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周期增长宏观模型中的稳定性与工资加速AI 解读

Abstract This paper is concerned with the stability of macroeconomic models in which there is no long‐run trade‐off between unemployment and inflation, because of a wage adjustment equation based on the NAIRU concept. It is shown, for a simple theoretical model and for the Bergstrom–Nowman–Wymer continuous‐time macro‐econometric model of the UK, that there is a bounded range of positive values of the wage acceleration parameter (determining the effect of labour demand on…

连续时间计量经济模型的历史AI 解读

Although it is only during the last decade that continuous-time models have been extensively used in applied econometric work, the development of statistical methods applicable to such models commenced over 40 years ago. The first significant contribution to the problem of estimating the parameters of continuous-time stochastic models from discrete data was made by the British statistician Bartlett [1946] only three years after the pioneering contribution of Haavelmo [1943]…

混合存量与流量数据下含外生变量的高阶连续时间动态模型估计AI 解读

This article extends recent work on the Gaussian or quasi-maximum likelihood estimation of the parameters of a closed higher-order continuous time dynamic model by introducing exogenous variables into the model The method presented yields exact maximum likelihood estimates when the innovations are Gaussian and the exogenous variables are polynomials in time of degree not exceeding two, and it can be expected to yield very good estimates under more general conditions. It is…

非平稳高阶连续时间动态模型的参数估计AI 解读

This paper is concerned with derivation of a new efficient algorithm for computing the exact Gaussian likelihood for structural parameters in nonstationary higher-order continuous-time dynamic models and with its application in the estimation of these parameters. The algorithm completely avoids the computation of the covariance matrix of the observations and is applicable to a system of any order with mixed stock and flow data. It is used as the basis for an iterative…

希尔伯特空间中的非参数函数估计AI 解读

This paper is concerned with the estimation of a nonlinear regression function which is not assumed to belong to a prespecified parametric family of functions. An orthogonal series estimator is proposed, and Hilbert space methods are used in the derivation of its properties and the proof of several convergence theorems. One of the main objectives of the paper is to provide the theoretical basis for a practical stopping rule which can be used for determining the number of…

高阶连续时间动态模型结构参数的高斯估计AI 解读

This paper is concerned with the efficient estimation of structural parameters in closed linear systems of higher order stochastic differential equations when the data are in discrete form and the model generally includes both stock and flow variables. A general existence and uniqueness theorem for the solution of such a system is proved and used in the rigorous derivation of exact discrete models satisfied by the various types of data. It is shown how these models can be…

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边际消费倾向的最小二乘与最大似然估计量的精确抽样分布AI 解读

In this article we derive the exact finite sample frequency functions of the least squares and maximum likelihood estimators of the marginal propensity to consume, assuming the basic stochastic Keynesian model. The properties of these functions are considered in more detail for particular values of the parameters and sizes of sample. It is concluded that, for samples of 10 or more observations, generated by the model considered (with realistic values of the parameters), the…