Maggie Branch

As part of my experience in the Texas A&M University Honors Program, I did a departmental research project. Research is an excellent way to supplement your college education by pushing yourself beyond what you think you can do to discover new and exciting information. There are countless topics in a variety of fields to choose from when it comes to research. Interestingly I did not choose my topic, which was on the consumption of Specialty Eggs in the United States. My project inspired by Dr. Senarath Dharmasena, a professor in the department of Agriculture Economics. Many University professors have projects that they have a desire to pursue, but not the time to do the work. This is where a dedicated undergraduate student who has a willingness to learn can be a useful resource for these professors. When Dr. Dharmasena first came to me about the potential project, I was hesitant to take it up. The methods in which to complete this project involved Master's level research analysis and several programs that I was not familiar with at all. However, my professor's encouragement combined with the University Honors Programs emphasis on completing a project eventually convinced me to start my project on "The Economic and Demographic Factors Affecting the Propensity to Consume Specialty Eggs in the United States."

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I was surprised to discover when I began my project that I wouldn't even look at my data for several months. The first steps in my project involved learning, and learning, and more learning. I had to first master the program that I would be using to do most of the analysis, called the Statistical Analysis System (SAS). This program is based on a computer programming language used for statistical analysis, and can read data from common spreadsheets and databases and output the results of statistical analyses in tables, graphs, and as RTF, HTML and PDF documents. The most useful thing about SAS is that it can sort through thousands upon thousands of data points in moments, allowing economists to create more accurate models. This program is often used in the Agriculture Economics Masters Programs, but is not introduced to undergraduates until their senior year. While it is extremely useful, it is very difficult to master. One wrong punctuation or letter placement in the programming leaves you with no results at all. It felt like learning a new language in the span of a month or two. Dr. Dharmasena provided me with reading material and practice data to help with the learning process, for which I was extremely grateful. After becoming familiar with SAS, I then did research on the Probit model, which is what I would eventually use to find the probabilities of how different demographic information affected a consumer's propensity to purchase different egg varieties. After several months of reading and practice, I finally got to take my first look at the data I would use for my project.

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The process of sorting the consumer purchase information first involved separating the egg products from the other products using the product descriptor code. The easily identified "Control Brand" egg types were worked with first and separating into regular eggs and specialty eggs. Specialty eggs were defined as any production process that varied from the traditional cage system egg production used by most producers. After the control brands were sorted, the name brands were exported and given a bi-variable indicator (0 or 1) to indicate if it was regular or specialty. This process took several months as I had to individually give the indicator to each one of the over 6000 different egg purchases. At the end of the sorting process I had a table for regular eggs and a table of specialty eggs. Then I added the household and demographic information and started sorting again. Thankfully SAS was actually able to help with the sorting process this time and it took considerably less time. At the end of the second sorting process I had a table for the households that purchased eggs, a table for the households that purchased only regular eggs, a table for the households that purchased only specialty eggs, and a table for the households that purchased both regular and specialty eggs. 

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It was only at this point in my research that I was able to run regressions and my Probit models. The regression analysis allowed me to find imputer prices for all the households, or what they WOULD have paid if they had bought that particular type of egg. This gave SAS all the data required to run a Probit model analysis. The variables that were used for the probit model were: price, income, household size, race (Black, White, Asian, Other), Hispanic, education (no high school, high school graduate, some college, college graduate), age (under 35, 36-50, 51-75, 75 plus), child presence, employment (part-time, full-time, not-for-pay), and region (New England, Mid-Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, Mountain Region, Pacific Region). The results of the Probit model showed whether the household was more or less likely to purchase the particular type of egg based on the base category that I set for the model. The base category for race was white, the base for education was no high school, the base for age was under 35, the base for employment was not-for-pay, the base for Hispanic is the household being Hispanic, the base for child is the household having a child presence, and the base for region was New England (Maine, Vermont, New Hampshire, Massachusetts, Connecticut and Rhode Island). Although my project was specifically on specialty eggs, I ran the profit model on all four of the tables that I created.

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In this project I found the demographic variables that marketers should look for when selling their specialty egg products to have the most efficient sales. Results found that the average consumers of specialty eggs young couples with not only a high income, but an increasing income, as well as a high education and no children. The best areas in which to sell specialty eggs were found to be areas in the Pacific region that have high part time employment and small household sizes. I also found that an increase in price of specialty eggs makes consumers more likely to purchase them, indicating that they are a luxury (or Giffen) good. 

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This project was an extremely rewarding experience. I can't really describe the elation that I felt when I received my final results after an entire year of work. My departmental research capstone will definitely be one of the most challenging memories that I will have of my time here at A&M, however, the skills that I learned throughout the process will benefit me for the rest of my life. I was excited to find out from my professor that my research paper was actually approved to compete in the Southern Agricultural Economics Association (SAEA) conference in February of 2018. It is here that I hope to represent Texas A&M while I present my project to the judges of the conference. I am grateful to the University Honors Program for giving me the resources and motivation to complete this project so that I can graduate form the college that I love with the Honors distinction. I can't wait to see what my senior year will bring, and I hope and pray that it will bring only success. 

 

Thank you to all who were involved in helping me to succeed in my research venture! I encourage everyone to find something that pushes them beyond what they think they can do, because that is the only way we can better ourselves. 

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