This paper proposes an innovative algorithm that significantly improves on the approximation of the optimal early exercise boundary obtained with simulation based methods for American option pricing. The method works by exploiting and leveraging the information in multiple cross sectional...

Within a New Zealand business cycle context, we assess whether Hamilton's (H84) OLS regression methodology produces stylised business cycle facts which are materially different from HP1600 measures, and whether using the H84 predictor and other forecast extensions improves the HP filter's...

Applied work often studies the effect of a binary variable ("treatment") using linear models with additive effects. I study the interpretation of the OLS estimands in such models when treatment effects are heterogeneous. I show that the treatment coefficient is a convex combination of two...

Purpose – Partial least squares structural equation modeling (PLS-SEM) is an important statistical technique in the toolbox of methods that researchers in marketing and other social sciences disciplines frequently use in their empirical analyses. The purpose of this paper is to shed light on...

Construction industry in developing and under developing country has the priority among the other industries. It assumes safe investment in an uncertain market on behalf of privatization. It is most important that the project in this industry is managed as per the best project management...

This study contains a repetition of the data analysis part of a research conducted on building the trust of generation Y customers in B2C websites. In this base study, since the samples size was a limitation of the study, analyses were conducted again by using CB-SEM and PLS-SEM methods...

Ordinary Least Squares (OLS) estimation of monetary policy rules produces potentially inconsistent estimates of policy parameters. The reason is that central banks react to variables, such as in ation and the output gap, which are endogenous to monetary policy shocks. Endogeneity implies a...