The Short-Term Rental Effect An Analysis of the Propagation and Legislation of Short-Term Rentals in Sandy City, Utah

An Analysis of the Propagation and Legislation of Short-Term Rentals in Sandy City, Utah

THE SHORT-TERM RENTAL EFFECT An Analysis of the Propagation and Legislation of Short-Term Rentals in Sandy City, Utah Darryll W. Wolnik University of Utah MCMP - 2019 Darryll W. Wolnik The Short-Term Rental Effect Acknowledgements To my beautiful and supportive wife Angela, who has put up with my pursuit of education, even while I continued to work full-time, and who moved to a new state just so I could study at an esteemed institution. There were weeks we did not see one another for more than an hour, but you kept me motivated and focused, and never let me stop pushing towards my goals. A special additional thanks to my project advisor, Keith Bartholomew, who always seemed to know exactly what to say to keep me motivated. Because of you, I was able to graduate early. Finally, to Dr. Stacy Harwood, Department Chair of the University of Utah’s Planning Department, for her wisdom and guidance; to Matthew Wheelwright, PhD candidate and Martin Buchert, GIS instructor, for their help with various portions of this project; to Jared Gerber, Sandy City Assistant Community Development Director, who had faith in me as a new employee and put me in charge of the short-term rental program; to James Sorenson, Sandy City Community Development Director, who gave me the amazing opportunity to work for an incredible organization; and to Mike Wilcox, Sandy City Zoning Administrator, for teaching me so much about planning and being patient with my persistent inquiries. 1 Darryll W. Wolnik The Short-Term Rental Effect This work is dedicated to the 48 United States Marines and Sailors of 3rd Battalion, 25th Marines, who made the ultimate sacrifice as part of Operation Iraqi Freedom in Al Anbar, Iraq, 2005 I will always remember you 2 Darryll W. Wolnik The Short-Term Rental Effect Table of Contents Acknowledgements 1 Dedication 2 Table of Contents 3 Introduction 4 Introduction to Arguments 7 In Support of STRs 7 STRs Have a Negative Effect on the Market 8 Strict Regulation of STRs and potential issues with such regulations 13 How to Create Good Regulations 15 History of Short-Term Rentals in Sandy City 17 Current Legislation 19 Analysis of Sandy City’s Short-Term Rental Ordinance 20 Short-Term Rental Analysis 22 Analysis of Permitted Units 23 Analysis of All Units 28 Impacts to Sandy City Housing 31 Limitations 35 Conclusion 36 References 37 3 Darryll W. Wolnik The Short-Term Rental Effect Appendix A 40 Appendix B 41 Appendix C 43 Appendix D 44 4 Darryll W. Wolnik The Short-Term Rental Effect Introduction The sharing economy is a relatively new phenomenon in western capitalism. First coined in 2008 by Professor Lawrence Lessig at the Harvard Law School (Cotrim, 2016), it describes a new frontier in commerce. The sharing economy has changed the landscape of the economy itself, empowering consumers by giving them more choice and better value in their purchasing decisions. However, this empowerment is not limited to end-users; rather it equally applies to service providers. Individuals can now drive their personal vehicle as a taxi and even rent part of their home to travelers, all under the protection and name-recognition of large corporations, for a nominal fee of course. The sharing economy has given rise to peer-to-peer business facilitators such as Airbnb (2008) and Uber (2009). With Uber revenue growth predicted at $326 billion between 2014 and 2025 (Yaraghi and Ravi, 2017), governments have been racing to regulate this exploding market. In New York City, taxi drivers and companies that pay 100’s of thousands of dollars for a “taxi medallion” to operate a cab demanded regulation for ride-sharing apps like Uber (New York Times, 9/10/17). This regulation was passed August 8, 2018. In January 2018, San Francisco passed a set of new regulations that reduced the number of available short-term rentals in that city by roughly 75%. Among the requirements were that the rental be owner-occupied (San Francisco Chronicle, 1/14/18). Among the most compelling arguments for sharing economy regulation is the argument to rein in the short-term rental market. Opponents of sharing sites such as Airbnb claim housing costs are inflated by individuals and companies that purchased existing homes for the sole purpose of using them as short-term rentals (Lee, 2016). A short-term rental is generally defined as a rental dwelling, anything from a room in an apartment to an entire house, rented by a party for less than thirty days. These accommodations are typically used by vacationers, although increasingly business travelers and those coming to an area looking for long-term housing have been utilizing short-term rentals. Some examples of the effects of short-term rentals can be found in recent publications. In Boston, an increase of one standard deviation in density of short-term rentals led to a 4% increase in rental rates and a 5.9% drop in housing stock available for standard housing use (Horn & Merante, 2017). In addition, the proliferation of short-term rentals leads to gentrification on a level not seen before. This is due to the ease of “redevelopment” in turning around a property and transforming it into a short-term rental. This new cycle of gentrification and redevelopment is driven by the adjustment to the rent gap caused by the above factors regarding short-term rentals (Wachsmuth & Weisler, 2018). By using these homes for short- 5 Darryll W. Wolnik The Short-Term Rental Effect term rentals, existing housing stock is removed from the market, creating scarcity in the market. Cities are increasingly worried about housing costs, as it prices people out of the market and may leave neighborhoods fractured from year-round vacation rentals among owner-occupied and long-term rental homes (Cocola Grant, 2016). Vacation rentals are nothing new to the housing market and the tourism industry. People have been renting rooms in their homes for many years. In fact, many cultures prefer to stay in accommodations such as these over hotels and motels. What is new, however, is the way these places are rented. No longer are vacation rentals secured through newspapers, magazines, tourism bureaus, or travel agents. The internet has made those methods of delivery nearly obsolete. Instead travelers can secure rooms and even entire homes through web sites like HomeAway, Turn Key, and the internationally known and utilized Airbnb (Cocola Grant, 2016). Having been on the scene just over 10 years, Airbnb has completely transformed the manner in which millions of people travel all across the globe. However, Airbnb’s resounding success (with millions of listings in over 190 countries) has exposed a dark side to the vacation rental phenomena: a housing crisis. In cities like Boston, a new technological rent gap has been created in which landlords and homeowners can transform their properties in short-term rentals for very little, if any, investment. Drawn by the sometimes 3-4x increase in possible monthly rents (Wachsmuth & Weisler, 2018). This has led to high-demand areas, many of which already suffer from an affordable housing crisis, having virtually no available housing and driving up the rents and asking prices of those that remain on the traditional housing market. In these high-density areas, regulations would be effective in controlling the effect of shortterm rentals, however Airbnb in many cases refuses to enforce local laws on their platform (Kim, et al., 2017). At the crux of these issues is the aforementioned infancy of Airbnb and the online vacation rental market. As such, very little research has been done into the effects of short-term rentals in this new information age. Even less research has been done on the effects of Airbnb on the housing market, and even then, the research is limited to cities like Los Angeles, Boston, New York, Barcelona, and Sydney. Therefore, it is of the utmost importance to forge ahead into this new realm of research, to begin making connections between data and real-world effects. Only then can we begin to understand how policies effect the way in which the short-term rental market operates. 6 Darryll W. Wolnik The Short-Term Rental Effect Introduction to Arguments With such a small body of research, the number of questions that need to be explored are boundless. This paper will attempt to cover a few of them in moderate detail. However, first we must investigate the current body of research. There are four main topic areas that the existing research generally covers; the net positives of short-term rentals, the negative impacts of short-term rentals, implications of strict regulations, and components of good short-term rental ordinances. This paper will look at these topics, in this order, with the understanding that compartmentalizing individual bodies of research into buckets can prove problematic, as those studies may highlight info that supports different viewpoints. However, for the purpose of this paper, these studies have been categorized to the best of the author’s ability. In support of STRs There is little doubt that short-term rentals produce at least some positive for the community. After all, if there was even a strong imbalance of negative to positive, there would not be the short-term rental problem that we have in many places. Understanding there are indeed net benefits from short-term rentals is key to understanding the scope of the problem. To deny this would pigeon hole ones thinking and severely hamstring any effort at crafting a fair, effective, and equitable solution. The most prevalent argument from Airbnb and other short-term rental supporters is the ability of short-term rentals to benefit the homeowner. Kaplan & Nadler, in their paper Airbnb: A Case Study in Occupancy Regulation and Taxation, cite both the positive effects of short-term rentals. In New York City between 2012 and 2013, short-term rentals brought in $632 in economic benefits and provided 4,580 jobs. Those visitors who stayed in a short-term rental had a tendency to stay two additional days and spend $200 more at local businesses. Shortterm rentals tend to be more dispersed than traditional hotels, with 82% of accommodations located outside of Manhattan, which is considered the central district in New York City. Shortterm rentals allow hosts to generate valuable income as well. Kaplan & Nadler found about half of all hosts in New York City to be mid-to-low income. This shows that short-term rentals help make housing more affordable by increasing income to households. In San Francisco, the authors found 86% of all listings to be single-owner listings; it was also found that 98% of hosts had three or fewer listings. In New York City, Kaplan & Nadler state that Airbnb has tried to voluntarily remit $20 million in taxes from short-term rental listings, but faced roadblocks from various levels and departments of government. 7 Darryll W. Wolnik The Short-Term Rental Effect Another net positive, and one that is less talked-about, is the affect short-term rentals have on the appearance of the home itself. Jamila Jefferson-Jones (2015) broaches this topic in her study on increasing homes values due to short-term rentals. In fact, she argues short-term rentals preserve home values. She points out that such rentals allow homeowners to make additional income from areas of their home not currently in use, which was already stated by Kaplan & Nadler above and is a common argument in support of short-term rentals. This income stream provides incentive for homeowners to maintain their homes, making a connection not immediately made by many researchers. By maintaining their homes, they hold their value better than homes not being maintained; or at least not being maintained to such a high standard. Aside from encouraging better home maintenance, short-term rentals can help to stabilize homeownership by way of the extra income provided. Furthermore, JeffersonJones argues that not only are short-term rentals good for home values, but the right of homeowners to operate one is a stick in the bundle of property rights which a homeowner holds, an idea we will approach later in this paper. While many researchers point to potential positives in their studies, those positives are far outweighed by the negatives. Most researchers infer a net negative impact from short-term rentals. It cannot be ignored that the above studies fail to address potential negative impacts; instead focusing on positive aspects of short-term rentals. STRs have a negative effect on the market Short-term rentals have been found to affect the market in a negative manner. Multiple researchers have commenced exploration of what these negative effects are, how widespread they are, and how to mitigate them. Researchers are still exploring just how strong these effects are, but preliminary conclusions indicate some important points. Early research from some groups has shown short-term rentals to affect rental rates and home values in at least some way across not just the county but also around the world. Research has also indicated some relationship between housing vacancy and the number of short-term rentals in a community. Finally, these rentals may even increase the rate at which gentrification occurs. One of the most robust studies to date was done by Dayne Lee (2016). The study explored the effect of short-term rentals in Los Angeles, California. While this effect is felt across the city, is is more pronounced in certain neighborhoods. In Lee’s exploration of the short-term rental market, he found short-term rentals were concentrated in the seven of the most expensive and densely-population neighborhoods; Venice, Downtown, Hollywood, Hollywood Hills, Miracle 8 Darryll W. Wolnik The Short-Term Rental Effect Mile, Echo Park, and Silver Lake. These neighborhoods accounted for about half of all listings on Airbnb. In addition, rents in these neighborhoods were 20% higher and were increasing 33% faster than the rest of the city. Of the 104,265 rental units in these neighborhoods, as much as 3% of this rental housing stock was taken up by whole-house year-round short-term rentals. When combined with a vacancy rate of about 3.5% and the 3 years required to add new housing stock, the sudden removal of units from the rental market by conversion to short-term rentals can constitute a housing shock. With this information, using a flat supply curve and constant rental demand, Lee found a 1% decrease in rental housing supply would lead to a .2% increase in rents. This increase alone does not account for the increased upward pressure on rental rates, homes values, and property taxes as a result of the allure of increased profits from conversion to a short-term rental. As such, this leads to a bidding wars between those people looking for housing and investors looking for properties to purchase for use as a short-term rental. Taking all this information into account, it was found by Lee that the presence of short-term rentals drove up the cost of housing slightly citywide, but significantly on a neighborhood basis. Lee also explored the reduction of housing supply from the proliferation of short-term rentals. It was found 89% of Airbnb revenue in Los Angeles as a whole came from whole-house yearround rentals. This would suggest that Airbnb (and other platforms) encourage the hotelization of properties by evicting long-term renters or by not renewing their leases. This runs counter to claims that short-term rentals help homeowners make ends meet in their own homes. Lee found that evictions increased in areas with the most short-term rentals. Such housing displacement causes middle-income renters to lower-cost areas, leading to gentrification of those areas due to housing shortages. Finally, Lee posits that those neighborhoods with high density of short-term rentals, where many people have been displaced, leads to rapid gentrification in adjacent neighborhoods, which are mostly lower-income. Lee offers a number of suggestions to combat the effects of short-term rentals. It is suggested to create an affordable housing fund from additional fees attached to short-term rentals. Such fees could fund the construction housing units annually. Regulations could also be passed in regard to short-term rentals. An outright ban is an option, although Lee argues it may not pass the Penn Central Test for regulatory takings. Another option is a 1-year requirement of homeowners to occupy the property before listing it on a short-term rental platform. While this may limit price increases, it too may fail the Penn Central Test, under the investor expectations portion. Permits to restrict the density of shortterm rentals are a viable option. However, such a regulation may force short-term rentals to surrounding areas, increasing the pace of gentrification. Inclusionary zoning could help increase the number of affordable units by mandating a percentage of units in a building be 9 Darryll W. Wolnik The Short-Term Rental Effect affordable. Inclusionary Zoning might be considered an exaction in this case, as it may be lacking in proportionality to affordability and public safety. Finally, the city could regulate the number of nights a short-term rental can be rented per year. However, this too may fail the Penn Central Test under the investor expectations test. In Boston, Horn & Merante (2017) explored how short-term rentals effect the rental market. Their study of the market found that the more short-term rentals there are, the more housing costs increase. An increase of one standard deviation of short-term rental density leads to a .4% increase in rents. For those census tracts with the highest density of short-term rentals, there was an increase in the cost of rents of 3.1%. Taking Boston’s mean monthly rent of $2,972 into account, this leads to a $93 increase in monthly rents. However, these effects are enhanced by the types of listing (IE additional bedrooms and bathrooms). Effects on rental housing availability are even more pronounced. The same increase in density of short-term rentals leads to a 5.9% decrease in available rental housing. Similarly, these effects are different based upon bedrooms, bathroom, and other identifying characteristics. Across the Atlantic in Berlin, short-term rentals were studied in terms of their impact on the rental market for flats when those short-term rentals are whole-house year-round accommodations. Schafer & Braun (2016) found 5,555 of these units across all of Berlin, accounting for only .3% of the total housing stock. However, an analysis of the dispersion of short-term rentals showed that a more significant concentration could be found in the five central tourist neighborhoods of downtown Berlin. In these neighborhoods, whole-house yearround short-term rentals made up between 3.6% and 7% of the entire housing market. 61% of those units were operated or listed by hosts with multiple listings. Some of these hosts were found to have up to 11 listings in a single neighborhood. When removing neighborhood barriers, hosts were found to have up to 22 listings. Schafer & Braun’s analysis showed these five neighborhoods to be the biggest short-term rental markets. These neighborhoods shared some common traits beyond physical location or attractions. In these neighborhoods there was a higher proportion of rentals than in other Berlin neighborhoods. In addition, the five neighborhoods studied displayed strong rental growth rates. Schafer & Braun concluded that while short-term rentals may not affect the housing stock or rental rates at the city level, they certainly have an impact at the neighborhood level. Just a few hundred miles south, in Spain, Cocola-Grant (2016) explored how short-term rentals, also known in Spain as holiday rentals, affect the market in tourist cities. Cocola-Grant explores this phenomenon in Barcelona and argues that short-term rentals (also called holiday rentals in Europe) are a method of gentrification; one that happens much faster than traditional gentrification. It was found the majority of short-term rental owners in Barcelona were 10 Darryll W. Wolnik The Short-Term Rental Effect investors who did not live in the unit, instead renting it out as a short-term rental year-round. These rentals tend to be concentrated in central and historic areas. In the neighborhood of Gotic, which contains 16.8% of the population of the Ciutat Vella District, 1 out of 6 apartments were listed on Airbnb. Ciutat Vella contains 9.6% of the 14,539 Airbnb listings. The high number of listings in these areas has caused exclusionary displacement, which occurs when tenants are excluded from renting. Tenants in this case are excluded from renting by the conversion of long-term rentals to short-term rentals. This exclusion has two effects; it forces people from their communities and it raises the cost of housing by removing housing stock while simultaneously increasing the number of those without housing. Those who are not forced from their homes by landlords in this manner face displacement pressure from shortterm rentals. Noise, density or rentals, and transients are some of the pressure that cause voluntary displacement. Those people who leave voluntarily and who own their residence are forced to sell. However, due to the rising prices, only investors can afford to purchase these residences. Investors purchase these units to convert to year-round short-term rentals, and the result is the displacement of an entire community and the creation of a tourist district. DiNatale et al. (2018) shifted focus from large tourist cities to small towns in the western United States, in this case Oregon. 237 cities with less than 100,000 residents, all in Oregon, were studied for effects from short-term rentals. In these cities, there are roughly 8,000 Airbnb short-term rentals, constituting roughly 44% of the total listings in Oregon. Di Natale et al found that short-term rentals accounted for more than 5% of total housing stock in only 16 of the 237 cities. In studying these cities, it was found there was, on the surface, no correlation between short-term rentals and demographics (shrinking/growing places, etc.). In these small cities, 78% of short-term rental hosts listed only 1 unit, however 70% list an entire home. These listings potentially remove housing from the housing market. In these cities, U.S. Census information showed an increase in seasonal vacancies. DiNatale et al suggests these points to strain on long-term supply in those cities with population growth. Effects on a national level were explored by Barron et al (2018) in their study The Sharing Economy and Housing Affordability: Evidence from Airbnb, Barron et al took data from the entire United States to determine effects of short-term rentals on housing markets. Airbnb listings were found to be positively associated with both home prices and rental rates, though this study did not differentiate between whole-home listings and shared home listings, nor did it differentiate between full-time listings and part-time listings. Barron et al explored how owner-occupancy rates in zip codes interacted with home prices and short-term rentals. Using the median owner-occupancy rate of 72%, a 1% increase in Airbnb lead to a .018% increase in rental rates and a .026% increase in home prices. Those zip codes with 56% owner-occupancy (25th percentile) showed a .024 increase in rental rates and a .037% increase in home prices 11 Darryll W. Wolnik The Short-Term Rental Effect when Airbnb listings increased 1%. Finally, when Airbnb listings increased 1%, those homes in zip codes with 82% owner-occupancy (75th percentile) saw rental rates increase .014% and home prices increase .019%. Therefore, it is found that Airbnb listings cause both rental rates and home prices to increase in those zip codes with lower owner-occupancy rates. Barron et al noted, however, that there was no association between vacancy rates in core-based statistical areas (CBSA) and Airbnb listings. Furthermore, seasonal vacancy rates in a CBSA is positively associated with Airbnb’s and negatively associated with vacant for rent and sale homes. Aside from strictly economic effects, there also appear to be some demographic and socioeconomic effects from short-term rentals. Wachsmuth & Weisler (2018) explore how short-term rentals are affecting the makeup of neighborhoods. Short-term rentals are seen by some researchers as a new mode of gentrification. These rentals have effectively created a new rent gap and increased the speed at which redevelopment and gentrification takes place. Traditionally, as land values and rents drop, they get low enough to attract investment from developers. These developers see the potential rent in the area and choose to invest to reap the benefits. Short-term rentals change this dynamic by eliminating both the time taken to redevelop and the money required to do so. Additionally, property owners see the increased rental rates which short-term rentals bring and elect to redevelop their properties from longterm to short-term rentals. The demand for these rentals is found to be higher in areas located near central business districts and other high amenity areas. Interestingly, Wachsmuth & Weisler found poor demand for short-term rentals in not just poor areas, but also culturally heterogeneous areas, mostly white middle class areas. In New York’s most desirable areas, there is significant economic incentive to flip properties from long to short-term rentals. Some of these neighborhoods have a median monthly income for short-term rentals of more than 300% above the income from long-term rentals. These neighborhoods also have the highest proportion of short-term rentals in relation to both total housing and vacant for-rent housing. Housing in some neighborhoods were comprised of over 3% short-term rentals. In those neighborhoods, and of those houses vacant and for rent, upwards of 60% of those available rentals were wholehouse short-term rentals. Wachsmuth & Weisler came to the conclusion that short-term rentals were increasing housing costs in New York City while simultaneously reducing the stock of available hosing. 12 Darryll W. Wolnik The Short-Term Rental Effect Strict Regulation of STRs and potential issues with such regulations As evidenced by the body of research explored above, short-term rentals appear to have some manner of effect on communities. These affects are wide-ranging, from economic to demographic. With this in mind, it is clear that regulations are needed to reign in short-term rentals and help to lessen their effect on communities, while still allowing benefits to be realized. A knee-jerk reaction for municipalities might be heavy regulation, or even complete prohibition, of short-term rentals. There is a growing body of research that determines this to be a poor decision that leads to economic loss and litigation against the municipality. An interesting approach is one involving the Coase Theorem. According to the Coase Theorem, property rights can form a basis for private arbitration and compensation over externalities without the need for government intervention. Gurran et al (2017) found that these externalities, however, create quite the problem. Because short-term rentals are a property rights issue, it is hard to say when one person’s right to enjoyment of their property infringes significantly on another person’s right to their own quiet enjoyment of private property. Gurran et al state that while some externalities such as noise can be mitigated and bargained over at the local level, there is discomfort in dealing with such matters at a personal level. Therefore, it is argued that laws must be created to not only define the externalities and nuisances and set limits, but also to provide a method of filing a complaint. Such limits might include a cap on the number of nights rented or a limit on density of short-term rentals. These items must be addressed before any arbitration and compensation system can be implemented. News stories abound regarding cities and states attempting to work with short-term rental platforms such as Airbnb. New York state even made an attempt to sue Airbnb for some of their records relating to operators in New York City. Although the suit was dismissed, it forced Airbnb to rethink their strategy and directly led to the platform voluntarily sharing some data on certain operators. Tuttle (2018) advocated for working with sharing platforms such as Airbnb to obtain such data on a voluntary nature in order to assist in solving many of the issues that short-term rentals bring. Through a combination of well-thought-out regulations and cooperation with platforms, local short-term rental ordinances can be more effective in the long run. These local ordinances should avoid overburdening potential short-term rental operators. Overbearing or complicated ordinances are shown to lead to a lower number of short-term rentals operating with a permit in relation to those operating without a permit. Such ordinances drive homeowners to the short-term rental “black market” by making the risk of being caught worth the reward of operating without jumping through the extensive hoops the government has created for licensing. Tuttle further argues that regulations pertaining to 13 Darryll W. Wolnik The Short-Term Rental Effect short-term rentals do not constitute a regulatory taking. In fact, these regulations serve a legitimate public interest by protecting the health, safety, and welfare of citizens. Kim et al (2017) provide an excellent evidentiary case on the poor performance of strict regulations. Anna Maria Island in Florida presented a unique opportunity for researchers. Home to three separate yet homogenous cities separated from the mainland, Kim et al were able to observe three distinct sets of regulations for short-term rentals. It was found that more stringent regulations are more likely to cause the share of owner-occupied residence to increase in low-density neighborhoods than in high-density neighborhoods. In terms of home values, these regulations were more likely to increase home values in high-density neighborhoods than they were to decrease home values in low density. In fact, Kim et al found that home values increased in area with a high density of short-term rentals. This is shown in Holmes Beach, one of the municipalities on Anna Maria Island. Holmes Beach outlawed rentals of less than 30 days in low-density residential neighborhoods and 7 days in high-density residential area. The ordinance had the effect of decreasing home values by 15% in low-density areas while subsequently reducing the share of non-resident owners. Kim et al concluded that zoning laws restricting short-term rentals are inefficient. Legally, there are issues with outright bans. Jefferson-Jones (2015b) outlines some of these issues. She infers the operation of short-term rentals is viewed by some as part of the fundamental rights of a property owner. In essence, this entitlement is a stick in the property rights bundle held by a property owner. By restricting short-term rentals, governments could be engaging in a regulatory taking. Jefferson-Jones (2015b) refers to Penn Central v NYC when determining whether a regulatory taking has occurred. Five categories of short-term rental restrictions are identified by Jefferson-Jones (2015b); full-prohibitions, quantitative restrictions, proximity restrictions, operational restrictions, and licensing requirements. The character of these restrictions must be taken into account when they are implemented. Municipalities must take into account investment-backed expectations. Owners that are able to show actual intent and steps taken to operate a short-term rental. Those owners who have previously rented their properties as a short-term rental may be able to argue that prohibitions are a regulatory taking. Finally, operators of short-term rentals must prove diminution of their property due to prohibitions on short-term rentals. Beyond the Penn Central Test, restrictions on short-term rentals could be an inverse condemnation. In this case, the government enacts a regulation that impacts the right to operate a short-term rental by taking property or impacting property rights without utilizing the actual condemnation process. Finally, Jefferson-Jones argues that restrictions such as occupational limits and inspections creates barriers to entry and leads to the establishment of a black market. 14 Darryll W. Wolnik The Short-Term Rental Effect How to Create Good Regulations One of the keys to successfully regulating short-term rentals is the regulation itself. A poorly written regulation can have far reaching implications. Regulations that ignore prior case law such as Penn Central subject themselves to intensive scrutiny and potential litigation. Poorly written regulations may even make it impossible to enforce those same regulations by way of failing to properly define key terms, thereby creating a situation in which short-term rentals are nebulously-defined. Poorly-written ordinances relating to short-term rentals can indeed have far-reaching legal implications for cities. Cory Scanlon’s 2017 research Re-zoning the sharing economy: Municipal authority to regulate short-term rentals of real property, identifies three types of short-term rentals; room rental / home sharing, whole-house rental on occasion, and full-time wholehouse rentals. Of these rentals, only whole-house year-round rentals have the potential to impact the housing market. Potential ordinances must identify and differentiate between these three types of rentals. By taking into account these categories and their varying effects, ordinances can be more viable in court. In addition, these ordinances must be related to the health, safety, and welfare of citizens. Any potential ordinance must avoid regulation of person behavior, such as “bedtimes” for residents and limits on the number of people who can occupy. These regulations could be construed as an unconstitutional taking because they deprive homeowners of beneficial use of land, and might violate the Due Process Clause by attempting to regulate personal conduct. By applying these and other regulations to currently-operating short-term rentals, jurisdictions risk a regulatory taking. In order to clear up confusion relating to short-term rentals and their relationship to zoning regulations, the type of use must be clearly called out and defined in the zoning code. This includes definitions such as “singlefamily dwelling”, “family”, and “short-term rental”. Taking these points into account is a crucial part of creating an effective and legally-defensible short-term rental ordinance. In New York City, James A. Allen found a 2015 report stating that releasing short-term rentals back into the housing market would increase the number of rental units by 10%. As a result, rental vacancy rates would also rise by 4%. Another report, published in 2014, found that many short-term rentals are located in gentrifying areas of New York City, and are used solely as yearround whole-house short-term rentals. Allen’s Disrupting Affordable Housing: Regulating Airbnb and Other Short-Term Rental Housing in New York City (2017) proposes a number of fixes for these and other effects of short-term rentals on the New York City housing market. These fixes are regulatory in nature and require well-written and well-thought-out ordinances. The one host, one listing policy is a measure which would bar individuals from offering more than one property for rent at any given time. Of course, this solution requires cooperation 15 Darryll W. Wolnik The Short-Term Rental Effect from Airbnb to enforce. This data sharing is of the utmost importance, as many regulations cannot be effective without cooperating from Airbnb, or other companies. In addition, a cap on the number of rented nights could be instituted. This would prevent owners from renting their property in excess of the mandated number of nights. In some areas, a total ban could be enacted. This would be best in those neighborhoods or districts where housing is already tight and the community is vulnerable to housing cost fluctuations. Such an ordinance could effectively protect not just vulnerable populations, but also the housing market. Finally, licensing and taxation could be implemented to defray the cost of enforcement and administration and fund employees or a division whose sole responsibility it is to keep track of short-term rentals. Another study focusing on New York City by Coles et al (2017) explored Airbnb usage across New York City neighborhoods. Coles et al wanted to find a regulatory solution to the issues. What Coles et al found was that as usage grows over time, the listings become more dispersed. This leads to a decentralization of both the benefits and burdens of short-term rentals As distance from the central location increases (in the case of this study, the central point was Manhattan), short-term rental prices tend to decrease However as distance from the central district increases, the rental rates for short-term rentals decline more slowly than that of longterm rentals. This led Coles et al to deduce that commute time is much less important for short-term rental tenants. Despite the gradual spread of short-term rentals, listings are still more dense near central locations; in this case Manhattan. However, this spread causes the number of listings in low-income districts near the central location to increase. Coles et al found that these districts in particular features more private rooms than whole houses. Along those same lines, it was found that short-term rentals were most profitable in lower and uppermiddle income neighborhoods. The authors found that a few regulations may help control the spread of short-term rentals and inhibit their negative effects. These include some type of ban on particular properties of types of listings, caps on number of rental nights, caps on the number of short-term rentals, and localized regulation. Regulations are necessary for controlling the proliferation of short-term rentals. Pearce (2016) in The Search of a Long-Term Solution to Short-Term Rentals: The Rise of Airbnb and the Sharing Economy goes beyond simply stating regulations might be necessary; he argues they are absolutely necessary. Without regulations, problems will arise. These problems include the conversion of residential properties to what are effectively commercial properties in wholehouse year-round short-term rentals. To combat this conversion potential ordinances must clearly delineate the line between residential, commercial, and hotel properties with explicit “as of right” uses or non-permitted use. As part of this differentiation, the definition of a shortterm rental is absolutely necessary. Absent this definition, effective regulation of short-term 16 Darryll W. Wolnik The Short-Term Rental Effect rentals and when they convert a property to commercial use is impossible. These regulations would benefit from the inclusion of clauses requiring insurance and methods for redress in the case of neighboring property damage. These ordinances require one thing; cooperation from short-term rental platforms. Even if the above advice is taken into account, issues can still arise. Often, policymakers search for the best practice is dealing with a certain issue, especially one as controversial relatively unknown as short-term rentals. In a study of short-term rentals in North Carolina, Walker (2018) found no clear best practice for regulating short-term rentals. A potential cause is the wide variance in local zoning laws, lodging ordinances, and other land-use and business laws. There is an absence of state laws governing these rentals in North Carolina, with the state government deferring to local jurisdictions because of the regional variances within the state. Charlotte, for example, is a fast-growing city with no regulations on short-term rentals while Asheville, a mountain town and tourist destination, restricts short-term rentals geographically and enlists 3rd party help with identifying those noncompliant rentals. Thomas reasons that, because of the varying types of cities and towns within North Carolina, state-level regulations would be incompatible with all cities. Covenants, Conditions, & Restrictions (CC&Rs) are the most effective method of regulating short-term rentals at the neighborhood level, mostly due to the fact CC&Rs have the legal authority to explicitly deny them. Whatever the method of regulation, Thomas argues they must be clear and easy to understand, otherwise homeowners will simply ignore them. A History of Short-Term Rental Law in Sandy City Sandy City is located in southeast Salt Lake County, along the Interstate 15 corridor and approximately fifteen miles from Downtown Salt Lake City and Salt Lake City International Airport. Nestled along the Wasatch Mountains, the city climbs upwards towards the mountains. Situated at the mouth of Little Cottonwood Canyon, the city acts as a gateway to natural areas and world-famous ski resorts Alta and Snowbird. Sandy City lacks the hotels and resorts that support widespread tourism. To fill this void, many homeowners and investors began offering their homes as short-term rentals, commonly known at the time as “ski rentals”. These rentals, which began showing up in the 80’s and 90’s, acted as de-facto hotels, often hosting large parties and families during ski season. In some cases, the homeowners never resided at the residence, creating what was essentially a commercial hotel 17 Darryll W. Wolnik The Short-Term Rental Effect property. In the mid 90’s, complaints began surfacing from those residents that lived near these ski rentals. In December 1995, the Sandy City Community Development Department interpreted the code as prohibiting short-term rentals. The department reasoned that, even though short-term rentals were not explicitly a non-permitted use in residential zones in question, that the department could not permit them based on their not being explicitly permitted. The city moved to ban short-term rentals based on this determination, finding that the operators of these rentals had no legal right to operate them, regardless of the timeframe. Short-term rental operators Brown, Cloward, and Bowen filed an appeal of the decision through the Board of Adjustment, alleging an error in staff interpretation of the code. The Sandy City Board of Adjustment found in favor of the city. Brown, Cloward, and Bowen filed an appeal with the District Court. The court upheld the board’s determination. Brown, Cloward, and Bowen appealed the decision to the Utah Court of Appeals. The court reversed, ruling in favor of the appellants. The decision had a few points of note that pertain to short-term rentals laws and policy. First, the court determined that a city cannot limit a rental period by an otherwise permitted occupant in an otherwise permitted structure without explicitly stating such limitation in the code. Second, and more importantly, the court found that short-term rentals can only be determined as not a permitted use if listed as such in city ordinance. While the court agreed that cities had the right to not permit short-term rentals under the auspices of health, safety, and welfare, Sandy City had not expressly listed short-term rentals as “not permitted”. Shortly after the Court of Appeals decision, Sandy City passed an ordinance prohibiting shortterm rentals. The existing “ski rentals” were allowed to continue operating as a legal nonconforming use with no amortization period. These rentals would be allowed to continue until the owners abandoned them. In the 2010’s, short-term rentals again became a popular topic of debate. With the emergence of Airbnb as a simple platform for homeowners to rent space, these rentals began to pop up across the country. Sandy City was no exception to this. Due to its geographic location at the mouth of the Little Cottonwood Canyon, and proximity to ski resorts and, to a lesser extent outdoor recreation, the short-term rental market exploded. By 2017, the Sandy City Community Development Department estimated there were over 250 short-term rentals spread across the city. All of these rentals were operating illegally, per the ordinance passed after the “ski rental” court case. However, Sandy City had made the decision to not actively enforce; instead the city investigated on a complaint-basis only. The reasoning was two-fold: 18 Darryll W. Wolnik The Short-Term Rental Effect first and foremost, the city only had four code enforcement officers to cover 22 square miles and 100,000 residents; the second problem being that enforcement would be seen as very unpopular and would have political implications. This is due to cultural and political issues in the City dating decades before and will not be explored here. Current Legislation In 2017, Utah State Representative John Knotwell began creating and gathering support for a bill that would make it illegal for cities to ban short-term rentals. In an interview with Representative Knotwell in February 2019, he described the tipping point that drove his desire to write and pass such legislation. Representative Knotwell heard about issues between St. George, UT and short-term rental operators the year before his 2017 legislation, in 2016. St. George City, located in southwestern Utah, is situated near numerous state parks, recreation areas, and Zion and Bryce Canyon National Parks. Much like Sandy City, St. George saw enormous growth in the number of short-term rentals, and make the decision to restrict them to certain zones, amongst other regulations. In 2018, St. George City began citing operators who were out of code compliance and burdening them with enormous fees, causing quite the media and public stir. These events inspired Representative Knotwell to begin drafting his legislation. In the meantime, he began a sort of speaking tour, visiting various Utah cities and speaking at council meetings. He made one such stop at the Sandy City and spoke to City Council on March 21, 2017. There, he made the case for cities like Sandy to pass legislation allowing short term rentals, lest they be forced to by his impending legislation. This drove Sandy City Council to act on short-term rental ordinances. Once Representative Knotwell’s legislation made it to the floor, it was hotly debated. The bill, known as HB253, was hotly debated. It went through numerous changes on the house floor, in the senate, and during senate readings. The bill as passed was not what Representative Knotwell wanted. Rather than preventing cities from banning short-term rentals, it only prevented cities from enforcing bans through rental listings. In effect, cities could no longer find a listing, find the address, and cite the owner. Cities now had to investigate and gather evidence before citing. In response to Representative Knotwell’s visit, and the passing of his legislation just days later on March 24, Sandy City Council Directed the Council Analysts Office and the Community Development Department to begin researching local legislation on short-term rentals from 19 Darryll W. Wolnik The Short-Term Rental Effect around the country. After more than a year of research and writing, Council adopted new short-term rental ordinances. These ordinances included residency and ownership restrictions, permit limits based on geographical area, and limits on the number of nights a property can be rented. During the month of October, those desiring a permit could turn in their completed application and be placed in a lottery, should there be any areas where the permit limit was met. On October 22, permitting was opened up to all residents. Analysis of Sandy City’s Short-Term Rental Ordinance Utilizing the extensive literature review above, we can determine how well Sandy City’s shortterm rental ordinances are working. More importantly, we can identify shortfalls and legal issues, if any are present. Sandy’s ordinances do some things well. There are well-thought-out requirements and restrictions that balance property rights of rental operators with the rights of neighboring property owners. Conversely, there are portions of the ordinance that make little sense and seek to needlessly encumber applicants with obtaining unnecessary documentation. The ordinance requires the transfer deed for the property in question. While the purpose of this is to verify homeownership by the applicant, it is ultimately unnecessary for the City to require the applicant provide this paperwork. The transfer deed itself elicits confusion from most, as the applicant often have no idea what the document is and where to get it. City staff finds themselves taking inordinate amounts of time explaining what the document is, what it looks like and contains, and where to get it. The City could solve this by pulling the document, or the information provided on it, directly from Salt Lake County records. These records are free for local governments to pull or view, but cost $10 or more for private citizens. In addition, citizens must go in person to the county building, which can be up to an hour or more away. Operating on “bankers’ hours”, it can be difficult for citizens to visit the county building without taking time away from work or their personal life. Other paperwork requires a significant amount of legwork, including physical travel. Still more documentation is time-consuming, both to wait for and to put together for the application. This applies to the City’s requirement that applicants obtain a state sales tax ID number. This ID can be obtained online, however there are numerous problems City staff identified with that method. The system takes up to 14 days to mail the tax ID number out to applicants. Because applicants may be on a time crunch to obtain a valuable permit, waiting two or more weeks could very well cause valuable permits to be taken by other applicants, thus forcing these people onto the waiting list. Some applicants would rather test the “black market” and operate unpermitted instead of taking the chance of ending up on the waiting list, thus informing the 20 Darryll W. Wolnik The Short-Term Rental Effect city of their address and making their unpermitted rental easier to locate for citation. On top of the waiting period, the sales tax ID system asks a series of questions to identify which tax ID type the applicant requires. Early in the process, many Sandy City applicants ended up with the incorrect tax ID type due to confusing and misleading questions on the sales tax ID questionnaire. An incorrect tax ID cost time and created confusion and road-blocks for applicants. These issues led City staff to encourage applicants to physically visit the sales tax ID office. This office, like the county office, operates on “bankers’ hours” and similarly saddles applicants with missed time at work or in their personal lives. The sales tax ID is unnecessary for nearly all applicants, as the vast majority (if not all of them) list their units on Airbnb or similar platforms, who happen to collect all applicable taxes and remit them on your behalf. Therefore, the process could be made easier and less cumbersome by only requiring applicants provide proof taxes have been collected and remitted, whether by them or by the listing service. One glaring item missing from the ordinances is definitions. While Pearce (2016) advocated for definitions as an integral part of enforceable ordinances, Sandy City has not provided one for a short-term rental. The ordinance does preclude certain situations and establishments from being identified as a short-term rental, namely residential leases of 30 days or more, and licensed bed & breakfasts, hotels, and motels. Sandy City’s ordinances, as stated earlier, do some things well. As outlined by Scanlon (2017), the need to identify types of rentals is paramount. While the ordinance does not call out whole-house rentals as suggested by Scanlon and others, it does stipulate a maximum timeframe in which the home may be rented on a short-term basis. This, coupled with requirements that the property be owned by the primary occupant (who is an individual and not a corporation or LLC) who uses the home as the primary residence, prevents whole-house year-round short-term rentals from being approved. Sandy City’s ordinances provide a land-use matrix for both residential and commercial/industrial zones. “Residential short-term rentals” are listed on both tables, and denoted under all zones as requiring a special use permit. This prevents the issue with Brown, Cloward, & Bowen from occurring again, as the use is now listed for all zones. Other positives of the Sandy City ordinance include a cap on the number of persons that can occupy a short-term rental at any given time. Occupancy is capped at 4 unrelated or 8 related persons. While there is certainly an issue of enforceability, this provides some insurance against the loud parties that were the basis for complaints in the 90’s. Short-term rental 21 Darryll W. Wolnik The Short-Term Rental Effect operators are barred from entering into more than one lease at a time. This regulation has two purposes; first to keep an operator from renting to more than one group and creating a defacto hotel property, and second to keep an operator from having a long-term renter and a short-term renter. Finally, Sandy City’s short-term rental ordinance deals well with dispersion, density, and permit caps. Utilizing a pre-existing system of 30 geographical communities, policymakers developed a system for allocating specific numbers of permits to those areas. Each community was given a base of two permits. Then, for every 100 single-family homes, an additional permit was granted. Such a method takes cues from Coles et al. (2017) by attempting to decentralize rentals from central draws and disperse them throughout the city. However, the ordinance really misses an opportunity to control the density of short-term rentals. As shown by Kim et al. (2017), clustering of short-term rentals can have significant effects on the immediate area. Nothing in Sandy City ordinances prevents short-term rentals form being next to one another. This issue presents itself on one street near Little Cottonwood Canyon, where 3 rentals are grouped in four homes on the same side of a dead-end street. On the whole, Sandy City’s ordinances are a step in the right direction. The ordinances attempt to mitigate hotelization of neighborhoods through owner-occupancy and limits on the number of nights a home can be rented annually. Density of rentals will need to be addressed moving forward, as will the overabundance of paperwork required of applicants. However, this ordinance provides a good starting point and is a respectable first attempt at a short-term rental ordinance. Short-Term Rental Analysis Before we analyze short-term rental units, the issue of permitting must be addressed. There are currently around 60 permitted short-term rentals in Sandy City. This is in stark contrast to the nearly 300 listed on various short-term rental platforms. Such a disparity makes conducting any meaningful analysis problematic. To remedy this, analysis and interpretation are broken into two parts. First permitted units will be analyzed. These units have the most complete information, including actual address. Such depth of information means short-term rentals in this category can be examined on a microscopic level and even subjected to statistical quantitative analysis in programs like SPSS. Unpermitted units however provide very little information. Their exact locations are hidden by 22 Darryll W. Wolnik The Short-Term Rental Effect the platform, preventing robust analysis. The most accurate geographic information is obtained from Airdna.co, a short-term rental research website used by researchers across the world. Even with this tool, only zip code can be obtained. However, this still allows some manner of analysis based upon geographical area. Analysis of Permitted Units In order to gauge the potential effect of short-term rentals on rental housing costs and housing availability, numerous GIS mapping methods were used. The most logical method of analysis was taken from Horn & Merante’s 2017 study of short-term rental impacts on Boston, MA. In their study, the authors used density as a way to help identify areas of impact. Higher densities in Zip Codes were found to cause greater impact to rental costs. Zip codes were chosen because they provide the most accurate rental housing values from Zillow. Some information can be gleaned from spatial analysis using ArcMap. By displaying all shortterm rentals, it is clear there are some geospatial trends. Just as Zip Codes 84092 and 84093 offer up key housing information related to short-term rentals, these Zip Codes also contain 46 out of 59, or 78%, of all rentals. Such a distribution of short-term rentals is not unexpected, as the majority of residential land is located in this area, which is east of 1300 East. Such a distinction would lead one to assume there is some connection between the proliferation of short-term rentals and additional metrics. One such is the idea that elevation plays some role in whether or not there are more short-term rentals in one area over another. This is somewhat related to Kim et al.’s work on clustering. While there has been no specific research on elevation in reference to short-term rentals, a rational predication is that elevation would have at least some effect. In research unrelated to short-term rentals, Muller et al. (2008) identified elevation and access to viewscapes as important for affluent people in selecting first and second homes. Using this information, permitted short-term rentals were mapped in ArcMap with a contour line overlay. Figure 2 shows contour lines at 200’ intervals with short-term rental locations. This map clearly shows that there are few short-term rentals at the highest elevations and the lowest elevations. The majority appear to be clustered in the middle elevations. 23 Darryll W. Wolnik The Short-Term Rental Effect Figure 1: Elevation Analysis The next geospatial analysis that can be done is the proximity to commercial areas. In a larger study, individual businesses could be recorded and broken out into categories. Bars and Restaurants are, after all, a different commercial amenity that grocery stores and retail establishments. For the purpose of this analysis, these categories are all listed under commercial. Analysis provided some interesting data points. Of all 59 short-term rentals, only 11 are within ¼ mile of a commercial zone. Of those, 7 rentals are west of 1300 South. This majority represents the minority area of short-term rental prevalence. ¼ mile was used as the metric for the simple fact that this is the distance used for walkability in most U.S. research studies (Yang & Diez-Roux, 2012). Data could be interpreted to mean one of two things; either proximity to commercial areas do not factor into the establishment of short-term rentals, or operators assume that renters will drive rather than walk anywhere. 24 Darryll W. Wolnik The Short-Term Rental Effect Figure 2: Proximity to Commercial Zones With proximity to commercial areas ruled out, the next logical amenity is recreation. In a 2016 study, Cocola-Grant explored the effects of tourism on areas with short-term rentals. CocolaGrant found that access to tourist destinations and amenities drove the proliferation of shortterm rentals. Utilizing these conclusions, short-term rentals in Sandy City were compared to a number of tourist amenities. ArcMap was used to determine distance to two three types of outdoor recreation: trailheads, parks, and golf courses. Parks, as used in this study, are county and local parks only. State parks and federal public lands were not used. State parks were eliminated because there are simply no state parks in the area. Federal public lands were eliminated because of the general proximity of the study area to vast tracts of federal lands, as the entire eastern border of the study area is federally owned public lands. Golf courses include both private and public golf courses, operating under the assumption that even private courses offer some type of benefit (IE aesthetic or size of home). 25 Darryll W. Wolnik The Short-Term Rental Effect If there is one place people are willing to walk, it is a park or open space. Geospatial analysis using ArcMap showed 32 out of 59 rental units were within ¼ mile of a park or open space. This accounts for just over half of all short-term rentals (54%). This is a potentially significant sign, although it may be a red herring due to the location of parks throughout the study area. More in-depth research in this area is required to approach a conclusion. Trail heads represent another valuable outdoor recreation amenity. Spatial analysis showed only 2 short-term rentals within ¼ mile of any trail heads. When substituting trails themselves for trail heads, that number jumps to 14. Trail cannot be accessed from just any point, but there are often multiple access points to a trail outside of the trail head. Unfortunately, the GIS data does not account for this. Finally, only 7 rentals are within ¼ mile of any golf course. Overall, outdoor recreation amenities appear to have some relationship to short-term rental locations. Significance is skewed heavily towards parks. This proximity to parks and recreation amenities, the distance from commercial areas, and the access to Little Cottonwood Canyon could be connected by a single factor: home value. Those homes in close proximity to recreation amenities and Little Cottonwood Canyon, and with significant distance from busy commercial areas, may have higher values by virtue of these things. These areas are also more desirable to live, making them more attractive to renters as short-term rentals. Therefore, the ability to operate a short-term rental increases the value further by adding that stick to the bundle of property rights. Figure 3: Proximity to Recreation Resources 26 Darryll W. Wolnik The Short-Term Rental Effect Taking a que from Kim et al.’s 2017 study of short-term rentals in Florida, short-term rental properties were examined for clustering. Permitted short-term rentals in Sandy City were geocoded by address and mapped in relation to one another. A 500-foot radius was set as a general buffer to account for impacts. This was done because Kim et al.’s study showed higher densities accounted for higher local impacts from short-term rentals. A majority of Sandy City single-family lots are under 10,000 square feet by zoning code, so this number made sense as a general metric. These short-term rentals were processed as a heat map using this 500-foot radius. The results showed distinct clustering in 3 areas, with minor clustering in 3 other areas. According to Kim et al., the impact in these areas may be significantly greater in relation to areas where there is little to no clustering. Analysis of this cluster map against previous maps offers explanation for the clustering at the far east. Those units are at the mouth of Little Cottonwood Canyon, the gateway to natural amenities and the ski resorts Alta and Snowbird. The other clusters, in the center top and center bottom of the map in Figure 4, have no relation to the metrics presented. It is possible these units are in neighborhoods where the average home or lot is larger, but that is unclear from this analysis. Further research into zoning, lot size, and impact from such clustering is suggested. Figure 4: Short-Term Rental Clustering 27 Darryll W. Wolnik The Short-Term Rental Effect What can be inferred from the data as presented is clear. Areas with higher rental values have more short-term rentals. In addition, areas with more seasonal vacancies have more shortterm rentals. It could be at least assumed that the number or density of short-term rentals increases rental values. Finally, with rental rates in the 84092 and 84093 increasing by 3-4% since 2011, it is clear something, potentially short-term rentals, is driving that increase. Analysis of All Units Short-term rentals as a percentage of housing can indicate some things about the local housing market and the impact of short-term rentals. Wachsmuth and Weisler’s 2018 study showed short-term rentals led to a decrease in available housing stock and an increase in rents. To explore this phenomenon in Sandy City, short-term rentals were compared against current housing. The number of overall homes was compared with short-term rental data from Airdna.co. This is an important distinction from other analyses, as this includes both permitted and unpermitted short-term rentals in Sandy City, broken out by Zip Code. The analysis showed short-term rentals comprise nearly ten percent or more of all rental housing in two Zip Codes (84093 and 84092). These same Zip Codes has over 5% of rental units taken up by “whole-house” short-term rentals. These rentals are classified as the rental of an entire house where the owner is absentee and does not live on site. These short-term rentals in particular have a significant effect on the housing market, as they remove rental homes from the market that may have otherwise been rented by those people seeking long-term housing. Interestingly, these same Zip Codes have the lowest percentage of rental units with owneroccupied dwellings. With such a low percentage of rentals, these Zip Codes are even more susceptible to rental units being taken off the market. That is not to say, nevertheless, that even the ability to use part of the home as a short-term rental does not raise home values. Kim et al. (2018) demonstrated that home values tend to increase with the land entitlement that short-term rentals are allowed. This could potentially drive rental values higher, as Wachsmuth & Weisler’s (2018) study showed, short-term rental rates have a potential to be significantly higher on a monthly basis than standard long-term rentals, thereby driving landlords to convert their units to short-term rentals. 28 Darryll W. Wolnik The Short-Term Rental Effect Figure 1: Short-Term Rentals as a Percentage al All Rentals 29 Darryll W. Wolnik The Short-Term Rental Effect Figure 2: Whole House Short-Term Rentals as a Percentage of All Rentals Figure 3: Rentals as a Percentage of All Homes Even without properly permitted units, it is still possible to at least infer a rational relationship between the proliferation of short-term rentals and effects on the housing market and housing tenure. Of particular interest to this study are the two eastern Zip Codes, 84092 and 84093, as these offer up the most significant data points. The first significant relationship is between rental vacancy rates and the number of whole-house short-term rentals. These rates tell two different stories; one of extremely high rental vacancy and one of extremely low rental vacancy. This could be attributed to the unique nature of short-term rentals; are they considered occupied or unoccupied? 84092 has a 2017 rental vacancy rate of nearly 15% while also having over 300 rentals classified for seasonal or occasional use. Conversely Zip Code 84093 has a 2017 rental vacancy rate of less than 1%, an extremely low vacancy rate. At the same time, 84093 has nearly 50 rentals classified as seasonal or occasional use. Perhaps these seemingly opposite data points tell the same story that short-term rentals take up a lot of the rental housing stock. With only 888 renter-occupied units, 84093 experiences a large impact form seasonal rental units. In fact, those seasonal rentals constitute an additional 35% of rental housing stock, while only 9% of 30 Darryll W. Wolnik The Short-Term Rental Effect new dwellings 2013-2018 were built in 84093. This could explain the high rental rates of nearly $1,900 per month. Table 3 shows the increase in what the American Community Survey determines as “rentals for seasonal, recreational, or occasional use”. The meaning here is potentially ambiguous and could represent second homes, ski homes, and short-term rentals. For the purpose of this study, it can be assumed this includes short-term rentals. The table shows the two Zip Codes in question have the highest rate of seasonal use homes, taking the largest number of rental homes off the market. Table 1: Rentals for Seasonal, Recreational, or Occasional Use For Sandy City Zip Codes 84070 84092 84093 84093 2011 91 448 23 0 2012 87 408 24 0 2013 10 416 9 0 2014 13 455 52 25 2015 14 361 53 24 2016 0 324 44 27 2017 0 313 47 23 SOURCE: ACS 5-Year Survey, 2011-2017, Table B25004 Impacts to Sandy City Housing Sandy City, like much of the Wasatch Front, is experiencing a period of unprecedented population growth. Unlike previous growth trends in the area that were driven primarily by Utah’s high fertility rate, recent growth is driven by in-migration from other parts of the country (Gardner Institute, August 2019). In fact, population projections based on Stefan Rayer’s (2008) methods show growth of up to 24% growth in Sandy City and up to 41% in Salt Lake County. This growth, and the booming economy accompanying it, has created certain challenges to municipalities along the Wasatch Front. One of these challenges, the increase in housing costs, relates directly to the short-term rental issue. As evidenced by Horn & Merante in Boston, Lee in Los Angeles, and XXXX in Berlin, the proliferation of short-term rentals, especially in densely populated or tourism service areas, can lead to an increase in housing prices or housing scarcity. In Sandy City Zip Codes up to 1% of all homes are short-term rentals, and up to 10% of all rentals are whole-house short-term rentals. Removal of these units from the long-term housing market can have consequences in terms of housing costs and availability, as evidenced by previously-stated research. 31 Darryll W. Wolnik The Short-Term Rental Effect Table 2: Population Projections For Sandy City and Salt Lake County Study Area 1990 2010 Base Launch Linear Sandy City 75,058 87,461 106,066 Salt Lake County 725,956 1,029,655 1,485,204 2040 Shift Share Exponential Share of Growth 108,742 1,550,740 106,332 1,631,056 Constant Share 110,012 114,740 1,739,257 1,350,805 Source: US Census Bureau The easiest way to deal with a shortage of homes is to encourage the construction of more residential units. Obviously Sandy City does not have the ability to determine what gets built where and when, it can encourage the construction of the highest-density housing units in areas where the zoning and master plan allow. Construction of housing units should also be encouraged in those places where housing prices are the highest, as the value of homes is most likely positively-associated with demand for housing in that area (statistical analysis of this nature is outside of the purview of this paper). Table 3 shows the growth of rental rates in the four zip codes associated with Sandy City between 2011 (when home values and rental rates began to recover from the recession) and 2018, the last whole year for which data was available. Zip codes 84092 and 84093 have homes with the highest rental rates as of 2018. However, it is worth noting that the other two zip codes, 84070 and 84094, saw much greater growth in rental rates during the observation period. Slower growth of rental rates can mean any number of things, and will not be explored here, but it could simply be a reflection of the lower percentage of rentals in the 84092 and 84093, as previously shown in figure 7. Table 3: Average Annual Median Rental Values, 2011-2018 For Sandy City Zip Codes Zip Code 84070 84094 84092 84093 2011 $1,204 $1,244 $1,691 $1,556 2012 $1,220 $1,285 $1,658 $1,529 Source: Zillow Research Data 2013 $1,299 $1,347 $1,755 $1,610 2014 $1,330 $1,376 $1,719 $1,563 2015 $1,384 $1,447 $1,818 $1,704 2016 $1,440 $1,496 $1,924 $1,795 2017 $1,485 $1,551 $1,965 $1,858 2018 $1,540 $1,623 $1,964 $1,877 7-Year growth 27.60% 29.50% 16.40% 21.00% 32 Darryll W. Wolnik The Short-Term Rental Effect Figure 8: Sandy City Median Rent by Census Block Group 33 Darryll W. Wolnik The Short-Term Rental Effect If 84092 and 84093 had the highest rental rates in Sandy City, then it should be assumed those areas have the highest housing demand. Therefore, housing should be built in those areas. An analysis of final built permits for the zip codes associated with Sandy City shows the opposite trend. Since 2012 (the first full year for which data on final completed permits was available) only 661 housing units have been completed in 84092 and 84093, while 2,181 have been completed in 84070 alone. Permit data like this is important to the study of short-term rentals because of the effect short-term rentals have been shown to have on housing markets. If there are a high number of short-term rentals in areas like 84092 and 84093, yet new units are not being built, the expansion of the number of short-term rentals will continue to apply upward pressure to rental costs. In this case, it would appear Sandy City has not done enough to alleviate the high cost of housing in these areas. With short-term rentals removing as much as 10% of the housing stock from these areas, more units must be permitted. As an alternative, regulations must be modified as explained earlier to mitigate the short-term rental effect on rental housing costs and housing availability in general. 2500 2181 2000 1500 1000 0 515 379 500 84070 282 84092 84093 Figure 9: Total Completed Permitted Units, 2013-2018 84094 Table 4: Completed Building Permits in Sandy City By Type of Housing Units Housing Unit Apartment Permits Duplex Permits Condo/Townhome Permits Single Family Permits Annual Permits Source: Sandy City Community Development Department 2013 360 6 11 107 484 2014 438 12 8 67 525 2015 747 0 8 51 806 2016 662 0 0 51 713 2017 391 0 83 49 523 2018 0 4 151 51 241 6-Year Total 2598 22 261 376 3292 34 Darryll W. Wolnik The Short-Term Rental Effect Limitations The limitations of this research have been laid bare in the preceding pages. I have made no attempt to hide them and have done my best to call out those areas where there are hinderances. There are a few that require at least some discussion as to their importance and overall implications for research in this area moving forward. Most glaring is the disconnect between permitted and non-permitted short-term rental units. While this was addressed, it is worth noting again (potential solutions are discussed in the conclusion of this paper). Airbnb is notoriously tight-lipped and protective about individual user data, especially listing data. They do not typically release addresses and owner info, though it has been done for cases in San Francisco and New York in the face of mounting litigation. I have relied on Airdna.co to obtain at least Zip Code level, but this does not lend itself to in-depth analysis, as addresses are not provided. Without being able to geocode addresses of all short-term rentals, it is impossible to explore the true impact on a neighborhood level. With permitted data, addresses can be geocoded and broken down on the census block group level to find out the true level of local impact. Analyses of zoning and lot size, among others, can be done to understand how and why short-term rentals operate more in specific areas. This disconnect between permitted and non-permitted data presents the most significant limitation on any research in this area. Another slightly less significant problem has to do with American Community Survey (ACS) information. ACS estimates are just that; estimates. This becomes problematic when attempting conduct housing research at the census block group level. At such a microscopic level in a less urban area like Sandy City, housing data experiences a significant margin of error. So much so that the data is unusable. In addition to margins of error is the ambiguous nature of some housing questions. Most important to this study is the question regarding rental vacancy on the basis of season, occasional, or recreational use. As stated earlier in this paper, the significant swing in those rates in relation to short-term rentals points to confusion on the part of respondents. The final limitation has more to do with the nature of short-term rentals. These rentals are very hard to track, as stated above. They are even harder to “blame” for any effect on the housing market. The regional housing boom makes it tough to track how significantly short-term rentals affect rental rates and occupancy rates. This limitation, as with the others, will probably be corrected over time as the housing market continues to evolve. 35 Darryll W. Wolnik The Short-Term Rental Effect Conclusion The lasting effect of short-term rentals is at the center of the short-term rental issue in Sandy City. While much can be gleaned from the data as presented, one fact stands out amongst everything; that there are a significant portion of short-term rentals that are not permitted. Before any concrete analysis of impacts can occur, this issue must be addressed. Policy changes are undoubtedly needed to bring short-term rental operators into compliance with the permitting process, as Allen (2018) determined that confusing or harsh regulations lead to lower rates of permitted units. It is clear this process must be changed in some way. Potential future research has been laid out throughout this paper. In conjunction with the above suggestion, a hard inventory of short-term rentals in Sandy City, or anywhere research is done for that matter, is an important start. Once that is complete, simply mirroring what previous researchers have done in other areas of the world would offer up copious amounts of valuable data. Additional research is needed to establish a connection between the number of permitted dwellings built and the trajectory of housing costs. While a connection is inferred in this paper, it is unclear how strong that connection is, or if there is even a connection at all. It must be determined why short-term rentals appear in clusters. There is quite obviously some driving force behind the phenomenon. Survey research of those who stay in short-term rentals might help answer these questions. Beyond that, an analysis of zoning and lot size could potentially offer up key information regarding how and why owners list homes as short-term rentals, and why those same units are booked in terms of frequency and nightly rate. The same goes for overall square footage of the unit. Data of this nature has potential to shed light on the rent gap in these areas and the new gentrification being seen through short-term rentals. Such information would truly offer insight into the changes caused by short-term rentals on the neighborhood level. Sandy City must seriously consider making changes to their short-term rental regulations. As laid out in this paper, there are shortfalls in current regulations. These shortfalls have a hand in facilitating the currently robust black market of short-term rentals. Eliminating confusing and laborious requirements, as well as addressing density issues at the neighborhood level would help to create more effective regulations. Making changes suggested in this paper would potentially bring more units into compliance and help the city create a more effective program. 36 Darryll W. Wolnik The Short-Term Rental Effect References Allen, James A. “Disrupting Affordable Housing: Regulating Airbnb and Other Short-term Rental Hosting in New York City.” Journal of Affordable Housing 26, no.1 (2017): 152-191. 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Yaraghi, Niam, and Shamika Ravi. 2017. “The Current and Future State of the Sharing Economy.” SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3041207. 39 Appendix A: Population Projections Table #: Population Projections For Sandy City and Salt Lake County Study Area Sandy City Salt Lake County 1990 2010 Base Launch 2020 2030 LIN SFT EXP LIN SFT 2040 EXP LIN SFT EXP 75,058 87,461 93,663 93,704 94,411 99,864 99,991 101,914 106,066 106,332 110,012 725,956 1,029,655 1,181,505 1,208,972 1,226,260 1,333,354 1,408,799 1,460,405 1,485,204 1,631,056 1,739,257 Source: US Census Bureau Zip Codes 2000 2010 2020 2030 2040 Base Launch LIN SFT EXP LIN SFT EXP LIN SFT EXP 84070 23,134 24,861 26,588 25,780 26,717 28,315 25,766 28,711 30,042 24,646 30,855 84092 30,219 29,525 28,831 26,584 28,847 28,137 21,015 28,184 27,443 12,307 27,537 84093 25,324 23,130 20,936 18,402 21,126 18,742 10,700 19,296 16,548 (557) 17,624 28,069 27,904 26,000 27,905 27,739 21,706 27,742 27,574 14,758 27,580 303,965,272 359,220,671 365,358,664 371,496,658 414,476,070 434,253,717 454,031,363 469,731,469 512,317,058 554,902,647 84094 28,234 United States 248,709,873 Source: US Census Bureau LNR (Linear) – Same change in population over each period, as a percentage; Good for places growing quickly (Rayer, 2008). SFT (Shift-Share) – Per Rayer (2008), “it is assumed that the average per decade change in each county’s share of the national population observed during the base period will continue throughout the projection horizon”; good for high growth places (Rayer, 2008). COS (Constant Share) – The share of the national population remains constant for each forecast; good for places growing quickly (Rayer 2008). Darryll W. Wolnik The Short-Term Rental Effect Appendix B: Building Permits Annual New Permits for Single Family Homes By Zip Code 7-Year Year 2012 2013 2014 2015 2016 2017 2018 Total 84070 82 61 44 15 15 7 11 235 84092 16 28 16 25 25 34 34 178 84093 1 3 1 4 4 1 5 19 84094 1 15 6 7 7 7 1 44 Annual Permits 100 107 67 51 51 49 51 476 Source: Sandy City Community Development Annual New Permits for Condos and Townhomes By Zip Code Year 84070 84092 84093 84094 Annual Permits 2012 2013 2014 2015 2016 2017 2018 7-Year Total 0 11 8 0 0 67 119 205 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 0 0 6 0 16 32 54 0 11 8 8 0 83 151 261 Source: Sandy City Community Development 41 Darryll W. Wolnik The Short-Term Rental Effect Annual New Permits for Duplexes By Zip Code Year 84070 84092 84093 84094 Annual Permits 2013 2 4 0 0 6 2014 8 4 0 0 12 2015 0 0 0 0 0 2016 0 0 0 0 0 2017 0 0 0 0 0 2018 6-Year Total 2 1 0 1 4 12 9 0 1 22 Source: Sandy City Community Development Annual New Permits for Apartments By Zip Code Year 2013 2014 2015 2016 2017 2018 6-Year Total 84070 282 100 747 394 206 0 1729 84092 0 0 0 72 120 0 192 84093 0 0 0 196 65 0 261 84094 78 338 0 0 0 0 416 Annual Permits 360 438 747 662 391 0 2598 Source: Sandy City Community Development Total Completed Permits For Sandy City Zip Codes Total Permits 2012-2018 84070 2181 84092 379 84093 282 84094 515 Source: Sandy City Community Development 42 Darryll W. Wolnik The Short-Term Rental Effect Appendix C: Short-Term Rentals Number of Permitted STRs In Sandy City Zip Codes Zip Code 84070 84092 84093 84094 Total # of STRs 9 33 14 3 59 Sources: Sandy City Community Development & Airdna.co Overall Number of STRs In Sandy City Zip Codes Zip Code 84070 84092 84093 84094 Total # of STRs 59 96 104 53 312 Sources: Sandy City Community Development & Airdna.co STRs as a Percentage of All Rentals For Sandy City Zip Codes Zip Code 84070 84092 84093 84094 Rental Units 3848 888 833 1950 # of STRs 59 96 104 53 Sources: ACS 2017 5-year Survey & Airdna.co % of Rentals as STRs 1.53% 10.81% 12.48% 2.72% 43 Darryll W. Wolnik The Short-Term Rental Effect Appendix D: Selected Housing Statistics Selected Housing Statistics For Sandy City Zip Codes Zip Code 84070 84092 84093 84094 Total Units 10251 9768 7605 9385 Rental Units 3848 888 833 1950 % Rental Units 39.6% 9.9% 11.3% 21.5% Rental Vacancy Rate 7.3% 14.4% 0.7% 3.2% Source: ACS 2017 5-year Survey Rental Vacancy Statistics For Sandy City Zip Codes 84070 84092 84093 84094 Vacancy Occupied Rate For Rent 3848 7.3% 302 888 14.4% 150 833 0.7% 6 1950 3.2% 68 Vacant For Seasonal, % For Recreational, or Seasonal/Rec/Occ Rented, Unoccupied Occasional Use Use 0 0 0.0% 2 313 35.2% 0 47 5.6% 81 23 1.2% Source: ACS 2017 5-year Survey 44 Darryll W. Wolnik The Short-Term Rental Effect Appendix E: Additional Maps 45 Darryll W. Wolnik The Short-Term Rental Effect 46