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Haavelmo 的实验方法论与协整向量自回归情景分析AI 解读

The paper provides a careful, analytical account of Trygve Haavelmo’s use of the analogy between controlled experiments common in the natural sciences and econometric techniques. The experimental analogy forms the linchpin of the methodology for passive observation that he develops in his famous monograph, The Probability Approach in Econometrics (1944). Contrary to some recent interpretations of Haavelmo’s method, the experimental analogy does not commit Haavelmo to a…

Haavelmo 的概率方法与协整 VARAI 解读

Some key econometric concepts and problems of great importance to Trygve Haavelmo and Ragnar Frisch are discussed within the general framework of a cointegrated VAR. The focus is on problems typical of time-series data such as multicollinearity, spurious correlation and regression, time dependent residuals, model selection, missing simultaneity, autonomy, and identification. The paper argues that the more recent development of unit root econometrics has been instrumental for…

数据线性变换下共同趋势的渐近不变性AI 解读

It is well known that if Xt is a nonstationary process and Yt is a linear function of Xt, then cointegration of Yt implies cointegration of Xt. We want to find an analogous result for common trends if Xt is generated by a finite order VAR with i.i.d. (0,Ωx) errors εxt. We first show that Yt has an infinite order VAR representation in terms of its white noise prediction errors, εyt, which are a linear process in εxt, the prediction error for Xt. We then apply this result to…

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长期与短期结构的识别：ISLM 模型应用AI 解读

In this paper we discuss the problem of identification in a model with cointegration. It is pointed out that there is an identification problem for both long-run parameters and short-run parameters. The identification of the equations and the cointegrating relations is achieved by linear restrictions on the parameters and a criterion for a statistical model to be identifying is given. We also define empirical identification of an estimated structure. A switching algorithm…

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