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Impact of Large Chain Store Closures on Retail Rents

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Impact of Large Chain Store Closures on Retail Rents

By Barbara Byrne Denham and Scott Rappaport

Barbara Byrne Denham is a Senior Economist in the research and economics department at Reis, the team responsible for the firm’s market forecasting, valuation, and portfolio analytics services. Throughout her 20-year career, Barbara has written a number of white papers on the commercial real estate market.

Scott Rappaport is a Senior Analyst in the quality assurance department at Reis. Scott has been with Reis for over 10 years, the past five as the lead market specialist for the retail sector.

IntroductionA number of major store brands have announced store closures over the last two years. This report looks at the impact of these store closures at a micro level and seeks to determine how these closures have affected retail rents in these metros. Specifically, for metros that have seen significant store closures we look at how rents have changed compared to those with fewer closures.

In short, the numbers herein show that while many factors contributed to the closing of the 470+ stores included in the analysis, there is very little evidence suggesting that the closings had a direct impact on retail rents.

BackgroundFew if any have analyzed the impact of these store closures on real estate statistics. Having property level retail real estate data, analysts at Reis have been tracking store closures for the larger, more high-profile brands across the country. The Reis database includes 470 store closures in properties located in 77 of the 80 primary retail markets as well as 36 of the tertiary markets that Reis tracks totaling 28.9 million square feet of closed stores across the U.S. These include Walmart, Kohls, Sports Authority, Pathmark, Superfresh, A&P, Waldbaums, Haggen, Kmart and more recently Sears, Golfsmith, Macy’s and JC Penney added in March. Many of these closures were concentrated in 15-20 metropolitan areas including Philadelphia, Houston, Chicago, Central New Jersey, Long Island and those listed on page 3. All of these had or will have more than 500,000 square feet of store closures from 2015 through July of this year.

This comprehensive report includes a number of tables and charts on the store closures by metro as well as a discussion of all the factors that have affected bricks-and-mortar retail businesses including growth in e-commerce, changing consumer spending habits and poor planning on the part of businesses. Finally, the paper includes two appendices: one on real-estate-using retail sales trends and one on retail and restaurant employment growth by metro.

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Metropolitan Areas with the Most Store Closures (in square feet)

More than any other store, Sports Authority had the highest store closures with 8.0 million square feet or 28% of the 28.9 million square feet of total closures. Macy’s has the second highest with 6.7 million square feet but most of these are still in the process of closing. Kmart has had three separate closing announcements over the last year. It will have closed

4.3 million square feet. Most of the brands incurred closures across the U.S., but other brands such as Haggen only operate on the west coast. Most of the Walmart store closings occurred in rural areas beyond the Reis geographic markets, but eight “Neighborhood Walmart” stores with less than 70,000 square feet closed within the Reis metros.

Neighborhood and Community Center Retail Power Centers Malls Total

Philadelphia 655,677 195,068 1,046,998 1,897,743 Houston 168,666 318,504 767,000 1,254,170 Chicago 623,720 403,717 149,000 1,176,437 Central New Jersey 682,130 268,124 - 950,254 Long Island 452,158 251,470 193,530 897,158Boston 65,605 358,541 432,923 857,069 Detroit 42,610 15,000 767,000 824,610 San Diego 334,186 86,375 385,000 805,561 Northern New Jersey 669,411 134,132 - 803,543 St. Louis 164,598 376,378 180,000 720,976 Seattle 335,420 40,000 310,679 686,099 Los Angeles 545,562 79,917 - 625,479 Dallas 145,513 132,085 347,000 624,598 New Orleans - 110,112 456,000 566,112 Charlotte - 223,276 340,517 563,793

Total Top 15 4,885,256 2,992,699 5,375,647 13,253,602 Total Primary Metros 9,981,903 6,342,463 9,433,061 25,757,427 Total Tertiary Metros 3,173,804 3,173,804

Source: Reis

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The enclosed report looks at the percentage of inventory that store closures account for and the change in rent growth rates by metro. The purpose of this analysis is to see what impact the store closures and announcements of closures have had on occupancy and rent trends. In short, the closures have impacted these metros but there is no compelling conclusion. That is, those with more store closures in general have seen a sharper deceleration in rent growth, but only a few have seen rent declines. Moreover, the correlation is not as high as one might expect; that is, some metros with significant store closures1 have seen no impact on rents while others with low store closings have seen significant declines in rents.

1 It should be noted that this detailed data does NOT include details on whether or not the store spaces have been re-leased to another user. Some may have been in the interim.

2 Some of the store closures were in “power centers” that are tracked by Reis, but are not included in the Reis neighborhood and community center retail aggregate data. Nevertheless, we added these closures in with the others to see if they, as closed stores, could impact rents.

Brand Square Feet of Store Closings

Sports Authority 8,072,865 Macy's 6,686,000 Kmart 4,327,207 Pathmark/A&P/Superfresh 2,272,858 Haggen 2,176,206 JC Penney 2,088,531Sears 1,290,680 Golfsmith 1,034,481 Kohls 556,325 Walmart 426,078 Total 28,931,231

Source: Reis

Store Closures in Square Feet (2015 through 2017)

Impact on Primary Metropolitan AreasTo measure the change in rent growth we subtracted the quarterly rent growth rate of Q3 2015-to-Q4 2015 from that of Q3 2016-to-Q4 2016 to measure deceleration (if negative) or acceleration (positive). We then ranked these measures by metro against the percentage2 of total inventory that the store closures accounted for.

The general conclusion that one would draw from this analysis is that the higher the percentage of closed stores, the steeper the decline in rent growth. That is, the two measures should have a strong negative correlation coefficient. However, the correlation coefficient for the two measures is 5.4%, a number that suggests that there is little if any correlation. This suggests that the same factors that led to the store closures – oversupply, sluggish economic growth — impacted rent growth more than the actual closures themselves.

It should be noted that this study includes mall and power center closings, yet the rent data used in this study pertains to neighborhood and community shopping centers. When using only the neighborhood and community center closed square feet as a percentage of inventory for the 59 metros that had a store closure within this type of retail, the correlation coefficient drops to -14.8% which is still weak but more in line with what the logic would suggest: negative.

Many neighborhood and community shopping centers are anchored by a Kmart or A&P, but much of the other retail in these centers – hardware stores, nail/hair salons, delis and pharmacies — sell goods and services that consumers need in a pinch. Thus, these retailers are less impacted by the growth in e-commerce or the closing of a nearby store.

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Looking at the 20 metros with the highest percent of store closings, 10 showed a deceleration in rent growth overall from 2015 to 2016. These metros are highlighted below.

Note in the table that four of the metros saw a rent decline in the fourth quarter while five did in 2015. Of the 80 retail metros that Reis tracks, 13 posted a rent decline in the fourth quarter of 2016 including two (of the three) that had no major store closing (Greensborough/Winston-Salem and Little Rock). Similarly, 15 metros posted a rent decline in the fourth quarter of 2015 including five listed below as well as two that had no store closings. In other words, there is likely some causation between store closings and rent declines,

but it is indirect. The economic forces leading to store closings are broad and complex.

Impact on Tertiary MarketsThis latter sentiment can be found in the tertiary metro results as well. That is, the markets that saw a rent decline and/or a high percentage of closed stores incurred a deeper economic event such as the drop in oil prices (Abilene and Killene) or a correction in the casino industry due to an oversupply (Atlantic City/Cape May). Grand Rapids has a stronger economy than many tertiary markets but it may be over-retailed, hence the store closures and rent decline in 2016.

MetroSq. FT. of

Store Closures% of (NC)

Retail InventoryQ3-Q4 2016

GrowthQ3-Q4 2015

GrowthDifference

(-Deceleration)New Orleans 566,112 8.0% 0.6% 0.5% 0.1%

Long Island 897,158 3.7% 0.5% 1.3% -0.8%

Northern New Jersey 803,543 3.6% -0.1% 0.7% -0.8%

Tulsa 388,000 3.2% 0.9% 0.7% 0.2%

Philadelphia 1,897,743 3.1% 0.4% 0.2% 0.2%

Ventura County 333,486 3.0% 0.5% 0.6% -0.1%

Pittsburgh 537,559 3.0% 0.7% 0.9% -0.1%

Salt Lake City 477,760 2.9% -0.1% -0.3% 0.2%

Knoxville 241,751 2.9% 0.7% -0.1% 0.8%

Central New Jersey 950,254 2.7% 0.2% 0.3% -0.2%

Tacoma 188,940 2.6% -0.8% -1.0% 0.2%

Seattle 686,099 2.5% 0.0% 0.6% -0.6%

St. Louis 720,976 2.5% 1.1% 0.5% 0.7%

Charlotte 563,793 2.4% -0.2% -0.1% -0.1%

Detroit 824,610 2.4% 0.3% 0.6% -0.3%

Boston 857,069 2.3% 0.2% 0.2% 0.0%

Albuquerque 238,529 2.2% 1.1% -0.5% 1.5%

Hartford 307,151 2.1% 0.3% 0.6% -0.3%

Rochester 214,000 2.0% 0.5% 0.0% 0.5%

San Diego 805,561 1.9% 1.2% 1.5% -0.3%

Source: Reis

Top 20 Metros with the Highest percent of Store Closures vs. Change in Rent Growth from 2015 to 2016

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Also note in the table below that five of the metros saw a rent decline in the fourth quarter, and all of them saw a high percentage of store closures. Thus, there may be a stronger impact on rent growth from store closures when the market is relatively small. Indeed, the correlation coefficient between the percentage of inventory of closed stores and rent rate deceleration for the tertiary markets was -35% which is significant. However, of the 116 retail tertiary metros that Reis tracks, 37 posted a rent decline in the fourth quarter of 2016 including 28 that had no major store closing. Similarly, 37 metros posted a rent decline in the fourth quarter of 2015 including three listed below as well as 22 that had no store closings. Again, this data suggests the connection between store closures and rent declines is more significant but it is not conclusive.

MetroSq. Ft. of Store

Closures% of Retail Inventory

Q3-Q4 2016 Growth

Q3-Q4 2015 growth

Difference(-Deceleration)

Abilene, TX 138,437 6.9% -0.5% 0.2% -0.7%

Columbus, GA 217,231 6.4% -0.1% 0.5% -0.6%

Killeen-Fort Hood, TX 115,000 4.8% -0.3% 0.3% -0.6%

Atlantic-Cape May, NJ 180,000 4.7% 0.1% -0.6% 0.7%

Grand Rapids, MI 204,662 3.4% -0.3% 0.4% -0.8%

Savannah, GA 104,000 3.0% 0.2% 0.4% -0.2%

College Station-Bryan, TX 63,506 2.6% -0.1% 0.3% -0.3%

Fayetteville, NC 80,000 2.5% 0.3% 0.3% 0.0%

Lancaster, PA 124,725 2.5% 0.3% 0.4% -0.1%

Visalia, CA 95,665 2.4% 0.3% 0.1% 0.2%

Spokane, WA 78,391 2.4% 0.1% 0.3% -0.2%

Santa Barbara, CA 92,900 2.2% 0.4% 0.1% 0.3%

Bakersfield, CA 135,741 2.1% 0.0% 0.1% -0.1%

Allentown, PA 146,343 2.0% 0.1% 0.1% 0.0%

Stockton, CA 109,500 1.9% 0.3% 0.3% 0.0%

Olympia, WA 32,165 1.9% 0.1% -0.4% 0.4%

San Luis Obispo, CA 99,479 1.8% 0.0% 0.1% -0.1%

Boise, ID 88,500 1.8% 0.1% -0.7% 0.8%

El Paso, TX 101,000 1.6% 0.5% 0.1% 0.3%

Naples, FL 91,266 1.6% 0.3% 0.7% -0.4%

Source: Reis

Top 20 Metros with the Highest Percent of Store Closures vs. Change in Rent Growth from 2015 to 2016

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Is Retail Dead?Many have attributed the decline in bricks-and-mortar retail to the growth in e-commerce. Retail sales growth has been weak throughout this expansionary period, yet e-commerce sales have been robust. Many presume that the retail pie is a zero-sum game, that the growth of e-commerce has come at a direct cost to bricks-and-mortar stores.

While e-commerce has hurt retail stores, the numbers herein suggest that the impact is not so direct. First, many may make the valid claim that the stores that have closed are brands that no longer appeal to buyers who prefer newer and “hipper” labels. Fashion trends change constantly as do the preferences that consumers have for stores that carry them. Just as Bonwit Teller and B. Altman went out of fashion (and business) a generation ago, so too possibly are Macy’s and Kmart on the wane now.

Few would argue that the retail industry was due for an overhaul. Some brands have not changed their image in decades and lack both the flexibility and foresight to change with the times. Perhaps it is the lack of marketing panache that doomed these stores.

A third theory on the demise of retail has to do with the con-sumer shift away from buying goods to more “experiential” spending including restaurants, travel, spas and fitness. This has hurt some retailers such as clothing and electronic stores. Malls with trampoline parks, gourmet food courts, yoga classes and/or other amenities are more likely to draw shoppers than those that do not. This shift in spending is not likely to change in the next few years; thus, landlords are advised to seek more service-oriented tenants that can adapt to consumer tastes.

In fact, the numbers below showing the trend in real- estate-using retail sales that include restaurant sales indicate that trends have continued to grow at a steady pace, although the pace of growth slowed in the fourth quarter of 2016. Moreover, the employment numbers also indicate that the industry is still adding jobs in most, but certainly not all, metros tracked by Reis.

Just as Bonwit Teller and B. Altman went out of fashion (and business) a generation ago, so too possibly are Macy’s and Kmart on the wane now.

In sum, retail is not dead. Consumers still love to shop and to go out to do so. Retailers that do not upgrade their stores and brands stand to suffer more than those that do so. Enhancing a brand with a hip and efficient e-commerce site should complement a retailer’s efforts, not cannibalize it. Some retailers have learned this, others have not and it is those retailers that did not or could not change with the times that are learning their lesson with the closing of their stores.

ConclusionThe data shown above suggests that to some extent, the closing of stores had a marginal impact on rent growth in some metros. Although, one could equally argue that the retail climate was already weak, that the closing of stores was more a national decision, or that rent declines were driven by an oversupply of retail stores. Economists call this an endogeneity problem; that is, the variables studied are connected along with other variables, making it difficult to determine how the causality works.

There are a number of economic factors that led to the closing of these stores including consumer tastes for brands, changing spending habits towards “experiential,” poor planning by retail businesses as well as the rise of e-commerce. This analysis suggests that all of these factors are affecting bricks-and-mortar retail businesses, but the closing of the larger stores is not necessarily hurting retail rent growth as directly as many would assume.

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APPENDIX A

Growth in Real-Estate-Using Retail Sales vs. Reported Retail Sales

Source: Reis

0%

5%

10%

15%

20%

25%

30%

2011

2012

2013

2014

2015

2016

Perc

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hang

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2011

Real-estate-using Retail Sales Annual Growth*Retail Sales Annual GrowthReal-estate-using Retail Sales*Retail Sales

Over the last few years, the media reports on retail sales figures have sent considerable fears through the economy as the weak overall report combined with strong e-commerce sales growth has led many to assume that bricks-and-mortar retail sales are negative. This doomsday sentiment is largely misplaced for a number of reasons. First, the drop in oil prices over the last two years has yielded negative gasoline sales which have hurt the aggregate retail sales numbers. Note, however, that gasoline sellers are not a part of traditional shopping centers. Second, automobile sales which are also not a part of shopping centers have been extremely volatile. Finally, restaurants that do lease space in traditional shopping centers have seen strong growth over the last few years, but these numbers are not reported in the general media report. Netting all of these variables — retail sales less gasoline, automobile and “nonstore”

retailers (e-commerce firms) but adding in restaurant sales — gives a “real-estate-using retail sales” (REU) number that has grown at a steadier rate than overall retail sales as the charts below show.

Note how REU retail sales was growing at a stronger rate than retail sales in 2014 through most of 2016, but a sharp shift is seen in the fourth quarter data as overall retail sales climbed while REU retail sales decelerated. The jump in the blue line in the last quarter is due to both higher e-com-merce sales as well as automobile and gasoline sales that have bounced back with the price of oil that has doubled in the last year.

While the drop in the red line in the fourth quarter looks a bit troubling, it could just be a one-quarter anomaly. This break-out of the data warrants watching on a regular basis.

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Average Annual Sales Growth by Retail Category

The chart below puts the differences in volatility in better perspective. This chart shows average annual growth in five categories. E-commerce, listed first, clearly shows accelerating average annual growth rates. Restaurants, however, have also seen higher annual growth rates every year throughout the recover. In fact, restaurants had grown in line with e-commerce on an aggregate level every year until 2016 when e-commerce growth soared.

Automobile and gas sales had seen sharp growth at the start of the recovery but then fell in 2015-2016. In 2015 alone, gasoline sales declined by more than $100 billion. Gasoline sales fell another $31 billion in the first three quarters of 2016. However, the trend reversed in the fourth quarter when automobiles and gasoline sales combined added $14.2 billion or 62% of the total sales growth.

The fourth category listed in the chart below includes general merchandise, food, clothing and pharmaceuticals. These categories represent necessities, or non-discretionary retail spending. Not surprisingly, growth in this “necessity” category was very steady, even in 2005 through 2010. However, the decelerating trend in 2014-2016 is concentrated in general merchandise, in particular, department stores that have declined $4 billion on average over the last two years.

Finally, the bottom category including furniture, electronics, sporting goods, building materials and miscellaneous categories captures more discretionary spending. This discretionary category clearly posted a net average loss from 2005 to 2010 and then saw slow growth in 2010 to 2014. Since then, this category has accelerated a bit suggesting that consumers were more confident on the economy.

-$40,000 -$20,000 $0 $20,000 $40,000 $60,000 $80,000 $100,000

Furniture, electronics, sporting goods, building materials and miscellaneous

General merchandise, food, clothing,health and pharmaceutical stores

Autos and gasoline

Restaurants

Electronic shopping and mail-order houses

Average annual sales growth (nominal, in millions)

2005 - 2010 Average Annual Growth 2010 - 2014 Average Annual Growth 2014 - 2016 Average Annual Growth

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APPENDIX B: RETAIL AND RESTAURANT EMPLOYMENT GROWTH BY METRO

Retail and Restaurant Employment Growth by Metro

EmploymentMetro 2015 2016 2015-2016 GrowthChattanooga 25,900 27,500 6.2%Tacoma 60,600 64,400 6.3%Austin 190,900 199,800 4.7%Charleston 71,400 74,700 4.6%Seattle 281,000 293,900 4.6%Orlando 245,900 255,900 4.1%Dallas 429,800 447,200 4.0%San Antonio 204,600 212,500 3.9%Tampa-St. Petersburg 262,800 272,900 3.8%San Bernardino/Riverside 291,000 302,000 3.8%Columbia 71,000 73,600 3.7%Atlanta 494,400 511,900 3.5%Palm Beach 132,000 136,600 3.5%Raleigh-Durham 161,500 167,100 3.5%Sacramento 169,900 175,800 3.5%Charlotte 213,000 220,200 3.4%Salt Lake City 112,500 116,100 3.2%Phoenix 382,700 394,800 3.2%Memphis 66,200 68,200 3.0%Colorado Springs 56,000 57,700 3.0%Louisville 117,200 120,800 3.1%Houston 542,900 559,000 3.0%Oakland-East Bay 196,300 202,100 3.0%Knoxville 46,600 47,900 2.8%

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Another, somewhat reassuring indicator is employment growth. Nationally, the retail and restaurant industries together added 70,000 jobs in the fourth quarter, a growth rate of 0.3%. The disparity in growth rates by metro area, however, was pronounced: as many as 48 of 82 metros saw a decline in employment in the fourth quarter but only four metros posted a decline for the year. Syracuse saw the

biggest drop followed by Hartford, Ventura County and Fairfield County. Metros ranked by retail and restaurant employment growth are highlighted below. The fact that so many metros are still adding retail jobs at a rate that is in line with overall job growth suggests that the retail industry is not suffering significantly from the store closures.

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Retail and Restaurant Employment Growth by Metro

EmploymentMetro 2015 2016 2015-2016 GrowthCincinnati 105,900 108,700 2.6%Indianapolis 188,500 193,500 2.7%Portland 202,600 207,800 2.6%Los Angeles 778,800 798,500 2.5%Denver 251,200 257,400 2.5%Orange County 283,800 290,300 2.3%Lexington 52,600 53,800 2.3%Kansas City 187,300 191,400 2.2%Fort Worth 200,300 204,700 2.2%Detroit 354,900 362,700 2.2%District of Columbia 73,000 74,600 2.2%Las Vegas 201,100 205,400 2.1%Greensboro/Winston-Salem 113,300 115,700 2.1%Jacksonville 75,800 77,400 2.1%Birmingham 97,300 99,200 2.0%Minneapolis 317,600 323,700 1.9%Boston 305,900 311,700 1.9%San Diego 272,800 277,900 1.9%Suburban Virginia 240,400 244,800 1.8%Omaha 88,500 90,100 1.8%Providence 116,200 118,200 1.7%Milwaukee 137,300 139,600 1.7%Little Rock 38,800 39,400 1.5%Oklahoma City 121,900 123,800 1.6%Nashville 95,200 96,700 1.6%San Francisco 174,300 176,900 1.5%Norfolk/Hampton Roads 152,400 154,700 1.5%Tulsa 84,900 86,200 1.5%Buffalo 109,300 110,900 1.5%Fort Lauderdale 108,700 110,300 1.5%New Orleans 123,400 125,200 1.5%Tucson 72,800 73,800 1.4%Rochester 90,600 91,900 1.4%San Jose 160,400 162,600 1.4%Central New Jersey 187,100 189,500 1.3%Richmond 65,900 66,700 1.2%Long Island 254,200 257,100 1.1%

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Retail and Restaurant Employment Growth by Metro

EmploymentMetro 2015 2016 2015-2016 GrowthColumbus 184,100 186,200 1.1%Miami 238,300 240,900 1.1%Greenville 44,400 44,800 0.9%New Haven 30,000 30,300 1.0%Suburban Maryland 98,700 99,700 1.0%Philadelphia 327,100 330,100 0.9%Chicago 465,400 469,600 0.9%Dayton 39,400 39,800 1.0%St. Louis 256,000 258,000 0.8%Northern New Jersey 293,600 295,700 0.7%Pittsburgh 212,300 213,700 0.7%Baltimore 238,900 240,300 0.6%New York 644,800 648,000 0.5%Westchester 134,500 135,100 0.4%Wichita 57,100 57,400 0.5%Albuquerque 42,000 42,000 0.0%Cleveland 102,100 102,100 0.0%Fairfield County 47,900 47,700 -0.4%Ventura County 39,900 39,800 -0.3%Hartford 56,000 55,500 -0.9%Syracuse 36,200 35,800 -1.1%

Source: Bureau of Labor Statistics and Reis

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