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.