Michal Franta
This paper examines the effect of non-linearities on density forecasting. It focuses on the relationship between credit markets and the rest of the economy. The possible non-linearity of this relationship is captured by a threshold vector autoregressive model estimated on the US data using Bayesian methods. Density forecasts thus account for the uncertainty in all model parameters and possible future regime changes. It is shown that considering non-linearity can improve the probabilistic assessment of the economic outlook. Moreover, three illustrative examples are discussed to shed some light on the possible practical applicability of density forecasts derived from non-linear models.
JEL codes: C11, C32, E44
Keywords: density forecasting, nonlinearity, threshold autoregressive model
Issued: September 2013
Download: CNB WP No. 9/2013 (pdf, 832 kB)