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Physical Sciences and Mathematics Commons

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Full-Text Articles in Physical Sciences and Mathematics

Applications Of Monte Carlo Methods In Statistical Inference Using Regression Analysis, Ji Young Huh Jan 2015

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.


An Exposition And Calibration Of The Ho-Lee Model Of Interest Rates, Benjamin I. Lawson Jan 2015

An Exposition And Calibration Of The Ho-Lee Model Of Interest Rates, Benjamin I. Lawson

CMC Senior Theses

The purpose of this paper is to create an easily understandable version of the Ho-Lee interest rate model. The first part analyzes the model in detail, and the second part calibrates it to demonstrate how it can be applied to real market data.


Price, Perceived Value And Customer Satisfaction: A Text-Based Econometric Analysis Of Yelp! Reviews, Eleanor A. Dwyer Jan 2015

Price, Perceived Value And Customer Satisfaction: A Text-Based Econometric Analysis Of Yelp! Reviews, Eleanor A. Dwyer

Scripps Senior Theses

We examine the antecedents of customer satisfaction in the restaurant sector, paying particular attention to perceived value and price level. Using Latent Dirichlet Allocation, we extract latent topics from the text of Yelp! reviews, then analyze the relationship between these topics and satisfaction, measured as the difference between review rating and user average review rating.