The researchers used a multivariate unobserved component model to estimate the output gap in Peru, which helps identify inflationary or disinflationary pressures. Their results show that this method is more reliable and has better predictive power for inflation compared to other estimation techniques like the Hodrick-Prescott filter. The multivariate unobserved component approach provides a more accurate understanding of the Peruvian inflation process.