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Articles 1 - 11 of 11
Full-Text Articles in Applied Statistics
The Impact Of Subjective Risk Analysis On Real Estate Prices In The Nisqually Region Following The 2001 Nisqually Earthquake, Ryan Espedal
The Impact Of Subjective Risk Analysis On Real Estate Prices In The Nisqually Region Following The 2001 Nisqually Earthquake, Ryan Espedal
All Master's Theses
Earthquakes are an environmental hazard that pose great risks to communities almost every day. With earthquakes, the main cause of concern is physical destruction of property, however, there are also psychological effects that are researched and discussed much less. In 2001, the Nisqually area of western Washington experienced a substantial earthquake that produced minimal physical damage but caused a significant decrease in real estate prices. Studying single-family homes from 1986-2012, this research utilizes hedonic property models to measure the change in consumer’s subjective risk calculations with reference to real estate purchases after the Nisqually earthquake, measure the relationship between earthquake …
On Cluster Robust Models, José Bayoán Santiago Calderón
On Cluster Robust Models, José Bayoán Santiago Calderón
CGU Theses & Dissertations
Cluster robust models are a kind of statistical models that attempt to estimate parameters considering potential heterogeneity in treatment effects. Absent heterogeneity in treatment effects, the partial and average treatment effect are the same. When heterogeneity in treatment effects occurs, the average treatment effect is a function of the various partial treatment effects and the composition of the population of interest. The first chapter explores the performance of common estimators as a function of the presence of heterogeneity in treatment effects and other characteristics that may influence their performance for estimating average treatment effects. The second chapter examines various approaches …
Applications Of Monte Carlo Methods In Statistical Inference Using Regression Analysis, Ji Young Huh
Applications Of Monte Carlo Methods In Statistical Inference Using Regression Analysis, Ji Young Huh
CMC Senior Theses
This paper studies the use of Monte Carlo simulation techniques in the field of econometrics, specifically statistical inference. First, I examine several estimators by deriving properties explicitly and generate their distributions through simulations. Here, simulations are used to illustrate and support the analytical results. Then, I look at test statistics where derivations are costly because of the sensitivity of their critical values to the data generating processes. Simulations here establish significance and necessity for drawing statistical inference. Overall, the paper examines when and how simulations are needed in studying econometric theories.
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.
Asimmetria Del Rischio Sistematico Dei Titolo Immobiliari Americani: Nuove Evidenze Econometriche, Paola De Santis, Carlo Drago
Asimmetria Del Rischio Sistematico Dei Titolo Immobiliari Americani: Nuove Evidenze Econometriche, Paola De Santis, Carlo Drago
Carlo Drago
In questo lavoro riscontriamo un aumento del rischio sistematico dei titoli del mercato immobiliare americano nell’anno 2007 seguito da un ritorno ai valori iniziali nell’anno 2009 e si evidenzia la possibile presenza di break strutturali. Per valutare il suddetto rischio sistematico è stato scelto il modello a tre fattori di Fama e French ed è stata studiata la relazione tra l’extra rendimento dell’indice REIT, utilizzato come proxy dell’andamento dei titoli immobiliari americani, e l’extra rendimento dell’indice S&P500 rappresentativo del rendimento del portafoglio di mercato. I risultati confermano la presenza di un “Asymmetric REIT Beta Puzzle” coerentemente con alcuni precedenti studi …
Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans
Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans
Lonnie K. Stevans
The econometric literature on unit roots took off after the publication of the paper by Nelson and Plosser (1982) that argued that most macroeconomic series have unit roots and that this is important for the analysis of macroeconomic policy. Yule (1926) suggested that regressions based on trending time series data can be spurious. This problem of spurious correlation was further pursued by Granger and Newbold (1974) and this also led to the development of the concept of cointegration (lack of cointegration implies spurious regression). The pathbreaking paper by Granger (1981), first presented at a conference at the University of Florida …
Empirical Methods-A Review: With An Introduction To Data Mining And Machine Learning, Matt Bogard
Empirical Methods-A Review: With An Introduction To Data Mining And Machine Learning, Matt Bogard
Economics Faculty Publications
This presentation was part of a staff workshop focused on empirical methods and applied research. This includes a basic overview of regression with matrix algebra, maximum likelihood, inference, and model assumptions. Distinctions are made between paradigms related to classical statistical methods and algorithmic approaches. The presentation concludes with a brief discussion of generalization error, data partitioning, decision trees, and neural networks.
Men In Black: The Impact Of New Contracts On Football Referees’ Performances, Babatunde Buraimo, Alex Bryson, Rob Simmons
Men In Black: The Impact Of New Contracts On Football Referees’ Performances, Babatunde Buraimo, Alex Bryson, Rob Simmons
Dr Babatunde Buraimo
No abstract provided.
Participation And Engagement In Sport: A Double Hurdle Approach For The United Kingdom, Babatunde Buraimo, Brad Humphreys, Rob Simmons
Participation And Engagement In Sport: A Double Hurdle Approach For The United Kingdom, Babatunde Buraimo, Brad Humphreys, Rob Simmons
Dr Babatunde Buraimo
This paper uses pooled cross-section data from four waves of the United Kingdom’s Taking Part Survey, 2005 to 2009, in order to investigate determinants of probability of participation and levels of engagement in sports. The two rival modelling approaches considered here are the double-hurdle approach and the Heckman sample selection model. The Heckman model proves to be deficient in several key respects. The double-hurdle approach offers more reliable estimates than the Heckman sample selection model, at least for this particular survey. The distinction is more than just statistical nuance as there are substantive differences in qualitative results from the two …
Gone In 60 Seconds: The Absorption Of News In A High-Frequency Betting Market, Babatunde Buraimo, David Peel, Rob Simmons
Gone In 60 Seconds: The Absorption Of News In A High-Frequency Betting Market, Babatunde Buraimo, David Peel, Rob Simmons
Dr Babatunde Buraimo
This paper tests for efficiency in a betting market that offers high-frequency data, the Betfair betting exchange for wagering on outcomes of English Premier League soccer matches. We find clear evidence of rapid adjustment of prices to large disturbances (news). Full adjustment takes place within a one minute interval after the news. This suggests that this particular wagering market is not just efficient at pre-match prices but is also efficient in the face of events within games.
Investigating Omitted Variable Bias In Regression Parameter Estimation: A Genetic Algorithm Approach, Lonnie K. Stevans, David N. Sessions
Investigating Omitted Variable Bias In Regression Parameter Estimation: A Genetic Algorithm Approach, Lonnie K. Stevans, David N. Sessions
Lonnie K. Stevans
Bias in regression estimates resulting from the omission of a correlated relevant variable is a well known phenomenon. In this study, we apply a genetic algorithm to estimate the missing variable and, using that estimated variable, demonstrate that significant bias in regression estimates can be substantially corrected with relatively high confidence in effective models. Our interest is restricted to the case of a missing binary indicator variable and the analytical properties of bias and MSE dominance of the resulting dependent error generated vector process. These findings are compared to prior results for the independent error proxy process. Simulations are run …