Poverty estimates usually lag behind two years, which makes
it difficult to provide real-time poverty analysis to assess the
impact of economic crisis and shocks among the less well-off,
and subsequently limits policy responses. This paper takes
advantage of up-to-date average economic welfare indicators
like the gross domestic product per capita and comprehensive
harmonized micro data of more than 180 household
surveys in 15 Latin American countries. The paper tests
three commonly used poverty nowcasting methods and
ranks their performance by comparing country-specific and
regional poverty nowcasts with actual poverty estimates for
2003–14 period. The validation results show that the two
bottom-up approaches, which simulate the performance
of each agent in the economy to nowcast overall poverty,
perform relatively better than the top-down approach,
which uses welfare estimates to explain the performance
of poverty at an aggregate level over time. The results
are robust to additional sensitivity and robustness tests.