CASE STUDY: Vietnam — Information brings progress to Vietnam’s communes

December 16, 2010
Michelle Hibler

In Vietnam, a community-based monitoring system builds on existing official poverty surveys to better target the poor. The additional data has led to improvements in communities, and in the lives of women in particular.

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A dozen or so young women concentrate on guiding silky fabric under the foot and needle of modern sewing machines in a classroom at the head office of the Women’s Union in Ninh Binh (WUNB). They are training: training to be seamstresses and training for a better life.

This is one of many programs offered by the WUNB to prepare women for employment. The organization is nothing if not dynamic. With more than 2000 local units in all of the province’s 147 communes, the WUNB works to advance women’s equality and protect their rights. Among these activities are education programs on gender issues, vocational and job creation programs, and microcredit and business development programs.

The WUNB also leads maternal and child health research and programs, among many others.

The WUNB is the provincial branch of the Vietnam Women’s Union, a unique country-wide non-governmental organization (NGO) established in 1930 to create conditions for women to take part in national development and to improve their position in society. In Ninh Binh, the women’s union counts more than 200 000 members. Membership is voluntary and paid: the fee is 6000 dong (US$0.34) annually, a not-negligible amount in a country where the poverty line is fixed at US$0.50 a day.  

 

About CBMS
 
The Community-Based Monitoring System (CBMS) is an organized way of collecting, analyzing, and verifying information at the local level to be used by local governments, national government agencies, nongovernmental organizations, and civil society for planning, budgeting, and implementing local development programs. It also serves to monitor and evaluate their performance. Piloted in the Philippines in 1994, it is now being implemented in 14 countries of Africa, Asia, and Latin America.
 
Identifying the poor

As WUNB President Vu Thi Tan explains, detailed information is needed for the union to carry out its work. But, she says, there is not enough data on life in the communities, on households, and on individuals — particularly women. To fill this gap, the WUNB collaborated in implementing a community-based poverty monitoring system (CBMS) in Nho Quan, the province’s poorest district, in 2007. CBMS was developed as part of research initially supported by Canada’s International Development Research Centre (IDRC) to determine micro impacts of macroeconomic and adjustment policies.

Gia Son is one of the 27 Nho Quan communes that participated. Le Thanh Trinh, chairman of the Gia Son Commune Administration, explains that the data gathered is used to implement policies, such as tax exemptions for the poor, free education, and preferred credit rates. “We consider CBMS a very important socio-economic survey,” he says. “It’s very basic information to be collected on our households and communities, but it’s very comprehensive because we know the development process in our communes.”

They found, for instance, that 20% of commune households were poor — 179 of them. “It’s most important that the information serve poverty reduction in the communes,” he adds. The goal for 2008 was to reduce that rate by 3%, and to continue to do so every year until poverty was eliminated.

Collecting data for identifying the poor is not new in Vietnam. “We’ve been doing it since 1995 when benefits were provided,” says Le Thanh Trinh. But as Vu Tuan Anh, Director of the Socio-Economic Development Centre (SEDEC) in Hanoi and CBMS project leader, explains, existing surveys covered only limited samples so did not serve local needs. At that level, governments were mandated to annually identify poor households so that services could be targeted to them, but because income was the sole criteria used, that survey was not adequate for poverty analysis and development planning.

The gender dimension of poverty

In 1997 Vu Tuan Anh began working on the problems of data availability, the needs of local communities for socioeconomic data, and the capacity of communities to produce and use data, with support from IDRC. A pilot project to introduce a community-based monitoring system showed that it was both feasible and helpful to local officers and NGOs. Since then, the system has been refined and is now used at the central level by the Managing Office of Vietnam’s National Program of Poverty Reduction, at the provincial and district levels in five provinces in four different regions, and at the project level by the Poverty Reduction Project in two districts of Thanh Hoa province.

In Ninh Binh, says Vu Thi Thanh, WUNB Vice-President, CBMS began when the commune chairman gathered commune officers to talk about the survey objectives and to solicit their support. He asked the WUNB’s activists to act as enumerators. District personnel served as resource persons.

The questionnaire was very simple and clear, she says. And the results were good, and useful for their work. Until now, she says “we haven’t had a census of the commune, just sample surveys. Now in every village, we can identify poor households. And we know why they are poor, whether it is because of unemployment or poor knowledge of technologies or another reason.”

From the WUNB’s point of view, they also know how many households are headed by women — 2000 in Nho Quan district alone — and how many are poor. “We know about educational levels, information we never had before. Also, how many lack safe water and sanitation facilities. Based on this information the commune can develop plans to solve the problems.”

 
According to Le Thanh Trinh, to reach their goal they encourage households to use new crop varieties and technologies, and to engage in non-agricultural activities. “We will also organize training to raise educational levels,” he says. “And local governments have to cooperate with NGOs, like the Women’s Union, to provide assistance to poor households.”
 
But he’s all too aware that there are also many people near the poverty line who could easily slip under. “Our achievements are fragile,” he says. “If we have flooding again this year, many more may become poor.” The strategy, he says, is to concentrate assistance on vulnerable groups, like women-headed households, widows, and invalids. There are 41 such deprived households in Gia Son.
 
Same data, many uses
 
The Women’s Union has its own use for the data. “We use the data to prepare programs to support women, especially in areas like health care,” says Ms Thanh. “We use it especially for education programs, to increase the educational level of women.”
 
The information also has political uses. “It led the Secretary of the Party to issue a decision to improve women’s lives. Our recommendation to focus support first on womenheaded households was accepted by the province,” she says. “We also recommended a focus on indigent women who have no house or land. The province accepted this: the commune is responsible for providing them with land or assistance to build a house. Our third recommendation was that the government support them through cash transfers to improve the household economy — provide them with agricultural tools, for example, or chickens that they can use to generate income.”
 
But, she adds, when they receive this assistance the WUNB helps them build pens for the chickens and pigs and vaccinate the animals, and trains them to use the tools.
 
And the data is useful when disaster strikes. Nho Quan district is the poorest in the province, says Ms Thanh. When it suffered from flooding in 2007, the government provided assistance. The CBMS data was used to identify communes and people who should benefit from the assistance.
 
Facing challenges
 
While the commune authorities and Women’s Union are convinced of the usefulness of CBMS, they also point to some of the difficulties in carrying out the survey. One is physical: in the very mountainous Nho Quan district, it was costly and time-consuming to visit and interview every household. The population’s low educational level made selecting interviewers challenging: because those in administrative positions did not want to do the surveying, Women’s Union activitists were selected. As the 700 enumerators carried out their duties, their training proved to be inadequate to fully equip them for the work.
 
The questionnaire itself, although modified to reflect local needs, posed some problems since farmers’ measurement units did not correspond to international measures and could not easily be converted. Some figures were impossible to obtain — farmers who grow cassava only for household consumption never calculate their production, for instance. Some standard animals like buffaloes were listed on the forms, but not those that villagers usually keep — rabbits, for instance, and ducks and wild animals that have a high economic value.
 
Encoding also caused a bottleneck. In Ninh Binh, this was done by WUNB officers when they had some spare time, as well as by students. Processing was done by SEDEC as the capacity did not exist in the commune.
 
Positive changes in Ha Tay
 
Ha Tay, formerly a province in the Red River Delta close to Hanoi and a part of Hanoi since August 2008, faced similar challenges: a shortage of human and financial resources.
 
Here the CBMS was implemented by the Social Protection section of the Department of Labour, Invalids and Social Affairs (DOLISA), the province’s main poverty reduction and social welfare agency.
 
Two survey rounds have been carried out and used by local partners to analyze the poverty rate and different dimensions of poverty. The goals: to evaluate poverty reduction measures and readjust poverty reduction policies. “Overcoming poverty is a big challenge for the administration,” says Le Van Hoang of Ha Tay’s DOLISA. While Ha Tay’s economic development is higher than other Red River Delta provinces, its per capita income is half that of Hanoi.
 
The two CBMS surveys were carried out in 10 Ha Tay communes in 2006 and 2007 — a total of more than 8000 households. The goal, says Hoang, was to evaluate the results of the normal identification of poor households surveys done by the communes — based mainly on income — and to collect additional data. For instance, is this a woman-headed household? A veteran? What is their occupation? Age?
 
As in Ninh Binh, the questionnaire was modified to meet local needs. Housing is different here, for instance, and the animals kept by farmers are different. “We also collect data on land use and the reasons why they are poor — lack of training, or labour, or land. When we know the reasons for poverty, we know about their needs, and what to support,” says Le Van Hoang.
 
In Ha Tay, the longer CBMS questionnaire was compressed to focus on the areas the commune had responsibility to address — for instance, the question on asset ownership was dropped. “Goods ownership is not always directly related to poverty levels and it does not change annually,” explains Le Van Hoang. The survey was also limited to lowincome households because DOLISA did not have the resources to cover all households.
 
The survey results have led to positive changes in Ha Tay. “We have made recommendations to provincial officials and they have accepted them,” he says. For instance, based on the data on the housing situation, they recommended that a budget be allocated to help resolve the situation. “Our recommendation for training for the poor was accepted at the national level,” he says. “We need to provide technical training to farmers who have lost their lands.”
 
The data has also led to programs to extend the activities of a traditional handicrafts village and involve more people in the activities. The provincial government allocated D5 million (US$282) for vocational training for the poor, and D1 billion (US$56 400) for animal husbandry projects.
 
This case study was written by Michelle Hibler, senior writer at IDRC.
 
The views expressed in this case study are those of IDRC-funded researchers and of experts in the field.