An Econometric Analysis of Some Models for Constructed Binary Time Series
研究了宏观金融研究中常用的构建二元时间序列的统计特性，指出其通常不是独立分布而是马尔可夫过程，且常存在删失，因此静态或动态Probit模型不适用，并提出了合适的建模方法。
Macroeconometric and …nancial researchers often use secondary or constructed binary random variables that di¤er in terms of their statistical properties from the primary random variables used in microeconometric studies. One important di¤erence between primary and secondary binary variables is that, while the former are, in many instances, independently distributed (i.d.), the latter are rarely i.d. We show how popular rules for constructing the binary states interact with the stochastic processes for of the variables they are constructed from, so that the binary states need to be treated as Markov processes. Consequently, one needs to recognize this when performing analyses with the binary variables, and it is not valid to adopt a model like static Probit which fails to recognize such dependence. Moreover, these binary variables are often censored, in that they are constructed in such a way as to result in sequences of them possessing the same sign. Such censoring imposes restrictions upon the DGP of the binary states and it creates di ¢ culties if one tries to utilize a dynamic Probit model with them. Given this we describe methods for modeling with these variables that both respects their Markov process nature and which We would like to thank a referee and an Associate Editor for constructive comments on an earlier version of the paper.