Abstract
Traditional assessments of economic growth and progress against poverty tell us little about whether the poorest are being left behind—whether the consumption floor is rising above the biological minimum. To address this deficiency, the paper identifies the expected value of the floor as a weighted mean of observed consumptions for the poorest stratum. Under the identifying assumptions and using data for the developing world over 1981–2011, the estimated floor is about half the $1.25 a day poverty line. Economic growth and social policies have delivered only modest progress in raising the floor, despite overall growth and progress in reducing the number living near the floor.
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Notes
The press release was for an IFPRI report Ahmed et al. (2007).
Quoted by James (2015).
The most commonly used axioms are: (i) focus: the measure of poverty should be unaffected by any changes in the incomes (or consumptions) of those who are not deemed to be poor ; (ii) monotonicity: holding all else constant, the measure of poverty must rise if a poor person experiences a drop in her income; (iii) subgroup monotonicity: poverty rises when any sub-group becomes poorer; (iv) scale invariance: the measure is unchanged when all incomes and the poverty line increase by the same proportion; (v) the transfer principle: the measure of poverty falls whenever a given sum of money is transferred from a poor person to someone even poorer. An influential early contribution to the axiomatic foundations was made by Sen (1976), although Sen’s measure did not satisfy all of the above axioms. Other axioms have also been proposed; for a fuller listing see Foster et al. (2013).
For further discussion of poverty lines in theory and practice see Ravallion (2012).
This reflects well known limitations of this measure, which fails both the monotonicity and transfer axioms. The income share of the poorest x % has been used as a measure of inequality, but it is also known to have deficiencies when judged by the standard axioms of inequality measurement; for further discussion see Fields (2001, Chap. 2).
The limit of the Foster et al. (1984) measure as their inequality aversion parameter goes to infinity is the lowest value level in the data. This is only the floor, as measured here, if one is certain that the lowest observed value is the lower bound to permanent consumption. It is argued below that this is questionable.
See, for example, Freiman’s (2012) comments on Rawls’s difference principle.
See, for example, the discussion in Fleurbaey and Maniquet (2011, Chap. 12).
While popularity need not guide ethical judgments, it is at least notable in the context of understanding debates about distributive justice that there is experimental evidence indicating that a non-negligible number of people make distributional judgments consistently with a Rawlsian “maximin” criterion (Michelbach et al. 2003).
The veil of ignorance was a thought device to assure that morally irrelevant—inherited or acquired—advantages in the real world did not color judgments about distributive justice.
There are also well-known efficiency arguments, notably in non-competitive labor markets. The first minimum wage law was introduced by New Zealand in 1894.
An early example was the Speenhamland System of 1795 introduced by the justices of Berkshire, which guaranteed local working-class residents a basic income indexed to the price of bread; for further discussion of this and subsequent policies see Ravallion (2016, Chap. 10).
On the arguments for a social security floor see Cichon and Hagemejer (2007).
The Di Bao program makes transfers to bring urban residents up to locally determined “Di Bao lines” (see, for example, Ravallion 2014b). The Rural Employment Guarantee Scheme in India aims to guarantee up to 100 days of work per household per year doing unskilled manual labor at stipulated minimum wage rates; see Dutta et al. (2014). The latter program can be interpreted as an attempt to enforce the minimum wage rate in an informal economy.
See Blaug’s (1962) discussion of the classical model of wage determination.
See Dasgupta (1993, Chap. 13). Blackorby and Donaldson (1984) proposed that social welfare increases with a larger population if and only if the extra people have a level of consumption above a critical minimum. This can be interpreted as an ethical floor, unlike the consumption floor, which is a positive concept.
The sources and estimation methods are described in greater detail in Chen and Ravallion (2010).
The version of the data set used here is for November 2014.
Notice that the use of a group average here is motivated by the data problem, namely that we do not observe the lowest level of permanent consumption. The aim is to estimate that level with the (imperfect) data on hand.
For example, for a uniform density \(f_j (y_i )\) in (3), \(\phi (y_i )\) is automatically a decreasing convex function.
I tested the approximation using micro data for Bihar, India in 2010. The actual \(P_3 \) was 0.022; the approximation using (12) gave 0.023.
Ravallion (2016, Chap. 7) reviews the evidence on the economic gradients in demographic variables.
This is the un-weighted mean over time. The inter-temporal variance is so low that it is unlikely that population weighting would make any detectable difference.
One might assume instead that nobody above median could be living at the floor. Then \(y^{*}=\$2.00\) per day (for 2005), giving a time-mean of the floor of $0.90. However, the median seems an implausibly high value for \(y^{*}\).
This is probably an overestimate given that PovcalNet uses grouped data for many countries, which require curve fitting; the software uses parameterized Lorenz curves fitted to the grouped data. These will give non-zero estimates to very low levels, even when the micro data do not indicate any observations.
The trend coefficient is very close to zero (a coefficient of 0.0002, with a standard error of 0.0009).
Observations confined to cases with a positive count of those living below $1.25 a day.
There is extra noise in the first few survey rounds when a number of survey design and implementation issues were still being resolved. So some averaging is needed.
This is true of Australia, Austria, Belgium, Canada, Czechoslovakia, Germany, Japan, Hungary, Korea, Luxembourg, New Zealand, the Scandinavian countries, Switzerland and Taiwan. Ravallion (2014a) gives the results. Exceptions are the United Kingdom and the United States, with 2.5 and 3.0 % still living in extreme poverty by 1992. While not strictly comparable, the estimates in Ravallion and Chen (2013) suggest that at some time after 1990 the number of people living below $1.25 a day in the high-income countries went to zero.
In the country groupings used by Bourguignon and Morrisson the consumption floor in 1850 was 45 % of the poverty line in Australia–Canada–New Zealand, 51 % in Austria–Czechoslovakia–Hungary, 54 % in Belgium–Luxembourg–Switzerland, 55 % in Germany, 41 % in Japan, 42 % in Korea–Taiwan and 49 % in Scandinavia.
White standard errors in parentheses. Using the smaller data set from Ravallion et al. (2009) the corresponding estimate of the floor was $0.647 (s.e. = 0.288; n = 73).
The preferred functional form in Ravallion et al. (2009) is not feasible since it uses a log transformation of \(\bar{{y}}_i\) for which \(E(z_i \left| {\bar{{y}}_i =0)} \right. \) is undefined.
The CDF is truncated above $20 a day to give greater detail at the lower end; however, there is first-order dominance over the entire range.
On the implications of first-order dominance in this context see Atkinson (1987).
The empirical quantile function is used for 1981. For the purpose of creating the graph, the quantile function for 2011 was based on a 10th degree polynomial, which fitted extremely well \((\hbox {R}^{2}=0.998)\), although the top 2 % were trimmed as these are considered less reliable.
The use of the 95 % confidence interval is essentially arbitrary. I also give results for other lines.
For the $0.77 line the annual trend is \(-\)0.69 % (s.e. = 0.05).
On the history of social protection policies in the U.K. and U.S. see Mencher (1967).
See World Bank (2014). For South Asia the overall coverage rate is 25 %, for MENA it is 28 %, for East Asia it is 48 % while for EECA it is 50 %.
The regression coefficient of the log of coverage rate for the poor on the log of GDP per capita is 0.91 with a standard error is 0.13. The corresponding elasticity for the population as a whole is 0.80 (s.e. = 0.11). If one controls for the overall coverage rate of the population there is no longer any statistically significant effect of GDP on the coverage rate of the poorest quintile.
Regressing the log of the ratio of coverage rate for the poor to the overall coverage rate on the log of GDP per capita gives a regression coefficient of 0.16, with a standard error of 0.04.
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For helpful discussions on the topic of this paper and comments on the paper the author is grateful to Francois Bourguignon, Mary Ann Bronson, Cait Brown, Shaohua Chen, Denis Cogneau, James Foster, Garance Genicot, Peter Lanjouw, Nkunde Mwase, Henry Richardson, Dominique van de Walle and seminar participants at the International Monetary Fund, the Paris School of Economics, the International Labour Organization, the University of Antwerp, the Human Development and Capabilities Association Conference 2015, Georgetown University, and the 30th annual conference of WIDER, Helsinki, 2015. The author also thanks the journal’s editor and five referees for their comments. One of the referees was especially helpful in developing a stronger rationale for the proposed estimator in Sect. 4.
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Ravallion, M. Are the world’s poorest being left behind?. J Econ Growth 21, 139–164 (2016). https://doi.org/10.1007/s10887-016-9126-7
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DOI: https://doi.org/10.1007/s10887-016-9126-7