Develop a regression model for a topic in an attept to explain a phenomenon of interest.

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Question Description

Part Two will involve developing a regression model for a topic of your choosing in an attempt to explain a phenomenon of interest. In doing so, you will be required to locate data on the Internet and do the appropriate analysis. You will also have to explain your topic of interest, the variables chosen, and why the variables were chosen, in addition to presenting and explaining your results. Your paper should include the following:

 Introduction - describe the phenomena you are attempting to model and its importance (2 – 3 paragraphs)

 Literature Review (find at least two references) - who has done similar work and what were their findings? (2 - 3 paragraphs)

 Data - summary statistics of the data (2 - 3 paragraphs)

 Methods and Results - what analysis did you perform and what were the expectations for the model? Were your results similar to those in the references you used? (3 - 6 paragraphs)

 Conclusions (2 - 3 paragraphs)

Your paper must follow current APA standards. Be sure to include tables as necessary and to label them properly (review the APA manual and the readings from Module 1).

Throughout the course there have been many topics related to analyzing data that you should consider including in your write-up such as a graph of the data. In the Appendix, you may want to include graphs used to evaluate normal distribution. A discussion of the results of such analysis should be included in the results section of the paper.

An example of a potential problem would be house values. Many counties have online tax records, which include detailed information about a house. Data may include square footage of a house, whether there is a fireplace, square footage of a deck, whether there is a basement, finished basement square footage, and lot size. Collecting the data would take a little work and would require determining how many houses you should collect data from to be able to develop a model. This topic is off limits but there are many topics available to you.

PLEASE ADDRESS ALL QUESTIONS. NO PLAGARISM. WILL BE CHECKED BY TURNITIN.

PROVIDE ALL LINKS TO SOURCES USED AND USE PROPER, CURRENT APA FORMAT.

Tutor Answer

FinAccGuru
School: UC Berkeley

Please keep these as final answer. Thanks

Introduction
During the period of 2007-2012, the USA economy has experience an economic crisis
(Business Today, 2015). The house market crisis, also termed as subprime mortgage crisis, was
considered as impetus factor of this crisis. Along with the other causes, lack of due diligence
(low customer assessment and documentation), and adverse selection is considered as one of the
cause of the subprime mortgage crisis. Households’ net worth, households saving, and household
disposable income are factors that are considered to assess the creditworthiness and granting loan
to the customers. But it was found that the customers’ loans were not made in consideration of
these creditworthiness factors (Business Today, 2015).
This paper aims at understanding the underlying relationship of total mortgage loan
outstanding with the household net worth, household savings, and household disposable income.
The overall intention is to observe where outstanding mortgage loan was affected by households’
net worth, households saving, and household disposable income. Based on that it can be
understood whether the loans were granted in consideration of households’ net worth,
households saving, and household disposable income (the variables based on which the
customers’ loan repayment ability can be judged), or in consideration of others.
Literature Review
Several analysts and writer on theoretical basis have tried to point out the impact of lack of due

diligence and adverse selection on the mortgage bubble. These theoretical studies strongly
blamed the lack of due diligence and adverse selection as cause of the high and undesirable
mortgage loan disbursement, and mortgage loan problem (Business Today, 2015). No empirical
historical studies are found on which regression analysis was employed to assess whether loans during the
pre-crisis period was not granted in consideration of these creditworthiness factors.

But this study...

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