population is being questioned. Recent research is increasingly showing that an economy could grow for sustained periods of time, while leaving large sections of its population behind and sometimes even worse off. Policies to ensure more inclusiveness are hence needed.

The main aim of this paper was to provide an informed assessment of how to prioritize policies in a low-income country with sparse micro data, putting special emphasis on income growth for lower-income households. Drawing on the growing availability of standardized country data on income distribution, this paper examined the drivers of the income of the two poorest quintiles for a sample of 117 countries between 1967 and 2011.

The results suggest that maintaining macroeconomic stability as well as investing in human and physical capital would not only accelerate overall economic growth, but benefit more particularly the poorest segments of the population. This paper shows that there thus need not be a trade-off between inequality and growth: the overall pie can grow larger as well as the slice allocated to the poorest households, all with the same set of policies. Governments can foster faster economic growth while at the same time increasing inclusiveness, ensuring that everyone can live up to their potential.

While our results, derived from a simple cross-country analysis, have limitations, we see our approach as a starting point to identify and prioritize broad policy areas. Financial development, for instance, is a complex process. The literature has been ambiguous about the channels through which finance may be associated with lower poverty (deposits or credit). Measuring credit to the private sector may be thus a too crude indicator and a finer analysis would be called for as alternative financial indicators become available for longer time periods.

Our analysis cannot substitute either for country-specific considerations and studies. It offers nevertheless some guidance where additional evidence could be most helpful when existing data and micro-evidence are scarce. Neither does our methodology provide any guidelines which specific policies should be implemented to make progress in certain policy dimensions. Furthermore, large gaps do not automatically imply that they are quickly or cheaply closed either.<sup>19</sup> However, by taking into account historical progress in comparable countries with respect to the identified policy gaps, our benchmarking approach allows to find reference countries that made considerable progress from similar starting points. Further work to refine the analysis provided in this paper could thus include case studies of countries where improvements in critical areas have taken place and might provide more concrete policy guidance.

> 19 One would expect that it is easier to improve life expectancy by 5 years when starting at an initial level of 40 years than at 70 years, that it is easier to bring down inflation from 12 to 10 percent than from 7 to 5 percent or to improve the school enrollment rate from 20 to 30 than from 85 to 95 percent. However, this does not mean that large gaps automatically translate into fast progress in terms of our policy proxy variables nor whether they would be the best use of public money. For example, it took Ecuador two decades to improve its life expectancy from 62 years (Haiti’s current level) to the current average of the reference group (74 years). For Dominican Republic and Belize it took almost four or five decades, respectively.

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