employment covariates<sup>55</sup> obtained from the RIF regressions for each sector and at each percentile of the population income distribution<sup>5657</sup> . Figure 4 reveals that the returns to finance, real estate, mining, and family services sectors, in terms of per capita real consumption, have been positive and statistically significant across most of the quantiles. This points to an increase in household welfare generated by employment in these sectors across the whole population distribution and throughout the decade. Out of these four sectors only the real estate sector had an impact that was lower in magnitude for 2010 compared to 2002.

However, the above pattern is not upheld when examining the other sectors. The plots in Figure 4 reveal diminishing welfare returns of all other sectors with the impact turning negative in upper quantiles<sup>58</sup> . Therefore, employment generated by these economic sectors has thoroughly reduced inequality in both 2002 and 2010. In particular, manufacturing and construction sectors contributed positively to the welfare of the poor and therefore reduced inequality at the lower tale of the distribution (up to the 20<sup>th</sup> percentile). Furthermore, the positive welfare returns from trade, tourism, and transport & telecom casted a wider net including the poor and lower middle class as it was depicted for households up to the 40<sup>th</sup> percentile.

Similar results were found for education and defense, two sectors that are largely dominated by the public sector. This reflects the magnitude of the employment created in those sectors along with the increase in wages and social benefits provided to civil servants and military personnel over the past decade in Jordan. The above described pattern is upheld in 2002 and 2010<sup>59</sup> , suggesting little changes in the structure of these economic activities. On the other hand, this harmonized pattern is not depicted for the agriculture sector. While welfare returns to the agriculture sector employment have been somehow flat across quantiles in 2002, Figure 4 reveals a U-shape plot in 2010 that is skewed towards the upper ends of the distribution. Thus,

> 55 More precisely these variables reflect whether the household has a at least one member working in a determined sector (education, defense, transport, tourism etc...). The sectors selected are similar to the ones provided officially by the department of statistics in the national accounts’ value added breakdown of GDP.

> 56 As a reminder, the paper uses household per capita expenditure to proxy the income distribution of the Jordanian population.

> 57 The coefficients estimates themselves can be found in Table 9.

> 58 The results on the upper percentiles should be taken with caution. Indeed, as most household surveys, the Jordan HIES have low reporting on expenditure data for richer segments of the population especially those at the upper end of the population income distribution. Therefore the sample distribution might have a bias by design of the survey where the rich are under-represented. However, the paper is forced to work with these constraints as no further data on these households is available to the authors.

> 59 The magnitude of the impact is more strongly observed in 2010 though.

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