# _Box 1: Grouped data poverty estimates_

<mark>Grouped data are consumption expenditure or income organized in intervals or bins, such as deciles or</mark> percentiles. These bins are used to derive a continuous Lorenz curve, which plots the cumulative welfare share (on the y-axis) against the cumulative population share (on the x-axis). Together with information about mean welfare, the Lorenz curve can be used to construct a full distribution. Two approaches are used to derive a Lorenz function, the general quadratic (GQ) Lorenz function and the Beta Lorenz function (Datt 1998). Both functions are parameterized and estimated. The function that provides the best fit is selected for poverty and distributional statistics, conditional on passing normality and validity tests. The GQ Lorenz function is estimated using the following specification: _L_ (1− _L_ )= _a_ ( _p_<sup>_2_</sup> _−L_ )+ _bL_ ( _p_ −1)+ _c_ ( _p−L_ ), where _p_ is the cumulative proportion of the population, L is the cumulative proportion of consumption expenditure or income, and a, b, c are parameter estimates. Poverty and inequality measures are based on the parameter estimates.

The Beta Lorenz function is estimated using the following specification: L(p)=p−θp<sup>γ</sup> (1−p)<sup>δ</sup> , where θ, γ, and δ are parameter estimates.

The methodology to estimate poverty starting from grouped data is applied on grouped data information on per household consumption by decile of the welfare distribution in 2007 and in 2009 HIES available from the CBS website. Information on average household size by decile, which is needed to convert household expenditure in per capita terms, was obtained from Prof. Heba El-Laithy, one of the authors of the Abu-Ismail et al. (2011) study who was in possession of 2007 HIES microdata. Through this consultancy, grouped data poverty estimates for 2007 were compared and validated with estimates based on the full distribution. Lacking information on average household size by decile for 2009, per capita expenditure by decile in 2009 is obtained using 2007 estimates. _Source_ : <u>Poverty and Inequality Platform Methodology Handbook</u> Table 2 below reports grouped data estimates of poverty incidence at different values of international poverty lines for 2007 and for 2009. Based on grouped-data estimation approach, in 2009, the latest year for which data are available before conflict started, Syria’s poverty at LMIC was 14.50 percent using 2011 PPP and 16.02 percent using 2017 PPP, whereas corresponding estimates based on the UMIC poverty line were 40.29 percent (2011 PPP) and 47.52 percent (2017 PPP). When comparing to 2007 group-based estimates, evidence suggests that poverty had stagnated, possibly reflecting the impact of the drought that affected the country over the period.

_Table 2: Poverty estimates using income class international poverty lines_

||||**Pover**|**ty Rate (%)**<br>||
|---|---|---|---|---|---|
||||**Estimates based on microdata**|**Estimates based**|**on grouped-data**|
||**PPP**|**PL value**|**2003**|**2007**|**2009**|
|**LIC**|2011|1.9|0.79|2.43|2.08|
||2017|2.15|0.93|2.83|2.44|
|**LMIC**|2011|3.2|9.48|14.90|14.50|
||2017|3.65|10.89|16.36|16.02|
|**UMIC**|2011|5.5|38.37|39.47|40.29|
||2017|6.85|47.26|46.43|47.52|

_Source:_ World Bank staff estimates