REGIONAL POVERTY DISPARITY IN VIETNAM

Vu Tuan Anh Socio-Economic Development Centre Hanoi, Vietnam

Vietnam has 82 million inhabitants, living in different regions, which have different geographical, climate, economical and social characteristics. Economic growth, livelihood, income, living conditions and poverty of population are varried by regions. Vietnam has made cosiderable progress in poverty reduction. The poverty rate in the whole country has halved after less than ten years. However, speed of poverty reduction is still low in some regions. Identification of regional disparities of multidimensional poverty provides background for right targeting to the poor and elaboration of appropriate poverty policies in each specific region. In some last years, the Vietnamese CBMS project has co-operated with local partners in 5 provinces to conduct poverty studies. These 5 provinces are located in 5 different regions. This paper presents results of CBMS implementation in Vietnam's localities and using CBMS data for analysis of regional disparities of poverty. The main objective of the analysis is to find out the possible explanatory factors affecting the disparity. Based on results of analysis of regional disparity in poverty, some poverty alleviation policies and proposal of application of a multidimensional poverty index are recommended. This paper consists of three parts. The first part gives an overview of poverty reduction and regional poverty disparity in Vietnam. The second part examines regional disparity in multi-dimenssional aspects of poverty, basing on analysis of CBMS data. The third part suggests a regional poverty index, which might be used for regional poverty comparison.

I. Economic Growth and Regional Poverty Disparity Economic growth is first and essential factor for improvement in the living standards of the population and to reduce absolute poverty. Where there is fast and stable econonomic growth, poverty is less and easierly alleviated. It is through the process of direct economic impacts on population's employment and income generation, and the process of trickle down that growth benefits percolate to the lowest strata of the society. The increased disparities in the distribution of living benefits both across social strata and between different regions, which are widely experienced in many developing countries reflect the failure of distribution policies, inappropriate social and political institutions. Regional disparity in living standard is used to be measured by difference of income, expenditure of population in different regions. It is measured also by indicators of specific aspects of welfare, such as education, health, etc. Regional disparity in poverty is measured by difference of poverty rates of regions. In the 1990s, Vietnam witnessed acceleration in the growth rate of GDP. It registered an average annual growth rate of GDP of 7.6% in the last 16 years (1990-2006). During this period, Vietnam’s population was increased 118 %, GDP grew to 322%. This caused GDP per capita to grow to 253% or 6% annually. Vietnam’s per capita GDP was US$288 in 1995, $639 in 2005, and $835 in 2007. Thank the stable economic growth, poverty rate has reduced significantly. The poverty rate measured by Vietnam Living Standard Surveys reduced continuerly from 58.1% in 1993 to 16,0% in 2006. Poverty rate in 2002 has halved, comparing to that in 1993, and poverty rate in 2006 has also halved, comparing to that in 1998. In average poverty rate halved in every 8-9 years. This means the first goal of MDGs is completed. Vietnam is considered as a successful case of poverty reduction among developing countries. Figure 1: GDP and poverty rate in 1993-2006

60 70

50 58.1 60 55 50 40 37.4 45.5 40 30 28.9 30 20 19.5 27.1 35.1 16 20 10 10 13.2 0 0 1993 1998 2002 2004 2006

GDP (bill. US$) Poverty rate (%)

Sources: General Statistical Office, Vietnam Statistic Yearbooks.

2 The Human Poverty Index for developing countries (HPI-1) developed by UNDP is an indication of the standard of living in a country . It is a measure of the extent to which people in a country are not benefitting from development. While Human Development Index consists of three essential dimensions of human life: longevity, knowledge and standard of living, and assesses these components as development; HPI assesses the same three components from an opposite point of view to take into account factors that HDI does not include1. HPI of Vietnam has significantly reduced in the last decade (Table 1).

Table 1: Human Poverty Index (HPI-1) of some Asian countries

HPI Rank 1998 2005 1998 2005 Malaysia 14.0 8.3 18 16 Thailand 18.7 10.0 29 24 China 19.0 11.7 30 29 Vietnam 28.2 15.2 47 36 Philippines 16.1 15.3 22 37 Indonesia 27.7 18.2 46 47 India 34.6 31.3 58 62

Source: UNDP - Human Development Reports 2000, 2007/08.

Despite of these successes, poverty reduction faces certain limitations and remains a major concern for Vietnamese society, namely:

- Poverty reduction is still fragile, unsustainable. A large proportion of people has low income, which closed to poverty line; therefore they easily fell to poverty when natual disasters, economic crisises happen, or even when a member in their families get serious sick. The probability of falling again into poverty is still common.

- The disparity in income and living standard between rural and urban areas, between different strata, between the poor and the rich provinces tends to increase. The income gap

1 Three components of HPI are following: 1) Longevity - measured by the proportion of the population not expected to survive to the age of 40 years.

2) Knowledge - measured by the adult illiteracy rate.

3) Standard of living - a composite value measured by the proportion of the population without access to clean water, health services, and the proportion of children under the age of 5 years who are underweight.

3 between the richest quintile and the poorest quintile doubled in 15 years (According to living standard survey of Vietnam's General Statistical Office, it was 4.2 in 1990 and 8.37 in 2006). The Gini index based on income indicator grew up from 0.35 in 1994 to 0.42 in 2006, while Gini index based on expenditure indicator was 0.34 in 1993, but only 0.37 in 20062. There are two opposite tendences: in one hand the poverty reduces, but in other hand the inequality increases.

- Regional poverty disparity is extending despite of reduction of poverty rates in all regions of the country. This paper will study more deeply on this tendence.

Regional poverty disparity is reflected through some following features.

First, poverty has declined significantly in all major regions in the country, but at different rates.

According to division of the General Map 1: Vietnam's 8 regions Statistical Office, there are 8 main geo-economic regions:

1. Red River Delta (11 provinces, population 18.4 mil.) 2. Northeast Mountains (11 provinces, population 9.5 mil.) 3. Northwest Mountains (4 provinces, population 2.7 mil.) 4. North Central Coat (6 provinces, population 10.7 mil.) 5. South Central Coast (6 provinces, population 7.2 mil.) 6. Central Highlands (5 provinces, population 4.9 mil.) 7. Southeast Region (8 provinces, population 14.2 mil.) 8. Mekong River Delta (13 provinces, provinces, population 17.5 mil.)

Among these 8 regions, four regions Northwest, Northeast, North Central Coat and Central Highlands are less developed in term of economic level. They are uplands and most of

2 General Statistical Office, Statistics Yeabook 2007. Hanoi 2008.

4 ethnic minority population lives there. They face many constrains in development process, including a difficult physical environment, hinders access to infrastructure and low educational level of population. The poverty rate areas is still high in these regions:

- The Northwest Region has though small population, but the highest poverty rate. During the 8-year period of 1998-2006, it fell by 24.4 percentage points (from 73.4% in 1998 to 49.0% in 2006).

- The Northeast was the second poor region in 1998, but in 2006 it ranked at the fourth place. The poverty incidence fell by 37.0 percentage points (from 62% to 25%).

- The Central Highland region was the third poor in 1998 and did not changed it's rank in 2006, despite it's poverty fell 23.8 percentage points (from 52.4% to 28.6%).

- The North Central Coast was in 1998 at the fourth rank, but it became the second poor region in 2006. The poverty incidence has declined by 19 percentage points (from 48.1% to 29.1%).

The rest four regions have reduced their poverty at different rates: the Red River Delta declines by 20.5% percentage points, the Mekong Delta by 26.6 percentage points, the South Central Coast by 21.9% percentage points, and the Southeast by only 6.4 percentage points, but it's original poverty rate was already low 12.2% in 1998. (Table 1)

Second, as results of the different speeds of poverty reduction, there exists a big diffenrence between poverty incidences of regions and this gap is widening for the poorest regions. The gap of poverty incidence has been reduced in most of regions, except three of the above four poorest regions. Compared to the lowest poverty rate in Southeast region, the poverty difference of the Northwest incresed from 6.0 times in 1998 to 8.4 times in 2006; the North Central Coast from 3.9 to 5.0 and the Central Highlands from 4.3 to 4.9 times. In the same time, the difference of Northeast has decreased from 5.1 to 4.3. (Figure 2)

5 Table 1: Difference of poverty rate

1998 2002 2006 Rate Difference Rate Difference Rate Difference (%) (time) (%) (time) (%) (time) Whole country 37.4 28.9 16.0 Red River Delta 29.3 2.4 22.4 2.1 8.8 1.5 Northeast Mountains 62.0 5.1 38.4 3.6 25.0 4.3 Northwest Mountains 73.4 6.0 68.0 6.4 49.0 8.4 North Central Coast 48.1 3.9 43.9 4.1 29.1 5.0 South Central Coast 34.5 2.8 25.2 2.4 12.6 2.2 Central Highland 52.4 4.3 51.8 4.9 28.6 4.9 Southeast Region 12.2 1.0 10.6 1.0 5.8 1.0 Mekong River Delta 36.9 3.0 23.4 2.2 10.3 1.8

Source: General Statistical Office, "Vietnam Statistics Yearbook 2007". Notes: 1) Poverty rate was calculated by poverty line which is measured by per capita expenditures in a month as follow: 1998: 149,000 VND; 2002: 160,000 VND, and 2006: 213,000 VND. 2) Regional poverty gap is the difference between poverty rates of other regions to the Southeast Region which has the lowest poverty rate.

Figure 2: Poverty gaps between regions (Southeast Region = 1)

9 8 Northwest Mountains 7 Central Highland

6 North Central Coat 5 Northeast Mountains 4 South Central Coast 3 2 Mekong River Delta

1 Red River Delta 0 1998 2002 2006

Source: General Statistical Office, "Vietnam Statistics Yearbook 2007".

6 II. Regional Poverty Disparity Measured by CBMS Data

During two last years 2006-2007, the CBMS-Vietnam project team has been supporting local partners in 5 provinces, which are representatives for 4 regions, to conduct CBMS in 50 communes (45 rural communes and 5 urban wards) of 14 districts.

Table 2: Scope of CBMS implementation in 2006-2007

Region Province Number Number of Number Number of of rural of urban households districts communes wards Red River Delta Ha Tay 10 9 1 10,016 Ninh Binh 1 24 1 16,725 Northern Mountains Yen Bai 1 3 2 6,314 Southern Central Coast Quang Ngai 1 5 0 6,382 Central Highlands Lam Dong 1 4 1 3,500 TOTAL 5 14 45 5 42,937

In the surveyed localities, there are 3 whole districts (in Yen Bai, Ninh Binh and Lam Dong). Except Quang Ngai, all surveyed localities consist of one or two urban wards and several rural communes. Although the structure of population in term of rural-urban is not similar in surveyed localities, but the collected data can be used as examples for comparing localitires in different regions.

Using CBMS-approach, in 2004-2005 in the framework of a research project of the Vietnam Academy of Social Sciences we have conducted a nation-wide sample household survey. The sample of this survey covered 14,044 households in 133 rural communes and urban wards of 63 provinces (of which 11,740 rural households in 60 provinces and 2304 urban households in 16 cities). In each province two communes /wards were selected, and in each commune/ward approximately 100 households were randomly selected for interview. The results of this survey showed changes of socio-economic situation of households and communities. [Vu Tuan Anh & Nguyen Xuan Mai (2007)]. In this paper we use also data of this survey, especially data of rural households for analysis of regional disparity.

7 The indicator set used in CBMS is modified in regions and provinces to adapt to circumstances of localities. However, a number of core indicators are the same in all surveyed localities. In this paper, we use these common core indicators for examining regional disparity in different aspects of socio-economic situation, which closely related to poverty. These aspects are: (1) household structure, (2) income, (3) dwelling, (4) property, (5) education, and (6) health care.

2.1. Population and household structure:

There is no significant difference in the sex structure of the population of the surveyed localities. The ratio of female population is a bit higher than that of male population. It's happenes now too in whole Vietnam (50.86% to 49.14% in 2007) as well as in almost all regions, except in Northwest and North Central Coast.

Regarding the age structure, the significant reduction in fertility and the gradual increase in life expectancy have resulted in the ageing population in Vietnam, with a smaller proportion of young population vis-a-vis the greater proportion of old population. The proportion of population aged less than 15 years old has reduced from 39% in 1989 to 33% in 1999 and further down to 26% in 2007. In the same time, due to higher and higher index of life expectancy, the proportion of population aged 65 and over in the country increased from 5% in 1989, 6% in 1999 to 7% in 2007. [GSO (2008a)].

Data of age structure of the surveyed households in all regions reflects this tendency in Vietnam's population change. However, data of regions also shows that the poorest regions (Northwest, North Central Coast, and Central Highlands) have higher proportions of young population (0-14 year old), and accordingly a lower proportion of people in labourable age and also old-aged comparing to other regions. The cause is the fact that in these poor regions, the family planning works have weak effects on fertility behaviour and having many children is still a popular phenomenon, especially among some ethnic minority communities .

The age structure of the population is used to calculate the total dependency ratio. This indicator reflects the relationship of age, fertility and mortality levels with labour force in the country. The dependency ratio is an indicator used to assess the quality of the population and it reflects the burden of the working age population able to work. Total dependency ratio is defined as the percentage of the number of people under 15 years old (0-14) plus old people (65 years old and over) per people aged 15-64.

8 Table 3: Population structure of the regions

Whole Red North North North South Central South Mekong country River west Central Central Highlan east River east Delta Coast Coast ds Delta

Surveyed households 11.740 2.001 2.695 731 999 999 1.014 901 2.400 Surveyed population 54.526 8.478 12.122 3.656 5.035 4.448 4.911 4.223 11.653 1. Sex structure - Male 50.5 50.1 50.6 49.8 49.9 51.1 51.2 50.4 50.5 - Female 49.5 49.9 49.4 50.2 50.1 48.9 48.8 49.6 49.5 2. Age structure (%) 0 - 14 27.6 24.7 27.8 30.6 33.5 28.2 33.3 27.6 23.1 15 - 64 67.3 68.5 66.9 64.8 61.9 66 63.4 68.4 71.8 65 and over 5.1 6.8 5.3 4.6 4.6 5.8 3.4 3.8 5.2 3. Dependency ratio (%) - Total dependency 48.6 46.0 49.5 54.3 61.6 51.5 57.9 45.9 39.4 - Child dependency 41.0 36.1 41.6 47.2 54.1 42.7 52.5 40.4 32.2 - Old dependency 7.6 9.9 7.9 7.1 7.4 8.8 5.4 5.6 7.2

The decline in total dependency ratio of Vietnam has been contributed mainly by the reduction of the child dependency ratio (0-14). This could be the result of the effective family planning programmes. The child dependency ratio of the whole Vietnam has declined over the same period from 84 in 1979 down to 39 in 2007. That is, after 26 years, the child dependency ratio has reduced to more than a half. Meanwhile the old dependency ratio has continuously increased but slightly. Data of the regions resembles to the national one. Again here, three poorest regions have the highest dependency ratios.

The average household size also reflects the differences in population change. While the average household size in the country is 4.6, the sizes of households varies in regions and three poorest regions have larger household size. Accordingly, large-scalled households (6 persons and over) in these regions occuppy bigger proportions. Households with 3-5 members are the most popular type in all regions. Especially, the proportion of households with 4 members - nuclea family with 2 children - is about one third of total number of households.

Poor households have larger household size. This tendency is precised for all regions. The witness is larger size of households belonging to low-income quintiles compared to that of higher-income quintiles.

9 Table 4: Structure of households by size (%)

Whole Red North North North South Central South Mekong country River west Central Central Highlan east River east Delta Coast Coast ds Delta

Average HH size 4.6 4.2 4.5 5.0 5.0 4.5 4.8 4.7 4.9 (person) Of which: Labourable 3.1 2.9 3.0 3.2 3.1 2.9 3.1 3.2 3.5 Dependent 1.5 1.3 1.5 1.8 1.9 1.6 1.8 1.5 1.4 Number of dependent 1.5 1.5 1.5 1.5 1.6 1.6 1.6 1.5 1.4 per labourable HH size by income quintile * Quintile 1 5.0 4.5 4.7 5.0 5.2 5.1 5.5 5.0 5.3 * Quintile 2 4.9 4.5 4.8 5.4 5.5 4.7 4.9 4.9 5.1 * Quintile 3 4.6 4.2 4.5 5.2 5.0 4.4 4.7 4.9 4.8 * Quintile 4 4.5 4.1 4.4 5.0 4.8 4.3 4.8 4.6 4.8 * Quintile 5 4.2 3.9 4.0 4.4 4.7 4.0 4.3 4.0 4.3 Structure of HH by size (%) * 1 person 1.1 1.6 1.4 0.4 0.7 1.5 1.3 0.8 0.8 * 2 persons 5.9 8.4 5.9 4.4 4.6 8.0 5.3 5.7 4.1 * 3 persons 14.4 14.8 15.6 10.1 10.9 15.3 14.8 16.2 14.4 * 4 persons 31.0 38.2 34.5 33.1 23.5 26.1 24.8 27.1 29.6 * 5 persons 22.3 21.7 22.0 21.2 24.3 21.7 23.6 23.5 21.8 * 6 persons and over 25.4 15.2 20.7 30.9 35.9 27.3 30.3 26.7 29.4

2.2. Income

Income is the major indicator, which is used by Vietnamese governmental authorities for identification of the poor. The Ministry of Labour, Invalids and Social Affairs has defined the national poverty line for every 5-year period, using monthly per capita income indicator. The local authorities use this poverty line for identifying the poor and distributing support and benefits to them. Household's income is also used for analysis of living standards, poverty and social stratification.

Two opposite tendencies exist in Vietnam during the fast economic growth: in one hand poverty rate reduces, but in other hand inequality in income distribution among social groups and regions increases. According to the national household surveys made by the General Statistical Office, while poverty rate halved during the last 7-8 years, the income difference between the rishes andthe poorest quintile increased from 7.3 times in 1996 to

10 8.37 times in 2006. The Gini index of income distribution increased from 0.36 to 0.42 in the same time.

Implemented CBMS in provinces of Vietnam consideres income as one of the most important indicators for comparison of regions and communities. Calculating average value, annual turnover per household in the whole country is 22.4 million Vietnam Dong (VND).Households in the Mekong River Delta have the largest scope of economic turnover with 33.7 mill. VND. Following are Southeast (30.7 mill. VND), Central Hishlands (25.8 mill. VND), South Central Coast (21.5 mill.VND), North east (17.7 mill.VND), the Red River Delta (16.8 mill. VND), Northwest (15.4 mill.VND) and lastly North Cenral Coast 913.8 mill. VND). Comparing to the lowest turnover level of North Central Coast, the largest scope is equivalent to 2.4 times, and the average scope 1.6 times. After deduction of expences from total turnover, the rest value is net income of households. In average, income per households in whole country is 18.4 mill. VND. The highest level is achieved in Southeast (27.2 mill. VND), then the Mekong River Delta (25.3), Central Highlands (20.8), South Central Coast (19.1), Northeast (15.6), the Red River Delta (14.1), Northwest (13.5) andat the last rank North Central Coast (10.8). Figure 4: Average household's turnover and income in regions (mill. VND)

33.7 30.7 27.2 25.8 25.3 22.4 21.5 20.8 18.4 17.7 19.1 16.8 15.6 15.4 14.1 13.5 13.8 10.8

Country Red River Northeast Northwest North South Central Southeast Mekong Delta Central Central Highlands River Delta Coast Coast

Turnover Income

Comparing the lowest income level, the highest level is 2.52 times higher, and the average level is 1.7 times. Namely: • North Central Coast = 1,00 • South Central Coast = 1,77 • Northwest = 1,25 • Central Highlands = 1,93 • Red River Delta = 1,31 • Mekong River Delta = 2,34 • Northeast = 1,44 • Southeast = 2,52

11 The difference of 2.52 times between the highest and the lowest average income shows that income disparity of regions is quite significant. However, according to the national household surveys conducted by GSO, this regional disparity is much wider - 2.85 times.

The average income per capita in a month is 351 thousands VND. The regional difference is quit big. Taken the lowest income of the North Central Coast as 1, indexes of the other regions are as follows: Northwest 1.29, Red River Delta 1.57, Northeast 1.65, South Central Coast 2.04, Central Highlands 2.10, Mekong River Delta 2.49, and Southeast 2.87.

Figure 5: Average monthly per capita income (thousand VND)

531 461 390 352 379 290 307 239 185 North Coast South Coast River Delta Central Central Delta Country Mekong Central Northeast Red River Highlands Northwest Southeast

Comparing the lowest income level (North Central Coast), the highest level is 2.87 times higher, and the average level is 1.9 times. Namely: • North Central Coast = 1,00 • South Central Coast = 2,05 • Northwest = 1,29 • Central Highlands = 2,11 • Red River Delta = 1,57 • Mekong River Delta = 2,49 • Northeast = 1,66 • Southeast = 2,87

A deeper analysis of income differenciation of quintiles helps to identify tendencies of social changes and to supply background for policy making process.

Data shows that the poverty rate and depth in Vietnam's rural areas are quit high. Because of this, the income differentiation in rural areas is sharp. Taken the poverty line of 200 thousand VND defined by MOLISA as criterium for poverty rate calculation for rural areas, one can remark that all households of the Quintile 1 and most of the Quintile 2 are poor. The poverty rate is 30-35%, which is similar as result of the national surveys in 2003-2004.

12 The income difference of quintiles between the poorest (North Central Coast) and the richest (Southeast) regions increases from 1.31 times in Quintile 1 to 1.89 in Quintile 5. That means the poverty situation is similar, but the richness has different levels in different regions. Table 5: Monthly per capita income by region and quintile (thousand VND)

Whole Quintile Quintile Quintile Quintile Quintile Quintile 5 : country 1 2 3 4 5 Quintile 1 Rural area 352 88 164 248 381 877 10.0 - Red River Delta 290 85 157 226 321 664 7.8 - Northeast 307 83 149 221 322 761 9.1 - Northwest 239 62 111 1687 272 584 9.4 - North Central Coast 185 54 103 152 214 405 7.5 - South Central Coast 379 103 187 272 404 928 9.0 - Central Highlands 390 68 148 257 478 1001 14.7 - Southeast 531 109 207 348 549 1439 13.2 - Mekong River Delta 461 112 208 311 488 1186 10.6 Max (Southeast) : Min (North 1.73 1.31 1.39 1.58 1.70 1.89 Central Coast)

The income distribution has not significant difference between regions. As data shows, in rural areas of the whole country 20% households belonging to Quintile 1 possesses only 5,7% of total income, while 20% households belonging to Quintile 5 possesses 46,8% of total income. The poorer regions have smaller gap between the rich and the poor. In the poorest region the gap between income share possessed by Quintile 5 and that of Quintile 1 is 6.8 times, while in the richest regionthis index is 10.1. Table 6: Income distribution (% total income) Total Quintile Quintile Quintile Quintile Quintile Quintile 5 : 1 2 3 4 5 Quintile 1 Rural area 100.0 5.7 10.4 14.9 22.2 46.8 8.3 - Red River Delta 100.0 6.4 11.9 16.0 22.4 43.3 6.7 - Northeast 100.0 5.9 10.6 14.7 20.8 47.9 8.1 - Northwest 100.0 5.5 10.5 15.7 23.8 44.4 8.0 - North Central Coast 100.0 6.2 12.5 16.8 22.5 42.0 6.8 - South Central Coast 100.0 6.5 10.9 15.2 21.9 45.4 7.0 - Central Highlands 100.0 4.2 8.5 13.8 25.3 48.2 11.4 - Southeast 100.0 4.8 9.1 15.2 22.3 48.6 10.1 - Mekong River Delta 100.0 5.6 10.2 14.1 21.9 48.2 8.6 Max - Min 2.3 4.0 3.0 4.5 6.6

13 2.3. Dwelling

Most of households in Vietnam ownes a house. In rural areas, almost all households have their piece of residential land and house. In the urban areas 90% households ownes a housing place (house, apartment or room), and only 10% rents dwelling [Vu Tuan Anh & Nguyen Xuan Mai (2007)].

The types of dwelling are diversified by regions because of the difference climate conditions, traditional housing habits of ethnic groups and living standards. For identification of living standards, however, one can classify dwelling in some types by criteria of solidity of construction and conveniences. There are three types of dwelling which are used by localities for identifying living standards and poverty: (i) Permanent houses, which consist of brick/betone houses (multi-storey or one-storey) and good wooden houses; (ii) Semi-permanent houses (wooden, brick dwelling of low quality); (iii) Temporary houses (bamboo houses, tent, dilapidated houses). Poor households owne certainly the third type of dwelling, and many of them possess also the second type of dwelling. Besides, a small number of young families and migrants do not have their owned dwelling.

In the National Program for Poverty Reduction, supporting poor households in "rubing out" temporary tents, degraded bamboo houses and constructing new dwelling is one important activity, despite of small proportion of temporary dwelling left in localities. Til the beginning of 2005, there were 4 provinces completed this objectives and in the beginning of 2006, 17 provinces more achieved the goal of in "rubing out" temporary dwellings.

There is still a noticeable number of households with temporary dwelling in the poor regions. The proportion of households which owne temporary dwelling is 17.7% in the whole country. The regions having high percentage of this dwelling type are Mekong River Delta (29.3%), North Central Coast (24.4%), Southeast (24.2%), Northwest (23.6%), Central Highlands (19.2%). Only the Red River Delta has low persentage of this dwelling type (2.8%). Regions in the North have lower proportion of temporary dwelling than regions in the South, because the climate in the North is cold in winter. (Table 7)

14 Table 7: Types of dwelling (%)

Whole Red North North North South Central South Mekong country River west Central Central Highlan east River east Delta Coast Coast ds Delta Proportion of households possessing dwelling (%) * Multi-storey 4.2 12.2 5.5 1.7 0.6 1.2 2.3 2.1 1.2 permanent house * One-storey 31.2 55.3 23.7 24.9 44.8 59.0 11.5 20.9 17.1 permanent house * Semi-permanent 46.1 29.2 56.5 49.9 29.9 26.7 64.7 52.5 51.7 dwelling * Temporary dwelling 17.7 2.8 14.1 23.6 24.4 10.7 19.2 24.2 29.3 * No owned dwelling 0.7 0.5 0.2 0.0 0.3 2.4 2.3 0.3 0.7 Average living area of main dwelling (m2) * Multi-storey 80 51 94 82 78 91 120 177 147 permanent house * One-storey 67 43 69 62 56 74 106 119 93 permanent house * Semi-permanent 82 29 124 69 47 51 70 87 78 dwelling * Temporary dwelling 55 29 80 65 46 29 34 53 54

Figure 6: Structure of dwelling types in regions

100% No owned 80%

60% Temporary

40% Semi-permanent

20% Permanent 0% North South River Central Central Delta Country Mekong Central Red River Northeast Highlands Northwest Southeast

15 Poor households and young families possess mostly temporary dwelling. Approximately 1/3 of households belonging to the quintile 1 (the poorest) have this dwelling type. The proportion of this dwelling type decreases with increasing income. (Table 8) The proportion of households possessing permanent dwelling increases with increase of income. This tendency is available in all regions. The Red River Delta has the highest proportion of this dwelling type with 55.8% households in Quintile 1 and 75.8% in Quintile 5. In the other regions, the number of households having permanent dwelling has trend to increase.

Table 8: Types of dwelling by regions and income quintile (%) Whole Red North North North South Central South Mekong country River west Central Central Highlan east River east Delta Coast Coast ds Delta Permanent dwelling (%) Total 35.6 67.5 28.9 26.7 45.9 60.7 14.4 22.8 18.5 * Quintile 1 25.8 55.8 19.4 24.7 36.5 48.5 6.4 12.2 7.7 * Quintile 2 29.5 67.0 19.8 21.9 36.0 53.5 7.9 23.3 10.4 * Quintile 3 33.6 66.5 25.0 25.9 46.0 62.0 9.3 19.4 16.7 * Quintile 4 40.0 72.6 35.3 26.0 51.3 63.5 19.2 26.1 21.7 * Quintile 5 49.3 75.8 45.1 34.9 60.0 75.5 29.2 32.6 36.0 Semi-permanent dwelling (%) Total 46.1 29.0 56.4 49.5 30.6 24.2 67.9 52.3 51.8 * Quintile 1 40.2 35.0 51.3 20.5 24.5 29.0 69.3 37.8 37.9 * Quintile 2 47.6 31.3 62.2 51.4 32.5 31.5 64.0 46.1 50.0 * Quintile 3 50.8 32.0 61.9 57.1 34.0 23.5 70.1 61.7 58.1 * Quintile 4 47.5 24.4 56.3 63.0 32.7 21.0 66.0 55.6 58.5 * Quintile 5 44.4 22.3 50.5 55.5 29.5 16.0 69.8 60.2 54.3 Temporary dwelling (%) Total 18.2 2.9 15.3 23.4 26.4 10.4 20.1 24.4 29.4 * Quintile 1 32.8 8.0 27.6 54.8 38.5 21.0 22.8 48.3 53.3 * Quintile 2 22.1 1.5 16.3 26.7 42.5 11.0 23.6 27.2 37.7 * Quintile 3 15.1 2.0 12.8 15.6 21.0 7.0 21.1 18.9 25.2 * Quintile 4 13.2 1.7 12.1 10.3 17.6 8.0 21.2 16.7 20.5 * Quintile 5 8.1 1.3 7.8 9.6 12.5 5.0 11.9 11.0 10.2

16 2.4. Ownership of durable consumer goods Ownership of valuable consummer goods reflects level of household's living standards. It also shows level of satisfaction of some basic needs, such as transportation, access to information, access to living convenience. Regarding transportation means, bicycle and motocycle are most popular individual transport means of Vietnamese. 47.8% of rural households possessing at least a motocycle. In average, there is one motocycle per two households, and every 100 people possesse 12 motocycles. The poorest region (North Central Coast) has the lowest number of per capita motocycles. More than ¾ of households possess at least a bicycle. The Mekong River Delta, where water transport is more popular than land transport, has the lowest percentage of ownership of bicycles. In average, every 100 people have 27 bicycles. 13.8% of households doesn't possess any motocycle or bicycle. Regarding equipment for accessing to information, tiviset is popularly used by people. 76.6% of households possess a tivi, of which 62.9% have a color tivi and 13.7% have a black-white tivi. This type of tivi is used mostly by the poor, or where there is no grid electricity yet. The difference between regions in ownership of tivi is significant. The poorest regions have lower percentages, namely Northwest 59.2%, North Central Coast 65.0%, Northeast 72.1% and Central Highlands 72.8%. In the sametime, the percentage in other regions are higher: Red River Delta 80,7%, South Central Coast 81,7%, Mekong River Delta 84% and Southeast 87.1%. In average, there are 35 video-audio equipments available per 100 people. The highest number is in Red River Delta, Mekong River Delta and Southeast (about 40 pieces), while the lowest number is in the poorest region (22 pieces in North Central Coast). 16.4% of households still do not possess any video-audio equipment to access to information. As ussual, the poor regions have higher proportion of households,which do not possess any equipment,namely: Northwest 29%, North Central Coast 26%, Central Highlands 21.5%, Northeast 20.5%; while the other regions have much lower proportion: South Central Coast 13.7%, Red River Delta 11.1%, Mekong River Delta 10.6%, and lastly Southeast 7.7%.

17 Table 9: Possession of durable consumer goods Whole Red North North North South Central South Mekong country River west Central Central Highlan east River east Delta Coast Coast ds Delta Percentage of households possessing goods (%): * Radio receiver 36.2 31.0 30.1 37.3 26.9 38.6 37.1 47.7 45.3 * B&W tiviset 13.7 11.6 16.8 13.3 8.9 4.9 12.4 17.0 17.3 * Colour tiviset 62.9 69.1 55.3 46.0 56.1 76.8 60.4 70.1 66.8 * Video, VCD, DVD 32.3 40.4 26.0 22.2 14.2 32.5 40.0 33.4 39.5 player * Audio equipments 13.9 7.7 8.9 9.6 5.4 18.4 21.6 17.1 23.3 * Electric fan 76.9 84.6 76.1 59.9 82.2 89.2 49.9 80.2 79.3 * Sewing machine 12.9 8.8 11.3 15.5 3.2 6.8 4.6 6.1 30.1 * Fridge 9.0 12.6 7.1 3.3 3.6 8.1 9.6 12.0 11.3 * Motocycle 47.8 39.3 45.6 40.8 33.5 66.3 56.5 64.3 47.8 * Bicycle 77.4 83.5 75.6 78.2 88.1 81.3 72.6 82.4 68.0 * Telephone 11.6 10.7 7.6 4.2 6.0 14.1 10.6 15.9 19.0 * Washing machine 1.1 0.6 0.4 0.1 0.3 1.2 3.7 1.7 1.4 * Computer 2.3 5.4 0.6 0.0 0.3 1.7 3.5 3.0 2.7 Households not 16.4 11.1 20.5 29.0 26.0 13.7 21.5 7.7 10.6 possessing any video- audio equipment (%) Households not 13.8 12.1 16.8 15.5 8.0 10.7 11.8 4.3 19.5 possessing any motocycle, bicycle (%) Number of 12.0 10.2 11.4 8.6 7.1 18.4 13.7 17.0 12.3 motocycles per 100 people Number of bicycles 27.1 36.4 26.9 25.0 29.6 29.8 21.9 28.2 20.9 per 100 people Number of video- 35.0 39.1 31.0 25.9 22.3 39.2 35.9 40.6 40.5 audio equipments per 100 people

Possession of durable consumer goods is also varried by households belonging to different income quintiles. Indicators of possession of three goods - tiviset, motocycle and telephone - show clearly correlation between living standards and satisfaction of needs for transport, access to information, and communication. (Table 10). Posession of tiviset is saturated by the rich households, while proportion of poor households (belonging to quintiles 1 and 2), who do not have any tiviset is still high (40- 50% in the poor regions).

18 Possession of motocycle is at 60-80% by the richer quintiles and at only 20-30% by the poor quintiles. 20-30% households of the richer quintile have a telephone, while it is a rare equipment for the poor households. Table 10: Possession of durable consumer goods by income quintile (% households) Whole Red North North North South Central South Mekong country River west Central Central Highlan east River east Delta Coast Coast ds Delta Tiviset (%) Total 76.6 80.7 72.1 59.2 65.0 81.7 72.8 87.1 84.0 * Quintile 1 58.5 66.8 52.4 39.0 45.0 72.5 58.4 65.6 61.5 * Quintile 2 70.2 77.5 64.3 46.6 55.0 82.5 56.7 85.0 79.6 * Quintile 3 78.2 82.8 72.0 59.2 68.5 78.5 71.1 93.9 88.1 * Quintile 4 86.1 87.8 84.0 75.3 73.4 85.0 86.2 93.9 93.3 * Quintile 5 90.1 88.8 88.1 76.0 83.0 89.5 91.6 97.2 97.7 Motocycle (%) Total 47.8 39.3 45.6 40.8 33.5 66.3 56.5 64.3 47.8 * Quintile 1 26.1 21.5 24.6 16.4 17.0 49.0 35.6 35.0 21.5 * Quintile 2 37.5 30.0 32.2 31.5 25.0 59.5 41.4 60.0 37.5 * Quintile 3 45.8 36.5 41.7 36.1 28.0 64.5 56.4 71.1 46.7 * Quintile 4 59.0 49.1 55.4 49.3 44.7 77.0 69.0 76.7 61.8 * Quintile 5 70.6 59.5 74.3 70.5 53.0 81.0 80.2 78.5 71.7 Telephone (%) Total 11.6 10.7 7.6 4.2 6.0 14.1 10.6 15.9 19.0 * Quintile 1 4.2 4.5 1.7 1.4 2.0 5.5 5.0 3.3 8.1 * Quintile 2 6.3 7.3 3.0 1.4 3.5 6.5 4.4 12.8 10.2 * Quintile 3 9.7 7.5 6.3 1.4 2.5 9.0 8.3 17.2 18.8 * Quintile 4 14.7 13.5 10.6 6.2 6.5 15.5 16.7 22.2 22.3 * Quintile 5 23.0 21.0 16.8 11.0 15.5 34.0 18.3 23.8 35.6

2.5. Education

We used two indicators for analysis of education situation: illiteracy and child school enrolment.

The rate of literacy calculated for people from 6 and over is 94.5% in the whole country. Accordingly, illiteracy rate is 5.5%. The mountainous and poor regions have higher illiteracy rate, namely: Northeast 6.9%, Central Highlands 9.1%, and Northwest 14.9%.

19 The percentage of people who have primary education (from grade 1 to grade 5) is 31.5%, lower secondary (6-9 grades) 41.6%, upper secondary (10-12 grades) 18.8%, college and university 1.8%.

Table 12: Education levels of 6 year-old and over population (%)

Whole Red North North North South Central South Mekong country River west Central Central Highland east River east Delta Coast Coast s Delta Illiteracy 5.5 3.0 6.9 14.9 3.8 3.0 9.1 2.5 4.4 Primary (1-5 grades) 31.5 19.5 25.0 42.0 29.6 34.7 36.3 32.7 40.5 Lower secondary (6-9 41.6 54.0 43.8 31.0 49.6 36.8 34.3 38.3 36.2 grades) Upper secondary (10- 18.8 20.8 21.3 11.3 15.3 21.9 17.7 23.1 16.4 12 grades) Vocational secondary 0.9 1.1 1.2 0.4 0.5 1.0 0.6 1.0 0.7 College, university 1.7 1.6 1.8 0.4 1.1 2.4 1.9 2.1 1.8

Regarding child's schooling, there is a small pcentage of children who give up study or not go to school at all. According to survey data, 5.5% of children in schooling age (6-14) does not attend study. The population in the North part of the country has a tradition of paying more attention on giving education to children. In the Red River Delta, the number is the smallest, only 2.3%. The Northeast and North Central Coast regions, despite of being poor regions, have also low percentages (3.4% and 3.6%). The other regions have significantly higher percentages than the national average level, namely South Central Coast 6.2%, Mekong River Delta 7.3%, Southeast 7.5%, Northwest 8.2% and Central Highlands 9.5%.

Poverty is an important reason explaining why children do not go to school. 46.3% of children, who have dropped-out the study, are caused by such reasons like lack of labour in the family, too high costs of schooling, etc. Invalidity, serious sickness caused 14.5% of not-schooling children. 27.6% of total number of not-schooling children has dropped out the study because they have bad results in study. The awareness of parents and children on necessarity of education caused 9.5% of the cases.

The structure of causes of child's not-schooling is different among the regions.

20 Table 13: Child's schooling Whole Red North North North South Central South Mekong country River west Central Central Highlan east River east Delta Coast Coast ds Delta Percentage of 6-14 5.5 2.3 3.4 8.2 3.6 6.2 9.5 7.5 7.3 years old children not attending school (%) * Boys 3.0 1.8 1.9 3.0 2.0 2.9 5.3 4.9 3.8 * Girls 2.5 0.5 1.5 5.3 1.6 3.3 4.3 2.7 3.5 Why not go to school (% responses) * Lackof labour in 21.7 8.8 27.9 29.8 8.3 16.3 34.9 19.4 19.0 family * High costs of 24.4 17.6 21.3 27.7 41.7 40.8 17.5 22.6 19.0 education * Bad results in study 27.6 35.3 19.7 23.4 13.9 18.4 28.6 32.3 37.2 * Invalidity, sickness 14.5 38.2 13.1 6.4 33.3 20.4 3.2 16.1 9.1 * No neccessarity to 9.5 0.0 18.0 10.6 2.8 0.0 15.9 6.5 10.7 study * Other 2.3 0.0 0.0 2.1 0.0 4.1 0.0 3.2 5.0

2.6. Health

It's difficult to measure the level of satisfaction of people's basic needs in health care. In CBMS we use some simple indicators which indirectly reflect situation of health care of households. They are basic household's sanitary facilities, such as supplying safe drinking water, using sanitary toilet, having a bathroom.

Vietnam's Goverment consideres supply of safe water for population and securing sanitary living environment as one of the national prioritised targets. The National Targeted Program of Safe Water Supply and Rural sanitary Environment had invested 7,000 billion VND (approx. equivalent to 0.5 bil. USD) in the period of 1999-2005. Until the end of 2005, 68% of rural population accessed to safe drinking water. Still 32% of rural population used unsafe water (from rivers, ponds, lakes, etc.). In the period of 2006-2010, this National Targeted Program has planned to invest 22,600 bill. VND (1.4 bil. USD). Poor regions belong to prioritised areas of this program.

Sources of water are diversified in the regions. One used to considere piped water, rain water, water from deep-driled wells as certainly safe. Water from dug wells may be safe or unsafe depending on concrete conditions of locations and seasons. Water from natural surface sources like rivers, lakes, ponds, streams is considered as unsafe.

21 Accepting working definition that water from dug well is considered as unsafe, we can remark that only 50% of population access to safe water. In the mountainous regions like Northwest, Northeast, Central Highlands and in the Southeast, more than 70% of population still use unsafe water sources. (Figure 7).

Table 14: Access to safe water for dringking and cooking (%)

Whole Red North North North South Central South Mekong country River west Central Central Highlan east River east Delta Coast Coast ds Delta Piped water, public 8.0 10.0 7.3 1.8 9.8 5.5 0.1 11.2 11.3 reservoir Rain water 21.6 65.0 0.3 13.8 1.3 0.0 1.0 1.4 42.3 Deep-drilled well 20.0 20.4 15.7 1.0 37.4 27.0 1.4 13.9 29.2 Dug well 37.7 4.1 55.5 43.8 45.8 67.0 91.5 61.7 1.3 Pond, lake, river 12.6 0.5 21.1 39.6 5.7 0.6 6.0 11.8 15.9 Note: Sum of all types might be over 100% because one household may use several water sources.

Figure 7: Access to safe drinking water (%)

100% 90% 80% 70% Unsafe 60% 50% 40% Safe 30% 20% 10% 0% Delta Country Central Delta Coast Coast Red River Northeast Highlands Southeast Northwest North Central North South CentralSouth Mekong River

The poor households face more difficulties in access to safe water sources. Taken two types of sources: deep-drilled well and natural surface sources and comparing percentage of users by income quintiles, one can see that the poorer quintiles have smaller percentages using the deep-drilled water, for which households have to invest a certain amount money

22 to equip; and they have larger percentages using the "free-of-charge" but unsafe water from natural surface sources. (Table 15)

Table 15: Access to safe and unsafe water by income quintile (%)

Whole Red North North North South Central South Mekong country River west Central Central Highlan east River east Delta Coast Coast ds Delta Deep-drilled well (%) * Quintile 1 17,9 17,8 14,3 0,0 29,0 26,0 1,0 10,6 29,4 * Quintile 2 18,4 19,8 13,9 1,4 30,0 23,5 0,5 12,8 30,2 * Quintile 3 20,0 22,0 13,3 0,7 37,5 27,5 1,0 14,4 31,7 * Quintile 4 21,7 20,2 14,9 1,4 43,2 30,5 3,0 16,7 33,8 * Quintile 5 24,2 22,8 19,2 2,1 48,5 30,0 1,5 15,5 38,3 Pond, lake, river (%) * Quintile 1 11,0 0,5 18,7 52,1 5,0 0,5 9,9 10,6 6,0 * Quintile 2 10,3 0,5 18,9 41,8 3,5 0,0 15,8 11,1 4,0 * Quintile 3 8,1 0,3 16,1 40,1 3,5 0,5 3,4 11,7 1,5 * Quintile 4 6,8 0,2 11,3 37,0 2,5 0,5 0,5 11,7 3,1 * Quintile 5 5,0 0,3 8,2 30,8 1,5 0,0 0,0 10,5 1,0

There is only 41.5% of households in the whole survey sample possessing a sanitary toilet. This figure is similar to the result of the health survey done by the Ministry of Health in 2003. Among regions, the Red River Delta has the highest percentage (64.7%), then follow South Central Coast (54.9%), Southeast (49.1%), Northeast (46.3%), North Central Coast (45.5%). The Northwest has only 22.9%, Central Highlands 23.3%, and Mekong River Delta 20.0%. These figures are too low, compared with the target of the National Strategy of Safe Water Supply and Sanitary Environment, in which 70% of households will possess sanitary toilets till 2010.

Table 16: Types of toilet (%)

Whole Red North North North South Central South Mekong country River west Central Central Highlan east River east Delta Coast Coast ds Delta Sanitary types 41.5 64.7 46.3 22.9 45.5 54.8 23.3 49.1 20 Unsanitary types 46.9 31.7 42.3 71.2 30.8 27 53 49.1 69.2 No toilet 11.6 3.6 11.5 5.9 23.7 18.1 23.6 1.8 10.8

23 III. Proposal of a Composite Poverty Index

Poverty rate measured by value indicators such as income and expenditures of households and individuals gives a general picture of poverty, but doesn't reflect concrete aspects of living in which people are in shortage. Poverty is a multi-dimensional phenomenon. Poverty is foremostly unsatification of human basic needs such as food, cloth, housing, education, healthcare, information, etc. However, if indicators of basic needs are used separately, one cannot define overall poverty rate, as well as compare poverty of different regions and in times.

In the CBMS, which was piloted by the Vietnam research project, poverty is comprehensively reflected by a set of indicators that include both value indicators (income) and the basic households needs (e.g., food intake, clothing, housing, transportation, education, healthcare). A study has been also done for identifying a composite poverty indicator for Vietnam [L.M. Asselin (2002); L.M. Asselin & Vu Tuan Anh (2005)]. In this study, eight simple non-monetary, categorical indicators of human and physical assets developed in CBMS research in Vietnam, have been analysed and aggregated in a composite indicator using the factorial technique. These indicators reflect the following groups of basic needs of population: (1) income generation (underemployment); (2) health (chronic sickness, access to safe drinking water, sanitary facilities); (3) education (adult illeracy, child under schooling); (4) housing (types of dwelling); and (5) access to information (ownership of tiviset, radio receiver).

The comparison of this multidimensional approach to poverty measurement with the moneymetric one base on total household expenditures shows that the CBMS type indicators present a strong analytical potential for multidimensional poverty analysis, being complementary to the more standard moneymetric analysis. In addition, due to their low cost, they should be looked at to meet the objective of regularly producing largely disaggregated poverty profiles for a more efficient monitoring of poverty reduction policies and programs.

During implementation of the proposed composite poverty index in localities, a problem is bared itself. It seems that the factorial analysis technique, precisely the multiple correspondence analysis (MCA) is implemented with difficulties, since local partners, especially people from district and commune levels are not able to understand and to use it.

In order to follow one of fundamental principles of CBMS, namely the simplicity of

24 indicators and methods, we propose to develop a composite poverty index,which is constructed withour weighting primary indicators. In practise, this type of composite index has been implemented widely. Human Development Index (HDI), Human Poverty Index (HPI), MDGs Index and some other indexes developed by UNDP belongs to this type. The Human Poverty Index fordeveloping countries (HPI-1), for example, attempts to capture deprivations in three essential dimensions of human life already reflected in the HDI. It includes in itself three components: - Longevity - measured by the proportion of the population not expected to survive to the age of 40 years (P1).

- Knowledge - measured by the adult illiteracy rate (P2). - Standard of living - a composite value measured by the proportion of the population without access to clean water(P31), health services (P32), and the proportion of children under the age of 5 years who are underweight (P33).

The composite variable P3 is constructed by taking a simple average of the three variables

P31, P32 and P33. Thus: P3= (P31 + P32 + P33) / 3 The HPI-1 is computed by the following formula: 3 3 3 1/3 HPI-1 = [1/3(P1 +P2 +P3 )]

The composite MDGs index includes 8 goals divided into 18 targets with 48 indicators. Despite of it's complexity, this index is calculated by a similar method as that of HPI. Implementing this computation method of composite indexes, we propose to compute a CBMS Composite Poverty Index (CBMS-CPI), using set of CBMS indicators, namely:

1- Food poverty: percentage of households which have income below food poverty line

(P1).

2- Dwelling poverty: percentage of households which have temporary dwelling and not have owned dwelling (P2).

3- Information poverty: Percentage of households which do not possess any audio-video equipments (P3).

4. Communication poverty: Percentage of households which do not possess any motocycle and bicycle (P4).

5. Knowledge poverty: Simple average of adult illiteracy rate and childt under-schooling rate (P5 = ½[P51 + P52])

25 6- Health poverty: Simple average of percentage of households, which do not access to safe drinking water and not possess a sanitary toilet (P6 = ½[P61 + P62]). In a better option, where data is available, we can add other indicators, which reflect fundamental situation of health poverty, like percentage of child malnutrition.

The CBMS Composite Poverty Index is simple average of the 6 above poverty indicators:

CBMS-CPI = 1/6(P1+P2+P3+P4+P5+P6)

CBMS-CPI has some following advantages:

- It containes the major aspects of human poverty, therefore it is a multi-dimensional poverty indicator. One can use it for measuring and comparing poverty across time and regions.

- Major aspects of poverty reflect most targets of the national poverty reduction program. Therefore one can use CBMS-CPI for monitoring poverty reduction activities and programs.

- Computing method is very simple and easily to be understood, so that everybody at grassrot levels can use.

- Excepts income, all rest indicators base on simply to be collected data. However, income is the data, which communities have to colect and to monitor regularly poverty by MOLISA poverty line. This poverty line is approximately at the level of food poverty. Therefore we can use this data for pomputing CBMS-CPI.

To test CBMS-CPI, we use CBMS data for computing and comparing CBMS-CPI of regions. (Table 17 and Figure 8)

Comparing CBMS-CPI with income poverty P1, one can see how the multi-dimensions poverty and purely value poverty are different. (Figure 9).

26 Table 17: Computing CBMS-CPI of regions

Whole Red North North North South Central South Mekong country River west Central Central Highlan east River east Delta Coast Coast ds Delta

P1: Income 15.5 12.9 23.2 46.1 29.4 21.3 29.2 6.1 15.3 poverty *

P2: Dwelling 18.4 3.3 14.3 23.6 24.7 13.1 21.5 24.5 30 poverty

P3: Information 16.4 11.1 20.5 29.0 26.0 13.7 21.5 7.7 10.6 poverty

P4: 13.8 12.1 16.8 15.5 8.0 10.7 11.8 4.3 19.5 Communication poverty

P5: Knowledge 5.5 2.7 5.2 11.65 3.7 4.6 9.3 5.0 5.9 poverty Illiteracy 5.5 3.0 6.9 14.9 3.8 3.0 9.1 2.5 4.4 Child 5.5 2.3 3.4 8.2 3.6 6.2 9.5 7.5 7.3 underschooling

P6: Health 54.4 20.0 65.2 80.3 53.0 56.4 87.1 62.2 48.6 poverty No safe water 50.3 4.6 76.6 83.4 51.5 67.6 97.5 73.5 17.2 No sanitary 58.5 35.3 53.8 77.1 54.5 45.1 76.6 50.9 80.0 toilet CBMS-CPI 20.7 10.4 24.2 34.4 24.1 20.0 30.1 18.3 21.7

Note: * Data of poverty rates is taken from GSO national household survey in 2006 [GSO (2008)]. Poverty rates have been measured by monthly average income per capita according to the latest standard of the Government for the period 2006-2010 with different standards as follows: 260 thous. VND for urban; 200 thous. VND for rural (excluding effect of price index).

Figure 9: Comparison of income poverty rate and CBMS-CPI

50 Income poverty CBMS-CPI 45 40 35 30 25 20 15 10 5 0 North Coast South Coast Central Central Delta Country Central Mekong Northeast Red RiverRed Highlands Northwest Southeast River Delta

27 Figure 8: Regional CBMS-CPI and it's components

IV. Conclussions 1. Regional disparity in poverty is one of the key challenges, which Vietnam faces on it's current development path. Despite of remarkable achievements in economic growth and poverty reduction, regional disparity and social inequality may be strong factors hampering the socio-economic progress in the future. Vietnam has to pay more attention on policies of inequality reduction towards regions, social groups and ethnic groups. 2. CBMS can be used as an appropriate tools for poverty monitoring, especially by local authorities, social organisations and communities. Using CBMS data, one can analyse diversified aspects of human life, including poverty, and do comparison across regions and times.

28 3. A CBMS Composite Poverty Index reflects the approach of multidimensional poverty. It can be used by local communities for analysis of different aspects of poverty, as well as for comparison of multidimensional poverty accross regions, localities and times. A Composite Poverty Index constructed by a simple method and based on community-based survey data is feasible to be implemented widely in poverty monitoring and evaluation of poverty reduction activities.

REFERENCES

• Asselin Louis-Marie (2002). Multidimensional Poverty. Theory. IDRC. in MIMAP Training Session on Multidimensional Poverty. Quebec. June 2002. • General Statistical Office. GSO (2008a). The 2007 Population Change and Family Planning Survey: Major Findings. Hanoi. • General Statistical Office. GSO (2008b). Statistics Yearbook of Vietnam 2007. Hanoi. • Louis-Marie Asselin & Vu Tuan Anh (2005). Multidimensional Poverty Monitoring: A Methodology and Implementation in Vietnam. Vietnam’s Socio-Economic Development Review. No. 41. Hanoi. March 2005. • Louis-Marie Asselin & Vu Tuan Anh (2008). Multidimensional Poverty and Multiple Correspondence Analysis. In "Quantitative Approaches to Multidimensional Poverty Measurement" edited by Nanak Kakwani and Jacques Silber. Palgrave Macmillan. New York. • Nguyen Xuan Mai & Vu Tuan Anh (2007a). Reduction of Urban Poverty. Vietnam’s Socio-Economic Development Review. No. 51. September 2005. Hanoi. • UNDP. Human Development Reports. • Vu Tuan Anh & Vu Van Toan (2004). Implementaion of the community-based poverty monitoring in Vietnam. Vietnam’s Socio-Economic Development Review. No. 39. Hanoi. September 2004. • Vu Tuan Anh & Nguyen Xuan Mai (2007). Socio-Economic Changes of Households. Publisher of Social Sciences. Hanoi.

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