BUSI344 CHAPTER 4.2 Flashcards
Identify the main steps of an appraisal assignment leading to selecting the correct market segment.
Explain the two fundamental components (subject/market) of the process of identifying thecorrect market segment.
What are the four “dimensional aspects” of the valuation solution.
How do these help and determine margins for the data frame and the most likely dataset to be used in the analysis?
What are the relevance and differences between the subject neighbourhood, the relevant district,and market segment;
Distinguish between a “sufficient” dataset from a data frame, and identify aspects or characteristics which may require additional research.
What circumstances dictate reconsideration of a dataset.
Explain how experimental method principles of control, randomization, replication, and blocking apply to valuation.
In Case Study 3, we examined the potential motivation related to vacant property sales. In our analysis, we also calculated the mean and median sale prices for tenant-occupied property sales. Do the reported means and medians for tenant-occupied properties make economic sense, as they relate to the other two values?
Yes, they do make economic sense. While tenants provide an income during the time of marketing, their presence may deter some buyers, who have a need to move in. Showing homes with tenants can be less pleasant than homeowner-occupied or vacant properties. There may be a confounding variable. It can be reasonably argued that, on average, tenant-occupied properties are more poorly maintained than owner-occupied properties. If so, the surrogate variable is measuring both the condition of the property, and its effect on both buyers and sellers. Perhaps the “occupant” data field is not as good a surrogate variable in the case of tenant-occupied properties as for vacant properties.
Two reasons were discussed for why an analyst might need to go back to expand an original dataset or even widen the data frame. One reason was simply that more data was needed. What was the other major reason and why is it important?
The analyst may need to expand a data set or data frame if more data is needed or if the optimal use is not what was originally asserted when the appraisal problem was identified.
4. (a) What are the four dimensions of comparability (similarity) and why are they important to identifying the right market?
(b) The transaction dimension has three elements. How do these differ substantially from the other three dimensions?
(c) The utility dimension encompasses the two fundamental types of property benefits, amenities and income. What are the three forms of utility?
4. (a) The four dimensions of comparability are: transaction elements; time; space; and utility characteristics. They are important because their relative independence enables simple regression and centres comparison methods.
(b) The elements of transaction terms do not measure any attributes of the property, only the contract and motivation.
(c) Similar to optimal use issues, the three forms of utility are physical characteristics, legal permissibility, and financial characteristics.
5. What are the five stages of data reduction for our purposes?
5. The five stages of data reduction are: a) data base or data sources; b) data frame; c) market data set; d) information set; e) illustrative set.
6. While neighbourhoods and districts are important to real estate economics, what economic division is the one we primarily rely on for defining our datasets? How is it defined?
We primarily rely on market segment.
Market segment is defined as a homogeneous market, as characterized by a set of similarity variables.
7. Name two major types of changes in market conditions (time)?
7. The two major types of changes in market conditions (time) are trends and event impacts.
8.
(a) How is information “better” than data?
(b) How is an information set different from the market dataset?
8.
(a) Information is data that has been organized to make it useful and understandable.
(b) An information set is a subset of the data set, useful for a particular analytic method.
9. What statistic is most useful in identifying the best unit of measure?
9. The main statistical measures useful in identifying the best unit of comparison is the correlation between sale prices and that particular variable (the higher the better) and the coefficient of variation of the variable itself (the lower the better) .
10. Why do you save sales deleted from your dataset in a separate file?
10. Saving deleted sales from your data set in a separate file helps with documentation and enables audit.
11. Appraisal has historically used less intensive data analysis methods. Why? How has this changed today?
11. Historically, appraisal has used less intensive data analysis methods because data was poor in quality, difficult to obtain, and difficult to analyze. Today, good quality data is much more easily available and computing power and software have made it much simpler to analyze effectively.
12. What is the difference between “reliability” and “credibility”?
12. Reliability is the more statistical term, relating to low variability (precision). Reliability is measurable. Credibility means worthy of belief and is more subjective, but equally important. Appraisal credibility can only be evaluated in terms of the intended use of the appraisal. Credibility includes appropriateness of the model used, as well as mathematical reliability.
13. Multiple regression analysis (MRA) is a powerful tool. Why don’t we just use MRA to solve all valuation problems?
13. Multiple regression analysis (MRA) is a powerful tool, but we have emphasized other tools in this lesson for two reasons: 1) simple graphs and two-variable statistics are easier to understand and explain to clients; 2) comparison of means and medians as well as simple regression can be used in conjunction with MRA, or within traditional procedures.
14. How is similarity identified and measured?
14. Similarity is defined by problem identification, including assignment conditions. It is measured by the four dimensions of similarity: transaction, time, space, and physical/financial utility.
15. You have started an internship with an older well-respected appraiser. Everyone tells you that you are lucky to get a position with someone of his stature. You are ready to begin applying your modern tools. You get your first assignment, and enthusiastically download what you believe is a good market dataset. Being your first assignment, you have your new mentor check your search parameters. He laughs, and says: “All that statistical stuff is OK for school, but a good appraiser never needs to use more than three ‘comps’! Just pick the best three and use those”. What can you say?
15. You face an interesting dilemma, if you have what you believe is a useful tool, but something your mentor does not believe in or perhaps does not understand. You will have to decide whether to do exactly what you’re told or whether to try and introduce something new to the process. This may be a business decision mixed up with an ethical question.
The profession has a long tradition of new appraisers learning new things, then bringing them to practice through their work. Being a professional requires tact as well as being “right”. If you were to take an all-or-none “MRA or bust!” attitude, you will likely lose your opportunity to bring new methods to the “old guard” and also to provide additional value-added techniques to clients.
The simple regression and grouped comparison methods you have learned here can provide a bridge between traditional methods and modern technology. Graphs, scatter plots, trend lines, and group comparisons are intuitive and easily understood. You can consider bringing these methods into your work, doing good for clients, your own reputation, and the future of the profession.
16. What are the four appraisal principles of experimental design? Provide a one-sentence explanation of each
The four appraisal principles of experimental design are control, randomization, replication, and blocking.
(a) Control: limiting data to homogeneous group(s).
(b) Randomization: relying on control (bracketing and balancing), so that elements are distributed by chance.
(c) Replication: relying on similar “experiments,” or similarity of missing information.
(d) Blocking: exploiting “natural” groupings of variables.
17. (a) List the sequence of five data group subsets we have learned regarding data reduction.
(b) Which of the above sets is most similar to the traditional three comparable sales?
17. (a) Five subsets in data reduction: database, data frame, market dataset, information set, and illustrative set.
(b) The illustrative set serves the best simplicity aspects of the traditional “3 comps” report.
