generated. These simulations assume homogeneous expenditure shocks across households, such that the degree of vulnerability to economic shocks is assumed to be constant in a population.

Table 8 shows the results for poverty headcount projections based on the elasticity approach. We produce two sets of estimates, one assuming full pass-through, and another assuming a growth elasticity of consumption equal to 0.33, which is the coefficient estimate from the regression of the logarithm of consumption on the logarithm of GDP for the time period 2003-2010, for which HBS data are available. Starting from the expenditure data in HBS 2010, with its associated poverty headcount of 9.2%, the model that relies on the full pass-through from GDP to consumption predicts a poverty rate of 8.3% in 2011, while the prediction based on the partial pass-through is 8.8%. In both cases, the lower poverty headcount in 2011 is due to the positive GDP growth between 2010 and 2011.

The key difference between the elasticity-based projections and the microsimulation-based projections is that the latter takes explicit account of the continued deterioration of the labor market conditions between 2010 and 2011, including falling employment and activity rates, and rapidly increasing unemployment rate. Thus, the improvements in household income as a consequence of the recovery process of the economy are compensated with increases in unemployment and inactivity rates, resulting in a higher predicted poverty headcount compared with the elasticity approach.

# _4.2 Distributional predictions_

One further advantage of the microsimulation approach over the elasticity approach is the possibility of fully taking into account the heterogeneity of individuals observed in the household survey. By generating predicted levels of income and consumption for all households in 2011, the simulation model allows the type of households that are likely to be affected by the macroeconomic context, the primary channels of impact and their relative importance, and the distribution of the impact across different welfare groups. We present two types of analysis: firstly, we examine the characteristic of the group called “New Poor”, which refers to those households that are not poor in 2010 but would have been in 2011 as consequence of the macroeconomic context. We also compare this group with “Old-Poor” or those who remain poor over time and the “Non-Poor” or those who are not poor in either year. Secondly, we use the growth incidence curves to see how changes in welfare are distributed across consumption groups and between areas.

# _4.2.1 A profile of the “New-Poor”_

Households that are expected to be in poverty in 2011 but were above the poverty line in 2010, termed as “New-Poor” are projected to suffer larger income losses – with more than 70% drop in average of household income (Figure 1). Most of this loss is due to a massive decrease in their labor income. Reductions in international remittances are almost negligible as a component of the overall income loss.

The characteristics of the New-Poor, relative to the rest of the population, are as follows (Figure 2). These households are slightly more rural (44% as compared to non-poor 39%) and fewer of them are headed by women compared to other groups (19% compared to 31% for non-poor). More than 50% of their household heads have less than 55 years of age and their levels of education are very similar to those of the non-poor households (albeit with a smaller share of post-secondary education).

The reason of their deterioration in social status would be explained by their change in labor status. In 2010 almost 70% of these household heads were employed -- mainly in services and almost equally distributed in industry and agriculture (Figure 2). However, the simulation in 2011 predicted that around 88% of them would be unemployed or inactive. The “New-Poor” households are different in a number of key aspects from the more permanently poor. Compared to the “Old-poor”, they have “better” characteristics such as higher skills levels, living in urban areas, younger and employed in services.

# _4.2.2 Distributional changes of welfare_

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