Due date: Possible Score: Work required:
Submission:
April 9, 2023 (Sunday) 11:59 PM (PST)
This project can be done alone or in teams with up to 2 people. If you are going to work as part of a team, I must receive an email by Friday (2/17/2023) with the name of both team members; otherwise, I will expect a solo submission (No exceptions). Your team member must be someone who is NOT on any of your other team Homework Assignments. Feel free to email to me your questions on the homework, or ask questions before, during, or after class.
Upload the file with your solutions (.doc or .pdf) on our Canvas class page along with the Excel file showing the raw data and calculations in the following manner:
Last Name(s)_FRL4832_HW2_Spring_2023. The write up should be submitted in Times New Roman or Calibri with an 11 font and single spaced. If you work in a team, put both names on the front page of your submission, and decide which one of you will upload it to Canvas.
The purpose of this homework assignment is to give you the opportunity to review and show your skills with the calculations we learned regarding different ways time series data can be forecast. Moreover, it will enable students to demonstrate their understanding of the calculations that are used for determining the size of a trade area based on supply and demand in the retail sector.
If you are comfortable with Excel, it will speed things up for you, as Excel is required for this assignment. Be sure to copy your Excel tables into Word and provide a detailed explanation as to how all answers were developed. If you followed everything we are doing in class, have reviewed the Power Points, and did the chapter reading, you should be able to complete this assignment in a couple of hours or less (especially as a team). Otherwise, you will need to review our slides as well as the assigned reading and may need to plan to spend a day or two on the assignment. Although I do explain in the assignment instructions which website you should use and how to navigate the site, plan to spend some time getting the required data online first.
Solve 5 numerical problems given on the ensuing pages. I will do the grading on Canvas within one (1) week, and we can go over any questions in class.
Each Problem is worth 10 points. See next page for grading rubric and examples.
Homework Assignment #2
Grading criteria:
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Below is the rubric I will be using when grading your solutions to each problem:
I expect to see the following:
Show correct numerical answer
Numerical answer is incorrect because of a typo somewhere in the calculations OR
Numerical answer is correct but only in some intermediate steps
Show correct formulas
Show correct numbers that go
into the formulas Appearance
Not shown Not shown
Handwritten
Shown for some, but not all, steps Shown for all steps
Shown for some, but not all, steps Shown for all steps
Partially hand-written and partially Typed typed
Brief verbal explanation: why you’re doing what you’re doing in each step
Shown for some, but not all, steps
Shown for all steps
You are offered an investment that guarantees to pay you back $200 per month for the next 5 years. The annual rate of return for similar investments is 12%. What is the most you should be willing to pay for it today?
Great answer!
(2 + 2 + 2 + 2 + 2 = 10 points)
Needs-some-work answer
(1 + 1 + 1 + 0 + 2 = 5 points)
This is an annuity problem because the problem is talking about the same cash flow ($200) repeating a number of times.
The problem is essentially asking to calculate the Present Value of this annuity. The formula is: PV = C x (1/R) x (1 – 1/(1+R)T). (OR: I can use the financial calculator and enter PMT, N, and I/Y keys to solve for PV.)
First, $200 is repeating monthly, and so I need to use the monthly rate and the number of months. Monthly R = annual R / 12 months = 12% / 12 = 1%. Number of months = 5 years x 12 months per year = 60 months. Then, I plug in the numbers into the annuity formula where I use C=200, R=0.01, T=60. (OR: Then, I plug all resulting numbers into the financial calculator: PMT=-200, I/Y=1, N=60, CPT PV.) This gives $8,991.01.
So, I would pay no more than $8,991.01 for this investment.
I/Y = 12 PMT = -200 CPT PV $720.96
Q: What’s missing?
A: Intermediate steps explaining & calculating the right numbers to be used for “N” and “I/Y”. Explanation in own words showing you know what you’re doing.
The questions in this homework assignment are based on data that you should collect from three (3) websites: (1) Bureau of Labor Statistics (www.bls.gov). (2) U.S. Census Bureau (www.census.gov), and (3) Simon Property Group (www.simon.com).
For each question, show in your write up all numbers you are working with, and explain all relevant calculations. Be sure to show the data that were downloaded in your Excel sheet, so I can verify your numbers, and upload the Excel document to Canvas along with the write up portion.
Problem #1 (10 points)
The manager of a shopping mall has noticed a continuous drop in overall mall sales in the last few years. Therefore, she decided that she might need to attract some new tenant shops. Her quick glance at the tenant mix indicated that shops selling clothing and footwear appear to be underrepresented in her tenant clientele. She knows that the majority of shoppers who come to her mall are people between 25 and 34 years old. The manager would like to identify the best rent per square foot of leasable area that she should offer to new tenants in the clothing and footwear sector. For that, she hired you as a real estate market analyst and asked you to calculate the purchasing potential of consumers in this age bracket for 2022.
a. On the Bureau of Labor Statistics (BLS) website go to “Data Tools”. Under “Data Retrieval Tools” select “One Screen”. Once there, search for the database on consumer spending collected from BLSs Consumer Expenditure (CE) Survey, which is under the Spending & Time Use section. Both the “one-screen data search” (green button) and “multi-screen data search” (yellow button), among others, should be able to help you find the data needed to solve this problem (I personally think one screen is much easier to navigate). Spending on clothing and footwear is labeled as “apparel and services”. What are the annual expenditures for 2011-2021 for the group noted above? Show results in a table and in a time series graph.
b. Forecast the expenditure for 2022 using the four moving-average (MA) methods below.
1. 2-year simple MA,
2. 3-year simple MA,
3. 2-year weighted MA,
4. 3-year weighted MA
Based on your analysis of the methods above, which one should be used in developing the 2022 forecast? Why? Show and explain all calculations and show the numbers used in performing your analysis and calculations.
Problem #2 (10 points)
Parts (a) and (b) of this problem are looking at the Location Quotient technique that is commonly used by real estate market analysts to see how concentrated a particular occupation, industry, demographic group, etc. is in a specific region as compared to a larger geographic area, such as the entire nation.
For both parts (a) and (b), show and explain your calculations, and show the numbers that you plugged in to do your calculations. (Hint: Read Chapter 3 of the textbook used in this course, as it will provide insight to location quotients and various NAICS codes and where to find existing location quotients using the (BLS) website. How does this compare to your calculations?)
For the source of data, visit the U.S. Census website (use Google Chrome). Always start by clearing all filters just to be safe. If you would like to navigate yourself, on the main page, hover the cursor over the “Explore Data” tab and select “Explore Main Data” from the selection window and then select “Tables and Maps”.
a. You are interested in the concentration of employees in different industry sectors – in a metropolitan statistical area of your choice as compared to the entire USA. The US Census website has information on the number of employees in your base area in different NAICS sectors. In conducting your analysis, select the most recent available year. Which year is that? What do the results tell you about potential real estate investment opportunities in your picked analysis area? What type of investments would instead not be a good idea?
b. Now, do similar Location Quotient calculations, except this time based on the population distribution by age rather than employment by industry. Compare any county of your choice with the entire state in which it is located – what are the relative concentrations of the population in different age groups? What does this tell you about potential real estate investment opportunities? For example, you may find that your chosen county has a high concentration of the population above 65 compared to the state statistic, which may suggest a good potential for senior housing developments; and so on. Again, show the numbers for the most recent year with available data (which year is it?).
Problem #3 (10 points)
Simon Property Group (www.simon.com) is one of the largest real estate companies in the world and owns hundreds of shopping centers in the North America, Europe, and Asia.
a. Pick one of the Simon Property Group’s shopping centers in California. On the website (this is where you will find most of this information), find and summarize in your write-up information for (visit “Portfolio” at the bottom of the page):
• Mall type
• Main anchors
• Size of, and information on, trade-area resident population
• Size of, and information on, trade-area non-resident population
• Main competitors in the trade area that the website provides
b. Using “Reilly’s Law of Retail Gravitation”, calculate the break-point distance for your shopping center in part (a) relative to the nearest Simon Property Group shopping center. Use the shopping center GLA size in place of the “population” information in the formula. What does the result tell you? Explain.
Problem #4 (10 points)
A real estate investment company in Southern California is applying for a construction loan for a proposed new gated community with 250 single-family detached houses. If the loan is approved, they can start the construction as early as next week and have all houses completed and available for sale in 2023 (Hint: You will need to calculate 2022 in order to calculate 2023 figures). The company’s research department recently performed a market study and identified Orange County, CA to be the main market area that will draw the majority of households interested in buying the houses in this price range.
For both parts (a) and (b), in the excel worksheet, show and explain all calculations as well as the annual household numbers that were used in developing the calculations.
For the source of data, visit the U.S. Census website (use Google Chrome). Always start by clearing all filters just to be safe. If you would like to navigate yourself, on the main page, hover the cursor over the “Data & Maps” tab and select “View all data resources” along the left-hand side of the selection window and then select “Tables and Maps”.
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a. What does the company’s research team project for the total number of households in 2022 & 2023? The team used the regression forecasting technique (This calculation should be done by hand. Do not use the Excel Add-in feature). It obtained information on the historical numbers of households in Orange County, CA for recent five years, 2017, 2018, 2019, 2020 (no data – see following note), and 2021 from the US Census Bureau website Tables, select the appropriate “Geography”, the appropriate “Topic”, and the ASC 1-year estimates comparison, based on the American Community Survey (ACS). Also, due to Covid, the area does not report 2020 Housing units, so use 2019 figures for 2020.
b. What is the required capture rate for this project, assuming the demand for new housing comes only from the increase in the number of households in the trade area?
Problem #5 (10 points)
For Los Angeles metropolitan statistical area (Los Angeles-Long Beach-Anaheim, CA Metro Area), calculate the Actual Sales Index (ASI) for “Health and personal care stores” based on the most recent available data. For the source of data, visit the U.S. Census website (use Google Chrome). Always start by clearing all filters just to be safe. If you would like to navigate yourself, on the main page, hover the cursor over the “Data & Maps” tab and select “View all data resources” along the left-hand side of the selection window and then select “Tables and Maps”.
Select the appropriate geography, the NAICS retail category code (446), and Topic (Business and Economy) to the find the “Sales, Value of Shipments, and Production” category. Under this NAICS retail category, locate the most recent year that reports retail sales volume, which is typically shown in thousands, so you will have to add 000 before you calculate the average expenditure per person in the MSA and nationwide. (Hint: to calculate the average expenditure per person and develop the ASI, you will have to look up the populations for the MSA and the U.S., and the divide the sales revenue by the population for each). Be sure you select the population estimate from the same year as the survey.
In addition, for the most recent year in the same geography, calculate the Spending Potential Index for “personal care products and services”. For this data, visit the Bureau of Labor Statistics website, in the search line type “Consumer Expenditure Survey Tables” (CEX). Once on this page, select the appropriate geography (Western MSAs) and find the average expenditure per person in the “Los Angeles Region” as well as nationwide (all consumer units). Be sure to use the same year as used in developing the ASI conclusion above.
Do your results suggest “leakage” or “inflow” of consumer spending in Los Angeles MSA? Explain. How can this finding be used in real estate market studies?
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