Demand for health care services in Ethiopia: exploratory analysis based on household surveys

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Demand for health care services in Ethiopia
exploratory analysis based on household surveys

• Almayehu Geda
• Abebe Shimeles

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outline

• Background
• Objectives of the study
• Theoretical framework
• Estimation strategy
• Discussion of main results
• Policy implications

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Background

• Ethiopia spends close to 5 of GDP, equally
  divided between public and private, on health
  related services
• This is not typical of Ethiopia, but, common
  among low income countries in SSA (Figure 1)

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Figure1 Per capita expenditure on health as a
share of per capita consumption expenditure in
Africa (2005)
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But, health outcomes are not that encouraging
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Objectives of the paper

• What factors influence individual demand for
  health care services that would improve health
  outcome?
• What are the lessons for public policy in
  combating disease burden beyond the provision of
  basic health care services?

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Theoretical framework

• Grossmans (1972, 2000, 2004) formulation of
  individual health both as investment and
  consumption good in a life cycle.

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The set up individuals maximize life time
utility subject to constraints
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Reduced form demand for health as investment good
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Standard demand function when health is treated
as a consumption good
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Data and key variable definition

• The paper uses the 2004/06 Household Income
  Expenditure Survey that covered around 21,000
  households close to 100,000 individual stories
• Dependent variable (health outcomes)
• A dummy if an individual has been sick in the
  last four weeks
• Number of days lost due to illness
• Stunting

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Variable definition

• Health inputs and control variables
• Affordability, distance to nearest health post,
  health center clinic, quality of services,
  perceptions about health care systems
• Highest grade attained
• Real per capita consumption expenditure, calorie
  intake and employment status
• Demographic characteristics (age, household size,
  gender) and regional dummies

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Empirical strategy

• In the health demand model, key individual
  characteristics may potentially be endogenous
• Particularly education attained and per capita
  income level are likely to be correlated with the
  error term for a number of reasons

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Empirical strategy

• We use two approaches to deal with these
  problems, particularly with the education
  variable.
• First, estimate structural model (joint
  determination of health demand and educational
  attainment in a two-step procedure)
• Second, using instrumental variables (distance to
  nearest primary and secondary schools)
• Both approaches led to valid orthogonality
  condition between regressors and error terms.

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Descriptive statistics

• Large family size (5.6), young population (mean
  32 years) and largely uneducated labor force.
• The highest grade completed in the country is
  grade 11 with 46 having never been to any formal
  school in their life. Poverty is the main reason
  for failing to go to school.

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Descriptive, contd..

• Close to 60 of individuals attributed lack of
  money as the main reason for not going to school.
  
• About 7 also said that they had to work instead
  of going to school probably to support family
  businesses.
• Access explains only 16 of the reason for
  failing to go to school.

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Descriptive..

• Family formation explains a significant
  proportion (10) of avoiding school probably more
  for women particularly in rural areas. Other
  reasons include disability and sickness which
  affect school attendance.
• Negative attitude is also one of the important
  variable explaining aversions towards schooling
  (10)

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Key results on demand for health as investment
good

• Dummy if the individual is down with illness in
  the last four weeks (Table 3 Table 4)
• In rural areas, the effect of individual
  demographic characteristics (age, sex, marital
  status, household size) depend on the choice of
  estimation method.
• In urban areas, being a female and older has a
  high risk of falling sick despite estimation
  methods.

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Key results ..

• Larger family size in both areas imply less
  vulnerability to illness episodes, but up to a
  point. Very large families tend to suffer from
  health shocks (combination of initial health
  endowment and reduced nutrition).

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Key results

• Education plays an important role in rural areas
  in enhancing the efficiency of individual level
  health production. This is not the case in urban
  areas, possibly due to the weakness of distance
  as an instrument for education.

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Key results (Table 5)

• Number of days lost due to illness is clearly and
  significantly affected by the level of education
  attained by the individual with elasticity of
  about 0.5 for the whole sample and 0.2 for rural
  areas.
• Per capita consumption is also very important in
  the whole sample as well as in rural areas.
• Both variables are not important in urban areas.

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Key results Table 5

• Health inputs (affordability, quality, distance,
  attitude to modern health care) seem to have
  large and significant impact in urban areas than
  rural areas.
• Employment status influences health outcomes in
  both rural and urban areas

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Key results table 6

• Education, particularly early access to formal
  school, has a large and significant impact on
  stunting

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Demand for health as a consumption good

• Estimates based on Linear expenditure system
  indicates that health demand is inelastic with
  respect to income (0.6) and price elastic as well
  (0.4) which is not surprising.
• Health is a necessity commodity (Figure 2)

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Figure 2 concentration curve on health and other
commodities
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Public policy implications

• The fact that education plays a key role in
  affecting health outcomes by enhancing efficiency
  implies that investment in education has a direct
  and large impact on health.
• Coordinating health policy with education policy
  could reduce enormously health burden faster and
  cheaper.

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Public Policy implications

• Distance to nearest health care services matters,
  but not so much as cost, attitude, and quality of
  the services (Annex Table 1)
• Regional distribution of health care services
  seem not to be that important which is
  interesting, perhaps indicating that access to
  heath care may not be region specific

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Thank you!