Social and Behavioral Sciences Commons^™

Three Essays On Natural Rates, Huseyin U. Demir

Dissertations, Theses, and Capstone Projects

Chapter 1. Non-accelerating inflation rate of unemployment and Non-accelerating inflation rate of output We followed Ball and Mankiw (2002) to estimate the natural rates of output and unemployment. The primary purposes of this paper are to provide more accurate estimates of a varying non-accelerating inflation rate of unemployment (NAIRU) than currently exist and to nd a new measure for the nonaccelerating inflation rate of output so we can estimate the output gap more accurately. Our contributions are adding time-varying coefficients estimated with a break test and finding more accurate measurements for the natural rate of unemployment. We also estimated the …

Applications Of Machine Learning And Deep Learning In Macroeconomic And Financial Forecasting, Andi Cupallari

Dissertations, Theses, and Capstone Projects

This dissertation consists of three chapters.

In the first chapter I propose a novel approach to forecast risk premia selecting relevant predictors among hundreds of correlated stock characteristics. I adapt a recently developed method from the deep learning literature, Deep Neural Networks with Group Lasso Regular- ization. This method achieves high out of sample R2, and at the same time yields a sparse representation of the characteristics space that allows for interpretability of the otherwise black box deep learning model. For each period, the model chooses a subset of characteris- tics to be relevant for the risk premia forecast. Our …

Phonologically-Informed Speech Coding For Automatic Speech Recognition-Based Foreign Language Pronunciation Training, Anthony J. Vicario

Dissertations, Theses, and Capstone Projects

Automatic speech recognition (ASR) and computer-assisted pronunciation training (CAPT) systems used in foreign-language educational contexts are often not developed with the specific task of second-language acquisition in mind. Systems that are built for this task are often excessively targeted to one native language (L1) or a single phonemic contrast and are therefore burdensome to train. Current algorithms have been shown to provide erroneous feedback to learners and show inconsistencies between human and computer perception. These discrepancies have thus far hindered more extensive application of ASR in educational systems.

This thesis reviews the computational models of the human perception of American …