STATISTICAL METHODS FOR ADVANCED ECONOMETRIC MODELS WITH APPLICATIONS TO VEHICLE HOLDING AND SPEED QUANTILES DISTRIBUTION

This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.

LISA SERGIO: HOW MUSSOLINI'S "GOLDEN VOICE" OF PROPAGANDA CREATED AN AMERICAN MASS COMMUNICATION CAREER

In 1937 Lisa Sergio, "The Golden Voice" of fascist broadcasting from Rome, fled Italy for the United States. Though her mother was American, Sergio was classified as an enemy alien once the United States entered World War II. Yet Sergio became a U.S. citizen in 1944 and built a successful career in radio, working first at NBC and then WQXR in New York City in the days when women's voices were not thought to be appropriate for news or "serious" programming. When she was blacklisted as a communist in the early 1950s, Sergio compensated for the loss of radio employment by becoming principally an author and lecturer in Washington, D.C., until her death in 1989. This dissertation, based on her personal papers, is the first study of Sergio's American mass communication career. It points out the personal, political and social obstacles she faced as a woman in her 52-year career as a commentator on varied aspects of world affairs, religion and feminism. This study includes an examination of the FBI investigations of Sergio and the anti-communist campaigns conducted against her. It concludes that Sergio's success as a public communicator was predicated on both her unusual talents and her ability to transform her public image to reflect ideal American values of womanhood in shifting political climates.