“Territorial dynamic and wellness”

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Previous work (Pérez and Soloaga, 2016) applied Lanjouw, Luoto and Mckenzie’s (2014) methodology to estimate movements out or into poverty in Mexico during 2006-2010. This allowed to evaluate poverty and vulnerability dynamics, and to identify main factors that were correlated to the different households’ trajectories. Through the application of transition analysis for years 2006-2010, the paper found that between 27%and el 32% of the Mexican population could be considered as chronically poor (Tpp), and that between 42%and 47% could be considered as sustainable not poor (Tnn). In turn, between 12% and 15% could be considered in a downward mobility (Tnp) phase (that is, entering poverty), and between 10% and 12% could be considered inan upward mobility (Tpn), (leaving poverty). Populations in Tpp and Tnp status were mostly characterized by their lacking of access to health, to social security, and food on a regular basis. All of these seemed to imply that it was vulnerability to idiosyncratic or systemic crisis what keep them in a low well-being situation. Although it is well known that in addition to the official safety nets (e.g., social security, health services), Social Capital is a powerful factor that could counteract or reinforce the trends described above (Abbafati, Soloaga and van Gameren, 2013, López-Rodríguez and Soloaga,2012 and 2014), there is no research that measures the importance of Social Capital on poverty transitions. This is in part due to lack of data. Nonetheless, since 2010 the Mexican Statistical Office (INEGI, by its acronym in English) began publishing good quality data on households´ networks and also on time-use in a special section contained in the household survey that is used to calculate the official poverty figures (Módulo de CondicionesSocioeconómicas MCS, in Spanish) . Moreover, a new data at the level of locality with detailed information on about 36,000 Organizations from the Social Sector (Organizaciones de la Sociedad Civil, in Spanish) were made available by the Mexican Institute for the Social Sector (INDESOL http://indesol.gob.mx). Research done jointly with Professor Isidro Soloaga during June-July 2016 explored the suitability of these new data sets to extend the previous analysis on poverty and vulnerability dynamics in such a way that measurements of Social Capital could also be included. With that purpose, we explored the data bases for years 2010, 2012, and 2014, and made a first selection of what variables in addition to those used in Pérez and Soloaga (2014) could be included in the analysis. The key issue to solve is how to construct good measures of Social Capital. Preliminary work shows that network variables from MCS module can be aggregated into one single indicator (in most years they have a unique principal component) for each household. Households´ time-use as well as the information on whether they give or receive help to/from friends and relatives seem to provide additional useful information. In turn, data for the Social Sector provided a rich detail to characterize the working of the social sector at the municipality level (e.g., goals and composition of the organizations). The work ahead is to run regressions and make an assessment on whether Social Capital (proxied by networks, time-use, goods-sharing and the presence of organizations from the civil society) provides additional evidence to understand households´ poverty and vulnerability dynamics.