The iterative least squares method for estimating panel models with unobservable factor structure is extended to cover the case where the number of factors is unknown a priori. The proposed estimation algorithm optimizes a penalized least squares objective function to estimate the factor...

We use a panel cointegration model with multiple time- varying individual effects to control for the enigmatic missing factors in the credit spread puzzle. Our model specification enables as to capture the unobserved dynamics of the systematic risk premia in the bond market. In order to estimate...

We use a panel cointegration model with multiple time- varying individual effects to control for the missing factors in the credit spread puzzle. Our model specification enables as to capture the unobserved dynamics of the systematic risk premia in the bond market. In order to estimate the...

Functional data analysis (FDA) has become a popular technique in applied statistics. In particular, this methodology has received considerable attention in recent studies in empirical finance. In this talk we discuss selected topics of functional principal components analysis that are motivated...

A notion of ''behavioral heterogeneity'' of a finite population of households is modelled. It is shown that the higher the degree of behavioral heterogeneity the less sensitive depends the aggregate consumption expenditure ratio upon prices.As a consequence, behavioral heterogeneity implies a...