How do we measure poverty in Paraguay for more agile responses?

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Feria de los productores de Capiibary en Paraguay. Feria de los productores de Capiibary en Paraguay.

Quality and timely information is essential for decision makers such as policy makers, analysts and researchers. Access to quality information is doubly important when decisions are likely to impact the most vulnerable populations.

Paraguay has made considerable progress in capturing reliable data for the estimation of poverty at the national, urban and rural levels, using the Permanent Continuous Household Survey (EPHC) prepared by the National Institute of Statistics (INE). This is a significant step for Paraguay, considering that not all countries in the Latin American and Caribbean region have managed to collect and store this kind of data. 

Poverty measurement is based on household surveys that collect data on household income or expenditure. The data are difficult to collect, requiring the completion of long, costly  and often complex questionnaires. The problem with this approach is that we only have data on the periods close to when the surveys are actually carried out. This presents difficulties for developing and implementing public policies, since we are unable to capture data on the poverty situation during the periods between surveys.

Governments need more frequent and reliable estimates to track poverty dynamics quickly and frequently and be assessed by policy makers. In addition to household data, we also need to forecast the effects of ‘positive’ events such as:

  • Favorable external market conditions
  • Establishment of firms in Paraguay with impacts on jobs
  • Good harvests

And on ‘negative’ developments such as:

  • Wars or pandemics
  • Climate shocks such as droughts or floods

A forward-looking evidence-based approach is crucial to help us prepare effective and timely public policy responses that can mitigate any negative fallout on the population.

Poverty measurement innovations in Paraguay and the world

The Ministry of Economy and Finance (MEF), with the support of the World Bank, is implementing a modern, innovative and robust methodology to deliver more frequent on poverty estimates in Paraguay, and enable interventions supported by quality data to be evaluated more quickly.   The SWIFT tool, developed by the World Bank, is used to produce more frequent poverty estimates using the EPHC. SWIFT applies machine learning techniques based on the latest available household survey data to generate high-frequency estimates comparable with official statistics.

SWIFT has been used in other contexts with promising results. For example, in Nigeria, where the most recent poverty figure was for 2018, SWIFT was adapted to enable more frequent estimations at various points in time (2010, 2012, 2015) and to allow comparisons with the 2018 figures.

In Mongolia, where improvements were made to the expenditure module of the 2020 household survey, in line with international good practices, SWIFT was used by the Bureau of Statistics and the World Bank to restore the comparability of expenditure data and poverty rates with previous survey years.

In Paraguay, the methodology has been tailored to the local context to ensure its sustainability, its implementation by the relevant institutions, and the possibility of making adjustments to the methodology . The results show that, in addition to producing estimates close to the official poverty figures, the quarterly estimates also capture short-term variations in trends.


Quarterly poverty forecast in Paraguay 


The methodology is based on variables that tend to be stable over time such as household size, property ownership and educational level, as well as fast-changing variables such as labor market indicators reflecting quarterly changes. Income is adjusted for inflation using the Consumer Price Index (CPI) produced by the Central Bank of Paraguay (BCP). This strategy uses the most recent (fourth quarter) data from the EPHC to train the models, thus enabling poverty rates to be estimated as soon as data from the quarterly surveys become available.

With the implementation of SWIFT, we will have more useful and timely data for implementing public policies. Furthermore, we will be in a better position to analyze changes between periods in greater detail, forecast the impacts of specific events, and implement measures  to mitigate the negative effects of adverse shocks on the economy  and protect the most vulnerable populations.


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Matilde Bordón

World Bank Representative in Paraguay

Juan José Galeano

Director of Economic Studies at the Ministry of Economy and Finance of Paraguay

Eliana Rubiano-Matulevich

Senior Economist at the Poverty and Equity Global Practice for Latin American and the Caribbean at The World Bank

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