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Drawing the Boundaries of Suburban Geography

Suburbs can be amorphous and hard to grasp. Where does a city end and a suburb begin? Where does a suburb end and a rural area start? Reportedly, 52% of Americans describe their home neighborhood as suburban. Yet, the US Census does not have a definition for a suburban area. The term suburban is considered more of a colloquialism in today’s world. 

In this piece we will look at how MSG defines suburban geography and how the geo-demographic team compensates for the US Census’ shortcomings and discrepancies.

To define a suburban area properly, we must look at all underlying geographic components – in particular urban and rural. To do this, we start by looking at Metropolitan Statistical Areas (MSA) as defined by the Office of Management and Budget (OMB). 

MSA’s are defined as urban areas of at least 50,000 people with one or more adjacent counties that are socioeconomically tied to that urban center. There are over 360 MSA’s currently defined in the US and each MSA has one or more principal cities. 

Traditionally, we consider principal cities to be the core socioeconomic center with the counties surrounding it dependent on it.  

Now, let’s think about how the US Census delineates cities and urbanity. The Census defines urban as being within the principal city of an MSA and any census block outside of the principal city that meets a specific population threshold. 

The problem is that the US Census does not distinguish between suburban or rural areas. It just assumes that anything not urban is rural. In fact, no government entity defines what a suburban area is.

Here we encounter a massive disconnect. According to Pew Research, a growing share of the population in the United States is living in suburban counties of large metropolitan areas. And as we already noted, a majority of Americans say they live in the suburbs. Suburban communities, moreover, have a distinct geo-demographic identity compared to urban and rural areas, yet the government doesn’t really account for it! Compounding the problem is the slippery nature of the term “suburban.” It can mean different things in different parts of the country. 

All of this means that we have to define what suburban is ourselves. Marketing Systems Group’s geo-demographic team has developed their own definitions of suburban areas to compensate. 

Taking a simplistic approach, we take the census blocks within the principal cities of the MSA’s and keep them coded as “urban.” Any census block outside these principal cities that was classified as urban by the Census we now classify as “suburban.” On the other hand, any census block classified as rural by the Census remains “rural”.

Additionally, we can apply an urban/suburban/rural rule to any kind of geography or polygon. For example, we could take a ZIP code and classify it as urban, suburban, or rural. This is done by rolling up the underlining geography (census blocks) and determining whether the population (or land area) within a ZIP code is predominantly urban, suburban or rural. However, we could end up with a checkerboard affect with how the census blocks distributed across urban, rural, and suburban, so some care is needed.

We can also leverage our Addressed Based Sampling (ABS) frame to our advantage. Using ABS, we can identify population growth in areas in a shorter time frame instead of relying upon decennial Census data, which is only updated once every 10 years. If you are trying to define suburban areas, which can grow suddenly and dramatically, you will see how stale the data can become if you merely rely on decennial Census data. Using ABS gives you a more current, more accurate picture. 

For more insight, click here and check out Coffee Quip episode 8, Geo-demographic Methods: Suburban Geography, featuring Dennis Dalbey, Manager, Geo-demographic Services, and David Malarek, Senior Vice President, Sampling & Database Services. 

Hybrid Sampling: Why a Blended Sampling Approach Is a Sensible Option

In an ideal survey research world, it is preferable to work with a single probability-based sample as it provides the best representation of the target population. In the real world, however, cost and feasibility often prohibit the luxury of using purely probability-based samples. This is where different sampling methods come into play to reduce cost and improve feasibility, especially those that rely on online panels. All in all, online sampling isn’t ideal, since such samples are void of “organic” representation. If you can’t get generalizable results from your surveys, then what’s the point?

A blended (hybrid) sampling approach can offer an effective and practical alternative, through which multiple frames are used for sample selection—oftentimes a combination of probability-based and convenience samples from online (opt-in) panels. Further, we might start with a fully probability-based sample from a telephone or address frame, but then tap into online panels to supplement what we get from the main probability sample.

Taking a hybrid sampling approach sounds well and good, but just because you’ve gone hybrid doesn’t necessarily equate to unbiased survey results. Sampling from online panels is always a little tricky because if you don’t know what you’re doing, you can end up taking a seemingly inexpensive sample component, mix it with your precious probability-based sample and end up with a poor combination.

Sure, theoretically it’s preferable to have all or most of the samples be probability-based, but they are expensive. At the same time, you don’t want samples from opt-in panels dwarfing your precious probability-based sample. As a general rule of thumb, something on the order of no more than 50% of your sample should be coming from opt-in panels. Keep in mind that budget and other factors may dictate a higher or lower contribution.

The selection of samples from opt-in panels needs to be carried out sensibly. Equally important is the way you blend the probability and nonprobability-based sample components to produce a single database capable of producing reliable conclusions. It’s a little bit like chemistry when different materials are tossed into the mix to produce an alloy with higher-level properties; you have to be measured about it and get the ratios down just right using correct weighting and calibration adjustments.

As response rates continue to decline into single digit territory, even with fully probability-based samples, geodemographic weighting of survey data becomes essential. This is proven true since nonresponses are always different in nature. However, this issue will magnify with hybrid sampling when part of the sample may come from opt-in panels. Hence, in addition to basic weighting, additional calibration adjustments become necessary as well. This means going beyond geodemographics and applying corrections based on attitudinal and behavioral characteristics to ensure respondent representation for their population.

If you are looking to enhance your phone or address-based surveys and supplement them with samples from online panels, survey research scientists at MSG have decades of knowhow and hands-on experience to support your hybrid sampling methods. Our experts can assist you with sample selection, survey administration and questionnaire design, as well as state-of-the-art weighting and calibration procedures. Additionally, we can support you with reporting and analysis of data from complex surveys.

To learn more about our hybrid sampling products and services, click here, or contact one of our specialists.

For a deeper dive, watch Episode 06 of our Coffee Quip YouTube series, wherein the panelists discuss the intricacies and benefits of Hybrid Sampling!

4 Surefire Ways to Increase ABS Response Rates Without Breaking the Bank

So you found the perfect sampling source with nearly 100% coverage and the ability to reach cell phone only homes with address based sample.  One can expect to get the completes needed but realistically what type of response rate will you achieve?  How can you boost it? Continue reading “4 Surefire Ways to Increase ABS Response Rates Without Breaking the Bank”

AAPOR ‘s Task Force on Address Based Sampling

In January of 2016, AAPOR ‘s Task Force on Address Based Sampling published it’s finding for the AAPOR Standard’s Committee.  MSG’s Trent Buskirk and David Malarek played a pivotal role in the formation of the ABS Standards.  Below is the Abstract for the report.  The full report can be found here: Continue reading “AAPOR ‘s Task Force on Address Based Sampling”

Harvard Case Study

MSG continually tries to build bridges to the academic and social science world by using long established contacts coupled with the will, desire and need to use its assets to assist in projects that serve the public good.  Frequently these projects involve project consultation, pro bona delivery of sample frame design and data or, as was the case with an MSG/Harvard University project a combination of all three.

In the Fall of 2014, the student’s in Professor Chase Harrison’s GVT 1010 Undergraduate Survey Research class undertook a multi-mode project to gauge the urban/suburban attitudes of residents in the Boston area.  MSG supplied not only the ABS sample but also allowed the students to consult with MSG personnel.  The result was a high response rate and statistically sound survey finding.  MSG would like to let all of academia know that we are available to work on select projects and can offer advice, suggestions and data if the project meets qualifications.

As Professor Harrison commented “MSG’s willingness to donate the sample for this project is just incredible.  I always encourage my students to use the best tools available, although I don’t always have the resources to help them use those tools, especially for things like general-population samples.  Thanks to MSG, this group was able to use a sample that otherwise would have been beyond their reach, and were able to experience what it is like to work on real-time survey with professional tools.”

Click Here for the full case study.