POVERTY DYNAMICS IN RURAL VIETNAM:
WINNERS AND LOSERS DURING REFORM
PATRICIA JUSTINO
Poverty Research Unit
University of Sussex, UK
JULIE LITCHFIELD
Poverty Research Unit
University of Sussex, UK
Abstract
This paper analyses poverty dynamics in Vietnam during the ‘Doi Moi’ renovation period and tries to identify the
winners and losers from the economic and trade reform process implemented in Vietnam in the late 1980s. Our
results are based on data available for a panel of 3494 rural households interviewed in 1992-93 and 1997-98. We
find that movements in and out of poverty between the two periods vary substantially across population subgroups,
suggesting that not everyone benefited equally from the process of reform. We model poverty dynamics using a
multinomial logit model that explains movements in and out of poverty between the two periods of time in terms of
household characteristics, characteristics directly related to the economic reforms and changes in the returns to
those characteristics. The results suggest that changes in household poverty status in Vietnam are correlated with
geographic location, access to key institutions and infrastructure, the education level of the head and spouse, as
well as changes induced by the economic reform. These results are robust to shifts in the poverty line and changes
in model specification. The paper forms part of a wider study funded by the UK Department for International
Development that examines the impact of trade reform and trade shocks on household poverty dynamics.
JEL codes: C23; I32; O53.
Keywords: Poverty dynamics, trade liberalisation, economic reform, panel data, Vietnam.
April 2003
Corresponding author: Patricia Justino, Poverty Research Unit, University of Sussex, Afras C, Falmer, Brighton BN1 9SJ, UK.
Tel. +44 1273 877402. E-mail: [email protected]
Acknowledgements: We are very grateful to Bob Baulch, Rhys Jenkins, Neil McCulloch, Andy McKay, Howard White and, in
particular, Alan Winters, for useful discussions and to Yoko Niimi and Puja Vasudeva-Dutta for excellent research assistance.
We would also like to thank the participants of seminars and conferences at Sussex (November 2001 and January 2003),
Nottingham (April 2002), Hanoi (September 2002) and the 2002 International Association of the Review of Income and Wealth
conference (Stockholm) for helpful comments. This paper is part of the project “The Impact of Trade Reforms and Trade Shocks
on Household Poverty Dynamics” (ESCOR-R7621) funded by the UK Department for International Development as part of their
Globalisation and Poverty Research Programme. Views and opinions expressed in this paper are, however, those of the authors
alone. We are grateful to the World Bank for making the trade data available for the DFID-funded Globalisation and Poverty
Research Programme’s projects on Vietnam.
Poverty Dynamics in Rural Vietnam
1. INTRODUCTION
Vietnam has been one of the success stories in the attack on poverty in developing countries. During the
1990s, poverty rates in Vietnam decreased dramatically from 58.1% in 1992-93 to 37.4% in 1997-98
(table 1), whilst more than a quarter of all households that were poor in 1992-93 moved above the
official poverty line in 1997-98 (table 2).1 Although poverty amongst urban households, households
living in the south of the country,2 households belonging to the ethnic majority Kinh3 and households in
which the head had a white collar job decreased more sharply, the reduction in poverty was substantial
for most sub-groups of the population (table 1) and was accompanied by large improvements in a range
of human development indicators (see Haughton, Haughton and Phong, 2001; Glewwe, Gragnolati and
Zaman, 2001 and Litchfield and Justino, 2002).
The economic and social changes experienced by Vietnam have been largely ascribed to the “Doi Moi”
or renovation policies introduced in 1986.4 These policies aimed at transforming Vietnam into an
outward-oriented economy and included the removal of price controls on many goods (including
fertilisers), the decollectivisation of land,5 the provision of greater autonomy to the private sector, the
reduction or removal of trade barriers and the opening up of the Vietnamese economy to foreign direct
investment.6 The largest and most visible economic changes took place in Vietnam’s export sector,
particularly in the rice market, where many tariffs were eliminated. Export rice quotas also increased
1
A household is defined as being poor if real consumption expenditure per capita is below an officially defined poverty line. In
Vietnam that poverty line is 1160 thousand dongs per year per person in 1992-93 and 1790 thousand dongs per year per person
in 1997-98. Those values were calculated based on the cost of a basket of food items that provide the minimum amount of 2100
calories per person per day plus a non-food component. For a detailed discussion of poverty issues in Vietnam and the analysis
of the sensitivity of poverty estimates in Vietnam to the choice of poverty line see Litchfield and Justino (2002).
2
For administrative purposes, Vietnam is divided into seven regions: the Northern Uplands, the Red River Delta, the North
Central, the Central Coast and the Central Highlands in the north and the South East and the Mekong River Delta in the south.
3
The VLSS specify eight ethnic groups: the Kinh (the Vietnamese majority), the Tay, the Thai, the Chinese, the Moung, the
Nung, the H’mong and the Dao. All remaining ethnic groups are aggregated under the heading ‘others’. These groups are usually
grouped for convenience into the majority Kinh, the ethnic Chinese (a special group that includes a small minority of quite welloff households) and other ethnic groups that are often located in specific regions only. See van de Walle and Gunewardena
(2001) and Baulch et al. (2002) for more detailed analyses of the social and economic position of ethnic groups in Vietnam.
4
Economic reforms, in particular agricultural reforms, started earlier in the late 1970s. However, the ‘Doi Moi’ process that
started in 1986 comprised a larger commitment to economic reforms and their extension to the whole economy.
5
Land was owned solely by the state prior to the ‘Doi Moi’ and land transactions were not allowed. After 1993, land tenure was
extended to 20 years for annual crop land and 50 years for perennials. Households were also given extended rights to exchange,
transfer, lease, inherit and mortgage land (Benjamin and Brandt, 2002).
2
Poverty Dynamics in Rural Vietnam
significantly and the private sector was allowed a greater role in the production and export of rice. As a
result, rice production and rice exports increased sharply during the 1990s (table 3), turning the country
from a net rice importer to the world’s second largest exporter of rice in 1997 after Thailand (in quantity
terms).7 Increases in land titling, removal of price controls and other trade reforms have also affected the
markets for other agriculture crops (particularly coffee) and industrial products (especially, marine
products, textiles and garments, footwear and food processing) (table 3).8
Despite the commitment of the Vietnamese government to the new economic and trade liberalisation
programmes, not all reform policies were immediately implemented. Until very recently, the trade
regime in Vietnam was still quite restrictive and involved a high level of state intervention (Niimi,
Vasudeva-Dutta and Winters, 2002; Nielsen, 2002). Even though the liberalisation programme has not
been fully implemented, Vietnam’s gross domestic product per capita grew at an average of almost 7%
during the period between 1990 and 1998 (table 3) and real consumption increased significantly in the
same period, both in the rural and urban sectors and across all regions (though it was higher in the urban
sector and in the southern regions - Mekong River Delta and South East) (table 1). These changes were
accompanied by an increase in private sector employment, which led to an overall employment growth
rate of almost 2% during the 1990s (table 2). Furthermore, although data on wages in Vietnam is scarce,
evidence suggests that real wages started to rise after 1995 (Economist Intelligence Unit, various issues;
O’Connor, 1996; World Bank, 1999; CIEM, 2000; IMF, 2000).
Increases in per capita incomes and real consumption during the 1990s, combined with a large reduction
in poverty, suggest that the economic reforms that took place after 1986 have had a significant impact on
the social and economic structures of Vietnamese households. However, although the existence of a link
6
Although flows of foreign direct investment in Vietnam were close to zero during the 1980s, they averaged around 5% of the
country’s GDP in the second half of the 1990s (Dollar, 2002).
7
Vietnam’s exports of rice in volume terms made up 17% of total world rice exports in 1997. However, this corresponded to 5%
in value terms (which puts Vietnam as the sixth largest exporter of rice in value terms in 1997). The lower value share is due to
the fact that Vietnam entered the world rice market at a time when rice prices were falling. This meant that Vietnam was forced
to sell its rice at a discount price in order to remain competitive (Nielsen, 2002).
8
For a more detailed account of trade-related changes in Vietnam see Niimi, Vasudeva-Dutta and Winters (2002), also part of
the ‘Impact of Trade reforms and Trade Shocks on Household Poverty Dynamics’ project.
3
Poverty Dynamics in Rural Vietnam
between economic reforms and poverty reduction in Vietnam is indisputable, it is not clear how the
macroeconomic changes that took place in Vietnam during the 1990s were transmitted to each individual
household and why some households have benefited more than others from the reforms. As shown in
table 1, the dramatic decrease in poverty that occurred in Vietnam between 1992 and 1998 did not
benefit all households equally and consumption inequality increased in the country by 12.5% during the
period (Litchfield and Justino, 2002). In addition, despite the large decrease in the poverty headcount
between 1992-93 and 1997-98 and the large economic achievements, a significant number of Vietnamese
households (28.73% overall; 34.19% in the rural sector) remained poor in 1997-98 and some households
fell into poverty (4.74% overall; 5.34% in the rural sector) (table 2). These were, as before, households
in the remote and mountainous Northern Uplands, ethnic minorities, large households, with a head
employed in the agriculture sector and with low levels of education.
In order to understand the relationship between economic reforms and poverty, it is important to discern
the reasons why this has happened and to determine whether movements into poverty and failures to
escape poverty are related in any way (and how) to the economic reforms implemented in Vietnam after
1986. Also we can not overlook the fact that, alongside the economic reforms, households and
individuals may have been subject to other changes that result from normal family and community living.
In a period of five years, household characteristics such as demographic composition, education
attainment and so forth may have changed and households may have been subject to shocks (for instance,
illness and weather and other covariant risks).9 This paper analyses the links between household poverty
in Vietnam during a period of economic reform by examining how those reforms may have impacted on
households’ incomes (and thus poverty) and comparing those effects with the impact in the levels and
changes of specific household characteristics that do not have necessarily to be related to economic
9
In previous work (Litchfield and Justino, 2002), we found that households in Vietnam have undergone changes that may be
associated with the reduction in poverty observed in the country between 1992-93 and 1997-98: there has been a significant
decreased in the percentage of households headed by a younger individual (and thus more prone to be poor), the number of very
large households decreased by over four percentage points, the number of households with a large number of young children also
decreased significantly (indicating that fewer children were born), the education level of household heads and their spouses
improved sharply and the number of household heads employed in sectors other than the agriculture sector increased. Although
some of these changes may be associated with the economic reforms that took place in Vietnam after 1986, they reflect, to a
4
Poverty Dynamics in Rural Vietnam
reforms.10 The paper aims not only to identify the winners and losers from the economic reforms but also
to understand why and how some households have benefited more than others from the new economic
policies. We provide thus both a framework to analyse the impact of trade and other economic reforms
on household poverty dynamics and a methodology to distinguish these effects from other household
characteristics.
Together with Niimi, Vasudeva-Dutta and Winters (2002), this is one of the first studies to explore
directly the empirical mechanisms of transmission between macroeconomic trade reforms and household
poverty dynamics. This is a particularly important topic in view of increased globalisation of the world
economy. One of the most visible manifestations of globalisation is the increase in international trade
and the implementation of trade liberalisation policies and reductions in trade barriers. These policies are
believed to provide opportunities for many people, especially those in developing countries. However
some people can be constrained in their ability to share in the opportunities generated by increased
international trade and may even suffer from trade reforms due to their vulnerability to trade shocks. We
expect the results obtained in this paper to contribute towards the understanding of how national policymakers and international institutions can maximise poor peoples abilities to seize opportunities that
economic openness may provide.
In order to understand the direct causes and consequences of poverty, it is important to know whether
poverty is simply a transitory state experienced by some households at one time or another or whether it
is a persistent phenomenon for certain groups. This information is central for the design and targeting of
policies aimed at reducing poverty. This paper focuses therefore not so much on changes in poverty rates
per se but in movements in and out of poverty (poverty dynamics), thereby taking advantage of the
important panel dimension of the Vietnamese household surveys.
large extent, intergenerational changes within the household (panel attrition) as well as the impact of non-economic policies such
as those promoting ‘one-child families’ and literacy-oriented programmes.
10
According with the 1997-98 commune survey, most communes attribute changes in their harvest patterns between 1992-93
and 1997-98 to weather changes and spreading of pests rather than change in agriculture policies. Only a few communes mention
the introduction of new seeds and new techniques as one of the biggest reasons for increases or decreases in harvest between the
two years.
5
Poverty Dynamics in Rural Vietnam
The results discussed in this paper are based on household consumption data provided in the Vietnam
Living Standards Measurement Surveys (VLSS) for 1992-93 and 1997-98. The VLSS data is obtained
from nation-wide household surveys conducted in 1992-93 (October 1992 to October 1993) and 1997-98
(December 1997 to December 1998), and contains valuable information on 4800 households and 120
communes surveyed in 1992-93 and 6000 households and 150 communes interviewed in 1997-98.11
These surveys are particularly useful as they allow the construction of a panel of 4303 households
interviewed in both years. Given that we only have available two time periods, it will not be possible to
analyse the duration of poverty spells or to determine the extent of persistent poverty in Vietnam.12
However, the panel feature of the VLSS data allows us to trace across the five years those households
that have remained poor, have moved out of poverty or have fallen into poverty and determine which
particular household characteristics are associated with those movements. The analysis developed in this
paper will be based on a panel of 3494 rural households.13 14
The paper is organised as follows. Section 2 provides a description of changes in variables directly
affected by the economic reforms and how those changes may have impacted on the dynamics of
household poverty in Vietnam. We focus on two important reforms: (i) liberalisation of agriculture
markets (rice and other crops) and of prices of agriculture crops and inputs (particularly, fertilisers),
which has affected household production decisions, and (ii) liberalisation of export markets, following
the removal of export quotas and tariffs, which has influenced employment patterns of Vietnamese
11
These surveys were conducted by the Vietnam’s General Statistical Office and the Ministry of Planning and Investment, with
financial assistance from the United Nations Development Programme (UNDP) and the Swedish International Development
Agency (SIDA) and technical assistance from the World Bank.
12
See Jenkins (1998) and Devicienti (1992) for analyses of poverty dynamics in the UK when several survey years are available.
13
Our analysis focuses only on those households living in the rural sector. Our focus on the rural sector is justified by the fact
that 78% of all households in Vietnam in 1997-98 lived in rural areas (80% in 1992-93) and 61% of all Vietnamese households
were employed in the agriculture sector in 1997-98 (65% in 1992-93) (table 1). Furthermore, two of the key economic reforms
implemented in Vietnam (reform of rice pricing and rice trade and de-collectivisation of the agricultural sector) were directed at
the rural sector.
14
Although the two survey years are, individually, representative of the population, the rural panel is not representative of the
total rural population (see Haughton, Haughton and Phong, 2001). However, our various calculations have shown that the
poverty levels and the changes in the population shares in the household in the rural panel across several socio-economic
characteristics do not differ significantly from the results for the whole rural population in each year. Thus, although we must be
careful when extrapolating our results to the whole rural sector, we believe that the differences between our results and the total
rural population results will not differ significantly.
6
Poverty Dynamics in Rural Vietnam
households. In section 3, we investigate the relationship between poverty dynamics, reform-induced
variables and other household characteristics (demographic characteristics, employment status, education
levels, illness and weather shocks and commune-related variables). We consider not only the levels of
those variables but also changes in household characteristics that took place between 1992-93 and 199798 and changes in reform-related variables. This relationship is modelled using a multinomial logit
model, which allows us to estimate the probabilities of a household (i) staying poor in both year, (i)
escaping poverty, (iii) falling into poverty or (iv) remaining above the poverty line in both years. We
provide also a decomposition of the impact of the various household characteristics and changes to those
characteristics on the probability of a household escaping or falling into poverty. Section 4 provides a
sensitive analysis of the results obtained in the previous section to changes in the poverty line and
compares the outcomes of the multinomial logit model with those of a consumption model. Section 5
concludes the paper.
2. ECONOMIC CHANGES AND POVERTY IN VIETNAM
Economists know very little about the behaviour of households during economic reforms and their
adaptation mechanisms to economic change. Winters (2000) and McCulloch, Winters and Cirera (2001)
are two of the first studies to examine this issue by analysing the links between trade liberalisation
programmes and household poverty. They explore how the effects of trade reforms trickle down to
households via their direct effects on product and labour (and other factors) markets and, indirectly,
through changes in labour revenue and public spending on social sectors. The effect of trade
liberalisation on household poverty via the product markets operates by means of changes in prices,15
which affect nominal and real incomes of households in their capacity as producers or consumers of the
product. Trade liberalisation policies can also affect household poverty via changes in wages and
employment occurred in the labour markets and through changes in government transfers.
7
Poverty Dynamics in Rural Vietnam
In the case of Vietnam, household incomes and consumption expenditures are likely to have been
significantly affected by the large increase in the exports of agricultural crops (particularly, rice and
coffee) and industrial products (especially, marine products, textiles and garments, processed food and
footwear) that took place in the country during the 1990s (table 3). In this analysis we focus on two main
mechanisms of transmission: (i) changes in the prices of agriculture crops and inputs (such as fertilisers),
which resulted from the elimination of trade tariffs and increases in export quotas, and (ii) the creation of
new employment opportunities in the main export industries.
Production of agriculture crops
The economic reforms implemented in Vietnam have triggered changes in the prices of commodities for
which tariffs were removed and new export quotas were established. Changes in prices, in turn, are likely
to have affected nominal and real incomes of households in their capacity as producers or consumers of
agriculture crops, if price changes were transmitted to the internal markets.16 When the price of a certain
good increases, producers of that good will benefit from the trade reforms, while consumers may lose
out. The final effect depends on how each household responds to external economic shocks and is able to
accommodate price changes by, for instance, switching to more profitable crops (Winters, 2000;
McCulloch, Winters and Cirera, 2001). It is well known that some population groups are likely to benefit
more than others from new economic incentives given that some groups are traditionally more vulnerable
to shocks than others, both in terms of their exposure and their ability to adjust to them. As demonstrated
by Glewwe and Hall (1998) using panel data from Peru, poor households are more vulnerable to
macroeconomic shocks, either because they are more exposed (because, for instance, they rely on private
and/or public transfers) or because they are constrained in their ability to adjust to new market incentives
(due to, for example, lack of credit). Similar effects are observed in Vietnam, where, as we discussed
above, some groups seem to have benefited more from the economic reforms than others.
15
Lowering tariff barriers is likely to reduce the price of imported goods, whereas export liberalisation may lead to higher prices
for exported goods (Winters, 2000).
8
Poverty Dynamics in Rural Vietnam
Table 4 illustrates the amount of production, area cultivated and unit values (obtained from sales) for a
selection of agriculture crops cultivated in Vietnam. With the exception of non-rice food crops and
livestock,17 the price of all agriculture crops produced in Vietnam increased significantly between 199293 and 1997-98. Table 5 portrays in further detail changes in the prices of rice (the most important crop
cultivated in Vietnam) and coffee (the crop with the largest increase in production) between 1993 and
1998. The table shows a large increase in the international price of coffee and in the unit values of
coffee. The change in unit values of coffee sold (farm price) is larger than the change in the retail unit
values of coffee, which represents a benefit for households that produce coffee. The table shows also an
increase in the domestic price of rice and paddy between 1993 and 1998. This increase was similar to the
international price of rice and paddy and reflects the impact of trade reforms on the Vietnamese rice
sector. The increase in the prices of rice and paddy is reflected at the household level, although the unit
values of rice have increased by more than three times the increase in the price of paddy.18
Production decisions are also likely to be affected by changes in the cost of agricultural inputs such as
fertilisers,19 which has decreased on average by 23% between 1992-93 and 1997-98 (table 5). The
decrease in the cost of this important agricultural input would have benefited farmers and encouraged
increases in the production of agriculture crops (table 4).
16
Governments may continue to fix the internal prices of goods which they have officially liberalised internationally (Winters,
2000). See McCulloch, Winters and Cirera (2002) for a theoretical analysis of these transmission mechanisms.
17
This was possibly due to smaller than expected increases in the demand between 1992-93 and 1997-98 for non-rice foods
(meat, oils, fish, fruit and vegetables) (Benjamin and Brandt, 2002).
18
This result is similar to what others have found (see, for instance, Edmonds and Pavenik, 2002). We have also calculated the
commune prices of rice and paddy since unit values, which are choice variables and not real prices, are typically affected by
measurement errors (Deaton, 1997). We found that commune prices of rice had similar increases to unit values but commune
paddy prices increased by 33.9% (table 5). It is not clear, however, that commune prices provide the best estimation of prices in
the specific case of Vietnam. The commune prices reported in the household surveys refer to the average of three observations
made in the commune surveys (which were done separately from the household surveys). According to the basic information on
the questionnaires provided by the VLSS team, the observations did not, however, necessarily involve an actual purchase. As the
anthropometrists were not local people, it is thus very possible that the prices quoted are not the true prices of the locality
(VLSS, 2001: 21). Given this problems we will not focus in very much detail on the effects of unit values changes on poverty
dynamics.
19
Fertiliser supply constraints were significantly reduced in Vietnam during the 1990s with the removal of restrictions to import
fertilisers. After 1991, central and provincial state-owned enterprises that earned foreign exchange were allowed to import
fertilisers directly (Benjamin and Brandt, 2002).
9
Poverty Dynamics in Rural Vietnam
Rice is produced in large quantities in Vietnam and is the single crop whose production involves the
most number of households. This is not a surprising result as rice represents the main staple for
Vietnamese households, comprising 42% of all food expenditure (51% for households below the poverty
line) and 75% of all calorific intake of a typical Vietnamese household (Minot and Goletti, 1998).
Furthermore, some of the most significant and visible ‘Doi Moi’ reforms took place in the rice market,
where many tariffs were eliminated and export quotas increased. The liberalisation of the rice markets,
the consequent increases in the price of rice and decreases in the price of fertilisers would have thus
created incentives for households to increase rice production. Table 4 shows that the quantity of rice
produced in Vietnam increased by almost 35% between 1992-93 and 1997-98. There has also been
significant intensification of rice production as the increase in rice production was accompanied by a
decrease in the number of households producing rice and the area cultivated with rice.20 This is likely to
reflect improvements in technology used in the cultivation of rice.21
In comparison to rice, the cultivation of fruit and vegetables is relatively small in Vietnam because the
priority was to cultivate staple food in order to avoid famines and other food shortcomings (Thang,
2002). Fruit and vegetables were mainly cultivated for own consumption and seen as secondary to the
cultivation of rice. Conditions for the cultivation of fruit and vegetables have, however, improved during
the 1990s due to increased food stability, farmers looking for crops with higher values than rice,22 and
benefits from government regulations (in the import of seeds, machinery, fertilisers, etc) (Thang, 2002).
As a consequence, the production and area cultivated of non-rice crops increased significantly in
Vietnam between 1992-93 and 1997-98, indicating an intensification of agriculture diversification, most
likely due to improvements in market infrastructure, agriculture technologies and increased integration of
20
Note that the drastic decrease in the area cultivated with rice between 1992-93 and 1997-98 (93.56%) hides changes in land
concentration. While in 1992-93, 96% of all households in the rural panel did not have any rice land, this percentage decreased
to 59% in 1997-98. Furthermore, in 1992-93, most rice plots of households that cultivated rice were over 5000 m2 (61.4%),
which explains the large average of land cultivated with rice in 1992-93, in comparison with the 1997-98 average. In 1997-98,
most plots were between 100 m2 and 5000 m2. If we average the total area cultivated with rice over the whole panel we get a
value of 382.39 m2 for 1992-93 and 251.60 m2 for 1997-98, which represents a lower decrease (34.2%) in the average land
cultivated with rice.
21
In fact, rice productivity (measured by kilos of rice harvested per square metre of land cultivated with rice) for those
households that produce rice increased by 14.3% between 1992-93 and 1997-98.
10
Poverty Dynamics in Rural Vietnam
Vietnam in the world markets.23 The largest production increases were those of coffee (almost 200%),24
annual industrial crops and fruit crops. Although rice production grew at over 6% per year, production of
annual industrial crops, coffee and fruit crops grew over three times that rate. Furthermore, whilst the
area of land cultivated with rice decreased between 1992-93 and 1997-98, the area cultivated with nonrice crops increased on average by over 200% in the same period.
Increases in the production of rice, coffee and other agriculture crops are likely to have affected the
welfare status of Vietnamese households. Table 6 illustrates movements in and out of poverty for
households that produce rice, coffee and other crops. The table shows that more rice producing
households are poor in both years than households that do not produce rice. However, less rice producing
rural households fell into poverty and more rice producing rural households moved out of poverty in
1997-98. Similar results were obtained for households that produce non-rice crops, particularly coffee.25
This suggests that, although the production of rice has benefited a significant number of Vietnamese
households, increased diversification into other crops between the two survey years has contributed
positively towards poverty reduction in Vietnam during the same period.
Employment effects
The new economic reforms implemented in Vietnam in the 1990s have created incentives for the
establishment of new production units that, in turn, may have affected traditional employment structures
and created new jobs. This effect is bound to be particularly strong in the main export industries (marine
products, textiles and garments, processed food and footwear). A larger demand for marine products in
22
The price of rice dropped significantly world-wide since 1998 and even in 1992-93 and 1997-98 the unit values of paddy were
lower than those of other crops. Recall also that farm unit values of paddy were significantly lower than retail unit values of rice,
which may have led some farmers to swap to other more profitable crops.
23
This result has been obtained in other studies. Benjamin and Brandt (2002), for instance, suggest that households that lived in
regions where it was not lucrative to cultivate rice may have decided to cultivate other crops.
24
Vietnam started to produce coffee intensively in the Central Highlands after 1995, following a boom in the world price of
coffee (Thang et al., 2001). This resulted in a large increase in the exports of coffee from Vietnam, which grew at an annual
average of 58.2% between 1993 and 1998 (table 3).
11
Poverty Dynamics in Rural Vietnam
Vietnam during the 1990s has led some households to breed and export shrimps, prawns and other types
of seafood as a complement to their normal farm activities. The exports of textiles and garments,
footwear and marine products increased also significantly in the same period (table 3), reflecting the
priorities assigned to the production of goods in which Vietnam would have a comparative advantage
(due to the abundance of cheap labour) and a larger diversification of agricultural incomes.26 In 1997, the
value added in the food processing sector was estimated to be about US$ 2.0 billion, which represented
about 8.8% of Vietnam’s total gross domestic product and 35.5% of industrial value added (Minot,
1998). Furthermore, the exports of agricultural, fishery and forest products, almost all of which are
processed in some way before being exported, account for around US$ 3.2 billion and grew during the
1993-1997 period at an annual rate of 20.7% (table 3).
New employment opportunities in those sectors will, however, only benefit the poor if those displaced
from traditional sectors are absorbed into the new growing sectors. If employment is concentrated
sectorally or geographically, there may be negative consequences for inequality and poverty reduction.
Transitional unemployment caused by the emergence of new markets and the disappearance of
traditional markets is not a problem for those that have enough assets to smooth consumption through the
adjustment period. However, it can be disastrous for the food and income security of poor vulnerable
households that generally do not save and are thus unable to adjust to periods of transitional
unemployment, however short these may be (Winters, 2000; McCulloch, Winters and Cirera, 2001).
These households are also more likely to live in remote areas with difficult access to the new markets
and be illiterate and poorly educated (and, consequently, unable to deal with the complexities involved in
the establishment of new markets and new employment opportunities and their access rules).
25
The percentage of coffee and other crops producing households that fell into poverty in 1997-98 is significantly lower than
that of households that produce rice, whilst the percentage of coffee producing households that moved above the poverty line in
1997-98 is significantly higher.
26
See Niimi, Vasudeva-Dutta and Winters (2002) for more detailed analysis of these changes.
12
Poverty Dynamics in Rural Vietnam
Table 7 shows the changes in the number of members of rural households employed in the main exports
industries.27 The first observation suggested by table 7 is the fact that only a very small number of rural
households has any members working in one of the four export industries. Given the large changes in the
exports of seafood, processed food, textiles and footwear, we expected a much higher impact in terms of
employment changes. Although there have been increases in the number of households with members
employed in the seafood, food processing and footwear industries, those changes have not been
substantial. This can perhaps be explained by the fact that rural non-agriculture activities are usually
limited to the production of handicrafts and the processing of raw materials for export goods.
Consequently, the majority of these rural non-farm enterprises employs one or two workers (usually
members of the family) and, as a result, job creation by these industries has not been high (Niimi,
Vasudeva-Dutta and Winters, 2002).
Despite small, changes in employment in the four main export industries have had positive welfare
impacts on rural Vietnamese households. In general, households that had at least one member working in
one of the main export industries had a higher probability of having fallen into poverty in 1997-98 than
households with no members employed in the export sectors. However, the probability of escaping
poverty (30.05%) is higher for households with members employed in the export sector. Of these,
households with members working in the seafood industry had the highest probability of having fallen
into poverty in 1997-98, whereas households with members working in the footwear industry registered
the lowest probability of having fallen below the poverty line and the highest probability of having
moved out of poverty in 1997-98.
Summary
27
The variables that represent the number of household members working in export industries were constructed using the list of
profession codes provided in the household surveys. Seafood includes in 1992-93 ‘fishermen, hunters and related workers’ and
‘aquaculture and fishing’ in 1997-98. Food processing includes ‘food, food stuff and beverage processors’ in 1992-93 and ‘food
processing’ in 1997-98. Textiles includes ‘spinners, weavers, knitters, dyers and related workers’ and ‘tailors, dressmakers,
sewers, upholsterers and related workers’ in 1992-93 and ‘textile and garment worker’ in 1997-98. Shoemaking includes
‘shoemakers and leather goods makers’ in 1992-93 and ‘leather and shoemaking industry worker’ in 1997-98.
13
Poverty Dynamics in Rural Vietnam
The analysis developed in this section shows some tentative links between the economic reforms
implemented in Vietnam after 1986 and changes in poverty status of rural Vietnamese households. The
results discussed above showed significant welfare benefits for households employed in the four main
export industries. The stronger links were, however, those reflected in the position of households as
producers of agriculture crops: trade reforms that resulted in the increase of prices of agriculture crops
and decrease in fertiliser prices have benefited households that produced rice, coffee and other crops in
1992-93. The results are particularly strong for producers of non-rice crops (particularly coffee).
3. MODELLING POVERTY DYNAMICS IN VIETNAM
Poverty dynamics is usually analysed using models that assess the risk of a household or an individual
remaining poor for a given period of time (see Jenkins, 1998). However, those models are inadequate to
the situation at hand given that we only have available two time periods. In order to model movements in
and out of poverty in Vietnam between 1992-93 and 1997-98 we had to resort to discrete outcome
models. We model poverty dynamics in Vietnam using a multinomial logit model.
Multinomial logit models are used to model processes that involve a single decision among several
alternatives that cannot be ordered (for example, choices between modes of travelling, occupational
choices, etc).28 Although there is not strictly speaking an element of choice involved in movements in
and out of poverty, the process that underlines poverty dynamics between two periods can be divided
into four mutually exclusive alternatives: (i) being poor in both periods, (ii) being non-poor in the first
period and poor in the second period, (iii) being poor in the first period and non-poor in the second
period and (iv) being non-poor in both periods.
28
This is what distinguishes the multinomial logit model from a simple logit model and from ordered logit models. The simple
logit model is used to analyse several decisions between two alternatives (0 and 1), whereas ordered logits are used to model
choices between several alternatives that can be ranked.
14
Poverty Dynamics in Rural Vietnam
The multinomial logit model determines the probability that a household i experiences one of the j
outcomes above. This probability is given by:
Pr ob(Yi = j ) =
e
β 'j xi
J
∑e
,
for j = 0, 1, 2, ..., J.
(1)
β k' xi
k =1
where Yi is the outcome experienced by household i, β k are the set of coefficients to be estimated and xi
includes aspects specific to the individual household as well as to the choices. The model is, however,
unidentified since there is more than one solution for β 1, ..., β J that leads to the same probabilities Y = 0,
Y = 1, Y = 1, ..., Y = J (Greene, 2000). In order to identify the model, one of the βs coefficients must be
set to zero (the base category), and all other sets are estimated in relation to this benchmark. For
convenience we have set β 1 = 0. In this case the probability function above becomes:
Pr ob(Yi = j ) =
e
β 'j xi
J
1+ ∑e
, for j = 1, 2, ..., J.
β k' xi
k =1
(2)
and
Pr ob(Yi = 0) =
1
J
1+ ∑e
.
(3)
β k' xi
k =1
In the case of the analysis of poverty in Vietnam we have that J = 4, where Pr ob (Y = 0) is the
probability of a household being poor in both years, Pr ob(Y = 1) is the probability of a household being
non-poor in 1992-93 and poor in 1997-98, Pr ob(Y = 2) is the probability of a household being poor in
15
Poverty Dynamics in Rural Vietnam
1992-93 and non-poor in 1997-98 and Pr ob(Y = 3) is the probability of a household being poor in both
years.
The multinomial logit model described above implies that we can compute J log-odds ratios
[
]
ln Pij Pi 0 = β j' x i . The log-odds ratios (also called relative risk ratios) can be normalised on any other
[
]
probability, which will yield that ln Pij Pi 0 = x 'j ( β j − β k ) (Greene, 2000). For convenience we have
decided to calculate
ln[P = 2 P = 0] = φ ( Fi , Dit , Lit , I it , Eit , Ait , Sit , Citk )
(4)
and
ln[P = 1 P = 3] = φ ( Fi , Dit , Lit , I it , Eit , Ait , Sit , Citk ) ,
(5)
which model, respectively, the probability of a household escaping and falling into poverty in terms of
fixed household characteristics (region and ethnicity) ( Fi ), household demographic characteristics
(household composition) in year t ( Dit ), occupation of the head of the household in year t ( Lit ), illness
shock (number of work days lost due to illness) in year t ( I it ),29 education levels of the head of the
household and spouse in year t ( Eit ), assets owned by the household (net income assets and
remittances)30 in year t ( Ait , ) and institutional and infrastructure characteristics in year t ( C itk ). This
variable represents the effects of access to electricity (as a proxy for access to development infrastructure
not included in other variables) and commune characteristics.31 In order to control for noise in the data
29
This is a dummy variable that takes the value 1 if the head of the household lost more than 7 days of work due to illness in the
month prior to the interview and 0 otherwise.
30
Net income assets represent total savings minus debts held by the household. We have decided to include remittances in our
model as these have become an important source of household income in Vietnam during the later 1990s (Dang and Le, 2002).
31
Communes differ in terms of availability of schools, access to roads and transport, access to markets and availability of
resources. Belonging to a certain commune is therefore likely to affect the poverty status of each household. Because commune
16
Poverty Dynamics in Rural Vietnam
originated from sampling methods, we have decided to include a variable that represents the quarter in
which the household was interviewed ( S it ). All these variables refer to household characteristics in
1992-93 and represent initial conditions.
The ratios above give us, respectively, the risk of a household falling into poverty in 1997-98 in relation
to staying non-poor in both years and the risk of a household moving out of poverty in 1997-98 in
relation to staying poor in both years. e
β j' xi
in equation (3) is thus the relative risk ratio for a unit change
in the variable x: a coefficient less than one means that the variables increases the probability of the
household to be in the base category, whereas a coefficient of more than one increases the probability of
the household being in the alternative state. The percentage of this probability is given by the coefficient
minus one, multiplied by one hundred. For example, in table 8, the value of 1.329 for the Red River
Delta means that an household living in the Red River Delta in 1992-93 (in relation to those living in the
North Central provinces, our base for the dummy variable) has a 32.9% increase in the probability of
having escaped poverty in 1997-98 (in relation to being poor in both years). Continuous variables have
been normalised and can be interpreted as the percentage effect of a one standard deviation in the
variable on the probability of a household escaping or falling into poverty.
We have used three alternative multinomial logit models to analyse poverty dynamics in Vietnam
between 1992-93 and 1997-98. The results are based on the rural panel of 3494 households. Equations
(4) and (5) above represent our base model. This model is similar to that of Glewwe, Gragnolati and
Zaman (2001) but differs in the choice of explanatory variables and the way they were constructed. The
second model introduces variables directly related to the economic reforms ( Tit ): production of rice (the
single most important crop in Vietnam), production of coffee (crop whose production increased the most
between 1992-93 and 1997-98), a measure of agriculture diversification (area cultivated with non-rice
characteristics are, to a certain extent, time-invariant (particularly in the short period of five years), we can control for commune
effects on household poverty dynamics. In order to capture the characteristics of the commune to which the household belongs
we have included in the model some institution characteristics of Vietnamese communes. Some of these characteristics reflect
17
Poverty Dynamics in Rural Vietnam
crops), whether or not the household has members employed in at least one of the four main export
sectors and the number of household members working in the main export industries (seafood, food
processing, textiles and footwear). We analysed also other variables that account for technological
changes possibly induced by the economic reforms. These are rice productivity (for households that
produce rice), the area of land irrigated per capita and the use of fertilisers.32 We examined also the
effect of land ownership since the land reforms implemented in Vietnam after 1986 have allowed
farmers to own their land. This is a dummy variable that takes the value 1 if the household owns the land
it uses. In addition we have included one other external shock variable: whether the commune where the
household lives has been affected by a weather disaster (flood, draught, pests, typhoon and other
weather-related disasters) between 1993 and 1998 ( Wi ). This variable should capture the influence of
factors not related to the economic reforms on the agriculture variables.
Models 1 and 2 include only the initial 1992-93 values for the explanatory variables. However, it may be
appropriate to look at changes (i.e. returns to the variables), as well as the initial characteristics, in order
to assess the impact caused by changes in the country’s technology between the two years into the
analysis (see Glewwe and Hall, 1998 and Dercon, 2000). This would allows us to model the relationships
between initial characteristics and poverty dynamics and between returns to those characteristics and
movements in and out of poverty. The third model analyses the relationship between poverty dynamics
and changes in household characteristics, as well as initial conditions, in order to allow for changes in
the coefficients between the two years:
ln[P = 2 P = 0] = φ ( Fi , Dit , ∆Dit , Lit , ∆Lit , I it , ∆I it ,Wi , Eit , ∆Eit , Ait , ∆Ait , Sit , Citk , ∆Cit ,
Tit , ∆Tit , ∆p r , ∆p c )
(6)
the integration of each commune within the whole Vietnamese economy (access to road, market and post office), whereas other
characteristics illustrate the availability of various resources within the commune (schools, food shop and clinic).
32
Rice productivity is defined by kilos of rice harvested per square metre of land. Land irrigation per capita is given by the
number of square metres of land irrigation per person in the household. Use of fertilisers was constructed by adding up the
18
Poverty Dynamics in Rural Vietnam
and
ln[P = 1 P = 3] = φ ( Fi , Dit , ∆Dit , Lit , ∆Lit , I it , ∆I it , Wi , Eit , ∆Eit , Ait , ∆Ait , Sit , Citk , ∆Cit ,
Tit , ∆Tit , ∆p r , ∆p c )
(7)
We added variables that represent change in the number of adults and children in the household between
1992-93 and 1997-98 ( ∆Dit ), changes in the education level of the head of the household and the spouse
( ∆Eit ), changes in net assets ( ∆Ait ), change in the access to electricity ( ∆C it ) and illness shocks ( ∆I it ).
We have also included changes in the trade variables ( ∆Tit ): changes in the number of members of the
household employed in the four main export industries,33 changes in land irrigated per capita, changes in
rice productivity for those households that are rice producers, changes in land ownership, changes in the
quantity of fertilisers used, change in the production of rice and coffee, changes in the area cultivated
with non-rice crops and change in the unit values of rice ( ∆p r ) and coffee ( ∆p c ) (as discussed in the
previous section). Given the significant effects that trade reforms in Vietnam have had on the country’s
agricultural sector, we have also included a dummy variable that represents changes in occupation of the
head of the household from the agricultural sector to other occupations and from other occupations to the
agricultural sector. The inclusion of change variables may raise questions of endogeneity, particularly the
inclusion of changes in the variables affected directly by the economic reforms. This is because these
variables may be simultaneously a cause and a consequence of changes in poverty status. However, we
felt that the information we obtained from the inclusion of these variables outweighed the possible
endogeneity problems. In any case, endogeneity is partially controlled for by the simultaneous inclusion
of initial values.
amount (kilos) of different fertilisers (urea-nitrogen, phosphate, potassium, NPK and other fertilisers) used by the household in
the 12 months prior to the interview.
33
Footwear gets dropped from models 2 and 3 because there are not any rural households from the panel working in the
footwear industry that are poor.
19
Poverty Dynamics in Rural Vietnam
The results for these models are given in table 8. The estimates in table 8 are already corrected for
heteroscedasticity34 using White’s adjusted heteroscedasticity-consistent variances.35 The models have
also been tested for independence of irrelevant alternatives since this is one of the most important
assumptions underlying the multinomial logit model and requires that the various outcomes Y must occur
independently of each other. If the independent of irrelevant alternatives assumption fails, the
multinomial logit model cannot be applied to the data and another model must be used. We have used the
Hausman test for independence of irrelevant alternatives and found that we could not reject the null
hypothesis that the multinomial logit model provides the most efficient coefficient estimates. The table
below provides a brief overview of the results estimated in table 8 (model 3) that were found to be
statistically significant.
Variables that increase probability
of escaping poverty
Variables that increase probability
of falling into poverty
Household characteristics
• Living in the South East and Mekong River Delta
• Older household head
• Head with white collar job or employed in sales or
production
• All levels of education of the head
• Spouse with technical and university education
• Increase in net assets
• Household with access to electricity and
improvements in the access to electricity in 1997-98
• Living in commune with daily market, food shop and
clinic
Household characteristics
• Belonging to ethnic minorities
• Large number of adults and children in the household
• Increase in the number of adults and children in the
household
• Weather shocks
• Living in commune with a road, primary school and
post office
Reform-related variables
• Head changed job to non-agriculture sector
• Household members employed in seafood industry
• Increase in the number of household members
employed in all four main export industries
• Quantity of fertilisers used
• Larger rice productivity for net rice producers and
increase in rice productivity
• Increase in retail unit values of rice and coffee
• Coffee production and increases in coffee production
• Cultivation of non-rice crops and increased in the area
cultivated with non-rice crops in 1997-98
34
Heteroscedasticity is common in household survey data (Deaton, 1997; Greene, 2000).
The results in the statistical tables are not population-weighted. As discussed above, although the two household surveys are
nationally representative, the panel is not necessarily representative of the whole population and we have not had access to the
sampling information necessary to built adequate weights.
35
20
Poverty Dynamics in Rural Vietnam
Variables that decrease probability
of escaping poverty
Variables that decrease probability
of falling into poverty
Household characteristics
• Belonging to ethnic minorities
• Large number of adults and children in the household
• Increase in the number of adults and children in the
household
• Weather shocks
• Living in commune with post office
Household characteristics
• Living in the Central Coast, South East and Mekong
River Delta
• Older household head
• Head with a white collar job or employed in sales or
production
• All levels of education of the head and spouse (except
spouse with lower secondary education)
• Changes in the education level of the spouse of the
head
• Larger net assets and increase in net assets
• Increase in remittances
• Household with access to electricity and
improvements in the access to electricity in 1997-98
• Living in a commune with upper secondary school,
daily market, food shop and clinic
Trade variables
• Head changed job to non-agriculture sector
• Household members employed in seafood industry
• Increase in the number of household members
employed in all four main export industries (except
footwear)
• Quantity of fertilisers used
• Increase in amount of land irrigated per capita
• Rice and coffee production and increases in coffee
production
• Increases in retail unit value of coffee
• Cultivation of non-rice crops and increase in the area
cultivated with non-rice crops in 1997-98
The results in table 8 are very consistent across the three models. However, the explanatory power of the
multinomial logit model increases as further variables are added to the base model. The inclusion of
trade variables into the base model explain an extra 20.7% of changes in poverty status of Vietnamese
households between 1992-93 and 1997-8, whereas adding change variables improve the explanatory
power of model 2 by 27.9% (and the explanatory power of model 1 by 54.3%).
The table shows that households that live in the southern regions (South East and Mekong River Delta)
have increased probabilities of escaping poverty. As expected, households with older heads,36
36
We believe that this result is associated with the fact that households with young heads are likely to have young children,
which poses a financial burden on the household (Litchfield and Justino, 2002). One important cause of higher poverty for
households with larger numbers of children is the high costs of education which have soared in Vietnam after the
implementation of the new economic reforms (World Bank, 1999).
21
Poverty Dynamics in Rural Vietnam
households with a head employed in a white-collar job, in sales and services or in production,
households living in communes with better infrastructure and households with better educated heads and
spouses have increased probabilities of escaping poverty, in relation to staying poor in both years.37 On
the other hand, ethnic minorities and large households were more likely to having fallen into poverty in
Vietnam between 1992-93 and 1997-98.
Models 2 and 3 show that household poverty dynamics in Vietnam between 1992-93 and 1997-98 was
significantly affected by variables associated with the economic and trade reforms that took place in the
country during the 1990s. The models show that households with members employed in the seafood
industry had increased probabilities of escaping poverty. Furthermore, households in which the number
of members employed in all the main export industries increased between 1992-93 and 1997-98, had also
increased probabilities of having escaped poverty in the latter year, in relation to remaining poor in both
years. This result suggests that the trade and economic reforms have had important employment effects
for Vietnamese households, even if only a small percentage of rural households was affected by those
changes. These effects have benefited not only those households that in 1992-93 were already involved
in the export industries, but in particularly those households that saw an increase in the number of
members employed in those industries in 1997-98.
The employment effects of the trade reforms were also felt strongly in the agriculture sector. The results
in table 8 show that changes in the main occupation of the head of the household from the agriculture
sector to any other sector increased the probability of the household escaping poverty by almost 72%.
This effect may have been counterbalanced by the technological changes that took place in the
Vietnamese agriculture sector between the two survey years, as the use of fertilisers, rice productivity
and increases in rice productivity have increased the probability of Vietnamese households escaping
37
Most institution and infrastructure variables seem to have welfare-enhancing effects. Living in communes with access to a
road (models 1 and 2), an upper secondary school (model 3 only), a daily market, a food shop and a clinic increase the
probability of a household escaping poverty. The only exception is access to a post office, which seems to decrease the
probability of households escaping poverty and increase the probability of households falling into poverty. This apparently
22
Poverty Dynamics in Rural Vietnam
poverty. Although rice production did not seem to affect the probability of households escaping poverty,
it decreased significantly the probability of households falling into poverty in 1997-98. This result seems
to have been related to increases in the retail price of rice. Coffee production and increases in coffee
production, as well as the cultivation of non-rice crops and increases in the area dedicated to the
cultivation of non-rice crops, have increased and quite large effects on the probability of households
escaping poverty.
This result seems to suggest that, although Vietnamese households have been
positively affected by changes in the rice market, they have benefited much more from agriculture
diversification, induced by changes in the prices of cash crops (which are higher than rice prices - table
4) and decreases in fertiliser prices. This confirms the results we obtained in our descriptive analysis in
the previous section.
We have decomposed the poverty dynamics effects of the various household characteristics and traderelated variables by summing equations (6) and (7) for all households i in our rural sample and dividing
each term by the sum of all changes (Dercon, 2000). Our analysis focused on the impact of those
variables on the probability of a household escaping poverty as very few households in Vietnam fell into
poverty in 1997-98. The results for this analysis are illustrated in table 9. The table shows that the largest
effects on poverty dynamics in Vietnam between the two survey years were caused by initial level in
education of the head and spouse of the head of the household and geographic location. This latter effect
is likely to reflect the impact of economic changes in specific regions, which again illustrates the
importance of trade reforms in household poverty dynamics in Vietnam between 1992-93 and 1997-98.
In fact, both initial trade conditions and reform-induced economic changes contribute significantly
towards changes in household poverty status in Vietnam between 1992-93 and 1997-98. Initial values in
reform-related agriculture variables and reform-induced agriculture changes explain, respectively 8% and
17.7% of all movements out of poverty. These effects increase, respectively, to 9.1% and 17.8% if
employment in the main export industries is included in this category. We have calculated that the largest
contributions to the impact of trade-induced reforms on movements out of poverty were increases in
perverse effect may be related to particular characteristics of communes that have post offices. Most of these are in the Mekong
23
Poverty Dynamics in Rural Vietnam
coffee production and cultivation of non-rice crops. These results suggest that movements out of poverty
in Vietnam between 1992-93 and 1997-98 were, to a relatively large extent, determined by the trade and
economic reforms that took place in the country during the 1990s. We cannot, however, overlook the
impact of education in explaining the reduction of poverty in Vietnam between those periods. Better
educated households have a clear advantage over all other households, not only because they will be able
to access better paid jobs, but also because they will be in a better position to take advantage of the
opportunities that economic openness provides.
4. SENSITIVITY ANALYSIS
Although the multinomial logit models analysed above show consistent results across three different
model specifications, the model itself may be subject to criticisms. One of those relates to the
interpretation of the model. This can be difficult when we estimate discrete variables, which are
calculated not only in relation to the benchmark state but also in relation to their base value. In order to
overcome this criticism we could estimate simple probit or logit models on the poor and the non-poor
rural household samples separately. These models would give us the probabilities of poor rural
households moving out of poverty and of non-poor rural households falling into poverty. We have
analysed these alternative models but did not obtain any significantly different conclusions from the
conclusions provided by the multinomial logit models (Justino and Litchfield, 2002; Litchfield and
Justino, 2002). This is because the models are equivalent (except for sample size) for outcomes 2 and 3
of the multinomial logit models, with the advantage that the multinomial logit model estimates
simultaneously the various error terms and thus introduces less measurement error into the analysis.
Another possible criticism is the underlying assumption of unordered choices forced upon the data by the
multinomial logit model. This model may not be the most adequate method for analysing household
poverty dynamics between two periods if we believe that there is an implicit ordering of the states ‘poor
River Delta, where quite a large percentage of households fell into poverty.
24
Poverty Dynamics in Rural Vietnam
in both years’, ‘non-poor in 1992-93 and poor in 1997-98’, ‘poor in 1997-98 and non-poor in 1997-98’
and ‘non-poor in 1997-98’. Although forming a complete ranking of poverty outcomes involves arbitrary
judgements, it may be reasonable to assume that each household will have a set of preferences regarding
the four states. Niimi, Vasudeva-Dutta and Winters (2002) have tested a few possibilities using the
methodology offered by the ordered logit models with not very satisfactory results.38
The multinomial logit model can also be criticised on the grounds that it introduces measurement errors
into the analysis due to the fact that it relies on an arbitrarily defined poverty lines. Reducing a
continuous variable, such as household expenditure, to a qualitative variable may “throw” information
away on the variation in the dependent variable with respect to the variation in explanatory variables
(Deaton, 1997). This is a particularly serious problem in analyses that use developing countries data,
since large numbers of households may be concentrated around the poverty line. We have thus further
tested the results of the multinomial logit models by using different poverty lines. We have considered a
poverty line 10% above the official poverty line of 1160 thousand dongs in 1992-93 and 1790 thousand
dongs in 1997-98 (model 4), and another 10% below those values (model 5). We have also tested the
multinomial logit results to the use of adult equivalent scales, which we decided not to adopt in this
paper (model 6).39 We found that models 4, 5 and 6 and model 3 (based on the official poverty lines)
differ only very slightly. In general, the magnitude and sign of the various coefficients do not change a
lot; only the statistically significance of some coefficients changes. One significant difference is the fact
that in model 5, which considers fewer households as poor and thus concentrates on the very poor, the
coefficient for the Central Highlands is now statistically significant. This seems to suggest that changes
in coffee production had larger impacts on poorer households. Also change in spouse education is now
statistically significant. This shows that the impact of this education variable on the reduction of
household poverty in Vietnam is larger for the poorest households.
38
This is likely due to the fact that it may not be possible to order the four outcomes. Recall that the Hausman statistics in all
multinomial logit models strongly indicated that the four outcomes are not interdependent.
39
We created expenditure per equivalent adult using the WHO equiv scale of 1 for adults and 0.65 for children. We also adjusted
the poverty line so it is in per adult terms, rather than per person terms. To do this we multiplied the poverty line by 2800/2100
(which is the calorie needs of an adult over the calorie needs of an average person).
25
Poverty Dynamics in Rural Vietnam
Although the multinomial logit models seem not to be very sensitive to the choice of poverty line and
show very consistent results across different model specifications and different panel samples, we have
also analysed a consumption model for Vietnam. An advantage of this type of models is the fact that the
whole distribution is taken into consideration. This decreases the likelihood of information being
‘thrown away’, although it also implies that all conclusions we reach will refer to the whole distribution
and not only the poor. We use two consumption models that examine, respectively, changes in household
consumption between 1992-93 and 1997-98 using non-adjusted consumption expenditures and
consumption expenditures adjusted to adult equivalence scales.40 These models are similar to the model
used by Stefan Dercon to analyse the impact of economic reforms on rural household in Ethiopia
(Dercon, 2000). The derivation of the model can be found in appendix A. Table 8 shows the results for
these models. The variable on the left-hand side is the difference between the logarithmic function of
household consumption expenditure in 1992-93 and 1997-98 (which can be approximated to the growth
rate of household consumption expenditure). The variables on the right-hand side are the same as in
model 3. These models allow us to calculate the different elasticities of consumption expenditure relative
to household characteristics that remain constant over time (region, tribe and religion) and household
characteristics that have changed over time. As long as we can relate some of these characteristics to the
economic and trade reform implemented in Vietnam, the model allows us to determine the effects of
those reforms on changes in real household consumption expenditure (Dercon, 2000). The difference
between this model and Dercon’s is that we have included not only price changes but also other tradeinduced changes in our variable inputs, which gives us two mechanisms to analyse the effects of trade
reforms on changes in household consumption expenditure: (i) changes in trade-related outcomes
(employment in export industries and changes in the household production of rice and coffee and
cultivation of non-rice crops) and (ii) changes in prices (in this case changes in the price of rice and
coffee).41
40
We did not find any significant differences between the two models.
26
Poverty Dynamics in Rural Vietnam
Although most variables behave in similar fashion in both consumption and multinomial logit models,
the two types of models show different results for quite important variables:
♦ Models 6 and 7 suggest that living in the Central Coast and in the Mekong River Delta has a
negative impact on the growth of consumption expenditure between 1992-93 and 1997-98, whereas
model 3 shows that living in the Central Coast decreases significantly the probability of a household
falling into poverty and living in the Mekong River Delta increases the probability of escaping
poverty.
♦ Larger numbers of children are associated with increases in consumption expenditure between 199293 and 1997-98, when the same variable decreases significantly the probability of a household
escaping poverty and increases significantly the probability of a household falling into poverty.
♦ The employment of the head in white collar jobs had quite a large positive impact on the probability
of a household escaping poverty, though the variable is statistically insignificant in models 6 and 7.
The same is true of employment of the head in sales. In fact, the coefficient of this variable is
statistically insignificant and negative in the consumption models.
♦ Models 6 and 7 show that employment in the export sectors and having members of the household
employed in the seafood industry contribute negatively towards the growth of consumption
expenditure. Furthermore, whilst all export industries had a positive and statistically significant
impact on the probability of escaping poverty, these coefficients are statistically insignificant in the
consumption models.
♦ Some of the education variables (head with primary school education, spouse with upper secondary
and technical/university education and change in head and spouse education) have negative
coefficients in the consumption models. However, all these variables contributed positively (and
most are statistically significant) towards the reduction of poverty in Vietnam between 1992-93 and
1997-98.
♦ Models 6 and 7 suggest that the use of fertilisers, land irrigation, rice production and cultivation of
non-rice crops have a negative impact on the growth of consumption expenditure of Vietnamese
41
Dercon considers only changes in a composite price.
27
Poverty Dynamics in Rural Vietnam
households between the two survey years. All these variables contributed positively towards the
reduction of poverty of many households in the same period, according to the results of model 3.
These results suggest that movements out of poverty are not necessarily related to increases in
consumption across the whole distribution. We can easily visualise a situation whereby households with
certain characteristics that escape poverty concentrate around the poverty line. A positive impact of those
characteristics could then be sufficient to move these households above the poverty line. Simultaneously,
a large number of households with the same characteristics and above the poverty line could have
experienced decreases in their consumption levels between the two years without falling below the
poverty line. We have investigated this hypothesis by re-examining the behaviour of the consumption
models across different expenditure quintiles.42 The results for those models are provided in table 10.43
The table shows that the negative consumption coefficients of households living in the Central Coast are
determined by the coefficients of households in the second and third quintiles. Poor households living in
the Central Coast have a positive coefficient. The results for the Mekong River Delta are driven by the
households in the first quintile. This is likely due to the high number of landless households in the
Mekong River Delta, which have experienced a deterioration of their living standards (Lam, 2001). The
quintile regressions also show that the impact of larger number of children is particularly damaging (and
statistically significant) for households in the first three quintiles despite the overall positive coefficient.
The quintile regressions show further that the negative coefficients of some of the education variables
are driven by the upper quintiles. Higher levels of education have a particularly positive impact on the
consumption levels of poor households (especially those in the second quintile).44
42
We divided households into five expenditure groups according to their consumption expenditure levels in 1992-93 (using
sumdist) and run the consumption regressions on each of these five groups. The independent variable is the different between the
logarithmic function of their consumption expenditure in 1992-93 and 1997-98. The explanatory variables are the ones used in
models 6 and 7.
43
In order to keep our table appendix more manageable, this table includes only the variables discussed above. The full results
are available upon request.
44
This confirms the results we obtained previously in model 5 (the multinomial logit model that uses a poverty line 10% below
the official poverty line).
28
Poverty Dynamics in Rural Vietnam
Although the employment in white collar and sales jobs increase probabilities of escaping poverty, these
affect more households in the higher expenditure brackets rather than the very poor. This seems to
suggest that employment in higher paid jobs impacts more significantly on the probability of households
around the poverty line escaping (or not falling into) poverty. The same is true with employment in the
export industries (particularly employment in the seafood industry), which has a positive impact on the
consumption levels of households in the higher expenditure groups. This could be driven by the fact that
workers that belong to poorer households will be employed by the worse-paying industries and take jobs
that require less skills. Increases between 1992-93 and 1997-98 in the number of household members
employed in the food processing, textiles and garments and footwear industries affects positively
households in the second and third quintiles. These are households around and immediately below the
poverty line. The impact of these variables on the poorest households is not statistically significant but
the coefficient is also positive. Thus, although initial employment in the export sectors may not have had
significant impacts on the consumption expenditure of poor households, increases in the household
employment in those sectors had a positive effect on their consumption levels.
The results for the agriculture variables are more disperse. Despite the overall negative coefficients, the
use of fertilisers and of land irrigation has benefited households in the lower expenditure brackets.
However, initial rice production has impacted negatively (the coefficient is also statistically significant)
on the very poor households, whereas it has a large positive impact on the consumption levels of
households in the upper income bracket. This may explain why the coefficient is statistically
insignificant and below 1 in model 1 (probability of escaping poverty) but above 1 in model 4 (which
uses a higher poverty line). On the other hand, cultivation of non-rice crops (in particularly, increases in
the cultivated area of non-rice crops) has benefited poorer households, which further confirms our
previous conclusion that increases in agriculture diversification in Vietnam had an important and
positive impact on the reduction of poverty in the country between 1992-93 and 1997-98.
29
Poverty Dynamics in Rural Vietnam
These results obtained in the quintile regressions clarify thus the main different between the overall
consumption models and the multinomial logit models. They also provide a bridge between the two
models. The conclusions yielded by the quintile regressions emphasise the fact that the multinomial logit
model provides a very useful method to analyse poverty dynamics, without introducing significantly
large measurement errors into the analysis. The model has in addition the advantage of focusing our
attention directly on how the poor – and not the whole distribution – were affected by the economic and
social changes that took place in Vietnam in the 1990s.
5. CONCLUSIONS
This paper intended to show how, empirically, we can identify the mechanisms of transmission of effects
induced by economic reform to household poverty dynamics. Our main objective was to isolate
particular characteristics and policies that maximise the ability of poor households to seize potential
opportunities brought about by economic liberalisation. The paper developed this analysis for the case of
Vietnam, where the economic and trade reforms implemented in the late 1980s have been credited for
the dramatic decrease in poverty observed in the country between 1992-93 and 1997-98. This analysis
was possible due to the availability of a panel of households that were interviewed in both years.
The paper analysed the transmission of economic reform effects to the household level using
multinomial logit models that provided estimates for the relative risk of households escaping or falling
into poverty. The results were generally consistent across all models estimated and were not sensitive to
the choice of different poverty lines or model specification. We focused on two important reforms: (i)
liberalisation of agriculture markets (rice and other crops) and of prices of agriculture crops and inputs
(particularly, fertilisers), which has affected household production decisions, and (ii) liberalisation of
export markets, following the removal of export quotas and tariffs, which has influenced employment
patterns of Vietnamese households. The results of our analysis showed that the employment effects were
in general positive and had significant welfare-enhancing effects for those households with members
30
Poverty Dynamics in Rural Vietnam
employed in the main export sectors (seafood, food processing, textiles and garments and footwear).
These effects have benefited not only those households that in 1992-93 were already involved in the
export industries, but in particularly those households that increased the number of members employed
in those industries in 1997-98. Although these changes would have affected only a relatively small
number of rural households, this suggests that there may be scope for further poverty reductions in
Vietnam by creating additional employment opportunities in the main export sectors for poor
households.
The stronger links were, however, those reflected in the position of households as producers of
agriculture crops. The results of our analysis suggested that trade reforms that resulted in the increase of
prices of agriculture crops and decrease in fertiliser prices have benefited households that produced rice,
coffee and other crops in 1992-93. In particular, increases in agriculture diversification between 1992-93
and 1997-98 benefited significantly rural households in Vietnam: poverty decreased more notably
amongst these households than amongst households that continued producing mainly rice or decided to
increase rice production. This impact was especially strong for the poorest households.
In face of these results, we think that the Vietnamese government must seriously re-evaluate some of its
economic policies for the rice sector, particularly in terms of their impact on poor households that
produce rice. Government policies should focus more on promoting further the diversification of rural
incomes by encouraging the establishment of small-scale agro-processing or other farm and non-farm
enterprises, thereby reducing the dependency of poor rural households on rice production. Special
attention should also be paid to the reinforcement of universal literacy and education, given the large
impact of levels of education on the poverty status and consumption levels of poor Vietnamese
households.
We must not also overlook the fact that the economic reforms have not prevented some households from
falling into poverty. Those were households living in remote areas, belonging to minority ethnic groups,
31
Poverty Dynamics in Rural Vietnam
with large number of members, low levels of education and whose main earnings derive from the
agriculture sector. This is a particularly worrying result as the large bulk of the economic reforms
implemented in Vietnam during the 1990s was concentrated in the agriculture sector. Although the
economic reforms have yielded large benefits for some, a lot still remains to be done in order to ensure
that some of the most vulnerable households are able to cope with the type of socio-economic shocks
induced by economic reforms and that clusters of persistent poverty do not start to form amongst these
households.
This paper is still a long way from providing a complete understanding of the effects of economic
reforms on household poverty dynamics. The paper, for instance, does not look at changes in wages or
changes in exchange rates that would affect the prices of tradable goods versus non-tradable goods
(which are bound to have large effects on movements in and out of poverty of most households).
Furthermore, although the economic reforms that took place in Vietnam have been quite extensive, only
very recently have important barriers been eliminated. Also after 1998 there was a drastic decrease in the
world price of rice and coffee. These economic changes would not have been captured by the 1997-98
survey. The mechanisms we have identified provide nonetheless an important and seminal step towards
the understanding of the microeconomic impact of economic reforms and the relationship between these
effects and other social and economic events.
32
Poverty Dynamics in Rural Vietnam
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33
Poverty Dynamics in Rural Vietnam
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34
Poverty Dynamics in Rural Vietnam
O’Connor, D., 1996. Labour Market Aspects of State Enterprise Reform in Viet Nam. OECD
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Government, Donor and NGO Working Group, Consultative Group Meeting for Vietnam,
December 14 - 15.
35
Poverty Dynamics in Rural Vietnam
TABLE 1 – CHANGES IN POVERTY AND CONSUMPTION EXPENDITURE MEANS
BY SOCIO-ECONOMIC CHARACTERISTICS
Category
Headcount index
Consumption expenditure
means
1992-93 1997-98 % change
1914.5 2763.75
44.4
Population share
(%)
1992-93 1997-98
100.0
100.0
1992-93 1997-98 % change
58.1
37.4
-35.6
All Vietnam
Type of household
Urban
24.9
8.6
-65.5
3092.3
4829.4
56.2
19.9
21.8
Rural
66.4
45.4
-31.6
1621.8
2166.4
33.6
80.1
78.2
Region
Northern Uplands
78.6
58.6
-25.4
1378.7
1920.0
39.3
15.6
17.9
Red River Delta
62.8
28.7
-54.3
1827.7
2938.0
60.8
21.6
19.6
North Central
74.5
48.1
-35.4
1439.0
2196.6
52.6
12.8
13.8
Central Coast
49.6
35.2
-29.0
2034.7
2641.4
29.8
11.9
10.7
Central Highlands
70.0
52.4
-25.1
1515.7
1941.7
28.1
3.2
3.7
South East
32.7
7.6
-76.8
2844.9
5019.5
76.4
12.6
12.8
Mekong River Delta
47.1
36.9
-21.7
2112.7
2535.9
20.0
22.4
21.5
Ethnic group
Vietnamese (Kinh)
55.1
31.6
-42.6
1981.5
2917.5
47.2
84.5
86.1
Chinese
11.8
8.4
-28.8
3542.7
5077.7
43.3
2.5
2.2
Other
86.4
75.2
-13.0
1177.4
1524.3
29.5
13.1
11.7
Household size
44.0
17.0
-61.4
2415.4
3753.2
55.4
12.2
12.1
Small (≤ 3 members)
Medium (3-6 members)
55.7
30.8
-44.7
1989.4
2933.3
47.4
36.4
44.1
63.2
49.7
-21.4
1742.5
2318.5
33.1
51.4
43.8
Large (≥ 6 members)
Occupation of the head1
White collar
23.6
9.9
-58.1
3043.7
4904.3
61.1
4.6
6.6
Sales
27.7
13.0
-53.1
2908.2
4337.7
49.2
8.1
9.5
Agriculture
69.0
48.2
-30.1
1566.2
2081.3
32.9
64.7
61.0
Production
45.9
25.9
-43.6
2288.5
3281.4
43.4
10.9
11.5
Other/no work
44.4
27.4
-38.3
2355.8
3340.2
41.8
11.7
11.3
Education of the head
None
62.6
55.0
-12.1
1702.1
2090.2
22.8
36.4
8.4
Primary
56.7
42.2
-25.6
1946.6
2407.2
23.7
26.1
34.9
Lower secondary
64.0
38.0
-40.6
1788.9
2581.9
44.3
22.6
36.3
Upper secondary
44.5
25.1
-43.6
2448.5
3566.3
45.7
4.3
12.3
Technical and university
39.2
14.2
-63.8
2616.1
4588.2
75.4
10.6
8.1
Source: Authors’ own calculations from Vietnam Living Standards Surveys (VLSS) 1992-93 and 1997-98.
Note: Consumption expenditure means are expressed at January 1998 prices (values for 1992-93 have been inflated by a factor
of 1.456 suggested by the VLSS). 1. This variable was constructed using the list of profession codes provided in the household
surveys. We have divided the occupation variable into white collar jobs (scientists, architects, lawyers, economists, academics,
clerical workers, etc), sales and services (retail and wholesale workers, salesmen, hotel managers and workers, hairdressers,
etc), agriculture (farmers, forestry workers, fishermen, etc), production (miners, masons, food processing workers, shoemakers,
painters, etc) and those not working. The unemployed include those heads looking for a job and those who have no job.
36
Poverty Dynamics in Rural Vietnam
TABLE 2 – POVERTY MATRIX FOR 1992-93 AND 1997-98
Category
% of rural
panel
Always poor
(%)
Nonpoor 92-3
Poor 97-8 (%)
Never poor (%)
Poor 92-3
Nonpoor 97-8
(%)
All
Rural
All
Rural
27.34
29.68
39.19
31.08
92-93 97-98
All
Rural
All
Rural
81.22
79.89
28.73
33.89
4.74
5.35
Vietnam
Region
Northern Uplands
16.54
16.54
47.15
54.84
4.53
4.84
27.30
25.61
Red River Delta
25.01
25.01
24.90
29.11
3.86
4.00
34.65
39.02
North Central
15.74
15.74
38.11
41.09
4.07
4.55
33.71
33.27
Central Coast
10.70
10.70
25.15
29.95
3.99
4.81
22.95
25.13
Central Highlands
3.29
3.29
41.74
41.74
2.61
2.61
25.22
25.22
South East
8.47
8.47
7.98
10.81
2.10
3.04
24.16
33.11
Mekong River Delta
20.23
20.23
23.89
27.16
8.57
9.76
18.74
20.37
Ethnic group
Kinh
84.77
84.60
23.81
27.95
4.73
5.39
29.14
31.90
Chinese
0.37
0.34
5.73
28.00
1.27
0.00
5.73
8.00
Others
14.85
15.05
65.86
67.66
5.30
5.26
18.14
17.61
Household size
22.70
22.35
17.93
22.30
5.58
6.73
27.04
30.05
Small (≤ 3 members)
Medium (3-6 members)
40.44
45.22
26.35
31.54
4.54
5.05
28.93
31.81
36.86
32.43
39.37
44.32
4.42
4.83
25.48
26.81
Large (≥ 6 members)
Occupation of the head
White collar
3.41
4.29
6.34
11.15
1.69
2.60
17.76
27.14
Sales and services
4.26
5.44
8.70
15.04
3.87
5.60
18.65
25.96
Agriculture
75.19
71.84
36.18
37.45
5.35
5.49
30.02
30.06
Production
7.81
8.21
20.33
27.86
3.98
4.46
28.73
33.57
Unemployed
9.33
10.22
21.35
30.31
4.23
6.00
22.58
26.50
Education of head
None
39.30
10.85
37.33
41.44
5.35
5.71
23.81
23.97
Primary
24.53
37.72
29.22
33.20
5.88
6.53
26.77
28.83
Lower secondary
24.10
35.89
29.02
33.30
4.48
4.77
33.45
35.35
Upper secondary
3.98
9.62
18.81
25.68
2.54
3.37
23.13
28.42
Technical and university
8.10
5.92
13.00
20.41
2.23
3.27
22.52
30.82
Source: Authors’ own calculations from the Vietnam Living Standards Survey 1992-93 and 1997-97.
37
21.02
36.58
24.10
47.90
30.43
65.76
48.80
14.71
27.57
21.09
40.11
30.43
53.04
42.72
42.32
87.26
10.70
34.76
64.00
9.47
49.45
40.18
30.73
40.91
31.61
24.04
74.21
68.78
28.44
46.96
51.83
59.11
53.39
27.00
34.11
37.19
33.51
38.13
33.05
55.52
62.25
28.88
31.45
26.57
42.53
45.51
Poverty Dynamics in Rural Vietnam
TABLE 3 – SELECTED ECONOMIC INDICATORS FOR VIETNAM
1991
1992
1993
1994
1995
1996
1997
1998
Av. ∆
93-8
8.3
6.8
1.8
30.5
24.6
38.7
58.2
1
20.7
15834
13552
15414
16299
17764
19392
20783
20044
GDP (const, US$ million)
5.8
8.7
8.1
8.8
9.5
9.3
8.2
5.8
GDP growth rates (%)
195
217
225
246
264
279
265
GDPpc (constant, US$)
5.6
6.6
10.0
7.7
6.5
4.2
GDPpc growth rates (%)
30571.6 31262.0 32022.4 32856.9 33666.8 33978.3
34352.7 34800.1
Employment (millions)
2338
2541
3924
5826
8155
11144
11592
11499
Imports (US$ million)
2087
2581
2985
4054
5449
7256
9185
9360
Exports (US$ million)
Rice
68
150
103
132
259
329
269
619
Coffee
28
76
113
351
614
375
469
603
Agricultural, forestry
1090
1276
1444
1905
2521
3051
3200
and fisheries
Marine product
292
329
415
544
575
607
713
707
14.2
Textiles
28
38
63
104
150
178
220
210
35.5
Garment
131
344
502
657
858
1142
1313
1275
25.4
Footwear exports
7
30
139
300
511
782
1149
1212
109.2
Source: GSO statistics. Export values by commodity from World Bank Mirror Statistics. Employment statistics by MOLISA and
supplied by CIEM.
Notes: 1. Refers to average change between 1993 and 1997.
TABLE 4 – CROP PRODUCTION, AREA CULTIVATED AND UNIT VALUES OF AGRICULTURE CROPS
IN VIETNAM, 1992-93 AND 1997-981
No producers
92-3
97-8
Ch
2986
2779
-6.9
2497
2385
-4.5
1258
1186
-5.7
92
101
9.8
926
997
7.7
Production (kgs)10
92-93
97-98
Ch
1405
1894
34.9
1059
1109
4.7
1482
3521
137.5
525
1572
199.3
326
421
28.9
Area cultivated (m2)
92-3
97-8
Ch
9543
615
-93.6
1814
1639
-9.6
1326
1583
19.4
3498
10221
192.2
206
808
293.0
92-3
1.72
5.20
4.44
9.21
3.69
Unit values
97-8
Ch
1.92
11.6
1.57
-69.8
4.44
0.0
14.10
53.1
6.37
72.6
Paddy2
Other food crops3
Annual ind crops4
Coffee
Oth per ind
crops5
1837
2277
24.0
341
473
38.6
320
430
34.3
1.80
2.20
22.2
Fruit crops6
667
577
-13.5
517
464
-10.1
1121
1701
51.8
Agro-forestry7
3046
2810
-7.8
18
21
15.8
44.4
43.48
-2.1
Livestock8
217
631
190.8
937
1963
109.4
476
5024
955.4
Aquaculture9
Source: Authors’ own calculations from the Vietnam Living Standards Surveys 1992-93 and 1997-98.
Notes: 1. Production and unit values represent the mean average for those households that produce the respective crop. Area cultivated is
averaged over those households that cultivate the respective crop. Production values and unit values are deflated by regional prices and are
expressed in January 1998 prices. 2. Paddy refers to the weighted average of ordinary rice (autumn, winter and spring rice), ordinary rice
cultivated in swidden land, glutinous rice and speciality rice. Rice was converted into paddy by a factor of 0.66 suggested by the VLSS. 3.
Other food crops include corn/maize, sweet potatoes, cassava, other staple foods, potatoes, cabbage, other leafy greens, tomatoes, water
morning glory, fresh legumes, dried legumes, herbs and spices and other vegetables. 4. Annual industrial crops include soy beans, peanuts,
sesame seeds, sugar cane, tobacco, cotton, jute, rush, other annual industrial crops and other annual crops. 5. Other perennial industrial
crops include tea, rubber, black pepper, coconut, mulberry, cashew and other perennial industrial crops. 6. Fruit crops include citrus,
pineapples, bananas, mangoes, apples, grapes, plums, papayas, litchis, sapodilla, custard apples, jackfruit and other fruit trees. 7. Agroforestry crops include mu oil tree, cinnamon, anise, pine trees, varnish trees, trees for wood, bamboo, fan palm tree, water coconut and
other silviculture trees. 8. Livestock includes water buffalos, cattle, pigs, horses, goats, chickens, ducks, geese, bees, silk worms, deer,
snakes and other animals kept as livestock. 9. Aquaculture includes: fish, shrimps and other water products. 10. Production refers to kilos
of the respective crop harvested in the 12 months prior to the interview, except for agro-forestry crops, livestock and aquaculture.
Production of agro-forestry crops refers to the value of amount of agro-forestry crops harvested in the 12 months prior to the interview (in
thousand of dongs). We could have used number of trees cultivated by the household. However, this variable is evaluated in the household
surveys using a mix of area of trees cultivated and number of trees. We were not able to convert area into number of trees. The best variable
we could thus used to measure changes in production of agro-forestry crops was the value of that production. Livestock refers to the
number of animals owned by the household at the time of the interview. Aquaculture refers to the value received from aquaculture in the 12
months prior to the interview (in thousand of dongs). The household surveys do not provide quantities of aquaculture production.
38
Poverty Dynamics in Rural Vietnam
TABLE 5 - CHANGES IN RICE, COFFEE AND FERTILISERS PRICES (RURAL PANEL)1
1992
1993
1994
1995
1996
1997
1998 % ∆ 93-98
International rice price (91=100)
91.47 80.20
91.47 109.56 115.70 103.41 103.75
29.4
International coffee price (91=100)
75.40 83.42 177.01 178.07 143.85 222.99 159.36
91.0
Domestic retail rice price (91=100)
62.99 63.66
69.11
80.82
78.25 73.96
80.82
27.0
Domestic retail paddy price (91=100)
62.14 62.58
66.87
82.30
81.21 73.05
79.64
27.3
1.72
1.92
11.6
Unit values of paddy (farm price)2
Unit values of rice (retail price)
3.06
3.91
27.8
1.74
2.33
33.9
Commune paddy prices3
Commune rice prices
2.79
3.69
32.3
9.21
14.10
53.1
Unit values of coffee (farm price)4
Unit values of coffee (retail price)
- 34.78
50.31
44.7
Unit values of fertilisers
2.49
1.92
-22.9
Source: World Bank (1999), Global Economic Prospects and the Developing Countries for international prices and State
Pricing Committee for domestic rice and coffee prices. Unit values and commune prices were calculated by the authors from
the VLSS 1992-93 and 1997-98.
Notes: 1. The table provides the means of household unit values, commune prices and changes in unit values and commune
prices. The values are per kilo. All prices are measured in 1998 prices and refer to the average price of one kilo of rice, coffee
or fertiliser. 2. Unit values of rice and paddy were derived as the weighted average of the ratio between the total value of
ordinary and glutinous rice (bought and sold) and their total quantities. There were some cases where we had observations
for total values but not total quantities. We decided that these were recording errors and corrected them by replacing the
missing values with the commune mean unit value of ordinary and glutinous rice. Given the importance of rice in the diet of
all Vietnamese households, we also replaced the missing unit values of those households who had no value for rice
consumption by the commune mean unit value. Rice was converted to paddy in 1997-98 by a factor of 0.66, recommended in
VLSS (2001). 3. We assume the commune prices of rice to be the price faced by consumers and the commune prices of
paddy (i.e. non-processed rice) to be the prices faced by rice producers. 4. The commune questionnaires do not provide
coffee prices and we have not had access to the domestic retail prices of coffee.
39
Poverty Dynamics in Rural Vietnam
TABLE 6 - POVERTY MATRIX FOR 1992-93 AND 1997-98:
CHARACTERISTICS OF AGRICULTURE PRODUCTION
Category
% of rural
panel
Always poor
(%)
Nonpoor 92-3
Poor 97-8 (%)
Poor 92-3
Nonpoor 97-8
(%)
All
Rural
92-93 97-98
All
Rural
All
Rural
Rice
Producer
85.46 79.54 35.45 36.05
5.11
5.24 30.31
30.41
Not producer
14.54 20.46 13.65 23.71
3.92
5.89 20.66
26.25
Coffee
Producer
2.63
2.89 22.49 23.32
4.31
4.66 34.93
35.75
Not producer
97.37 97.11 28.89 34.19
4.75
5.37 27.15
29.51
Other crops
Producer
84.37 83.80 34.18 35.40
5.00
5.14 30.25
30.31
Not producer
15.63 16.20 14.85 25.90
4.08
6.47 19.92
26.35
Source: Authors’ own calculations from the Vietnam Living Standards Survey 1992-93 and 1997-97.
Never poor
(%)
All
Rural
29.13
61.76
28.31
44.15
38.28
39.21
36.27
30.93
30.57
61.15
29.15
41.28
TABLE 7 - POVERTY MATRIX FOR 1992-93 AND 1997-98:
EMPLOYMENT IN EXPORT INDUSTRIES
Poor 92-3
Never poor (%)
Nonpoor 97-8
(%)
92-93 97-98
All
Rural
All
Rural
All
Rural
All
Rural
8.53
9.19
13.70
18.74
6.14
7.92
25.58
30.05
54.58
43.30
Employed in export sector1
Seafood industry
3.03
3.18
25.71
27.65
10.71
11.52
25.36
28.57
38.21
32.26
Food processing
2.46
3.09
11.89
14.95
4.90
5.15
29.72
30.93
53.50
48.97
Textiles
3.43
2.89
7.48
13.12
4.08
6.79
22.00
28.51
66.44
51.58
Shoes
0.00
0.49
9.68
5.88
3.23
5.88
38.71
58.82
48.39
29.41
Not employed in export sector
91.47
90.81
30.69
35.86
4.56
5.10
27.57
29.64
37.18
29.89
Source: Authors’ own calculations from the Vietnam Living Standards Survey 1992-93 and 1997-97.
Note: 1. Refers to households with at least one member employed in one of the four main export sectors.
Category
% of rural
panel
Always poor
(%)
40
Nonpoor 92-3
Poor 97-8 (%)
TABLE 8 - RELATIVE RISK RATIOS FOR ESCAPING AND FALLING INTO POVERTY AND CHANGES IN CONSUMPTION EXPENDITURE
PNP
Model 1
NPP
PNP
Model 2
NPP
PNP
Model 3
NPP
PNP
Model 4
NPP
PNP
Model 5
NPP
PNP
Model 6
NPP
Model 7
Model 8
Geographic/ethnic
characteristics
Northern Uplands
Red River Delta
(North Central)
Central Coast
Central Highlands
South East
Mekong River Delta
1.043
1.329*
1.043
1.023
1.088
1.129
0.919
1.231
1.114
0.978
0.861
1.381
0.885
0.853
1.045
1.703**
1.102
1.016
0.795
1.287
1.024
1.036
1.105
1.580**
-0.040
0.043*
-0.037
0.046**
1.298
1.861*
5.544***
2.409***
0.347***
0.178***
0.053***
0.096***
1.186
0.751
4.133***
1.880***
0.381***
0.511
0.075***
0.168***
1.381
0.472
5.229***
2.121***
0.300***
0.549
0.064***
0.176***
1.167
0.710
5.506***
1.768**
0.364***
0.458
0.073***
0.226***
1.540*
0.974
7.915***
1.855**
0.271***
0.356**
0.049***
0.206***
1.238
0.672
5.384***
1.840**
0.325***
0.542
0.078***
0.207***
-0.129***
-0.030
0.077**
-0.183***
-0.125***
-0.019
0.090***
-0.172***
0.524
0.411***
0.359
2.709***
0.350
0.430***
0.690
2.594***
0.404
0.474***
0.815
2.177***
1.831
0.484***
0.686
2.870***
0.797
0.735*
1.137
1.574**
1.806
0.430***
0.474
2.130***
-0.072
-0.043*
-0.054
-0.046*
0.981
1.190
1.015
1.159
0.945
1.156
1.047
1.014
0.998
1.129
1.033
1.047
0.055***
0.054***
Head is male
(Head is female)
0.969
1.010
0.915
1.191
1.006
1.187
1.021
0.936
0.988
1.226
0.968
1.017
0.001
0.003
Head age in 92-93
Change in head age
Head age squared
1.340***
0.611***
1.353***
0.605***
0.844***
1.354***
0.837***
1.399***
1.213**
1.082
0.920
0.656***
0.887
1.258***
1.172*
0.993
0.872**
0.657***
0.953
1.242***
1.231**
1.200*
1.071
0.647***
0.839
1.146**
1.031
0.856*
0.875**
0.754***
0.904
1.280***
-0.011
0.006
0.009
-0.014
-0.007
0.019**
No adults in 92-93
Change no. adults
No children 92-93
Change no. children
1.077
1.081
0.976
1.494***
0.727***
2.365***
0.668***
2.965***
0.583***
0.519***
0.443***
0.343***
2.026***
1.397***
4.603***
2.489***
0.569***
0.528***
0.458***
0.352***
2.122***
1.274***
4.516***
2.651***
0.623***
0.566***
0.442***
0.331***
1.941***
1.318***
4.766***
2.552***
0.548***
0.519***
0.630***
0.424***
2.265***
1.255**
2.677***
2.329***
-0.037***
-0.125***
0.024**
-0.160***
-0.050***
-0.134***
0.043***
-0.109***
2.054***
0.441***
2.004***
0.462***
2.047***
0.433***
1.897***
0.508***
1.827***
0.399***
1.961***
0.426***
-0.033*
-0.035*
(Kinh)
Chinese
Other ethnicity
Buddhist
(Non-Buddhist)
Demographic
characteristics
Human capital
characteristics
(Head no educ)
Primary school
Poverty Dynamics in Rural Vietnam
Low sec school
Up sec school
Technical/university
Ch head education
2.992***
3.192***
2.260***
0.272***
0.166***
0.223***
2.954***
3.089***
2.262***
0.286***
0.167***
0.211***
3.383***
3.781***
2.636***
1.421***
0.211***
0.109***
0.156***
0.571***
3.322***
3.550***
2.582***
1.506***
0.249***
0.143***
0.194***
0.591***
4.377***
3.709***
2.918***
1.648***
0.134***
0.090***
0.124***
0.474***
3.239***
3.235***
2.578***
1.409***
0.219***
0.127***
0.172***
0.620***
0.012
0.038
0.009
-0.010
0.009
0.037
0.005
-0.014
Hh w/ no spouse
1.043
1.002
1.083
1.008
1.083
0.841
1.016
0.769
1.164
0.980
1.085
0.713
-0.002
-0.002
(Spouse no educ)
Primary school
Low sec school
Up sec school
Technical/university
Ch spouse educ
1.116
1.128
1.308
2.212***
0.683**
0.934
0.672
0.190***
1.200
1.180
1.364
2.609***
0.643**
0.891
0.611
0.145***
1.279
1.324
1.659
3.270***
1.157
0.573***
0.687
0.399**
0.109***
0.648***
1.324*
1.184
1.566
3.021***
1.032
0.485***
0.630*
0.309***
0.140***
0.817
1.360*
1.494*
1.271
2.279**
1.275*
0.614**
0.611**
0.498*
0.137***
0.638***
1.366*
1.388*
1.724*
3.045***
1.145
0.525***
0.606**
0.364**
0.120***
0.756*
0.030
-0.009
-0.073
0.005
-0.014
0.032
-0.004
-0.057
0.008
-0.014
3.520***
1.283
0.151***
0.386***
3.751***
1.569
0.125***
0.232***
4.153***
1.913*
0.115***
0.215***
3.929***
2.212**
0.121***
0.196***
5.029***
1.258
0.092***
0.235***
4.138***
1.826*
0.120***
0.243***
0.026
-0.058
0.028
-0.059
1.038
0.670**
0.734
1.115
1.318
0.692*
0.496***
0.943
1.778**
0.936
0.402***
0.751
1.717**
1.185
0.430***
0.617*
1.547
0.837
0.460***
0.798
1.917***
1.514*
0.360***
0.566**
0.020
0.036
0.024
0.041
1.719***
0.643**
1.431**
0.770
1.418**
0.727*
1.390**
0.751
0.077***
0.081***
0.781
1.259
0.955
1.201
0.759
1.547
0.737
1.398
-0.054*
-0.061*
Labour market
characteristics
White collar
Sales
(Agriculture)
Production
Not working
Ch other occu9 978
Ch to agric in 97-8
Empl. export sector
(Not empl exp sec)
No hh workers in
exp industries 92-3
Seafood
Food processing
Textiles
Ch no work exp ind
Seafood
Food processing
Textiles
Footwear
1.480
0.495*
1.425
0.509
1.433
0.510
1.067
0.495
1.374
0.590
-0.089*
-0.094**
1.083
0.933
1.015
0.823**
0.952
1.018
1.244**
1.025
1.185
0.695***
0.859
0.874
1.133
1.115
1.030
0.774**
0.811*
0.927
1.370**
1.153
1.135
0.672**
0.787
0.912
1.153
1.044
1.060
0.731***
0.821*
0.854
-0.019**
0.007
0.009
-0.018**
0.010
0.008
1.125*
1.151*
1.237**
1.112*
0.822***
0.828***
0.799**
0.928
1.003
1.229***
1.182*
1.114***
0.884**
0.786***
0.830*
0.957
1.219**
1.150*
1.000
5.311***
0.792***
0.827***
0.967
0.071***
1.121*
1.167**
1.164*
1.092**
0.837***
0.842**
0.802**
1.069
-0.009
0.010
0.006
0.006
-0.008
0.010
0.004
0.006
External shocks
42
Poverty Dynamics in Rural Vietnam
No. wdays lost 92-3
(No work lost)
Head ill in 1997-98
(Head not ill)
1.243
0.895
No weather dis 93-8
1.284
0.804
1.476
0.692
1.210
0.766
1.162
0.947
1.180
0.719
-0.029
-0.027
1.083
0.998
1.001
1.061
1.097
0.823
1.162
0.990
0.005
0.004
0.979***
1.025***
0.982**
1.024***
0.985**
1.035***
0.969***
1.023***
0.977***
1.024**
-0.006***
-0.006***
1.557***
0.583***
1.089
0.914
1.813***
1.216
1.017
0.988
0.534***
0.892
0.846
0.860*
1.217
1.165
1.114
1.111
0.755
0.908
0.833
0.800***
2.327***
1.260
0.733*
0.967
0.471***
0.856
1.059
0.883
1.354
1.203
1.099
1.023
0.703
0.930
0.780**
0.814***
-0.017
0.009
-0.028**
0.013*
-0.021*
0.009
-0.027**
0.012
1.230*
0.891
1.157
0.458***
1.404**
1.207*
0.976
1.157
1.166***
1.018
0.927
1.101
0.511***
0.897
0.986
1.029
1.319**
1.184
1.307
1.037
1.161***
1.020
1.068
1.143
0.401***
1.000
1.014
1.057
1.444**
1.597***
0.995
1.076
1.159**
1.011
0.732*
0.855
0.415***
0.985
0.948
1.065
1.288*
1.205*
1.221
1.072
1.099**
1.029
1.057
1.141
0.458***
0.949
1.049
1.076
0.006
0.020
-0.032**
0.017
0.032***
0.009
0.005
0.019
-0.029*
0.018
0.032***
0.007
5.068***
0.176***
2.365*
0.092***
3.305***
2.104***
1.326**
0.842
6.754***
4.236***
0.233***
0.514***
0.611***
1.790
0.039***
0.243***
2.860***
2.100***
1.345***
0.810
4.356***
3.297***
0.269***
0.503***
0.622***
1.946*
0.048***
0.312***
2.414***
1.894***
1.302*
1.389
3.879**
2.546**
0.322***
0.583**
0.580***
0.985
0.019***
0.181***
3.264***
2.054***
1.328***
0.802
6.819***
4.328***
0.248***
0.517***
0.605***
2.138*
0.037***
0.238***
0.003
0.025***
0.000
0.102**
-0.214***
0.004***
0.002
0.026***
0.001
0.098**
-0.222***
0.004***
1.112
0.917
1.101
1.180
1.802**
1.080
1.004
1.431
1.535
1.252
0.074**
0.080**
1.735
1.354
2.422*
1.328
2.176
0.895
1.693
1.959
0.057
0.075
Agriculture
variables
Quant fert 1992-93
Ch in quant fert
Land irrig pc 92-93
Ch land irrig pc
Rice
Productivity 92-3
Ch productivity
Quant prod 92-93
Ch quant prod
Ch retail uv
Ch farm uv
Other crops
Quant prod cf 92-3
Ch coffee prod
Ch retail uv coffee
Ch farm uv coffee
Cult non-rice 92-3
Ch area cultivated
Assets
Land in 1992-93
(No land)
Ch in land rights
Net assets in 92-93
Change in net assets
0.728
0.292**
0.748
0.251***
0.624
1.887***
0.246**
0.528**
0.502
2.243***
0.206**
0.463***
0.815
1.409
0.252**
0.530**
0.885
2.227***
0.105***
0.524**
0.030
0.054**
0.028
0.055**
Hh rec remit 92-3
1.083
0.872
1.149
0.781*
1.061
0.859
1.043
0.769*
0.946
0.906
1.127
0.769*
0.014
0.014
43
Poverty Dynamics in Rural Vietnam
(Not receive rem)
Increase remittances
(No increase)
1.229
0.744*
1.159
0.830
1.315*
0.750*
1.243*
0.870
0.060***
0.060***
1.907***
0.181***
2.266***
0.152***
2.209***
0.213***
2.365***
0.146***
-0.019
-0.020
1.634***
0.446***
1.635***
0.457***
1.800***
0.444***
1.711***
0.454***
0.011
0.015
Infrastructure and
institutions
Hh w/ elect 92-3
(No electricity)
Ch electricity access
Commune vars 92-3
Road
Primary school
Low sec school
Up sec school
Post office
Daily market
Food shop
Clinic
1.510***
0.309***
1.373***
0.325***
1.644***
0.933
0.874
1.348
0.555***
1.276*
1.456***
2.092***
1.466**
6.228***
0.879
0.674*
2.584***
0.640***
0.460***
0.517***
1.540**
0.876
0.863
1.559**
0.613***
1.498***
1.442***
2.076***
1.505**
7.952***
0.987
0.560***
2.419***
0.531***
0.451***
0.420***
1.190
0.662
0.871
1.755***
0.589***
1.547***
1.413**
1.928***
2.289***
8.376***
0.969
0.535***
2.607***
0.458***
0.496***
0.484***
1.108
0.926
1.026
1.778***
0.535***
1.663***
1.343**
1.385
2.302***
6.338***
0.881
0.536***
2.245***
0.453***
0.576***
0.690
0.880
0.432*
0.815
1.788**
0.732*
1.394**
1.300
1.981***
2.712***
9.978***
1.225
0.473***
2.090***
0.500***
0.513***
0.450***
1.026
0.575
1.202
1.748***
0.582***
1.494***
1.342**
1.789**
2.758***
12.281***
0.778
0.543***
2.367***
0.433***
0.567***
0.578*
0.149***
0.291***
-0.081***
0.011
-0.023
0.011
-0.018
0.007
0.151***
0.284***
-0.082***
0.012
-0.021
0.010
-0.021
0.005
(Interv 1stq 92-3)
2nd quarter
3rd quarter
4th quarter
0.950
1.015
0.892
1.470**
0.820
1.026
0.919
1.269
0.902
1.502**
0.647***
0.986
0.911
1.287
0.800
1.364
0.613***
0.942
0.980
1.262
0.726**
1.306
0.646**
0.906
0.973
1.441**
0.980
1.576**
0.625**
1.065
0.830
1.107
0.751**
1.394
0.563***
0.898
0.058**
-0.063***
-0.050**
0.058**
-0.066***
-0.052***
Constant
0.174***
1.283
0.227***
1.455
0.087***
1.448
0.035***
2.038
0.198**
0.184
0.043***
3.504
-0.067
-0.086
Seasonality
Observations
3494
3494
3494
3494
3494
3494
3494
3494
3494
3494
3494
3494
3494
3494
Adjusted R-squared
0.184
0.184
0.222
0.222
0.284
0.284
0.288
0.288
0.278
0.278
0.276
0.276
0.252
0.228
Hausman statistic
-22.73
-22.73
-6.86
-6.86
-33.14
-33.14
-2685.02 -2685.02
-125470
-125470
-112.87
-112.87
Notes: ***significant at 1% level, **significant at 5% level, *significant at 10% level. Model 1: base model. Model 2: includes variables affected by the trade reforms. Model 3: includes ‘change’
variables. Model 4: uses poverty line 10% above the official poverty line. Model 5: uses poverty line 10% below the official poverty line. Model 6: uses adult-equivalent adjusted poverty line. Model 7:
consumption model using non-adjusted consumption expenditure estimates. Model 8: consumption model using consumption expenditure estimates adjusted to adult equivalent scales.
44
Poverty Dynamics in Rural Vietnam
TABLE 9 – DECOMPOSITION OF POVERTY DYNAMICS EFFECTS (%)
Variables
Location
Ethnicity and religion
Initial demographic characteristics
Initial education levels (head and spouse)
Initial employment characteristics
Number of workdays lost due to illness
Weather shocks
Initial agriculture conditions
Initial infrastructure
Initial assets
Seasonality effects
Probability of escaping poverty
27.4
-4.6
-8.0
33.6
4.7
0.5
-1.7
8.0
11.7
0.9
-0.6
Changes in demographic characteristics
Educational changes
Changes in employment characteristics
Illness shock
Agriculture changes
Changes in infrastructure
Change in assets
Total
Source: Own calculations based on estimates from model 3.
45
3.0
3.2
0.8
0.1
17.7
2.4
0.9
100.0
Poverty Dynamics in Rural Vietnam
TABLE 10 – CHANGES IN CONSUMPTION PER EXPENDITURE QUINTILE (SELECTED VARIABLES)
Model 7
Quint 1
Geographic characteristics
Central Coast
Mekong River Delta
Quint 2
Quint 3
-0.129***
-0.183***
0.022
-0.152**
-0.090*
0.088
-0.097*
-0.017
-0.033
-0.074
-0.042
-0.108
Demographic characteristics
Head age in 1992-93
Number children 1992-93
-0.011
0.024**
0.025
-0.033*
0.041**
-0.100***
-0.007
-0.053***
0.014
-0.013
0.048
-0.048
Human capital characteristics
Head with prim school educ
Ch head education
Spouse with upper sec educ
Spouse with tech/univ educ
Ch spouse education
-0.033*
-0.010
-0.009
-0.073
-0.014
0.004
0.006
0.025
0.025
0.001
0.077**
0.067**
0.097**
0.118
0.055**
0.041
0.001
-0.016
-0.012
-0.018
0.026
0.030
-0.042
-0.038
-0.012
-0.023
0.022
0.206**
-0.046
0.067
Labour market characteristics
White collar in 1992-93
Sales in 1992-93
Employed in export sector
Workers in seafood ind
Workers in food proc ind
Workers in textiles ind
Ch workers seafood
Ch workers food proc
Ch workers textiles
Ch workers footwear
0.026
-0.058
-0.089*
-0.019**
0.007
0.009
-0.009
0.010
0.006
0.006
0.036
-0.157
-0.257**
0.028
0.033
0.085**
0.001
0.015
0.014
0.005
0.164**
0.048
0.017
-0.000
0.037
0.015
-0.011
0.032***
0.027
0.026***
0.123*
0.056
0.015
0.000
0.026
0.011
0.021
0.036***
0.054**
0.002
0.096
0.121**
-0.137*
-0.024
0.029
0.030
-0.024**
-0.013
-0.006
-0.013
0.227***
0.015
-0.045
0.062***
-0.006
0.012
0.016
0.009
-0.001
0.000
Agriculture production
Quantity fertilisers 1992-93
Ch use of fertilisers
Land irrigaped pc 1992-93
Ch land irrigated per capita
Quantity rice produced
Ch rice production
Area cultiv w/ non-rice 92-3
Ch area cult w/ non-rice crops
-0.017
0.009
-0.028**
0.013*
-0.032**
0.017
-0.214***
0.004***
0.240***
0.091**
0.017
0.009
-0.260***
-0.033
0.018
0.179**
0.093***
0.045**
0.005
-0.014
-0.008
-0.008
0.005
0.145**
0.005
0.023
0.001
0.006
0.001
0.036
-0.077
0.003**
-0.008
0.000
-0.030
0.022*
0.012
-0.002
0.206**
0.076**
-0.038
0.010
0.002
0.026**
0.047**
0.021
-0.042
0.103
681
0.49
444
0.44
Observations
3494
813
801
755
R-squared
0.25
0.35
0.42
0.39
Notes: ***significant at 1% level, **significant at 5% level, *significant at 10% level.
46
Quint 4
Quint 5
Poverty Dynamics in Rural Vietnam
APPENDIX A – CONSUMPTION MODEL
The model assumes risk neutral households that maximise their expected profits and is based on a household’s
joint income generation process described as q=f(x,k,u), in which q is total output, x is a vector of n variable
inputs, k is a vector of j fixed inputs and u is a vector of m stochastic factors shared by all households (climatic
conditions, commune characteristics, etc). x represents effectively the fixed effects in the model, whereas k
represents the effects of variables that change between the years of the analysis.
The household’s maximisation problem is then written as
max E (Y ) = p.g ( x, k , u ) − p x .x , where p is the
x,q
output price and px represent the input prices. Assuming that the production function takes a Cobb-Douglas form
q = a.x α k β u γ , we have that
Y =a
1
1−α
.α
1
1−α
.(1 − α ).k
β
1−α
.p
1
1−α
.px
−α
1−α
.u
γ
1−α
(1)
Taking logs, aggregating (1) over all households, using subscripts I to denote different households and
introducing a household-specific effect
δ i for each household I, we have that (Dercon, 2000: 7):
ln Yi = δ i + ln ai* + ϕ * ln p i + ∑ α n* ln p inx + ∑ β *j ln k ij + ∑ γ m* ln u im
n
j
(2)
m
Allowing for these possible changes, considering periods t and t+1 as respectively before and after the reforms,
and denoting ∆ as the difference in values between t+1 and t, differences in profits over time are:
∆ ln Yi = ∆ ln a i* + ϕ t*+1∆ ln pi + ∆ϕ * ln pit + ∑ α nt* +1 ∆ ln p inx + ∑ ∆α n* ln pintx + ∑ β *jt +1 ∆ ln k ij
n
+ ∑ ∆β ln k ijt + ∑ γ
*
j
j
m
*
mt +1
n
∆ ln u im + ∑ ∆γ ln u imt
*
m
m
47
j
(3)
Poverty Dynamics in Rural Vietnam
The formulation above allows us to calculate the different elasticities of consumption expenditure relative to
household characteristics that that remain constant over time (region, tribe and religion) and household
characteristics that have changed over time. As long as we can relate some of these characteristics to the
economic and trade reform implemented in Vietnam, then the model allows us to determine the effects of those
reforms on changes in real household consumption expenditure (Dercon, 2000).
The theoretical model (3) can be easily transformed into an econometric model:
∆ ln Yi = η + ϕt*+1∆ ln pir + ∆ϕ * ln pitr + β t1+1∆Di + ∆β 2 ln Dit + βt1+1∆Ei + ∆β 2 ln Eit + β t1+1∆Li + ∆β 2 ln Lit +
β t1+1∆Ti + ∆β 2 ln Tit + βt1+1∆Ai + ∆β 2 ln Ait + β t1+1∆I i + ∆β 2 ln I it + ∆ ln Wi + ∑ ∆ k ln Citk + eit +1
k
where:
η = fixed characteristics (including interview quarter)
p r = rice and coffee prices (producer and consumer)
Dit = demographic characteristics (household size and household composition) in year t
Eit = education characteristics in year t
Lit = labour market characteristics in year t
Tit = trade-related variables (employment in export industries, production of rice and coffee and measure of
diversification) in year t
Ait = household assets in year t
C itk = institutional and infrastructure characteristics in year t
I it = illness shock
Wi = weather shock
e = error term
48