Leonardo Becchetti Stefano Castriota

1. Fall and recovery. Disruption and catching up effects after tsunami on a sample of MFI borrowers_________________________________________________ Leonardo Becchetti Stefano Castriota

2. Sri Lanka and the 2004 tsunami_____________________________________________ • Over 1,000 kilometers coast hit by the wave: two thirds of the country’s coastline • Huge human losses: over 35,000 dead and 443,000 displaced people • Huge economic damages: 24,000 boats, 11,000 businesses and 88,500 houses damaged or destroyed • Several international organizations and NGOs provided help and support

3. Characteristics of the research_____________________________________________ • Field research in Sri Lanka conducted in April 2007 • Research support provided by the Italian Civil Protection, ETIMOS (Italian NGO) and Agro Micro Finance (Sri Lankan MFI) • 305 Sinhalese people interviewed, all clients of AMF before and after the tsunami • Two randomly selected groups: 200 damaged (treatment) and 105 non-damaged (control) • Our study can be assimilated to a “(quasi) natural experiment”

4. Targets of the paper_____________________________________________ • Analyze the behavior of the economic and psychological wellbeing indicators over time • Evaluate the psychological reaction of neighboring non-damaged people after the shock • Test the existence of convergence and/or full recovery in material and psychological variables after the MFI refinancing • Evaluate on the whole the importance of microcredit as recovery tool after natural disasters like a tsunami

5. Agromart Foundation and Agro Micro Finance_____________________________________________ • Agromart Foundation is a Sri Lankan NGO founded in 1989 to carry out grassroots work with a large number of communities in Sri Lanka • The Head Office is located in Colombo with nine other provincial offices in Uva, the Southern, North Western and Eastern provinces • The core of its mission is strengthening the competencies of its members through participatory trainings • In 1994 the Foundation broadened its activity by working as a microcredit institution for its clients, but in 2000 it decided to fund Agro Micro Finance (AMF) and to delegate this task to it • AMF lends only to members of community based organizations which received for at least six months self-employment, entrepreneur development and literacy trainings from the Agromart Foundation • 72 % of AMF borrowers are women. In March 2005 the MFI’s loan portfolio was of 295.000 €

6. AMF and the tsunami_____________________________________________ • Certified direct and indirect losses on 620 clients in the districts of Galle, Matara and Hambantota • The estimated corresponding financial needs to cover such losses amounted to 72,600 €, that is, almost 24.4 % of the MFI loan portfolio • Foreign intervention was very important to avoid the MFI financial distress and the consequent restriction to credit access for the MFI borrowers • The liquidity provided by foreign institutions allowed AMF to avoid credit restrictions to non-damaged clients necessary to finance damaged clients • Support to AMF refinancing needs came from USAID, UNDP and an Italian MFI (Etimos)

7. Organization of the questionnaire_____________________________________________ • 305 people randomly selected from the database of AMF clients • More damaged people (200) than non-damaged (105) in order to distinguish the effect of different damage types • Clients interviewed face to face by one of the authors (Stefano Castriota) and two more researchers • Questionnaire translated in Sinhalese by three professional translators with economic degree • Interviews carried on in the monthly society meetings, at the clients’ homes or in extra-meetings arranged for this purpose by AMF

8. Backcast (or retrospective) panel data approach_____________________________________________ • Well-established methodology (e.g. McIntosh, Villaran and Wydick, 2007) • Respondents are asked to declare the current and remember the past wellbeing levels by making reference to several different periods • One unique questionnaire/cross-section allows to create a panel • This allows to reconstruct the path of economic and psychological wellbeing indicators over time

9. Our backcast panel: four time windows_____________________________________________ • The six month interval before the first microfinance loan ever obtained • The period going from the first microfinance loan to the tsunami date (26th of December 2004) • The period between the tsunami date and the first microfinance loan after tsunami • The period from the first microfinance loan after tsunami to the survey date (April 2007)

10. Advantages and disadvantages of this approach_____________________________________________ Advantages • It is a cheaper approach (only one survey instead of several) • It allows analyses otherwise impossible to do (the tsunami was unexp., we cannot go back to pre-tsunami period and interview people) Disadvantages • Problem: time windows are irregularly spaced Solutions: (i) differences are not big and (ii) we insert the time windows length in the regression analysis as a control • Problem: memories can be imprecise, especially if people are asked to remember events far away in time Solution: we rely on memorable events

12. Questions in the survey_____________________________________________ • Socio-demographic variables: distance from the sea, province of residence, age, sex, marital status, education, employment status, sector of activity, number of people living at home and number of children • Economic variables: real income in April 2007 Rps., self-declared level of standard of living, probability in having problems in providing daily meals, ownership of transportation means, number of hours worked, average savings • Loans: amount of money loaned by the MFI (from bank records), existence of other loans provided by banks, organizations, family members or friends • Psychological variables: self-declared levels of happiness, life satisfaction, self-esteem, trust and health • Damages from the tsunami: to family members, house, financial wealth or economic activities • Post-tsunami aid: support from governmental and international organizations, NGOs etc.

13. Description of the socio-demographic variables

14. Description of the economic variables

15. Ex-ante differences between treatment and control group_____________________________________________ • All socio-demographic, economic and psychological characteristics are not statistically different between the two groups at 5% level • Average age, share of female clients, education, income, standard of living, life satisfaction, self-esteem and average MFI loans are similar • The only variables which differ are obviously the geographic position and the sector of activity • People hit by the tsunami (treatment) live closer to the coast and are less involved in agricultural activities

16. Summary statistics of selected indicators over the four time windows_____________________________________________ • Half the sample lives close to the sea (max 1 km) • Most of clients are female, mid-age, married, self-employed and have a relatively low education level and five people currently living at home • Psychological wellbeing indicators are good, especially if one thinks that the real per capita income in international terms is low • Half the people in the sample had at least one type of damage from the tsunami • A substantial share of clients received subsidies, donations and grants after the catastrophe

17. Summary statistics of selected variables(1)

18. Summary statistics of selected variables (2)

19. Changes over time of mean of selected indicators_____________________________________________ • Amelioration in several economic and psychological wellbeing indicators from P1 to P2 • Fall in wellbeing indicators from P2 to P3 (tsunami effect) • Improvement from P3 to P4 (after the tsunami) • Strong negative tsunami effect on damaged people, almost no effect on non-damaged people • No evidence of “solidarity effect”, contrary to the findings by Kimball et al. (2006) with the hurricane Katrina • Probably due to the longer time window (average length of P3 is 10.5 versus two-three weeks in Kimball et al., 2006), although in our case damaged and non damaged people live very close each other

20. Changes over time of mean of selected indicators, full sample

21. Changes of mean of selected indicators, only no damaged

22. Changes over time of mean of selected indicators, only damaged

23. Some considerations_____________________________________________ • Psychological wellbeing indicators in P4 are similar or even higher than in P2 for all groups • Economic indicators are higher in P4 than in P2 only for non-damaged people. Damaged people did not fully recover yet (more work and lower income) • While the worsening situation from P2 to P3 is obviously due to the tsunami... • ... the improvements from P1 to P2 and from P3 to P4 can be due both to the effect of microcredit and to the improvements in the general macroeconomic situation • Testing the relevance of microcredit for wellbeing improvements and recovery is only possible by use of econometric analyses

24. Magnitude of the tsunami effects (change/ s.d. of the first difference in the previous period)

25. Cumulative distribution function_____________________________________________ • The CDF is important because it allows to examine not just average values but also the dynamics of the entire distribution of selected well being indicators across the four time intervals • Downward shift of the cumulative distribution of real household income, life satisfaction and self esteem in the third period for the whole sample and the subsample of the most damaged people • Clear stochastic dominance of values in P1, P2 and P4 with respect to the tsunami period (P3) • The dominance is more severe for the weakest part of the population (left wing part of the distribution)

27. Cumulative distribution function of real income_____________________________________________

28. Cumulative distribution function of life satisfaction_____________________________________________

29. Cumulative distribution function of self-esteem_____________________________________________

30. Catching up of damaged with respect to non damaged____________________________________________________ • We tests period by period the difference in the mean of wellbeing indicators between damaged and non-damaged respondents • This is done to verify whether the two groups were significantly different before and after the tsunami and whether there has been a perfect catch up in the fourth period • All the indicators were not significantly different among the two groups at 5 % level before the tsunami (P1 and P2) • In the third period all the means become strongly different (tsunami effect) • In the fourth period there is a partial convergence of damaged people to the levels of non-damaged ones: partial but still incomplete catch up

31. Difference in mean of selected indicators between damaged and non-damaged people

32. Effect of MFI loans on wellbeing indicators_____________________________________________ • Higher real income increase if the initial income is lower and people receive higher loans compared to their initial income • Microcredit has a positive direct effect on real income and an indirect positive effect on psychological wellbeing through income • No clear direct effect of microcredit on psychological wellbeing: no evidence of positive effects of society meetings etc. • The limited sample of 305 individuals might be partly responsible for it. However, money seems to be much more important for psychological wellbeing

33. Econometric analysis_____________________________________________ • Four different econometric methodologies adopted: OLS, ordered logit, treatment approach and seemingly unrelated regression (SUR) • OLS is adopted for continuous variables like real income • Ordered logit is adopted for discrete variables like happiness • The treatment approach is used to control for the selection effects of location on the coast and agricultural activity • SUR is used to control for contemporaneous effects of the variables in the equations • All regressions control for locality, socio-demographic and economic determinants and make use of robust standard errors

34. Effect of the first MFI loan on ΔRealIncome

35. Effect of the first MFI loan on ΔStandLiv

36. Effect of the first MFI loan on ΔHappiness

37. Effect of the tsunami on ΔRealIncome (*)

38. Effect of tsunami on ΔStandard of Living

39. Effect of tsunami on ΔHappiness_____________________________________________

40. Effect of MFI loans after tsunami on ΔRealIncome

41. Effect of MFI loans after tsunami on ΔStand.liv.

42. Effect of MFI loans after tsunami on ΔHappiness

43. Damage Regione del paese Family status Job status gender Age Change in income after refinancing Caching up or convergence in the considered wellbeing indicator Damage entity post-tsunami microfinance loan over post tsunami real income Damage entity Length of MFI/customer relationship Lagged income The pattern of post-tsunami catching up

44. SUR for the second time window (P2)

45. SUR for the fourth time window (P4)Δ Life Satisf. Δ Real Income Relative Loan

46. Conclusions_____________________________________________ • Improvement of wellbeing indicators in P2, strong deterioration in P3 and process of (incomplete) recovery and convergence in P4 • Psychological wellbeing displays bigger fluctuations than material wellbeing • No evidence of “solidarity effect”, contrary to what found with the hurricane Katrina (longer length of the time windows) • Impressive speed of recovery even if, given the short time since the natural catastrophe occurred, convergence and recovery are not complete yet • Positive direct contribution of microcredit on the growth rate of real income and an indirect effect (through income) to the other material and psychological wellbeing indicators • The same positive effects are not found for governmental subsidies, donations and grants