Downtown Retailing in Smaller Rural Regional Centers Under the New Normal

Posted on October 18, 2016 by DANTH

By N. David Milder

Introduction

This article is a follow up to: “The Changes in the Retail Industry That Are Impacting Our Downtowns” which can be found at: https://www.ndavidmilder.com/2016/09/the-changes-in-the-retail-industry-that-are-impacting-our-downtowns and “How Smaller Rural Downtowns Are Faring Under the New Normal’s New Retailing“ which can be found at: https://www.ndavidmilder.com/2016/10/how-smaller-rural-downtowns-are-faring-under-the-new-normals-new-retailing

Following the path of the last article, it also will explore how the changes in the nation’s retailing are manifesting themselves in different types of downtowns. The changes this article will look at are:

The emergence of the deliberate consumer
Reduced demand for retail spaces
The growing strength of e-commerce
The continued growth of a broadly defined “value” category of retailers
The decline of traditional department stores and traditional specialty retailers
The uneven opportunities for small merchants

This time the focus will be on downtowns in Smaller Rural Regional Commercial Centers. Again, I will focus attention on a few that I know well, because I have visited them and previously done research about them. These downtowns or the communities they are embedded in have seen the substantial decline of traditional department stores and/or traditional specialty retailers and/or the retail malls that depend on such tenants.

I suggest that many of the conclusions and observations I make below should be treated as hypotheses, since I cannot claim that they are based on a rigorous, wide reaching, systematic research effort. However, I hope that the discussion below convinces readers that I have done enough number crunching, field visits, personal interviews and analytical thinking to warrant my observations and conclusions being deemed worthy of serious attention and consideration.

Many of the old rules of the retail game are still in effect. Bad urban design and the lack of appropriate spaces can still thwart downtown retail health and growth. Also, the dynamics of constructive economic destruction can still mean that when some retailers falter in a market, others have the opportunity to enter and compete for that lost market share. If retailers are not open when people want to shop, then sales will be lost.

Downtowns in Smaller Rural Regional Commercial Centers

These small cities are among the most interesting for seeing how the effects of the new retailing are playing out. Rural cities, they usually have populations in the 12,000 to 30,000 range, but have addressable trade area populations of roughly 70,000 to 120,000. Their trade areas can extend to between 30 and 120 minute drive sheds. Their combined financial, government, health care, cultural, entertainment and retail assets give them sufficient magnetism to penetrate such large geographic areas. Sometimes they also benefit from strong tourist traffic. To penetrate these geographically large trade areas, they attract the kinds of retail entities that cannot be easily incorporated into a downtown – malls, big box stores and power centers. The size, magnetism and proximity of such strong retail entities in the community usually places their downtown’s GAFO merchants under substantial competitive pressure. However, substantial opportunities for successful downtown retail niche development can remain. To realize those opportunities, the downtowns in these small rural regional commercial centers will need to strongly develop their central social district functions, especially by developing a significant amount of nearby housing and creating strong entertainment niches, especially ones containing vibrant, well-activated public spaces.

I have researched two of these rural regional commercial centers, Rutland, VT, and Scottsbluff, NE. Their retail development has followed fairly similar courses over recent decades. More attention will be paid to Rutland, because I know it better, having done two major projects in the 1990s for the Downtown Rutland Partnership. I have followed events since then and recently visited Rutland.

Over the years, I have concluded that these small rural regional centers do not get the attention and respect they deserve as economic entities. As can be seen in the above table, although the populations and household incomes of Rutland and Scottsbluff are dwarfed by those of three eastern suburbs known for their large numbers of trophy retail chains, the annual retail sales of the small rural cities compares quite favorably with those of the more prestigious eastern suburbs. They certainly are not retail weaklings.

These two rural cities have similar income and education levels (see the table below). Their populations are similar, too, though Scottsbluff has an adjacent twin city, Gering, and they have a combined population that is 46% larger than Rutland’s. Their trade area populations and household incomes are also basically similar. However, they differ quite a bit on tourism. Except for “mud season” in early spring, Rutland has a variety of tourist streams year round, e.g., three major ski resorts are within a 30-minute drive, and loads of “leaf peepers” pass through in the Fall. About 2 million tourists come through the city annually. Scottsbluff has a far more modest tourist flow.

Both have relatively old and small (under 400,000 SF) enclosed retail malls that today have significant vacancies and lost most of their anchor department stores. Both malls also have had ownership problems and changes. In smaller cities during the 1970s to early 1990s, Sears, JCPenney and Kmart often were the retail mall anchors, as they were for the Monument Mall in Scottsbluff and Diamond Run Mall in Rutland. Sears, at one time, was the largest retailer in the USA. Monument lost Walmart back in 2000 and more recently lost Sears and Kmart; Diamond Run has lost Sears and JCPenney. These older department store chains were in decline before the Great Recession and were further weakened by it. Many retail experts are expecting Sears – it also owns Kmart – to disappear any day now.

While Monument Mall has the stronger remaining anchor, a Hersberger’s department store (a subsidiary of Bon Ton, itself a financially troubled department store chain), Diamond Run has the better known specialty retail chains, e.g., Old Navy, Victoria’s Secret and Eastern Mountain Sports.

Overall, Rutland has more retail chains that are also to be found in larger cities and metropolitan areas, while Scottsbluff has more chains that feel comfortable in smaller cities, e.g., Maurice’s, Murdoch’s, Rue21, Buckle, Hibbett Sports, Dunham’s Sports etc.

Both cities have loads of value-oriented big box retailers. They both have a Walmart — though Rutland’s is not a super store –- and a Home Depot. Scottsbluff also has a Target and a Menard’s, while Rutland has a Dick’s Sporting Goods, Michael’s and Bed, Bath & Beyond. Rutland has two 60,000 SF+ supermarkets – Price Chopper and Hannaford – as well as an Aldi. Rutland also has an off-price TJ Maxx that has been going strong for over 20 years.

In Rutland, the years between 1998 and 2007 saw the opening of many of its strongest retailers, e.g., Home Depot, Dick’s Sporting Goods, Michael’s, etc. They greatly strengthened the retail power of the Routes 4/7 corridor that is well outside the downtown’s retail core. When the recession hit in 2008, many downtown independent merchants were hurt and closed. As the recession ebbed, the downtown’s Rutland Plaza Shopping Center saw its movie theater change operating companies, and it attracted Dollar General, Sleepy’s and Payless as replacements for struggling tenants. (This is what good ownership does.) The attraction of national chains to other parts of the city basically stopped until 2013 when the Aldi opened. Since then a few chains have come in, such as Ashley Furniture. A BJ’s entered in negotiations for a site in 2016, but the deal fell through – because of permitting issues, not because BJ’s doubted the strength of the Rutland retail market. The interest of national retail chains has definitely ebbed. Those interested tend to offer low prices and/or value pricing.

Scottsbluff, its county and its state were among those least impacted nationally by the Great Recession. Nonetheless, Monument Mall continued to weaken and the recruitment of major retail chains ebbed. One sign of its current plight: it recently recruited a business from Scottsbluff’s downtown.

Scottsbluff’s downtown is basically about a half-mile portion of the Broadway corridor. With state money, the city has made a number of physical improvements to the area. Its strengths are its historical features, including the Midwest Theater, nearby office buildings, and a number of independent retail operators who have been around for some time and are effective destination stores. Eateries are another of its strengths as is its seasonal Farmers Market. It does not have any major retail chains. Its sidewalks usually appear to have little to no pedestrian traffic. It has not recently attracted any significant amount of residential development. It also lacks a well-activated and frequently used public space.

“The Pit” parking lot in downtown Rutland, sometimes used as an event venue. It is said to have very good acoustics.

Downtown Rutland is larger and not linear. It, too, has a major restored theater, the Paramount Theater, that is financially successful and draws 50,000+ patrons annually. Many other elements of a downtown entertainment niche are also present: numerous eateries and bars with live music; a children’s museum; art galleries and a movie theater. The Farmer Market is the biggest in VT and runs year round. It attracts many hundreds of shoppers on Saturdays. Additionally, downtown Rutland has a major transportation center and an Amtrak station. It also has seven banks and four financial services companies, City Hall and state offices and courts. A community college is also located in this downtown and Castleton University has established a major presence in the district. As in downtown Scottsbluff, its sidewalks usually appear to have little to no pedestrian traffic and it, too, has not attracted any significant amount of residential development, though Castleton University has turned two floors of a major building into student housing. It also lacks a well-activated and frequently used public space where people can simply sit and enjoy being outdoors as well as gather for events. For example, the Downtown Rutland Partnership currently uses, according to its website, the Rutland Theater, Depot Park, “The Pit” parking lot and the top level of a downtown garage to hold its events.

Rutland differs from Scottsbluff in a very important way – back in the mid 1990s, the downtown’s Rutland Plaza shopping center was intentionally revitalized by bringing in Walmart, Price Chopper, TJ Maxx and a multi-screen cinema. The Downtown Rutland Partnership, under the leadership of Dick Courcelle, strongly backed this approach. Its strategic reasoning was that it was better for these two superstores (Price Chopper and Walmart) to be located downtown, where local merchants could have a chance of attracting their shoppers, than to have the superstores situated farther away where local merchants would have no such opportunity. It was also thought that the Plaza, thus strengthened, would help other downtown merchants compete with the then new Diamond Run Mall.

In 1997 – 1998, DANTH, Inc. conducted an intensive study of how the Plaza’s superstores impacted the downtown merchants located outside of that shopping center. I published an article about our findings in Urban Land (see https://www.ndavidmilder.com/wp-content/uploads/2012/05/superstore.pdf ) . Our research accessed a downtown shoppers intercept survey that had over 1,300 respondents, a trade area telephone survey that had 465 completed interviews, and a survey of downtown merchants supplemented by numerous in-depth, face-to-face interviews with local merchants.

Our major findings were:

Most downtown merchants located outside of the Plaza felt that their sales had increased since the Plaza had been revamped and that many more shoppers were to be seen walking along downtown streets. Also, about 90% felt they offered unique products and services that did not compete with those offered by the Plaza’s new stores. However, among those feeling most threatened by the new Plaza shops were the operators of the apparel shops. Worrisome was the finding that over half of the downtown merchants felt that they were not getting as many of the Plaza’s new shoppers into their stores as they wanted
The intercept survey showed that there was considerable cross- shopping among the Plaza’s stores – e.g., over 62% of Walmart and Price Chopper shoppers shopped in other Plaza stores on the same shopping trips.
However, only about 21% of the Plaza’s shoppers also shopped in downtown stores located outside of the Plaza.

The Walmart is at least 430 feet away from other shops in Rutland’s downtown retail core

Our analysis indicated that the primary reason for the lower cross shopping rate with shops located in the downtown’s old retail core was that the Plaza’s in front parking lot constituted a huge pedestrian moat. “The distances between the shops in Rutland Plaza and those just across the street vary between 430 and 848 feet; Plaza shoppers therefore must be strongly motivated to walk such distances. (See photo above). Walking is difficult because it is not easy to quickly traverse the intervening Plaza parking lot—and it is made even more difficult by Rutland’s long winters.”
The single most important factor that influenced Plaza shoppers’ decisions about visiting other downtown shops outside the Plaza was whether they planned on eating downtown while on their shopping trip. This factor was at least twice as strong as their knowledge of downtown stores or if they liked the merchandise, customer service or uniqueness of those stores (see table below). Ever since, this finding has strongly shaped my approach to downtown retail revitalization, because it indicated how important restaurants and opportunities for social interaction are to retail success. This is a view increasingly held by major developers and retail chains. For instance, Apple’s Angela Ahrendts has recently said that Apple’s stores should become more like town squares (https://in/d88XcR9 ) .

The trade area telephone survey found that the strongest factor for explaining how often respondents visited downtown shops located outside of the Rutland Plaza was how often they visited the Plaza. This means that without the Plaza or with a diminished Rutland Plaza, the shops in the traditional downtown core would have many fewer shoppers, especially those with longer driving times.
The telephone survey also showed, quite surprisingly, that even after the Rutland Plaza brought in TJ Maxx, Fashion Bug and Poore Simon’s and Diamond Run Mall brought in department stores and specialty shops, trade area residents were more dissatisfied with the trade area’s apparel shops than any other types of retailers. Our analysis also showed that those with more comfortable incomes were prone to be most dissatisfied.Looking at more recent times, those findings suggest that the stressors causing small downtown merchants to close during and after the Great Recession probably were not either the retail chains located in the Rutland Plaza or the new big boxes that opened on the Routes 4/7 corridor. Most of the latter also sell merchandise that does not strongly compete with the offerings of downtown merchants. The more likely causes of those closings were the significantly decreased demand generated by the emerging mass of deliberate consumers and the already weak competitive capabilities of these failing merchants that resulted from a weak financial condition, an inability to adapt to new conditions and/or a poor set of merchant skills.
I would argue that today, even with the growth of e-commerce, in both Rutland and Scottsbluff, there are substantial opportunities for savvy independent downtown retailers to find the parts of the retail bed the 800 pound value-oriented/low price retail gorillas are not occupying and to consequently have considerable success. Additional market opportunities are being provided by the weakness of their malls, department stores and traditional specialty retail chains. Also, independent small merchants typically can survive on a lot fewer annual sales dollars than is needed by a major retail chain store. But, and this is an important but, the independent merchants must be competent to benefit from such opportunities.

The apparel shops I saw in downtown Rutland on my recent visit indicate that to some extent these opportunities now are being realized. One operator has opened two women’s apparel shops on Merchants Row since about 2011. A small chain selling outdoor clothing and equipment opened – even in face of competition from the local Dick’s Sporting Goods and Eastern Mountain Sports. It has two other locations in VT and NH. They show that smaller retailers are seeing significant opportunities. The closing of Sears and JCPenny lso has opened opportunities in the men’s clothing market. However, given the current track record of small men’s apparel shops, an existing men’s store that has survived the Great Recession is probably better positioned to capture some of the surrendered market share than a new entrant.

These apparel merchants are also using the Internet, though some have much more sophisticated uses than others. Of the eight apparel shops located outside of Rutland Plaza, seven have websites and seven have Facebook pages. All are somehow present on the Internet. Notably, only one has an e-store where purchases can be made online. Two use their websites to really push their customer services by offering personal shopper assistance and home visits.

Also worthy of note is that two of downtown Rutland’s eight apparel merchants are parts of small regional chains that have three to nine locations. These shops are not under “newbie” operators and have a greater likelihood of success. Downtown Rutland’s core lacks the available 3,500+ SF retail spaces that might enable it to recruit the types of retail chains that feel at home in smaller cities. Scottsbluff’ has attracted many of them them, but not to its downtown.

One major reason that small merchants in both of these downtowns have not had still greater success is that by themselves they lack sufficient magnetism for drawing a lot more people. If these two downtowns could attract more people, they would have more potential shoppers, have more successful retailers and attract better retailers.

Over the past two decades, downtowns of all sizes across the nation have come up with two successful tactics to attract more people downtown. More downtown housing has proved to be very helpful because it creates a captive market of people who want a wide range of activities to engage in – shopping, dining, being entertained, recreating, etc. — within easy walking distance of their residences and their impacts are amplified by their friends and relatives who visit them. In my opinion, both downtown Scottsbluff and downtown Rutland would benefit greatly from a significant amount of housing being located in or near (e.g., within a 10-minute walk) their districts. In my discussions in various rural cities over the past decade, I have heard the following reasons cited to explain why downtown housing was impractical in their communities:
- The unavailability of appropriate sites
- The general low level of housing demand
- The lack of specific demand for condo apartments and townhouses because they are somewhat alien to residents of rural areas.
It can be argued that if local leaders are aware of the potential benefits of such housing and prepared to act, the above concerns most probably can be successfully addressed with arguments along these lines:
- Sites on the fringes of the district, within a 5-minute walk, are probably easier to find and cheaper to build than those within the district, but they still make it easy for residents to walk downtown
- The growing senior popualtion is increasingly active and many are looking to downsize to easier to maintain smaller residences. Scottsbluff already has been attracting many retiring ranchers and farmers. Many of the seniors would enjoy the close proximity of restaurants, shops, cultural and entertainment venues and professional offices.
- The young people who are leaving these communities are often going to other cities that have a lively downtown with lots of nearby apartments and townhouses.
Many downtowns have also found that strong, broadly defined entertainment niches can bring many new visitors downtown on a sustained, long-term basis. Both downtown Scottsbluff and especially downtown Rutland have elements of such a niche. However, my sense is that the impact of their entertainment niches on downtown retailers has not been as strong as it could be. In Rutland, that certainly has not been for the lack of trying or even for a lack of important successes. The Downtown Rutland Partnership along with the Rutland Development Authority and other civic groups worked long and hard to successfully redevelop the Paramount Theater and to encourage the attraction and development of the art galleries and children’s museum. The owners of the Rutland Plaza succeeded in getting a new operator for its movie theater at a time when quality operators had become much harder to find. The Famers Market has developed into a strong regional draw, though it only operates on one weekend day.

There are definitely things to do in downtown Rutland after dark – and that may be part of the problem. Most of the customer traffic to two of its strongest entertainment niche elements, the Paramount Theater and Flagship Cinemas probably comes when most small independent retailers are closed, i.e., in the evenings and on Sunday afternoons. The children’s museum, art galleries and Farmers Market are certainly assets, but they target rather specialized interests or have limited operating hours. What seems to be missing is a well activated public space, something akin to Mitchell Park in Greenport, NY, or The Division Street Plaza in Somerville, NJ, or Grand Central Plaza Park in Valparaiso, IN, that can attract people during the daytime, providing both a pleasant respite and entertainment.

Such public spaces not only can provide venues for a wide variety of events and activities, but they can also provide visitors with opportunities to find a safe and comfortable retreat or to simply be entertained by watching what other users of the space are doing. Importantly, such spaces also can provide opportunities for visitors to engage in a broad range of activities such as playing chess, riding a carrousel, ice skating, running through a splash pad, reading a book or magazine, playing miniature golf, etc.

Over the past two decades, I have engaged in a number if informal discussions with downtown leaders in cities with populations under 35,000 about creating strong downtown public spaces. In too many instances I have heard that such projects were not feasible in their downtowns because:
- They would be too expensive to build and operate
- Their winters are too long and too cold
- A lack of appropriate sites
- Such spaces would be dominated by drug users and dealers, the homeless and/or unruly and intimidating teenagers.
Public spaces definitely require funding, but DANTH’s research has shown that attractive and successful downtown public spaces can be created and maintained at significantly lower costs than PACs, theaters, arenas, ballparks and museums. Moreover, their operating cost per visitor are also far lower. For any downtown that wants to strengthen their entertainment niche, creating an attractive public space will most likely produce the biggest bang for their bucks. See: https://www.ndavidmilder.com/2014/11/bryant-park-part-3-a-comparison-to-other-entertainment-venues-on-annual-expenditures-and-annual-expenditures-per-visitor. The downtown leaders who create these spaces often use numerous funding sources, e.g., city, state, federal and foundation grants and private donations, as well as several financial tools, e.g., tax increment financing, to pay for their construction. All are well known, not protected secrets.

Many downtowns are located in cold climes and a lot of them have found ways to make their public spaces active during the winter months. A favorite tactic is to turn them into ice skating rinks. For example, Grand Central Plaza Park in downtown Valparaiso, IN, just added a new pavilion that covers an open air ice rink in the winter and provides a shaded venue for events during hot summers. The park also has a splash pad for children on hot days and an amphitheater for outdoor concerts and other events.

Central Park Plaza’s Splash Pad in Valparaiso, IN. Photo by SEH

Central Park Plaza’s new pavilion during the summer

Central Park Plaza’s new pavilion during the colder months – an ice skating rink

I have been amazed by how appropriate sites for such public spaces have been found. Division Street Plaza was a decaying side street. Mitchell Park was a burned out hotel and marina on badly contaminated land. The 4,000 SF pocket park in Washington Borough, NJ, was a decayed old building. It’s surprising what a little ingenuity can come up with and how that ingenuity appears when downtown leaders really want a vibrant public space.

Effective and humane programs for dealing with the homeless in public areas are to found in many places across the nation. That wheel does not need reinvention, though some tailoring to local conditions may be required. Other bad behaviors can be kept out by bringing in a lot of well-behaved users and nipping some behavioral problems when they are still in the bud.

As I researched for this article, I was most happily surprised to find that serious steps are now being taken in both downtown Scottsbluff and downtown Rutland to meet their needs for new vibrant public spaces. In Scottsbluff, buildings are now being cleared to provide the land needed for the Downtown Plaza. Eventually it will have a stage, space for vendors, a venue for their Farmers Market, an artificial ice rink in the winter (like Bryant Park in NYC) and space for other events, such as outdoor movies. Very importantly, it also will provide public restrooms. (See the graphic below.) It will be completed in three phases.

Basic design of downtown Scottsbluff’s new Downtown Plaza

Given its size, visibility, uses and proximity to downtown retailers, one might anticipate that the Downtown Plaza will have positive benefits for nearby merchants and restaurateurs. One concern is that while care is being taken to have adequate shading, I have not found in my brief search any mention of how seating will be provided. Seating can be a critical issue. Another concern is how long it will take for the Plaza project to be completed or to reach a critical mass.

In Rutland, for about a decade now, local leaders have been trying to redo an existing public space, the Center Street Alley, that had been used in the early 1980s as a venue for downtown events. It later fell into disrepair and encountered user avoidance. Public use was halted. With federal funding, plans for this space reportedly again on the table and call for it to be reopened to the public after the installation of “new brickwork, lighting, benches and trees.”

The Center Street Alley space, to my ken, is rather strange. Its main part has little visibility from any of the surrounding streets, as can be seen from the map below. It occupies the center of a city block and seems to have been created from the backyards of the surrounding buildings that face Strongs Avenue, Washington Street, Center Street and Wales Street.

Look for the Center Street Alley in the center of this map — Map from Downtown Rutland Partnership, cropped by NDM

One can easily visualize how such a space might provide both a nice refuge for visitors to sit quietly and a venue for public events. But, its ability to make the downtown appear more active and exciting seems hampered by its lack of visibility to passing pedestrians and autos. I plan on following what happens to this space. My concern is that its “hiddenness” may impede daily use levels and limit its favorable impacts on nearby merchants. On the other hand, its hiddenness may give the space a kind of quirky, being in the know appeal.

Some Takeaways

The weakening of retail malls and traditional specialty retail chains in our smaller rural regional commercial centers is giving savvy downtown merchants serious market opportunities. The apparel shops in downtown Rutland show that savvy, small downtown merchants can indeed take advantage of these market opportunities. Their presence on the Internet is helping them do that, at least with shoppers within their trade area. They are not using the Internet to generate online sales from national markets.
The growth of big box and value oriented retailers probably is not what mainly forced many small downtown retailers out of business during and after the Great Recession. More important was the reduced demand created by the emergence of deliberate consumers and the merchants’ inability to respond appropriately to the new and highly stressful situation.
Downtown Rutland shows that attracting some of the big retail chains, e.g., Walmart and TJ Maxx, can be good for downtown merchants because of the strong customer traffic they bring in.
However, good urban design has to be used to assure that these big retailers will be physically integrated into the downtown. That enables small downtown merchants to share in the big retailers’ customer traffic.
Downtown restaurants, public spaces and other central social district entities can help bring people downtown who then become potential shoppers for local merchants.
There is a tendency in these rural commercial centers for multi-unit housing not to be developed in or near their downtowns, probably due to cultural preferences and poor market research. The downtowns would greatly benefit from such development, especially their restaurateurs and retailers.
A challenge for the merchants in these downtowns is to get the shoppers who are going to other shopping centers and malls in the city to visit their district. Developing the downtown’s central social district functions, which includes housing, restaurants, bars, entertainment and cultural venues is a sound strategy for attracting those shoppers. For small downtown retailers, restaurants and public spaces are especially helpful because they are active when the merchants’ shops are open. Of course, if downtown merchants would change their hours to coincide more with those of downtown entertainment assets, they probably would get significantly more sales. We can dream, can’t we!
Having a public space does not mean it necessarily will have the desired level of positive benefits for local merchants. The space must work, it must be vibrant and attract people and events. Simple things like adequate seating and shade can be critical to their success. The space also probably needs to be fairly visible to pedestrians and cars passing by.

Up Next : Affluent suburbs with lots of trophy retailers

Retail Leakage Analyses Should Be Treated With Great Caution by Analysts and End Users: 2 Some Serious Data Issues

Posted on September 13, 2016 by DANTH

By N. David Milder

Introduction

This is the second of a two-part article on the need to be very cautious when doing or using a leakage analysis. Part 1 focused on the analytical issues associated with this economic development research tool. It can be found at

https://www.ndavidmilder.com/2016/09/retail-leakageleakage-analyses-should-be-treated-with-great-caution-by-analysts-and-end-users-analytical-issues.

This article will focus on the problematical data too often used in leakage analyses.

GIGO is an acronym well-worth knowing. It stands for Garbage In, Garbage Out. Too many leakage studies are very problematic because the data they use are very questionable. This is often not the result of data suppliers being slovenly in their data gathering or analysis – although sometimes, it is – but because getting information about small and medium sized firms’ sales, workforces and finances can be very difficult. To counter this problem, the leakage market data firms sometimes will try to use business census and related data to estimate the sales of the firms in the major NAICS codes that have been identified in a study area. Their resulting estimates are not based on primary research and have a number of degrees of separation from the original firm level data that is usually unknown to the data purchasers. Different research firms will have different methodologies for making these estimates. Which, if any of them, produce accurate estimates about NAICS retail categories’ sales is a key question. Unfortunately, I have not seen any studies that validate the accuracy of these estimates. This suggests caution and prudence in their use.

A Good Starting Point for the Discussion

esri-vs-sales-tax-retail-sales-estimates-xlsx

The table above is a good starting point for this discussion. It shows the results of the leakage analyses generated by Nielsen and Esri for a city in the West that has a population of about 30,000. These two respected private firms provide a lot of the demographic and business data used in the economic development field and the table is representative of the leakage analysis data they produce. They certainly are not the only ones that generate the data used in a leakage analysis, but because of their affordable prices and easy online access, they are used by many EDOs (mostly by their consultants) looking for such information.

The table’s first column shows the NAICS retail categories being analyzed. Leakage analyses subtract retail sales in the study area from consumer expenditures. If the expenditures exceed sales, there is a leakage. Conversely, if sales are larger than consumer expenditures, there is a surplus. Columns three-five provide the data on consumer expenditures, store sales and leakages/surpluses for each category. The data in columns three and four are estimates – these firms have not directly surveyed the residents of City XYZ about their expenditures or the retail stores about their sales. That’s one reason why their leakage analysis reports can cost $50 and not $25,000. The data in column five are simply the results of subtracting the data in column four from those in column three.

Given that the numbers in column five are supposed to facilitate an understanding of economic growth potentials and possibly an assessment of the market viability of substantial private investments, looking at the table probably leaves the reader disturbingly confused. While there is agreement in direction (i.e., leakage or surplus) and quantitative closeness in some categories, e.g., gasoline stations, furniture and home furnishings, on many others the size of the leakage/surplus differs substantially, e.g., food and beverage stores, or conflicts on direction, e.g., health and personal care stores and eating & drinking places.

Looking at the estimated data in columns three and four, there is an even more divergent pattern. The estimates of both consumer spending and stores sales are in most cases substantially different. These two market data-producing firms are obviously using very different methodologies and/or formulas to generate these estimates.

How, then, do we know which, if any, of these leakage estimates can be trusted?

An Example of the Explanations They Provide

If you call these firms or look online for explanations of how they generate their estimates, they may use quite a few words, but seem nonetheless not very transparent. Here, for example, is how ESRI in “2014 Methodology Statement: Esri Data—Retail MarketPlace,” a 2014 white paper,” described how they estimated retail sales:

“Estimates of retail sales begin with the benchmark, the 2002 and 2007 CRT (Census of Retail Trade) from the US Census Bureau. Trends from the economic censuses are used to update the base along with Esri’s extensive portfolio of demographic and business databases. These include commercial and government sources such as the Dun & Bradstreet business database and economic statistics from the Bureau of Labor Statistics. Supply estimates also incorporate data from the Census Bureau’s Non-employer Statistics (NES) division. Smaller establishments without payrolls, such as self-employed individuals and unincorporated businesses, account for a small portion of overall sales. However, these businesses represent more than half of all retailers in the United States. Their inclusion completes the report of industry sales.

Esri’s model captures economic change by first differentiating employer and non-employer sales growth. Multivariate statistical techniques are used to model data that is subject to disclosure issues in CRT and NES. Sales estimates have been recalibrated against the Monthly Retail Trade (MRT) survey and independent sources to address the disparities that can exist between independent input data sources. This methodological improvement yields a more precise estimate of the retail sales attributable only to domestic households.

Esri licenses Dun & Bradstreet’s business database, which also provides sales for the retail market. Although Esri utilizes this database in the derivation of small-area estimates, the methods differ. Esri estimates retail sales only to households for implementation within the Retail MarketPlace data. Additionally, Esri relies heavily on data from both the CRT and MRT to improve estimation. Furthermore, the Dun & Bradstreet business data file is reviewed and cleaned to improve data content. All estimates of market supply are in nominal terms and are derived from receipts (net of sales taxes, refunds, and returns) of businesses that are primarily engaged in the retailing of merchandise. Excise taxes paid by the retailer or the remuneration of services are also included, for example, installation and delivery charges that are incidental to the transaction.”

This explanation shows that Esri s methodology is a rather complicated, multi-step process, which involves quite a few data sources and data manipulations. Part of those complications is the result if its recognition that the estimates based on one data source or another are in need of improvement.

Dun & Bradstreet (D&B) and MRT data are needed because:

The business census data are aggregated to such geographic units as states and counties that are not congruent with the non-legally defined boundaries of many study areas. Addressed based D&B data can be aggregated to the needed geographic boundaries.
The business census is done only every seven years and the actual data are only released two to three years after it is taken. Depending when they are used by outside analysts, the business census data can be three to six years old. The census data cannot be depended on to detail what businesses are there and what they are like. The D&B data are supposedly more recent and able to establish who is there now. ESRI’s methodology recognizes the importance of knowing how many firms by size there currently are in each retail NAICS code in a leakage analysis study area. The NES data are used to address the presence of small firms.

On a key question, whether and how Esri uses D&B’s data on firm sales, Esri’s white paper is unclear.

My take aways from Esri’s explanation of how estimates of retail sales are made are that it

Reveals the sources of some of the data they use, e.g., the Census Bureau, BLS, Dun & Bradstreet. However, they do not detail the data obtained for each retail firm (e.g., name, NAICS code, sales, number of employees) or, very importantly, how these data may have been statistically manipulated to produce their estimates. This is understandable to the degree that their methodology provides a competitive advantage over their rivals and therefore needs to be kept confidential. Nevertheless, it makes assessing their estimates more difficult.
Additionally, and perhaps even more importantly, Esri provides no indication that they have validated their estimates, i.e., shown that their estimates are accurately measuring what they are supposed to be measuring, or that they even made an attempt to do so. How, then, can we know that their methodology is sound? How can we have confidence in them?
Is a complicated methodology with many steps. I was taught that every time basic data are manipulated or added to there is a potential for a new error factor to be brought in. Esri has added steps to its methodology to overcome some known errors. Whether they are successful or simply add new errors is unknown.

I have not found any better explanation from Nielsen or its corporate predecessor Claritas about how they estimate retail sales.

A Closer Look at Basic Supply Side Information: Retailers –Their Number, NAICS Codes, Sizes and Sales

Accurate basic firm level data are absolutely essential to an accurate and useful to a traditional leakage analysis. Having directed numerous surveys of business firms, especially retailers and those prone to renting office spaces, and conducting countless personal interviews with business owners and managers in the USA and France, I am well aware of the difficulties involved in getting reliable data from business firms. This is especially true for the sales and finances of small and medium-sized operators.

As the following quote from Mike Stumpf indicates, I’m not the only one that questions the verisimilitude of the firm-level data that is often the foundation of a leakage analysis. From a recent email, here is Mike’s description of how ESRI looked at one area’s business mix:

“ESRI looked at the area’s business mix, then talked about the very large number of establishments in the financial sector. ESRI’s database lists every ATM as a business establishment! A grocery store with a deli, pharmacy, and liquor store can be listed as four different businesses, each with its own estimated sales, but then they do not pick up the restaurant in the Mexican grocery. Their sales estimates for one Mexican bakery were under $100,000, but they actually do more than that in a single month.”

Both Nielsen, ESRI and other leakage analysts obtain basic data about the stores in a study area from other market research firms, such as InfoUSA, Dun & Bradstreet or, its subsidiary, Hoovers, etc. that focus on firm-level data gathering. Nielsen and ESRI combine that info with data from the economic census and other sources to produce their estimates. In a sense they are heaping estimates upon estimates, with each potentially having unknown error factors that may combine through addition or multiplication.

Over the past three decades my company, for our client’s downtowns, has purchased establishment level data from some of the same business market researchers that have supplied firm level data to ESRI and Nielsen. On occasion, we obtained such data from local economic development agencies. Our experience with those data made a deep impression because:

There were usually error factors of 20% to 40% in the listings of firms. The errors, as might be expected, were most frequent among the really small firms that have a high probability of failure and turnover, but some of a downtown’s larger retailers were too often also omitted or listed after they had closed. We have seen annual retail churn rates in our clients’ downtowns (they include newcomers as well as closures) that can range between 5% and 30%. Unless these gatherers of firm-level data research businesses annually, which is very expensive, there is a high probability that their collected facts will be out of date. The year-to-year errors can really add up.
The Retail NAICS codes often may be wrong. Our discussion with one of the businesses that gathers firm-level data revealed that the downtown firms themselves were surveyed and provided their NAICS code(s). They were aware that errors were frequent. They attributed this to a difficulty in getting knowledgeable executives to respond to their survey. My review of the NAICS codes listed for retailers in the downtowns we bought data for frequently found numerous questionable codes.
I have supplied the NAICS code for my firm in the business census and to insurance companies and found out what many of the not large downtown business owners have told me over the years: selecting the right NAICS code isn’t easy, its takes too much time, and consequently, they just put down whatever is easiest to get the task done. Some reported giving the job of responding to the business census and enquires from firms like InfoUSA to their secretary or assistant or salesperson. I suspect that there are even substantial NAICS code errors in the US Business Census returns — especially from respondents who are the types of independent retailers found in our small and medium-sized downtowns and urban ethnic neighborhood commercial centers. DANTH, Inc. has conducted many surveys of businesses over the years, including the largest corporations headquartered in Manhattan, those in the healthcare industry, manufacturers in Nassau County, NY, etc. We quickly found there was a tendency for high-level executives to avoid responding to our survey. They felt it was a waste of their time.
Getting accurate firm-level retail sales data is really, really difficult. In addition to the surveys mentioned above, DANTH has also done numerous surveys of downtown merchants. Unsurprisingly, we found that there is strong resistance among most independent downtown merchants to providing such information. Interestingly, they sometimes reported that, off hand, they don’t know that information. The managers of the national chain stores also are loath to reveal their sales statistics. Many downtown managers – probably most – can attest to the difficulty of obtaining such information.
One of the business market researchers reported to me a few years ago that they have similar challenges getting information about a firm’s sales, workforce and finances. For the national chains, they use the chain’s average store’s sales. For the independent merchants they ask for the number of employees – which they said small retailers are more willing to provide – and multiply that by the average sales per employee for that NAICS code in the state. D&B is in the credit rating business, so small and medium-sized retailers who are concerned about their credit rating have an incentive to respond to D&B inquiries.

Getting basic information about small and medium sized business is a tough job, fraught with potential errors. Given that this type of information is such a basic building block in the often-complicated process of estimating the retail sales of a study area, it seems wise to treat such estimates with caution and prudence.

DANTH, Inc. has used leakage analyses generated by Claritas Esri and UWEX. In each instance, I created small tests of the data. Sometimes running a leakage analysis on a small of part of the study area enabled a comparison of the number of firms with my visual counts. If a NAICS category was identified as being very strong, I tried to verify that by visual inspection and interviews with local business operators. In a project in Sherwood, WI, a fast growing community, I thought that both the demographic data and the leakage analysis of one provider were badly out of date. Instead, I used the UWEX Gap Calculator and data from the Census Bureau’s American Community Survey. On another project, one of my little tests was to see if the leakage analysis had captured the sales of a food operation inside of a convention center. Finally, there is the “making sense test.” Sometimes I’ve looked at one of these leakage analysis reports and felt it just does not make sense. It just may be that the numbers do not jive in my mind with what I saw touring the study area and what I heard from local business people and economic development officials. Reports that fail the making sense test cause me to take a much closer look at the situation.

Sales Tax Data. In a number of states, retail sales tax information sorted by NAICS codes are gathered and published for the state, counties and sometimes the cities. These data are potential analytical gold for those researchers who find those geographic units congruent with their study area. Even when they are not, the validity of such data may provide a strong foundation for making needed extrapolations for the non-legally defined study areas.

Most of my project experience has been in states that do not provide such information. On the two occasions when I did projects in such states, I encountered some problems that impeded my use of the sales tax data. In one state, the sales tax is applied to only a portion of the merchandise in various NAICS categories and we could not determine what those percentages were. In the other state, the data for the counties were only provided at the two-digit NAICS code level, e.g., that of the entire Retail Trade category.

However, I have been told by some economic development consultants in California whom I respect that the state’s sales tax by NAICS code data enables them to produce more reliable leakage analyses.

Avoiding the Need for Retail Sales Estimates

In the 1990s and early 2000s, instead of the usual leakage analysis, DANTH, Inc. used an approach based on the consumers’ satisfaction with the retail services in their market area. We thereby solved the unreliable retail sales estimates issue by avoiding the subject. Our analysis focused solely on the consumer. Back then, response rates to our telephone surveys were far more acceptable than today’s 30% or so and we asked respondents if they were satisfied with the stores within a 15 minute drive in each of the higher level retail SIC or NAICS codes. Those that were dissatisfied we deemed as probable out-shoppers and open to being attracted by new retailers within the trade area. We also knew from the survey about these dissatisfied shoppers’ incomes, education levels, age cohorts, etc.

Using consumer expenditures potentials generated by ScanUS, Esri or Claritas we also provided estimates of the consumer expenditures for some of the products associated with each retail SIC/NAICS code. The expenditures of the “underserved” shoppers were, in a sense, up for grabs and prone to being spent out of the trade area. Back then we were not able to match completely BLS product categories to NAICS codes as can now be done. Our retail growth strategies were based on capturing these up for grabs shoppers and a sample of their retail expenditures.

This approach is sort of like a leakage analysis, though not the same. However, it enables an analyst to answer the same important retail growth questions, with far fewer questions about the validity and reliability of the data used.

DANTH has not used this approach recently because the cost of a really good telephone survey has become unaffordable and their findings less reliable, while the use of lower cost non-panel online surveys have serious sample issues.

Of course, others have used local surveys to ask respondents about whether they mostly buy various products in town, out-of-town or online. That, too, tells you about the leakage of shoppers and avoids the need for data about retail sales. Here, again, being able to do an affordable survey with a representative sample is a critical question.

My guess is that within the next 10 years online survey techniques will solve the sampling issue and affordable surveys will be possible. Then researchers will be able to answer the questions that leakage analyses are intended to address without needing to know about local retail sales or complicated methodologies for estimating them.

The Demand Side – Consumer Expenditures by NAICS Category

BLS Based Approaches. As I have written elsewhere, the best way of obtaining reliable, acceptably accurate data on how consumers spend their money is to survey them. However, such surveys require substantially more methodological skills and resources than most other kinds of surveys. For many consumer items, the relevant information must be obtained close to the points in time when the expenditures are made, lest memories of them quickly fade. For example, the Bureau of Labor Statistics (BLS) probably sets the gold standard for this type of research and it has half of its 14,000 survey respondents keep diaries of their expenditures and interviews the other half 5 times over 15 months. In contrast, I’ve seen many inept downtown and Main Street surveys that ask about shopper expenditures that are oblivious of the challenges involved, have no where near the rigor of the BLS surveys, have relatively few respondents and their results aren’t worth the paper they are printed on.

While the BLS expenditure data are solid and a good starting point, using them to inform estimates of consumer expenditures in a leakage analysis study area presents a number of barriers that must be overcome:

The BLS uses categories to order its data that are product oriented, about the things people buy not the kinds of stores consumers buy in. The demand side retail sales data are ordered by the NAICS codes that are about the characteristics of aggregations of retail stores. To be useful in a leakage analysis, the BLS data have to be “crosswalked” into the NAICS categories. Such data crosswalks are enabled by a list of the products that are typically sold in the different retail NAICS codes that was produced by the Census Bureau. Using the list can take a lot of effort. Computerizing the list makes things easier, but also takes resources. Both Nielsen and Esri do these data coding crosswalks. This data crosswalking is a possible opportunity for errors to enter the analysis, but I think the probability of that happening are relatively low.
The geographies used by the BLS are far, far larger than the size of any retail leakage study area. The 14,000 respondent BLS sample is still too small to provide enough respondents to be directly used even at the state level of analysis; the sample would average only about 280 respondents per state. Consequently, some methodology is needed to make estimates of consumer spending within retail leakage study areas that is based firmly on the BLS data. Both Nielsen and Esri have developed methodologies to make such estimates based on the BLS data. My research experience says these research tasks have significant opportunities for errors to enter into the analysis.
Different types of people have different spending levels and patterns and different retail leakage study areas will vary in the kinds of people that live in them, e, g., by income, education, race, lifestyle group. The BLS data based estimation process needs to be able to adjust expenditure estimates by taking these population differences into consideration. Both Nielsen and Esri use their demographic and lifestyle segmentation databases, Prism and Tapestry, to make these adjustments. My research experience again says these research tasks have significant opportunities for errors to enter into the analysis.

The data presented in the table earlier in this article about City XYZ shows big differences in Esri’s and Nielsen’s estimates of consumer expenditures. This suggests that while they both are trying to address the problems just enumerated above, their methodologies vary significantly. Again we are posed with the problem of whose estimates, if any, should we trust?

The BLS data covers household expenditures. Used in a leakage analysis they inform only about the expenditures of study area residents. They do not appear to inform about the expenditures of day and overnight tourists and non-residents who work in the area. Yet, accurate estimates of retail sales should include the sales dollars from those types of customers. For many downtowns, the non-resident customer base can be extremely important. There consequently seems to be an imbalance between the customers included in the analysis on the demand and supply sides. Bill Ryan has recently upgraded UWEX’s Gap Calculator to incorporate data on the expenditures of tourists and people working downtown. Others should follow suit.

ecommerce-retail-2013-and-projections-xls

Also, of increasing importance, the BLS data does not tell us whether consumer expenditures are being made in brick and mortar shops or online. The total of online retail sales now only accounts for about 6.5% of all retail sales nationally. However, as can be seen in the above table,

By 2017 it is anticipated, if trends continue, that e-commerce will account for 50%+ of the sales for music, videos, books, magazines, computer hardware and software, toys and games, electronics and appliances,
By 2017 e-commerce is projected to account for 25%+ of the national sales of furniture, sporting goods, office equipment and supplies, clothing, accessories and footwear.

The vast majority of online purchases will be going to retailers based geographically outside of the retail leakage study area, perhaps across the country or even on another continent, yet they are very close because they can be reached from a living room chair almost instantaneously via a smartphone, tablet or computer. The online purchases are, of course, leaked purchases. The important question then becomes do local merchants have a real chance to recapture these dollars? The strong trend now is for online sales to grow at a rapid pace. Younger Americans, especially the Millennials feel very much at ease with making online purchases and they will be growing in number. Older folks are getting more accustomed to buying online, but not like the younger age cohorts, and many of them will soon fade away. Consequently, a strong argument can be made that, for the foreseeable future, it will be much harder for local brick and mortar merchants to win back dollars spent on the internet than for dollars spent in other brick and mortar shops located beyond their trade area’s boundaries.

If this is the case, then knowing about how many consumer dollars in a study area are going online is, in effect, identifying “dead dollars” that now are well beyond the reach of local retailers who really have little hope of recapturing them – unless they, too, are able to become strong competitors on the internet. Unfortunately, this is the type of information that many downtown leaders need to know, but don’t want to hear.

None BLS Approaches. Leaders of EDOs in many small and medium sized communities may want a leakage analyses done for their downtown, but the don’t have a lot of money to pay for a consultant. Some consultants and economic development organizations have constructed leakage calculators that can be used by EDO leaders or their staffs either for free or for little cost. These builders of these calculators do not have the funds that take the BLS data and crosswalk then into NAICS codes, or to generate expenditure estimates at the study area level, or to adjust such estimates through the use of a lifestyle database. Instead, they take a simpler and less expensive approach:

They take the retail sales by NAICS code at the state level and adjust them for inflation
Then they divide those sales numbers by e the population of the state to get per capita sales per NAICS code at the state level.
Then they treat these per capita sales estimates as measures of per capita spending. They identify the population of the study area in question and then multiply the NAICS per capita sales estimates by that population number to estimate total consumer expenditures by NAICS codes for the study area.
They then identify the median household income in the trade area and adjust the consumer expenditure estimates accordingly.

In a lot of ways this is a simpler and easier way of estimating consumer expenditures in a study area than how Nielsen and Esrsi do it. I’ve used the UWEX Gap Calculator and can attest that its easy to use. It’s intended users are small and medium-sized downtowns, where local leaders can input their own data about the retailers in their trade areas.

The use of sales data at the state level to estimate consumer expenditures at a study area level may raise a few eyebrows. It did mine. Since the state retail sales data includes tourist sales, those dollars are also finding their way into estimates of resident retail expenditures and inflates them inversely to the actual flow of tourists through the study area. The theoretical explanation for it escapes my understanding. But, can Nielsen and Esri prove that their estimates are any better?

Given that there is no evidence that the gap calculators do any worse than the leakage reports the big private market data firms put out, who’s to say they are not worth considering. The price is right. Moreover, they are methodologically rather transparent: it’s easy to understand how all the estimates are being made.

Some Final Comments.

To properly do our research we need to live in the real world and in that real world we most relay on doing secondary or tertiary levels of analysis on primary data collected by someone else. Professionally, we should have been trained to understand that we must be very cautious about how we do our secondary analyses and transparent about our methodology when we present our findings to others. We need to be even more cautious about how we accept the secondary analyses done by others – especially when their methodology is not transparent and their findings have a significant number of apparent errors and conflict with the findings of other analysts.

That is why I argue that the estimates of retail sales and consumer expenditures generated by most leakage analyses should be treated with caution and used with prudence.

CENTRAL SOCIAL DISTRICTS

Posted on February 17, 2016 by DANTH

A fuller and updated version of my analysis of Central Social Districts can be found at https://theadrr.com/wp-content/uploads/2021/07/Strong-Central-Socia-LDistricts-__-the-Keys-to-Vibrant-Downtowns__-Part-1-FINAL.pdf

An Invitation

On March 4, 2016 Andrew Dane, of SEH, and I will be doing an APA sponsored webinar on “The Central Social District – the Key to Tomorrow’s Successful Downtowns.” We hope you will join us. APA members can register at: http://tinyurl.com/j6m8sek . Non-APA members perhaps have a friend or colleague who is a member and can be convinced to attend.

Andrew and I teamed up on downtown revitalization projects in Sherwood, WI and Gering, NE. Even in those relatively small communities, we found the Central Social District (CSD) to be a compellingly useful concept when assessing a downtown’s assets and liabilities as well as for developing solution paths.

My own interest in CSD functions dates back to the late 1970s, when I tried (alas unsuccessfully) to get a Celebrate Charlotte program going in that city’s CBD. Since then, fostering a strong entertainment niche has been key element in many of the downtown revitalization strategies I helped develop for such communities as Rutland, VT, White Plains, NY, Morristown, NJ and Peoria, AZ.

In recent years, the portion of my research that I have written about here on the Downtown Curmudgeon bog has been almost exclusively related to the entertainment and restaurant components of CSDs, e.g., arts venues’ attendance and funding, the advantages of informal entertainment venues, assessing the impacts of formal and informal entertainment venues, the need to protect our downtown cinemas, restaurants as the cornerstones of vibrant CSDs.

Can’t make the webinar? Email me at [email protected] and I’ll send you a copy of our presentation.

What Are Central Social Districts (CSDs)?

A CSD is that part of a downtown that has venues performing CSD functions. Since antiquity, successful communities have had vibrant central meeting places that bring residents together and facilitate their interactions, such as the Greek’s agoras and the Roman’s forums. Our downtowns long have had venues that performed these central meeting place functions, e.g., churches, parks and public spaces, museums, theaters, arenas, stadiums, housing, etc. However, local leaders often seemed to give higher priority to their CBD related venues – e.g., retail shops, financial institutions, public and private sector offices, hospitals, etc. Indeed, for decades the terms downtown and CBD often have been used interchangeably in common parlance.

Why Are CSD Functions Becoming Much More Important

There are three main reasons:

Since the Great Recession, for many downtowns, especially those with mainly middle income users, retail and office growth have become far more problematical, if not plainly impossible. For them, CBD functions are far less able to sustain a healthy and popular downtown. There is little evidence that this situation will turn around anytime soon.
There has been a major cultural shift and today a significantly larger segment of our population wants to live and play in downtown-type environments than was the case in past decades. In other words, the popularity of downtown CSD venues has grown very substantially, while those associated with the CBD are often floundering
With long working hours and the growth of e-communications, people are increasingly looking for entertaining places to spend scarce quality time with those they care for. More and more they are finding that their downtown’s CBD venues can provide such places.

More Downtowns Should Focus On Strengthening Their CSD

Today, for most small and medium-sized downtowns, CSD development offers the best prospects for economic growth by:

Growing their base of downtown visitors and sense of vibrancy
Maintaining or raising real estate values
Providing the amenities, ambience and customer traffic that makes the district a more attractive location for retail and office tenants.

CSD Development Is No Slam Dunk

One does not have to travel far to find examples of successful CSD development. However, a similar trip might also reveal a theater, PAC, museum, park, public space or other CSD venue that is either struggling financially or finding it hard to attract the numbers and types of users its plan called for.

It is crucially important to choose the CSD components that best fit your downtown from the perspectives of:

— Market demand.

— The ability of the private and/or public sectors to fund the construction of a needed building or facility

— Once built, the ability of the managing organization to earn and/or raise adequate operational funds

— Its potential impacts on the downtown on these dimensions:

Number of users
The revenues and customer traffic of nearby merchants and CSD organizations
Real estate values and taxes
The walkability of nearby streets and pedestrian flows
The physical attractiveness of the area
The ease of finding parking
Traffic congestion
Comparative cost benefits
Quality of life issues: crime, vagrancy and panhandling, noise, litter, smells.

Because another town has successfully developed a particular type of CSD venue does not necessarily mean a similar project will succeed in yours.

Some types of CSD venues have a higher probability of success than others:

They have a larger potential local customer base
They cost less to build
They cost less per user to operate.

N. David Milder

Part 2: SOME THOUGHTS ABOUT STUDIES OF THE ECONOMIC IMPACTS OF DOWNTOWN ENTERTAINMENT VENUES

Posted on April 3, 2015 by DANTH

An Assessment, From a Downtown Perspective, of Economic Impact Studies Done on Downtown Arts Venues That Use I-O Economic Models (Multipliers) cont’d.

The Critical Geographic Problem. Downtowns, even in NYC, Chicago or L.A., are geographically far smaller than counties. Consequently, there is an inherent mismatch between the geographic area the I-O model impact studies utilize and the one downtowners are most concerned about. Furthermore, the nature of the available data needed to construct these models precludes their being built for impact areas smaller than a county. While there are data available for zip code areas — a geographic unit sometimes useful for looking at large downtowns — experts in their use strongly recommend that analyzing a single zip code absolutely should be avoided. Instead, they advise that the zip code data should mainly be used to look at custom defined geographic regions that are not congruent with one or more counties, though sometimes they also can be used to cover part of a county (or counties) if enough zip codes are to be analyzed (7). C3D, for example, has done some studies on arts organizations that use a multiple zip code approach to define their impact areas (8).

According to Ben Davidson, Americans for the Arts’ (AftA) senior director of research services: “Our I-O models are generally constructed at the county level (obviously), and then aggregated for larger regions. But our proprietary model also allows us to customize it to specific local economic characteristics such as a city-based lodging tax“ (9). Each model is the basis of an Excel spreadsheet “calculator” that can estimate the impacts of a specific arts venue or of a community’s entire arts industry on the number of full time jobs, household incomes, local and state tax revenues.

One probably unintended and undesirable consequence of using county-centric I-O models is that the related off-site expenditures of county residents are often basically discarded and the analytical spotlight is focused solely on daytime and overnight tourists. The explanation given for this exclusion in a study done for the Los Angeles County Museum of Art (LACMA), which is similar to what can be found in many other large arts venue impact study reports, is that:

“Ancillary spending of local visitors (i.e., residents of Los Angeles County) is excluded, since these visitors would have spent these same monies elsewhere in the region, making their expenditures related to LACMA a displacement of local spending and not new spending attributable to the Museum.” (10).

For downtowners, a significant percentage of their counties’ residents will be in their trade areas and very important customers. They absolutely cannot be ignored. Another fact that cannot be ignored is that making a downtown again successful means it must recapture the expenditure dollars of its trade area residents. PC puffery may attempt to hide that fact, but its veracity will remain unrefuted. Information about an arts venue’s ability to draw trade area residents downtown and their demographic characteristics, lifestyles and spending patterns (how much and for what) would be very valuable pieces of impact information for downtown EDOs and merchants. There are surveys of arts audiences that provide such information. For example, the audience surveys done by AftA, which are done on site and only ask a limited number of questions, has provided such information about many arts venues and, in many ways are a model of how they should be done.

The heavy emphasis the I-O impact studies place on tourists also can be harmful. It can lead to downtown businesses over targeting tourists in their marketing and merchandise selection to the detriment of local shoppers, with seriously negative consequences in terms of sales and customer relations. It can also help generate bad town-tourist vibes that, in turn, can have undesirable political consequences. Over the past decade, DANTH has visited a number of small and medium-sized communities with penny-wise pound-foolish growth strategies: local merchants and politicians mistakenly placed far more attention and resources on attracting more tourists than on improving their abilities to serve local residents. Of course, merchants that fail to well serve their resident customers are not likely to succeed with tourists.

Arts/culture tourism certainly can be a valuable revitalization asset, but not every town can be an arts tourist mecca. As the growing success of downtown Valparaiso’s entertainment/hospitality niche is demonstrating, a strategy targeting that market segment is probably best used when local residents are also being well served by downtown merchants. Getting a good handle on the proportion of downtown retail, hospitality and entertainment sales that arts tourists are most likely to provide can help determine the level of attention and resources it deserves.

Audience Expenditures: It’s Critical to Get Good Data for This Critical Variable. Besides arts venue expenditures, the other variable that arts venue I-O model impact studies start from is audience expenditures. It also is a variable that, in and of itself, is highly likely to be of considerable interest and value to downtowners — even without the benefit of the information an I-O model can provide about how it is respent. Moreover, in many, perhaps most cases, downtowners will benefit more from audience direct expenditures than from the arts venue’s direct expenditures. Both downtowners and I-O models need or want good data on audience expenditures. The I-O model uses estimates of audience expenditures provided by other sources as an input. For downtowners, audience expenditures represent a very important impact. Downtowners do not need, nor can they use, an I-O model to get reliable and accurate information about audience expenditures.

Nonetheless, it is often a very troublesome one to research. The best way of obtaining reliable, acceptably accurate data on how consumers spend their money is to survey them. However, such surveys require substantially more methodological skills and resources than most other kinds of surveys. For many consumer items, the relevant information must be obtained close to the points in time when the expenditures are made, lest memories of them quickly fade. For example, the Bureau of Labor Statistics (BLS) probably sets the gold standard for this type of research and it has half of its 14,000 survey respondents keep diaries of their expenditures and interviews the other half 5 times over 15 months.

In contrast, too many of the arts impact studies do a secondary analysis of surveys conducted by an organization other than the one doing the impact study. These surveys are seldom done to BLS’s methodological standards and usually have far fewer respondents. Their ability to establish the causal connection between respondents expenditures and their arts venue attendance is usually weak or non-existent. Surveys done in the same community can produce very dissimilar expenditure estimates, leaving their wiser clients to be uncertain about their accuracy and reliability.

Forced to used surveys designed by others for other research objectives, the impact analysts often must make numerous assumptions or stipulations if they are to be able to use the “other research house” surveys for their own arts venue related research purposes (11). For example, the original survey may have been of the expenditures of all tourists visiting the community. The secondary analysts must figure out how to deal with an impact attribution problem: how much of this type of spending can be attributed to the tourists visiting the arts venue whose impacts are being studied, but who have not been surveyed? Of course, there will be other unanswerable issues such as: are the venue’s tourist visitors sufficiently similar to those tourists who do not visit the venue that the secondary use of the data is warranted?

Such impact research thereby becomes more and more of a modeling exercise, with each assumption or stipulation bringing in another unknown error factor and their interaction being potentially exponential rather than additive. For example, in the LACMA study:

“(V)isitors who have traveled from other parts of California, as well as from other states …are assumed to spend at least one additional night in Los Angeles County in order to visit LACMA…..International visitors to Los Angeles …are also assumed to have spent one additional day in the region in order to visit LACMA” (12).

The average expenditures for one day for these two types of tourists, as determined by the “outside” general survey of tourists, were then applied to estimate the economic impacts of the comparable tourists who visit LACMA.

Of course, most researchers and decision-makers live in a world of imperfect data and limited financial resources for obtaining the information they would like to use. Doing the necessary survey work may be beyond their allotted time and financial resources. Very often, they then find that making assumptions enables a kind of modeling exercise that, though admittedly imperfect and capable of only yielding ballpark type findings, still may promise sufficient enlightenment to be worth doing and for its findings to be seriously, if cautiously, considered. Such exercises, however, should come with some standards and responsibilities. For example:

Are the assumptions really reasonable? Re the LACMA study’s assumptions: Are tourists really likely to spend a full day or most of it at LACMA? Could they not also walk to the La Brea Tar Pits next door, or the other museums nearby on the “Miracle Mile or shop at The Grove just a 15 minute walk away– or get in their rented cars to go look at the Hollywood sign or the beach scene in Venice on that same day? Are they really spending a day in town just because of their visit to LACMA – so the motive not the behavior is the justification for the assumption? Or are they going to LACMA to fill part of a day they already planned on spending in LA and they then plan on also eating dinner, say at Spago, because they are not only are art lovers, but also restaurant tourists, etc.? In a world of multi-tasking, is uni-motivation for a day’s schedule really reasonable? Why then should a full day’s spending be attributed to the LACMA visit if its visitors – or at least a good number of them –are likely spending only a fraction of the day there and going to other destinations they might highly value in the remaining hours? Should portions of their daily expenditures be allocated to these other venues? If so, then by what formula? Will the assumptions produce answers that are sufficiently accurate to be usefully informative?
Are the consumers of the research being told about its data and methodological limitations and overtly adequately cautioned about its conditional value and utility?

Expenditure estimates based on iffy assumptions and that arrive without adequate and overt cautions about their use should be treated as probable horse puckey.

The LACMA study also provides a good example of just how much estimates of visitor expenditures can vary in one community, in this instance Los Angeles. Its analysis uses the following data, based on research published by TNS TravelAmerica in 2010, about visitor off-site spending per day: $53 those from Southern CA; $75 those from other places in CA; $75 those from other places in the US and $116 international visitors (12). However, the authors then note that:

“These estimates are conservative. In comparison, the estimates used by the Los Angeles Convention Center and Visitors Bureau for international visitors are at least four times as high, and those for domestic non-California visitors are five times that shown in the exhibit” (13).

The variation in these survey findings speaks more to the variation in their researchers’ skills and methodologies than to visitor expenditure patterns.

Realizing that its I-O models would be far more accurate and useful with accurate and reliable estimates of audience expenditures, AftA has made an enormous and impressive effort to get to surveys of arts audiences completed in each of the study areas for which it has generated an I-O model. The arts induced daily expenditures reported by AftA for the nation and in its 139 study regions are considerably lower than those cited in the LACMA study, though they still show a good deal of variation. Nationally, nonprofit arts attendees averaged arts induced daily expenditures of $24.60 per person (admission costs excluded) in 2012, with local audience members spending $17.42 and non-locals spending $39.96 (14). As can be seen in Table 6, the average resident daily expenditure across the six study region groups ranged from $16.55 to $21.89, with the highest community average within each group ranging from $24.69 to $39.39. Much the same is the case for non-residents, though the expenditures are, as to be expected, about twice as high. (It should be remembered that the non-arts related downtown expenditures of local residents may well easily erase this discrepancy.) The average individual expenditure ranged among the study region groups from $32.26 to $53.95, with the highest community average within each group ranging from $49.97 to a Colorado ski resort town’s $191.81.

AftA’s survey data across 139 communities and the data cited by the LACMA report indicate that there is so much potential variation in visitor daily expenditure estimates that data not gathered specifically for and in the subject arts venue is likely to be too error prone to warrant any useful and actionable conclusions. Secondary analysis of someone else’s survey of guest expenditures certainly should not be the preferred way to go.

For Downtowners, Audience Surveys Provide Much Richer Information About an Arts Venue Impacts Than I-O Models. Downtowners in the communities that did AftA directed surveys and have arts venues in their districts are likely to find the information collected and the way it is presented to be very useful, indeed. In these instances, the data describe the total arts induced spending that arts visitors bring along with them into the larger community (e.g., the large city, county or region) when they visit downtown arts venues, but not what they spend downtown. In other words, these data detail the sizes and types of spending pies (e.g., meals, clothing, gifts, ground transportation, etc.) downtown merchants can go after (see Table 7). They do not address how big a slice downtown merchants have won of each pie, though the survey has established that the respondents have visited the downtown, and the merchants’ geographic proximity should give them some competitive edge. This is similar to the information benefits merchants in downtown North Adams can get from the I-O model C3D used because AftA survey data for comparably sized communities were entered into that model.

Importantly, the survey data detail a number of other interesting audience characteristics, e.g., the visitors’ household incomes, education levels (see Table 8) and their reasons for visiting the community. For the vast majority of downtown business people and EDOs, these surveys provide much more useful and simple impact-related information (the characteristics and spending patterns of people brought downtown are the impacts, the arts venue is the “impacter”) than any I-O model can. Undeniably, the I-O models cannot function properly without them, since data about audience spending are a critical initial impacting force variable.

Looked at another level, the AftA data on the 139 study regions constitutes a unique database in which the audiences of many more than 139 arts venues (study areas can contain more than one venue) have been surveyed using the same questionnaire and in similar settings. It can facilitate the drawing of general conclusions about the impacts of arts venues. For example, Table 7 indicates that arts venue induced spending is most likely to go for “need” type purchases, such as food and drink away from home and lodging, while apparel and accessory shops might not win as many sales dollars or benefit so much from the arts venue’s downtown presence. Table 8 shows just how strongly arts venues attract well-educated visitors. True, these conclusions were long generally held within the economic development community, but never before has such strong systematic evidence been gathered in their support.

Downtowners and their EDOs also can learn a lot from AftA’s survey techniques:

Survey people on-site at the venue being studied
Don’t ask too many questions (but make sure that the respondents zip code is one of them)
Have a lot of respondents
Do it over enough calendar time to account for variation in events and weather
Make it easy for people to respond by asking about recent situations and actions, about things that are easy to know or remember, e.g., about purchases that were made recently.

These are also characteristics that should be found in the surveys downtown EDOs do of people employed in their districts or attending a college there.

A Closer Look at the Audience Expenditures Impact Attribution Problem. Impact attribution is a problem that plagues many entertainment niche element impact analyses, not just those in the arts. It derives from the essential tasks of logically establishing and/or measuring the causal linkage between an entertainment venue and some effect, sometimes when compared to other potential impacting factors or agents. For example, in earlier articles in this series, questions arose about:

How much of the improvements on Division Street Plaza (in Somerville, NJ), could be attributed to its conversion into a pedestrian mall and how much was the result of the general revitalization of its downtown?
How much of the revitalization of Manhattan’s Upper West Side, especially the Lincoln Square area, was due to the creation and growth of Lincoln Center and how much was due to the revitalization of Central Park and/or the area’s proximity to the Midtown CBD and strong transportation assets?

A similar problem also frequently arises regarding the spending of arts venue visitors, a critical variable for I-O impact analyses: how much of their local spending can be attributed to their visit to the venue? This was, for example, the challenge that prompted the LACMA study to make various assumptions about non-resident museum visitor spending. Making assumptions is one approach to establishing the causal linkage. A more effective one is to undertake an audience survey structured so that the respondents essentially report the causal linkages they have made between their arts venue visits and the local expenditures. Unfortunately, the impact attribution problem also can crop up in such surveys.

Americans for the Arts, as an advocacy organization, wants to show that arts venues and local arts industries provide strong economic benefits for their communities. It knows that its survey respondents are arts venue guests and so they just could be asked about their purchases in the community that day. But, their concern about arts impact attribution apparently is so strong that their survey asks the following two questions:

“2. Which of the following best describes your primary reason for being in this community today?

— I am a full-time resident/I live here

— I am a part-time resident (e.g., I own a vacation home)

— I am here specifically to attend this arts/cultural event

— I am here on a vacation/holiday

— I am here to conduct business (e.g., meeting)

— I am here for a combination of business & pleasure

— I am here on personal business (e.g., wedding)

— I am here to visit friends or relatives who live here

— Other (Please specify)”

“5. List below the estimated amount of money that you and the members of your immediate travel party have spent or plan to spend in this community specifically as a result of your attendance to this arts event. Remember to include money spent before, during, and after the event. If exact figures are not available, use your best estimates.

Admission tickets to this event
Refreshments and/or snacks purchased while at this event
Food, drinks, or meals purchased before or after this event (i.e., at a local restaurant)
Souvenirs, gifts, books, recordings, and/or art
Clothing or accessories specifically for this event
Local transportation (e.g., gas, parking, tolls, rental car, taxi or bus fare—not air fare)
Child-care specifically to attend this event
Overnight accommodations because of this event (e.g.,hotel, motel, bed & breakfast)
Other (Please specify):” (underline added) (15).

Question 2 allows residents and non-residents to be identified, though that can be equally achieved by another question that asks for the respondents residential zip code. More importantly, it allows the non-residents who are visiting specifically to attend an arts/cultural event to be identified. That helps measure the magnetism of the arts venue to attract tourists to the community. In building a downtown as a tourist center, venues that are strong tourist magnets are very important assets.

The question also enables non-residents who are visiting for other purposes to be identified. For these visitors, the arts venue is not a magnet, but more of a potential amenity. The arts venue, for them, makes the downtown “stickier,” i.e., it can pleasantly occupy visitors’ time and makes them want to stay longer and return. Successful downtowns are sticky, especially those targeting tourists. One well-known axiom about tourism is the “four times one rule, ” i.e., that “people will visit your community if it has activities that interest them, and that keep them busy four times longer than it took to get them there” (16). Entertainment venues are often recommended by tourism experts as good ways to make a downtown stickier.

Notice that the differentiators being looked for here are specific motivations; surveys are essential for capturing information about them. The reported behaviors of traveling to the community and attending the event cannot do the job by then turning into assumption burdened surrogate variables.

Q5 aims at establishing a very clear causal link so AftA can claim their findings show: “The total direct expenditures made by arts and culture audiences in each participating study region as a direct result of their attendance to nonprofit arts and culture events…” (underline added) (17). The question enables the art venue visitors — not the impact analysts — to make the connection between their expenditures and their visits. The arts impact attribution is very clear.

Downtowners, of course, will wish that the AftA surveys had asked about expenditures in the arts venues’ downtowns, something they can fix when they do their own surveys of their arts audiences. For some downtowners, the filter AftA used to establish the impact attribution may be too clear, perhaps finding that the wording in question 5 would exclude purchases that they would want to know about and see as causally related to visits to the arts venue. For instance, what about a desk or antique lamp purchased in the downtown that trip , but shipped to the home of the arts event attendee? Q5 does not ask about home furnishings or antiques. Also, what does “a direct result of your attendance” mean? Is the wording clear enough that respondents will not be confused or puzzled? Does the article of clothing purchased have to be worn at the event or simply purchased on the trip to attend the event for it to be counted? However, issues about question wording are, of course, endemic in survey research. Nevertheless, while the AftA surveys are understandably not perfect for downtowners, downtowners can learn much from their methodology and from the findings of all the surveys done in communities of comparable size to their own.

That said, it is still necessary to also keep in mind that surveys asking about how people spend their money are very error prone because of respondents’ memories and their concerns about confidentiality. Items that cost a lot ( e.g., a TV, computer or car) or are repetitive payments (e.g., rent, car payments) are best remembered. Smaller transactions are less well remembered. Survey questions that ask for expenditures in categories, such as the AftA survey asks, essentially require respondents to work, to remember individual transactions and then add them up in their heads. Consequently, the data produced by AftA type surveys are likely to have more erroneous responses, the extent of which cannot be determined. Nevertheless, they still may be the best information we can get about arts audience expenditures and still useful if we treat them as pretty good ballpark estimates, rather than some kind of precise statistical photograph of the real situation. Such estimates very likely will be good enough to meet the needs of decision-makers who are thinking in the ordinal measurement terms of everyday language (e.g. none, some, most, all) that inherently lack rigorously defined boundaries.

The essential question of whether or not such data are good enough really can only be answered by their potential end users and the people to whom they are accountable. For those of us who live in a world filled with imperfect data, this is not an unfamiliar question.

Up Next: Part 3 of this article will focus on analyzing the economic impacts of downtown parks.

ENDNOTES

7. Telephone conversation with Implan’s technical support.

8. See, for example, its research on the Casita Maria Center for Arts and Education (Bronx, NY) at: http://web.williams.edu/Economics/ArtsEcon/Casita.html

9. Quoted from an email message to the author

10. Christine Cooper, Shannon M. Sedgwick, and Somjita Mitra THE TRANSFORMATION OF LACMA: AN ECONOMIC IMPACT ANALYSIS. Economic And Policy Analysis Group, Los Angeles County Economic Development Corporation. January 2014, pp.17, p.9. (Hereafter referred to as LACMA study,)

11. For a good example, see: Economic Development Research Group, “The Economic Role and Impact of Lincoln Center,” September 2004, pp.49, p.18

12. LACMA study, p. 11-13

13. LACMA study p. 12

14. Americans for the Arts, “Arts Facts…Spending by Arts Audiences.” http://www.americansforthearts.org/by-program/reports-and-data/legislation-policy/naappd/arts-facts-spending-by-arts-audiences-2012

15. Americans for the Arts, “Arts & Economic Prosperity IV: National Statistical Report,” pp. 377, p. C-27

16. Roger A. Brooks, Maury Forman, “Twenty-five Immutable Rules of Successful Tourism,” Kendall/Hunt Publishing Company, 2003, pp. 55, p. 46.

17. Americans for the Arts, “Arts & Economic Prosperity IV: National Statistical Report,” p. B149

SOME THOUGHTS ABOUT STUDIES OF THE ECONOMIC IMPACTS OF DOWNTOWN ENTERTAINMENT VENUES Part 1

Posted on March 31, 2015 by DANTH

Introduction

While downtown leaders could benefit greatly from impact studies done on the entertainment venues located in their districts, they will find that far too many either geographically do not provide downtown relevant information, employ questionable research techniques and/or fail to look at key downtown-related impact variables. Much of this is because they too often lack a downtown perspective, one that is based on how a successful downtown works and that responds to the reasons so many downtown leaders and EDOs want strong entertainment venues in their districts. Such a perspective can not only help establish the needed geographic analytical lens, but also spotlight which impact variables are really important and explain why. Some impact studies seem to select variables not because they have high policy or program importance, but because there are available relevant data.

The Use of I-O Models. A lot of these impact studies primarily rely on input-output (I-O) economic models, a well respected tool among economic development analysts. However, their findings tend to be the least useful for downtowners. Most importantly, they focus on a geographical unit — the county, large city or region — that is far larger than any downtown, requiring a secondary analyst to work really hard if anything with downtown relevance is to be culled from them. They also often state the impacts in terms of variables that may be very pleasing for economists or funders or those giving projects government approvals, but do not touch upon downtowner economic concerns about district entertainment venues. Far too often, they use questionable estimates of arts audience expenditures. This variable is a critical starting point for the I-O models and a subject of immense interest for downtowners. The consequences of the questionable estimates follow the old adage: garbage in, garbage out. Studies that use such problematical data are of little use for their arts venue clients, even less for downtowners.

Real Estate Impacts. Other studies focus mainly on the entertainment venue’s impacts on nearby real estate. In contrast to the I-O model based studies, they tend to have significant geographic relevance and analytic value for downtowners. They are among the most useable by downtowners because they speak to major downtowner concerns and do not have a problem with their geographic focus. However, the real estate focused analyses frequently have impact attribution problems, e.g., how much of the impact is due to the arts venue and how much to other forces and agencies present in the area. It isn’t so much that there are methodological barriers to overcoming this problem as that the issue is so often simply ignored. Also, they too often overlook impacts related to audience growth and expenditures that are so important to downtowners. On the plus side, the needed real estate data are usually readily available and not that expensive to obtain.

Comprehensive Approaches. Some entertainment venues, e.g., MASS MoCA in downtown North Adams, MA and downtown Chicago’s Millennium Park, have had their impacts assessed by multi-dimensional approaches developed in academia, e.g., Williams College and Texas A&M. Their studies have yielded the most useable information for downtowners about an entertainment venue. For example, the analyses done by the Center for Creative Community Development (C3D) at Williams College of MASS MoCA’s economic impacts on its host city combines:

The output of a county focused I-O model that is somewhat useful for the business people in North Adams interested in knowing how the spending of the museum and its guests work their way through the regional economy they are part of
An analysis showing that the museum has made North Adams a more desirable place to live, with property values rising with increasing proximity to the museum
An analysis of the museum’s impacts on the opening of more new businesses, higher employment and higher salaries in the town
The mapping of the museums visitors and graphically displaying what is the museum’s trade area (1).

However, other impact studies done for some very large and well-known entertainment venues have combined an I-O analysis with some real estate analysis, but they have not had similar methodological strength, analytical depth or potential utility for downtowners.

KISS. While C3D utilized two rather sophisticated research techniques – the I-O model and an hedonic analysis to model neighborhood improvement through property appreciation — it also utilized other, simpler, types of data, such as counts of museum visitors, the block groups of visitors and their associated demographic data, and the data reported in the Census Bureau’s Zip Code Business Patterns about the number of firms, their number of employees, and payrolls. The visitor mapping is, in effect, an identification of MASS MoCA’s trade area that includes tourists as well as local residents. The ability of MASS MoCA to bring many visitors in from places well beyond its residential trade area is certainly an “economic impact” of immense interest to downtowners. Such analyses demonstrate the value of keeping in mind the Keep It Simple, Stupid principle in downtown entertainment niche impact studies.

Most of These Impact Analyses Are Done to Achieve the Objectives of Other Organizations and Consequently Often Lack Downtown Perspective or Relevance. Downtown entertainment niches can contain a wide variety of constituent venues, e.g., stadiums, arenas, PACs, theaters, cinemas, restaurants, bars, night clubs, coffee shops, museums, concert halls, parks, other outdoor and indoor public spaces, etc. Most of the impact studies have been done for the venues that need very substantial political support and/or very significant financial donations/ subsidies/ incentives: e.g., stadiums and arenas, arts venues, parks and other public spaces. A prime objective of these studies is to persuasively demonstrate their positive impacts on the local economy and community. This objective is commonly joined to the expectation that such evidence will spark greater financial support and/or stronger political backing or project approvals. Needless to say, the impact outcomes reported in the publicized studies are, unsurprisingly, habitually positive. Their sponsors apparently are getting what they need and pay for.

It is notable that far fewer impact studies are done on the for-profit entertainment niche elements, e.g., restaurants and watering holes, nightclubs, cinemas, theaters, etc. That should change because they are so often powerful contributors to a downtown entertainment niche. For example, a restaurant niche in one Little Italy on the east coast has over $80 million in annual sales and is a very strong tourist magnet: 20.2% of its patrons live 20-40 miles away and another 28.5% live 40+ miles away (2). This study was based on an analysis of patrons’ residential zip codes that was very similar to C3Ds analysis of MASS MoCA’s visitors.

And so….Some useful pieces of information for downtowners still can sometimes be gleaned from these studies. Also, downtowners and their EDOs would probably benefit from knowing what an entertainment venue impact study that meets their needs might look like. Consequently, the remainder of this article aims at:

Outlining a “downtown perspective” that frames the rest of the analysis presented below
An overall assessment of these studies
Identifying, as the discussion proceeds, the types of useful information for downtowners that can be culled from the existing studies of the impacts of downtown entertainment venues, even if they lack a downtown perspective
Outlining an approach for assessing the economic impacts of entertainment venues that is based on a downtown perspective
Identifying, as the discussion progresses, the types of data that can be used in such analyses. Many are relatively easy to collect. Downtown EDOs may already be gathering them, but do not realize they are measures of economic impact.

A Stab at Describing a Downtown Perspective for Such Impact Studies

Though they may be located in a downtown or large commercial district, the organizations that own/operate arts venues, parks, other public spaces, arenas and stadiums rightfully and understandably may want to learn about and publicize their economic impacts in a larger geographic area. Their impact studies consequently treat them as the impacting agents and seek to show that their influences are strongly positive in a whatever geographic unit – city, county, region –is needed to meet these objectives and/or required by an analytical tool.

In contrast, downtown leaders, EDOs and business operators start with concerns about how their specific and smaller geographic area will be impacted by these entertainment venues. The downtown geographic focus is critical. Downtowners also have the perspective of impact recipients. A district may or may not benefit more by having a significant entertainment venue locate within it than if it had located elsewhere in the region. The downtowners’ support for locating an entertainment venue in their district or for maintaining or enhancing the strength of those that are already there – almost always readily obtained — is based on expectations that their impacts will be significantly positive for the downtown’s businesses, property owners and/or residents.

Most important are the themes that usually characterize the downtowners’ impact expectations and provide the rationale for their support. Readers are invited to think about the downtown entertainment venue projects they may have been involved with or read about. Odds are the downtown advocates for those projects raised the following impact themes. These themes imply the use of certain variables and data:

Downtown Customer Spending Power and Merchant Revenues Will Increase. This promised increase in the number of downtown visitors with stronger spending power is often the most important factor for downtown leaders and business owners favoring entertainment venues in their districts. This theme can be further decomposed into the following points:
- The entertainment venues will bring more people downtown. That means that simple audience counts are an important variable and way to measure this economic impact
- The audience created increase in downtown visits will translate into more money being spent in the district to the benefit of the owners of local retail shops, restaurants, bars, hotels, etc. This means that reliable data on audience downtown spending and data on downtown sales revenues from the arts audience(s) are two more important economic impact variables. Getting reliable about both audience spending and retail related sales can be difficult
- Not only will there be more visitors, but they are likely to be those with more disposable income to spend. Data on the audience’s household incomes compared to those of non-arts audience downtown visitors, and preferably over time, is a way to measure this impact
How the Downtown Works. The increased customer traffic and venue operating hours will make the downtown more active and attractive during both the day and evening hours:
- There will be more pedestrian traffic and events, which can be measured by pedestrian counts on sidewalks adjacent to the arts venue and by counts of the number of events the venue has added
- It will induce the merchants nearby to lengthen their operating hours past 6:00pm, when many arts venue audiences arrive. This can be easily measured in many ways, including simple field observations or a quick call.
- There will be a consequent increased sense that the downtown is vibrant and exciting. This can be measured by a traditional opinion survey or a content analysis of what is being said about the downtown in selected media, both traditional and electronic
Strategic District Properties Will Be Improved. The specific properties occupied by the entertainment venues — that are often significant in their size , strategic location, historical importance and/or architectural merit – will be redeveloped, through new construction or renovation, with consequent increases in market value, rents and attractiveness. The latter requires opinions, so some sort of survey or content analysis would be required. Moreover, the real estate improvements can also mean fewer blank walls and other pedestrian discontinuities, less intrusive vehicle parking, or better utilization of mass transit assets. The reduction in the linear feet of pedestrian discontinuities is one relatively easy measure to employ. Increased transit boardings and debarkings would be another simple and useful measure
The District Will Be More Appealing to Individuals. The strong entertainment venues will make the downtown, overall, a more appealing place to live and work as well as visit. Counts of increased residents, non-arts visitors, retail customers, etc. as well as of rising rents and property values can be used as indicators of greater appeal if some assumptions are made about the causal link. Still, one can argue that “appeal” is a psychological factor and one better measured through opinion surveys that explore why people moved into the downtown or decided to visit it. Then, it is the individual visitor or resident who establishes the causal link between the venue and their actions, not an analyst postulating it

Figure 1. A sign on a new apartment building abutting High Line Park

The District Will Be More Appealing to Businesses. The locational desirability and market values of nearby properties also will increase because of the new venues, their physical appeal and the additional customer traffic they draw. This, in turn, will attract new commercial and residential tenants and spark new development projects. Here, too, there are behavioral indicators such as rising rents and greater investments in downtown properties. A good and easy to collect tell about a venue’s appeal are the significant buildings and businesses that coopt its name in their addresses or advertising. For example, in NYC, all the nearby office buildings that use Bryant Park in their addresses, the Bryant Park Hotel and all the new residential buildings along the High Line Park that have the park in their names or advertisements (see Figure 1). Better, yet, are the landlords who report that their vacancy rates are down and rents are way up because of the entertainment venue that is across the street or down the block, as the owners of the Grace Building have reported about Bryant Park (3). Another good data gathering tool are surveys of recent new commercial tenants that investigate the reasons why they selected their new locations.

One impact theme that is seldom raised among downtowners is how many of the dollars spent by the entertainment venue will be captured by other downtown businesses. Their focus is usually on what the expenditures of the audience will bring in. Probably this is because, for one reason or another, the expectation is that this arts venue revenue stream will not be all that important. Although contrary to basic economic development tenets, another impact theme that is not often heavily noted by downtown advocates of an entertainment venue is the jobs in the region the venue would directly or indirectly provide – except as these workers might be downtown customers.

Implicit in this collection of impact themes is an understanding of the downtown as a distinct socio-economic system based in a very specific geographic area that is strongest when it:

Contains, in a compact walkable area, a wide range of economic functions and activities, e.g. retail, entertainment, professional and personal services, education, healthcare, etc.
Attracts significant numbers of residents, workers and visitors who engage in multi-destination, multi-purposed visits and walk from one destination to another
Makes walking between destinations and the use of public spaces safe, interesting and attractive. This facilitates significant levels of pedestrian traffic and high levels of multi-destination trips
Provides commercial and residential spaces that are attractive to tenants and tenant prospects
Has mass transit assets to take people to and from the downtown
Facilitates district business people to make sales and have their assets appreciate in value.

An Assessment, From a Downtown Perspective, of Economic Impact Studies Done on Downtown Arts Venues That Use I-O Economic Models (Multipliers).

Since the early 1990s, there has been a rising tide of studies of the economic impacts of arts and cultural institutions that rely on using I-O economic models (4). Such a model “traces how many times a dollar is re-spent within the local economy before it leaks out, and it quantifies the economic impact of each round of spending” (5). They usually start with two key data points: the annual expenditures of the arts venue being studied and an estimate of how much the venue’s audience spends within its geographic study area. As the data in Table 1 demonstrate, see below, the venue’s direct expenditures tend to be greater than the related expenditures of its audience members. The data from 15 museums studied by C3D, shows that the museums themselves, on average, accounted for about 64% of the direct expenditures. The Table also shows data collected from surveys of arts and culture organizations and onsite surveys of their audiences in139 study regions across the nation by the arts advocacy organization, Americans for the Arts (AftA). Within each of these study areas there are usually several arts organizations. The AftA surveys indicate that, on average, about 55.7% of the direct expenditures are accounted for by the arts venues. A lot of the 8.5% difference between these two data sources probably can be accounted for by the fact that AftA counts the expenditures of both resident and non-resident audience members, while C3D’s estimates are based only on AftA data for non-residents reported in the study area fitting the population of the community in which the museum is located.

These models are attractive to impact analysts and report sponsors because, by the very nature of their stricture, they should be able to identify much greater impacts than other analytical approaches. They have a longer causal chain aimed at including ripple effects. They not only look at the “direct impacts” in terms of the total annual direct expenditures of the venue and its audience, but also their “indirect impacts”, e.g., how these expenditures are “re-spent“ by recipient companies (excluding wages), and also the “induced impacts” that look at the growth in household incomes and jobs that are created by the direct and indirect impacts. Table 2 shows, for the 15 museums studied by C3D, how the I-O models can demonstrate a very strong economic clout that goes well-beyond an arts venue’s own expenditures. The total impacts of these museums, for example, averaged being about 2.72 times greater than their annual expenditures, with the highest having a multiple of 5.1.

Of course, the arts venues’ audiences’ related off-site expenditures being included in the analysis significantly increases the magnitude of the computed total impacts. The 15 museums’ non-local visitors (i.e., tourists), on average, accounted for about 33.4% of their total impacts’ dollar values, though they ranged from a low of 13.8% to a high of 65%.

The Variable and Report Language Problems. Quite frankly, it is doubtful that downtown leaders will willingly give much attention to reports and presentations that use terms such as direct, indirect and induced impacts or outputs or economic activity. Its also doubtful that this type of vocabulary will help persuade arts venue funders, be they in government, foundations or private businesses. Table 3, below, shows the AftA’s estimates of the impacts of the City Theater on the economy of Greater Pittsburgh (Allegheny County). Again, the two key initial impacting variables studied are the annual expenditures of the arts organization and the expenditures of the people who attend its events. However, the variables selected to represent and measure the effects are household income, local tax revenues and full-time job equivalents. This vocabulary is less jargony, more tangible and speaks directly to important business and political concerns.

Nonetheless, for many downtowners, it still does not tell them what they most want to know. How does the arts venue bring people and their dollars into the district? How does it add to the revenues of their businesses? The vocabulary used by the C3D team in their assessment of MASS MoCA’s impacts on North Adams, comes much closer to meeting downtowner needs because it shows the impacts broken down by industry and type of impact. Furthermore, it limits the number of industries presented to those with significant impacts and does not give the complete and long list of industries an I-O model analyses. These data can help downtowners know more about how the studied arts venue is affecting a primary economic market in which they compete, the county or region. Such data can alert the downtown firms in these positively impacted industries that there are more dollars they can compete for as a result of the arts venue, but these data cannot specify how many dollars will be captured by downtown firms.

Some research suggests it’s only a very small portion. For example, a study done in 2011 on LCPA’s Fashion Week (that really lasts about a month) by students at the Fordham University Graduate School of Business. It found that about 10% of the spending generated by the event goes to Lincoln Square neighborhood businesses (6). The Fashion Week events, however, differ significantly in two respects from other LCPA events: they are relatively short, lasting under 30 minutes, and most occur during the daytime. Consequently, their audiences are likely to be less time-pressured and probably more likely to stroll around the neighborhood and to spend money in its shops, eateries and watering holes. The audiences for other LCPA events probably spend even less than 10% of their event related expenditures in the neighborhood, because they lack the time to roam the neighborhood.

Further support for the limited neighborhood impact hypothesis is provided by looking at the characteristics of the annual expenditures of arts organizations. Table 5 shows the annual expenditures of the Paramount Theater in Rutland, VT. Performance expenses, the payroll for its eight employees, occupancy costs and depreciation account for about 91% of the Paramount Theater’s annual expenditures. Given the theater’s programing, that is very heavy on individual and small group performances, most of the performance costs probably go for paying out-of-town talents. The needed sets and costumes are probably produced by firms that need low-rents and sometimes large spaces; their location in downtown Rutland is probably iffy. The theater’s staff is small. Even if they all lived downtown, their economic impact would be marginal. Their daytime local expenditures are also likely to be relatively small. Banking and professional services are likely to be found in downtown Rutland, but they only account for about 3.3% of the Paramount’s expenditures.

If the biggest source of an arts venue’s economic impacts, its direct annual expenditures, is highly unlikely to end up in the tills of nearby downtown businesses, then even if an I-O model could be built for a downtown, it would not provide very much additional illumination.

For the Downtown EDOs that do want to know about the impacts of an arts venue’s expenditures on other downtown businesses, the best way to research this issue is to do a simple survey of their downtown businesses operators. The questionnaire should be very short and not ask questions that require specific answers in dollars, if a decent response rate is to be successfully achieved. The more work you require your respondent to do – to answer a lot of questions or to provide very specific answers that really requires them to do research or makes them worry about confidentiality – the more likely they are to opt out of the survey. DANTH has done many surveys of small and medium sized businesses and it quickly became apparent that their owners/operators close up when asked to reveal specific data about their firm’s sales revenues or expenditures.

Answers in dollars probably would not be any more actionable for downtown EDOs or their members than those that are ordinal, i.e., that rate things in rank order and for which ordinary words can be used to do the ranking. For example:

None, some, a lot
Not significant, somewhat significant, very significant

Sometimes, the preciousness of numerical precision or the magic of impact multipliers makes us captives of otherwise questionable research techniques because they can generate data in discretely measured units, such as dollars or miles, or that are scaled. We then are prone to ignoring the simpler level of data needed for our decision-making, which often also can be easier and cheaper to obtain.

ENDNOTES

1. Stephen C. Sheppard, Kay Oehler, Blair Benjamin and Ari Kessle. “Culture and Revitalization: The Economic Effects of MASS MoCA on its Community,” Center for Creative Community Development (C3D), William College, 2006, pp.25

2. From a 2011 DANTH, Inc. project report.

3. See for example Howard Kozloff “The Payoff from Parks,” Urban Land August 29, 2012, http://urbanland.uli.org/economy-markets-trends/the-payoff-from-parks/

4. See for example: Rosemary Scanlon and Richard Roper, “The Arts as an Industry: Their Impacts on the New York-New Jersey Metropolitan Region.” The Port Authority of New York & New Jersey. October 1993, pp.77.

5. Americans for the Arts, “Arts & Economic Prosperity IV: National Statistical Report,” p. A6

6. Eric Wilson, “Fashion Week’s Impact, by the Numbers,” New York times, September 6, 2011 http://runway.blogs.nytimes.com/2011/09/06/fashion-weeks-impact-by-the-numbers/

N. David Milder at DANTH, Inc.

Downtown Revitalization Specialist

Category Archives: EDOs

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