The estimation of comparable poverty trends using the 2014 and 2016 rounds of the HIES data is not straightforward. The 2014 survey was administered from January through July (instead of the full calendar year as planned) due to the outbreak of Ebola Virus Disease in Liberia. When fieldwork was halted in August 2014, approximately half of the data had been collected. By contrast, the HIES 2016 was collected throughout the full year.
The difference in survey dates between the HIES 2014 and 2016 has several implications for the estimation of consumption and poverty lines. First, the consumption data for HIES 2014 collected between January and July, coincides with the lean season in Liberia, which is a time in the calendar year when poverty levels are expected to be at their highest. Second, households and individuals eat a different mix of foods in the pre-harvest period than over the year in general, and have a different balance in their food and nonfood spending. And third, adjusting for inflation the poverty line calculated using 6 months of data for the HIES 2014 and using the CPI in the full sample of 2016 will not render a comparable poverty line across time.
For all these reasons, the poverty estimates for 2014 calculated using the half-year data (54.1 percent), are not comparable to the poverty estimates calculated using the full year data for 2016 (50.9 percent). These numbers represent different measures.
The only way to arrive at comparable poverty trends in Liberia between 2014 and 2016 is to focus on the first semester (Q1Q2) of both HIES rounds; and in doing so use consumption aggregates and poverty lines derived from the same time period (i.e., the poverty line from the baseline in 2014 is inflated to the new survey period in 2016 using the CPI only for the same six months of data available in both surveys).
Figure shows the trend in the poverty status of the population between 2014 and 2016. This comparison shows an increase in the poverty headcount from 54.1 percent in to 61.2 percent nationally using as a base the 2014 poverty line.10 In urban areas, the incidence
of poverty remained much lower than rural areas and flat between 2014 and 2016 (it fell from 43.3% to 40.1% though without statistical significance). While poverty was already much higher in rural areas, it rose significantly from 70% in 2014 to 82.4% in 2016, thus widening the urban-rural poverty divide.
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