Turkey Property is a Wise Buy in the Current Economic Climate

By : Marc Da Silva

Turkey has developed a reputation as a value-for-money destination, helping to boost the country’s popularity as a property investment destination. Spurred by relatively cheap property prices, demand for Turkey property is growing.

Weak Turkish currency
A recent report from the Post Office named Turkey as one of the world’s most affordable places for Brits’ to visit, due to sterling’s strength against the Turkish lira. Yet, the Turkish currency is expected to fall in value in 2009, according to Deloitte Turkey, making already low property prices even more affordable.

“It (the Turkish lira) started the year (2009) relatively weak due to a 200 basis point interest rate cut by the Turkish Central Bank,” says Homes Overseas’ Percy Pound.

Robert Nixon, executive director, Nirvana International, comments: “From a British buyers perspective the purchase of property in Turkey is a wise move in the current economic climate as it is outside the eurozone and therefore your pound goes further.” Turkey, which now attracts around 25 million tourists each year, was last year named number one holiday destination for British tourists. Nonetheless, international visitor numbers to Turkey are expected to rise further this year. Travel association body, ABTA, predicts that Turkey will be one of two "big growth areas" in 2009, along with Egypt. The economy The Turkish economy, which is partly and unsurprisingly reliant on tourism, appears to be well equipped to withstand the current global financial calamity, after recovering from its own crisis in 2001. A levelling up situation - wage inflation, growing prosperity and access to less constrained mortgage finance - is driving greater domestic and international demand for properties in Turkey. Mortgages in Turkey were introduced in 2007, enabling buyers under the age of 75 to borrow up to 80 per cent of the property’s value for a maximum term of 20 years, according to Eric Kaya, director of Cumberland Properties. Mortgage borrowing rates currently start from around 5.8 per cent. Kaya says that the previous inability to obtain mortgages was “stifling demand, preventing people from buying property and holding our (Turkey’s) economy back. The new mortgages that are now available are good news for both Turkish and overseas buyers.” He adds: “Prices of property in Turkey are a lot cheaper than much of the rest of Europe” and this presents “a lot of opportunities for investors to make very good returns from property.” The Turkish Statistical Institute shows that there are now around 73,000 overseas nationals registered with Turkey’s Land Registry, many of who will have benefited from recent capital growth. Property price growth Estate agent, Aston Lloyd, reports that average Turkish property prices appreciated by 7.3 per cent between 2004 and 2008. Given Turkey’s economic strength, combined with a general housing shortage, hopes of joining the European Union and a maturing mortgage market, Turkish property prices should strengthen further moving forward. However, there are signs that property price growth may slow across some parts of the country or even depreciate in the short-term, as the worlds’ economy all but grinds to a halt. Economic caution Despite the country’s seemingly strong economic position, Turkey’s economy will potentially face a tough year in 2009, having made around £51 billion of financial obligations, according to Deloitte Turkey in its Economic Outlook 2008. This means that the country will need to raise money in financial resources to cover a current account deficit and matured debt, according to the report. Consequently, an agreement with the International Monetary Fund will be vital to help produce these funds. Nevertheless, the medium to long-term outlook for Turkey’s economy looks positive, which should in turn benefit the country’s maturing housing market. Turkish news provider Hurriyet estimates that the rapid growth of the country's tourism industry will contribute to a property boom in 2010, while investment banking firm Goldman Sachs estimates that Turkey will become the world’s ninth largest economy by 2050. Where to buy Istanbul With a rapidly growing young population of over 10 million inhabitants, developers are whipping up new residential units across the city to meet growing demand for homes. Prices of property in Istanbul reportedly jumped annually by up to 40 per cent between 2002 and 2005, after a law was introduced, permitting foreign nationals to purchase property in Turkey in their own name. Although capital growth in the city has since slowed, there are signs that prices of Istanbul property will continue to appreciate moving forward, especially as the city will be crowned European Capital of Culture for 2010. Furthermore, some of the greatest rental yields in Turkey can typically be found in Istanbul, with an average rental return of 7.54 per cent currently achievable, according to the Global Property Guide. Nixon says: “The rental market [in Turkey] is very good and being fueled by the continued popularity of Turkey as a summer holiday destination, as well as by local demand, particularly in Istanbul. There is excellent potential for long-term lets to professionals [in Istanbul],” says Nixon. “Such is the confidence in the letting sector that many developers operating in Turkey offer rental guarantees. We are currently selling property with a 5-year rental guarantee at 9.5 per cent”. Bodrum Away from Istanbul the Turkish government is making significant investment in infrastructure improvements, particularly in places like Bodrum, located along the Aegean coastline, in southwest Turkey. This popular yachting and tourist hub attracts an estimated 70 per cent of all tourists that visit Turkey each year. Cumberland Properties is currently marketing a luxurious gated development in the region, Seaview Regency, which features 19 contemporary three-bedrooms, three-bathroom, detached and semi-detached villas situated on a hillside overlooking the bay of Kucukbuk. Prices for Bodrum property here start from £165,000. Alanya Although the overall standard of accommodations in Alanya, which is also situated in the Antalya Province, remains somewhat inadequate, attempts are being made to improve build-quality. “We expect branded developers to start building property in Alanya City over the next few years,” says Ali Pusat of prominent construction firm Koray. “Alanya has the potential to replicate Spain’s property success, without the oversupply of homes.” Koray has joined forces with developer BPI to build the Hill, located in Konakli, Alanya. Apartment prices at the hillside development, which will feature a selection of modern one to three-bedroom properties in Konalki, a stone's throw from the beach, start from £89,000. Amongst some of the other popular choices are: Marmaris, Fethiye, Dalaman, Altinkum and Dalyan. Summary With a number of low-budget airlines now flying into Turkey, a burgeoning property market, a strengthening economy, and plans to join the European Union, the ingredients seem right to buy into Turkey’s residential property market – whether for investment or personal reasons. However, despite all the positives, Turkey still lacks transparency. Tales of corruption and rogue housebuilders are not uncommon, and so it is necessary to approach any purchase of Turkey property with caution. Ensure that you seek independent legal advice and conduct appropriate due diligence before committing to buying a house in Turkey.

Author Resource:- Marc Da-Silva for Homes Overseas. Search our extensive range of Turkey property. In particular, view our range of Bodrum properties Homes Overseas - International property experts since 1965.

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Selling and governing the green project: owner risks in marketing, entitlement and project governance

Publication: Real Estate Issues

Author: D'Arelli, Paul

COPYRIGHT 2008 The Counselors of Real Estate

INTRODUCTION

CRITICAL THINKING ABOUT THE LEGAL AND RISK MANAGEMENT issues related to green buildings is in its relative infancy. With the sustainable development revolution upon us and a general consensus that it is here to stay, attorneys for owners, architects, contractors, lenders and the like are beginning to identify how designing, building, certifying and marketing green buildings could subject the various project participants to liability as well as how to protect their clients accordingly. There are an astounding number of players in the sustainability arena sporting green blinders and operating under the premise that green buildings are better buildings, therefore eliminating or reducing the risks in designing, constructing and delivering certified green buildings to the marketplace. Those of us currently counseling clients undertaking green building projects and pursuing third-party certification find such a premise not only untrue but also irresponsible. When you combine new building systems and technologies, inexperienced players throughout the development chain, and the relentless pursuit of a third-party green building certification with exploitation of its attendant marketing benefits, the result is a perfect recipe for potential legal exposure.


While the first generation of certified green buildings has been around for several years, industry groups are only now working on model green building lease language, tooling green design and construction contract provi- sions, and beginning to identify the insurance risks, coverage implications and possible new products. Why the delay in focusing on legal and risk management issues? After having the opportunity to meet many participants in the delivery of green buildings over the past few years, I have concluded that many developers, designers and contractors bold enough to embrace sustainable development and pursue third-party certification before it was chic, did not know if green building was a fad or if it was here to stay. Without knowing the longevity of the movement and not truly appreciating or understanding areas of potential exposure, there was little investment made or attention paid to risk management issues such as reworking design and construction contracts, scrutinizing the sufficiency of standard professional liability and property insurance, or implementing marketing and leasing protocols to minimize unreasonable expectations of certification and performance outcomes.

From entitlement, design, construction and consulting to incentives, leasing, marketing and insurance, the delivery to market of a building that is striving for LEED [R] (1) or some other third-party certification poses a host of legal and risk issues that require deliberate and thoughtful management. Nonetheless, attention to legal and risk management issues for buildings or developments seeking certification under green rating systems significantly legs behind the uptake and utilization of green building rating systems. This author believes that important areas for sound risk management in the delivery of a green building or development must be the marketing and entitlement statements and the project governance.

RISK MANAGEMENT ISSUES FOR CONSIDERATION:

Marketing the Green Project

One of the areas rife with legal exposure is the marketing of green buildings. The genesis of the risk comes from enthusiastic owners and zealous marketing in combination with leasing professionals who are proud and eager to tout the sustainable aspects of the project; the time lag between commencing a green building project and the actual receipt of the certification; a general lack of knowledge or unwillingness to acknowledge or appreciate that all green buildings are not meeting certification or performance expectations; and finally, mismatched incentives for owners, marketers and leasing brokers. When the marketing claims discussed below regarding the certification of the project or the building performance are untrue at the inception or prove to be inaccurate, a tenant, purchaser or other third party with unmet expectations (or the desire to get out of a contract for an unrelated purpose altogether) could allege misrepresentation, fraud in the inducement or breach of contract.

Certification Statements

Let's assume an owner/developer is proposing to build an office building and it is the owner's objective to obtain a LEED Gold certification under the LEED for Core & Shell Green Building Rating System[TM]. Procedurally, the project is registered with the U.S. Green Building Council (USGBC) early in the design process. However, it is not until construction of the building is completed that all final LEED letter templates and documentation are submitted to the USGBC to begin the final certification process. Note that under the LEED Core & Shell program, it is possible to obtain "Precertification" based on an early design document review that is intended to essentially allow the owner (and third parties such as tenants and lenders) to expect that if the building is constructed as designed, it is likely to receive certification. Based on current estimates, it can take from several months to a year after the building is completed and final project documentation is submitted for a final disposition of the rating. It is only upon completion of that final USGBC review and certification decision and exhaustion of any appeal, if applicable, that our hypothetical owner will know if the project obtained the LEED Gold certification. In light of this lag, marketing of the project form its inception until the certification determination is made can be problematic.

It is not uncommon, for example, after merely registering a project with the USGBC in pursuit of certification, for an owner to make statements early on in advertising, project signage and other marketing materials that the building "is LEED Gold," "will be LEED Gold" or "will be the first LEED Gold office building in X Town." The design and construction of an office building involves multiple parties--architects, engineers, contractors, subcontractors, and vendors--who all have the ability to compromise the owner's certification objectives. Combine this with the fact that the ultimate rating decision is made by an independent, non-profit, non-governmental organization which often doesn't confer the level of certification being sought by the owner, and it becomes clearer why it is imprudent to make assertions that the project "is" or "will be" certified or certified at any particular level. Furthermore, just because a building may be the first in a particular jurisdiction to be registered with the USGBC is no assurance that another building will not be registered and actually complete certification first. In fact, the number of buildings registered far outstrips the number actually certified. If a tenant or purchaser ascribes substantial value to a particular building being first in some market based on an owner/developer's marketing claims and this ends up not being the case, the owner/developer could face substantive difficulties. Last, it is important to realize that many in the corporate/tenant community do not clearly understand the difference between "Precertification," "Certification," "Registered," "Certifiable," or other locutions devised by marketing departments or currently part of the green building vocabulary. Therefore, developers should take extra care not to promote their building as being certified, or assured of certification, and should be particularly careful about these representations if a prospective tenant or purchaser is drawn to "green" as a differentiating advantage.

Now consider that the risk of promoting; but not achieving the rating sought is compounded for a project seeking certification under the proposed LEED for Neighborhood Development (LEED-ND) rating program, and why extra vigilance will be merited in marketing the project. According to the USGBC, LEED-ND is a rating system that integrates the principles of smart growth, new urbanism and green building into the first national standard for neighborhood design. It is being developed by the USGBC in partnership with the Congress for the New Urbanism and the Natural Resources Defense Council. Whereas other LEED rating programs focus primarily on green building practices, LEED for Neighborhood Development looks not only at the buildings but also the location of the project and its site design, and draws largely on new urbanist planning principles such as high-density mixed-use, connectivity and reduced reliance on the automobile. Certified green buildings are not required; however, points are available within the LEED-ND rating system for including LEED-certified buildings and for integrating green building practices within the buildings on the project site. These credits relate to energy efficiency, reduced water use, building reuse, recycled materials, and heat island reduction.

LEED for Neighborhood Development is currently being tested as a pilot program that includes 238 projects in 39 states and six countries. The pilot projects are in the process of gathering documentation based on the rating system, which will be submitted to the USGBC with the goal of becoming certified. After feedback and refinement, the resulting draft rating system will be posted for public comment before it is submitted for final approvals and balloting. It is expected to be released to the public in 2009.

There are three stages in the certification process for LEED-ND: 1) Optional Pre-Review; 2) Certification of an Approved Plan; and 3) Certification of a Completed Neighborhood Development.

* Stage 1 - Optional Pre-Review is available for projects to use at any point before the entitlement process begins. If pre-review approval of the plan is achieved, the USGBC will issue a letter stating that if the project is built as proposed, it will be eligible to achieve LEED for Neighborhood Development certification. The Pre Review letter is intended to assist the developer in garnering local government support for the project during entitlement, as well as attracting financing and potential occupants.

* Stage 2 - Certification of an Approved Plan is available after the project has been granted any necessary entitlements. During this step, any changes to the original plan reviewed during the Optional Pre-Review step are reviewed again by the USGBC for their potential effect on prerequisite or credit achievement. If approved, the USGBC will issue a certificate stating that the approved plan is a LEED for Neighborhood Development Certified Plan.

* Stage 3 - Certification of a Completed Neighborhood Development occurs when construction is complete or nearly complete. The USGBC will review any changes made to the certified approved plan that could potentially affect prerequisite or credit achievement, and if certification requirements are met, the project will be certified as a completed neighborhood development.

By the USGBCs design, LEED-ND was intended for larger, multiple building projects where the master developer is likely to sell off portions of the project to other developers or owners. While there are projects of all sizes and varieties currently in the LEED-ND Pilot Program, many are large, mixed-use projects with multiple buildings that will be built out over several years. Thus, while the owner/developer could obtain USGBC approval of a Certified Plan after the project is entitled, actual certification of the project could be many years away pending on the final build-out of the project. This additional time lag between project inception and the project certification determination provides more time and opportunity for the owner's rating objectives to be compromised. As discussed below regarding project governance, the potential for multiple owners/developers of parcels within the master development also presents a challenge in ensuring that no one owner or developer detrimentally impacts the master developer's LEED-ND rating objectives, and also should merit extra care in marketing statements.

RISK MANAGEMENT ISSUES FOR CONSIDERATION:

Performance Statements

In addition to the tendency of temptation to make speculative statements in marketing materials regarding the project's desired green building certification, some owners/developers make ill-advised claims about green building performance. With indoor air quality and enhanced efficiency and/or lower consumption of energy and water being some of the driving factors in the decision to pursue a green building, promoting these performance objectives is understandable from the landlord's or tenant's perspective. However, too much credence is being given by owners to the "average" efficiencies that are being achieved with LEED-certified buildings as reported by the USGBC and others, or to the anecdotal evidence that is widely circulated in publications, the Internet and at the myriad of conferences on sustainable development. In reality, while the averages may be true, there are a significant number of certified green buildings that are on the low end of the spectrum and not meeting their anticipated performance metrics.

For example, the executive summary of a recent report by the New Buildings Institute, funded by the USGBC and entitled "Energy Performance of LEED[R] for New Construction Buildings," studied 121 LEED New Construction certified buildings that have been operational for at least one year and which provided actual energy use data, states that:

"This study analyzes measured energy performance for 121 LEED New Construction (NC) buildings, providing a critical information link between intention and outcome. The results show that projects certified by the USGBC LEED program average substantial energy performance improvement over non-LEED building stock." (2)

This sounds good, but hold the presses on that project marketing brochure. The report also notes later that:

"Program-wide, energy modeling turns out to be a good predictor of average building energy performance for the sample. However, as with the other metrics in the study, there is wide scatter among the individual results that make up the average savings. Some buildings do much better than anticipated. ... On the other hand, nearly an equal number are doing worse--sometimes much worse." (Emphasis added)

"At the extreme, several buildings use more energy than the predicted code baseline modeling. ... This degree of scatter suggests significant room for improvement in energy use prediction accuracy on an individual project basis." (Emphasis added)

"Variation in results is likely to come from a number of sources, including differences in operational practices and schedules, equipment, construction changes and other issues not anticipated in the energy modeling process." (3)

Because of the tendency of the media and those with vested interests in furthering, the noble agenda of green buildings to publicize the efficiencies that are accruing "on average" more vigorously than publicizing performance failures, owners, tenants and others understandably have a perception and expectation that these "average" efficiencies will accrue to them if they commit to a certified green building. These expectations can easily get translated into a well-intentioned owners marketing material, creating further expectations in tenants and purchasers. For example, statements made in marketing materials such as "this LEED Gold office building will save 28% in energy and 45% in potable water or "tenants will save money on operating costs and see higher worker productivity and less absenteeism in this LEED Gold office building" are not unheard of. What happens, however, when the publicized performance metrics or green building benefits are not realized? What happens when a tenant or purchaser acquires information during the due diligence process indicating that a study or data used to make these representations is not credible? Or worst of all, what happens if the tenant or purchaser has poor performance outcomes and comes to realize that the representations made by the owner were questionable or less than credible from the beginning? While owners or developers themselves may take recourse against their design and construction team, they may also have disappointed tenants and purchasers whose financial pro forma is distorted or whose reputation is jeopardized when the operational savings or human resource benefits are not realized. Naturally, this creates a potential for claims of breach of contract, misrepresentation and the like, and potential harm to the developer or owner's reputation in the marketplace.

In addition to the increasing challenge of managing risk when promoting the pursuit of certification objectives, managing risk in the marketing of project performance goals may also become more complicated with new rating systems addressing larger-scale projects like LEED for Neighborhood Development. For example, the targeted efficiencies for energy use, water use, etc., may extend beyond a single building to multiple building, project-wide goals. As discussed in more detail below, certain credits under LEED-ND could require cooperation or compliance by multiple building owners or developers, increasing the potential for non-attainment

To protect against potential third-party claims when expectations are not met, owners and developers should be careful to not make statements in their marketing materials regarding building performance that could prove untrue and be alleged as a significant inducement to lease or purchase. While "puffery" or exaggeration of a product's benefits is common in sales, it should probably be avoided in the context of green building performance expectations, as many on the receiving end of the statements may not know them to be speculative. It would be wise to train marketing, sales and leasing professionals involved with the project so that they fully understand the certification process and the attendant risks of making untrue statements or statements of desired performance outcomes which the owner may not have adequate control to ensure. Also, given the frequent disconnect between marketing, management and legal departments, developing a company protocol for review and approval of all green building aspects in project marketing materials, press releases, etc, by counsel knowledgeable in these matters could be a sound component of the project risk management strategy.

ENTITLING THE GREEN PROJECT

Everything discussed above in terms of the need to exercise caution when marketing a green building project should also be taken into consideration when entitling the project. Regarding entitlements, many local governments are interested in increasing the amount of green building stock within their jurisdictions; and regardless of whether the jurisdiction has any green building mandate or formal incentive program, "going green" is increasingly being encouraged. As such, owners or their zoning counsel seeking support for a development proposal, may be inclined to make statements or commitments regarding the project's green building objectives in comprehensive planning, zoning, site plan or other development approval applications, in conversations with local government staff or elected officials or at the dais during a public hearing.

As in the sales context, it is not uncommon for land development counsel or other project advocates to passionately extol the many virtues of their projects in an effort to secure project approval. If that is done in the context of green building objectives, an owner could inadvertently find those statements manifested in the form of development approval conditions. As such, obtaining a building permit or a certificate of occupancy could end up being conditioned on the owner's demonstrating that the green building commitment is assured or was met--a risky proposition if that commitment is to obtain a third-party certification. While this may sound remote to some, an acquaintance of this author recently disclosed that he is involved in a project with which the local government made LEED Silver certification a condition of approval for the project's conditional use permit. With this example in mind, it is suggested that all development approval applications and statements made on the public record during project entitlement be carefully tailored so that mere aspirations to pursue third-party green building certification do not to become approval conditions unless the owner is prepared to accept them.

When the USGBCs pilot program for LEED for Neighborhood Development is completed and LEED-ND is rolled out for general use, any such conditions of approval that are tied to a LEED for Neighborhood Development certification could be particularly risky or constraining. Since LEED-ND includes concepts of new urbanism that affect land planning rather than just building design and construction, a commitment to obtain LEED-ND certification could carry significantly greater risk than committing to build a certified green building. For example, in an effort to meet neighborhood certification commitments or requirements, developers could be compelled to pursue credits that affect such things as solar orientation of lots and blocks; inclusion of affordable housing; residential unit type, mix and density requirements; and project access spacing requirements, to name a few. In fact, one LEED-ND prerequisite, "Neighborhood Pattern & Design Prerequisite 1: Open Community," requires that the developer: "Designate all streets and sidewalks that are built as part of the project or serving the project directly as available for general public use and not gated. Gated areas and enclaves are NOT considered available for public use, with the exception of education and healthcare campuses where gates are used for security purposes." As such, even to be eligible to seek certification under LEED-ND as it currently stands in the pilot version, the developer could not gate the project. While such concepts of new urbanism may be "good planning," developers may find themselves in a very difficult position. This is particularly so since developers seeking land use or zoning entitlements often do not have enough design detail and information to know exactly how such far-reaching commitments will translate in terms of cost or suitability in a particular market. Owners or developers who make or accept the commitment to obtain LEED-ND certification during early stage entitlement should be prepared to accept the design constraints and potential implementation costs associated with these planning schemes.

PROJECT GOVERNANCE

In addition to marketing and entitlements, project governance also should be revisited to accommodate green building issues. Consider, for example, the project governance complexities in the case of a mixed-use building with residential condominiums, hotel and retail that is seeking certification under the LEED for New Construction rating program. The residential condos are proposed to be sold and there will be a condominium association. The hotel will be sold as a commercial condo and will be operated under a national flag with a green lodging initiative pursuant to a hotel management agreement. The retail will be sold as commercial condos and the owner will cater to retail stores and restaurants whose sustainability commitment drives their decision to locate in a LEED-certified building, including one national retailer with a corporate mandate to locate only in LEED Silver certified space. In addition to attaining LIED certification, the commercial condo owners desire that the building continue to he maintained and operated at the same standard that qualified the project for LEED certification in the first place, so that it can be certified in the future under LEED for Existing Buildings. There will be a master association over the entire project.

As a threshold matter, it becomes imperative to understand and anticipate the objectives and expectations of both the developer, and to the extent possible, each of the end users in mixed-use green buildings. In the example noted above, for a least two of the uses (hotel and retail), the proposed LEED certification is an integral component of the business model for product differentiation and a corporate mandate for one of the targeted tenants. With the objectives identified, project governance needs to be put in place to ensure that the objectives are likely to be met over both the short and long terms. A mere sampling of issues to consider includes:

* How will the green building objectives (certification, performance, maintenance, etc.) be defined and translated into all appropriate project documentation (e.g., condo documents, property owner association documents, CC&Rs, etc.)?

* How does the master developer ensure that each of the owners and end users will cooperate in any requirements necessary to obtain the desired LEED certification?

* How will controls be established (e.g.., integrating LEED or other consulting into the architectural review committee process) so no owner, tenant or association can make physical alterations that could compromise the project rating or performance objectives?

* If there are multiple associations, what controls will be put in place to ensure no association could lake action to impair the future project certification or performance objectives by amending the association documents?

* How will operational requirements such as green cleaning, green pest control, recycling, etc., be imposed and enforced project-wide?

* How do the project documents provide sufficient assurance to the end users regarding maintaining the integrity of the green building objectives, while retaining flexibility for the master developer to make adjustments based on market conditions, pursuit of the certification, etc.?

Clearly, the project governance issues for a single mixed-use building are already complex. Some ol the projects in the LEED-ND pilot program and the types that are likely to pursue LEED-ND certification once it is released to the public include large-scale, mixed-use or "town center" projects that could include multiple residential, office and retail buildings, hotels and other uses. In addition to the governance challenges that accrue just by virtue of the number and types of buildings in the project, there are also certain credits in the LEED-ND rating system that can create issues. Consider the challenge in structuring project documentation to allocate among the various parcels, buildings and owner/developers, the rights and responsibilities to ensure compliance with the following LEED-ND prerequisites and credits:

NPD Prerequisite 2: Compact Development, which requires the developer to build any residential components of the project at an average density of seven or more dwelling units per acre of buildable land available for residential uses, and build any non-residential components of the project at an average density of 0.50 FAR or greater per acre of buildable land available for nonresidential uses, with the specified average density required to be achieved by the point in the project's construction at which 50 percent of dwelling units are built, or within five years of the date that the first building is occupied, whichever is longer.

NPD Credit 3: Diversity of Housing Types, which requires inclusion of a sufficient variety of housing sizes and types in the project such that the total variety of housing within the project, or within one quarter mile of the center of the project, achieves at least 0.5 according to a calculation based on the Simpson Diversity Index.

NPD Credit 4: Affordable Rental Housing, which requires inclusion of a proportion of rental units priced for households earning below area median income pursuant to certain standards and requirements for 15 years.

NPD Credit 5: Affordable For-Sale Housing, which requires inclusion of a proportion of for-sale housing affordable to households at or slightly above the area median income pursuant to certain standards.

GCT Credit 1: LEED Certified Green Buildings, which requires projects with up to five habitable buildings to design, construct or retrofit one of those buildings to be certified under one of the specified LEED building rating systems. Additional points (no more than three) may be earned for each additional certified building that is part of the project. For projects with more than six habitable buildings, it is necessary to design, construct or retrofit a specified percentage of the square footage of project buildings for certification under one of the LEED building rating programs.

GCT Credit 2: Energy Efficiency in Buildings, which requires design and construction of at least 90 percent of all buildings in the project such that they meet certain energy improvement requirements.

GCT Credit 3: Reduced Water Use, which requires design and construction of at least 90 percent of all buildings in the projects such that they meet certain water efficiency requirements.

A review of these few credits alone poses such questions as: how will time requirement compliances be assured, such as those for achieving density targets? How will green building certification requirements be imposed and enforced for certain buildings? How will minimum energy and water efficiency requirements be allocated and assured on a per building basis to ensure compliance with project-wide goals? Because there are no form documents available to address these issues, knowledgeable counsel and creative and comprehensive document drafting are required for successful implementation and risk management. It has been this author's experience that many-owners and other stakeholders believe there is a simple paragraph or magic contractual provision to insert into their documents to defray the risks. Unfortunately, no such easy prescriptive solution exists. Every project and the objectives and requirements of the parties are unique and require scrutiny. Furthermore, providing form language to those who do not understand the implications of negotiating revisions to the language may not be prudent.

CONCLUSION

Advocates of sustainable development argue that green buildings are "better" buildings for the environment and the health of our planet. Those offering effective criticism, including discussion of the potential for risk, may mistakenly be perceived as anti-environmental. Still, the reality is that while green buildings may very well be better buildings for the environment and the planet, depending on the measure and the particular building, there are risks inherent in building certified green buildings.

If we want to encourage more green building, we need to help all project participants understand and manage the project and process risks, including those related to entitling, marketing and governing green projects.

ENDNOTES

(1.) LEED[R] is a registered trademark of the U.S. Green Building Council.

(2.) New Buildings Institute final Report, March 2008, "Energy Performance of LEED[R] for New Construction Buildings" Cathy Turner and Mark Frankel, pp. 1-4. It should be noted that this study was funded by the USGBC.

(3.) Ibid.

BY PAUL D'ARELLI, ESQ.

[ILLUSTRATION OMITTED]

About the Author

Paul D'Arelli, Esq., is a shareholder with the international law firm Greenberg Traurig, P.A. He was the fifth attorney in the U.S. and the first in Florida to become a LEED[R] Accredited Professional by the U.S. Green Building Council. D'Arelli also is co-chair of Greenberg Traurig's Green Building & Sustainability Group. He serves as counsel on two major mixed-use LEED for Neighborhood Development Pilot Projects, and has advised clients on a variety of other green building projects and matters. D'Arelli holds an LL.M. from the University of Miami School of Law in Real Property Development and is a licensed California general contractor. He lectures and writes frequently on sustainable development risk management issues.

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How major hurricanes impact housing prices and transaction volume

Publication: Real Estate Issues

Author: Beracha, Eli ; Prati, Robert S.

The Counselors of Real Estate

WE SEEK TO INVESTIGATE THE EXTENT TO WHICH COASTAL impacts of major (1) hurricanes may affect short- and medium-term housing prices. Our investigation is largely motivated by the increased strength and frequency of storms threatening the eastern and southeastern United States. Namely, several major hurricanes have recently impacted the Gulf of Mexico region and the Eastern Seaboard causing billions of dollars in damages. Escalating worldwide focus on global warming and other potential causes of this increased meteorological activity has not altered the contention by meteorologists that this is not an aberration. On the contrary, widespread expectation of future storm seasons characterized by above-average frequency, strength and duration of hurricane-level storms remains the consensus. It follows then that a better understanding of the economic impact of these storms is a beneficial contribution to real estate literature.


CONVENTIONAL WISDOM AND THE POPULAR PRESS

Conventional wisdom and the popular press suggest that a noticeable shock to the housing industry is to be expected after a major hurricane. How that shock plays out, however, is not so clear. Following the recent sequence of highly active storm seasons, the popular press published mixed opinions regarding the repercussions these storms might have on real estate markets sustaining substantial damage. Generally speaking, press articles imply the reaction in residential real estate to major storms takes the form of a bubble. That is, markets surge from a housing shortage immediately following a storm, and then correct in the medium term as supply gradually returns to prior levels. For example, Katrina, the most notorious of these recent storms hit New Orleans in August 2005. Rich (2005) suggests that storms like Katrina are a stimulus to local real estate. Pointing to frenzied buying activity as people left homeless scramble to secure a residence, the shortage of building supplies driving up housing costs, and out-of-state investors buying in droves, Rich paints a rosy picture of real estate markets impacted by a major storm.

Roney (2007) also points to an initial surge in residential real estate, quoting the National Association of REALTORS[R] (NAR) as her source for median home sale prices jumping more than 8.7 percent in the New Orleans area immediately following Katrina. Roney then backtracks, however, suggesting that home prices rose only as a direct result of federal and state aid for the multi-billion dollar damage left in the wake of the storm. She cites a subsequent price correction of 6.7 percent as evidence of the unpredictability of home values. Bajaj (2007) explains this drop by quoting Jan Hatzius, a Goldman Sachs economist, as saying that prices have fallen in the past year to correct for a surge immediately after Katrina, again suggestive of a bubble pattern.

Not all press articles project a bubble reaction, however. Keegan (2005) points to his personal experience with Hugo in 1989 and its impact on the Charleston, S.C. region, observing a massive and lengthy recovery effort after substantial devastation in the region. He also points to panhandle and central communities in Florida "still reeling" a year after storms ravaged these areas. Nonetheless, even if it belies conventional wisdom, practitioners and academics alike might be interested to know what the data collected surrounding these events do suggest.

PRIOR ACADEMIC RESEARCH

Conventional wisdom and popular press articles aside, existing academic research on this subject is sparse. In fact, very little in academic or practitioner real estate journals has addressed natural disasters and their impact on residential prices.

Hallstrom and Smith (2005) hypothesize that housing values respond to information about new hurricanes. Using a difference-in-differences framework based on the 1992 storm, Andrew (one of the strongest storms to ever hit the U.S.), they find a proximity effect where homeowners respond to information conveyed by storms passing nearby and subsequently observe prices dip as much as 19 percent, in spite of missing that residential area. Bin and Polasky (2004) conduct a highly regionalized study examining the home price differential for Pitt County, N.C. homes located in flood zones ex-ante and ex-post hurricane Floyd. They find the discount of residential property values for homes located in flood-plains significantly increased after the 1999 major storm and its associated flood damage to those homes.

Counter to Bin and Polasky, however, Speyrer and Ragas (1991) find repeated flooding does not continue to reduce prices, suggesting the market is relatively efficient in discounting the risk of repeat floods. Consistent with prior studies, Speyrer and Ragas find homes located in floodplains do experience lower property values than comparable homes not located in floodplains. New to their study, however, they determine that a large part of the price reduction is a direct result of mandated flood insurance as required by The Flood Disaster Protection Act of 1973. This Act requires Federal Standard Flood Insurance coverage for homes in certain zones. Accordingly, real estate pricing in our study should not be sensitive to zones, as this information should already be incorporated in price data.

A DIFFERENT APPROACH

Our contribution to this area of research is unique, first, because of our ability to look at Zip Code-level data. Most prior studies employ MSA-level (Metropolitan Statistical Area) or state-level data, neither of which allows for the precision obtained by a Zip Code-level analysis. Second, by examining the impact from several major hurricanes in a relatively constrained time period, we eliminate some of the variability of macroeconomic factors over time that could potentially affect results. Conversely, where some studies have considered only data from one or two storms during a brief interval (or even two unrelated intervals) taking our data from several hurricanes over a continual, but longer period generates less bias in the data. Finally, by considering several measures (price per square foot and transaction volume, in addition to raw price change differences), we aim to generate more comprehensive and definitive results.

In sum, we explore the sensitivity of median U.S. home prices and volume to the impact of major hurricanes, at the Zip Code level. Specifically, we examine quarterly changes in residential real estate price and volume following a major hurricane impact, and we test whether these particular Zip Code quarterly changes differ significantly from changes occurring in the rest of the state over the same time periods. In this way, we account for the rapid growth in population and associated increasing price trend occurring over this timeframe in the coastal states we examine.

We find some evidence from our three measures suggesting that during the first two quarters following a major hurricane, changes in home prices and transaction volume in the affected Zip Codes experience a temporary relative decline, followed by a positive correction. This temporary dip and bounce-back pattern exhibits characteristics resembling a short-term reversal consistent with the overreaction hypothesis, as often applied to financial market events. When looking at one full year following a hurricane, however, we see some evidence that areas hit by hurricanes outperform comparable areas not affected by the storm, a counterintuitive result.

DATA COLLECTION

To glean impacts on pricing and volume, we utilize quarterly median sales prices for single-family homes reported by U.S. postal Zip Code. Our Zip Code level data set was purchased from American Real Estate Solutions and includes over 3,000 Zip Codes. For each Zip Code, at least 20 quarterly median home price observations are available between the fourth quarter of 2000 and the fourth quarter of 2006, or a total of over 60,000 individual quarterly observations. Such a powerful data set permits greater precision than many prior real estate studies which are often limited to the use of MSA-level or state-level data. Further, the frequent observations allow a better time-lapse reflection of what actually happens with prices over time as opposed to yearly observations as is typically seen in real estate research.

Our use of quarterly data also imposes some burdens, however, in terms of the data's time series properties and resulting implications for estimation. First, our dependent variable is likely to display significant autocorrelation. Observed autocorrelation can be due to both fundamental factors and measurement biases. Fundamental factors include the tendency for some housing markets to display short-term momentum in home price movements, while others show fundamental mean reversion.

In addition to fundamental autocorrelation in "true" home price movements or in home price index changes measured by carefully constructed repeat-sales methods, autocorrelation in changes in observed median home prices could be induced by changes in the characteristics of home sales and their cross-sectional composition within a Zip Code. Specifically, if the distribution of homes sold within a Zip Code for a particular calendar quarter were skewed positively in terms of unobserved quality dimensions (e.g., date and quality of construction) relative to all homes within the Zip Code, the current quarter's observed median home price and price change relative to the prior quarter would be biased upwardly, and the subsequent period's observed price change would be biased downwardly. The opposite would occur if a quarter's sample of home sales were skewed negatively relative to average quality of all homes within a Zip Code. This kind of measurement-error induced autocorrelation, similar to so-called bid-ask price bounce errors in observed stock prices, would tend to induce negative autocorrelation in home price changes across calendar quarters. (2)

A further limitation of using quarterly home price data is that homes are sold throughout a calendar quarter with identification of the median price of all home sales based on all such sales within a quarter. The six major hurricanes we examine impact the coastline at different times during the quarter. Consequently, our Zip Code level median home prices for the quarter in which the natural event occurs are likely to be inclusive of home price changes surrounding the date of the hurricane impact. We define impacted Zip Codes as those where the eye of the major storm crossed directly through the region, retaining sustained winds measuring at least 55 knots. (3)

We identify major hurricanes impacting the U.S. coastline during the period for which we have Zip Code-level data using National Oceanic and Atmospheric Administration (NOAA) hurricane data, available on its website. As a part of NOAA, the National Hurricane Center is the central authority in predicting, monitoring and tracking tropical depressions, storms, and hurricanes in the North Atlantic basin. Of all the Atlantic-based storms originating between 2001 and 2005, only six storms qualify for our study due to Zip Code data limitations. In chronological order, these are Charley, Frances, Jeanne, Dennis, Katrina, and Wilma, all of which struck between August 2004 and October 2005. Damage from these hurricanes ranged from just over $2 billion (Dennis) to over $80 billion (Katrina). Geographically, these storms limit our study to Florida impacts in 2004 (Charley (4), Frances and Jeanne) and 2005 (Dennis and Wilma), and the one big gulf-coast storm, Katrina, in 2005.

To maximize accuracy in identifying affected Zip Codes, we recreate unique detailed storm tracks and overlay these on Google Earth images of the impact zones. To recreate these tracks and gauge intensity levels with precision, we use the exact geographical coordinates of these storms as tracked and measured by NOAA at fixed time intervals, as well as multiple records of sustained wind speeds detected at various weather stations. The Google Earth images from U.S. military satellite imaging also show Zip Code border outlines. Thus, with geographically precise storm tracks and associated sustained wind speeds, we can then employ a duplicate-matching method to locate and confirm those Zip Codes directly under the path of the eye of the storm. The result is a unique set of hand-compiled data which, although limited in scope, makes a detailed examination possible for several natural and unpredictable events. After imposing the 55-knot minimum sustained wind-speed condition on available matching data, the final set includes 52 Zip Codes from our Zip Code-level data set.

Table I displays some descriptive statistics on this sample of Zip Codes. The six major hurricanes in our sample are distributed across 52 Zip Codes encompassing nearly 11,000 transactions over our study period. Of the 52 Zip Codes, four were impacted twice as a result of Frances and Jeanne in 2004. We matched each of these Zip Codes with their respective states using the www.zip-code.com website.

METHODOLOGY

To gauge the effect that hurricanes included in our study have on the housing market, we employ three core variables taken from our Zip Code-level data set. These variables are median sales price (PRICE), median sales price per square foot (PPSF) and transaction volume (VOL), as measured on a quarterly basis. Changes in these variables around the natural event should indicate any significant positive or negative deviations over time, when the changes for Zip Codes affected by the hurricanes are compared to changes for a control group.

Specifically, we adjust the quarterly changes in these three variables to control for seasonality effects as well as the overall housing trend in the surrounding areas during a given time period. Our adjustments are made by first pairing each hurricane-affected Zip Code with its particular state. Then, we find the difference between the variable change (percentage change from the previous quarter) in each affected Zip Code and the variable change in its paired state data. We refer to this difference in quarterly changes as the adjusted difference (denoted) for each of our three price and transaction volume variables.

Finally, to derive the adjusted difference for each variable, we average these adjusted differences across all Zip Codes. These state-adjusted values draw a direct comparison of quarterly sales price and transaction volume changes in the affected Zip Codes with quarterly changes in Zip Codes statewide. More formally, we measure:

ADJ[DELTA]PRIC[E.sub.t,i] = [DELTA]PRIC[E.sub.t,i] - [DELTA]ST_PRIC[E.sub.t,i] (1)

ADJ[DELTA]PPS[F.sub.t,i] = [DELTA]PPS[F.sub.t,i] - [DELTA]ST_PPS[F.sub.t,i] (2)

ADJ[DELTA]VO[L.sub.t,i] = [DELTA]VO[L.sub.t,i] - [DELTA]ST_VO[L.sub.t,i] (3)

where ADJ[DELTA]PRIC[E.sub.t,i], [DELTA]PPS[F.sub.t,i], and [DELTA]VO[L.sub.t,i] are the quarterly changes in median sales price, median sales price per square foot and transaction volume, respectively, for Zip Code i, from time t-1 to t-0. Similarly, [DELTA]PRIC[E.sub.t,i], [DELTA]ST_PPS[F.sub.t,i], and [DELTA]ST_VO[L.sub.t,i] are the quarterly changes in median sales price, median sales price per square foot and transaction volume, respectively, for the state including Zip Code i, from time t-1 to t-0. Time t-0 is defined as the quarter in which the hurricane occurred. Thus, a [DELTA]PRIC[E.sub.t,i] value measures from the prior quarter to the current quarter, t. Using the adjusted differences for each of these variables found with equations (1), (2) and (3), we evaluate five subsequent quarters beginning with the quarter in which the major hurricane hit (t-0) and ending four quarters later (time t+4). In this way, we examine both short and medium term effects.

To capture the short-term impact of these major hurricanes on residential properties directly affected, we first compare the arithmetic average of all the adjusted differences generated by equations (1), (2) and (3) across time periods using a two-sample mean comparison test. This quickly allows us to observe any statistically significant increase or decrease in the average adjusted difference for each variable, around the event date.

To further assess short term impact on residential property markets, we also use linear regression analysis to observe adjusted differences for each of our three variables around the hurricane event. Linear regression analysis allows us to emphasize changes in differences for each of the affected Zip Codes rather than changes in differences across all 52 Zip Codes in our sample. Accordingly, for each variable, we regress percentage changes in adjusted differences during a given quarter (dependent variable) on the previous quarter's percentage changes in adjusted differences (independent variable) to identify significant differences over time. More formally, we define these regressions as:

ADJ[DELTA]PRIC[E.sub.t,+1,i] = a + [beta]ADJ[DELTA]PRIC[E.sub.t,i] (4)

ADJ[DELTA]PPS[F.sub.t,+1,i] = a + [beta]ADJ[DELTA]PPS[F.sub.t,i] (5)

ADJ[DELTA]VO[L.sub.t,+1,i] = a + [beta]ADJ[DELTA]VO[L.sub.t,i] (6)

where a statistically significant positive or negative beta coefficient in any of the equations (4), (5) or (6) may suggest a significant increase or decrease in the adjusted difference in median sales price, median sales price per square foot, or transaction volume from one period to the next, near the major hurricane event.

Finally, to capture the medium term effects of the hurricanes on residential real estate, we compare adjusted differences in median sales price and median sales price per square foot over the full year following the hurricane. (5). We accomplish this in a manner similar to equations (1) and (2). Rather than quarterly, however, this time we calculate the annual post-event percentage change in median sales price and median sales price per square foot, for each Zip Code, as:

[DELTA]PRIC[E.sub.t_t+4,i] = ((PRIC[E.sub.t+4,i] / PRIC[E.sub.t,i]) - 1) *100 (7)

[DELTA]PPS[F.sub.t_t+4,i] = ((PPS[F.sub.t+4,i] / PPS[F.sub.t,i]) *100 (8)

where PRIC[E.sub.t,i] and PPS[F.sub.t,i] are the median sales price and median sales price per square foot, respectively, for Zip Code i, at time t. Correspondingly, for the state including Zip Code i, we define the one year change in median sales price ([DELTA]ST_PRIC[E.sub.t_t+4,i]) and median sales price per square foot ([DELTA]ST_PPS[F.sub.t_t+4,i]) in a manner similar to equations (7) and (8). Again, we use the two-sample mean comparison test to contrast the arithmetic average of all values generated by equations (7) and (8) from the 52 Zip Codes with their associated states' average values, respectively. A statistically significant difference between the changes in the values for affected Zip Codes and those of their surrounding state would suggest some medium-term effect on the residential real estate within those Zip Codes struck by major hurricanes.

HYPOTHESES

While the colloquial concept of market overreaction as a manifestation of normal psychological behavior has been observed for generations, its formal documentation and analysis is a relatively modern development. DeBondt and Thaler (1985) define the overreaction hypothesis simply as a hyper-response to new information. The hypothesis suggests both that extreme movements in stock prices are followed by movements in the opposite direction to "correct" the initial overreaction and that greater magnitudes of the initial price change are generally offset by increasingly extreme reactions.

Evidence of overreaction has primarily been found in analysis of stock returns following large one-day stock price declines. Brown, Harlow and Tinic (1988) as well as Atkins and Dyl (1990) find significant reversals for stocks experiencing one-day price declines. Many differences between investments in marketable securities versus homes exist, however. Exposure to housing price risk is largely non-diversifiable for individual homeowners. Home prices and changes in home prices vary by location. Arbitrage is costly and largely infeasible. Further, real estate markets do not have the liquidity of financial markets. As a result, the residential real estate market is often characterized as relatively inefficient relative to markets for financial securities. Still, similarities remain.

Bremer and Sweeney (1991) examine common stock returns following one-day price declines of 10 percent or more over nearly a quarter century, finding significant positive abnormal returns extend three days immediately following the declines. They further note that this prolonged recovery period is inconsistent with prices fully and quickly reflecting relevant information and suggest that market illiquidity may partially explain their findings, as also supported by Capozza, Hendershott, and Mack, (2004). The real estate market, as one of the more illiquid asset markets, consequently provides a vehicle to help maintain the idea that prolonged recovery periods may indeed be associated with illiquid markets. The reaction in real estate may remain analogous, but the timeframe may also be extended as a result of a relatively slower and more illiquid marketplace.

Accordingly, as we are interested in how major hurricanes affect observed changes in median home prices, median price per residential square foot, and residential transaction volume across our sample of 52 affected Zip Codes, we expect to see reactions resembling some form of overreaction, as a hurricane clearly is viewed as a natural (unforeseen) event with negative implications. Consequently, we test hypotheses gauging any reaction to six natural events in these three variables. Specifically, we look first at quarterly movements, and then reaction over a one-year period.

We expect quarterly changes in our price and volume variables across the state will differ significantly from changes occurring in those Zip Codes impacted by a major hurricane. Our method tests consecutive null hypotheses that the state-adjusted difference for each volume and price variable at times t-1, t-0, t+1, t+2 and t+3 is not significantly different than the adjusted difference for each variable at time t-0, t+1, t+2, t+3 and t+4, respectively.

Further, when looking specifically at how these differ, we expect to see some evidence of a decline in the quarter or quarters immediately following the hurricane event, and then we anticipate some form of rebound as a correction to the initial negative impact. Should there be these results, this should also break out as evident in basic regressions, showing as negative correlation between periods. That is, if the initial reaction is lower, then subsequent results should be higher. Conversely, if higher initially, then lower subsequently.

While Rich (2005) suggests post-storm growth "could come at the expense of building in other regions" in the state, we expect our findings to suggest otherwise. Substantial and rapidly occurring negative shocks to the market are likely to be associated with a substantial drop in demand, leading selling pressures to temporarily lower prices. As the public perception is that hurricanes spur growth and investment, any market drop should indeed be a temporary effect.

RESULTS

Benchmarking the adjusted differences at time t-0 as an index of 100, Figure 1 shows the adjusted differences for each of the three variables over the five sequential quarters, first from t-1 to t-0 (the quarter prior to that containing the hurricane) through t+3 to 1+4 (the last quarterly change one year after the hurricane). The state adjusted median sales price, which is presented in panel A, does not initially decline (during t+1). It does increase slower than all other quarters, however, before sharply rising during quarter t+2. On the other hand, panels B and C clearly illustrate the adjusted difference in both median sales price per square foot and transaction volume decline during the quarter following the hurricane and increase sharply in the subsequent quarter. This is consistent with our hypothesized expectations.

[FIGURE 1 OMITTED]

To emphasize the changes in the adjusted differences, in Figure 2, we present the derivative of Figure 1. That is, Figure 2 shows the rate of change in differences from each time period to the next. All three panels illustrate a sharp decline from time t-0 to t+1 as well as a sharp increase from time t+1 to t+2. This is again consistent with our hypothesized expectations. Yet, while differences in changes across time are visible to the eye for both volume and prices, we do test the statistical significance of these differences in Table II.

Table II documents a quarter-to-quarter comparison of the change in adjusted difference for median price, median price per square foot, and transaction volume. Panel A presents the results of a two-sample mean comparison, in which we compare average adjusted differences in one quarter to the quarter that follows. The first row in this panel indicates a positive, but insignificant, statistical difference between variable changes during the quarter the hurricane hit and the subsequent quarter. The second row, however, indicates a negative and significant statistical difference between changes during the quarter that immediately followed the hurricane and its subsequent quarter. This significant difference is observed for all three variables with test-statistics of -1.96, -1.98 and -2.85 for median sales price, median sales price per square foot and transaction volume, respectively. The results of these two comparisons suggest that changes in prices and volume dip during the quarter following the hurricane, correcting soon thereafter, roughly during the second quarter that follows the hurricane (t+2). This supports the contention that illiquid markets lag the overreaction effect.

Figure 3 portrays results for prices and volume over the medium term, in the form of an indexed horse-race comparison between the affected Zip Codes and statewide Zip Codes. A visible difference between the changes in values for the affected Zip Codes and their statewide counterparts is counterintuitive. It suggests that over a course of one year, in spite of the direct and indirect negative effects brought to these Zip Codes by the hurricane, the prices of residential real estate in the affected Zip Codes rose faster than the median prices in the rest of the state (panel A and B). Similarly, panel C suggests that the relative number of transactions made in the affected areas increased over the course of the year more rapidly than at the rest of the state. This could explain the generalized conclusions drawn by the popular press in suggesting that housing markets experience a boom following hurricane impacts.

[FIGURE 2 OMITTED]

[FIGURE 3 OMITTED]

The second panel of Table II shows the statistical significance of the results presented in Figure 3. When comparing the change in median sales prices and median sales price per square foot between the affected Zip Codes and those statewide, we generate test-statistics of 1.95 and 1.46, respectively. Both of these values suggest price measures rose faster in the affected Zip Codes, with the median sales price measure bordering on statistical significance.

Finally, Table III presents the beta coefficient results for equations (4), (5) and (6). Negative and statistically significant beta coefficients appear in the first two rows, suggesting negative autocorrelation between changes in quarters t-0, t+1, and t+2. These results further support the results shown in panel A, but with stronger statistical significance. In summary then, our results for the short term suggest that a dip in changes for each of our three variables during quarter t+1 is statistically significant and is followed by a statistically significant upside correction during quarter t+2, again consistent with our hypothesized market reaction.

CONCLUSION

We investigate subsequent changes in quarterly housing prices and volume for 52 U.S. Zip Codes impacted by six major hurricanes from 2004-2005, for one year following the natural event. We obtain results that are consistent with home price changes following an overreaction pattern, similar to that found in financial markets after an unforeseen negative shock to the market. During the first two quarters following a major hurricane, our data suggest that changes in home prices and transaction volume in the affected Zip Codes experience a temporary dip, followed by a positive correction. Thus, some evidence emerges that a transitory price decline presents a buying opportunity, providing some support for a short-term reversal. A time-extended form of a short-term reversal (a few months as opposed to a few days) as we find, is consistent with Bremer and Sweeney (1991) who suggest that illiquid markets may partially explain the inefficiency of a prolonged recovery period.

When examining changes in our measures one full year following a hurricane, little evidence emerges suggesting a lingering effect on residential real estate prices, as prices have generally corrected back to their prior trend-line. Still, a nominal positive difference is found. Although statistically insignificant, this presents some evidence that areas hit by hurricanes outperform comparable areas not affected by the storm, a counterintuitive result. This leaves the door open to further research in this area, something presently in development.

Our study is unique compared to prior work in this area. First, we look at Zip Code-level data where most prior studies employ MSA-level (Metropolitan Statistical Area) or state-level data, neither of which allows for the precision obtained by a Zip Code-level analysis. Second, by examining the impact from several major hurricanes in a relatively constrained time period, we have less bias in our data than data from only one or two hurricanes and we eliminate some of the variability of macroeconomic factors that could potentially affect results. Finally, we use several measures to generate more definitive results.

Contrary to popular opinion, our results do not present evidence of an immediate surge in prices from a housing supply reduction and capital infusions to drive demand as prior popular press articles have implied. Thus, the housing market reaction to a major hurricane impact does not seem to exhibit behavior indicative of a bubble. That is, while it may be possible that a housing shortage immediately follows major storms and later corrects as supply returns to prior levels, overshadowing this possible outcome seems to be a short-term precipitous drop in demand. This might be due to large quantities of people relocating after a major storm, but all such reasoning would be entirely speculative. We do not seek to explain our results, only to present them.

REFERENCES

Atkins, Allen B., and Edward A. Dyl, 1990. Price reversals, bid-ask spreads, and market efficiency, Journal of Financial and Quantitative Analysis 25, 535-547.

Bajaj, Vikas. Home prices fall in more than half of the nation's biggest markets. The New York Times, February 16, 2007. http://www.nytimes.com/2007/02/16/business/16home.html

Bin, Okmyung, and Stephen Polasky, 2004. Effects of flood hazards on property values: Evidence before and after hurricane Floyd. Land Economics 80(4), 490-500.

Bremer, Marc, and Richard J. Sweeney, 1991. The reversal of large stock-price decreases, Journal of Finance 46, 747-754.

Brown, Keith C., W. V. Harlow, and Seha M. Tinic, 1988. Risk aversion, uncertain information, and market efficiency, Journal of Financial Economics 22, 355-385.

Case, Karl E. and Robert Shiller, 1989. The efficiency of the market for single family homes, American Economic Review 79(1), 125-137.

Capozza, Dennis R., Patric H. Hendershott, and Charlotte Mack, 2004. An anatomy of price dynamics in illiquid markets: analysis and evidence from local housing markets, Real Estate Economics 32(1), 1-32.

DeBondt, Werner F. M., and Richard H. Thaler, 1985. Does the stock market overreact? Journal of Finance 40, 793-905.

Dehring, Carolyn A., Craig A. Depken, and Michael R. Ward, 2007. The impact of stadium announcements on residential property values: Evidence from a natural experiment in Dallas-Fort Worth, Working paper.

Dimson, Elroy, 1979. Risk measurement when shares are subject to infrequent trading. Journal of Financial Economics 7, 197-226.

Hallstrom, Daniel G., and V. Kerry Smith, 2005. Market responses to hurricanes. Journal of Environmental Economics and Management 50(3), 541-561.

Keegan, Matthew, 2005. Hurricane Katrina and the impact on real estate prices. EzineArticles (August 31), http://ezinearticles.com/?Hurricane-Katrina-And-The-Impact-On-Real-Estate-Prices&id=65544.

Piazzesi, Monika, Martin Schneider, and Selale Tuzel, 2005. Housing, consumption, and asset pricing, working paper, University of Chicago.

Rich, Motoko, 2005. Housing boom may continue after storm, experts say. The New York Times (September 5), http://www.nytimes.com/2005/09/05/business/05build.html?pagewanted=print.

Roney, Maya, 2007. House hunting in a hurricane zone. Businessweek Online (September 12), http://www.msnbc.msn.com/id/20744411/.

Speyrer, Janet F., and Wade R. Ragas, 1991. Housing prices and flood risk: An examination using spline regression. Journal of Real Estate Finance and EconomicsC4(4), 395-407.

NOTES:

1. Hurricanes rated at 3 or greater on the Saffir-Simpson scale are technically defined as Major Hurricanes. The Saffir-Simpson scale categorizes hurricane strength from 1 to 5, the strongest being 5. A category 3 storm has sustained winds of 111-130 mph.

2. The problem would appear to be endemic in annual data, too, but to a lesser degree given more observations over longer time horizons.

3. While each hurricane in our study is categorized at 3 or greater, this categorization stems from maximum sustained wind speed. It is understood that storms will weaken over land. Although a 55-knot threshold, or nearly 64 mph, falls about 8 knots short of hurricanestatus sustained winds, this level still ranks in the upper quartile of tropical storm strength and is a minimum speed, exclusive of gusts. Accordingly, with continual data unavailable, measurements of sustained winds exceeding 55 knots maintain enough power in the storm area for continued property damage, fatalities, and extensive flooding from the storm surge.

4. Charley hit Port Charlotte, FL, with 150 mph winds (category 4) and then crossed the state to re-emerge in the Atlantic before looping back into Myrtle Beach, SC, where it only briefly sustained winds over 55 knots.

5. Transaction volume difference would have no meaning at this stage because it is not a continuous variable; accordingly, we omit this measure here.

The authors would like to thank Professors Surendra Singh and George Bittlingmayer from the University of Kansas School of Business for generous financial assistance in securing the home price data used in this study, and gratefully express appreciation to ECU-MBA students, Derek Vestal and Denise Thompson, for their diligent Zip Code matching efforts.

BY ELI BERACHA, PH.D., AND ROBERT S. PRATI, PH.D.

About the Authors

Eli Beracha, Ph.D., is an assistant professor of finance in the College of Business at East Carolina University, Greenville, N.C. He earned a Ph.D. in finance and a masters in economics from the University of Kansas, and has special interest in empirical research in the area of real estate and finance. Dr. Beracha teaches courses in real estate financing and real estate analysis at the undergraduate and the MBA level and has personal experience in real estate investments. Dr. Beracha also occasionally contributes to a locally syndicated newspaper column entitled Your Financial Health.

Robert Prati, Ph.D., is an assistant professor of finance in the College of Business at East Carolina University, Greenville, N.C., and a member of the Beta Gamma Sigma honor society. A graduate of Emory University, he earned his MBA at the Burnham-Moores Center for Real Estate at the University of San Diego, thereafter co-managing a loan portfolio of nearly a billion dollars at Wells Fargo Bank, N.A. Dr. Prati taught at Florida State University while earning his doctorate there, and presently serves on the Investment Advisory Committee for the University of North Carolina (the state's 16 public universities), advising on retirement options for over $3 billion. Dr. Prati has been a guest on the television/radio program Financially Speaking, and has served on several nonprofit boards, most recently helping to orchestrate a merger between the ECU Credit Union and the North Carolina State Employees Credit Union, combining over $15 billion in assets at the end of 2007. Dr. Prati also occasionally contributes to a locally syndicated newspaper column entitled Your Financial Health.

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How to Get a Real Estate Offer to Purchase

By : John Cutts

Property owners who want to have their homes for sale by owner must know that they need to have a legal document called a real estate contract or an Offer to Purchase. A real estate agent may tell you a lot of real estate bogus but you must know who to consult if it involves a legal real estate document? — a real estate attorney.

A FSBO seller must know these steps to have an FSBO offer to purchase:

1. Search for a real property lawyer that does deed preparations for FSBOs.
   
   
2. Ask how much this document may cost. A deed preparation may cost around $100 to $200.
   
   
3. Know if the sales contract they provide is approved by the Bar association of your state.

Ask your real estate attorney if they do contract reviews and consultations. You may need this before you do the final contract signing. You are now set to handle the contract details of your FSBO real estate offer to purchase. *** Note: Number 3 and 4 may have additional fees so be sure to ask. With this new knowledge you must always remember that the purchase to offer is a legal document. To get the best advice and the quickest process, consult the right people. Legal documents are handled by legal professionals like your real estate attorney. Do not believe those real estate agents that seem to take advantage of your FSBO status. They can trick you into shouldering 10 up to 200 times the actual fee. So, if you are planning to sell your property by for sale by owner, know what you need, who to ask for help; know the real process; and save money. Even selling your own home by owner may be tricky and pricey if you do not know how it is done properly.

Author Resource:- John Cutts has been educated in the finer points of the foreclosures market over 5 years. Read houses for sale by owner information on OwnersAndHouses.com - Find homes for sale by owner.

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