Estimating Nonlinear DSGE Models with Moments Based Methods

作     者：Ivashchenko Sergey 

作者机构：St. Petersburg Institute for Economics and Mathematics Russian Academy of Sciences St.Petersburg 191187 Russia 

出 版 物：《Frontiers of Economics in China-Selected Publications from Chinese Universities》 (中国高等学校学术文摘·经济学（英文版）)

年 卷 期：2015年第10卷第1期

页      面：38-55页

学科分类：11[军事学] 080904[工学-电磁场与微波技术] 02[经济学] 07[理学] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 070103[理学-概率论与数理统计] 110503[军事学-军事通信学] 0810[工学-信息与通信工程] 0202[经济学-应用经济学] 1105[军事学-军队指挥学] 020208[经济学-统计学] 1104[军事学-战术学] 082601[工学-武器系统与运用工程] 081105[工学-导航、制导与控制] 0826[工学-兵器科学与技术] 0714[理学-统计学（可授理学、经济学学位）] 081001[工学-通信与信息系统] 081002[工学-信号与信息处理] 0701[理学-数学] 0811[工学-控制科学与工程] 

主　　题：DSGE DSGE-VAR GMM nonlinear estimation 

摘      要：This article suggests a new approach to approximating moments for nonlinear DSGE models. This approach is fast and sufficiently accurate to estimate nonlinear DSGE models. A small financial DSGE model is repeatedly estimated by several modifications of the suggested approach. Approximations of the moments are close to the results of the large sample Monte Carlo estimation. The quality of parameter estimation using our suggested approach is close to the Central Difference Kalman Filter （CDKF）; and our suggested approach is much faster.