Spatial Variation in the Disability-Poverty Correlation – Evidence from Vietnam

1 Spatial Variation in the Disability-Poverty Correlation: Evidence from Vietnam Daniel Mont Leonard Cheshire Disability and Inclusive Development Centre University College London Cuong

Munich Personal RePEc Archive

Spatial Variation in the

Disability-Poverty Correlation: Evidence from Vietnam

Mont Daniel and Cuong Nguyen

15 June 2013

Online at http://mpra.ub.uni-muenchen.de/48659/

MPRA Paper No 48659, posted 28 July 2013 09:10 UTC

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Spatial Variation in the Disability-Poverty Correlation:

Evidence from Vietnam

Daniel Mont Leonard Cheshire Disability and Inclusive Development Centre

University College London

Cuong Nguyen National Economics University in Hanoi

Abstract

Poverty and disability are interrelated, but data that can disentangle to what extent one causes the other and vice versa is not available However, data from Vietnam allows us to examine this interrelationship in a way not done previously Using small area estimation techniques, we uncover three findings not yet found in the literature First, disability prevalence rates vary significantly within a county even at the district level Second, the correlation between disability and poverty also varies at the district level And most importantly, the strength of that correlation lessens based on district characteristics that can be affected by policy Districts with better health care and infrastructure, such as road and health services, show less of a link between disability and poverty, supporting the hypothesis that improvements in infrastructure and rehabilitation service can lessen the impact of disability on families with disabled members

Keywords: Poverty, disability, small area estimation, household survey, population

census, Vietnam

JEL codes: I12, I31, O15

Acknowledgments: The authors would like to thank Sophie Mitra for her comments on an earlier draft of this paper

However, when one looks at the empirical relationship between consumption measures of poverty and disability, the link is not always strong In the broadest available look at the relationship of disability and poverty, Mitra et al (2013) found that only four countries showed a significant relationship In fact, while growing incomes can lessen the rate of poverty by ameliorating many of the factors mentioned above, growing incomes can also increase disability rates First, primarily by leading to longer life expectancies Disability rates are much higher for older people (WHO/World Bank 2011) And not only

do richer societies have longer life expectancies, but among people with later onset disabilities the link to poverty is weaker (Mont and Nguyen 2011, Demographic Institute, 2013) Not being disabled when of working age, people who become disabled as older adults have not had their education, training, employment, and years of asset building affected by disability And the richer they are, the more they have been able to afford health care, rehabilitative services, or assistive devices that can help them survive disabling conditions that might have otherwise proved fatal

Nevertheless, Mitra et al (2013) found a significant correlation between disability and multidimensional poverty in most of the developing countries under study when looking at various measures of exclusion, such as deficits in education,

employment, life expectancy, etc The World Report on Disability (WHO/World Bank

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2011) reports a wide literature showing this to be the case It also points out that disability

is not a rare event Globally, the prevalence rate for disability is about 15 percent, and about 4 percent for those with severe disabilities The percentage of people living in households with a disabled member is much higher And it should be remembered that disability impacts family members, as well, by affecting their schooling and work decisions In Vietnam, for instance, children of parents with disabilities are significantly less likely to attend school (Mont and Nguyen 2013)

Moreover, having a disability imposes extra costs (Tibble 2005, Zaidi and Burchardt 2005) such as extra medical costs, assistive devices, and special transportation needs In fact, studies estimate that in Vietnam disability increases the cost of living by about 10% (Braithwaite and Mont 2009, Mont and Nguyen 2011) Thus, the relationship between disability and poverty – adjusting for those costs – is even stronger

Disentangling the effects of disability on poverty and vice versa, though, is difficult To our knowledge, a panel data set that could be used to examine the transitions

in and out of both states is not available.Moreover, as Mitra et al 2013 state “whether disability and poverty are causally related is an empirical question and the answer will be environment specific.”Indeed, we hypothesize that various factors may lessen the link between disability and poverty For example, improved roads and transportation systems could lessen the barriers that disabled people face in obtaining education and employment,

or even participating in community events To the extent those systems are more inclusive, the barriers to participating in things such as work would become even less Also, improved access to health and rehabilitation services could increase functional capabilities of individuals And, the more people with disabilities move about their communities, the more they can break down existing stereotypes and misconceptions that might be serve as attitudinal barriers to their increased participation in society

This paper uses a unique source of data to explore how local characteristics – within a single country – could influence the link between disability and poverty While data directly related to inclusion – for example, accessibility audits of infrastructure and the availability of assistive devices – are not available, the hypothesis is that improved

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infrastructure related to those concepts – better roads, more doctors, and a more developed infrastructure (e.g., communication and transportation systems, electrification, etc) – can make people with disabilities and their families less likely to experience poverty As such, this is the first empirical paper the authors are aware of that explores not only the relation between disability and poverty, but also what specific factors influence that relationship

The findings in this paper can potentially be useful for policymakers in two regards First, because these techniques can be used to identify potential policy levers for lessening the link between disability and poverty, but secondly because they can identify regional differences in disability rates and the disability-poverty connection that can be useful in targeting programs

The remainder of this paper is organised as follows Section 2 briefly presents the data sets used in this study Section 3 presents the methodology to investigate the association between poverty and disability Next, section 4 presents the empirical findings Finally, section 5 concludes

2 Data

This study relies on two main data sets The first is the 15-percent sample of the Vietnam Population and Housing Census (referred as the 2009 VPHC) The 2009 VPHC was conducted in April 2009 by the General Statistics Office of Vietnam (GSO)with technical assistance from the United Nations Population Fund (UNFPA)

The 2009 VPHC is designed to be representative at the district level.1 It covered 3,692,042 households with 14,177,590 individuals The 2009 VPHC contains data on individuals and households Individual data include demographics, education,

1 Administratively (?) Vietnam is divided into 63 provinces Each province is divided into districts, and each district is further divided into communes (communes are called wards in urban areas) Communes are the smallest administrative areas In 2009, there were 690 districts and 10,896 communes

The second dataset is the 2010 Vietnam Household Living Standard Survey (VHLSS) The 2010 VHLSS was carried out by GSO with technical support from the World Bank in Vietnam The 2010 VHLSS covers 9,402 households with 37,012 individuals, who are sampled from the population frame of the 2009 Population Census The 2010 VHLSS is representative for rural/urban areas and 6 geographic regions

The 2010 VHLSScontains very detailed data on demographic and living standards

of individuals, households and communes Individual data includeinformation on demographics, education, employment, health and migration, while household data include information on durables, assets, production, income and expenditure, and participation in government programs However, there are no data on disability in the

2010 VHLSS

In this study, we define a household as poor if their real per capita expenditure is below the GSO-World Bank expenditure poverty line of 653 thousand VND/month/person (7836 thousand VND/year/person) Under this line the poverty rate of Vietnam in 2010 is 20.7 percent

3 Methodology

2 There is a full population census which was conducted in April 2009 However, this census contains onlylimited data on basic demographic and housing data There are no data on disability in the full census Thus we do not use the full census in this study

3

See http://www.cdc.gov/nchs/washington_group.htm

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Poverty gaps between households with and households without disabled members

The main objective of this study is to examine the spatial correlation between poverty and disability and subsequently investigate several factors associated with this disability-povertycorrelation in Vietnam We will estimate the poverty measures for households with and without disabled members at the provincial and district level Although the 2010 VHLSS contains expenditure data for households, it is not representative at the provincial

as well as district level On the contrary, the 2009 VPHC is representative at the district level, but it does not contain expenditure data to estimate the poverty measures To overcome this data limitation, we will use a small area estimation method that essentially links the information in both data sets (Elbers et al 2002, 2003) In Vietnam, this method has been widely applied to construct the poverty and inequality maps (e.g., Minot et al., 2003; Nguyen et al., 2010; Nguyen, 2011; Lanjouw, 2012)

The Elbers et al (2002, 2003) method is used to combine a population census and

a household survey to predict welfare measures such as poverty and inequality indicators for small areas It can be described in three steps as follows First, we select common variables of the census and the households The common variables can include household-level variables, commune-level and district-level variables

Secondly, we regress the log of per capita expenditures on the common variables using the household survey More specifically, we use the following model:

, )

ln( yic = Xicβ + ηc + εic (1) whereln( yic) is log of per capita expenditure of household i in cluster c, Xic the vector of the common variables, β the vector of regression coefficients, ηc the cluster-specific random effect and εic the household-specific random effect The subscript ic refers household i living in cluster c

In the third step, we use the estimated model to predictper capita expenditure of households in the census:

It should be noted that the point estimates as well as the standard errors of the poverty estimates are calculated by Monte-Carlo simulations In each simulation, a set of values β ˆ,

c

η ˆ and ε ˆic are drawn from their estimated distributions, and an estimate of per

capita expenditure and the poverty indices are obtained After k simulations, we can get the average and standard deviation over the k different simulated estimates of the

expenditure and poverty indexes

In this study, we will estimate the poverty indexes of households with and without

a disabled member at the regional, provincial and district levels Using the data on disability in the 2009 VPHC, we can divide households into one group of households with

a disabled member and another group of households without a disabled member We can estimate the poverty indexes of the two groups of households, then compute the gap in poverty indexes between these two groups:

ND D

whereGpis the gap in poverty indexes or mean expenditure, P D and PND are the mean expenditure or poverty indexes of households with a disabled member and households without a disabled member, respectively The gap in poverty can be regarded as a measure

of the correlation between poverty and disability at the small areas If there is no

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correlation between poverty and disability, we will expect a small difference in poverty between households with and households without disability

Regressions of poverty gaps between households with and households without disability

We will examine several factors associated with the poverty-disability correlation The poverty-disability correlationis measured by the gap in the poverty indexes between households with and without disabled members We will run a regression of the gap in poverty indexes on several explanatory variables at the district level Since the observations are districts and there can be a spatial correlation between dependent variables and error terms, we apply the following spatial model:

d d d

d d

WhereGdis the gap in poverty indexes between disabled and non-disabled households of

district d, Xd is a vector of explanatory variables of the district W and M are weighting matrices (with zero diagonal elements) The dependent variables are allowed to

spatial-be correlated with each other The model is a type of spatial econometric model with the first-order spatial-autoregressive and first-order spatial-autoregressive disturbances (see,

e.g., Haining, 2003; Drukker et al., 2010, 2011) W and M are spatial-weighting, which are

set equal to each other and equal to the inverse-distance between centroids of districts This matrix weight allows for the high correlation between close districts and low correlation between far districts

4 Empirical results

4.1 Disability in Vietnam

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Construction of an uncontroversial definition of disability is difficult According to a measurement method suggested by the Washington Group, which was established by United Nations Statistical Division with the participation of over 100 National Statistical Offices and international agencies (Madans et al., 2010), disability is measured in household surveys by asking respondents about their difficulties in basic functional domains such as seeing, hearing, walking, self-care, cognition, and communication (Schneider, 2009; Madans et al., 2010)

The 2009 VPHC relies on a similar method suggested by the Washington Group

on Disability Statistics to measure the disability More specifically, interviewees are asked about their difficulties in the four basic functions including seeing, hearing, walking, and remembering There are four multiple exclusive responses: (i) no difficulty, (ii) some difficulty, (iii) a lot of difficulty and (iv) unable to do (cannot do at all)5 Based on the availability of the 2009 VPHC data and following Loeb, Eide, and Mont (2008) and Mont and Nguyen (2011), we will define a person to be disabled if she or he has a little difficulty in at least two of the functional domains (seeing, hearing, walking, and remembering), or a lot of difficulty or unable to do at least one of the domains

The above measure of disability includes people with mild and moderate, as well

as severe disabilities In addition, we also conduct the analysis using a higherthreshold level fordisability, which is defined as having considerable difficulty (a lot of difficulty and unable to do) in at least one of the four functional domains This measure of disability excludes those with only mild or moderate disabilities

Table 1 presents the proportion of people aged above five with difficulties in the four functional domains There are 5.0 and 3.1 percent of respondents having difficulty in seeing and difficulty in hearing, respectively The proportion of people having difficulty in walking and remembering is 3.7 and 3.5 percent, respectively

5 The WG recommended six census questions, but set the minimum useful set as four questions, recognizing that space on censuses is often tight and some countries were resistant to including all six questions Vietnam was one such country – and as such there is probably an underestimation of the rate of disability

Having difficulty in hearing

Having difficulty in walking

Having difficulty in remembering

Having difficulty includes little difficulty, considerable difficulty and inability to do

Standard errors in parentheses

Source: Estimates from the 2009 VPHC

Table 2 presents the prevalence of people with any disability and those with only a severe disability The proportion of people using the two respective measuresare 4.3 and 1.7 percent, respectively The proportion of households with at least one member with any disabilityis 12.3 percent (It is important to remember this means the person has at least a low level of disability but includes people with more significant disabilities as well) The proportion of households with at least one member who has anydisability is 5.3 percent

Table 2: The prevalence of disability (in percent)

Region

Proportion of people from 5 years old with

Proportion of households with at least a member with Any

disability

Severedisabi lity

Anydisabilit

y

Severedisabi lity

disability

Severedisabi lity

Anydisabilit

y

Severedisabi lity

Standard errors in parentheses

Source: Estimates from the 2009 VPHC

Figure 1 presents the proportion of households with at least one member with any disability at the provincial and district levels Households who live in North East and Central Coast are more likely to have a member with a disability Figure 2 shows a similar spatial pattern of the proportion of households with at least one member with threshold severe disability

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Figure 2: The proportion of households with at least one member with a severe disability

(%)

Source: Estimates from the 2009 VPHC.

Moving down to the district level, though, reveals the variation in disability within

a given province This suggests that the causes of disability could stem from relatively local effects, possibly related to water sources, traffic patterns, lack of availability of medical services, or any variety of factors

4.2 Disability and poverty

To estimate the poverty indexes for households with and without disabled members, we combine the 2009 VPHC and the 2010 VHLSS using the small area estimation method Lanjouw et al (2013) also use the same data set and method to estimate the poverty and inequality maps of districts in Vietnam Thus we refer to Lanjouw et al (2013) for the