Reyntjens (2015) stated that “we can do this by starting from the 2010/11 poverty figure of 45%, but then adapting the 2010/11 poverty line in the same proportion (-19 points) as the 2013/14 adjustment. Based on the EICV3 micro data and lowering the poverty line (of the 2013/14) by 19%, the actual poverty figure is then 33% in 2010/11. There is nothing wrong in principle with a working out a new poverty line for EICV4 – as “many changes in the socio-economic structure of the country have taken place [since the first EICV in 2000/1]” – but even if the change is accepted, the 2013/14 report should measure change in poverty using a comparable poverty figure in 2010/11, namely 33% instead of 45%.” cited from Reyntjens (2015).

We now apply Propositions 1 and 2 to examine the claims made in Reyntjens (2015), asking whether the poverty rates (33 percent in EICV3 and 39 percent in EICV4) are comparable. Since Reyntjens (2015) uses a different poverty line for EICV3 and EICV4, we apply Proposition 2 for the comparability assessment.

First, condition (i) of Proposition 2 seems satisfied. Although it is not clear from the blog, we can safely assume that he uses nominal expenditure data available in EICV3 and EICV4, as released by NISR, and if so, we can say that household expenditure data are comparable. Second, condition (iii) is roughly satisfied. He discounts the poverty line of the 2013/14 by 19 percent, which is close to the inflation rate between January 2011 and January 2014 calculated from the monthly CPI published by NISR (monthly CPI provides an inflation rate of 23 percent). It is not however clear whether condition (ii) is satisfied. The problem here is that it is not clear from the blog as to what COLIs are used. If he is using the COLI of NISR (2015) for estimating poverty rates in EICV3, then the national poverty rate in 2010/11 should be close to 45 percent. If the COLI is not used and nominal expenditures are used, the national poverty rate should be close to 39.7 percent. In both cases, we cannot replicate his result. Since we cannot identify what COLIs he used, we cannot guarantee that condition (ii) is satisfied. In conclusion, we cannot confirm his poverty estimates of 33 percent for EICV3 are comparable with 39 percent for EICV4.

# **VII. Conclusion**

This paper revisits the declining poverty trend published in NISR (2015) and NISR (2016). Findings from this analysis support the official trend published in NISR (2016). We also compare the methodology adopted by NISR (2015) and NISR (2016) and although both produce similar poverty trends, it shows several methodological advantages of the latter. Moreover, we show that poverty rates for Rwanda measured at an international poverty line, $1.90 per day per capita, also show a declining poverty trend if the international measure properly adjusts for spatial price variations across regions and temporal price variations during survey data collection. Given the significance of spatial and temporal price variations, we recommend that the international poverty statistics be updated by properly adjusting for these. Finally, this paper presents possible reasons behind the significant differences between national CPIs and NISR (2016) COLIs. It is important to continue research on these differences to establish a common understanding and agreement on the price index deemed most appropriate for poverty monitoring over time.

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