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理性预期模型的全信息估计与随机模拟
Abstract A computationally feasible method for the full information maximum‐likelihood estimation of models with rational expectations is described in this paper. The stochastic simulation of such models is also described. The methods discussed in this paper should open the way for many more tests of the rational expectations hypothesis within macroeconomic models.
动态非线性理性预期模型的求解与极大似然估计
A solution method and an estimation method for nonlinear rational expectations models are presented in this paper.The solution method can be used in forecasting and policy applications and can handle models with serial correlation and multiple viewpoint dates.When applied to linear models, the solution method yields the same results as those obtained from currently available methods that are designed specifically for linear models.It is, however, more flexible and general…
理性预期宏观经济模型的估计与控制
The paper investigates an econometric method for selecting macroeconomic policy rules when expectations are formed rationally. A simple econometric model of the U.S. is estimated subject to a set of rational expectations restrictions using a minimum distance estimation technique. The estimated model is then used to calculate optimal monetary policy rules to stabilize fluctuations in output and inflation, and to derive a long run tradeoff between price stability and output…
动态模型中最小二乘估计的强一致性
The least squares estimate of the parameter matrix $\mathbf{B}$ in the model $\mathbf{y}_t = \mathbf{B'x}_t + \mathbf{u}_t$, where $\mathbf{u}_t$ is an $m$-component vector of unobservable disturbances and $x_t$ is a $p$-component vector, converges to $\mathbf{B}$ with probability one under certain conditions on the behavior of $x_t$ and $\mathbf{u}_t$. When $\mathbf{x}_t$ is stochastic and the conditional expectation of $\mathbf{u}_t$ given $\mathbf{x}_s$ for $s \leqslant t$…
控制问题中最小二乘估计统计性质的实验结果
The statistical properties of the certainty equivalence control rule and of the least squares estimates generated by this rule are examined experimentally in a linear model with two unknown parameters. It is found that the least squares certainty equivalence rule converges to its true value with probability one and is asymptotically efficient, having an asymptotic distribution with a variance as small as any other strongly consistent rule. However, while a linear combination…
正态线性回归中最小二乘估计的强相合性
In the usual linear regression model the sample regression coefficients converge with probability one to the population regression coefficients when the dependent variables are normally distributed and the inverse of the second-order moment matrix of the independent variables converges to the zero matrix.