The primary focus of this article is the provision of tests for additional conditional moment constraints in cross-section or short panel data contexts. The principal contribution is the explicit incorporation of conditional moment restrictions defining the maintained hypothesis in the formulation of the test statistics thus mirroring that of the classical parametric likelihood setting by defin...

abstract today, debt stabilization in an uncertain environment is an important issue. in particular, the question how fiscal and monetary authorities should deal with this uncertainty is of much importance. especially for some developing countries such as iran, in which on average 60 percent of government revenues comes from oil, and consequently uncertainty about oil prices has a large effect ...

This paper is in the line of the recent literature on weak instruments, which, following the seminal approach of Staiger and Stock (1997) and Stock and Wright (2000) captures weak identification by drifting population moment conditions. In contrast with most of the existing literature, we do not specify a priori which parameters are strongly or weakly identified. We rather consider that weaknes...

Speech based cognitive load estimation is a new field of research. Due to this relative ‘lack of maturity’, a single best approach to building cognitive load estimation systems has not been established yet. The primary aim of this submission is to report the performance of various basic utterance level classification frameworks developed using important elements of state-of-the-art speaker reco...

The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to the...

An automatic Language Identification (LID) is the task of automatically recognizing a language from the given spoken utterance. Language identification is used to identify the language of the particular audio and reduce the complexity of the audio sample. LID systems that rely on multiple language phone recognition language modeling (PRLM) and n-gram language modeling produces the best performa...

Today, digital audio applications are part of our everyday lives. Automatic audio classification is very useful in audio indexing; content based audio retrieval and online audio distribution. The accuracy of the classification relies on the strength of the features and classification scheme. In this work both, time domain and frequency domain features are extracted from the input signal. Time d...