Econ 3050: Second-Hand Cars Assignment Research project (term paper ) guidelines Components of the term paper The paper that you should write should have the following components Identification of the problem/issue Theorization of the problem to as much detail as possible Construction of the mathematical model General assumptions about the linear regression model and the […]

**Components of the term paper**

The paper that you should write should have the following components

- Identification of the problem/issue
- Theorization of the problem to as much detail as possible
- Construction of the mathematical model
- General assumptions about the linear regression model and the parameters of the model
- Description, method of collection, and source(s) of data
- Application of statistical /quantitative method and its justification
- Reporting and analysis of the results
- Conclusions
- References
- Footnotes/endnotes

State very clearly the problem/issue you are investigating. Mention why this is an interesting and important exercise. Also, mention what you hope to learn at the end of your analysis and how your analysis might be helpful to others.

Give a theoretical description of the relationship between/among the variables in question to as much detail as possible. Example of a simple Keynesian consumption function.

Present the variables and the relationship between/among them in mathematical form. Define them and explain what is what.

*Example of a consumption function;*

C_{1} = a + bY_{d} + U

List general assumptions of the classical linear regression model from your text. Under your own theory, what do you assume about the relationship between/ among the dependent and explanatory variables and the model's parameters?

What kind of data are you going to use to estimate the model? Define your data. What is your sample size? Why is it so?

Give a detailed source(s) and/ or data collection method.

Describe in detail the statistical technique that you are using. Describe why you are using a particular technique/ methodology over other.

- Estimate the equation.
- Summary statistics, t, R
^{2}, SEE (standard error of estimates) - Analysis of them

The purpose of this section is pretty straightforward. If someone barely has time to read about one page or less, the right section would be the conclusion section. Here you need to answer the following: What is the central message of your research? How can others use the insight that your research generates? What is your main advice? This section MUST BE absolutely non-technical in nature. Even a non-specialist should be able to read the section and understand the main feature of your work. You should also include the limitations of your research and give future direction as well.

Cite all books, magazines, articles, websites, etc.

If you use a word/term that needs elucidation, please use footnotes or endnotes consistently.

**Price of Spare Parts.** Most consumers tend to prefer cars whose spare parts are cheap and readily available. Such cars, hence, have high demand, and their value tends to be high. Therefore, the price of spare parts negatively correlates to the value of a used car.**Price of Other Models of Cars.** If Ford and Nissan's cars cost much higher than Toyota cars, then consumers would prefer what is affordable. Hence, the price of other car models is negatively correlated to the value of a used car.**Automatic Transmission.** More people are attracted to cars with automatic gear transmission systems as opposed to manual. Thus, this system is positively correlated with the value of a car.**Colour.** The color of a car makes consumers spend much in purchasing an automobile. Precisely, popular color is positively correlated to the value of the car.**Mileage.** This is the distance in miles that a car has traveled in its life. A car with higher mileage will likely break down due to wear and tear. Hence, the higher the mileage, the lower the value of a used car.**The Year of Manufacturing.** A car that was manufactured like 10 years ago costs less when compared to a car made just one year ago. Hence, the number of years since a car was made negatively correlates to the value of a used car.

In the USA, many consumers prefer buying used cars for various reasons, but the price factor is the dominant cause. Many citizens have shifted their focus from using public transport automobiles, taxis, and rented cars to owning private vehicles. This trend explains why almost every household in the USA owns at least one car. For the sixth year in a row, the market for second-hand vehicles has continued to grow by over 6% (“Used Car Market: What’s Driving Growth?”). This spurred growth is expected to continue until an unknown time in the future, and this means that more Americans will own used cars as time goes by. With reliable information that the used-cars industry in the USA is thriving, there are sufficient reasons why research seeking to unravel the factors determining the value of used cars in the USA is relevant. Therefore, the fundamental goal of this research project is to tell which are the most critical factors a used car buyer or trader should consider to know the actual value of the automobile they are about to purchase.

The used cars industry in the USA has been there for a long, but it has only experienced tremendous growth in the past few years. This means that most market players (buyers and traders) are oblivious to what factors they should consider when purchasing a used car. So, what aspects do buyers of second-hand cars consider when making purchases, and what should they consider? This is a critical issue/problem that needs to be addressed. As of now, it is public knowledge that consumers make purchasing decisions based on elements such as the brand of the car, engine capacity, the type of gear transmission, color, mileage, and vehicle condition. This clue of what aspects could influence the price of used cars is the first step in establishing the real determinants of the value of used cars through research. At the end of the analysis, the findings will be essential, especially for those who intend to purchase used vehicles.

The foundation of the economic aspect of business decisions is the theory of demand and supply. In simple terms, the resolve to buy a used car is based on the influence of market forces. Demand considers three attributes: the desire to acquire, the ability to pay, and the motivation to spend (Singh). In the market, demand is subject to the influence of several factors, which are discussed in detail below.

Price of Commodity (P_{N}). The price of a commodity, for example, a used car, depends on the price of related products. In this context, “related” implies that the other products are either complimentary goods or substitute goods (Singh).** A product becomes less desirable when the price of complementary goods is high**. A commodity becomes more desirable when the price of substitute goods is high. This is the basic concept of demand and prices, and it can be mapped to the problem identified for this research project. If spare parts and fuel of a used car (complimentary goods) are expensive, consumers find the car unsuitable for purchase. This could explain why second-hand car buyers refrain from buying fuel guzzlers. Consumers purchase a product if the price of substitute goods (other car models) is high. This explains why the Toyota model of cars is more popular than German cars such as Mercedes Benz in the USA.

**Taste and Preference of Consumers (T).**** **Every consumer has his/her unique taste and preferences (Singh). As a result, certain commodities tend to have a higher demand and, therefore, prices when compared to others. In the case of the problem identified for this research project, some consumers are likely to prefer white cars instead of red or black cars. Others are likely to desire automatic-gear transmission cars rather than manual-gear transmission automobiles. If most consumers prefer white cars to red cars, the value of these cars will definitely be high.

**Other Factors (O). **The demand, and hence, the price of a commodity, could be influenced by a wide range of other factors. They include demographic factors, marketing effects, social pressure, household income, and perceived value. In the case of the identified issue for this research project, these “other factors” include mileage and manufacturing year.

The factors highlighted above influence the demand and price of a commodity, and a simple theoretical model can be derived as shown below.

QdN (f) = f {(PN) ± (T) ± (O)}

**Construction of the Relevant Regression Model**

This model (QdN (f) = f {(PN) ± (T) ± (O)}), in the case of the issue of the used car, can be adjusted as shown below.

QdN (f) = f {(price of spare parts ± price of other models of cars) ± (automatic transmission ± color) ± (mileage ±the year of manufacturing)}

Each of the identified variables has a unique correlation to the value (QdN) of the used cars, as discussed below.

• Price of Spare Parts. Most consumers tend to prefer cars whose spare parts are cheap and readily available. Such cars, hence, have high demand, and their value tends to be high. Therefore, the price of spare parts negatively correlates to the value of a used car.

• Price of Other Models of Cars. If Ford and Nissan’s cars cost much higher than Toyota cars, then consumers would prefer what is affordable. Hence, the price of other car models is negatively correlated to the value of a used car.

• Automatic Transmission. More people are attracted to cars with automatic gear transmission systems as opposed to manual. Thus, this system is positively correlated with the value of a car.

• Colour. The color of a car makes consumers spend much in purchasing an automobile. Precisely, popular color is positively correlated to the value of the car.

• Mileage. This is the distance in miles that a car has traveled in its life. A car with higher mileage will likely break down due to wear and tear. Hence, the higher the mileage, the lower the value of a used car.

• The Year of Manufacturing. A car that was manufactured like 10 years ago costs less when compared to a car made just one year ago. Hence, the number of years since a car was made negatively correlates to the value of a used car.

The precise model is, hence:

QdN (f) = α- β_{1} price of spare parts + β_{2 }price of other models of cars + β_{3} automatic transmission + β_{4 }color- β_{5 }mileage- β_{6 }the year of manufacturing.

Linear Relationship. This is an assumption that each of the independent variables explains the dependent variable linearly. In this case, the majority of the scatter plots are close to one another with only a few, if any, cases of outliers. A straight line, in other words, can be drawn such that most of the scatter plots fall on it and not below or above it.

No Auto-Correlation. The model has both dependent and independent variables. The independent variables are correlated to the dependent variable but not amongst themselves. This is to mean that there is no multicollinearity.

Normality. The regression model follows a normal curve; hence, the residuals are not skewed.

Equality of Variance. From the scatter plot, linearity, given the Y and X-axis, is expected to be observed. This is confirmed when the plots do not form a triangular shape.

The Parameters of the Model. They are either negative or positive depending on the factors at hand. The negative parameter indicates an inverse relationship, while the positive parameter indicates a positive correlation.

In the regression model highlighted above, both quantitative and qualitative data will be estimated. Some of the factors alleged to influence the price of used cars can be quantified, while others, for instance, color, cannot. That is why the model will be estimating both quantitative and qualitative data. Data will be collected from consumers in the USA through an online survey. Besides, online portals that provide information on second-hand cars demanded in the USA will be used as a source. The sample size for the online survey will be 1000 people, while a total of 100 cars will be sampled from the online portal that will be consulted.

Given the highlighted model and the collected data, the expected regression model is as follows.

QdN (f) = α- 0.5 price of spare parts + 0.6 price of other models of cars + 0.4 automatic transmission + 0.05 colour- 0.8 _{ }mileage- 0.7 the year of manufacturing

QdN (f) = α- 0.5 Psp + 0.6 Pmc + 0.4AT + 0.05 C- 0.8M – 0.7 YOM

The parameters are replaced by positive and negative figures showing each factor’s weight in determining the value of a used car in the USA. Negative values of 0.5 or above show the most critical factors that reduce the value of used cars, while positive values above 0.5 show the factors that increase the value of these cars. Since color has a parameter that is below 0.5, it is not a significant determinant of the value of a used car.

Purchasing a car in the USA used cars market can be challenging since prices are skewed. However, this research project has identified the price of spare parts, the price of other models of cars, automatic transmission, mileage, and the year of manufacturing as the key determinants of the value of a used car. This is what the consumers need to know. It was definitely challenging to come up with a precise regression model. Through a lot that has been explored, there is a need for future research focusing on other factors that have not been covered in this research project.

Works Cited

Singh, Jean. “6 Important Factors That Influence the Demand of Goods.” Economics Discussion, 29 Aug. 2016. Accessed 4 Dec. 2018.

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