. The four sectors are namely Agriculture, Governance,

Private sector and Infrastructure. It is important to mention that these four sectors employ a

large portion of Rwandan population, especially agriculture and private sector. The baseline

and key indicators shall enable the elaboration of a gender responsive monitoring and

accountability framework to be implemented by the four sectors.

This report presents the assessment of gender indicators in four sectors: Governance,

Agriculture, Infrastructure and Private Sector. It gives a list of identified gender indicators in the

mentioned sectors which would help to assess the progress in achieving gender equality.

Gender indicators are a valuable tool for gender advocates, policy makers, and other actors

working on gender related issues. The importance of indicators and statistics was further

reinforced at the Fourth World Conference on Women (Beijing, 1995) in setting the generation

and dissemination of gender-disaggregated data and information as strategic objectives for

planning and evaluation (Platform for Action and the Beijing Declaration, United Nations, 1995).



2. Objectives

The overall objectives of this report are:

1. To develop a baseline in the four mentioned sectors for effective gender monitoring-

evaluation and stakeholder’s accountability.

2. To analyze sectors listed above and gender mainstreaming context of the country

development planning and budgeting, gender mainstreaming baseline assessment

system and gender mainstreaming baseline.

3. To explore possibility of influencing other national planning and budgeting processes

with significant impact on economic sustainability and poverty reduction point of view.

3. Definition of Concepts

There is a need of defining some concepts used in this report to enable a same understanding

of them.

Indicator: An instrument that gives you information. An indicator is just a long way of saying

"how much" or "how many" or "to what extent" or "what size." Indicators are ways to measure.

Quantitative indicators: Quantitative indicators are defined as measures of quantity, such as

the number of women users in a telecentre, the number of women trained in computer skills or

the number of women who have access to the internet compared to men. Quantitative data

have long been cited as being more objective, and seek to quantify the experiences or

conditions among beneficiaries in numeric terms.

Qualitative indicator: Qualitative indicators are defined as people’s judgments and perceptions

on a subject, such as the confidence gained from acquiring computer skills to enable better

employment opportunities or having access to the internet for better trading/marketing

opportunities. Qualitative data are said to be more subjective. Qualitative data seek to uncover

the context, perceptions and quality of, as well as opinions about, a particular experience or

condition as its beneficiaries view it. It specially measures the impact of any program, policy,

politic, …



Key Performance indicator: it is a set of quantifiable measures that a company, industry or an

organization uses to compare performance in terms of meeting its strategic and operational

goals. Key Performance indicators (KPIs) vary between companies and industries, depending on

the priorities or performance criteria of each company or industry.

Gender indicators: are indicators that give information on gender issues. They differ from

gender-sensitive indicators in that gender indicator focuses on issues other than gender

relations but include data disaggregated by sex. Gender-sensitive indicators do not specifically

address gender issues per se but are coined in a way that does not invisibilise women. Gender

indicators are primarily used for the purpose of monitoring the not only the implementation of

international agreements that relates to gender equality but also used to monitor and evaluate

gender issues at national level.

Baseline: it is a 'pre-operation exposure' condition for the set of indicators that will be used to

assess achievement of the outcomes and impact expressed in the programme's logical

framework. When compared with the condition of the same indicators at some point during

implementation (mid-term evaluation) and post-operation implementation (final evaluation),

the baseline forms the basis for a 'before and after' assessment or a 'change over time'

assessment. Without baseline data to establish pre-operation conditions for outcome and

impact indicators it is difficult to establish whether change at the outcome level has in fact

occurred.

Gender mainstreaming: is defined as the reorganisation, improvement, development and

evaluation of policy processes so that a gender equality perspective is incorporated in all

policies at all levels and all stages, by the actors normally involved in policy making.

Governance: Governance is the study of identifying and choosing alternatives based on the

values and preferences of the governor agent. Making a decision implies that there are

alternative choices to be considered, and in such a case we want not only to identify as many of

these alternatives as possible but to choose the one that (1) has the highest probability of

success or effectiveness and (2) best fits with our goals, desires, lifestyle, values, and so on.



4. Methodology and Research Methods

The methodological approach used to attain the objectives of this report and to compile the

baseline combined the strengths of both desk research and consultations with technical

institutions involved in the four sectors.

4.1 Desk Research

A literature review on gender indicators was carried out. This enabled us to understand not

only what has been done so far in compiling data for gender indicators but also indicators for

which data are collected on a regular basis and their source. Desk research enabled also to

review policies and strategies developed at both national and international levels to promote

gender equality in the four sectors. The findings from the desk research informed on the

proposed list of national and international gender indicators to be collected on a regular basis.

This enabled also to propose the list of useful indicators at both national and international

levels. From a long list of international indicators, only those which were applicable and

relevant to the Rwandan context and can be collected were selected.

4.2 Consultations

After desk research, it was also necessary to do some consultations with technicians from the

four sectors (Agriculture, Governance, Private sector and Infrastructure) to ensure that there is

no indicator left out of the list. These consultations made it possible for us to validate the list of

indicators with stakeholders. This provided also an opportunity of knowing new indicators that

were missing in the literature review.

4.3 Building the Baseline

After working through the process of selecting key performance indicators to monitor

outcomes, the next step led to the building of baseline data, that is, showing the current status

compared to the outcome the four sectors are trying to achieve. Gathering of reference data

permitted to categorize indicators that have their data collected on a regular basis and those



that do not have data. One cannot predict performance in the future (set targets) without first

putting in place a baseline.

The baseline is the first measurement of an indicator. It sets the current status against which

future changes can be tracked. For instance, it helps to inform decision-makers about current

circumstances before embarking on setting targets for a given program, policy, or project. In

this way, the baseline is used to get more knowledge about current or recent levels and

patterns of performance. Importantly, baselines provide the evidence by which decision-

makers are able to measure a subsequent policy, program, or the project performance.

The building of the present baseline information for every indicator was guided by the following

eight questions:

1. What is the performance indicator?

2. What is the origin of the indicator?

3. What is the reference value of the indicator?

4. What are the sources of data?

5. What are the data collection methods?

6. How often will the data be collected?

7. Who will collect the data?

8. Who will use the data?



Chapter I

GENDER BASELINE AND INDICATORS IN GOVERNANCE

1. Introduction

The government of Rwanda has made tremendous achievement towards equal participation of

women and men in governance positions. The Rwanda’s political commitment has been

illustrated by the development of national frameworks and mechanisms including, but not

limited to The Constitution of the Republic of Rwanda of 04 June 2003, the Vision 2020,

Economic Development and Poverty Reduction Strategy, National Gender Policy and

Decentralization Policy.

Also, major achievements have been registered in adopting legal measures and reforms

favouring women, putting in place policies and strategies to ensure that women participate

actively in the leadership. The Constitution of the Republic of Rwanda of 04 June 2003

highlights gender as a cross-cutting issue and provides that women should be represented at a

rate of “at least 30%” in governance organs at all levels, of public sector, private sector and civil

society. This provision applies also to political parties.

Equal representation of men and women in governance bodies is essential for the achievement

of both transparent and accountable governance and administration, and sustainable

development in all areas of life. It is therefore important to ensure that women and men have

equal rights in regards to voting, participating in the formulation of government policies,

participation in non-governmental organizations and representation of their government at the

international level.

Achieving the goal of equal participation of women and men in governance provides a balance

that reflects more accurately the composition of society and it is needed in order to strengthen

democracy and promote its proper functioning.



Equal participation of men and women in governance plays a pivotal role in the general process

of the advancement of both genders. It does not only reflect the demand for simple justice or

democracy, but it can also be seen as a necessary condition for taking into consideration

women’s interests. A good representation of women in politics, decision making organs,

Governments and legislative bodies may contribute to redefining political priorities, placing

new items on the political agenda that reflect and address women's gender-specific concerns,

values and experiences, and providing new perspectives on mainstream political issues.

2. Presentation of gender Indicators in governance sector

Considering key gender indicators in governance in international frameworks and EDPRS, it is

necessary to mention that there is no specific gender indicator for governance in EDPRS.

However, some few gender indicators related to governance at international level (BPFA, CEDAW,

MDGs, Resolution 1325) are discussed below.

- Number of women into the public sector,

- Number of women in civil servants to senior level positions,

- Proportion of women’s representation in national and local committees,

- Number of women and men participating in politics;

- Measures to eliminate discrimination against women in the political and public life of

the country,

- Number of women and men who have equal rights in the field of employment,

- Participation of women and men in security organs;

- Role of security organs to fighting gender based violence,

At national level, the identified gender indicators are subdivided into three main categories

including:

- Men and women in governance organs,

- Men and women in high governance positions,

- Men and women in technical governance positions



Proposed gender indicators are discussed at the following levels of power: the Executive, the Legislative, and the Judiciary. Key gender indicators in Civil Society Organizations and Private Sector are also discussed.

2.1. Quantitative Gender Indicators

a. The Executive Power

Table1: The Executive governance organs

Indicator Reference value in percentage Data source Data collection method

Frequency to collect

Responsible of data collection

User of data Total number

Male in number/ %

Female in number /%

Percentage of men and women in Board of directors in Public institutions

473 346 73.2%

127 26.8%

Premature & MIFOTRA

Administrative data

Regular update

Premier Minister’s Office

Premier Minister’s Office, MIGEPROF, MINALOC, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women District Council Bureau

90 56 62.2%

34 37.8%

National Electoral Commission(NEC), Districts

Election records

5 years Districts MINALOC

MIGEPROF, MINALOC , FFRP,UNITY CLUB, PRO FEMMES, NWC, RALGA , GMO.

Percentage of men and women District Consultative Council/Njyanama

790 463 58.6%

327 41.4%

MINALOC / Territorial administration analysis

Administrative and electoral records


MIGEPROF, MINALOC FFRP,UNITY CLUB, PRO FEMMES, NWC, RALGA GMO

Percentage of men and women District Executive Committee/ Nyobozi

120 92 76.7%

28 23.3

MINALOC Electoral Commission




Percentage of men and women bureau of Kigali City Consultative Council

3 2 66.7%

1 33.3%

MINALOC Kigali City

Election and administrative records

5 years Kigali City MINALOC


Percentage of men and women bureau of Kigali City Executive committee

3 2 66.7%

1 33.3%

MINALOC Kigali City

Election and administrative records

5 years Kigali City MINALOC


Percentage of men and women sector Consultative Council/Njyanama y’Umurenge

8 157 4503 55.2%

3654 44.8%





Percentage of men and women Cell Consultative Council/Njyanama y’Akagari

30 536 17 589 57.6%

12 947 42.4%











Male in number/ %

Female in number /%

Percentage of men and women consultative committee of Youth Council at national level

100% 60.6% 39.4% MINALOC Administrative and electoral records

5 years MINIYOUTH MINALOC NYC

MIGEPROF, MINALOC, MINIYOUTH , FFRP,UNITY CLUB, PRO FEMMES, NWC, RALGA & GMO

Percentage of men and women in national committee of persons living with disabilities

100% 66.2% 33.8% MINALOC Administrative data

Regular update

MINALOC MIGEPROF, MINALOC FFRP,UNITY CLUB, PRO FEMMES, NWC & GMO

Percentage of men and women in Board members in Public and private primary schools

NA MINEDUC Administrative data

Regular update

MINEDUC MIGEPROF, MINEDUC, MIFOTRA, FFRP,UNITY CLUB, PRO FEMMES, NWC, GMO

Percentage of men and women in Board members in Public and private Secondary schools


Regular update

MINEDUC MIGEPROF, MINEDUC, MIFOTRA, FFRP,UNITY CLUB, PRO FEMMES, NWC,GMO

Percentage of men and women in Board members in Public and private High learning Institutions


Regular update

MINEDUC MIGEPROF, MINEDUC, MIFOTRA, FFRP,UNITY CLUB, PRO FEMMES, NWC &GMO

Percentage of men and women in boards of directors of Publics and Private Hospitals

NA MINISANTE Administrative data

Regular update

MINISANTE MIGEPROF, MINISANTE FFRP,UNITY CLUB, PRO FEMMES, NWC,GMO

Percentage of men and women in management committees of Publics and private Hospitals

NA MINISANTE Administrative data

Regular update

MINISANTE MIGEPROF, MINISANTE, FFRP,UNITY CLUB, PRO FEMMES, NWC, GMO

Percentage of men and women in Army High commandment

NA MINADEF Administrative data

Regular update

MINADEF MIGEPROF, MINADEF FFRP,UNITY CLUB, PRO FEMMES, NWC &GMO

Percentage of men and women in general commissariat of Prisons

5 4 80%

1 20%

Prisons Commissariat Office/ Human Resource Office

Administrative data

Regular update

Prisons Commissariat Office, MININTER

MIGEPROF, MININTER FFRP,UNITY CLUB, PRO FEMMES, NWC, GMO

Percentage of men and women in High commissariat in Police

100% 81% 19% National Police Head Office / Gender promotion department

Administrative data

Regular update

National Police

MIGEPROF, MININTER FFRP,UNITY CLUB, PRO FEMMES, NWC, GMO



Analysis of identified gender indicators and baseline in governance organs reveals that one of

the most sustained approaches is affirmative action that promotes participation of women in

different areas through set percentages or quota. In this context, The Constitution of the

Republic of Rwanda of 04 June 2003 provides, under Article 9, al.4, building a state governed by

the rule of law, a pluralistic democratic government, equality of all Rwandans and between

women and men reflected by ensuring that women are granted at least thirty per cent of posts

in governance organs.

This justifies the high number /percentage of women in elected organs compared to organs

where people are appointed. Thus, higher percentage of women is found in District Councils

(41.4%), Kigali City (33.3%), sectors (44.8%) and cells (42.4%). The imbalance in equal

participation of men and women in the Executive power governance organs is observed at the

level of security organs: e.g. women in general commissariat of Prisons (20%), women in High

commissariat in Police (19%).

Table2: The Executive high decision making positions




User of data

Total number

Male in number/ %

Female in number /%

Percentage of men and women Ministers

22 16 72.7%

6 27.2%

Prime Minister’s Office

Administrative data

Regular update


Premier Minister’s Office, MIGEPROF, MINALOC , FFRP,UNITY CLUB, PRO FEMMES GMO

Percentage of men and women State Ministers

3 1 33.3%

2 66.7%


Administrative data

Regular update


Premier Minister’s Office, MIGEPROF, MINALOC , FFRP,UNITY CLUB,

Percentage of men and women Permanent Secretaries of Ministries

18 9 50%

9 50%


Administrative data

Regular update


Premier Minister’s Office, MIGEPROF, MINALOC , FFRP,UNITY CLUB,

Percentage of men and women DG/President /Executive Secretaries of Public institutions

83 70 84.3%

13 15.7%

MIFOTRA Administrative data

Regular update


Premier Minister’s Office, MIGEPROF, MINALOC, NWC,

Percentage of men and women Rectors in public High learning institutions

17 16 94.1%

1 5.9%

MINEDUC/ High Council Learning Office

Administrative data

Regular update

MINEDUC Premier Minister’s Office, MIGEPROF, MINEDUC , FFRP,UNITY CLUB, PRO FEMMES, NWC &GMO






User of data

Total number

Male in number/ %

Female in number /%

Percentage of men and women Vice- Rectors Academic Affairs in public and private sector

20 19 95%

1 5%

MINEDUC Administrative data

Regular update

MINEDUC Premier Minister’s Office, MIGEPROF, MINEDUC , FFRP,UNITY CLUB, PRO FEMMES, NWC & GMO

Percentage of men and women Vice Rectors Administrative and Financial Affairs in public and private sector

19 18 94.7%

1 5.3%

MINEDUC Administrative data

Regular update

MINEDUC Premier Minister’s Office, MIGEPROF, MINEDUC , FFRP,UNITY CLUB, PRO FEMMES, NWC & GMO

Percentage of men and women Coordinators of publics projects

62 48 74.4%

14 22.6%

MINECOFIN/Project management and Monitoring Unity

Administrative data

Regular update


Premier Minister’s Office, MIGEPROF, MINECOFIN,FFRP,UNITY CLUB, PRO FEMMES, NWC &GMO

Percentage of men and women Governors and Mayor of Kigali City

5 4 80%

1 20%

MINALOC Administrative data

Regular update


Premier Minister’s Office, MIGEPROF, MINALOC, FFRP,UNITY CLUB, PRO FEMMES, NWC & GMO

Percentage of men and women Mayors of districts

30 27 90%

3 10%

National Electoral Commission

Data from election

5 years Districts NEC

Premier Minister’s Office, MIGEPROF, MINALOC, FFRP,UNITY CLUB, PRO FEMMES, NWC, RALGA & GMO

Percentage of men and women Vices-Mayors Economic Affairs of districts

30 25 83.3%

5 16.7%

National Electoral Commission MINALOC

Data from election


Premier Minister’s Office, MIGEPROF, MINALOC,FFRP,UNITY CLUB, PRO FEMMES, NWC, RALGA & GMO

Percentage of men and women Vices – Mayors Social Affairs of districts

30 5 16.7%

25 83.3%

National Electoral Commission

Data from election


Premier Minister’s Office, MIGEPROF, MINALOC, FFRP,UNITY CLUB, PRO FEMMES, NWC, RALGA & GMO

Percentage of men and women Hospital Directors

41 39 95%

2 5%

MINISANTE Administrative data

Regular update

MINISANTE Premier Minister’s Office, MIGEPROF, MINISANTE, FFRP,UNITY CLUB, PRO FEMMES, NWC & GMO

Percentage of men and women Specialists Doctors

105 92 87.6%

13 12.4%


Regular update

MINISANTE Premier Minister’s Office, MIGEPROF, MINISANTE, . FFRP,UNITY CLUB, PRO FEMMES, NWC, GMO






User of data

Total number

Male in number/ %

Female in number /%

Percentage of men and women Generalists Doctors

138 113 81.8%

25 18.2%


Regular update

MINISANTE Premier Minister’s Office, MIGEPROF, MINISANTE, . FFRP,UNITY CLUB, PRO FEMMES, NWC, GMO

Percentage of men and women Ambassadors

21

16 76.2%

5 23.8%

MINAFFET/Human Resource Officer

Administrative data

Regular update

MINAFET Premier Minister’s Office, MIGEPROF, MINAFET, MINECOFIN, FFRP,UNITY CLUB, PRO FEMMES, NWC, GMO

Percentage of men and women of Directors of print media

32 27 84.3%

5 15.7%

Media High Council

Administrative data

Regular update

Media High Council

Premier Minister’s Office, MIGEPROF, MINALOC FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women heads of department in Police.

36 33 92%

3 8%

National Police/Gender Department

Administrative data

Regular update

National Police

Premier Minister’s Office, MIGEPROF, MINALOC, MININTER FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women senior officers in Police

161 160 99.4

1 0.6%

National Police

Administrative data

Regular update

National Police


Percentage of men and women Junior officers in Police

953 870 91.3%

83 8.7%

National Police /Gender Desk

Administrative data

Regular update

National Police


As displayed in the above table, great achievement is observed at the level of Permanent

Secretaries of Ministries (50% of women against 50% of men). In the last seven years, women

were not highly represented: 10.5% (Source: Gender profile 2004) for the same position of

Permanent Secretaries. The low representation in the executive high governance positions is

observed in Health were women Hospital Directors, women Specialist Doctors and women

Generalist doctors represent respectively 5%, 12.4% and 18.2%.



Table3: Executive technical governance positions

Indicator Reference value in percentage Data source

Data collection method



User of data

Total Male Female Percentage of men and women Executive Secretaries of Provinces

4 3 75%

1 25%

MINALOC

Administrative data

Regular update

MIFOTRA Premier Minister’s Office, MIGEPROF, MIFOTRA, MINALOC FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women Executive Secretaries of districts

30 28 93.3%

2 6.7%

MINALOC

Administrative data

Regular update


Percentage of men and women Advisors

100% 90% 10% MIFOTRA

Administrative data

Regular update


Percentage of men and women directors units

100% 77.1% 22.9% MIFOTRA

Administrative data

Regular update


Percentage of men and women sector Executive Secretaries

416 378 90.9%

38 9.1%

District MINALOC

Administrative data

Regular update

District MINALOC


Percentage of men and women Cell Executive Secretaries

2148 1 339 62.3%

809 37.7%

MINALOC

Administrative data

Regular update

District MINALOC


Percentage of men and women Chief of Villages

14. 814 no disaggregated by gender

District MINALOC

Administrative data

Regular update

District MINALOC


Percentage of men and women Heads of primary Public Schools

2745 1946 70.9%

799 29.1%

District MINEDUC / Statistic OFFICE

Administrative data

Regular update

District MINEDUC

Premier Minister’s Office, MIGEPROF, MINALOC, MINEDUC, MIFOTRA FFRP,UNITY CLUB, PRO FEMMES, NWC, GMO

Percentage of men and women Heads of Public Secondary Schools

281

234 83.3%

47 16.7%

District MINEDUC

Administrative data

Regular update

District MINEDUC

Premier Minister’s Office, MIGEPROF, MINALOC, MINEDUC, MIFOTRA FFRP,UNITY CLUB, PRO FEMMES, NWC,GMO







User of data

Total Male Female Percentage of men and women senior staff in Embassies

37 32 86.5%

5 13.5%

MINAFET

Administrative data

Regular update

MINAFET Premier Minister’s Office, MIGEPROF, MINAFET FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women directors of prisons

14 11 78.5%

3 21.5%

Prisons Head Office

Administrative data

Regular update

MININTER Premier Minister’s Office, MIGEPROF, MINALOC, MININTER FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women vice - directors of prisons

14 10 71.4%

4 28.6%

Prisons Head Office

Administrative data

Regular update

MININTER Premier Minister’s Office, MIGEPROF, MINALOC, MININTER FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

From the above table, it can be observed that apart from the representation of women

Executive Secretaries at Cell level of 37.7%, it appears that the representation of men and

women in the rest of executive technical governance positions needs a positive improvement.

The minimum quota required in all governance positions has not yet been respected at this

level. Data show that the percentage of women in other positions mentioned in the above table

varies between 28.6% and 6.7%.

b. The Legislative Power

Table4: Legislative governance organs






Male in number/ %

Female in number /%

Percentage of men and women in Bureau of chamber of Deputy

3 2 66.7%

1 33.3%

National Parliament, Chamber of Deputy

Electoral data

5 years FFRP Premier Minister’s Office, MIGEPROF, MINALOC . FFRP,UNITY CLUB, PRO FEMMES , NWC . GMO

Percentage of men and women in Bureau of chamber of Senate

3 2 66.7%

1 33.3%

National Parliament, Chamber of Senate

Electoral data

8 years FFRP Premier Minister’s Office, MIGEPROF, MINALOC . FFRP,UNITY CLUB, PRO FEMMES, NWC GMO



Table5: Legislative high governance positions





Male in number/ %

Female in number /%

Percentage of men and women in bureau of Chamber of Deputy

3 2 66.6

1 33.3%

Chamber of Deputy

Data from election

5 years Parliament NEC

Premier Minister’s Office, MIGEPROF, MIFOTRA, MINECOFIN . FFRP,UNITY CLUB, PRO FEMMES, NWC

Percentage of men and women Deputies

80 35 43.7%

45 56.3%

Chamber of Deputy/Department of Research

Data from election


Premier Minister’s Office, MIGEPROF, MIFOTRA, MINECOFIN . FFRP,UNITY CLUB, PRO FEMMES, NWC

Percentage of men and women president of chamber of standing committees

11 7 63.6%

4 36.4%

Chamber of Deputy

Data from election


Premier Minister’s Office, MIGEPROF, MIFOTRA, MINECOFIN . FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women in bureau of Chamber of Senate

3 2 66.6

1 33.3%

Chamber of Senate /Department of research

Data from election



Percentage of men and women Senators

26 17 65.4%

9 34.6%


Data from election



Percentage of men and women president of standing committees Chamber of Senate

4 2 50%

2 50%


Data from election


Premier Minister’s Office, MIGEPROF, MIFOTRA, MINECOFIN . FFRP,UNITY CLUB, NWC

In legislative power, at both governance organs and high governance positions, the

representation of men and women is evolving positively. The electoral system is guided by the

law N° 27/2010 of 19/06/2010 put in place to support participation of women in leadership at

both executive, legislative level and local level. The laws highlight the principle of gender

equality and provide that the constitutional rate of “at least 30%” representation of women

should be respected in all electoral processes. This justifies why the representation of men and

women is well respected in legislative compared to the executive.



The Judiciary Power

Table6: Judiciary high governance positions





User of data

Total number

Male in number/ %

Female in number /%

Percentage of men and women President and Vice president at supreme court

1 1 50%

1 50%

Supreme court / Planning Unit

Administrative data

8 years Supreme court

Premier Minister’s Office, MIGEPROF, MINIJUST MIFOTRA, MINECOFIN FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women Judges at supreme court

14 8 57%

6 43%


Administrative data

Regular update

Supreme court


Percentage of women and men inspectors at supreme court

6 5 83.3%

1 16.7%


Administrative data

Regular update

Supreme court

Premier Minister’s Office, MIGEPROF, MIFOTRA, MINECOFIN FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women President and Vice President/ High Court

2 2 100%

0 Supreme court / Planning Unit

Administrative data

Regular update

Supreme court


Percentage of Judges/ High Court

24 18 75%

6 25%


Administrative data

Regular update

Supreme court








User of data

Total number

Male in number/ %

Female in number /%

Percentage of men and women President and Vice President/High commercial Court

3 3 100%

0 Supreme court / Planning Unit

Administrative data

Regular update

Supreme court

P M’s Office, MIGEPROF, MINIJUST MIFOTRA, FFRP,UNITY CLUB, PRO FEMMES, NWC, GMO

Percentage of men and women Judges/High Commercial Court

7 4 57%

3 43%


Administrative data

Regular update

Supreme court

Premier Minister’s Office, MIGEPROF, MINIJUST, MIFOTRA, MINECOFIN FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women Vice President/ Commercial Courts

3 2 66.7%

1 33.3%


Administrative data

Regular update

Supreme court


Percentage of men and women Judges/ Commercial Courts

15 12 80%

3 20%


Administrative data

Regular update

Supreme court


Percentage of men and women presidents Intermediate Courts

12 8 66.7%

4 33.3%


Administrative data

Regular update

Supreme court


Percentage of men and women Vice Presidents/ Intermediate court

12 9 75%

3 25%


Administrative data

Regular update

Supreme court


Percentage of men and women Judges/ intermediate courts

99 60 60.6%

39 39.4%


Administrative data

Regular update

Supreme court








User of data

Total number

Male in number/ %

Female in number /%

Percentage of men and women presidents of Primary courts

60 46 76.7%

14 23.3%


Administrative data

Regular update

Supreme court


Percentage of men and women Judges at primary courts

116 67 57.8%

49 42.2%


Percentage of men and women General prosecutor and Deputies

5 5 100%

0 General prosecutor Office / Human resource office

Administrative data

8 years Office of the General prosecutor


Percentage of men and women Head of Department at Higher Courts

6 5 83.3%

1 16.7%

General prosecutor Office

Administrative data

Regular update

Office of the General prosecutor

Premier Minister’s Office, MIGEPROF, MINIJUST, MIFOTRA, MINECOFIN FFRP,UNITY CLUB, PRO FEMMES, NWC , GMO

Percentage men and women procurement Chief at lower courts

12 11 91.7%

1 8.3%

General prosecutor Office

Administrative data

Regular update

Office of the General prosecutor


The representation of women in the area of justice shows that there is a positive trend of

gender balance in some levels of justice such as judges at supreme courts (43%), in high

commercial courts (43%), president at intermediate courts (33.3%), and vice president at

commercial courts (33.3%) and judges at intermediate (39,4%) and primary courts (42,2%).

However there is a need of improvement in the rest of judiciary levels as it is displayed in the

table.



c. Decision making in Civil Society organizations

Table7: Civil Society governance organs





Male in number/ %

Female in number /%

Percentage of men and women members of Boards of Directors in Plate form of Civil Society Organizations

15 13 86.7%

2 13.3%

Plate form of Civil Society /Human Resource Office

Administrative data

Regular update

Plate form of Civil Society Secretariat

MIGEPROF, MINECOFIN, MINICOM etc. FFRP,UNITY CLUB, PRO FEMMES, NWC, etc GMO

Percentage of men and women members of Boards of Directors of Civil Society Organizations( Human rights , women’s organizations, Faith based organizations etc)

NO DATA Pro femmes, Forum des confessions religieuses, NHRC

Administrative data

Regular update

MINALOC MIGEPROF, MINALOC etc. FFRP,UNITY CLUB, PRO FEMMES, NWC, etc GMO

Percentage of men and women in Bureaus of Boards of Civil Society Organizations

NO DATA Pro femmes, Forum des confessions religieuses, NHRC

Administrative data

Regular update

MINALOC MIGEPROF, MINALOC etc. FFRP,UNITY CLUB, PRO FEMMES, NWC etc GMO

Men and women in board members of churches

NO DATA Religious forum

Administrative data

Regular update

Religious forum

MIGEPROF, MINALOC etc. FFRP,UNITY CLUB, PRO FEMMES, NWC, etc GMO

Women are underrepresented in Board of Directors in Platform of CSOs where they are only

13.3%. The remaining governance organs in Civil Society do not have data.



Table8: High governance positions in civil society Indicator Reference value in percentage Data source Data

collection method




Male in number/ %

Female in number /%

Percentage of men and women President of Civil Society Organizations’

No data Office of the plate form of Civil Society Organisations

Administrative data

Regular update

PRO FEMMES

Premier Minister’s Office, MIGEPROF, MINALOC FFRP,UNITY CLUB, PRO FEMMES,

Percentage of men and women vice president of civil society


Administrative data

Regular update

PRO FEMMES


Percentage of men and women Executive Secretaries/National coordinators of civil society organizations.


Administrative data

Regular update

PRO FEMMES

Premier Minister’s Office, MIGEPROF, MINALOC FFRP,UNITY CLUB

Percentage of men and women Heads of churches

No data Office of the Forum of faith based organisations

Administrative data

Regular update

Forum Secretariat

Gender Machineries

d. Governance in Private sector

Table9: Governance organs in Private sectorIndicator

Reference value in percentage Data source




User of data Total Male in

number/ %

Female in number /%

Percentage of men and women members of PSF Board ,

16 14 87.5%

2 12.5%

PSF Head Office / Human Resource Office

Administrative data

Regular update

PSF MIGEPROF, MINICOM FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women in PSF Bureau of Board

3 2 66.7%

1 33.3%

PSF Head Office

Administrative data

Regular update

PSF Gender Machineries

Percentage of men and women in High management/board of big companies/Enterprises in PSF

NO DATA

PSF Head Office

Administrative data

Regular update

PSF MIGEPROF, MINICOM. FFRP,UNITY CLUB, PRO FEMMES

Percentage of men and women in small and medium enterprises in PSF

NO DATA

PSF Head Office

Administrative data

Regular update

PSF MIGEPROF, MINICOM. FFRP,UNITY CLUB, PRO FEMMES, NWC, GMO

Women are underrepresented as members of PSF board because they are only 12.5%. .

However, in the PSF Bureau of Board, women are 33.3%. The rest of indicators have no data.



Table10: High governance positions in Private sector

Indicator Reference value in percentage

Data source




User of data

Total number

Male in number/ %

Female in number /%

Percentage of men and women Rectors in Private High learning institutions

12 12 100%

0 MINEDUC/ High Council Learning Office

Administrative data

Regular update

MINEDUC Premier Minister’s Office, MIGEPROF, MINEDUC FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Number of men and women PSF Chief Executive Secretary

1 1 100%

0 PSF Administrative data

Regular update

PSF Premier Minister’s Office, MIGEPROF, MINALOC FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women owners of Private Radio

14 14 100%

0 Media High Council

Administrative data

Regular update

Media High Council


Percentage of men and women of print media owners

32 32 100%

0 Media High Council

Administrative data

Regular update

Media High Council

Premier Minister’s Office, MIGEPROF, MINALOC FFRP,UNITY CLUB, PRO FEMMES, GMO

Percentage of men and women Directors of Private Radio

14 13 92.8%

1 7.2%

Media High Council

Administrative data

Regular update

Media High Council


In general, gender representation in high governance positions in Private sector is very low with

only 7.2% of women in private radio.



Table11: Private technical governance positions





User of data

Total number

Male in number/ %

Female in number /%

Percentage of men and women Heads of primary Private Schools

151 77 51%

74 49%

District MINEDUC / Statistic OFFICE

Administrative data

Regular update

District MINEDUC

Premier Minister’s Office, MIGEPROF, MINALOC, MINEDUC, MIFOTRA FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women Heads of Private Secondary Schools

286 236 82.5%

50 17.5%

District MINEDUC

Administrative data

Regular update

District MINEDUC

Premier Minister’s Office, MIGEPROF, MINALOC, MINEDUC, MIFOTRA FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women director of departments in PSF

5 4 80%

1 20%

PSF/Human Resource Officer

Administrative data

Regular update

PSF Premier Minister’s Office, MIGEPROF, MINICOM, FFRP,UNITY CLUB, PRO FEMMES, NWC , GMO

Percentage of men and women President of chambers in PSF

9 7 77.8%

2 22.3%

PSF/Human Resource Officer

Administrative data

Regular update

PSF Premier Minister’s Office, MIGEPROF, MINICOM, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Percentage of men and women BDS managers in districts

26 25 96.2%

1 3.8%

PSF BDS Department

Administrative data

Regular update

PSF Premier Minister’s Office, MIGEPROF, MINICOM, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

A part from women head of private primary schools, which represent 49%, the representation

of women in other technical governance positions in private sector varies from 3.8% to 22.3%.

This implies that PSF should take positive measures to ensure that women and men are equally

represented.



2.2. Qualitative Gender Indicators

This section discusses identified qualitative gender indicators in governance as shown in the table below:

Table12: Qualitative indicators in governance

Indicator Origin of the indicator

Reference value

Data source




User of data

Women and men have an equal and effective participation in cabinet debate

BPFA Rwanda Constitution 2003

No reference value for all qualitative indicators

Survey report

Survey 5 years GMO Premier Minister’s Office, MIGEPROF, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

How the influence of men and women Ministers are perceived the by the population;

BPFA Rwanda Constitution 2003 NGP

Report Survey 5 years GMO Premier Minister’s Office, MIGEPROF, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Environment for women’s participation in Parliament decision making organs is conducive.


Report Survey 5 years FFRP Parliament, MIGEPROF, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Women and men in Parliament have equal access of official information at the same time


Report Survey 5 years FFRP Parliament, MIGEPROF, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Permanent framework of dialogue between women leaders elected at national level and those elected at grassroots level exist and is functioning


Reports Meetings records

Regular update

FFRP Districts

PARLIAMENT, MIGEPROF, MINALOC , FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Men and women perform decision making functions without any stereotype


Reports Survey Regular update

FFRP Unity Club

Premier Minister’s Office, MIGEPROF, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

Men and women in decision making positions participate in national dialogue without any discrimination or stereotypes;


Reports SURVEY Regular update

FFRP Unity Club

Premier Minister’s Office, MIGEPROF, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO.

Cabinet decisions consider the needs and interests of both men and women


Reports Cabinet resolution and survey

Regular update

UNITY CLUB Premier Minister’s Office, MIGEPROF, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO



Indicator Origin of the indicator

Reference value

Data source




User of data

The language/ jokes used by men and women in various decision making bodies are fair for both men and women;


Reports Gender audit

Regular update

GMO Premier Minister’s Office, MIGEPROF, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

The PSF board members decisions take into consideration the capacities, constraints and opportunities of both men and women


Reports Gender audit

Regular update

PSF GMO

Premier Minister’s Office, MIGEPROF, MINICOM, PSF FFRP,UNITY CLUB, PRO FEMMES, NWC & GMO

The active and effective participation of both men and women in PSF are often to be the same;



PSF Premier Minister’s Office, MIGEPROF, MINICOM, PSF FFRP, UNITY CLUB, PRO FEMMES, NWC & GMO.

The national security organs(army, police and prisons services) are aware on the issues of gender equality and GBV;

UN 1325 Resolution NGP


MINADEF MININTER National Police

Premier Minister’s Office, MIGEPROF, MINADEF, MININTER, NP FFRP,UNITY CLUB, PRO FEMMES, NWC & GMO

CSOs/Faith based organizations dialogue and debate consider the difference needs and interests of men and women;


Reports Research Regular update

MINALOC Plate form of CSO’s

Premier Minister’s Office, MIGEPROF, MINALOC (FFRP,UNITY CLUB, PRO FEMMES, NWC & GMO

The perceptions of men and women of their level of influencing decisions taken in various bodies, forum, committees.


Reports Meetings records

Regular update


Premier Minister’s Office, MIGEPROF, FFRP,UNITY CLUB, PRO FEMMES, NWC GMO

The degree of mutual support among men and women in decision making organs, positions etc.

CEDAW, BPFA, NGP


MIGEPROF Premier Minister’s Office, MIGEPROF , FFRP,UNITY CLUB, PRO FEMMES, NWC & GMO

The schools decision making organs are aware on specific gender issues of both boy and girls at school environment.

MDG, BPFA, NGP

Reports Administrative records and survey

Regular update

MINEDUC Premier Minister’s Office, MIGEPROF, MINEDUC FFRP,UNITY CLUB, PRO FEMMES, GMO

How the participation of men and women in schools decision making organs/positions facilitate to reduce gender inequalities between boy and girls

MDG, BPFA, NGP

Reports Resolution from school committees ; Survey

Regular update

MINEDUC Premier Minister’s Office, MIGEPROF, MINEDUC FFRP,UNITY CLUB, PRO FEMMES, NWC & GMO.

It should be noted that all identified qualitative indicators do not have baseline as it can be seen

in the above table.



3. Conclusion

In order to accomplish its mandate of assuring gender mainstreaming in all development

activities, GMO thinks that the starting point is to set up mechanisms that will guarantee proper

data collection and analysis methods in gender sensitive way for effective monitoring and

evaluation of different interventions as well as planning processes.

The development of gender sensitive indicators and baseline in governance sector has revealed

that disaggregation of data by sex are not available in some institutions despite enormous

achievements observed in the area of decision making. Each public, private and CSO, from

central to decentralized level should conduct a situational analysis and generate sex

disaggregated data in their areas of focus. An analysis of baseline data establishes whether

there is any difference between men and women’s access to resources and opportunities that

promote gender equality. In this regards, CSOs have to put more effort in collecting data and

disaggregate them by sex in order to help in achieving gender mainstreaming goal.

The following recommendations can help bridging the gap identified during the process of

developing gender sensitive indicators and baseline in governance sector.

Establish and support capacity building programs for planners and Human Resource

Managers and relevant professional staff on gender mainstreaming with more emphasis

on data collection taking into consideration gender dimension;

GMO and other relevant institutions should assist various institutions in producing

gender sensitive data, developing data collection tools, and ensuring that they are

effectively used;

Identify the best practices of sharing gender sensitive data with other stakeholders

intervening in gender area,

GMO can facilitate the development of a reporting system that takes into consideration

sex disaggregated data and gender sensitive data;

Establishing a systematic mentoring and coaching mechanism from central level to

decentralized level in producing and using disaggregated data by sex;

Raising awareness among the institutions on the importance of gender indicators in

governance sector;



Chapter II

GENDER BASELINE AND KEY INDICATORS IN AGRICULTURE

1. Introduction Rwanda’s economy is largely based on agriculture; it employs more than 80% of the population

and its contribution to GDP varies from 30% to 40%1. In terms of household, 85% of heads of

households, of which 27% are female, are occupied in agriculture2. The objectives of the Vision

2020 include modernization of agriculture and its integration with other economic activities3 by

introducing improved practices in both land management and utilization, but also the adoption

of soil fertility-enhanced techniques.

The culmination of this transformation should lead to sustainable development that requires,

among other things, participation of all, men and women, without any kind of discrimination

because social cohesion and equity between various actors are of fundamental importance.

Meanwhile, it can be highlighted that, in terms of gender equity, heavy burdens continue to be

placed upon women, who contribute much in the activities of producing food crops.

Furthermore, certain activities, such as manuring and managing livestock, are also mainly done

by girls and boys4.

However, participation of everyone in the country's major policies requires compliance with the

principle of equal access to opportunities between men and women. To this end, the EDPRS as

1 MINAGRI, Agriculture Gender Strategy, November 2010, p.2. 2 NISR, National Agricultural Survey 2008, February 2010, p.20. 3 MINECOFIN, Vision 2020, November 2002, p.8. 4 MINAGRI, Strategic Plan for the Transformation of Agriculture in Rwanda – Phase II (PSTA II), Final Report, February 2009.



other important policy documents and sector strategies recommend that gender be considered

in all actions undertaken for economic growth and poverty reduction and for the well-being of

the population.

Given that gender equality is reflected in day-to-day life, its impact could be measured from

objectively verifiable indicators. These indicators help not only in identifying the gap between

men and women but also in formulating recommendations to reduce the gap in the short,

medium or long-term.

In this chapter, our attention focuses on gender indicators in the field of agriculture at

international and national levels.

2. Presentation of Agriculture Indicators

The following table shows key international indicators (with the origin of the indicator)

recommended at national level.

Table 13: International indicators recommended at national level

Indicator Percentage of female/male labour force in agriculture (age 15 and over). Percentage of female/male labour force in managerial occupations in the agriculture sector. Employment/unemployment rate of women/men, urban/rural. Average fertilizer consumption (kg per hectare of arable land) by sex of household head. Percentage of women who have access to credit, vis-à-vis men. Percentage of available credit and financial and technical support going to women/men from government and non-government sources.

At national level, reference values were collected for national key indicators shown in the table

below.

The existing values shown in the table below will serve as a reference for future evaluation of

progress.



Table14: National key indicators with baseline

Indicator Reference value Data Source




User of data Type of data

Total Male Female

a.Human resources and capacity building

Staff in agriculture institutions disaggregated by sex

Number Administrative data

Annually MINAGRI GMO – NWC MIGEPROF - NISR MINAGRI

% 100% 66% 34% MINAGRI HR

Researchers in agriculture disaggregated by sex

Number 98 74 24 Administrative data

Quaterly MINAGRI ISAE, INATEK, IRST, NUR,NGO’s

GMO – NWC MIGEPROF - NISR MINAGRI

% 100% 76% 24% HR ISAR Quaterly

Number of veterinary technicians (by sex) at sector level (RIMS: Result indicator Management System:)


Quaterly MINALOC MINAGRI


% 100%

Proportion of persons trained inseminators disaggregated by sex

Number 500 Administrative data

Annually

MINAGRI/RAB


% 100%

Number of farmers (by sex) trained in agribusiness)


Quaterly MINAGRI GMO – NWC MIGEPROF - NISR MINAGRI

%

Number and percentage of farmers (by sex) adopting new technologies (sericulture, aquaculture, irrigation, post harvest,horticulture,org manure production)



% 100%

Number of farmers trainers (by sex) in farmer field school methodology


Quaterly MINAGRI GMO – NWC MIGEPROF - NISR MINAGRI

% 100%







User of data Type of data Total Male Fem.

Number of leader farmers trained (by sex)


Monthly MINAGRI GMO – NWC MIGEPROF - NISR MINAGRI

Percentage 100%

Number of farmers in participatory research trials, by sex


Quaterly MINAGRI, Research institutions


Percentage 100% Quaterly

Number of farmers (by sex) trained in agricultural input use


Quaterly MINAGRI MINALOC


Percentage 100%



Indicator Reference value Data

Source Data collection method




Total Male Female

b.Financial activities

Number and percentage of RIF2 beneficiaries disaggregated by sex

Number

Administrative data

Quarterly MINAGRI BDF


Percentage 100% 87,3% 12,7% BNR March 2011

Agricultural credit disaggregated by sex of beneficiaries


MINAGRI GMO – NWC MIGEPROF - NISR MINAGRI

Percentage 100% 64% 36% BNR Quarter Report, March 2011


Percentage 100%

c. Cash crops and land

Number of men and women in cooperatives owning Coffee washing stations


Annually MINAGRI NAEB


Percentage

Number coffee farmers disaggregated by sex

Number 389,236 272,831 116,405 NAEB 2010

Administrative data

Annually MINAGRI NAEB


Percentage 100% 70,1% 29,9%

Number of tea farmers disaggregated by sex

Number 40,027 24,525 15,502 NAEB, Situation season 2010

Administrative data


Percentage 100% 61,3% 38,7%

d.Livestock

Household benefiting under the programme “one cow one family” by sex of household head

Number 115,052 RARDA reports February, 2011

Administrative data

Quaterly MINAGRI /RAB


Percentage

100%








Total Male Female

Number of households (by sex of Head of Households) benefiting from small ruminants distribution activities (including through pass on mechanism)


Quartelly

MINAGRI/RAB

Percentage 100% GMO – NWC MIGEPROF - NISR MINAGRI

e.Cooperatives

Number and percentage of farmers (by sex) who are members of farmers’ Cooperatives per crop/livestock type


Monthly RCA

Percentage 100%

f.environment

Proportion of men and women in soil conservation comittees

Number Survey Annually

Percentage MINAGRI MINALOC


Numbers of men and women participating in soil conservation work


Annually Percentage 100% MINAGRI

, MINALOC


Number of farmers members of water use Associations (WUA) by sex


Annually

Percentage MINAGRI GMO – NWC MIGEPROF - NISR MINAGRI




Data collection Method


User of data Type of

data Total Male Female

Agribusiness

Number of women and men participating in improved post harvest technologies (Storage in cocoons)

Number - - - Reports Monthly GMO – NWC MIGEPROF - NISR MINAGRI

Percentage - - -

Cold chains with capacity of tones by sex of owners

Number - - - Survey Annually Percentage - - -

Number of agro dealers by sex of effectively owners

Number - - - Reports Monthly Percentage - - -

The above table shows that most indicators with reference values have data that are not

disaggregated by sex. However, it can be observed that disaggregated data indicate that there

are disparities between men and women. Even for some indicators with data disaggregated by

sex, the proportions of women are very low compared to those of men, especially in crops,

where the percentage of women coffee farmers are only 29.9% and 70.1% of men and only

6.5% of women are owners of coffee washing stations, where 93.5% are men. Also, 38.7% of

women are tea farmers where 61.3% are men.

However, non-disaggregated indicators are not useful for this study to highlight the disparities

between men and women.

Most indicators do not have available data for the whole population or for both sexes. Tables

below present quantitative or qualitative indicators without reference data by distinguishing

international indicators from national ones.



2.1. Quantitative indicators

a. International indicators

Table15: Key international quantitative indicators without baseline

Indicator Reference value Data source




Type of data

Total Male Female

User of data

1. Staff and Capacity building

Number of farmers (by sex) trained in agricultural input use

Number MINAGRI Survey Annually

MINAGRI GMO - NWC MIGEPROF MINAGRI MINALOC - NISR

Number of farmers (by sex) trained in agribusiness)

Number MINAGRI Reports Quaterly

MINAGRI GMO - NWC MIGEPROF MINAGRI – NISR MINICOM

2. Land and Crops Persons who have received land titles under land reform schemes disaggregated by sex

Number MINELA Reports Annually MINELA GMO - NWC MIGEPROF MINAGRI- NISR MINELA

3. Livestock

Honey farmers household by sex of household head

Number MINAGRI Survey Annually MINAGRI GMO - NWC MIGEPROF MINAGRI- NISR

Number of households chicken producers by sex of HHead

Number

4. Cooperatives and service satisfaction

Number of extensionists disaggregated by sex

Number MINAGRI Reports Quartely MINAGRI MINALOC

GMO - NWC MIGEPROF MINAGRI MINALOC - NISR

5. Health and Environment

Proportion of household below minimum food requirements by sex of household head

Number NISR Survey Every 5 years

NISR MINISANTE

GMO - NWC MIGEPROF MINAGRI- NISR MINISANTE

Household planting 30 trees annually by sex of household

Number MINELA Survey Annually MINELA MIGEPROF








Total Male Female

Household having a composter by sex of household head

Number NISR Survey Every 5 years

REMA MINAGRI

GMO - NWC MIGEPROF MINAGRI- NISR MININFRA - REMA

6. Agri-business

Number of agriculture specialist in BDC disaggregated by gender

Number PSF/RDB Reports Quaterly PSF/RDB GMO - NWC MIGEPROF MINAGRI – NISR

Number and percentage of exporters of horticulture products by sex

Number/%

Number of agro dealers by sex of effectively owners

Number MINAGRI Reports Quaterly MINAGRI GMO - NWC MIGEPROF MINAGRI – NISR MINICOM

Percentage of agroprocessing SMEs by sex of owners

% MINICOM RRA

Reports Quarterly GMO - NWC MIGEPROF MINAGRI – NISR MINICOM

1. Land

Percentage of property owned or accessible by women/men (land, livestock) across income groups

% MINAGRI

Survey Annually NISR MINAGRI

GMO - NWC MIGEPROF MINAGRI - NISR

Percentage of female/male headed households without land

% MINAGRI



Average area of agricultural land under irrigation (% of total agricultural land) by sex of household head

Number

MINAGRI

Reports Monthly MINAGRI GMO - NWC MIGEPROF MINAGRI - NISR

Arable land (hectares per person) by sex of household head

Number

MINAGRI


GMO - NWC MIGEPROF MINAGRI – NISR








Total Male Female

2. Labour and wage

Percentage of female/male labour force who are unpaid family workers or are working in the informal sector (age 15 and over)

% NISR Survey Every 5 years

NISR

GMO - NWC MIGEPROF MINAGRI MIFOTRA - NISR

Salary/wage differentials of women/men, by category of workers

Number/ %

MIFOTRA

Reports Monthly NISR


Average wage for agricultural labourers by sex

% MIFOTRA

Reports Monthly NISR


Percentage of rural households where female/male head is the main earner

% NISR Survey Every 5 years

NISR MINAGRI


Right to maternity leave/number of weeks/percentage of women who avail themselves of right

% MIFOTRA

Reports Monthly MIFOTRA GMO - NWC MIGEPROF MINAGRI MIFOTRA – NISR MINIJUST

2.2. Qualitative indicators

Table17. Key qualitative indicators without baseline






Total

Male Female

International indicators Incidence of part time/full time work of women and men

Number/ %

NISR Survey Every 5 years

MIFOTRA NISR


Changes over x-year period of project activities in household nutrition disaggregated by sex

Number/ %

MINAGRI

Survey Annually MINAGRI NISR

GMO - NWC MIGEPROF MINAGRI – NISR MINECOFIN








Total Male Female

National indicator Change in behaviour among men and women due to “One Cow One Family ” programme

Number MINALOC

Survey Annually MINAGRI MINALOC

GMO - NWC MIGEPROF MINAGRI MINALOC - NISR

For the above indicators, no data were found in institutions supposed to produce them.

However, in order to have the needed data, a template to be used for collecting information

should be designed.

3. Conclusion

According to the results from this part of the study on gender indicators in Agriculture, it is true

that production of related data is still poor. This applies also for the disaggregation of existing

data.

In order to satisfy the need of monitoring results of various actions of the gender strategy in

agriculture, it is recommended that GMO undertakes, in collaboration with NISR, a campaign

for raising awareness among producers of statistics to collect data disaggregated by sex on a

regular basis.



Chapter III

GENDER BASELINE AND KEY INDICATORS IN INFRASTRUCTURE

1. Introduction

Improving access to infrastructure is fundamental for promoting women’s economic

empowerment. It increases agricultural productivity, a sector in which women contribute more

in developing countries, gives free time for productive activities, facilitates employment and

provides easy access to markets.

However, many infrastructure projects and programmes are gender-blind as they assume that

both women and men will automatically benefit from them. Given that the achievement of the

Millennium Development Goals (MDGs), especially in Africa, depends on how living conditions

of women and girls are improved, there is a pressing need of improving women’s lives. Well

designed, appropriately located and affordable infrastructure can be a powerful tool in the

pursuit of gender equality. In other words, infrastructure projects should be designed to

increase economic opportunities for women, provide appropriate services to women, and

actively involve and empower women.

This chapter presents key indicators that can be used to monitor gender in the infrastructure

sector both at international and national levels. It covers ICT, transport, energy, urbanism and

housing and metrology.

2. Presentation of infrastructure indicators In this section, we first present indicators commonly used at international level to monitor

progress made in gender equity and promotion. Second, we present indicators at national level

by indicating the origin of information, the methodology used to collect data, the frequency of

data production, institutions responsible for data collection and the list (not exhaustive) of

users of collected data.



2.2 Indicators at international level

Indicators on gender and infrastructure have been obtained from different sources.

Table18: Key gender and ICT

ICT-Indicators Users of Internet by sex and age Users of mobile telephone by sex Reasons for Internet use by sex Reasons for not using Internet by sex Number of customers at telecentres by sex Usage of ICT to access information on health care and market opportunities Gender-related employment within ICT industries Internet sites used by sex Persons employed within telecommunication industries Persons employed within ICT industries by level of employment Persons employed within telecommunication industries by level of employment Persons by sex employed in jobs using ICT Persons by sex employed in computer science and engineering research Persons by sex employed in research institutions, higher skilled, higher ranking and higher paid positions Persons by sex studying ICTs and computer sciences ( formal and informal education) Persons by sex studying sciences and technology Persons by sex boards members and senior management of ICT companies and ICT regulatory organizations Persons by sex employed in ministries of communication and information technology by level of employment

Table19: Key gender and transport indicators

TRANSPORT -Indicators Means of transport by sex Persons by sex participating in transport infrastructure design and implementation Share of Government investment in transport related to gender issues

Table20: Key gender and transport indicators

ENERGY-Gender

Persons by sex participating in energy projects design and implementation Source of energy used by households by sex of household head Share of investment in energy related to gender issues, especially to women activities Share of energy used for domestic, agricultural, small-scale informal production activities where women predominate

Table21: Key gender and urbanism and habitat indicators

URBANISM AND HABITAT -Indicators Satisfaction about habitat by sex of household head Participation by sex in urbanism and habitat planning Number of women with titled land Proportion of population in unplanned urban settlements who have access to safe means of sanitation by sex

Table22: Key gender and metrology indicators

METROLOGY -Indicators Gender and access to meteorological information with impact on economic activities like agriculture and other business Gender and number of subscribers accessing daily, weekly and seasonal weather forecasts



2.2 National quantitative indicators

a. ICT and Gender

The recent study conducted by RURA in 2010 to evaluate the ICT sector performance analyzed

the market share in mobile telephone by different telecommunication companies, the trend of

the number of subscribers both to mobile and landline telephones, and also in terms of

geographic and population coverage. The study also discussed the Internet market share, the

number of subscribers per operators, Internet users per hundred inhabitants and the trend in

ICT investment. However, available data are not disaggregated by sex.

Table23: Internet and mobile phone access and use


source Data collection method



Users of data

Type of data

Total Male Female

Users of Internet at national level

Number Percentage

801 787 NA

NA NA

NA NA

RURA Survey Annually or after two years

RURA and NISR

RURA, Ministry of ICT, Ministry of Gender and Family Promotion, GMO.

Users of Internet at district level


RURA and NISR


Users of Internet at district level by age


RURA and NISR


Reasons for Internet use


RURA and NISR


Reasons for not using Internet by age

RURA

Survey

Annually or after two years

RURA and NISR


Users of Internet by telecentres In average

178 393 NA NA RURA Survey Annually or after two years

RURA and NISR


Users of Internet to access markets’ information and health care information

Number Percentage

8018 NA

NA NA

NA NA


RURA and NISR








Users of data

Type of data

Total Male Female

Users of mobile phone at national level

Number Percentage

4 300 495 41.3%

NA NA

NA NA


RURA and NISR


Users of mobile phone at district level


RURA and NISR


Users of Internet by site


RURA and NISR


Updated information on Internet users to be presented in the report under preparation by

RURA indicates that 801,787 persons use Internet; the estimated number of Internet customers

in a telecentre is 178,393. Among persons using Internet, only 8,018 use this facility to access

markets’ information and health care information.

Concerning the use of mobile phones, 4,300,495 persons use mobile phone, representing

around 41.3% of the total population of Rwanda.

Table24: Employment in infrastructure subsectors






Total Male Female

Persons employed within ICT companies

Number Percentage

761 100%

541 71.1%

220 28.9%

RURA

Survey Annually RURA RURA, Ministry of ICT, Ministry of Gender and Family Promotion, GMO.

Persons employed within telecommunication institutions

Survey Annually Ministry of Labour, National Institute of Statistics, RURA


Persons employed within ICT companies by level of employment

Ministry of Labour and NISR

Survey Annually Ministry of Labour and NISR








Users of data

Type of data

Total Male Female

Persons employed within telecommunication institutions by level of employment



Number of persons participating in transport infrastructure design and implementation

Number Percentage

44 100%

36 81%

8 19%


Persons working in research institutions, higher skilled, higher ranking and higher paid positions by level of employment

Ministry of Labour and NISR



Number of persons employed in transport sector5

Number Percentage

67 100%

48 71.6%

19 28.4%


Number of persons accessing jobs in public infrastructures

Number Percentage

130 100%

97 74.6%

33 25.4%


Persons employed in the sector of urbanism and habitat in 2011

Number Percentage

42 100%

33 78.6%

9 21.4%


Number of persons employed in the sector of urbanism and habitat in 2011 at managerial level

Number Percentage

10 100%

8 80%

2 20%


The information on the number of persons employed within ICT companies is sex

disaggregated. The report shows that 761 persons are employed in this sector. Male and female

are 541 and 220, representing 71% and 29% respectively. Information from Rwanda Transport

Development Agency-RTDA (Human Resource Department) shows that 44 persons participated

5 In MININFRA and RTDA



in design and implementation of transport infrastructure in 2011, 81% of them being male and

19% female. Of 67 persons who are in charge of transport programs both in MININFRA and

RTDA, 19 are female and 48 are male. Based on the information from MININFRA (Human

Resource Department, 2011), among 130 persons who had jobs in public infrastructure, 97

were male and 43 female. Among 42 persons employed in the sector of urbanism and housing,

only 9 are female and 33 are male (RHA), Human Resource Department). In addition, only 2

persons over 10 at high level of management in this sector are female.

Table25: Education in ICT and sciences





User of data

Type of data

Total Male Female

Persons studying sciences and technology

Number Percentage

25 894 100%

17349 67%

8545 33%

MINEDUC Reports Annually MINEDUC MINEDUC, Ministry of Gender and Family Promotion, GMO

As indicated in the table below, in 2010 academic year, 25 894 students were registered in the Faculty of

Sciences and Technology, male representing 67% and female 33% (MINEDUC, Department of Statistics).

Table26: Participation in telecommunication and ICT decision-making





User of data

Type of data

Total Male Female

Persons composing boards and senior management of ICT companies, ICT regulatory organizations

Ministry of ICT

Survey annually Ministry of cabinet affairs’ NISR

MINEDUC, Ministry of Gender and Family Promotion, GMO

Persons employed in the Ministry of ICT and level of employment

Ministry of ICT

Reports Annually Ministry of ICT

MINEDUC, Ministry of Gender and Family Promotion, GMO



Table27: Participation in ICT projects Indicator Reference value Data




User of data

Type of data

Total Male Female

Persons participating in ICT projects by sex and level of responsibility

Ministry of ICT

Reports Annually Ministry of ICT MINEDUC, Ministry of Gender and Family Promotion, GMO

Beneficiaries of ICT projects

Ministry of ICT

Reports Annually Ministry of ICT MINEDUC, Ministry of Gender and Family Promotion, GMO

Table28: Transport and Gender Indicator Reference value Data source Data

collection method



User of data

Type of data

Total Male Female

Persons employed in transport sector

Ministry of Labour Survey Annually Ministry of Labour

Ministry of Labour Ministry of Gender and Family Promotion, Ministry of Infrastructure, GMO

Means (bicycle, motorcycle, taxis, air) of transport

MINIFRA Survey Annually MINIFRA Ministry of Labour Ministry of Gender and Family Promotion, Ministry of Infrastructure, GMO

Persons employed in transport infrastructure design and implementation

MINIFRA Survey Annually MINIFRA Ministry of Labour Ministry of Gender and Family Promotion, Ministry of Infrastructure, GMO

Number and percentage of man and women recruited and retained in activities related to construction of roads

Ministry of Gender and Family Promotion and MININFRA

Survey

Annually

Ministry of Gender and Family Promotion and MININFRA

Ministry of Labour Ministry of Gender and Family Promotion, Ministry of Infrastructure, GMO

Number and percentage of man and women accessing jobs in public infrastructure

MININFRA Survey Annually MININFRA Ministry of Labour Ministry of Gender and Family Promotion, Ministry of Infrastructure, GMO



Table29: Energy and Gender Indicator Reference value Data




User of data

Type of data

Total Male Female

Number of persons employed in the sector of energy by responsibility

MININFRA/NISR

Survey Annually MININFRA and NISR

MININFRA and MIGEPROF

Level of satisfaction about access to electricity by sex of household head

MININFRA/NISR



Type of used sources of energy by sex of household head

MININFRA/NISR



Number of households accessing electricity by sex of household head

MININFRA/NISR



Duration of having electricity connection by sex of household head

MININFRA/NISR



Number of households accessing to micro central by sex of household head at district level

MININFRA/NISR



Table30: Urbanism and Habitat

Indicator Reference value Data source Data

collection method




Tot Male Fem.

Persons satisfied with the improvement in urbanism and habitat

Ministry of Infrastructure, MINALOC


Annually

Ministry of Infrastructure

Ministry of Infrastructure, MINALOC, MIGEPROF

Persons employed in the sector of urbanism and habitat by level of responsibility



Annually

Ministry of Infrastructure




Indicator Reference value Data source Data collection method




Tot Male Female Data source

Number of households having access to social facilities by sex of household head (water, school, markets, healthcare, etc.)



Annually Ministry of Infrastructure


Persons having lands title in 2011

Number Percentage

4802 124 100%

2881274 60%

1920850 40%





Projects in urbanism and habitat taking into account needs of women in their design and implementation compared to total number of projects





Share of Government investment related to gender issues as percentage of total budget in projects on urbanism and habitat.





Table31: Metrology Indicator Reference value Data




User of data

Type of data

Total Male Female

Persons accessing to meteorological information

Number Percentage

125 NA

NA NA

NA NA

Survey Annually Metrology agency

Gender based regulations on meteorology Gender-based strategic plan on meteorology.

Survey Annually Metrology agency

Regarding access to meteorological information, the annual report of the service in charge of

meteorology indicates that only 125 persons have access to this information.



Based on these indicators and also on international practice, we propose that the following

indicators be regularly produced in Rwanda and disaggregated by sex to support gender

monitoring in infrastructure sector.

1.1. National qualitative indicators

Table32: Qualitative indicators

Indicator Reference

value Data source




User of data

The impact of Internet use on the improvement of economic conditions by sex


RURA and NISR RURA, Ministry of ICT, Ministry of Gender and Family Promotion, GMO

The impact of Internet use on the improvement of economic conditions by sex


RURA and NISR RURA, Ministry of ICT, Ministry of Gender and Family Promotion, GMO

2. Conclusion

Based on the number of indicators discussed in this chapter and compared to governance and

agriculture sectors, there are few indicators on infrastructure sector. Some indicators are

available regarding the access and use of Internet and mobile phone. Indicators on transport,

urbanism and housing and energy are not produced by concerned institutions.



Chapter IV:

GENDER BASELINE AND INDICATORS IN

PRIVATE SECTOR

1. Introduction

Private sector development is a key engine for economic growth and crucial to reducing

poverty. Women and girls make up to three-fifths of the world’s one billion poorest people.

Promoting equal participation of women and men in the labour force, especially for women

who seem to be among the poorest people, constitutes a critical potential tool for reducing

poverty and increasing the poor’s income and therefore ensures economic growth of the whole

country.

In fact, private firms, from farmers and micro-entrepreneurs to local manufacturing and

multinational enterprises, are at the centre of the development process by providing more jobs

than the public sector, by creating opportunities for people to apply their skills. This enhances

people improving their living conditions, is the main source of tax revenues and contributes to

public funding for transport, education, health and other services.

The aim of this chapter on “Gender Baseline and Indicators Development in Private Sector” is to

assess the levels and trends of gender indicators at international and national level. This

chapter reviews indicators on the investment climate, access to credit and business

entrepreneurship for women and men, situation of women and men at workplace, trade policy

and trade liberalization in Rwanda. The actions mentioned have different impacts on women

and men due to unequal gender roles and relationships.



2. Presentation of Private Sector Indicators Table33: Key Gender Indicators in Private Sector with Baseline

Indicators Reference value Data source





Total Male Female

INTERNATIONAL INDICATORS

Number and percentage of private investors in energy by gender

a) Hydro Number

16 13 3 MININFRA Administrative data

Monthly MININFRA, RDB

MINAGRI, MINALOC, MINIFOM, MINELA, ISAE, PSF, CNF, GIZ, GMO

% 100.0% 81.3% 18.7%

b) Solar Number

2 2 0 RDB Administrative data


RDB, GMO

% 100.0% 100.0%

0.0%

c) Biogas Number

70 68 2 MININFRA-NDBP

Administrative data



% 100.0% 97.1% 2.9%

Number and percentage of investors in telecoms by gender

Number6

(1) 43 (2)561 (3)611

37 - -

6 - -

RDB Administrative data


PSF, GMO

%

- - -

Number and percentage of investors in water and sanitation by gender

Number

40 37 3 MININFRA Administrative data



%

100.0% 92.5% 7.5%

6 Investors in telecoms includes (1) Enterprises, (2) Domestic companies and (3) Telecom companies








Total Male Female

Number and percentage of investors in transport by gender

Number

7952 - - RURA, RTDA

Administrative data

Monthly RURA, RTDA RURA, PSF, MINIFRA, RTA, GMO

% - - -

Number and percentage of new businesses registered by gender of owners (since June 2010)

Number

1082 - - RDB-ORG Administrative data

Daily RDB-ORG RDB, GMO

%

- - -

Percentage of adult employment that is part-time by gender

Number

33218 13602 19616 PSF census report, 2008

Census/Survey

Every 5 years

PSF PSF, MIFOTRA, MINICOM, NISR, WDA, GMO

%

16.8% 6.9% 9.9%

Women’s share of part-time employment

Number

- - - PSF census report, 2008

Census/Survey

Every 5 years

PSF PSF, MIFOTRA, MINICOM, NISR, WDA, GMO

%

- - 59.1%

Percentage of employees by gender

Number

197816 90103 107713 PSF census report, 2008

Census/Survey

Every 5 years

PSF, NISR PSF, MIFOTRA, MINICOM, NISR, WDA, GMO

%

100.0% 45.6% 54.4%

Women’s wages in manufacturing as a percentage of men’s wages

Number

- - - MIFOTRA Administrative data

Law MIFOTRA PSF, MIFOTRA, MINICOM, NISR, WDA, GMO

%

100% 100% 100%

Length of maternity leave

Number

- 4days 1month MIFOTRA Administrative data

Law MIFOTRA MIFOTRA, GMO

%

- - -

Percentage of wages paid in maternity leave covered period

Number

- - - MIFOTRA Administrative data

Law MIFOTRA MIFOTRA, GMO

%

- 100% 100%








Total Male Female

Number and percentage of clients by gender of owners accessing funds from registered Micro-finance

a) UMWALIMU SACCO

Number

28436 17333 11103 UMWALIMU SACCO

Administrative data

Monthly UMWALIMU SACCO

BNR, GMO

%

100.0% 61.0% 39.0%

b) IMF UNGUKA sa

Number

1891 1511 380 IMF-UNGUKA

Administrative data

Monthly IMF-UNGUKA

BNR, GMO

%

100.0% 79.9% 20.1%

c) COOPEDU Number

2037 248 1789 COOPEDU Administrative data

Annually report

COOPEDU BNR, GMO

%

100.0% 12.2% 87.8%

d) AMASEZERANO COMMUNITY BANKING

Number

1941 1235 706 AMASEZERANO Community Banking

Administrative data

Annually report

AMASEZERANO

BNR, GMO

%

100.0% 63.6% 36.4%

e) GOSHEN Finance sa

Number

2277 1883 394 GOSHEN Administrative data

Annually report

GOSHEN BNR, GMO

%

100.0% 82.7% 27.3%

f) AL-HAALAL sa Number

263 187 76 AL-HALAAL sa

Administrative data

Annually report

AL-HALAAL sa

BNR, GMO

P%

100.0% 71.1% 28.9%

g) SWOFT sa Number

7372 4309 3063 SWOFT sa Administrative data

Annually report

SWOFT sa BNR, GMO

%

100.0% 58.5% 41.5%

h) INKINGI Number

416 268 148 INKINGI Administrative data

Annually report

INKINGI BNR, GMO

%

100.0% 64.4% 35.6%

i) RIM (Réseau Interdiocésain de Micro-finance)

Number

9096 6005 3091 RIM Administrative data

Annually report

RIM BNR, GMO

%

100.0% 66.0% 34%








Total Male Female

Number and percentage of women and men in new cooperatives (since 2010)

Number

24949 - - RCA Administrative data

Monthly RCA BNR, RCA, MINICOM, PSF, MINECOFIN, GMO

%

- - -

Number and percentage of SMEs and cooperatives by gender of owners

a) Micro Enterprises

Number

177837 - - PSF census report, 2008

Census/Survey

Every 5 years

PSF, RDB PSF, MIFOTRA, MINICOM, NISR, WDA, GMO

%

89.9% - -

b) Small Enterprises

Number


Census/Survey

Every 5 years


%

7.6% - -

c) Medium Enterprises

Number


Census/Survey

Every 5 years


%

0.2% - -

d) Large Enterprises

Number


Census/Survey

Every 5 years


%

0.2% - -

e) Cooperatives Number

656452 - - RCA Monthly RCA BNR, RCA, MINICOM, PSF,

% - - -

Number and percentage of private companies by gender of owners operational

a) in agriculture Number 14 12 2 RDB-ORG Administrative data

Monthly RDB-ORG PSF, MINECOFIN, MINICOM,

%

14.3%

b) in mining

Number 74 69 5 OGMR Administrative data

Monthly OGMR PSF, MINICOM, NWC, MIGEPROF,

% 100.0% 93.2% 6.8%








Total Male Female

c) in coffee

Number 43 40 3 Rwanda Coffee Authority

Administrative data

Monthly Rwanda Coffee Authority

RDB, PSF, MINICOM, International Importers, NWC, MIGEPROF, GMO

% 100.0% 93.0% 7.0%

d) in tea

Number 8 - - Rwanda Tea Authority

Administrative data

Monthly Rwanda Tea Authority

PSF, MINICOM, NWC, MIGEPROF, GMO

e) in tourism (accommodation)

Number 161 115 46 RDG-Tourism

Administrative data

Monthly RDG-Tourism

PSF, NWC, MIGEPROF, GMO

% 100.0% 71.4% 28.6%

f) in tourism (tour operators)

Number 33 27 6 RDG-Tourism

Administrative data

Monthly RDG-Tourism

PSF, NWC, MIGEPROF, GMO

% 100.0% 81.8% 18.2%

g) in manufacturing

Number 124 80 44 RDB-ORG Administrative data

Daily RDB-ORG RDB, PSF, MINICOM, MINECOFIN, NWC, MIGEPROF, GMO

% 100.0% 64.5% 35.5%

Number and percentage of business registered with RDB by gender

Number

5870 - - RDB-ORG Administrative data

Daily RDB-ORG RDB, PSF, MINICOM, MINECOFIN, NWC, MIGEPROF, GMO

%

- - -

Number and percentage of visitors to BDS (by gender

Number

463 318 145 RDB-BDS Administrative data

Monthly RDB-BDS RDB, PSF, MINICOM, NWC, MIGEPROF, GMO

%

100.0% 68.7% 31.3%

Number and percentage of immigrant work visas issued for skill shortage areas by gender

Number

1757 - - Immigration & Migration

Administrative data

Daily Immigration & Migration

RDB, PSF, MINICOM, NWC, MIGEPROF, GMO

%

- - -



Indicators Reference value Data source Data

collection method




Total Male Female

Literacy rate of people ages 15 and above by gender

Number

- - - EICV-3, Census

Census/Survey

Every 5 years

NISR RDB, PSF, MINICOM, NWC, MIGEPROF, GMO

%

- - -

level of ducation completed by gender of employees in manufacturing sector: - Primary, - Secondary/Technical, - Tertiary

Number P=28.0% S=34.8% T=37.2%

- - PSF Census/Survey

Census report

PSF RDB, PSF, MINICOM, NWC, MIGEPROF, GMO

A perusal of the baseline shows that most indicators have reference values whose percentages

are very high for men and very low for women, except in COOPEDU Microfinance where

percentages of women are higher than those of men.

This shows that involvement of men in business is far greater than that of women. This means

that, contrary to the significant participation of women in governance bodies, women's

participation in economic development is still very low.

Another observation is that some indicators are not disaggregated by sex. This is mainly due to

lack of a good understanding by some managers of the need of having disaggregated data by

sex which provide information on equity between men and women and the harmonious

development between all inhabitants of the country without any exclusion.

Table 34 below presents the baseline for indicators without reference values.



Table 34: Key Gender Indicators in Private Sector without Baseline






Total Male Female

Percentage of firms with ISO certification ownership by gender

Number

- - - PSF - -

Percentage

- - -

Economic activity rate of people aged 15 and above by gender

Number

- - - EICV-3 Every 5 years

MINECOFIN, PSF, MINICOM, NISR, WDA, NWC, MIGEPROF, GMO

Percentage

- - -

Share of women in adult labour force (aged 15 and above)

Number



Percentage

- - -

Percentage of employers by gender

Number

- - - 2011 Establishment Census

Every 5 years

PSF, MIFOTRA, MINICOM, NISR, WDA, NWC, MIGEPROF, GMO

Percentage

- - -

Percentage of own-account workers by gender

Number


Every 5 years

PSF, MIFOTRA, MINICOM, NISR, WDA, NWC, MIGEPROF, GMO

Percentage

- - -

Percentage of contributing family workers by gender

Number



Percentage

- - -



Indicators Reference value Data





Total M F

Percentage of managers by gender in: a) Agriculture b) Mining c) Coffee d) Tea e) Tourism f) Manufacturing

Number


Every 5 years

% - - -

Unemployment rate by gender

Number

- - - General Population and Housing Census

Census Every 10 years

NISR MINECOFIN, PSF, MINICOM, NISR, WDA, NWC, MIGEPROF, GMO

%

- - -

NATIONAL INDICATORS Number and percentage of firms citing finance as ”major” or “severe” constraint reduced: - Large, - Small

Number - - - PSF Survey PSF, MINICOM, MINECOFIN

% - - -

Number and percentage of firms by gender of owners rating electricity as a “major” or “severe” constraint to growth

Number

- - - MININFRA Survey MININFRA, PSF, MINICOM, MINECOFIN

% - - -

Number and percentage of firms by gender of owners rating communication as a “major” or “severe” constraint to growth

Number


% - - -

Number and percentage of firms rating water and sanitation as a “major” or “severe” constraint to growth

Number


% - - -

Number and percentage of firms by gender of owners rating transport as a “major” or “severe” constraint to growth

Number


%

- - -



Indicators Reference value Data source Data collection method



User of data Type of

data Total M F

Number and percentage of private sector enterprises by gender of owners which have implemented employment laws for gender by size: - Small, - Medium, - Large

Number - - - PSF Survey PSF, MIFOTRA

PSF, MIFOTRA, MIGAPROF

% - - -

Number and percentage of regional/provincial investment groups operational by gender composition: - Male, - Female

Number - - - RDB, PSF Administrative Survey

RDB, PSF PSF, MINICOM,

% - - -

Percentage of staff (permanent workers) trained by gender and job category: - Agriculture, - Mining, - Coffee, - Tea, - Tourism, - Manufacturing

Number - - - 2011 Establishment Census

Census, Administrative data

Every 5 years

RDB, PSF PSF, MIFOTRA, MINICOM, NISR, WDA, GMO % - - -

3. Conclusion

Having 44% of indicators of the present baseline without reference values is very worrying.

These indicators were set as a tool that will enhance gathering needed data for monitoring and

evaluating the achievement of assigned objectives. However, concerned institutions have not

been able to provide these data up to date.



CONCLUSION AND RECOMMENDATIONS

1. Conclusion

Despite the existence of logical frameworks for the four sectors since 2008, most of reference

values for indicators are not collected. There are still many indicators that have no baseline.

In general, most of all values or percentages for selected indicators in the four sectors are very

high for men and too low for women. This shows that women's participation in social and

economic development of the country is far from being a reality despite the political will of the

government to promote gender equity and equality. However, women representation is

respected in the judiciary, legislative and it is even very high in few pro-women sectors, such as

COOPEDU Microfinance.

There are also some indicators that cannot be collected by the four sectors. This implies that

they can only be collected through major national censuses and surveys, such as the 2012

Population and Housing Census, the Establishment Census and EICV-3 and many other surveys

undertaken by the institutions concerned will reduce the number of indicators without

reference values.

A big challenge is registered in some areas such as infrastructure where there are no available

data or else they are not disaggregated by sex.

2. Recommendations

Given the status of the current situation in the four sectors, some recommendations are

formulated for various institutions that complement each other in achieving their respective

objectives. It is therefore recommended that:

MINECOFIN should remind all institutions having the EDPRS logical framework of the

imminent evaluation of the work done on the basis of indicators that should have

reference values for evaluation at the end of 2012.



GMO should conduct awareness campaigns for different sectors to encourage the

production of disaggregated data by sex. Disaggregated data will inform the disparity

between men and women in the four sectors because under-investing in women not

only limits development opportunities, but also slows down poverty reduction and

economic growth of the country.

GMO in collaboration with NISR should undertake a systematic mentoring and coaching

mechanism from central level to decentralized level in developing gender sensitive data

collection tool and ensuring they are effectively used.

NISR should assist in strengthening technical capacities of institutions part of the

National Statistical System (NSS) and bring all stakeholders to provide needed data for

monitoring and evaluation of the trend of achievement of their goals and objectives in

general, and to produce disaggregated data by sex in particular.



REFERENCES

1. Beijing Declaration and Platform for Action, 1995. 2. Convention on the Elimination of all Forms of Discrimination against women (CEDAW),

1979. 3. DANIDA, Gender Equality in the Private sector, Ministry of Foreign Affairs of Denmark,

2008. 4. Emily ESPLEN & Alyson BRODY, Putting Gender Back in the Picture: Rethinking

Women’s Economic Empowerment, Bridge Development Gender, 2007. 5. Gender profile 2005-2007, 2008. 6. Gender profile, 2004. 7. MIGEPROF, National Gender Policy, July 2010. 8. Millennium Development Goals, 2000. 9. MINAGRI, Agriculture Gender Strategy, November 2010. 10. MINAGRI, Annual Report 2009/2010, August 2010. 11. MINAGRI, Evaluation d’impact des activités du PAPSTA, Rapport définitif, Janvier 2011. 12. MINAGRI, National Agricultural Extension Strategy. 13. MINAGRI, Strategic Plan for the Transformation of Agriculture in Rwanda – Phase II

(PSTA II), February 2009. 14. MINECOFIN, Economic Development and Poverty Reduction Strategy 2008 – 2012

(EDPRS), 2007. 15. MINECOFIN, Vision 2020, November 2002. 16. Ministry of Gender and Family Promotion, National Gender Policy, 2010. 17. Ministry of Gender and Family Promotion, Strategic plan for the implementation of the

national gender policy Plan for the Implementation of the National Gender Policy, 2009. 18. National Decentralisation Policy, 2000. 19. National Gender Policy, 2010. 20. NICI, Mid-term Evaluation of the Implementation of NICI Plan, 2008. 21. NISR, National Agricultural Survey 2008, February 2010. 22. PSF, EDPRS Private Sector Logical Framework, 2008. 23. PSF, Rwanda Business Operators Census Report, 2008. 24. RURA, ICT Sector Performance, 2010. 25. Rwanda Economic Development and Poverty Reduction Strategy (EDPRS), 2007; 26. Rwanda Vision 2020, 2000. 27. Rwandan National Constitution of June 2003 as amended to date. 28. The COMMONWEALTH SECRETARY, Gender Mainstreaming in Agriculture and Rural

Development, June 2001.



29. THE WORLD BANK, Gender equality as smart economics: Third-Year Progress Report (2007-2010), A World Bank Group Action Plan, 2010.

30. The WORLD BANK, Gender in Agriculture Sourcebook by “International Bank for Reconstruction and Development/”, 2009.

31. THE WORLD BANK, Global Private Sector Leaders: Promoting Women’s Economic Empowerment, 2010.

32. The WORLD BANK, Report, www.data.worldbank.org/indicator. 33. Tony BECK, Using Gender-sensitive Indicators: A Reference Manual for Governments

and other Stakeholders, Commonwealth Secretariat, 1999. 34. UN Security Council Resolution 1325, 2000. 35. UNCTAD, Trade and Gender: Opportunities and Challenges for Developing Countries,

2004. 36. Universal Declaration of Human Rights, 1948. 37. Vicki DONLEVY & Rachel SILVERA, Implementing Gender Gquality in Enterprises: Report

on Best Practices and Tools in Europe, 2007. 38. Zo RANDIAMARO, Gender and Trade: Making Trade Work for Gender Equality, 2006. 39. Abbott, P. and Rwirahira, J. (2010). Millennium Development Goals Progress Report.

Rwanda Country Report. Washington: UNDP



Appendix

List of Contacted persons

INSTITUTION NAMES CONTACT MININFRA - NDBP HATEGEKA AUGUSTIN 0788562413 MININFRA NTAWURUHUNGA GABRIEL 0788567697 MIFOTRA NDUWIMANA JUSTIN 0788423610 MIFOTRA TURAYISHIMYE LEANDRE 0788608315 OGMR KANYANZIRA JOHN 0788487821 RDB - BDS KAREGYEYA WILSON 0782731743 RDB – TOURISM RUDASINGWA JOEL 0788831264 RDB – OFFICE OF REGISTRAR GENERAL SANGANO YVES 0788679086 RDB TWAGIRAYEZU INNOCENT 0788487131 RWANDA COOPERATIVE AGENCY MUGABO DAMIEN 0788301599 RWANDA TEA AUTHORITY MUHOZA CHRISTINE ING. 0788897386 RWANDA TEA AUTHORITY SEBUDANDI AMOUR 0788516310 RWANDA COFFEE AUTHORITY UWERA ROSINAH 0788511469 AL-HAALAL SA KALUME ZAMZAM 0788844984 SWOFT SA MASUTALA JULIEN 0788479996 AMASEZERANO COMMUNITY BANKING MUGABONAKE DANIEL 0788532850 GOSHEN FINANCE SA MUNYANKUMBURWA SAM 0788301313 IMF – UNGUKA NYIRANYAMIBWA K. VESTINE 0788308211 COOPEDU RUGWIRO GILBERT 0788866700 RIM UWUMWANAYEZU M. THERESE 0788820969 INKINGI SA YOMBO SAMUEL 0788751100 MINAGRI RURANGWA RAPHAEL 0788301498

NDAGIJIMANA ALEXIS 0788878430 RUZIGA VERENA 0788851536 RADA

BISANGWA 0788547748 CYUBAHIRO EDOUARD 0788748357

RARDA DR FABRICE 0785781138 MAHORO 0788582906

RHODA MUNANURA JAMES 0788838247 MINECOFIN NDARUHUTSE JEAN BOSCO 0783300797 ISAR CHARLES 0788481374 PAIGELAC KAYITARE 0788407059 BRD/BDF RUTAGENGWA JOHN 0788428676

IRIBONEYE JEAN CLAUDE 0788301835 LWH MUTUMAYI CELESTIN 0788353439 OCIR-CAFE MUNYANKERA PONTIEN 0788303709

MAURICE 0788405963 JACQUES 0788502354 BANDROU 0788872186

OCIR-THE MUGENI ALICE 0788526062 MUHOZA CHRISTINE 0788897386

NLC EVODE 0788448633 MUNYANEZA LEOPOLD 0788474825

PAPSTA KARANGWA VIATEUR 0788577181 GASASIRA JANVIER 0788307522

PSTA II NYIRASANGWA VIOLET 0788469101 KWAMP KAMWE RAYMOND 0788615830 TS-IRRIGATION DR J. JACQUES MBONIGABA 0788301123 MINISANTE DR DASSAN 0788850947 RURA RUTIMIRWA BENJAMIN 0788445550 RURA UMULISA CONSOLEE 0788860180 MININFRA RWAKUNDA CHRISTIAN 0788306635 MININFRA JEAN BOSCO HAGWIRINEZA 0788764025 MININFRA MUKANKUSI ALPHONSINE 0788845789 RWANDA HOUSING AUTHORITY MARARA CAMILLE 0788301811

CONTACT US

Gender Monitoring Office Gishushu

P.O. Box: 837 Kigali - Remera Rwanda Telephone: +250 (0) 252581794 Fax: +250 (0) 252581795

Email: [email protected] Website: www.gmo.gov.rw

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