Fostering social mobility. The case of the Bono de Desarrollo Humano in Ecuador

ABSTRACT

Social protection programmes are now expanded due to their efficacy in reducing poverty and vulnerability. However, the literature is scarce regarding long-term effects. Using administrative panel data, this study analyses social mobility in Ecuador and evaluates the effect of the social transfer programme Bono de Desarrollo Humano (BDH). Results show that social policies should focus on household composition, the accumulation of human capital, and the accumulation of durable goods. Complementary policies must address gender and ethnic equity, as well as reproductive health. Finally, we find that the BDH does foster social mobility, especially if the transfer is complemented with economic inclusion programmes.

KEYWORDS:

• Social mobility
• social transfers
• human development
• poverty and inequality

Acknowledgments

We are grateful to the Ecuadorian Coordination Ministry of Social Development (Ministerio Coordinador de Desarrollo Social, MCDS) for providing access to the data set, especially to Cecilia Vaca and Reinaldo Cervantes. Previous versions benefitted from comments from Cathal O’Donoghue and Andrea Franco, and participants of the III Latin-American and Caribbean Congress of Social Sciences in Quito, and the 2015 HDCA Annual Conference “Capabilities on the move: Mobility and aspiration” in Washington D.C. All remaining errors and omissions are those of the authors.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. For surveys of empirical evidence see Handa and Davis (2006), Barrientos and Scott (2008), Barrientos and Niño-Zarazúa (2010), Arnold, Conway, and Greenslade (2011), IEG (2011), Barrientos (2012), UNICEF (2012), Alderman and Yemtsov (2012), Mideros, Gassmann, and Mohnen (2012), Tirivayi, Knowles, and Davis (2013), World Bank (2015), Bastagli et al. (2016).

2. For a discussion on chronic poverty see for example Jalan and Ravallion (2000), Hulme, Moore, and Shepherd (2001) and Hulme and Shepherd (2003). For a link between upward social mobility and overcoming chronic poverty see for example Carter and Barrett (2006).

3. The human development paradigm provides a people’s centred focus of development, based on the capability approach (Robeyns 2005). In this perspective development is about expanding capabilities, choices and agency of all people (Funkada-Parr 2003).

4. For a recent discussion of poverty traps and the role of the aid transfers at the macro level see Meysonnat, Muysken, and Van Zoon (2015).

5. For seminal literature on the role of human capital and intergenerational mobility see Becker and Tomes (1986, 1994). For the importance of early child conditions on social mobility see Heckman and Mosso (2014).

6. In most developing countries large labour market gender inequalities exist against women, reducing the returns of their labour participation. In addition, authors like Molyneux (2009) argue that conditional cash transfers may entrap women in patriarchal gender roles.

7. Own estimations based on official data show that on average the BDH reflects at USD 15 7% (12%) of the income (extreme) poverty line; at USD 30-35 12% (22%), and at USD 50 15% (27%).

8. The variables used to calculate the RS index are presented in Annexe 1.

9. According to the population census of 2010, Ecuador has 3.8 million households with a total population of 14.5 million inhabitants.

10. For a discussion on social mobility indexes see Cowell and Schluter (1998) and Jäntti and Jenkins (2015).

11. It is important to note that the mobility index is equal to one minus the rigidity index used by Woolard and Klasen (2005). The formula for the Shorrock’s mobility index is then $1-\left\{G_{\left(x+y\right)}/\left[\left({\mu }_x{G}_x+{\mu }_y{G}_y\right)/\left({\mu }_x+{\mu }_y\right)\right]\right\}$, where $x$ and $y$ are periods, ${\mu }_t$ the mean welfare value at period $t$, and $G_t$ the Gini index for period $t$.

12. Total mobility is measured as $\frac{1}{n}\sum _{j=1}^n\left|x_j-y_j\right|$ while positive mobility is calculated by $\frac{1}{n}\sum _{j=1}^n\left(x_j-y_j\right)$.

13. Current GNI per-capita, by the Atlas method, was USD 6,010 in 2015 (World Bank 2016).

14. Gini coefficient was 45.4 in 2014 (World Bank 2016).

15. We use median schooling as a proxy of a household’s productivity level.

16. Durables are included as proxy of physical capital. However, as they are also part of the RS index we test for collinearity using variance inflation factors.

17. While the inclusion of other variables can be debated, we are constrained by those variables available in the RS.

18. Montubios are peasant populations along the coast.

19. Not presented here, but available upon request from the authors.

20. We use the enlarged panel for comparative purposes. On top of the 413,043 households from the original panel, it includes another 845,419 households (in RS 2009 and RS 2014, but not in RS 2003).

Additional information

Notes on contributors

Andrés Mideros

Andrés Mideros Mora (PhD in Economics) is Dean of the Faculty of Economics and Director of the Economic Research Institute at the Pontifical Catholic University of Ecuador. His own research studies social protection policies, poverty and inequality, and economic policy exploiting quantitative methods. Currently, the focus of her research is on understanding investments in social protection in low and middle-income countries, and the relation between social protection and labour market participation.

Franziska Gassmann

Franziska Gassmann (PhD in Economics) is Professor of Social Protection and Development at Maastricht University and Professor Poverty and Social Protection at Bonn-Rhein-Sieg University of Applied Science. At UNU-MERIT, she is leading the research theme on Social Protection, Inclusive Innovation and Development. Her own research studies social protection policies and the measurement of poverty and vulnerability using primarily empirical methods on the basis of large household surveys.