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The Effects of Emergency Housing on Wellbeing: Evidence from Argentina’s Informal Settlements

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Abstract

The aim of this paper is to present evidence on the effects on wellbeing of providing a basic dwelling on-site to households living in situations of extreme poverty in urban slums. In particular, the paper evaluates the impact of the NGO TECHO’s emergency housing programme in informal settlements of Buenos Aires, Argentina. Using a quasi-experimental pipeline approach, the paper shows that the programme has a large effect on privacy, security, interpersonal relations, psychological wellbeing and perception of quality of life. Regarding health, the program only produces a reduction in the prevalence of cough and congestion. While indicators of sleep quality improve, the effects are not statistically significant after adjusting for multiple hypothesis testing. Additionally, the programme increases the likelihood that households with school age children have a tranquil place to study, evidence that the programme could broaden children’s long-term opportunities.

Résumé

Le but de cet article est d’analyser les effets sur le bien-être des personnes d’un programme de construction de logements de base pour des familles qui vivent en situations d'extrême pauvreté dans les bidonvilles. L’article évalue en particulier l’impact du programme de logements d’urgence de l’ONG TECHO dans les quartiers informels de Buenos Aires en Argentine. En utilisant une approche de pipeline quasi expérimentale, l’article montre que le programme a un effet important sur le privé, la sécurité, les relations interpersonnelles, le bien-être psychologique et la perception de la qualité de vie. En ce qui concerne la santé, le programme ne fait que réduire la prévalence de la toux et de la congestion. Bien que les indicateurs de la qualité du sommeil s'améliorent, les effets ne sont pas statistiquement significatifs après ajustement pour les tests d'hypothèses multiples. De plus, le programme augmente la probabilité que les familles avec des enfants d’âge scolaire aient un endroit tranquille pour étudier, preuve que le programme pourrait élargir les possibilités à long terme des enfants.

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Fig. 1

Source TECHO Argentina

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Notes

  1. The informal settlements included in this study satisfy the operational definition employed by TECHO: neighbourhoods with at least eight families in which at least half of the households do not have a formal land title nor formal access to at least two basic services (water, sanitation and electricity) (TECHO 2013).

  2. While all of the households that were selected for the program chose to participate, a few households did not receive the dwelling due to lack of compliance with the contract’s conditions.

  3. Poverty estimates are based on the poverty and indigence lines set by Salvia (2014, p. 40).

  4. Some studies have shown positive effects of density on wellbeing. Regoeczi (2002), however, demonstrated that the apparent inconsistency in the literature is due to threshold effects. While negative behaviour may initially diminish with reductions in available space, once a critical threshold is reached, these problems increase exponentially with density.

  5. The decision to prioritize objective indicators was motivated by the evidence that prolonged periods of deprivation can distort perceptions of wellbeing—what Sen (1985) refers to as ‘adaptive preferences’—and that people tend to compare their living conditions with those of people living within their geographic or social proximity, rather than with society as a whole (Cruces et al. 2013). Another argument for focusing on objective over subjective indicators was to minimize the potential problem of confirmation or ‘social desirability’ bias (Kahneman 2011) stemming from the participation of TECHO volunteers in the survey field work.

  6. A total of 20 households were divided during the year after receiving the TECHO house. In these cases, we applied the follow-up survey separately to each household in order to collect accurate information on all members, but measured the combined effect on both households taken together. Footnote 16 presents the results of a robustness test excluding these 20 households.

  7. The respondent was the person who was considered to spend the most time in the home and was best able to provide information on all members. In most cases, the respondent was the mother of the principal nuclear family.

  8. Due to the continuous expansion of Greater Buenos Aires, all of the settlements included in the survey form part of the same urban area that extends from Pilar in the north to La Matanza in the west and to Greater La Plata in the south.

  9. The normalized difference is defined as: \(\frac{{\left( {\bar{X}_{\text{T}} - \bar{X}_{\text{C}} } \right)}}{{\sqrt {(S_{{{\text{X}},{\text{T}} }}^{2} + S_{{{\text{X}},{\text{C}}}}^{2} )/2} }}\),where \(\bar{X}_{\text{T}}\) and \(\bar{X}_{\text{C}}\) are, respectively, the treatment and control group means and \(S_{{{\text{X}},{\text{T}}}}^{2}\)and \(S_{{{\text{X}},{\text{C}} }}^{2}\) the treatment and control group variances of the covariates. Imbens and Wooldridge (2009) indicate that, when the values of the normalized differences are greater than 0.25—two and a half times greater than the highest value for any of our indicators—,then one should be cautious about measuring treatment effects using a linear regression with a dummy variable for treatment.

  10. To apply the Holm procedure, one first orders the family of p values i from smallest to largest and then sequentially rejects each hypothesis as long as the p value \(< \alpha_{i} = \alpha /(s - i + 1).\)

  11. In order to obtain a unit of analysis that would permit comparisons across households that use the TECHO house in different ways, each dummy variable describing the quality of the dwelling was used to construct a new indicator referring to the fraction of rooms with each characteristic.

  12. All security indicators refer to the security of the TECHO house, except for the respondent’s perception of security which refers to the dwelling in which the respondent sleeps and robbery, which refers to robbery in either the TECHO house or other dwellings.

  13. Fires are common in the settlements and there is no evidence that the incidence of fires is higher among programme participants than in the overall population in the settlements.

  14. When both the higher and lower bound coefficient estimates are statistically significant and the same sign, there is no way that the ‘lost’ cases could have changed the results enough for the true effect to be zero. If the two regressions have different signs, they include the zero in the interval, and it is possible for the true effect to be zero. If the two regressions have the same sign, but only one is statistically significant, one of the bounds includes the zero in its confidence interval and thus we cannot be sure that attrition did not lead us to conclude there was an effect when there really was none.

  15. As the distribution of the number of treatment and control households drawn from each neighbourhood showed that there was a negative correlation in the quantity of households surveyed in each neighbourhood between the two periods, we also applied the following test. We obtained two additional sets of impact estimates: one in which we included only those neighbourhoods with more treatment than control households and another with the neighbourhoods with more control than treatment households. However, a comparison of the results did not show any clear pattern. For some variables, the coefficient increases and for others the coefficient declines, suggesting that the sequential process of selecting treatment and control households did not lead to the selection of relatively more (or less) needy households for the control group.

  16. Additionally, in order to assess how changes in the respondent (16 cases) and the division of households (20 cases) between the baseline and follow-up surveys could be affecting our results, we re-estimated the pipeline regression model excluding these 36 cases. As a result of this change, the effects were virtually unaltered in terms of economic or statistical significance.

  17. In a final robustness test, we re-estimated the pipeline regression using contemporaneous instead of pre-treatment values for the control variables. The results show that using contemporaneous controls causes seven outcome variables that were previously not statistically significant to become significant, whereas none of the outcome variables loses statistical significance, suggesting that the use of pre-treatment values for the control variables clearly does not result in the overestimation of impact.

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Acknowledgements

The authors would like to thank the following people for their valuable comments: María Laura Alzua, Roger Betancourt, James Copestake, Osvaldo Feinstein, Cythia Goytia, Patricio Millán, Ricardo Perez Truglia, Mariano Rabassa and two anonymous referees. We also thank Paula Araujo for providing excellent research assistance.

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Authors and Affiliations

  1. Department of Economics, Pontificia Universidad Católica Argentina, Av. Alicia Moreau de Justo 1400, 4º Piso, Oficina 468, C1107AAZ, Ciudad de Buenos Aires, Argentina

    Ann Mitchell & Jimena Macció

  2. Department of Economics, Universidad de San Andres, Vito Dumas 284, B1644BID, Victoria, Pcia de Buenos Aires, Argentina

    Diego Mariño Fages

  3. Department of Economics, Universidad Nacional del Nordeste, Av. Las Heras 727, 3500, Resistencia, Chaco, Argentina

    Diego Mariño Fages

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  1. Ann Mitchell
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  3. Diego Mariño Fages
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Correspondence to Ann Mitchell.

Appendix

Appendix

See Table 3.

Table 3 Robustness tests on the treatment effect of the TECHO house
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Mitchell, A., Macció, J. & Mariño Fages, D. The Effects of Emergency Housing on Wellbeing: Evidence from Argentina’s Informal Settlements. Eur J Dev Res 31, 504–529 (2019). https://doi.org/10.1057/s41287-018-0166-z

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