Forecasting using a Nonlinear DSGE Model

被引:3
|
作者
Ivashchenko, Sergey [1 ,2 ,3 ]
Gupta, Rangan [4 ]
机构
[1] Russian Acad Sci, St Petersburg Inst Econ & Math, St Petersburg, Russia
[2] St Petersburg State Univ, Fac Econ, St Petersburg, Russia
[3] Natl Res Univ Higher Sch Econ, St Petersburg, Russia
[4] Univ Pretoria, Dept Econ, Pretoria, South Africa
关键词
Nonlinear DSGE; Quadratic Kalman Filter; Out-of-sample forecasts;
D O I
10.2478/jcbtp-2018-0013
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
A medium-scale nonlinear dynamic stochastic general equilibrium (DSGE) model was estimated (54 variables, 29 state variables, 7 observed variables). The model includes an observed variable for stock market returns. The root-mean square error (RMSE) of the in-sample and out-of-sample forecasts was calculated. The nonlinear DSGE model with measurement errors outperforms AR (1), VAR (1) and the linearised DSGE in terms of the quality of the out-of-sample forecasts. The nonlinear DSGE model without measurement errors is of a quality equal to that of the linearised DSGE model.
引用
收藏
页码:73 / 98
页数:26
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