The conditions under which ordinary least squares (OLS) is an unbiased and consistent estimator of the linear probability model (LPM) are unlikely to hold in many instances. Yet the LPM still may be the correct model or, perhaps, justified for practical reasons. A sequential least squares (SLS)...

This paper builds on Kočenda (2001) and extends it in two ways. First, two new intervals of the proximity parameter ε (over which the correlation integral is calculated) are specified. For these ε- ranges new critical values for various lengths of the data sets are introduced and through...

In this paper we develop a regression and a kernel density based model for finding fixed points and attractors of dynamical systems to explore attractors of structural change for NICs. The results show that countries consume longer time in some structures than the others. This can be interpreted...

In this paper we develop a regression and a kernel density based model for finding fixed points and attractors of dynamical systems to explore attractors of structural change for NICs. The results show that countries consume longer time in some structures than the others. This can be interpreted...

This paper extends and generalizes the BDS test presented by Brock, Dechert, Scheinkman, and LeBaron (1996). In doing so it aims to remove the limitation of having to arbitrarily select a proximity parameter by integrating across the correlation integral. The Monte Carlo simulation is used to...