Poverty gap index

{{Short description|Measurement of poverty intensity}}

{{Use mdy dates|date=November 2020}}

{{Update|date=March 2025}}

The poverty gap index is a measure of the degree of poverty in a country. It is defined as extent to which individuals on average fall below the poverty line, and expresses it as a percentage of the poverty line.{{Cite web |title=Poverty Gap |url=https://stats.areppim.com/glossaire/poverty_gap_def.htm |access-date=2023-06-03 |website=stats.areppim.com}}

The poverty gap index is an improvement over the poverty measure head count ratio, which simply counts all the people below a poverty line in a given population and considers them equally poor.{{cite journal|title=Poverty: An Ordinal Approach to Measurement|last=Sen|first=Amartya |author-link=Amartya Sen|journal=Econometrica|volume= 44|number= 2|date=March 1976|pages= 219–231|jstor=1912718|doi=10.2307/1912718}} Poverty gap index estimates the depth of poverty by considering how far the poor are from that poverty line on average.{{cite book|url=https://books.google.com/books?id=Bmx00pzs3lsC|title=Poverty and Inequality |series=Studies in Social Inequality|editor-last1=Grusky|editor-first1=David B.|editor-link1=David Grusky|editor-last2=Kanbur|editor-first2=Ravi |editor-link2=Ravi Kanbur|year=2006|place=Stanford, California|publisher=Stanford University Press|page={{page needed|date=November 2020}}|isbn=978-0-8047-4843-8}}

The poverty gap index sometimes referred to as 'poverty gap ratio' or 'pg index' is defined as an average of the ratio of the poverty gap to the poverty line.{{cite book|title=Indicators for Monitoring the Millennium Development Goals|place=New York|publisher=United Nations |year=2003|page=9|url=http://mdgs.un.org/unsd/mdg/Resources/Attach/Indicators/HandbookEnglish.pdf}} It is expressed as a percentage of the poverty line for a country or region.{{cite web|title=Poverty Measures|publisher=World Bank|year=2009|url=http://info.worldbank.org/etools/docs/library/93518/Hung_0603/Hu_0603/Module4MeasuringPovertyMeasures.pdf|archive-url=https://web.archive.org/web/20120710075625/http://info.worldbank.org/etools/docs/library/93518/Hung_0603/Hu_0603/Module4MeasuringPovertyMeasures.pdf|archive-date=2012-07-10}}

Significance

The most common method measuring and reporting poverty is the headcount ratio, given as the percentage of the population that is below the poverty line. For example, The New York Times in July 2012 reported the poverty headcount ratio as 11.1% of American population in 1973, 15.2% in 1983, and 11.3% in 2000.{{cite news|last=Edelman|first=Peter |author-link=Peter Edelman|url= https://www.nytimes.com/2012/07/29/opinion/sunday/why-cant-we-end-poverty-in-america.html |title=Poverty in America: Why Can't We End It?|date=July 28, 2012|work=The New York Times|access-date=2020-11-20}} One of the undesirable features of the headcount ratio is that it ignores the depth of poverty; if the poor become poorer, the headcount index does not change.{{cite book|last=Ravallion|first=Martin |author-link=Martin Ravallion|url=http://documents1.worldbank.org/curated/en/965061468739145705/pdf/multi-page.pdf|title=Issues in Measuring and Modeling Poverty|date=June 1996|series=Policy Research Working Paper|volume=1615 |place=Washington, D.C.|publisher=World Bank |access-date=2020-11-20}}

Poverty gap index provides a clearer perspective on the depth of poverty. It enables poverty comparisons. It also helps provide an overall assessment of a region's progress in poverty reduction and the evaluation of specific public policies or private initiatives.{{cite web|title=Indicators of Sustainable Development|publisher=United Nations Department for Policy Coordination and Sustainable Development|year=2004|url=http://esl.jrc.it/envind/un_meths/UN_ME.htm|access-date=2012-08-10|archive-url=https://web.archive.org/web/20120421005418/http://esl.jrc.it/envind/un_meths/UN_ME.htm|archive-date=2012-04-21|url-status=dead}}

Calculation

The poverty gap index (PGI) is calculated as,

::{\rm PGI} = \frac{1}{N} \sum_{j=1}^{q} \left( \frac{z-y_j}{z} \right)

or

::{\rm PGI} = \frac{1}{N} \sum_{j=1}^{N} \left( \frac{(z-y_j).1(y_j

where N is the total population, q is the total population of poor who are living at or below the poverty line, z is the poverty line, and y_j is the income of the poor individual j. In this calculation, individuals whose income is above the poverty line have a gap of zero.

By definition, the poverty gap index is a percentage between 0 and 100%. Sometimes it is reported as a fraction, between 0 and 1. A theoretical value of zero implies that no one in the population is below the poverty line. A theoretical value of 100% implies that everyone in the population has zero income. In some literature, poverty gap index is reported as P_1 while the headcount ratio is reported as P_0.{{cite book|title=Introduction to Poverty Analysis|chapter=Poverty Measures, Chapter 4|chapter-url=http://siteresources.worldbank.org/PGLP/Resources/povertymanual_ch4.pdf |place=Washington, D.C.|publisher=World Bank Institute|date=August 2005|archive-url=https://web.archive.org/web/20120710075646/http://siteresources.worldbank.org/PGLP/Resources/povertymanual_ch4.pdf|archive-date=2012-07-10}}

Features

The poverty gap index can be interpreted as the average percentage shortfall in income for the population, from the poverty line.

If you multiply a country's poverty gap index by both the poverty line and the total number of individuals in the country you get the total amount of money needed to bring the poor in the population out of extreme poverty and up to the poverty line, assuming perfect targeting of transfers. For example, suppose a country has 10 million individuals, a poverty line of $500 per year, and a poverty gap index of 5%. Then an average increase of $25 per individual per year would eliminate extreme poverty. $25 is 5% of the poverty line. The total increase needed to eliminate poverty is US$250 million—$25 multiplied by 10 million individuals.

The poverty gap index is an important measure beyond the commonly used headcount ratio. Two regions may have a similar head count ratio, but distinctly different poverty gap indices. A higher poverty gap index means that poverty is more severe.

The poverty gap index is additive. In other words, the index can be used as an aggregate poverty measure, as well as decomposed for various sub-groups of the population, such as by region, employment sector, education level, gender, age, or ethnic group.

Limitations

The poverty gap index ignores the effect of inequality between the poor. It does not capture differences in the severity of poverty amongst the poor. As a theoretical example, consider two small neighborhoods where just two households each are below the official poverty line of US$500 income per year. In one case, household 1 has an income of US$100 per year and household 2 has an income of US$300 per year. In second case, the two households both have annual income of US$200 per year. The poverty gap index for both cases is same (60%), even though the first case has one household, with US$100 per year income, experiencing a more severe state of poverty. Scholars, therefore, consider poverty gap index as a moderate but incomplete improvement over poverty head count ratio.{{Cite journal|title=Absolute versus Relative Poverty|last=Foster |first=James E. |author-link=James Foster (economist)|journal=The American Economic Review|volume= 88|number= 2|date=May 1998|pages= 335–341|jstor=116944|citeseerx=10.1.1.383.6488}}

Scholars such as Amartya Sen suggest poverty gap index offers a quantitative improvement over simply counting the poor below the poverty line, but remains limited at the qualitative level. Focusing on precisely measuring income gap diverts the attention from qualitative aspects such as capabilities, skills and personal resources that may sustainably eradicate poverty. A better measure would focus on capabilities and consequent consumption side of impoverished households.{{cite magazine|title=Who Is Poor?|last=Morrell |first=Dan |magazine=Harvard Magazine|date=January–February 2011|url=http://harvardmagazine.com/2011/01/who-is-poor|access-date=2020-11-22}} These suggestions were initially controversial, and have over time inspired scholars to propose numerous refinements.{{cite journal|title=A Sociological Approach to the Measurement of Poverty: A Reply to Professor Peter Townsend|last=Sen |first=Amartya |journal=Oxford Economic Papers|volume= 37|number= 4|date=December 1985|pages= 669–676|jstor=2663049 |doi=10.1093/oxfordjournals.oep.a041716}}{{cite journal|title=Poverty, Income Inequality, and Their Measures: Professor Sen's Axiomatic Approach Reconsidered|last=Takayama |first=Noriyuki |journal=Econometrica|volume= 47|number= 3|date=May 1979|pages= 747–759|jstor= 1910420|doi=10.2307/1910420}}{{cite journal|title=Three 'I's of Poverty Curves, with an Analysis of UK Poverty Trends|last1=Jenkins|first1=Stephen P. |last2=Lambert|first2=Peter J. |journal=Oxford Economic Papers | date=July 1997|volume= 49|issue= 3|pages= 317–327|jstor=2663596 |doi=10.1093/oxfordjournals.oep.a028611}}

Related measures

The Foster–Greer–Thorbecke metric is the general form of the PGI. The FGT_\alpha formula raises the summands to the power alpha, so that FGT0 is the headcount index, FGT1 the PGI and FGT2 the squared PGI.

Squared poverty gap index, also known poverty severity index or P_2, is related to poverty gap index. It is calculated by averaging the square of the poverty gap ratio. By squaring each poverty gap data, the measure puts more weight the further a poor person's observed income falls below the poverty line. The squared poverty gap index is one form of a weighted sum of poverty gaps, with the weight proportionate to the poverty gap.

Sen index, sometimes referred to P_{\text{SEN}}, is related to poverty gap index (PGI).{{cite web|title=Poverty Measurement|last=Vecchi|first=Giovanni |publisher=World Bank|date=September 2007|url=http://siteresources.worldbank.org/PGLP/Resources/200709gv-03-povertymeasurement.pdf|archive-url=https://web.archive.org/web/20160303225039/http://siteresources.worldbank.org/PGLP/Resources/200709gv-03-povertymeasurement.pdf|archive-date=2016-03-03}} It is calculated as follows:

:: {\rm P_{\text{SEN}}} = H*G_z + PGI*(1-G_z)

where, H is the head count ratio and G_z is the income Gini coefficient of only the people below the poverty line.

Watts index, sometimes referred to W, is related to poverty gap index (PGI). It is calculated as follows:

:: {\rm W} = \frac{1}{N} \sum_{j=1}^{q} \ln \left( \frac{z}{y_j} \right)

The terms used to calculate W are same as in poverty gap index (see the calculation section in this article).

Poverty gap index by country

{{Update|section|date=November 2020}}

The following table summarizes the poverty gap index for developed and developing countries across the world.

class="wikitable sortable" style="text-align:right"

|+Poverty gap ratio for various countries{{cite web|title=Poverty database|publisher=World Bank|year=2012|url=http://iresearch.worldbank.org/PovcalNet/index.htm|archive-url=https://archive.today/20121202223302/http://iresearch.worldbank.org/PovcalNet/index.htm|archive-date=December 2, 2012|url-status=dead}}{{cite web|title=Poverty and Inequality Platform (version 20240627_2017_01_02_PROD) [data set]|publisher=World Bank|year=2024|access-date=2024-11-26|url=https://pip.worldbank.org/poverty-calculator}}{{cite book|chapter=Poverty rates and gaps|title=OECD Factbook 2010: Economic, Environmental and Social Statistics|place=Paris |publisher=OECD Publishing|year=2010|pages=236–237|doi=10.1787/factbook-2010-89-en|isbn=9789264083561}}

CountryPoverty
line
($/month){{efn|This is on purchasing power parity basis, international dollar adjusted for inflation to 2005; To convert to $ per day income, divide by 30.4; for annual income multiply by 12.}}
Head count
ratio
(%)
style="background-color:orange;"| Poverty
gap
index
(%)
Year
align="left" | {{flag|Albania}}5222.914.182020
align="left" | {{flag|Angola}}3854.3129.942000
align="left" | {{flag|Argentina}}{{efn|This data is for urban population only.}}380.920.652010
align="left" | {{flag|Armenia}}381.280.252008
align="left" | {{flag|Australia}}95912.42.932010
align="left" | {{flag|Austria}}10246.61.812010
align="left" | {{flag|Azerbaijan}}380.430.142008
align="left" | {{flag|Bangladesh}}3843.2511.172010
align="left" | {{flag|Belarus}}380.10.12008
align="left" | {{flag|Belgium}}9308.81.802010
align="left" | {{flag|Belize}}3812.215.521999
align="left" | {{flag|Benin}}3847.3315.732003
align="left" | {{flag|Bhutan}}3810.221.812007
align="left" | {{flag|Bolivia}}3815.618.642008
align="left" | {{flag|Bosnia and Herzegovina}}380.040.022007
align="left" | {{flag|Botswana}}3831.2311.041993
align="left" | {{flag|Brazil}}3503.913.622015
align="left" | {{flag|Burkina Faso}}3844.614.662009
align="left" | {{flag|Burundi}}3881.3236.392006
align="left" | {{flag|Cambodia}}3822.754.872008
align="left" | {{flag|Cameroon}}389.561.22007
align="left" | {{flag|Canada}}105612.12.962010
align="left" | {{flag|Cape Verde}}3821.026.052001
align="left" | {{flag|Central African Republic}}3862.8331.262008
align="left" | {{flag|Chad}}3861.9425.642002
align="left" | {{flag|Chile}}381.350.692009
align="left" | {{flag|China}}{{efn|This data is for rural population of China.}}3816.254.032005
align="left" | {{flag|Colombia}}388.163.782010
align="left" | {{flag|Comoros}}3846.1120.822004
align="left" | {{flag|Costa Rica}}383.121.792009
align="left" | {{flag|Cote d'Ivoire}}3823.757.52008
align="left" | {{flag|Czech Republic}}5155.81.372010
align="left" | {{flag|Denmark}}9555.31.292010
align="left" | {{flag|Djibouti}}3818.845.292002
align="left" | {{flag|Dominican Republic}}382.240.522010
align="left" | {{flag|Congo, Dem. Rep.}}3887.7252.82005
align="left" | {{flag|Congo, Rep.}}3854.122.82005
align="left" | {{flag|Ecuador}}384.62.12010
align="left" | {{flag|Egypt}}381.690.42008
align="left" | {{flag|Estonia}}388.94.42009
align="left" | {{flag|Ethiopia}}38399.62005
align="left" | {{flag|Fiji}}385.91.12009
align="left" | {{flag|Finland}}8757.31.482010
align="left" | {{flag|France}}8617.11.442010
align="left" | {{flag|Gabon}}384.8.92005
align="left" | {{flag|Gambia}}3833.611.72003
align="left" | {{flag|Germany}}918113.672010
align="left" | {{flag|Georgia}}3815.34.62008
align="left" | {{flag|Ghana}}3828.69.92006
align="left" | {{flag|Greece}}72012.63.362010
align="left" | {{flag|Guatemala}}3813.54.72006
align="left" | {{flag|Guinea}}3843.315.2007
align="left" | {{flag|Guinea-Bissau}}3848.916.62002
align="left" | {{flag|Guyana}}388.72.81998
align="left" | {{flag|Haiti}}3861.732.32001
align="left" | {{flag|Honduras}}3817.99.42009
align="left" | {{flag|Hungary}}4077.11.662010
align="left" | {{flag|Iceland}}9427.12.552010
align="left" | {{flag|Ireland}}93414.83.082010
align="left" | {{flag|India}}3832.77.52010
align="left" | {{flag|Indonesia}}3818.13.32010
align="left" | {{flag|Iran}}381.450.342005
align="left" | {{flag|Iraq}}382.80.422007
align="left" | {{flag|Italy}}70011.43.082010
align="left" | {{flag|Jamaica}}380.210.022004
align="left" | {{flag|Japan}}95014.95.172010
align="left" | {{flag|Jordan}}380.120.032010
align="left" | {{flag|Kazakhstan}}380.110.032009
align="left" | {{flag|Kenya}}3843.416.92005
align="left" | {{flag|Kyrgyzstan}}386.41.52008
align="left" | {{flag|Laos}}384412.12002
align="left" | {{flag|Latvia}}380.140.12008
align="left" | {{flag|Lesotho}}3843.420.82003
align="left" | {{flag|Liberia}}3883.840.92007
align="left" | {{flag|Lithuania}}380.160.12008
align="left" | {{flag|Luxembourg}}15118.11.622010
align="left" | {{flag|Macedonia}}380.290.042008
align="left" | {{flag|Madagascar}}3881.343.32010
align="left" | {{flag|Malawi}}3873.932.32004
align="left" | {{flag|Maldives}}381.480.142008
align="left" | {{flag|Mali}}3850.416.42010
align="left" | {{flag|Mauritania}}3823.46.82008
align="left" | {{flag|Mexico}}19218.46.972010
align="left" | {{flag|Micronesia}}3831.216.32000
align="left" | {{flag|Moldova}}380.390.082010
align="left" | {{flag|Montenegro}}380.120.082008
align="left" | {{flag|Morocco}}382.5.542007
align="left" | {{flag|Mozambique}}3859.625.12008
align="left" | {{flag|Namibia}}3831.99.52004
align="left" | {{flag|Nepal}}3824.85.62010
align="left" | {{flag|Netherlands}}11687.71.612010
align="left" | {{flag|New Zealand}}80310.83.632010
align="left" | {{flag|Nicaragua}}3811.92.42005
align="left" | {{flag|Niger}}3843.612.42008
align="left" | {{flag|Nigeria}}386833.72010
align="left" | {{flag|Norway}}11096.82.002010
align="left" | {{flag|Pakistan}}38213.52008
align="left" | {{flag|Panama}}386.62.12010
align="left" | {{flag|Papua}}3835.812.31996
align="left" | {{flag|Paraguay}}387.23.2010
align="left" | {{flag|Peru}}384.91.32010
align="left" | {{flag|Philippines}}3818.43.72009
align="left" | {{flag|Poland}}33814.65.202010
align="left" | {{flag|Portugal}}51212.93.742010
align="left" | {{flag|Romania}}380.410.192009
align="left" | {{flag|Russia}}{{cite web|title=Poverty and Economic Growth in Russia's Regions|last1=Mosley|first1=Paul |last2=Mussurov |first2=Altay |date=April 2009|publisher=University of Sheffield|series=Sheffield Economic Research Paper Series |issn=1749-8368 |url=http://eprints.whiterose.ac.uk/10002/1/SERPS2009006.pdf}}6114.35.092006
align="left" | {{flag|Rwanda}}3863.226.62011
align="left" | {{flag|São Tomé and Príncipe}}3828.27.92001
align="left" | {{flag|Senegal}}3833.510.82005
align="left" | {{flag|Serbia}}380.260.172009
align="left" | {{flag|Sierra Leone}}3853.420.32003
align="left" | {{flag|Slovakia}}3688.12.072010
align="left" | {{flag|South Africa}}3813.82.32009
align="left" | {{flag|South Korea}}80914.65.262010
align="left" | {{flag|Spain}}74914.14.512010
align="left" | {{flag|Sri Lanka}}38712007
align="left" | {{flag|Sudan}}3819.85.52009
align="left" | {{flag|Suriname}}3815.55.91999
align="left" | {{flag|Swaziland}}3840.616.2010
align="left" | {{flag|Sweden}}8635.31.312010
align="left" | {{flag|Syria}}381.710.22004
align="left" | {{flag|Switzerland}}11488.73.372010
align="left" | {{flag|Tajikistan}}386.61.22009
align="left" | {{flag|Tanzania}}3867.928.12007
align="left" | {{flag|Thailand}}380.370.052009
align="left" | {{flag|East Timor}}3837.48.92007
align="left" | {{flag|Togo}}3838.711.42006
align="left" | {{flag|Trinidad and Tobago}}384.21.12008
align="left" | {{flag|Tunisia}}381.350.282005
align="left" | {{flag|Turkey}}21117.55.762010
align="left" | {{flag|Turkmenistan}}3824.871998
align="left" | {{flag|Uganda}}3838.0112.22009
align="left" | {{flag|Ukraine}}380.060.042009
align="left" | {{flag|United Kingdom}}10278.32.062010
align="left" | {{flag|United States}}{{efn|The U.S. defines its poverty line on a dynamic basis and household size. As an example, for a family of 4 in a household, the poverty line was about $1,838 per month.}}123217.16.552010
align="left" | {{flag|Uruguay}}380.20.072008
align="left" | {{flag|Venezuela}}386.63.72006
align="left" | {{flag|Vietnam}}3816.93.82008
align="left" | {{flag|Yemen}}3817.54.22005
align="left" | {{flag|Zambia}}3868.5372006

See also

Notes

{{notelist}}

References

{{Reflist}}