Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We estimate the approximate non-linear solution of a small DSGE model on euro area data, using the conditional particle filter to compute the model likelihood. Our results are consistent with previous findings, based on simulated data, suggesting that this approach delivers sharper inference compared to the estimation of the linearised model. We also show that the non-linear model can account for richer economic dynamics: the impulse responses to structural shocks vary depending on initial conditions selected within our estimation sample.