ESTIMATION AND INFERENCE BY THE METHOD OF PROJECTION MINIMUM DISTANCE: AN APPLICATION TO THE NEW KEYNESIAN HYBRID PHILLIPS CURVE*
提出一种两步估计法“投影最小距离”，利用局部投影估计沃尔德表示，再通过最小距离技术估计模型参数，适用于参数非线性但沃尔德系数与参数线性映射的宏观模型。
The stability of the solution path in a macroeconomic model implies that it admits a Wold representation. This Wold representation can be estimated semi‐parametrically by local projections and used to estimate the model's parameters by minimum distance techniques even when the stochastic process for the solution path is unknown or unconventional. We name this two‐step estimation procedure “projection minimum distance” and investigate its statistical properties for the broad class of models where the mapping between Wold coefficients and parameters is linear. This includes many situations with likelihood score functions nonlinear in the parameters that would otherwise require numerical optimization routines.