Frequently Asked Questions
What PATs Do
PATs are used to calculate the percent of a population living below one or more national or international poverty lines. PATs measure household-level poverty. After administering the 10-20 question country-specific survey to each individual in your sample or population, the survey results are entered into a data entry template created by the PAT team. After the data is entered, you will run the analysis program (also created by the PAT team) to get your survey results. The results will tell you what percent of your survey population lives below each of two to five poverty lines. ("33% of target households live below the $1.25/day line; 71% of targeted households live below the $2.50/day line"; etc.)
PATs tell you about your poverty outreach. Depending on the population to which you apply the survey, the PAT can be useful in many ways, including:
Though they could be reconfigured to predict the poverty level of an individual household, the tools are designed to provide a statistically accurate assessment of poverty among a pool of clients, rather than of individual households. This reflects the Congressional requirement that the tools measure the total percentage of very poor households among each organization's microenterprise clients.
All tools designed to assess human and social phenomena- poverty being only one of them- are subject to measurement errors. In the case of poverty assessment, these errors are of two types: misclassifying a very poor household as not very-poor; and the opposite, misclassifying a not very-poor household as very poor. Finding ways to reduce the size of these errors in the poverty assessment tools has been a key task for IRIS. One of the accomplishments of the project is the development of statistical techniques that identify poverty indicators that ensure that the number of very poor households misclassified as not very-poor is the same as the number households misclassified in the other direction. This means that, over a large enough sample, individual misclassifications do not matter- since the two types of errors would cancel each other out, regardless of how large they are. However, these misclassifications still matter at the individual level. This explains why the same tool can be very accurate when measuring poverty at a collective level, but very inaccurate if used on an individual basis.
Consider this example: if a tool is used to report on the number of very poor clients in a group, it does not matter that two very poor clients are incorrectly classified as not very-poor, as long as two not very-poor clients are misclassified as very poor; the errors cancel out and do not affect the aggregate result. If the tool, however, is used for individual assessment (or targeting), the errors add up: four people have been incorrectly identified, with the result that two very poor clients will not receive the services designed for them, while two not very-poor clients will receive services they may not need.
The PATs measure the percentage of extreme poverty of a group of people at one point in time. A tool can be used to measure the poverty level of a specific group of people at one point in time, then again on the same group of people at a second point in time, but an organization must remember that even if the two measurements indicate a change in poverty level of this specific group of people between these two points in time, the results do not establish causation for the change in poverty level. The PATs only measure poverty levels; they do not measure why there has been a change in poverty level. USAID encourages organizations to use the PATs for other uses outside of reporting to MRR, but only if they have a full understanding of the limitations of the tool.
If an organization uses the PAT as one component of an impact study, it should only be used under the following conditions: a) impact is assessed on the same, sufficiently large, group of clients, and not for individual clients; b) the tools are calibrated for the country or region in question; c) the poverty line across which the movement is measured is the line used to calibrate the tools; and d) tools are kept up-to-date between the first and the subsequent measurements (so that the poverty measurement continues to capture changing economic conditions).
Even if these conditions are met, it is unclear that the tools will be able to identify real changes in poverty over time due to their inherent measurement errors. Unless the changes in poverty rate are exceptionally large and the tools exceptionally accurate, the changes identified are likely to be contained within the margin of error.