“Drive ‘til You Qualify”: Urban Sprawl and Residential Values in Metropolitan Los Angeles

“Drive ‘til You Qualify”: Urban Sprawl and Residential Values in Metropolitan Los Angeles

This assignment is designed to (1) provide you with some insight into the difficulties inherent in generalizing about the distribution of contemporary residential land values within a complex metropolitan area, (2) provide you with an opportunity to explore the unprecedented residential land values encountered in contemporary southern California, (3) encourage you to explore the “self-sustaining” nature of residential property values—i.e. why “driving until you qualify” tends to perpetuate residential property value on the urban fringe and encourages urban sprawl, and (4) require you to use empirical data to evaluate the nature of residential trends in metropolitan Los Angeles.

■ Research Question/Hypothesis:

There is an emerging consensus in urban studies that the US is currently undergoing a major shift in attitudes about what constitutes the ideal residential situation. From the end of WWII through the end of the 20th Century, the vast majority of Americans seemed to prefer to live in a large, single family home in a suburban location. The urban sprawl that characterized this period presumably reflected that preference as developers constructed suburban housing tracts to meet the market. More recently, however, Americans seem to be changing their attitudes about suburban living and more than 75% of “millennials” indicate they would prefer to live in a dense urban setting. Citing various economic and environmental factors, urban planners are simultaneously calling for a return to higher density urban development that reflects the way cities were developed before the automobile was the dominant mode of commuting and sprawl was largely unknown; “smart growth,” as it is known, promises more walkable communities with true urban densities and less environmental impacts.

If this is true—that Americans are ending their love affairs with suburban living (Gallagher’s hypothesis)—a decrease in suburban property values might be expected as the demand for homes in the suburbs drops. Similarly, if more Americans want to live in the urban core, the demand for urban residences would presumably be driving up prices in the central cities. Is that true? Do contemporary trends in residential property values reflect changing attitudes about the desirability of living in the suburbs versus the urban core? Fortunately, empirical data are readily available to answer that question.

► Hypothesis: As more Americans want to live in the urban core and fewer want to live in the suburbs, property values in urban areas are rising, while property values in suburban areas are declining.

► Assignment: Test the hypothesis by analyzing SFR sales in metropolitan Los Angeles

1) Compile a sample of “urban” and “suburban” SFR sales trends from metropolitan Los Angeles (using the Core Logic data discussed below).

For the sake of this assignment, pick 10 urban zip codes in Los Angeles County for areas of the county that you know are relatively centrally-located—i.e. are “urban” locations (if you are unfamiliar with Los Angeles County communities, get a map to help you identify zip codes that appear to be in the urban core—i.e. are relatively close to downtown Los Angeles).

Construct a simple table that shows the 10 urban zip codes you’ve selected and include the data for (1) the median price for SFRs in those zip codes and (2) the price trend for SFRs in those zip codes over the past year (labeled “price % change from [same month last year]” in the Core Logic table).

Now repeat this process for 10 suburban zip codes in the Los Angeles metropolitan area (i.e. in Orange, Riverside, San Bernardino, and Ventura Counties) that you know are essentially suburban areas. If you are unfamiliar with the metropolitan area, select zip codes that had a relatively high number of SFR sales—i.e. areas of these counties that appear to have significant residential development, as opposed to areas that are still largely undeveloped/rural.

Again, construct a simple table that shows the 10 suburban zip codes you’ve selected and include the data that indicate the (1) median sales price and the (2) price trend for SFRs in those zip codes over the past year.

2) Analyze the data in your tables. Have the 10 zip codes in each set gone up or down in value? If some zip codes in each set went up while others went down, what was the dominant trend in the set of ten? In your analysis you might calculate a mean for the ten zip codes price trends in each set that you compiled; again, the key question is did they go up, down, or remain stable? Now compare the two sets of zip codes; do the data support the hypothesis—i.e. did the “urban” zip codes go up in value, while the “suburban” zip codes went down in value as the hypothesis would suggest? Or was it the opposite, in which case the hypothesis would presumably be wrong? Or is there no dominant trend revealed by your analysis—if there doesn’t appear to be any trend, can you offer an explanation for that?

In addition to examining the percentages of price changes over the past year, you should also examine the median prices for each set of zip codes. Are property values higher in the “urban” zip codes or in the “suburban” zip codes? What does that suggest about the relative desirability and/or affordability of “urban” versus “suburban” areas? If property values are higher in the “suburbs” than in the “urban” areas, what does that suggest about the future pattern of residential development in our cities? Conversely, if suburban property values are lower than urban ones, what does that suggest about the future of American cities? What will happen when there is a significant “mismatch” between the housing supply and the market?

3) Based on your analysis, write a short paper (3 pages max, including your zip code tables) in which you (1) present and summarize your data sets and (2) provide your interpretation and analysis of what your data suggest about the future of residential patterns in metropolitan Los Angeles.

■ Reference: Core Logic Tables

Los Angeles County property values (by zip code) are conveniently compiled by Core Logic—an online real estate research organization. To find the appropriate data, log on to:

http://www.corelogic.com/solutions/configurable-real-estate-data-reports.aspx/

That should link you to a page headed “Configurable Real Estate Data Reports.” Toward the center of the page, left side, is a box with a header that reads “Standard Charts & Reports.” Click on the chart labeled “Southern California Home Resale Activity.” That link will take you to a multiple page table that provides data on the number of sales for the most recent month available, median price, and % of change from the previous year for single family homes (and condominiums) in cities in all seven Southern California counties. This data is tabulated by city/neighborhood name and zip code.

■ SFRs – For this assignment, restrict your analysis to single family home sales only (not condominiums). In the tables the two relevant columns are labeled “single family homes” and then abbreviated as “SFR” (single family residences).

■ “Five County Metropolitan Area” – While the Core Logic chart includes data for seven Southern California counties, it is conventional to define “metropolitan Los Angeles” as a five county area (Los Angeles, Orange, Riverside, San Bernardino, and Ventura Counties). For this assignment, restrict your analysis to the five county metropolitan area (excluding San Diego and Santa Barbara Counties).

► For the sake of this assignment, treat Los Angeles County zip codes as “urban” and those in the other four counties (OC, Riverside, San Bernardino, and Ventura) as “suburban.”

(Sample Table: 10 “urban” zip codes in Los Angeles County)

Community Name Zip code Price % chg from Aug 20XX
Compton 90220 12.1%
Culver City 90230 -10.3
LA/Baldwin Hills 90008 16.3
LA/Highland Park 90042 5.8
LA/Westchester 90045 24.2
Monterey Park 91754 11.8
Pasadena 91107 21.8
San Gabriel 91776 7.8
Torrance 90504 13.2
West Covina 91792 5.6

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