While not explicitly stated, these methods include underlying assumptions on the constant distribution of labor across sectors and no relative wage changes. Moreover, the formulation of these models does not lend itself to modeling specific country-specific conditions in households' income-generating functions, such as changes in remittance flows or social transfers.

We compare the nowcasted and forecasted poverty rates obtained through different methods incorporating headline inflation. Table 4 presents the results for a range of models: PGE,<sup>15</sup> NGD, and NGD with a pass-through rate of 0.86, QGC, and sectoral models. Overall, we observe that, regardless of the method used, the poverty rate increases for FY20, attributed to lower growth caused by COVID-19. Thereafter, poverty consistently declines until FY23, when this trend is reversed. For FY24 and FY25, the last two years forecasted, poverty goes down following the projected economic recovery. The poverty levels in FY25 differ across methods as they accumulate differences across the years, meaning that the size of the prediction divergence increases with the length of the time used.

**Table 4: Comparison of Projected Poverty Estimates through Different Methods**

|**Methods**|FY19|FY20|FY21|FY22|FY23|FY24|FY25|
|---|---|---|---|---|---|---|---|
|Preferred specification: equation (1)||24.6|20.8|17.1|22.2|20.8|18.9|
|Poverty Growth Elasticity||22.5|21.6|20.7|21.2|21.3|21.3|
|Neutral distribution (0.86 passthrough)||24.3|20.7|16.8|20.5|16.0|13.9|
|Democratic|21.9|23.9|20.9|17.8|19.9|20.3|20.1|
|Plutocratic||24.1|21.0|17.9|19.80|20.2|20.2|
|3-Sectors||24.7|20.8|16.7|21.2|17.6|15.7|
|11-Sectors||25.0|20.5|16.2|22.8|20.8|18.8|

Source: Authors’ estimations based on HIES 2018/19 Note: Results from FY20 onwards are projections. Preferred specification follows equation (1), including information from nominal growth from eleven economic sectors to model labor income and household-specific inflation as described in the methodological section until FY23. Due to the lack of disaggregated inflation projections, past FY23 projections have been deflated using headline inflation. All other projections rely on headline inflation and nominal growth rates. All models have the total household expenditure vector except for the preferred specification. Growth and poverty changes between FY16 and FY19 are used to estimate the elasticity for the Poverty Growth Elasticity and the Growth Incidence Curve for the Quintile growth contribution. Estimate poverty growth elasticity for real GDP per capita and official poverty rate between FY16 and FY19 is -1.06. The neutral distribution model uses a passthrough of 0.86 to reflect the consumption share on total GDP; results using higher (lower) passthrough rates present marginally more (less) pronounced variations of poverty to growth. Quintile growth contribution projections include a Democratic approach, where households within a quantile receive the same per-capita income amount, and a Plutocratic Approach, where each household receives an income based on its share in the total income within its quantile. Projections using sector-level growth rely on the sector of employment of the member with the highest reported labor income.

To assess the accuracy of these methods, we conducted a back-casting exercise for poverty rates spanning from FY18 to FY12. Among the methods employed, our preferred specification is competitive in predicting poverty rates in FY16 and FY14, presenting point estimates that are

> 15 The measure of elasticity is based on the international poverty line.

15