| Title: | Lookup Tables to Generate Poverty Likelihoods and Rates using the Poverty Probability Index (PPI) |
|---|---|
| Description: | The Poverty Probability Index (PPI) is a poverty measurement tool for organizations and businesses with a mission to serve the poor. The PPI is statistically-sound, yet simple to use: the answers to 10 questions about a household’s characteristics and asset ownership are scored to compute the likelihood that the household is living below the poverty line – or above by only a narrow margin. This package contains country-specific lookup data tables used as reference to determine the poverty likelihood of a household based on their score from the country-specific PPI questionnaire. These lookup tables have been extracted from documentation of the PPI found at <https://www.povertyindex.org> and managed by Innovations for Poverty Action <https://poverty-action.org/>. |
| Authors: | Ernest Guevarra [aut, cre] |
| Maintainer: | Ernest Guevarra <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.5.5.9000 |
| Built: | 2025-03-01 06:38:30 UTC |
| Source: | https://github.com/katilingban/ppitables |
Search for PPI table by specifying region, country and/or calculation type.
find_table( region = steer$region, country = steer$country[steer$region %in% region], type = steer$type[steer$country %in% country] )find_table( region = steer$region, country = steer$country[steer$region %in% region], type = steer$type[steer$country %in% country] )
region |
Region of the world to search PPI table from. Default is
|
country |
Country to search PPI table from. Default is vector of all country names from the specified region/s. Allows specification of one country name or a vector of country names. |
type |
Type of PPI calculation used. Can be one of two options: |
A data frame in tibble format of corresponding PPI table/s
matching the search parameters. The data frame contains information on the
region, country, description, survey year,
release year, calculation type, and filename of the
returned PPI table/s.
## View the full data frame of all the PPI tables available through ppitables find_table()## View the full data frame of all the PPI tables available through ppitables find_table()
Get PPI table/s based on a specified PPI table/s search output
get_table( region = steer$region, country = steer$country[steer$region %in% region], type = steer$type[steer$country %in% country] )get_table( region = steer$region, country = steer$country[steer$region %in% region], type = steer$type[steer$country %in% country] )
region |
Region of the world to search PPI table from. Default is
|
country |
Country to search PPI table from. Default is vector of all country names from the specified region/s. Allows specification of one country name or a vector of country names. |
type |
Type of PPI calculation used. Can be one of two options: |
A data frame in tibble format of corresponding PPI table/s
matching the search parameters. The data frame is in tidy format
and contains the corresponding poverty probability (ppi) for a
specific score (score) for various poverty definitions)
for the country (country) and PPI calculation type (type).
## Create a tidy format PPI table for Nepal get_table(region = "Asia", country = "Nepal")## Create a tidy format PPI table for Nepal get_table(region = "Asia", country = "Nepal")
Poverty Probability Index (PPI) lookup table for Afghanistan
ppiAFG2012ppiAFG2012
A data frame with 7 columns and 101 rows:
scorePPI score
nlNational poverty line
nu150National poverty line (150%)
nu200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Afghanistan PPI table ppiAFG2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiAFG2012[ppiAFG2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiAFG2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiAFG2012[ppiAFG2012$score == ppiScore, "extreme"]# Access Afghanistan PPI table ppiAFG2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiAFG2012[ppiAFG2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiAFG2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiAFG2012[ppiAFG2012$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Angola
ppiAGO2015ppiAGO2015
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
# Access Angola PPI table ppiAGO2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiAGO2015[ppiAGO2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiAGO2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiAGO2015[ppiAGO2015$score == ppiScore, "extreme"]# Access Angola PPI table ppiAGO2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiAGO2015[ppiAGO2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiAGO2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiAGO2015[ppiAGO2015$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Benin
ppiBEN2012ppiBEN2012
A data frame with 7 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Benin PPI table ppiBEN2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBEN2012[ppiBEN2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBEN2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiBEN2012[ppiBEN2012$score == ppiScore, "nl100"]# Access Benin PPI table ppiBEN2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBEN2012[ppiBEN2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBEN2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiBEN2012[ppiBEN2012$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Benin for 2022 for 11 questions score card
ppiBEN2022_11qppiBEN2022_11q
A data frame with 14 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp215Below $2.15 per day purchasing power parity (2017)
ppp365Below $3.65 per day purchasing power parity (2017)
ppp685Below $6.85 per day purchasing power parity (2017)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Benin PPI table ppiBEN2022_11q # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBEN2022_11q[ppiBEN2022_11q$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBEN2022_11q, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiBEN2022_11q[ppiBEN2022_11q$score == ppiScore, "nl100"]# Access Benin PPI table ppiBEN2022_11q # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBEN2022_11q[ppiBEN2022_11q$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBEN2022_11q, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiBEN2022_11q[ppiBEN2022_11q$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Benin for 2022 for 6 questions score card
ppiBEN2022_6qppiBEN2022_6q
A data frame with 14 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp215Below $2.15 per day purchasing power parity (2017)
ppp365Below $3.65 per day purchasing power parity (2017)
ppp685Below $6.85 per day purchasing power parity (2017)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Benin PPI table ppiBEN2022_6q # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBEN2022_6q[ppiBEN2022_6q$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBEN2022_6q, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiBEN2022_6q[ppiBEN2022_6q$score == ppiScore, "nl100"]# Access Benin PPI table ppiBEN2022_6q # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBEN2022_6q[ppiBEN2022_6q$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBEN2022_6q, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiBEN2022_6q[ppiBEN2022_6q$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Burkina Faso
ppiBFA2011ppiBFA2011
A data frame with 8 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl50National poverty line (50%)
nl75National poverty line (75%)
nl150National poverty line (150%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
Poverty Probability Index (PPI) lookup table for Burkina Faso
ppiBFA2014ppiBFA2014
A data frame with 18 columns and 101 rows:
scorePPI score
foodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp125Below $1.00 per day purchasing power parity (2005)
ppp200Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp844Below $8.44 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
medianMedian poverty line
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile50Below 50th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Poverty Probability Index (PPI) lookup table for Burkina Faso
ppiBFA2017ppiBFA2017
A data frame with 15 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Burkina Faso PPI table ppiBFA2017 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBFA2017[ppiBFA2017$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBFA2017, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiBFA2017[ppiBFA2017$score == ppiScore, "nl100"]# Access Burkina Faso PPI table ppiBFA2017 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBFA2017[ppiBFA2017$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBFA2017, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiBFA2017[ppiBFA2017$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Burkina Faso for 2023
ppiBFA2023ppiBFA2023
A data frame with 14 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp215Below $1.25 per day purchasing power parity (2017)
ppp365Below $2.50 per day purchasing power parity (2017)
ppp685Below $5.00 per day purchasing power parity (2017)
ppp190Below $1.00 per day purchasing power parity (2011)
ppp320Below $1.90 per day purchasing power parity (2011)
ppp550Below $3.20 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Burkina Faso PPI table ppiBFA2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBFA2023[ppiBFA2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBFA2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiBFA2023[ppiBFA2023$score == ppiScore, "nl100"]# Access Burkina Faso PPI table ppiBFA2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBFA2023[ppiBFA2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBFA2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiBFA2023[ppiBFA2023$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Bangladesh
ppiBGD2013ppiBGD2013
A data frame with 10 columns and 101 rows:
scorePPI score
nlNational lower poverty line
nu100National upper poverty line (100%)
nu150National upper poverty line (150%)
nu200National upper poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp175Below $1.75 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Bangladesh PPI table ppiBGD2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBGD2013[ppiBGD2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBGD2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiBGD2013[ppiBGD2013$score == ppiScore, "extreme"]# Access Bangladesh PPI table ppiBGD2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBGD2013[ppiBGD2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBGD2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiBGD2013[ppiBGD2013$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Bolivia
ppiBOL2015ppiBOL2015
A data frame with 10 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp844Below $8.44 per day purchasing power parity (2005)
# Access Bolivia PPI table ppiBOL2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBOL2015[ppiBOL2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBOL2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the food # poverty line definition ppiScore <- 50 ppiBOL2015[ppiBOL2015$score == ppiScore, "nl100"]# Access Bolivia PPI table ppiBOL2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBOL2015[ppiBOL2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBOL2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the food # poverty line definition ppiScore <- 50 ppiBOL2015[ppiBOL2015$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Bolivia for 2023
ppiBOL2023ppiBOL2023
A data frame with 15 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl_extremeNational poverty line (extreme)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp190Below $1.25 per day purchasing power parity (2011)
ppp320Below $1.25 per day purchasing power parity (2011)
ppp550Below $2.00 per day purchasing power parity (2011)
ppp215Below $2.15 per day purchasing power parity (2017)
ppp365Below $3.65 per day purchasing power parity (2017)
ppp685Below $6.85 per day purchasing power parity (2017)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Bolivia PPI table ppiBOL2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBOL2023[ppiBOL2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBOL2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the food # poverty line definition ppiScore <- 50 ppiBOL2023[ppiBOL2023$score == ppiScore, "nl100"]# Access Bolivia PPI table ppiBOL2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBOL2023[ppiBOL2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBOL2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the food # poverty line definition ppiScore <- 50 ppiBOL2023[ppiBOL2023$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Brazil
ppiBRA2010ppiBRA2010
A data frame with 10 columns and 101 rows:
scorePPI score
belowHalfWageBelow the half minimum wage line
belowQtrWageBelow the quarter minimum wage line
belowOneWageBelow the one minimum wage line
belowTwoWageBelow the two minimum wage line
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
# Access Brazil PPI table ppiBRA2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBRA2010[ppiBRA2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBRA2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiBRA2010[ppiBRA2010$score == ppiScore, "extreme"]# Access Brazil PPI table ppiBRA2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiBRA2010[ppiBRA2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiBRA2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiBRA2010[ppiBRA2010$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Ivory Coast
ppiCIV2013ppiCIV2013
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
# Access Ivory Coast PPI table ppiCIV2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiCIV2013[ppiCIV2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiCIV2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiCIV2013[ppiCIV2013$score == ppiScore, "extreme"]# Access Ivory Coast PPI table ppiCIV2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiCIV2013[ppiCIV2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiCIV2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiCIV2013[ppiCIV2013$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Ivory Coast
ppiCIV2018ppiCIV2018
A data frame with 15 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp125Below $1.00 per day purchasing power parity (2011)
ppp250Below $1.90 per day purchasing power parity (2011)
ppp500Below $3.20 per day purchasing power parity (2011)
ppp100Below $5.50 per day purchasing power parity (2011)
ppp190Below $1.25 per day purchasing power parity (2005)
ppp320Below $2.50 per day purchasing power parity (2005)
ppp550Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Poverty Probability Index (PPI) lookup table for Cameroon
ppiCMR2013ppiCMR2013
A data frame with 8 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Cameroon PPI table ppiCMR2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiCMR2013[ppiCMR2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiCMR2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiCMR2013[ppiCMR2013$score == ppiScore, "extreme"]# Access Cameroon PPI table ppiCMR2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiCMR2013[ppiCMR2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiCMR2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiCMR2013[ppiCMR2013$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Colombia
ppiCOL2012ppiCOL2012
A data frame with 10 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
Poverty Probability Index (PPI) lookup table for Colombia
ppiCOL2012_appiCOL2012_a
A data frame with 12 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100 national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
Poverty Probability Index (PPI) lookup table for Colombia
ppiCOL2018ppiCOL2018
A data frame with 19 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
extremeExtreme national poverty line
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Poverty Probability Index (PPI) lookup table for Dominican Republic
ppiDOM2010ppiDOM2010
A data frame with 11 columns and 101 rows:
scorePPI score
nl50National poverty line (50%)
nl75National poverty line (75%)
nl100National poverty line (100%)
nl150National poverty line (150%)
extremeUSAID extreme poverty
nl200National poverty line (200%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
# Access Dominican Republic PPI table ppiDOM2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiDOM2010[ppiDOM2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiDOM2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiDOM2010[ppiDOM2010$score == ppiScore, "extreme"]# Access Dominican Republic PPI table ppiDOM2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiDOM2010[ppiDOM2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiDOM2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiDOM2010[ppiDOM2010$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Dominican Republic
ppiDOM2018ppiDOM2018
A data frame with 16 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodNational poverty line (150%)
nl150National poverty line (200%)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Poverty Probability Index (PPI) lookup table for Ecuador
ppiECU2015ppiECU2015
A data frame with 11 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp844Below $8.44 per day purchasing power parity (2005)
# Access Ecuador PPI table ppiECU2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiECU2015[ppiECU2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiECU2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiECU2015[ppiECU2015$score == ppiScore, "nl100"]# Access Ecuador PPI table ppiECU2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiECU2015[ppiECU2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiECU2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiECU2015[ppiECU2015$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Ecuador for 2022
ppiECU2022ppiECU2022
A data frame with 20 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl_extremeNational poverty line (extreme)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp215Below $2.15 per day purchasing power parity (2017)
ppp365Below $3.65 per day purchasing power parity (2017)
ppp685Below $6.85 per day purchasing power parity (2017)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Ecuador PPI table ppiECU2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiECU2015[ppiECU2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiECU2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiECU2015[ppiECU2015$score == ppiScore, "nl100"]# Access Ecuador PPI table ppiECU2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiECU2015[ppiECU2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiECU2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiECU2015[ppiECU2015$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Egypt
ppiEGY2010ppiEGY2010
A data frame with 8 columns and 101 rows:
scorePPI score
nu100National upper poverty line (100%)
nl100National lower poverty line (100%)
nlFoodFood poverty line
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
# Access Egypt PPI table ppiEGY2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiEGY2010[ppiEGY2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiEGY2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiEGY2010[ppiEGY2010$score == ppiScore, "extreme"]# Access Egypt PPI table ppiEGY2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiEGY2010[ppiEGY2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiEGY2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiEGY2010[ppiEGY2010$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Ethiopia
ppiETH2016ppiETH2016
A data frame with 21 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp100Below $1.00 per day purchasing power parity (2005)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp175Below $1.75 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
ppp380Below $3.80 per day purchasing power parity (2011)
ppp400Below $4.00 per day purchasing power parity (2011)
half100Poorest half below 100 national
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile50Below 50th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Ethiopia PPI table ppiETH2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiETH2016[ppiETH2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiETH2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiETH2016[ppiETH2016$score == ppiScore, "nl100"]# Access Ethiopia PPI table ppiETH2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiETH2016[ppiETH2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiETH2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiETH2016[ppiETH2016$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Ethiopia for 2023
ppiETH2023ppiETH2023
A data frame with 20 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl_extremeNational poverty line (extreme)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Ethiopia PPI table ppiETH2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiETH2023[ppiETH2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiETH2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiETH2023[ppiETH2023$score == ppiScore, "nl100"]# Access Ethiopia PPI table ppiETH2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiETH2023[ppiETH2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiETH2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiETH2023[ppiETH2023$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Fiji
ppiFJI2014ppiFJI2014
A data frame with 8 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
medianPoorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Fiji PPI table ppiFJI2014 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiFJI2014[ppiFJI2014$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiFJI2014, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiFJI2014[ppiFJI2014$score == ppiScore, "nl100"]# Access Fiji PPI table ppiFJI2014 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiFJI2014[ppiFJI2014$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiFJI2014, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiFJI2014[ppiFJI2014$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Ghana based on legacy definitions
ppiGHA2015ppiGHA2015
A data frame with 8 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $2.75 per day purchasing power parity (2005)
# Access Ghana PPI table ppiGHA2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGHA2015[ppiGHA2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGHA2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiGHA2015[ppiGHA2015$score == ppiScore, "nl100"]# Access Ghana PPI table ppiGHA2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGHA2015[ppiGHA2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGHA2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiGHA2015[ppiGHA2015$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Ghana using poverty definitions deflated with Ghana's CPI
ppiGHA2015_appiGHA2015_a
A data frame with 13 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
# Access Ghana PPI table ppiGHA2015_a # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGHA2015_a[ppiGHA2015_a$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGHA2015_a, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiGHA2015_a[ppiGHA2015_a$score == ppiScore, "nl100"]# Access Ghana PPI table ppiGHA2015_a # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGHA2015_a[ppiGHA2015_a$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGHA2015_a, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiGHA2015_a[ppiGHA2015_a$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Ghana using poverty definitions deflated with the change in 100% of national poverty line
ppiGHA2015_bppiGHA2015_b
A data frame with 8 columns and 101 rows:
scorePPI score
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
# Access Ghana PPI table ppiGHA2015_b # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGHA2015_b[ppiGHA2015_b$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGHA2015_b, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the below $1.25 # per day purchasing power parity (2005) ppiScore <- 50 ppiGHA2015_b[ppiGHA2015_b$score == ppiScore, "ppp125"]# Access Ghana PPI table ppiGHA2015_b # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGHA2015_b[ppiGHA2015_b$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGHA2015_b, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the below $1.25 # per day purchasing power parity (2005) ppiScore <- 50 ppiGHA2015_b[ppiGHA2015_b$score == ppiScore, "ppp125"]
Poverty Probability Index (PPI) lookup table for Ghana
ppiGHA2019ppiGHA2019
A data frame with 20 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
extremeExtreme poverty line
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 50th percentile poverty line
percentile80Below 60th percentile poverty line
# Access Ghana PPI table ppiGHA2019 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGHA2019[ppiGHA2019$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGHA2019, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line is used ppiScore <- 50 ppiGHA2019[ppiGHA2019$score == ppiScore, "nl100"]# Access Ghana PPI table ppiGHA2019 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGHA2019[ppiGHA2019$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGHA2019, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line is used ppiScore <- 50 ppiGHA2019[ppiGHA2019$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Guatemala
ppiGTM2016ppiGTM2016
A data frame with 17 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile50Below 50th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Guatemala PPI table ppiGTM2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGTM2016[ppiGTM2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGTM2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiGTM2016[ppiGTM2016$score == ppiScore, "nl100"]# Access Guatemala PPI table ppiGTM2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGTM2016[ppiGTM2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGTM2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiGTM2016[ppiGTM2016$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Guatemala for 2023
ppiGTM2023ppiGTM2023
A data frame with 17 columns and 101 rows:
scorePPI score
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp215Below $2.15 per day purchasing power parity (2017)
ppp365Below $3.65 per day purchasing power parity (2017)
ppp685Below $6.85 per day purchasing power parity (2017)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Guatemala PPI table ppiGTM2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGTM2023[ppiGTM2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGTM2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiGTM2023[ppiGTM2023$score == ppiScore, "ppp190"]# Access Guatemala PPI table ppiGTM2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiGTM2023[ppiGTM2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiGTM2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiGTM2023[ppiGTM2023$score == ppiScore, "ppp190"]
Poverty Probability Index (PPI) lookup table for Honduras
ppiHND2010ppiHND2010
A data frame with 7 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
# Access Honduras PPI table ppiHND2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiHND2010[ppiHND2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiHND2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiHND2010[ppiHND2010$score == ppiScore, "extreme"]# Access Honduras PPI table ppiHND2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiHND2010[ppiHND2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiHND2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiHND2010[ppiHND2010$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Honduras for 2023
ppiHND2023ppiHND2023
A data frame with 18 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl_extremeNational poverty line (extreme)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Honduras PPI table ppiHND2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiHND2023[ppiHND2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiHND2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiHND2023[ppiHND2023$score == ppiScore, "nl_extreme"]# Access Honduras PPI table ppiHND2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiHND2023[ppiHND2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiHND2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiHND2023[ppiHND2023$score == ppiScore, "nl_extreme"]
Poverty Probability Index (PPI) lookup table for Haiti
ppiHTI2016ppiHTI2016
A data frame with 10 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
# Access Haiti PPI table ppiHTI2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiHTI2016[ppiHTI2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiHTI2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiHTI2016[ppiHTI2016$score == ppiScore, "nl100"]# Access Haiti PPI table ppiHTI2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiHTI2016[ppiHTI2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiHTI2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiHTI2016[ppiHTI2016$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Indonesia using legacy poverty definitions
ppiIDN2012ppiIDN2012
A data frame with 4 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Indonesia PPI table ppiIDN2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIDN2012[ppiIDN2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIDN2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiIDN2012[ppiIDN2012$score == ppiScore, "nl100"]# Access Indonesia PPI table ppiIDN2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIDN2012[ppiIDN2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIDN2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiIDN2012[ppiIDN2012$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Indonesia using new poverty definitions
ppiIDN2012_appiIDN2012_a
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
# Access Indonesia PPI table ppiIDN2012_a # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIDN2012_a[ppiIDN2012_a$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIDN2012_a, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiIDN2012_a[ppiIDN2012_a$score == ppiScore, "nl100"]# Access Indonesia PPI table ppiIDN2012_a # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIDN2012_a[ppiIDN2012_a$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIDN2012_a, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiIDN2012_a[ppiIDN2012_a$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Indonesia
ppiIDN2020ppiIDN2020
A data frame with 20 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
extremeExtreme poverty line
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 50th percentile poverty line
percentile80Below 60th percentile poverty line
# Access Indonesia PPI table ppiIDN2020 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIDN2020[ppiIDN2020$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIDN2020, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiIDN2020[ppiIDN2020$score == ppiScore, "nl100"]# Access Indonesia PPI table ppiIDN2020 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIDN2020[ppiIDN2020$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIDN2020, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiIDN2020[ppiIDN2020$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Indonesia for 2023
ppiIDN2023ppiIDN2023
A data frame with 10 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
ppp365Below $3.65 per day purchasing power parity (2017)
ppp685Below $6.85 per day purchasing power parity (2017)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 50th percentile poverty line
percentile80Below 60th percentile poverty line
# Access Indonesia PPI table ppiIDN2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIDN2023[ppiIDN2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIDN2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiIDN2023[ppiIDN2023$score == ppiScore, "nl100"]# Access Indonesia PPI table ppiIDN2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIDN2023[ppiIDN2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIDN2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiIDN2023[ppiIDN2023$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for India using r59 poverty definitions
ppiIND2016_r59ppiIND2016_r59
A data frame with 4 columns and 101 rows:
scorePPI score
saxenaNational saxena
ppp108Below $1.08 per day purchasing power parity (1993)
ppp216Below $2.16 per day purchasing power parity (1993)
# Access India PPI table ppiIND2016_r59 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIND2016_r59[ppiIND2016_r59$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIND2016_r59, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the saxena # poverty definition ppiScore <- 50 ppiIND2016_r59[ppiIND2016_r59$score == ppiScore, "saxena"]# Access India PPI table ppiIND2016_r59 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIND2016_r59[ppiIND2016_r59$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIND2016_r59, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the saxena # poverty definition ppiScore <- 50 ppiIND2016_r59[ppiIND2016_r59$score == ppiScore, "saxena"]
Poverty Probability Index (PPI) lookup table for India using r62 poverty definitions
ppiIND2016_r62ppiIND2016_r62
A data frame with 7 columns and 101 rows:
scorePPI score
saxenaNational saxena
ppp108Below $1.08 per day purchasing power parity (1993)
ppp81Below $0.81 per day purchasing power parity (1993)
ppp135Below $1.35 per day purchasing power parity (1993)
ppp162Below $1.62 per day purchasing power parity (1993)
ppp216Below $2.16 per day purchasing power parity (1993)
# Access India PPI table ppiIND2016_r62 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIND2016_r62[ppiIND2016_r62$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIND2016_r62, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # saxena poverty definition ppiScore <- 50 ppiIND2016_r62[ppiIND2016_r62$score == ppiScore, "saxena"]# Access India PPI table ppiIND2016_r62 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIND2016_r62[ppiIND2016_r62$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIND2016_r62, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # saxena poverty definition ppiScore <- 50 ppiIND2016_r62[ppiIND2016_r62$score == ppiScore, "saxena"]
Poverty Probability Index (PPI) lookup table for India using r66 poverty definitions
ppiIND2016_r66ppiIND2016_r66
A data frame with 8 columns and 101 rows:
scorePPI score
tendulkarNational tendulkar
tendulkar100National tendulkar (100%)
tendulkar150National tendulkar (150%)
tendulkar200National tendulkar (200%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp188Below $1.88 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access India PPI table ppiIND2016_r66 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIND2016_r66[ppiIND2016_r66$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIND2016_r66, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # tendulkar poverty definition ppiScore <- 50 ppiIND2016_r66[ppiIND2016_r66$score == ppiScore, "tendulkar"]# Access India PPI table ppiIND2016_r66 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIND2016_r66[ppiIND2016_r66$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIND2016_r66, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # tendulkar poverty definition ppiScore <- 50 ppiIND2016_r66[ppiIND2016_r66$score == ppiScore, "tendulkar"]
Poverty Probability Index (PPI) lookup table for India using r68 poverty definitions
ppiIND2016_r68ppiIND2016_r68
A data frame with 16 columns and 101 rows:
scorePPI score
rangarajan100National rangarajan (100%)
rangarajan150National rangarajan (150%)
rangarajan200National rangarajan (200%)
half100Poorest half below 100% national
rbiUrbanRBI urban
rbiRuralRBI rural
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
ppp380Below $3.80 per day purchasing power parity (2011)
ppp400Below $4.00 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile50Below 50th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access India PPI table ppiIND2016_r68 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIND2016_r68[ppiIND2016_r68$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIND2016_r68, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # rangarajan poverty definition ppiScore <- 50 ppiIND2016_r68[ppiIND2016_r68$score == ppiScore, "rangarajan100"]# Access India PPI table ppiIND2016_r68 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiIND2016_r68[ppiIND2016_r68$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIND2016_r68, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # rangarajan poverty definition ppiScore <- 50 ppiIND2016_r68[ppiIND2016_r68$score == ppiScore, "rangarajan100"]
Poverty Probability Index (PPI) lookup table for Jordan
ppiJOR2010ppiJOR2010
A data frame with 10 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
nl250National poverty line (250%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
# Access Jordan PPI table ppiJOR2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiJOR2010[ppiJOR2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiJOR2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiJOR2010[ppiJOR2010$score == ppiScore, "extreme"]# Access Jordan PPI table ppiJOR2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiJOR2010[ppiJOR2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiJOR2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiJOR2010[ppiJOR2010$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Kenya
ppiKEN2011ppiKEN2011
A data frame with 11 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp400Below $4.00 per day purchasing power parity (2005)
ppp844Below $8.44 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
# Access Kenya PPI table ppiKEN2011 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKEN2011[ppiKEN2011$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKEN2011, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiKEN2011[ppiKEN2011$score == ppiScore, "extreme"]# Access Kenya PPI table ppiKEN2011 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKEN2011[ppiKEN2011$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKEN2011, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiKEN2011[ppiKEN2011$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Kenya
ppiKEN2018ppiKEN2018
A data frame with 17 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 50th percentile poverty line
percentile80Below 60th percentile poverty line
Poverty Probability Index (PPI) lookup table for Kyrgyzstan
ppiKGZ2015ppiKGZ2015
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
medianPoorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
# Access Kyrgyzstan PPI table ppiKGZ2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKGZ2015[ppiKGZ2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKGZ2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiKGZ2015[ppiKGZ2015$score == ppiScore, "nl100"]# Access Kyrgyzstan PPI table ppiKGZ2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKGZ2015[ppiKGZ2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKGZ2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiKGZ2015[ppiKGZ2015$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Cambodia
ppiKHM2015ppiKHM2015
A data frame with 6 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp125Below $1.25 per day purchasing power poverty (2005)
ppp250Below $2.50 per day purchasing power poverty (2005)
# Access Cambodia PPI table ppiKHM2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKHM2015[ppiKHM2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKHM2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiKHM2015[ppiKHM2015$score == ppiScore, "nl100"]# Access Cambodia PPI table ppiKHM2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKHM2015[ppiKHM2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKHM2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiKHM2015[ppiKHM2015$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Cambodia
ppiKHM2015_govppiKHM2015_gov
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
medianMedian poverty line
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
# Access Cambodia PPI table ppiKHM2015_gov # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKHM2015_gov[ppiKHM2015_gov$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKHM2015_gov, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiKHM2015_gov[ppiKHM2015_gov$score == ppiScore, "nl100"]# Access Cambodia PPI table ppiKHM2015_gov # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKHM2015_gov[ppiKHM2015_gov$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKHM2015_gov, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiKHM2015_gov[ppiKHM2015_gov$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Cambodia
ppiKHM2015_wbppiKHM2015_wb
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
medianMedian poverty line
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
# Access Cambodia PPI table ppiKHM2015_wb # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKHM2015_wb[ppiKHM2015_wb$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKHM2015_wb, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiKHM2015_wb[ppiKHM2015_wb$score == ppiScore, "nl100"]# Access Cambodia PPI table ppiKHM2015_wb # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKHM2015_wb[ppiKHM2015_wb$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKHM2015_wb, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiKHM2015_wb[ppiKHM2015_wb$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Cambodia for 2023
ppiKHM2023ppiKHM2023
A data frame with 14 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp550Below $3.20 per day purchasing power parity (2011)
ppp800Below $3.20 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
ppp685Below $6.85 per day purchasing power parity (2017)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Cambodia PPI table ppiKHM2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKHM2023[ppiKHM2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKHM2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiKHM2023[ppiKHM2023$score == ppiScore, "nl100"]# Access Cambodia PPI table ppiKHM2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiKHM2023[ppiKHM2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiKHM2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiKHM2023[ppiKHM2023$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Sri Lanka
ppiLKA2016ppiLKA2016
A data frame with 16 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile50Below 50th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Sri Lanka PPI table ppiLKA2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiLKA2016[ppiLKA2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiLKA2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiLKA2016[ppiLKA2016$score == ppiScore, "nl100"]# Access Sri Lanka PPI table ppiLKA2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiLKA2016[ppiLKA2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiLKA2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiLKA2016[ppiLKA2016$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Morocco
ppiMAR2013ppiMAR2013
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
# Access Morocco PPI table ppiMAR2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMAR2013[ppiMAR2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMAR2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMAR2013[ppiMAR2013$score == ppiScore, "nl100"]# Access Morocco PPI table ppiMAR2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMAR2013[ppiMAR2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMAR2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMAR2013[ppiMAR2013$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Madagascar
ppiMDG2015ppiMDG2015
A data frame with 9 columns and 101 rows:
scorePPI score
nl100Food poverty line
nl150National poverty line (100%)
nl200National poverty line (150%)
medianNational poverty line (200%)
ppp125Poorest half below 100% national
ppp200Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.00 per day purchasing power parity (2005)
ppp500Below $2.50 per day purchasing power parity (2005)
# Access Madagascar PPI table ppiMDG2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMDG2015[ppiMDG2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMDG2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMDG2015[ppiMDG2015$score == ppiScore, "nl100"]# Access Madagascar PPI table ppiMDG2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMDG2015[ppiMDG2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMDG2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMDG2015[ppiMDG2015$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Mexico using legacy definitions
ppiMEX2017ppiMEX2017
A data frame with 8 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nlCapabilityCapabilities
nl100National poverty line (100%)
nl125National poverty line (125%)
nl150National poverty line (150%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Mexico PPI table ppiMEX2017 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMEX2017[ppiMEX2017$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMEX2017, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMEX2017[ppiMEX2017$score == ppiScore, "nl100"]# Access Mexico PPI table ppiMEX2017 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMEX2017[ppiMEX2017$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMEX2017, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMEX2017[ppiMEX2017$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Mexico using new poverty definitions
ppiMEX2017_appiMEX2017_a
A data frame with 17 columns and 101 rows:
scorePPI score
nl100National lower poverty line (100%)
nu100National upper poverty line (100%)
nu150National upper poverty line (150%)
nu200National upper poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile50Below 50th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Mexico PPI table ppiMEX2017_a # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMEX2017_a[ppiMEX2017_a$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMEX2017_a, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMEX2017_a[ppiMEX2017_a$score == ppiScore, "nl100"]# Access Mexico PPI table ppiMEX2017_a # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMEX2017_a[ppiMEX2017_a$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMEX2017_a, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMEX2017_a[ppiMEX2017_a$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Mali
ppiMLI2010ppiMLI2010
A data frame with 6 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Mali PPI table ppiMLI2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMLI2010[ppiMLI2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMLI2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMLI2010[ppiMLI2010$score == ppiScore, "nl100"]# Access Mali PPI table ppiMLI2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMLI2010[ppiMLI2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMLI2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMLI2010[ppiMLI2010$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Myanmar
ppiMMR2012ppiMMR2012
A data frame with 8 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Myanmar PPI table ppiMMR2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMMR2012[ppiMMR2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMMR2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMMR2012[ppiMMR2012$score == ppiScore, "nl100"]# Access Myanmar PPI table ppiMMR2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMMR2012[ppiMMR2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMMR2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMMR2012[ppiMMR2012$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Myanmar
ppiMMR2019ppiMMR2019
A data frame with 20 columns and 101 rows:
scorePPI score
nl100National poverty line (100)
extremeNational poverty line (150)
nl150National poverty line (200)
nl200Below $1.90 per day purchasing power parity (2011)
ppp100Below $3.20 per day purchasing power parity (2011)
ppp190Below $5.50 per day purchasing power parity (2011)
ppp320Below $8.00 per day purchasing power parity (2011)
ppp550Below $11.00 per day purchasing power parity (2011)
ppp800Below $15.00 per day purchasing power parity (2011)
ppp1100Below $21.70 per day purchasing power parity (2011)
ppp1500Below 20th percentile poverty line
ppp2170Below 40th percentile poverty line
ppp125Below 50th percentile poverty line
ppp250Below 60th percentile poverty line
ppp500Below 80th percentile poverty line
percentile20NA
percentile40NA
percentile60NA
percentile80NA
# Access Myanmar PPI table ppiMMR2019 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMMR2019[ppiMMR2019$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMMR2019, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiMMR2019[ppiMMR2019$score == ppiScore, "extreme"]# Access Myanmar PPI table ppiMMR2019 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMMR2019[ppiMMR2019$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMMR2019, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiMMR2019[ppiMMR2019$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Mongolia
ppiMNG2016ppiMNG2016
A data frame with 18 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
ppp380Below $3.80 per day purchasing power parity (2011)
ppp400Below $4.00 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile50Below 50th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Mongolia PPI table ppiMNG2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMNG2016[ppiMNG2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMNG2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMNG2016[ppiMNG2016$score == ppiScore, "nl100"]# Access Mongolia PPI table ppiMNG2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMNG2016[ppiMNG2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMNG2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMNG2016[ppiMNG2016$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Mozambique
ppiMOZ2013ppiMOZ2013
A data frame with 7 columns and 101 rows:
scorePPI score
ppp100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Mozambique PPI table ppiMOZ2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMOZ2013[ppiMOZ2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMOZ2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMOZ2013[ppiMOZ2013$score == ppiScore, "nl100"]# Access Mozambique PPI table ppiMOZ2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMOZ2013[ppiMOZ2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMOZ2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMOZ2013[ppiMOZ2013$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Mozambique
ppiMOZ2019ppiMOZ2019
A data frame with 15 columns and 101 rows:
scorePPI score
nl100National poverty line (100)
nl150National poverty line (150)
nl200National poverty line (200)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 50th percentile poverty line
percentile80Below 60th percentile poverty line
# Access Mozambique PPI table ppiMOZ2019 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMOZ2019[ppiMOZ2019$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMOZ2019, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line is used ppiScore <- 50 ppiMOZ2019[ppiMOZ2019$score == ppiScore, "nl100"]# Access Mozambique PPI table ppiMOZ2019 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMOZ2019[ppiMOZ2019$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMOZ2019, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line is used ppiScore <- 50 ppiMOZ2019[ppiMOZ2019$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Malawi using legacy poverty definitions
ppiMWI2015ppiMWI2015
A data frame with 3 columns and 101 rows:
scorePPI score
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Malawi PPI table ppiMWI2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMWI2015[ppiMWI2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMWI2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, below $1.25 # purchasing power parity (2005) ppiScore <- 50 ppiMWI2015[ppiMWI2015$score == ppiScore, "ppp125"]# Access Malawi PPI table ppiMWI2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMWI2015[ppiMWI2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMWI2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, below $1.25 # purchasing power parity (2005) ppiScore <- 50 ppiMWI2015[ppiMWI2015$score == ppiScore, "ppp125"]
Poverty Probability Index (PPI) lookup table for Malawi using government poverty definitions
ppiMWI2015_govppiMWI2015_gov
A data frame with 14 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp844Below $8.44 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
ppp1000Below $10.00 per day purchasing power parity (2011)
# Access Malawi PPI table ppiMWI2015_gov # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMWI2015_gov[ppiMWI2015_gov$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMWI2015_gov, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMWI2015_gov[ppiMWI2015_gov$score == ppiScore, "nl100"]# Access Malawi PPI table ppiMWI2015_gov # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMWI2015_gov[ppiMWI2015_gov$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMWI2015_gov, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMWI2015_gov[ppiMWI2015_gov$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Malawi using PBM poverty definitions
ppiMWI2015_pbmppiMWI2015_pbm
A data frame with 13 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp844Below $8.44 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
# Access Malawi PPI table ppiMWI2015_pbm # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMWI2015_pbm[ppiMWI2015_pbm$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMWI2015_pbm, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMWI2015_pbm[ppiMWI2015_pbm$score == ppiScore, "nl100"]# Access Malawi PPI table ppiMWI2015_pbm # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMWI2015_pbm[ppiMWI2015_pbm$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMWI2015_pbm, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiMWI2015_pbm[ppiMWI2015_pbm$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Malawi
ppiMWI2020ppiMWI2020
A data frame with 16 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
extremeExtreme poverty line
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 50th percentile poverty line
percentile80Below 60th percentile poverty line
# Access Malawi PPI table ppiMWI2020 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMWI2020[ppiMWI2020$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMWI2020, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiMWI2020[ppiMWI2020$score == ppiScore, "nl100"]# Access Malawi PPI table ppiMWI2020 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMWI2020[ppiMWI2020$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMWI2020, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiMWI2020[ppiMWI2020$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Malawi for 2023
ppiMWI2023ppiMWI2023
A data frame with 13 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
foodFood poverty line
ppp215Below $2.15 per day purchasing power parity (2017)
ppp365Below $3.65 per day purchasing power parity (2017)
ppp685Below $6.85 per day purchasing power parity (2017)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 50th percentile poverty line
percentile80Below 60th percentile poverty line
# Access Malawi PPI table ppiMWI2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMWI2023[ppiMWI2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMWI2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiMWI2023[ppiMWI2023$score == ppiScore, "nl100"]# Access Malawi PPI table ppiMWI2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMWI2023[ppiMWI2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMWI2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiMWI2023[ppiMWI2023$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Namibia
ppiNAM2013ppiNAM2013
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National lower poverty line (100%)
nu100National upper poverty line (100%)
nu150National upper poverty line (150%)
nu200National upper poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Namibia PPI table ppiNAM2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNAM2013[ppiNAM2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNAM2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNAM2013[ppiNAM2013$score == ppiScore, "nl100"]# Access Namibia PPI table ppiNAM2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNAM2013[ppiNAM2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNAM2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNAM2013[ppiNAM2013$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Niger
ppiNER2013ppiNER2013
A data frame with 9 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Niger PPI table ppiNER2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNER2013[ppiNER2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNER2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNER2013[ppiNER2013$score == ppiScore, "nl100"]# Access Niger PPI table ppiNER2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNER2013[ppiNER2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNER2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNER2013[ppiNER2013$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Nigeria
ppiNGA2015ppiNGA2015
A data frame with 13 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp400Below $4.00 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
# Access Nigeria PPI table ppiNGA2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNGA2015[ppiNGA2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNGA2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNGA2015[ppiNGA2015$score == ppiScore, "nl100"]# Access Nigeria PPI table ppiNGA2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNGA2015[ppiNGA2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNGA2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNGA2015[ppiNGA2015$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Nicaragua
ppiNIC2013ppiNIC2013
A data frame with 10 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp800Below $8.00 per day purchasing power parity (2005)
# Access Nicaragua PPI table ppiNIC2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNIC2013[ppiNIC2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNIC2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNIC2013[ppiNIC2013$score == ppiScore, "nl100"]# Access Nicaragua PPI table ppiNIC2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNIC2013[ppiNIC2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNIC2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNIC2013[ppiNIC2013$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Nepal using legacy poverty definitions
ppiNPL2013ppiNPL2013
A data frame with 4 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Nepal PPI table ppiNPL2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNPL2013[ppiNPL2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNPL2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNPL2013[ppiNPL2013$score == ppiScore, "nl100"]# Access Nepal PPI table ppiNPL2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNPL2013[ppiNPL2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNPL2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNPL2013[ppiNPL2013$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Nepal using new poverty definitions
ppiNPL2013_appiNPL2013_a
A data frame with 9 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Nepal PPI table ppiNPL2013_a # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNPL2013_a[ppiNPL2013_a$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNPL2013_a, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNPL2013_a[ppiNPL2013_a$score == ppiScore, "nl100"]# Access Nepal PPI table ppiNPL2013_a # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiNPL2013_a[ppiNPL2013_a$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiNPL2013_a, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiNPL2013_a[ppiNPL2013_a$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Pakistan
ppiPAK2009ppiPAK2009
A data frame with 10 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl50National poverty line (50%)
nl75National poverty line (75%)
nl125National poverty line (125%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Poorest half below 100 national
ppp250Below $1.25 per day purchasing power parity (2005)
ppp375Below $2.50 per day purchasing power parity (2005)
# Access Pakistan PPI table ppiPAK2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPAK2009[ppiPAK2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPAK2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPAK2009[ppiPAK2009$score == ppiScore, "nl100"]# Access Pakistan PPI table ppiPAK2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPAK2009[ppiPAK2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPAK2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPAK2009[ppiPAK2009$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Peru
ppiPER2012ppiPER2012
A data frame with 9 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
# Access Peru PPI table ppiPER2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPER2012[ppiPER2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPER2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPER2012[ppiPER2012$score == ppiScore, "nl100"]# Access Peru PPI table ppiPER2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPER2012[ppiPER2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPER2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPER2012[ppiPER2012$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Peru
ppiPER2018ppiPER2018
A data frame with 19 columns and 101 rows:
scorePPI score
extremeExtreme national poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Poverty Probability Index (PPI) lookup table for Philippines using legacy poverty definitions
ppiPHL2014ppiPHL2014
A data frame with 6 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp432Below $4.32 per day purchasing power parity (1993)
# Access Philippines PPI table ppiPHL2014 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPHL2014[ppiPHL2014$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPHL2014, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPHL2014[ppiPHL2014$score == ppiScore, "nl100"]# Access Philippines PPI table ppiPHL2014 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPHL2014[ppiPHL2014$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPHL2014, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPHL2014[ppiPHL2014$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Philippines using new poverty definitions
ppiPHL2014_appiPHL2014_a
A data frame with 11 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
medianPoorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
# Access Philippines PPI table ppiPHL2014_a # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPHL2014_a[ppiPHL2014_a$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPHL2014_a, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPHL2014_a[ppiPHL2014_a$score == ppiScore, "nl100"]# Access Philippines PPI table ppiPHL2014_a # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPHL2014_a[ppiPHL2014_a$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPHL2014_a, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPHL2014_a[ppiPHL2014_a$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Philippines
ppiPHL2018ppiPHL2018
A data frame with 18 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
foodFood poverty line
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Poverty Probability Index (PPI) lookup table for Philippines for 2023
ppiPHL2023ppiPHL2023
A data frame with 13 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
foodFood poverty line
ppp215Below $2.15 per day purchasing power parity (2017)
ppp365Below $3.65 per day purchasing power parity (2017)
ppp685Below $6.85 per day purchasing power parity (2017)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Poverty Probability Index (PPI) lookup table for Papua New Guinea 2023
ppiPNG2023ppiPNG2023
A data frame with 9 columns and 101 rows:
scorePPI score
percentile20_wiBelow 20th percentile wealth index
percentile40_wiBelow 40th percentile wealth index
percentile60_wiBelow 60th percentile wealth index
percentile80_wiBelow 80th percentile wealth index
percentile20_wi_urBelow 20th percentile wealth index urban/rural
percentile40_wi_urBelow 40th percentile wealth index urban/rural
percentile60_wi_urBelow 60th percentile wealth index urban/rural
percentile80_wi_urBelow 80th percentile wealth index urban/rural
# Access Papua New Guinea PPI table ppiPNG2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPNG2023[ppiPNG2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPNG2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiPNG2023[ppiPNG2023$score == ppiScore, "percentile20_wi"]# Access Papua New Guinea PPI table ppiPNG2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPNG2023[ppiPNG2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPNG2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiPNG2023[ppiPNG2023$score == ppiScore, "percentile20_wi"]
Poverty Probability Index (PPI) lookup table for Paraguay
ppiPRY2012ppiPRY2012
A data frame with 8 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Paraguay PPI table ppiPRY2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPRY2012[ppiPRY2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPRY2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPRY2012[ppiPRY2012$score == ppiScore, "nl100"]# Access Paraguay PPI table ppiPRY2012 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPRY2012[ppiPRY2012$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPRY2012, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPRY2012[ppiPRY2012$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Palestine
ppiPSE2014ppiPSE2014
A data frame with 11 columns and 101 rows:
scorePPI score
deepDeep poverty
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
medianPoorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
# Access Palestine PPI table ppiPSE2014 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPSE2014[ppiPSE2014$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPSE2014, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPSE2014[ppiPSE2014$score == ppiScore, "nl100"]# Access Palestine PPI table ppiPSE2014 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPSE2014[ppiPSE2014$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPSE2014, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiPSE2014[ppiPSE2014$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Romania
ppiROU2009ppiROU2009
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
laekenLaeken poverty line
# Access Romania PPI table ppiROU2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiROU2009[ppiROU2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiROU2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiROU2009[ppiROU2009$score == ppiScore, "nl100"]# Access Romania PPI table ppiROU2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiROU2009[ppiROU2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiROU2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiROU2009[ppiROU2009$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Russia
ppiRUS2010ppiRUS2010
A data frame with 4 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
extremeUSAID extreme poverty
ppp625Below $6.25 per day purchasing power parity (2005)
# Access Russia PPI table ppiRUS2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiRUS2010[ppiRUS2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiRUS2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiRUS2010[ppiRUS2010$score == ppiScore, "nl100"]# Access Russia PPI table ppiRUS2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiRUS2010[ppiRUS2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiRUS2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiRUS2010[ppiRUS2010$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Rwanda
ppiRWA2016ppiRWA2016
A data frame with 11 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp844Below $8.44 per day purchasing power parity (2005)
# Access Rwanda PPI table ppiRWA2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiRWA2016[ppiRWA2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiRWA2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiRWA2016[ppiRWA2016$score == ppiScore, "nl100"]# Access Rwanda PPI table ppiRWA2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiRWA2016[ppiRWA2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiRWA2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiRWA2016[ppiRWA2016$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Rwanda
ppiRWA2019ppiRWA2019
A data frame with 20 columns and 101 rows:
scorePPI score
nl100National poverty line (100)
extremeNational poverty line (150)
nl150National poverty line (200)
nl200Below $1.90 per day purchasing power parity (2011)
ppp100Below $3.20 per day purchasing power parity (2011)
ppp190Below $5.50 per day purchasing power parity (2011)
ppp320Below $8.00 per day purchasing power parity (2011)
ppp550Below $11.00 per day purchasing power parity (2011)
ppp800Below $15.00 per day purchasing power parity (2011)
ppp1100Below $21.70 per day purchasing power parity (2011)
ppp1500Below 20th percentile poverty line
ppp2170Below 40th percentile poverty line
ppp125Below 50th percentile poverty line
ppp250Below 60th percentile poverty line
ppp500Below 80th percentile poverty line
percentile20NA
percentile40NA
percentile60NA
percentile80NA
# Access Rwanda PPI table ppiRWA2019 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiRWA2019[ppiRWA2019$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiRWA2019, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line is used ppiScore <- 50 ppiRWA2019[ppiRWA2019$score == ppiScore, "nl100"]# Access Rwanda PPI table ppiRWA2019 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiRWA2019[ppiRWA2019$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiRWA2019, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line is used ppiScore <- 50 ppiRWA2019[ppiRWA2019$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Senegal
ppiSEN2009ppiSEN2009
A data frame with 11 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
extremeUSAID extreme poverty
nl75National poverty line (75%)
nl125National poverty line (125%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
# Access Senegal PPI table ppiSEN2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiSEN2009[ppiSEN2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiSEN2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiSEN2009[ppiSEN2009$score == ppiScore, "nl100"]# Access Senegal PPI table ppiSEN2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiSEN2009[ppiSEN2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiSEN2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiSEN2009[ppiSEN2009$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Senegal
ppiSEN2018ppiSEN2018
A data frame with 16 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Poverty Probability Index (PPI) lookup table for Sierra Leone
ppiSLE2011ppiSLE2011
A data frame with 8 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
nl75National poverty line (75%)
nl150National poverty line (150%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Sierra Leone PPI table ppiSLE2011 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiSLE2011[ppiSLE2011$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiSLE2011, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiSLE2011[ppiSLE2011$score == ppiScore, "nl100"]# Access Sierra Leone PPI table ppiSLE2011 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiSLE2011[ppiSLE2011$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiSLE2011, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiSLE2011[ppiSLE2011$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for El Salvador
ppiSLV2010ppiSLV2010
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
# Access El Salvador PPI table ppiSLV2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiSLV2010[ppiSLV2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiSLV2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiSLV2010[ppiSLV2010$score == ppiScore, "extreme"]# Access El Salvador PPI table ppiSLV2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiSLV2010[ppiSLV2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiSLV2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiSLV2010[ppiSLV2010$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for El Salvador for 2021
ppiSLV2021ppiSLV2021
A data frame with 21 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl_extremeNational poverty line (extreme)
ppp215Below $2.15 per day purchasing power parity (2017)
ppp365Below $3.65 per day purchasing power parity (2017)
ppp685Below $6.85 per day purchasing power parity (2017)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access El Salvador PPI table ppiSLV2021 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiSLV2021[ppiSLV2021$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiSLV2021, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiSLV2021[ppiSLV2021$score == ppiScore, "nl_extreme"]# Access El Salvador PPI table ppiSLV2021 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiSLV2021[ppiSLV2021$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiSLV2021, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiSLV2021[ppiSLV2021$score == ppiScore, "nl_extreme"]
Poverty Probability Index (PPI) lookup table for Syria
ppiSYR2010ppiSYR2010
A data frame with 8 columns and 101 rows:
scorePPI score
nu100National upper poverty line (100%)
nl100National lower poverty line (100%)
nu150National upper poverty line (150%)
nu200National upper poverty line (200%)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
# Access Syria PPI table ppiSYR2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiSYR2010[ppiSYR2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiSYR2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiSYR2010[ppiSYR2010$score == ppiScore, "nl100"]# Access Syria PPI table ppiSYR2010 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiSYR2010[ppiSYR2010$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiSYR2010, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiSYR2010[ppiSYR2010$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Togo
ppiTGO2018ppiTGO2018
A data frame with 15 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Poverty Probability Index (PPI) lookup table for Togo for 2023
ppiTGO2023ppiTGO2023
A data frame with 14 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp215Below $2.15 per day purchasing power parity (2017)
ppp365Below $3.65 per day purchasing power parity (2017)
ppp685Below $6.85 per day purchasing power parity (2017)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Poverty Probability Index (PPI) lookup table for Tajikistan
ppiTJK2015ppiTJK2015
A data frame with 9 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
medianPoorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Tajikistan PPI table ppiTJK2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiTJK2015[ppiTJK2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiTJK2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiTJK2015[ppiTJK2015$score == ppiScore, "nl100"]# Access Tajikistan PPI table ppiTJK2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiTJK2015[ppiTJK2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiTJK2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiTJK2015[ppiTJK2015$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Timor Leste
ppiTLS2013ppiTLS2013
A data frame with 8 columns and 101 rows:
scorePPI score
nl100National lower poverty line (100%)
nu100National upper poverty line (100%)
nu150National upper poverty line (150%)
nu200National upper poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Timor Leste PPI table ppiTLS2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiTLS2013[ppiTLS2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiTLS2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiTLS2013[ppiTLS2013$score == ppiScore, "nl100"]# Access Timor Leste PPI table ppiTLS2013 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiTLS2013[ppiTLS2013$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiTLS2013, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiTLS2013[ppiTLS2013$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Tanzania
ppiTZA2016ppiTZA2016
A data frame with 19 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
ppp380Below $3.80 per day purchasing power parity (2011)
ppp400Below $4.00 per day purchasing power parity (2011)
half100Poorest half below 100 national
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile50Below 50th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Tanzania PPI table ppiTZA2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiTZA2016[ppiTZA2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiTZA2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiTZA2016[ppiTZA2016$score == ppiScore, "nl100"]# Access Tanzania PPI table ppiTZA2016 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiTZA2016[ppiTZA2016$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiTZA2016, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiTZA2016[ppiTZA2016$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Tanzania 2022
ppiTZA2022ppiTZA2022
A data frame with 21 columns and 100 rows:
scorePPI score
nl_upperNational upper poverty line
nl_lowerNational lower poverty line
extremeExtreme poverty line
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 50th percentile poverty line
percentile80Below 60th percentile poverty line
# Access Tanzania PPI table ppiTZA2022 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiTZA2022[ppiTZA2022$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiTZA2022, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiTZA2022[ppiTZA2022$score == ppiScore, "extreme"]# Access Tanzania PPI table ppiTZA2022 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiTZA2022[ppiTZA2022$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiTZA2022, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the USAID # extreme poverty definition ppiScore <- 50 ppiTZA2022[ppiTZA2022$score == ppiScore, "extreme"]
Poverty Probability Index (PPI) lookup table for Uganda
ppiUGA2015ppiUGA2015
A data frame with 13 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp400Below $4.00 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp844Below $8.44 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
# Access Uganda PPI table ppiUGA2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiUGA2015[ppiUGA2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiUGA2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiUGA2015[ppiUGA2015$score == ppiScore, "nl100"]# Access Uganda PPI table ppiUGA2015 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiUGA2015[ppiUGA2015$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiUGA2015, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiUGA2015[ppiUGA2015$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Uganda 2022
ppiUGA2022ppiUGA2022
A data frame with 21 columns and 100 rows:
scorePPI score
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
ppp1100Below $11.00 per day purchasing power parity (2011)
ppp1500Below $15.00 per day purchasing power parity (2011)
ppp2170Below $21.70 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 50th percentile poverty line
percentile80Below 60th percentile poverty line
# Access Uganda PPI table ppiUGA2022 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiUGA2022[ppiUGA2022$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiUGA2022, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the purchasing # power parity at $1.00 ppiScore <- 50 ppiUGA2022[ppiUGA2022$score == ppiScore, "ppp100"]# Access Uganda PPI table ppiUGA2022 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiUGA2022[ppiUGA2022$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiUGA2022, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the purchasing # power parity at $1.00 ppiScore <- 50 ppiUGA2022[ppiUGA2022$score == ppiScore, "ppp100"]
Poverty Probability Index (PPI) lookup table for Vietnam
ppiVNM2009ppiVNM2009
A data frame with 8 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
extremeUSAID extreme poverty line
ppp125Below $1.25 per day purchasing power parity (2005)
ppp175Below $1.75 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
molisaMOLISA poverty line
# Access Vietnam PPI table ppiVNM2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiVNM2009[ppiVNM2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiVNM2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiVNM2009[ppiVNM2009$score == ppiScore, "nl100"]# Access Vietnam PPI table ppiVNM2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiVNM2009[ppiVNM2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiVNM2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiVNM2009[ppiVNM2009$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for Vietnam for 2023
ppiVNM2023ppiVNM2023
A data frame with 8 columns and 101 rows:
scorePPI score
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access Vietnam PPI table ppiVNM2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiVNM2023[ppiVNM2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiVNM2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiVNM2023[ppiVNM2023$score == ppiScore, "percentile20"]# Access Vietnam PPI table ppiVNM2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiVNM2023[ppiVNM2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiVNM2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiVNM2023[ppiVNM2023$score == ppiScore, "percentile20"]
Poverty Probability Index (PPI) lookup table for Yemen
ppiYEM2009ppiYEM2009
A data frame with 8 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp300Below $3.00 per day purchasing power parity (2005)
ppp400Below $4.00 per day purchasing power parity (2005)
# Access Yemen PPI table ppiYEM2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiYEM2009[ppiYEM2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiYEM2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiYEM2009[ppiYEM2009$score == ppiScore, "nl100"]# Access Yemen PPI table ppiYEM2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiYEM2009[ppiYEM2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiYEM2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiYEM2009[ppiYEM2009$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for South Africa
ppiZAF2009ppiZAF2009
A data frame with 8 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
extremeUSAID extreme poverty
nu100National upper poverty line (100%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp400Below $4.00 per day purchasing power parity (2005)
# Access South Africa PPI table ppiZAF2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiZAF2009[ppiZAF2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiZAF2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiZAF2009[ppiZAF2009$score == ppiScore, "nl100"]# Access South Africa PPI table ppiZAF2009 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiZAF2009[ppiZAF2009$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiZAF2009, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiZAF2009[ppiZAF2009$score == ppiScore, "nl100"]
Poverty Probability Index (PPI) lookup table for South Africa for 2023
ppiZAF2023ppiZAF2023
A data frame with 6 columns and 101 rows:
scorePPI score
wealth_indexWealth index poverty line
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
# Access South Africa PPI table ppiZAF2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiZAF2023[ppiZAF2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiZAF2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiZAF2023[ppiZAF2023$score == ppiScore, "wealth_index"]# Access South Africa PPI table ppiZAF2023 # Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiZAF2023[ppiZAF2023$score == ppiScore, ] # Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiZAF2023, score == ppiScore) # Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiZAF2023[ppiZAF2023$score == ppiScore, "wealth_index"]
Poverty Probability Index (PPI) lookup table for Zambia
ppiZMB2013_csoppiZMB2013_cso
A data frame with 9 columns and 101 rows:
scorePPI score
foodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
Poverty Probability Index (PPI) lookup table for Zambia
ppiZMB2013_gotppiZMB2013_got
A data frame with 9 columns and 101 rows:
scorePPI score
foodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
Poverty Probability Index (PPI) lookup table for Zambia
ppiZMB2017ppiZMB2017
A data frame with 17 columns and 101 rows:
scorePPI score
foodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
medianMedian poverty line
percentile20Below 20th percentile poverty line
percentile40Below 50th percentile poverty line
percentile50Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Poverty Probability Index (PPI) lookup table for Zambia
ppiZMB2017_appiZMB2017_a
A data frame with 16 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp100Below $1.00 per day purchasing power parity (2011)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp320Below $3.20 per day purchasing power parity (2011)
ppp550Below $5.50 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line