On the other hand, for this sub-sectoral group, the gender wage gap markedly increased, particularly for female workers at the lower end of the distribution. As seen in Figure A.7, the gender gap is actually larger within the low-productivity service sector than in the economy as a whole. Men earn on average 35-45 percent more than women, whereas the gap is 25 percent when looking at the entire economy. Estimating the gender gap across the distribution for this sector shows that women in the lower quantiles received particularly less than their male counterparts in 2012, with a 60 percent wage gap compared to 2007.

The realities of this sector point to the larger issues of Haiti’s labor market and its challenges to become more inclusive and productive. While informality continues to define the lower-productivity jobs, a reduction in the gaps between formal and informal could be encouraging. However, the growing gender gap for poor female workers of this sub-sector testifies to the persisting hurdles that the poor and vulnerable face in getting returns to their labor that will allow them to exit poverty within a reasonable horizon.

# **Box 3 - Making the Most of Existing Data in Haiti: The Way Forward**

Analyzing labor markets in Haiti has obvious limitations due to the paucity of data. The release of the 2012 ECVMAS considerably improved this situation and enabled the definition of a new baseline analysis of labor markets (and poverty) following the 2010 earthquake, and five years after the 2007 EEEI survey.

The recent release of the 2012 survey of Haitian firms opens further possibilities to refine the analysis, particularly through the use of a spatial lens. Both the ECVMAS and the firm census are geo-referenced, which enables expansion of the analysis to take into account the economic and labor context—both formal and informal.<sup>16</sup> This analysis could further be enhanced by including infrastructure data to identify patterns of firm locations, typologies, and synergies (such as sectors, size, status, and agglomeration effect).

Such analysis could also improve understanding of both job creation and self-employment. Regarding the latter, a separate draft (Cuevas and Rodella, 2014) that the authors prepared for the Haiti Systematic Country Diagnostic (SCD) looks into the different types of self-employment (one-person firm, family firm, and micro-enterprise). The draft’s goal is to provide a finer lens on the differences between survival and growth entrepreneurs.

With the caveat that correlations rather than causal relations are being found, the analysis of correlates of successful self-employment uses three measures: revenues per worker (in log), revenues per worker that are in the top 30 of the distribution, and profits per worker that are in the top 30 of the distribution. These help identify the characteristics and inputs that are significantly more relevant for entrepreneurial success. This type of study, combined with evidence-based analysis like the one conducted for the present paper, can help improve understanding of what it will take to elevate productivity and generate jobs in the self-employed and small business sector. The five main findings of the draft’s analysis are:

> 16 Although the coordinates have not been shared at this point and remain with the respective national agencies (IHSI, ONPES, MCI and MEF).

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