Removing the anonymity axiom in assessing pro-poor growth

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThe recent focus on 'pro-poor growth' led also to an intense debate on how exactly to define and to measure pro-poor growth. However, all suggested measures, irrespective whether they use the absolute or the relative definition of pro-poor growth have in common that they are based on the anonymity axiom, i.e. they do not distinguish between changes in horizontal and vertical inequality. That means usual assessments of pro-poor growth look at distributional changes over time and ignore how specific groups or households moved. Such a perspective may provide a very incomplete picture given that the common objective of most studies investigating the pro-poorness of growth is to test whether specific policy reforms where beneficial to the initially poor or not. Using panel data from Indonesia and Peru, this paper analyzes and illustrates empirically the implications of removing the anonymity axiom from measurements of pro-poor growth. It is shown that postulating anonymity, when assessing pro-poor growth can lead to misleading conclusions on how a specific policy affected the incomes of the initially poor. For both countries, the analysis shows substantial convergence to the mean, which is, at least for the case of Indonesia, robust to measurement error in the expenditure data.JEL Classification: D31, D63, O15.

Childhood obesity and maternal education in Ireland

“…In carrying out this analysis we apply techniques employed in the economics literature on poverty and mobility. Recent research in these areas has moved on from just analysing snapshots at a given point in time and attention is now paid to examining persistence of poverty for the same cohort of people (see for example Jenkins and van Kerm, 2006, Grimm, 2007, Gradin et al, 2012. Similarly, in our analysis of obesity below, we incorporate measures which explicitly take account of persistence between periods.…”

Can a Poverty-Reducing and Progressive Tax and Transfer System Hurt the Poor?

“…Growth incidence curves (Ravallion and Chen, 2003) and related pro-poor partial orderings (Duclos, 2009) can fail to capture impoverishment for the same reason that stochastic dominance tests do: they are anonymous with respect to initial income. Although their non-anonymous counterparts (Bourguignon, 2011a, Grimm, 2007, Van Kerm, 2009) resolve this issue in theory, in practice-to become graphically tractablethey average within percentiles, and hence impoverishment can still be overlooked if within some percentiles, some poor are "hurting behind the averages" (Ravallion, 2001(Ravallion, , p. 1811. For consumption tax and subsidy reform, Besley and Kanbur (1988) derive poverty-reducing conditions for reallocating food subsidies; these results are extended to commodity taxes and a broader class of poverty measures by Makdissi and Wodon (2002) and Duclos et al (2008).…”

Intertemporal pro-poorness

“…Because of this, recent contributions have argued that pro-poor and welfare judgments of the effect of growth should be based on a 'non-anonymous' perspective (see notably Grimm, 2007, Jenkins and Van Kerm, 2011, Bourguignon, 2011, Palmisano and Van de gaer, 2013, Palmisano and Peragine, 2014. Proponents of this emphasize the role played by mobility in the distributional effects of growth.…”

“…For instance, Grimm (2007) introduces an Individual Rate of Pro-Poor Growth (IRPPG) which, being equivalent to the average income growth of the initially poor individuals divided by the proportion of those individuals in the population, specifically focuses on the impact of growth on the initially poor and ignores the negative income effects of those who experience deprivation after growth. Foster and Rothbaum (2012) use cutoff-based mobility measures to explain variations of poverty over time.…”