, such as a regression function, and treating it as a conditional expectation is central to its identification and estimation … identification related properties of this model when the unknown function mu* belongs to a linear space. We also investigate … underidentification of mu* along with the identification of its linear functionals. Several examples are provided in order to develop …

This paper studies the problem of nonparametric identification and estimation of binary threshold-crossing and binary … choice models. First, conditions are given that guarantee the nonparametric identification of both the function of exogenous … observable variables and the distribution of the random terms. Second, the identification results are employed to develop …

Portuguese micro bank data. In contrast to the conventional approach, which addresses the identification issue by resorting to …

identification method we are able to attribute instability in the parameters of the VAR solely to changes in the parameters of the …

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 … to be identifying is given. We also define empirical identification of an estimated structure. A switching algorithm for …

practice has required an act of faith in the empirical plausibility of the delay restriction used for identification. An … identification. …