Shocks, household choices, and children’s education

1. Shocks, household choices, and children’s education Francesca Modena Ph.D. in Economics and Management - CIFREM

2. OUTLINE • Preliminary analysis of the data • Model the household choices to cope with shocks • Shocks and implications for household vulnerability • Shocks and implications for children’s education

3. PRELIMINARY ANALYSIS OF THE DATA

4. INTRODUCTION Microeconomic shocks may push households into poverty or exacerbate their existing poverty status. Income shocks reduce household wealth not only directly, but also indirectly as a consequence of the measures used by the household to overcome or insure against them. Hence it is important to understand how households cope with actual shocks and the possibility of future shocks, and to evaluatewhich responses are costlier for the household.

5. Some issues to be considered

6. Different types of shocks • Idiosyncratic versus common shocks - Idiosyncratic shocks are household specific, for example the death or sickness of a householder. - Aggregate shocks are common across any given area: this may be the case of crop loss or price falls. • Demographic versus non-demographic shocks • Demographic shocks are for example death and sickness • of a householder

7. Different risk coping strategies: • Risk-sharing strategies formal institutions (insurance), and informal mechanisms such as transfers between friends and neighbours, and in general family/friend assistance • Intertemporal consumption smoothing households smooth consumption through savings, borrowing, accumulating and selling assets

8. DATA • Indonesia Family Life Survey Data (IFLS), 1993 • Data on household economic shocks

9. DESCRIPTIVE ANALYSIS OF DATA Sample: 6280 households, 3454 rural (after dropping income outliers)

10. The most frequent shocks are sickness of a householder and crop loss Business loss and unemployment affect only a few households

11. COSTS OF DIFFERENT SHOCKS (Rural Sample) • Demographic shocks are costlier than non demographic shocks • Looking at the percentage on household income, crop loss becomes costlier than sickness • Shocks have a great impact on household income • At the aggregate level, crop loss has the largest impact, even if the aggregate effects of all these shocks are rather small

12. Focusing on rural sample, this table shows the percentage of households that used each measure * Business loss and unemployment affect only a few households

13. INFORMAL INSURANCE MECHANISMS • Our data confirm what suggested in the literature (see Alderman and Paxson, 1992): • - informal insurance mechanisms, such as family and community assistance, may protect households against idiosyncratic shocks thereby smoothing consumption across households through risk-sharing • the community may not provide an insurance if all households in the same area face the same shock (this could be the case of crop loss); therefore households would be obliged to use other means. In these cases, the consumption reduction is more severe than in the case of an idiosyncratic shock in response to which households seem more able to smooth consumption (see the percentage of households that cut down on expenditures)

14. ASSETS SALE Another measure that may be more useful in coping with idiosyncratic shocks than with common shocks is asset sale: it gives less protection against common shocks because when the majority of households try to sell assets, their prices fall (Morduch, 1994; Frankenberg, Smith and Thomas, 2002).

15. LABOUR AS INSURANCE • Labour supply response plays an important role in the face of crop loss and price falls (see Cameron and Worswick, 2003) • This is not the case for those shocks (demographic shocks) that affect the household’s labour force and may induce the household to use alternative, possibly costlier, methods of insurance (Kochar, 1995) • Sickness may increase the need for domestic labour

16. SAVINGS the percentage of households that use savings to overcome shocks is, in general, low, in particular for non-demographic shocks Separating households into groups according to the level on income: savings is one of the most used measures by the richest 20% to cope with demographic shocks.

17. Model the household choices to cope with shocks

18. EMPIRICAL STRATEGY The aim of this work is to model the probability that a household chooses a given measure to overcome a given shock I would like to control for some income indicators household income and household expenditures are endogenous estimate the permanent and transitory income components allow us to solve the endogeneity problem and to examine the different roles of different income components

19. MEASUREMENT OF PERMANENT AND TRANSITORY INCOME: Cameron and Worswick’s approach (2003) Cameron and Worswick (2003), following Paxon (1992), propose a different approach that treats transitory income not as a residual but as a function of a set of variables. Where is household income, and are vectors of variables that may affect permanent and transitory components of income.

20. EXTENSION OF THE CAMERON AND WORSWICK’S APPROACH Our approach extends the Cameron and Worswick (2003) method including other shocks (not only crop loss) in the estimation of the transitory component What Cameron and Worswick call transitory component captures only certain negative shocks, and the residual includes important income information. Therefore, I prefer not to distinguish between permanent and transitory income, but to decompose income in three components: y1, y2 and y3, where y2 captures negative hardships and y3 is the residual of the income regression, i.e. the non-identified income component.

21. Logit equation: probability that household h uses the mode m to overcome shock s • is the weighted average of households that experienced the shock in a given area, this variable controls for the commonality of shock in the same village • are demographic variables (i.e. sex and education of the household head) • , and are estimates of household income components: permanent component, a component that reflect transitory negative shocks, and the residual component

22. Estimates of income components • Variables used to identify permanent income (X1): - demographic (the number of household members in each age categories, the number of adult members in a number of education/gender categories) - wealth (occupation of the household head, the number of householders that earn a wage, a dummy that identifies if there is a householder who has a non-farm business, the value of land - location dummy (Java-Sumatra or the rest of Indonesia). • Variable used to identify negative transitory component (X2): dummy variables that indicate whether a household experienced a shock in 1992-93 • Some shocks may affect income in a permanent way • death of a householder is included in the estimation of permanent income (y1)

23. INCOME EQUATION RESULTS • Death and unemployment of a householder have a significant effect on income • The dummy if a householder works in a non-farm business is very relevant and significant (nt01), such as the number of household members that earn a wage/salary (N_empl) • Land value is significantly and positively correlated to income • Secondary and higher education play an important role in the income equation, both for male and for female • The coefficients of household head’s employment type strengthen the positive correlation between wages/salaries and income

24. The data we are examining have two important features: • Households have a number of possible ways of responding to shocks (we aggregate to 6 responses). • Multiple responses are possible – responses are non-exclusive Multivariate logit allows modelling of multiple responses, but does not accommodate non- exclusivity.

25. Theoretical model • Households respond in such a way as to minimize the cost of shock adjustment • By analogy with the McFadden random utility model, adjustment shocks chms (for household h adjustment mode m to shock-type s) have a deterministic component fhms and a random component hms where xh is a vector of household h characteristics.

26. Choice of adjustment mode • We first consider the standard multinomial logit case in which choices are exclusive. • Write household h’s response to a shock of type s asrhs and let phms be the probability rhs = m. • Focusing on adjustment mode 1, • Under the standard logit assumption that the stochastic component hms follow an extreme value (Gnedenko) distribution, the probabilities phms are logistic:

27. Non-exclusive responses • We generalize the random adjustment cost framework by introducing a household-specific threshold th = t(xh). • Suppose the cost minimizing adjustment mode is 1. The household reports an adjustment mode set The probability of choosing mode 1 is now Under the standard logit assumptions

28. Shocks and implications forhousehold vulnerability(Future research)

29. SHOCKS AND VULNERABILITY Different measures have different implications for vulnerability, in the sense of increasing the risk of entering poverty when faced with future shocks. Some responses may destroy or reduce the physical, financial, human or social capital of the household more that others (as suggested by Dercon, 2005). Reducing children’s education or health expenditure affects children’s human capital and may worsen the effect of transitory shocks Other measures, such as asset sale, may destroy the household physical capital.Gold, usually in the form of jewellery, is seen as an important way to save money (Frankenberg, Smith and Thomas, 2003) and using it to mitigate transitory shocks reduces the possibility for a household subsequently to overcome long term shocks such as the 1998 financial crisis.

30. The effects of shocks on future vulnerability are relevant in particular for poor households. e.g. the percentage of households that take a loan is higher for the poorest 20% than for the richest 20%, in particular for a death of a householder (this is not true for price falls, probably because in this case poor people do not have collaterals). This may push poor households into a poverty trap.

31. There are three principal approaches to assessing vulnerability (Hoddinott and Quisumbing, 2003): • Vulnerability as expected poverty (VEP) vulnerability=probability that a household will fall into poverty in the future where z is the consumption poverty line

32. Vulnerability as low expcted utility (VEU) vulnerability= the difference between the utility derived from some level of certainty-equivalent consumption, zCE, at and above which the household would not be considered vulnerable, and the expected utility of consumption

33. Vulnerability as uninsured exposure to risk (VER) This approach asses whether observed shocks causes a household to deviate from expected welfare  Estimates the effects of common and idiosyncratic shocks on household consumption net of the mitigating role played by private coping strategies and public responses

34. Shocks and implications for children’s education

35. The effects of shocks on child labour/child education • Do households use child labour as an insurance (by taking child out of school and sending them to work)? • Link between shocks, uncertainty, credit constraints and child labour/child schooling (Beegle, Dehejia and Gatti, 2003; Duryea, Lam and Levison, 2003; Fitzsimons, 2002; Jacoby and Skoufias, 1997;)

36. Child labour as the outcome of an intra-household bargaining process (Basu, 1999) collective models Household allocation decisions are the outcome of a bargaining process between parents or parents and child; there is no income pooling, but householders agree on how to divide the household income according to the individual bargaining power. The only assumption is that outcomes are Pareto efficient.

37. I will outline a simple one period cooperative model to analyse the effect of shocks on household human capital decisions.

38. DATA • taking child out of school as response to a shock • why child has never been to school / stop going to school (help parents earn money, help at home,… ) • child works during the school year / how many hours per week • hours per day/per week spent in school and for studying outside the school For older than 10: • whether they receive a salary/income • what primary work (professional, management, farm-forestry, production line, transportation, blue collar, etc.) & work field

39. HOUSEHOLD DECISION-MAKING (1) Are you free to spend your money for household expenses? Apart from hh exp., can you spend your income without consulting your partner?

40. From a preliminary analysis (probit): • the probability the mother keeps some income depends mainly on household’s wealth (household tot expend.) • the probability the father keeps some income depends on HH wealth, but also on his education (+), and wife’s education (-)

41. HOUSEHOLD DECISION-MAKING (2)