Study | Country | Data source | Statistical model | Measure of health shocks | Coping strategies |
---|---|---|---|---|---|
Phung Duc & Waibe, 2009 [77] | Vietnam | Cross-sectional survey data, June-August 2007 | Fixed effect regression | Idiosyncratic demographic shocks (death or illness of a household member) since 2002 | 11%-13%*** higher number of income sources used |
Kruk et al. 2009 [30] | 40 LMICs | World Health Survey, 2002-2003 | Multiple logistic regression | Any health expenditure in last one year | ***African households 87% and Southeast Asian households 61% more likely (compare to European households) to borrow or sell assets to finance health expenditure |
Gertler et al. 2009 [69] | Indonesia | Indonesian Family Life Survey panel (1993, 1997) | Panel regression | Individual’s limitations in performing ADLs. Index based on a formula using self-reported ability to perform basic and intermediate activities of daily living. | ***Smaller effects on consumption for households within 1 km of financial institution compared to within 10 km or more |
Islam & Maitra, 2012 [72] | Bangladesh | Panel household survey (1998, 2000, 2005) | Fixed effect regression | Household incurred any big expenditure/income loss due to illness in past one years; Whether the main income earner died in the last one year | **Access to microcredit helps to insure consumption |
Powell-Jackson & Hoque, 2012 [73] | Bangladesh | Household survey 2 panels (2007–2008) | Panel regression | Severe maternal complications (dystocia, haemorrhage, hypertensive disorders of pregnancy, septic shock or septicaemia, severe anaemia) | *** US$17 borrow per month, **US$4 asset sale and ***US$4.4 transfer per month compared to normal delivery to fully smooth consumption |
Dercon & Krishnan, 2000 [63] | Ethiopia | Ethiopian Rural Household Survey 3 panels (1994–1995) | Generalized method of moments | Male or female household members are too weak to work in last 28 days | Household with more land are able to insure consumption |
Asfaw & Braun, 2004 [64] | Ethiopia | Ethiopian Rural Household survey panel (1994, 1995) | Two-stage least square | Self-reported illness of household head within 4 weeks before the survey | Able to protect food consumption using own production and gifts |
Park, 2006 [78] | Bangladesh | Matlab Health and Socioeconomic Survey, 1996 | Two-stage least squares & Instrumental Variable | Income shocks out of death or illness of household members | **Relationship between neighbours and relatives helps in pooling risks to smooth food consumption |
Sparrow et al. 2012 [79] | Indonesia | Socio-economic survey panel (2003, 2004) | Fixed effect regression | Household welfare affected during the last year by an event related to illness | 15%*** used borrowing; 9%*** used selling assets; |
22%*** used family assistance; 9%*** reduced consumption | |||||
Abegunde & Stanciole, 2008 [42] | Russia | Life Standards Measurement Survey (8 rounds: 1997–2004) | Two-part Heckit model | Adults reporting chronic disease | 7%*** increase in transfer income (gifts) per increase in household number of chronic diseases |
Nguyen et al. 2012 [80] | Vietnam | Survey on 706 households (2008) | Multiple logistic regression | Hospitalization | Odds ratio = 18** (using loans); |
Odds ratio = 44* (reducing food consumption) | |||||
Raccanello et al. 2007 [81] | Mexico | Survey on 400 pawnshop users, 2005 | Probit regression | Health expenditure due to persistence health shocks | (+) households used pawning to finance OOP health expenditure** |
Modena and Gilbert, 2011 [82] | Indonesia | Family Life Survey, 1993 | Poisson Multinomial Model | Demographic shocks (family deaths or illness) | (+) taking loans***; |
(+) selling assets***; | |||||
(+) using family assistance*** | |||||
Debebe et al.[83] | Ethiopia | Household survey, 2011 | Probit regression | (self-reported illness, death or disability) | (+) 15%*** borrowed; |
(+) 17%*** used savings; | |||||
(+) 17%*** sold assets; | |||||
Dhanaraj, 2014 [84] | India (Andhra Pradesh) | Young Lives survey panel (2006, 2009) | Multinomial logistic regression | Serious illness or death of father affected household economy negatively since the interviewer’s last visit | (+) 49%*** labour supply; (-) 93% *** consumption; |
(+) 53% borrowed or sold assets; (+) 54% received help | |||||
Alam & Mahal, 2014 [43] | 4 South Asian countries | World Health Survey, 2002-2003 | Propensity Score Matching (PSM) | Diagnosed or symptomatic angina | (+) 6-10%** households borrowed or sold assets to finance OOP health expenditure |