Browsing by Author "Rybarczyk, Adam"

Standard business cycle models rely on contemporaneous shocks to productivity in order to generate business cycles. Therefore a technological regress is necessary for a recession to occur. This is not always a satisfactory explanation, as for example the recession of 2001 is often not considered as created by a negative technological shock. Instead many economists believe it was caused by a revision in expectations. Technological news shocks is a topic that has gained interest in the recent macroeconomic literature and is aimed at tackling the aforementioned issue. A news shock is a shock which on arrival does not affect the variable of interest, instead the value is only expected to change in the future. In standard real business cycle models introduction of news shocks to productivity leads to recessions, as households experience a positive wealth effect while the firms do not yet change their behaviour. Thus a multitude of general equilibrium models designed specifically for news shocks have been proposed. This thesis investigates the role of technological news shocks as drivers of business cycles in Finland. To this end a Bayesian structural vector moving average model is used, which allows for non-invertible data generating processes. Non-invertibility arises when a shock can not be recovered from current and past observables, instead future observables are also needed. The prior of the model is informed with a combination of two DSGE models, one informing the news shock impulse responses, and other informing the rest of the impulse responses. Two out of three estimated specifications of the model do create a positive co-movement of the included macroeconomic aggregates. This is not reflected in a non-informative specification, in which output growth rate increases, but the growth rate of hours worked decreases. The results suggest that news shocks could indeed play a role in the Finnish business cycles, but more research into the topic would be in place.