Econometrics Project

Running head: ECONOMETRICS PROJECT 1
Econometrics Project
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ECONOMETRICS PROJECT 2
Executive Summary
Econometrics is the application of mathematical and statistical theories in economics. It
enhances forecasting the future trends and hypothesis testing (Theil. 2013). It incorporates
economic models, analyzes them through statistical trials, and makes a comparison of the results
of the real-life examples (Kennedy, 2013). For instance, it is possible to generate a sales
prediction for a firm using econometric methods. The quantity demand depends on the average
price of a pizza per slice and the tuition fee Pizza Hut will spend on offering college degrees. It
will also rely on the mean price per soft drink, and if individuals are in residential or urban areas.
This paper analyzes the sales prediction made for a Pizza Hut using econometric methods. It also
analyzes the multivariate model constructed from the variables that affect the demand for a slice
of pizza.
Model Specification
The demand for a slice of pizza is affected by socio-economic variables such as the average price
per slice and soft drink. It is also affected by the tuition fee spent by the Pizza Hut to educate
undergraduates and the areas where people live such as residential and urban areas x (Hox et al.
2017). From the economics point of view, an increase in price per slice of pizza and soft drink
will decrease the demand for pizza and vice versa, because the increase in the price of a good
reduces the quantity demanded. Besides, money spent on tuition by Pizza Hut do not have a huge
effect on the demand for pizza. However, it may either increase demand or decrease demand.
Conversely, people living in urban areas will consume more pizza than the individuals living in
residential areas, because urban areas are highly populated. The average quantity demanded is

ECONOMETRICS PROJECT 3
treated as a dependent variable (Y). Other variables, which include price per pizza slice, tuition,
the price of a soft drink, and the residence are treated as independent variables (X variables).
The variables used in generating the sales forecast for Pizza Hut were the sales dealt with as the
independent variable (X), and the period “quarter” treated as the depended variable (Y). It is
clear that in every time, the sales of the firm may either increase or decrease.
Description of Pizza Hut
Pizza Hut started in 1958 in USA at a place called Witchitta, when two Brothers Frank and Dan
Carney started it. The company was the beginning of the largest Pizza in the globe, and in the
year 1973, Pizza Hut moved to the United Kingdom. What began as a single place for Pizza is
currently having above seven hundred Delivery outlets and Restaurants up and down the United
Kingdom (Mike & Slocum. 2013). The company is the best when it comes to providing quality
Pizza. The company initiated Cheesy Bites and Stuffed Crust and brought Deep Pan to the
United Kingdom. The company is still leading when it comes to the sale of quality Pizza
Model development
The multivariate regression model developed from the socio-economic variables was formulated
in Ms excel. The data on the quantity demanded, the price of pizza and soft drink, tuition, and the
place where people live “rural and residential areas” were obtained from a Pizza Hut. The
variable, “if people live in residential areas, or if people live in urban areas” were treated as
dummy variables.
The data on sales for the firm was obtained from Bloomberg. The multivariate regression on
Excel enabled the development of the regression model for the socio-economic model