In 2023, approximately 11.7 percent of the Peruvian population was living on less than 3.20 U.S. dollars per day. This share has been continuously decreasing since 2010 when it totaled until 2019. Still, social inequality remains a challenge in Peru and in the whole Latin American region.

The share of the population with at least one poverty condition or unmet need in the Peruvian capital of Lima reached its lowest during 2017 with *** percent. In 2023, the share of residents of the metropolitan area was over **** percent.

Historical dataset showing Peru poverty rate by year from 1985 to 2023.

Poverty rate at $3.2 a day of Peru surged by 9.35% from 10.70 % in 2022 to 11.70 % in 2023. Since the 40.74% slump in 2021, poverty rate at $3.2 a day went up by 4.46% in 2023. Population below $3.1 a day is the percentage of the population living on less than $3.1 a day at 2005 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

Poverty headcount ratio at national poverty lines (% of population) in Peru was reported at 27.5 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Peru - Poverty headcount ratio at national poverty line (% of population) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Throughout the depicted period in Peru, the population witnessed a rapid decline in extreme poverty, except for an increase observed between 2020 and 2023. This increase caused the share of extreme poverty to reach 5.7% in the most recent reported year.

5,90 (%) in 2023. Population below $1.9 a day is the percentage of the population living on less than $1.9 a day at 2005 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

In 2022, the poverty headcount ratio at national poverty lines in Peru stood at 27.5 percent. Between 2004 and 2022, the figure dropped by 31.2 percentage points, though the decline followed an uneven course rather than a steady trajectory.

Peru was one of the countries most affected by the COVID-19 pandemic in terms of health and economic impacts and the erosion of the socialgains achieved in the previous decade. By July 2022, Peru had registered more than 6,000 deaths per million population because of COVID-19,placing the country among the countries with the highest COVID-related mortality rates per capita. The economy contracted by 11 percent in 2020, its biggest fall in 30 years and the largest in Latin America during that year. As a result, the national poverty rate increased to 30.1 percent, a level not seen since 2010, and extreme poverty reached 5.1percent in 2020, comparable with the rate in 2013. By the end of 2021, the economy had recovered, but poverty and extreme poverty remained at the levels of 2012 and 2015, respectively. The magnitude of the welfare loss during the crisis revealed the fragility of the social gains that had been achieved during the previous two decades.

Peru had, in 2023, more than 20 percent of the indigenous population living in poverty, thus representing an increase of 2.1 percentage points compared to the previous year. Furthermore, over a fourth of afro-descendants in Peru lived under the poverty line as well.

Peru PE: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at 3.080 % in 2016. Peru PE: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging 3.080 % from Dec 2016 (Median) to 2016, with 1 observations. Peru PE: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank: Poverty. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

27.5 (%) in 2022. National poverty rate is the percentage of the population living below the national poverty line. National estimates are based on population-weighted subgroup estimates from household surveys.

Peru PE: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data was reported at 2.180 % in 2016. Peru PE: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data is updated yearly, averaging 2.180 % from Dec 2016 (Median) to 2016, with 1 observations. Peru PE: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank: Poverty. The growth rate in the welfare aggregate of the total population is computed as the annualized average growth rate in per capita real consumption or income of the total population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

Peru PE: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data was reported at 24.300 % in 2016. This stayed constant from the previous number of 24.300 % for 2015. Peru PE: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data is updated yearly, averaging 44.050 % from Dec 1997 (Median) to 2016, with 20 observations. The data reached an all-time high of 55.100 % in 2001 and a record low of 24.300 % in 2016. Peru PE: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank.WDI: Poverty. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

During the depicted period in Peru, the proportion of individuals living in poverty experienced fluctuations, initially displaying an organic downward trend. However, the economic impact of the COVID-19 pandemic disrupted the country's situation, causing the poverty rate to reach its highest level.

Peru PE: Proportion of Population Pushed Below the $1.90: Poverty Line by Out-of-Pocket Health Care Expenditure: 2011 PPP: % data was reported at 0.052 % in 2015. This records a decrease from the previous number of 0.118 % for 2014. Peru PE: Proportion of Population Pushed Below the $1.90: Poverty Line by Out-of-Pocket Health Care Expenditure: 2011 PPP: % data is updated yearly, averaging 0.317 % from Dec 2000 (Median) to 2015, with 10 observations. The data reached an all-time high of 1.235 % in 2000 and a record low of 0.052 % in 2015. Peru PE: Proportion of Population Pushed Below the $1.90: Poverty Line by Out-of-Pocket Health Care Expenditure: 2011 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank: Poverty. Proportion of population pushed below the $1.90 ($ 2011 PPP) poverty line by out-of-pocket health care expenditure, expressed as a percentage of a total population of a country; ; Wagstaff et al. Progress on Impoverishing Health Spending: Results for 122 Countries. A Retrospective Observational Study, Lancet Global Health 2017.; Weighted Average;

Rural poverty rate of Peru declined by 4.17% from 48.0 % in 2013 to 46.0 % in 2014. Since the 1.08% reduction in 2005, rural poverty rate plummeted by 44.24% in 2014. Rural poverty rate is the percentage of the rural population living below the national rural poverty line.

Peru PE: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 10.000 % in 2016. This records a decrease from the previous number of 10.400 % for 2015. Peru PE: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 25.000 % from Dec 1997 (Median) to 2016, with 20 observations. The data reached an all-time high of 32.900 % in 2001 and a record low of 10.000 % in 2016. Peru PE: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank: Poverty. Poverty headcount ratio at $3.20 a day is the percentage of the population living on less than $3.20 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Peru PE: Poverty Gap at $1.90 a Day: 2011 PPP: % data was reported at 0.900 % in 2016. This records a decrease from the previous number of 1.000 % for 2015. Peru PE: Poverty Gap at $1.90 a Day: 2011 PPP: % data is updated yearly, averaging 3.750 % from Dec 1997 (Median) to 2016, with 20 observations. The data reached an all-time high of 7.200 % in 1999 and a record low of 0.900 % in 2016. Peru PE: Poverty Gap at $1.90 a Day: 2011 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank.WDI: Poverty. Poverty gap at $1.90 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $1.90 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Abstract

The rapid and massive dissemination of mobile phones in the developing world is creating new opportunities for the discipline of survey research. The World Bank is interested in leveraging mobile phone technology as a means of direct communication with poor households in the developing world in order to gather rapid feedback on the impact of economic crises and other events on the economy of such households.

The World Bank commissioned Gallup to conduct the Listening to LAC (L2L) pilot program, a research project aimed at testing the feasibility of mobile phone technology as a way of data collection for conducting quick turnaround, self-administered, longitudinal surveys among households in Peru and Honduras.

The project used face-to-face interviews as its benchmark, and included Short Message Service (SMS), Interactive Voice Response (IVR) and Computer Assisted Telephone Interviews (CATI) as test methods of data collection.

The pilot was designed in a way that allowed testing the response rates and the quality of data, while also providing information on the cost of collecting data using mobile phones. Researchers also evaluated if providing incentives affected panel attrition rates.

The random stratified multistage sampling technique was used to select a nationally representative sample of 1,500 households. During the initial face-to-face interviews, researchers gathered information on the socio-economic characteristics of households and recruited participants for follow-up research. Questions wording was the same in all modes of data collection.

In Peru, households were randomly assigned to a communication mode (SMS, IVR, CATI), which stayed constant for all rounds (waves) of the survey.

Geographic coverage

Includes the entire national territory, with the exception of neighborhoods where access of interviewers is extremely difficult, due to lack of transportation infrastructure or for situations that threaten the physical integrity of the interviewers and supervisors (i.e. extremely high crime rate, warfare, etc.)

Analysis unit

• Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The Peru panel was built on a nationally representative sample of 1,500 households. The sample was based on the sampling frame for the National Household Survey (ENAHO) conducted by the Peruvian National Statistics Office (INEI) every three months.

In Peru, the sample selection was guided by the following criteria: (i) the sample should be representative nationally, and in urban and rural areas, and (ii) households close to poverty line should be oversampled because policy decisions in time of crises need to be especially mindful of the poor and vulnerable. For the purposes of this project, "close to poverty line" was defined as 40 percent of consumption distribution that symmetrically band the national poverty line: 20 percent above and 20 percent below. In 27 percent of Peruvian households monthly per capita consumption was below the moderate poverty line in 2010 (ENAHO).Those households whose monthly per capita consumption falls between 7 and 47 percent of the national distribution were oversampled.

The L2L sample frame comprises all the panel conglomerados from the fourth trimester of ENAHO 2010, or 281 conglomerados.

Detailed information about the sampling procedure is available in "Listening to LAC: Using Mobile Phones for High Frequency Data Collection, Final Report" (p. 65-69) and "The World Bank Listening to LAC (L2L) Pilot Project Sample Design for Peru."

Sampling deviation

A number of restive communities in Peru did not allow Gallup's interviewers to enter the area. Where possible, these were replaced following INEI's standard methodology. When confronted with a problem in a particular location, INEI moves to the next "Centro Poblado" in the same "Conglomerado."

Mode of data collection

Other [oth]

Research instrument

The following survey instruments were used in the project:

1) Initial face-to-face questionnaire

In Peru, the starting point was the ENAHO (National Household Survey) questionnaire. Step-wise regressions were done to select the set of questions that best predicted consumption. For the purposes of robustness, the regressions were also done with questions that best predicted income, which yielded the same results.

The survey gathered information on households' demographics, household infrastructure, employment, remittances, income, accidents, food security, self-perceptions on poverty, Internet access and cellphones use.

2) Monthly questionnaires (SMS, IVR, CATI)

The questionnaires were worded exactly the same way, regardless of the mode, which meant short questions, since SMS is limited to 160 characters. A maximum of 10 questions had to be chosen for the monthly questionnaire. In addition, two questions sought to ensure the validity of the responses by testing if the respondent was a member of the household. Most questions were time-variant and each questionnaire was repeated to observe if answers changed over time. All questions related to variables that strongly affect household welfare and are likely to change in times of crisis.

A maximum of 10 questions was chosen for the monthly questionnaire. In addition, two questions sought to ensure the validity of the responses by testing if the respondent was a member of the household. To accomplish this, the first two questions in each monthly questionnaire asked the respondent for their gender and year of birth, and the answers were compared to the household roster obtained during the face-to-face interview.

3) Final face-to-face questionnaire

Gallup conducted face-to-face closing surveys among 700 panelists. The researchers asked about issues the respondets had with mobile phones and coverage during the test. Panelists were also asked what would motivate them to keep on participating in a project like this in the future.

Response rate

In Peru, 67 percent of recruited households failed to answer the first round of follow-up surveys. Attrition slightly increased with each wave of the survey (between 1 and 3 percentage points per wave), reaching 75 percent in wave 6.

As part of the survey administration process Gallup implemented a number of mechanisms to maximize the response rate and panelist retention. The following strategies were applied to respondents who did not replay first time:

• The surveys were left open for responses for up to 2 weeks after the original transmission of the survey (from original call in the case of IVR and CATI).
• First reminder was sent within 72 hours of first attempt (SMS and IVR).
• Second reminder was sent within 144 hours of first attempt (SMS and IVR).
• Call backs were made within 72 and 144 hours of first attempt (CATI); or
• Up to 2 call backs were made per appointment with respondent (CATI).

Also, in order to minimize non-response, three types of incentives were given. First, households that did not own a mobile phone were provided one for free. Approximately 200 phones were donated in Peru. Second, all communications between the interviewers and the households were free to the respondents. Finally, households were randomly assigned to one of three incentive levels: one-third of households received US$1 in free airtime for each questionnaire they answered, one-third received US$5 in free airtime, and one-third received no financial incentive (the control group).