2026-10-14T19:43:22Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34024704 2026-09-29T15:02:39Z category_1 category_12 category_39 category_734 category_931 category_811 category_62 portal_87 item_type_6 month_year_09_2026

Fast and Efficient Estimation of Macromodels with Large Shocks Luisa Corrado (6934754) Stefano Grassi (12032480) Aldo Paolillo (25137591) Biophysics Cell Biology Ecology Biological Sciences not elsewhere classified Information Systems not elsewhere classified Mathematical Sciences not elsewhere classified Marine Biology COVID-19 DSGE Nonlinear Non-Gaussian <p>We propose a new approach for efficiently estimating and analyzing macroeconomic models subject to large shocks. We apply the methodology to a two-sector model that captures the heterogeneous exposure of different sectors to the COVID-19 pandemic. We solve the model nonlinearly and propose a new nonlinear, non-Gaussian filter designed to handle large shocks and identify their source and time location. Monte Carlo experiments show that the estimation and identification of large shocks are feasible with a massively reduced running time. Empirical results indicate that the pandemic-induced economic downturn can be reconciled with a combination of large demand and supply shocks. Finally, we present a set of counterfactual experiments to filter out potential demand and supply shock complementarities, and perform a robustness exercise to check the sensitivity of the model parameters to large shocks.</p> 2026-09-29T15:02:39Z Text Journal contribution 10.6084/m9.figshare.34024704.v1 https://figshare.com/articles/journal_contribution/Fast_and_Efficient_Estimation_of_Macromodels_with_Large_Shocks/34024704 CC BY 4.0