Dynamic Stochastic General Equilibrium Models In a Liquidity Trap and Self-organizing State Space Modeling

This paper estimates new Keynesian, dynamic stochastic general equilibrium models in a liquidity trap (the non-negativity constraint on short term nominal interest rates) using the Monte Carlo par-ticle filter, proposed by Kitagawa (1996) and Gordon et al. (1993), and a self-organizing state space model, proposed by Kitagawa (1998). This method is a natural extension of Yano (2009). In our method, we estimate the parameters of the models using the time-varying-parameter approach, which is often used to infer invariant parameters in practice. Moreover, natural rates of macroeconomic data, time-varying parameters, and unknown states are estimated simultaneously using self-organizing state space modeling. Adopting our method creates the great advantage that the structural changes of parameters are detected naturally. In empirical analysis, we estimate new Keynesian DSGE models in a liquidity trap using Japanese macroeconomic data which includes the “zero-interest-rate ” period (1999-2006). The analysis shows that the target rate of inflation is too low in the 1990s and th