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Full-Text Articles in Econometrics
Top Of The Order: Modeling The Optimal Locations Of Minor League Baseball Teams, W. Coleman Conley
Top Of The Order: Modeling The Optimal Locations Of Minor League Baseball Teams, W. Coleman Conley
Undergraduate Economic Review
Over the last twenty-five years, minor league baseball franchises have defined firm mobility. Revisiting the work of Michael C. Davis (2006), I construct a logistic regression model to predict which cities house minor league baseball teams. Six variables are tested for inclusion in the model, including population, income level, the number of major-league professional sports teams in a city, five-year population change, and distance from the closest professional team. Based on the model's predicted probabilities, cities are ranked in order of highest probability of having a team at each of the different levels from Class A to Class AAA.
Application Of Sgt Family Distributions In Quasi Maximum Likelihood Estimation, Samuel Dodini
Application Of Sgt Family Distributions In Quasi Maximum Likelihood Estimation, Samuel Dodini
Undergraduate Economic Review
In the classical normal linear regression model, ordinary least squares estimators (OLS) will be consistent and achieve the Cramer-Rao lower bound for any unbiased estimators. This paper examines the impact of several other error distributions on the properties of the OLS estimators. Several different types of example data commonly available to students and researchers in economics are used to illustrate the impact of nonnormality, because, in application, the assumption of normality may not hold in empirical testing. Using maximum likelihood, I demonstrate that flexible probability density functions better model the residual distribution of different types of data, which suggests improvements …
Examining Success At The Domestic Box-Office In The Motion Picture Industry, Patrick Topf
Examining Success At The Domestic Box-Office In The Motion Picture Industry, Patrick Topf
Honors Projects
The movie business is a multi-billion dollar industry involving production crews, marketing crews, actors, directors, distribution companies, movie theaters, and movie rental companies, but while each movie created follows the same routine, why do some perform so much better than others at the box-office? Why did Juno become a smash hit, while Poseidon is regarded as a major box-office bomb? This study investigates the impact of production cost, star power, professional reviews, release date, sequels, genre, age-rating, and distribution company on total domestic box-office revenue of the widely released films from January 2006 to December 2008.