Σε ένα γραμμικό υπόδειγμα βοηθητικών μεταβλητών η ασθενής συσχέτιση των βοηθητικών μεταβλητών με τις ενδογενείς ερμηνευτικές μεταβλητές είναι γνωστή στη βιβλιογραφία ως το ζήτημα των ασθενών βοηθητικών μεταβλητών. Στην παρούσα εργασία διερευνώνται διάφορες πτυχές του εν λόγω ζητήματος και επισημαίνονται πιθανές μέθοδοι για την αντιμετώπισή του. Επίσης, μελετάται η απόδοση των εκτιμητών OLS, TSLS, BTSLS, LIML και Fuller-k κάτω από την υπόθεση των ασθενών βοηθητικών μεταβλητών, μέσω ενός πειράματος Monte Carlo, με τα αποτελέσματα να τεκμηριώνουν τη δυσκολία λήψης αξιόπιστων σημειακών εκτιμήσεων. / Weak instruments arise when the instruments in linear instrumental variables (IV) regression are weakly correlated with the included endogenous variables. We review most of the recent studies on weak instruments and point to several methods that have been proposed to deal with such instruments. Using a Monte Carlo experiment we study the performance of OLS, TSLS, BTSLS, LIML and Fuller-k estimators under weak instruments. Our results indicate the difficulty of obtaining reliable point estimates.

This dissertation examines a number of issues related to Static and Dynamic Student t Regression Models. The Static Student t Regression Model is derived and transformed to an operational form. The operational form is then examined in a series of Monte Carlo experiments. The model is judged based on its usefulness for estimation and testing and its ability to model the heteroskedastic conditional variance. It is also compared with the traditional Normal Linear Regression Model. Subsequently the analysis is broadened to a dynamic setup. The Student t Autoregressive Model is derived and a number of its operational forms are considered. Three forms are selected for a detailed examination in a series of Monte Carlo experiments. The models’ usefulness for estimation and testing is evaluated, as well as their ability to model the conditional variance. The models are also compared with the traditional Dynamic Linear Regression Model. / Ph. D.