This assignment will require you to determine what a fixture is and how to recognize them in your home. You will take a walk through your home to identify five fixtures and provide a written descripti

LITERATURE REVIEW In recent years, home value estimates have been subject to heightened scrutiny, with a housing price bubble followed by a sharp downturn. Interested parties such as appraisers, tax assessors, buyers and sellers seek reliable data from which they can derive an unbiased estimate of value. Th e real estate industry is based on “information asymmetry,” which means that one party (typically the seller) knows more about a product than the other (the buyer). It’s an opaque market that encourages obfuscation and leads to fl awed pricing. A motivation behind the founding of Zillow.com in 2006 was to make real estate more like a stock exchange, a transparent market where all information about every property is readily available and, as a result, pricing is less imperfect. 1 Zillow provides an estimate of market value for more than 100 million homes based on a proprietary formula.

In general, it off ers free value estimates, or “Zestimates,” using data from appraisal districts and from multiple listing services (MLSs), depending on availability. Zillow uses a “static” formula employing tax information, and applies it uniformly across the country. Th eir stated mission is “to empower consumers with information and tools to make smart decisions about homes, real estate and mortgages.” 2 Zillow is a home and real estate marketplace created to help homeowners, homebuyers, sellers, renters, real estate agents, mortgage professionals, landlords and property managers fi nd and share vital information about homes, real estate, mortgages and home improvement.

Th ey assert to be “transforming the way consumers make home-related decisions and connect with professionals.” Zillow partnered with Yahoo! in 2011 to provide the vast majority of Yahoo’s real estate listings online, cementing their place as the largest real estate network on the Web according to several online measurement agencies. 3 Th e focus of this article is to determine whether Zillow’s Zestimates refl ect actual sale prices. Realtors generally have been critical of the values produced by Zillow, claiming the data are secondhand, not locally sourced and out of date. Realtors with specifi c market knowledge are more likely to know specifi c factors aff ecting the sale of a home such as the overall condition of the home, room fl ow, landscaping, views, traffi c noise and privacy. Th ese factors have been called unzillowable. 4 Hagerty 5 studied the accuracy of Zillow’s estimates and found that they “oft en are very good, frequently within a few percentage points of the actual price paid. But Charles P. Corcoran, Ph.D., CFA, is a professor and chair of the Accounting and Finance Department at the University of Wisconsin/River Falls. His recent publications have appeared in Asset International’s CIO, Global Journal of Business Research, Journal of International Business and Economics, The Journal of Accounting and Finance Research, the Journal of Instructional Pedagogy, among others. Corcoran teaches Real Estate Finance. He received his Ph.D. from the University of Minnesota.

Fei Liu is a visiting scholar at the University of Wisconsin/River Falls.

Fei is pursuing a Ph.D. in Trade and Finance from Central China Agricultural University, Wuhon, China. About the Authors 45 REAL ESTATE ISSUESVolume 39, Number 1, 2014 FEATURE Accuracy of Zillow’s Home Value Estimates when Zillow is bad, it can be terrible.” O’Brien 6 asserts that “Zillow has Zestimated the value of 57 percent of U.S. housing stock, but only 65 percent of that could be considered ‘accurate’—by its defi nition, within 10 percent of the actual selling price. And even that accuracy isn’t equally distributed.” Th e article cites the state of Louisiana as an example, where “the site is just about worthless.” Th e National Community Reinvestment Coalition fi led a complaint with the Federal Trade Commission stating that Zillow was “intentionally misleading consumers and real-estate professionals to rely upon the accuracy of its valuation services, despite the full knowledge of the company offi cials that their valuation Automated Valuation Model (AVM) mechanism is highly inaccurate and misleading.” 7 Zillow oft en overestimates home values, much as homeowners themselves do. Goodman and Ittner 8 compare owners’ estimates of value with subsequent sale prices; their results indicate that homeowners overestimate value by approximately six percent. Riel and Zabel 9 fi nd an 8.4 percent overestimate compared to sale prices.

Th ese fi ndings suggest that Zillow estimates are not as accurate as homeowners’ estimates. Hollas, Rutherford and Th omson 10 fi nd that Zillow estimates overvalue homes by 10 percent compared to the sale price. Zillow also overestimates values for approximately 80 percent of the houses in their sample by at least one percent. Th ey conclude that homeowners’ estimates of value may be more accurate than Zillow’s estimates. Th e coeffi cients on a Zillow model compared to the coeffi cients on a sale price model indicate that Zillow prices some housing characteristics diff erently than the market. Specifi cally, vacant properties are overvalued. It appears that Zillow does not track the occupancy of a property, yet vacancy is known to aff ect value. Moreover, Doshan 11 asserts that Zestimates are “gamed.” Zillow uses the Zestimate “on or before the sales date.” In other words, they use the Zestimate aft er the listing price becomes public. Th at makes their Zestimate look more accurate than it really is since the Zestimate can be drastically aff ected by the listing price.

In response to homeowners’ complaints about the quality of the data Zillow extracts from public archives across the United States, in 2011 Zillow added tools that enable homeowners to edit facts and add information about their properties. Zillow also off ers listing services for homeowners and real estate agents, which enable these users to edit and add information, both manually and through automated data feeds. Th ese tools are becoming increasingly popular. At present, nearly 20 percent of archived properties have been edited through such tools.

By default, Zillow shows the facts that are supplied by the owner or agent, and these facts are supplemented by public data. Zillow also uses the user-contributed facts when computing Zestimates. Zillow’s website declares:

“we’ve made it easier for our users to help us improve accuracy by incorporating edited home facts into our Zestimate calculations.” 12 Zillow asserts that the improved algorithm models have improved the Zestimate median margin of error to 8.5 percent from 12.7 percent. However, Gelman and Wu 13 fi nd that edited facts improve the completeness of the information that Zillow has in store, but the “accuracy of Zillow’s edited facts is not high.” An inherent shortcoming in Zillow’s AVM formulation is its reliance on assessed valuation. If a property happens to be in a Proposition Th irteen (California) type of jurisdiction, with limited periodic assessment increases, over time its assessed valuation could be well below market value. Recent sales and reassessments of valuation impact the Zestimate. So Zestimate values can be “off ” signifi cantly for a property with no sales history, in a jurisdiction where assessed value is not signifi cantly increased until a sale occurs.

Zillow’s no-cost, no-hassle model seems to stand apart from most competitors. Redfi n 14 off ers a free, no-strings- attached service but its model is rudimentary, considering only comparables in deriving value. Trulia.com and HomeValues.com require a return contact from a realtor; RealEstate.com requires registration, including disclosure of phone number and email address; RealEstateABC.

com relies on Zillow’s Zestimates. FreddieMac off ers its Home Value Explorer. Th is AVM tool generates an estimate of property value quickly, relying on a proprietary algorithm that blends model estimates, a repeat sales model and a hedonic model. Th is product is licensed and serviced through a distributor network. Each distributor adds services and charges fees.

15 LexisNexis provides a seemingly sophisticated AVM model incorporating price indexing, tax assessment values, and a hedonic model that utilizes comparables sold in the previous year. Th ere is a fee for this service. 16 METHODOLOGY Th e objective of this research is to compare diff erences between Zillow’s Zestimates and actual sale prices in diff erent markets and at diff erent price ranges for single- 46 REAL ESTATE ISSUESVolume 39, Number 1, 2014 FEATURE Accuracy of Zillow’s Home Value Estimates family homes. For 2,005 transactions, the following model was developed for measuring mean error:

(Zestimate value – sale price) / sale price.

To measure for signifi cant diff erences between the two markets, and within fi ve price ranges in each market, a one-way analysis of variance (ANOVA) was used.

Th e ANOVA is used to determine whether there are signifi cant diff erences among the means of three or more independent groups. In this study there are ten groups altogether, fi ve price ranges within two markets— suburban St. Louis, Missouri, and St. Paul, Minnesota.

ANOVA compares the variance (or variation) between any two markets’ data sets to variation within each particular market sample. If the between variation is much larger than the within variation, as measured by the F-ratio 17, the means of diff erent samples will not be equal. If the between and within variations are approximately the same size, then there will be no signifi cant diff erence between means. Tukey’s test is a post-hoc test, meaning that it is performed aft er an ANOVA test. Th e purpose of Tukey’s test is to determine which groups in the sample diff er. Th e ANOVA measures only whether groups in the sample diff er; it does not measure which groups diff er.

Th is study seeks to measure Zestimate accuracy along two dimensions. First, measuring accuracy between markets.

Is the Zestimate value more accurate in markets with better data inputs? And second, between price ranges.

Is Zestimate accuracy between the markets aff ected by property price?

For comparison purposes, a Zillow one-star market (suburban St. Louis) and a Zillow four-star market (suburban St. Paul), segregated into fi ve price ranges, are analyzed. Th ese are both large suburban markets in the Midwest, for which the quality of valuation information diff ers considerably, according to Zillow’s four-star rating scheme. Four-star markets supposedly provide the most accurate, “best” Zestimates, followed by three- star markets, noted as “good,” “fair” two-star markets and, fi nally, one-star markets where estimates cannot be computed accurately or are simply the tax assessor’s value.

Zestimate accuracy is computed by comparing a property’s fi nal sale price to the Zestimate on or before the sale date.

Ratings are based on accumulated data over the previous three months. Zillow promotes the star-rating scheme from an implied presumption that a four-star rating must be good, as it exceeds the other three-star categories and is termed “best.” A Tukey post-hoc test was conducted on multiple price range comparisons between the two markets.

Of the 2,005 properties analyzed, 849 were in the St.

Paul market and 1,156 were in the St. Louis market.

Five price ranges were employed: (1) < $103,000; (2) $103,000–$203,000; (3) >$203,000–$253,000; (4) >$253,000–$353,000; and (5) > $353,000. Th e $203,000 price benchmark was based on the median existing single- family home price for the second quarter of 2013. 18 FINDINGS In aggregate, for both markets and for all prices ranges, the mean error is 24.8 percent. Mean error rates in the four-star (St. Paul) market compared with the one-star (St. Louis) market are signifi cantly diff erent, with a mean error rate of 17.15 percent in the four-star market and 30.48 percent in the one-star market. Th e signifi cance level is 0.000 (p = .000), which is below 0.05. Note the large F-ratio. See Figure 1 and bottom of Figure 2.

Even though Zestimate values are signifi cantly closer to sale prices in the four-star market compared with the one-star market, the diff erences are most prevalent among properties with sale prices under $203,000, the benchmark price level used in this study. For homes under $103,000, four-star market data may not have signifi cantly better information value than the one-star market, given mean error rates of 52.43 percent and 64.23 percent, respectively. Further, overestimates are far more common on the lower-priced homes. Zestimates exceed actual market values in 63.44 percent of all transactions, but for properties with sale prices under $103,000, 93.08 percent (121/130) of properties in the four-star market and 95.14 percent (333/350) of properties in the one-star market are associated with overestimated Zillow values. Figure 1 One-Way ANOVA Diff erence Sum of Squares df Mean Square F Sig.

Between Groups Within Groups To t a l 85.976 137.958 233.934 9 1995 2004 9.553 .069 138.143 .000 Signi cance at .05 level Source: SPSS statistical package 47 REAL ESTATE ISSUESVolume 39, Number 1, 2014 FEATURE Accuracy of Zillow’s Home Value Estimates For homes priced between $103,000 and $203,000, the four-star market does provide an outcome signifi cantly diff erent from the one-star market, with mean error rates of 10.77 percent and 19.68 percent, respectively.

Within higher price ranges, above $203,000, diff erences between the two markets are not signifi cant, with mean error rates ranging from 9.53 percent to 14.63 percent.

See Figure 2.

CONCLUSION Th e four-star market had a signifi cantly lower mean error rate than the one-star market, 17.15 percent versus 30.48 percent. High mean error rates are concentrated among lower-priced homes. At prices above the median home price of $203,000, diff erences between the four-star and one-star markets are not signifi cant.

While diff erences between the two markets are signifi cant for homes selling for less than $103,000, the mean error rates are so great that they are of little value in either the four-star or one-star markets. A four-star’s mean error of 52.43 percent indicates little more credibility than a one- star’s 64.23 percent. While diff erences at all price levels in both markets are usually overestimates, at this lowest price level they are almost always overestimates.

Diff erences between the two markets are also signifi cant in the $103,000–$203,000 price range. But with a mean error in the four-star market of 10.77 percent, this is close to the 10 percent error level noted by O’Brien as an acceptable threshold. So for properties in this price range, a four-star rating may be meaningful.

For the three price ranges beginning with the national median of $203,000 and above, diff erences between the four-star and one-star markets are not signifi cant. With the exception of the $203,000–$253,000 price range, this does not imply improved outcomes in the four-star market for the top two price ranges. Diff erences in both markets, while not statistically signifi cant, are quite large, with mean error rates ranging from 11.54 percent to 14.63 percent.

Within the middle price range, $203,000–$253,000, the smallest diff erences are found within both markets. In the four-star market, the mean error rate is 9.53 percent, while in the one-star market it is 12.38 percent. Th is diff erence is, again, statistically insignifi cant.

Zillow’s value as a pricing tool is questionable. With the possible exception of the $203,000–$253,000 price range, the four-star designation is of little value. Even the best results in the four-star market produce mean error rates approaching 10 percent. In both markets and for all other price levels, mean error rates are above the 10 percent level. Accuracy of 10 percent still implies an error of more than $20,000 for an average price property.

While Zillow may be a useful tool, providing an ever- changing snapshot of home prices, don’t bet the ranch on it. ■ ENDNOTES 1. For details about Zillow’s estimation methods and models, see http://www.zillow.com/zestimate/#what. 2. http://www.zillow.com/corp/About.htm.

3. http://websearch.about.com/od/Alternative-Search-Engines/p/ Zillow-Com-Real-Estate-Search-Made-Simple.htm.

4. http://forsalebylocals.wordpress.com/2006/08/18/unzillowable-the- perfect-term/ 5. Hagerty, James R., “How Good Are Zillow’s Estimates?” Th e Wall Street Journal , Feb. 14, 2007, sec. D.

6. O’Brien, Jeff rey, “What’s Your House Really Worth?”, For tune, Feb. 15, 2007. Figure 2 Tukey Post-Hoc Test for Multiple Comparisons Price (x1000) <103 103-203 <203-253 <253-353 <353All Diff erences between markets (mean values) SP - SL -.11793235* -.08910191* .02845627 .008355306 .02245725 Signifi cance .001 .000 .997 1.000 1.000 SP 0.52434 (130) 0.10771 (434) 0.09531 (133) 0.11541 (99) 0.12386 (53) 0.17147 (849) SL 0.64227 (350) 0.19682 (344) 0.12376 (138) 0.12376 (208) 0.14632 (116) 0.30475 (1,156) *denotes signi cance at the .05 level. SP=St. Paul, SL= St. Louis Source: SPSS statistical package Mean percent difference within markets, (sample size) (Zest.-sale price)/sale price 48 REAL ESTATE ISSUESVolume 39, Number 1, 2014 FEATURE Accuracy of Zillow’s Home Value Estimates 7.

http://www.hou sing-information.org/articles/ft c_complaint_against_ zillow_online_appraisal_site.

8. Goodman, John L., Jr., and John B. Ittner, “Th e Accuracy of Home Owners’ Estimates of House Value,” Journal of Housing Economics, Vol. 2, Issue 4, December 1992, pp. 339–357.

9. Kiel, Katherine A. and Jeff rey E. Zabel, “Th e Accuracy of Owner- Provided House Values: Th e 1978-1991 American Housing Survey,” Real Estate Economics , Vol. 27, Issue 2, 1999, pp. 263–298.

10. Hollas, Daniel, Ronald Rutherford and Th omas Th omson, Appraisal Journal , Winter 2010, Vol. 78, Issue 1, pp. 26–32.

11. Doshan, Brett, http://www.HomeVisor.com , Oct. 19, 2012.

12. http://www.zillow.com/zestimate/#update , April 4, 2014.13. Gelman, Irit and Ningning Wu, Proceedings of the 44th Hawaii International Conference on System Sciences, p. 9, Jan. 5, 2011.

14.

https://www.redfi n.com/what-is-my-home-worth?estPropertyId= 51230374&src=lan ding-page, April 5, 2014.

15. http://www.freddiemac.com/hve/distributors.html , April 5, 2014.

16. http://www.lexisnexis.com/legalnewsroom/lexis-hub/b/legaltoolbox/ archive/2011/09/23/automated-valuation-models-from-lexisnexis.aspx.

17. Th e F ratio is the ratio of the variance between groups to the variance within groups, i.e., the ratio of the explained variance to the unexplained variance.

18. Op. cit. at 12. 49 REAL ESTATE ISSUESVolume 39, Number 1, 2014 4 Editor’s Note Mary C. Bujold, CR E 5 Contributors FEATURES AND PERSPECTIVES 9 The Boom and Bust of the Greek Housing Market Nicholas Chatzitsolis, CRE, FRICS, and Prodromos Vlamis, Ph.D.

Th e Greek housing market may be characterized as imperfect and opaque. Th e aim of this article is to present a review of the recent developments in the Greek residential market and identify the possible links with all of its “peculiarities.” Considerations under assessment include socioeconomic factors such as the ill- based concept that every family must own at least one residential unit for “security” purposes; the extensive land fragmentation in Greece; the trend to concentrate residential development in virtually two cities (Athens and Th essaloniki); and the “unique”—by global standards—development process known as “counter performance.” Th e authors expect their analysis of the Greek residential market to be useful for industry professionals, policymakers and real estate investors alike.

18 Watch Your Real Estate Language!

Jack P. Friedman Ph.D., CRE, FRICS, MAI; Barry A. Diskin, Ph.D., CRE; and Jack C. Harris, Ph.D.

Th e same word, spelling and all, can take on diff erent meanings.

In this article, the authors hope to illustrate that when using a real estate term that has a diff erent meaning in another profession, oft en as used in accounting, it may be necessary to explain the defi nition used in order to avoid misunderstanding.

21 Land lls: Operations and Opportunities Joe W. Parker, CRE, MAI, FRICS, and Curtis A. Gentry IV, MAI Landfi lls are unique properties that present both questions and opportunities for real estate professionals. In this article, the authors emphasize that the better that real estate professionals understand what landfi lls are and how they work, the better they can help their clients who either have or anticipate business issues related to landfi lls.

29 Form-Based Zoning from Theory to Practice David Walters and Dustin C. Read, Ph.D., J.D.

In this article, the authors explore the potential advantages and disadvantages of form-based zoning to understand how it can be used eff ectively to support development that is fi nancially viable and socially benefi cial.

Instead of focusing mainly on “use” as the controlling factor in regulating development, form-based zoning is primarily intended to enhance the “public good” derived from private sector development by defi ning the “urban character” of neighborhoods and districts. Th is involves managing the siting, massing and frontage design of buildings in ways that create safe, attractive and effi cient public spaces for movement and public activities.

By emphasizing urban design features, as opposed to use restrictions, and by the inclusion of key “by-right” provisions in the code, form-based zoning can provide real estate developers with greater fl exibility to respond to market forces. If properly administered, form-based zoning can also reduce the amount of uncertainty faced by developers in the entitlement process.

However, both these advantages can be compromised through the structure and (mis)application of local regulations. 37 Historic Tax Credit Transactions in the Wake of Revenue Procedure 2014-12 Doug Banghart, J.D., LL.M., and Jeff Gaulin, J.D.

Th e historic rehabilitation tax credit (HTC) market was all but frozen by the highly controversial Historic Boardwalk Hall, LLC, v. Commissioner (HBH) court decision of August 2012.

Th en last December, the HTC market was given new life by the Internal Revenue Service’s highly anticipated issuance of Revenue Procedure 2014-12. Th is article summarizes the HTC, describes typical investment structures before HBH, recounts the court case and its impact on those structures, and analyzes the practical implications of the Revenue Procedure. While the HTC industry is still adjusting to the new HTC landscape, the authors suggest that investors and principals should be able to craft arrangements that, though not free from risk for developers or investors, have far more tax certainty for both sides than was the case immediately aft er HBH. For that reason they anticipate the Revenue Procedure will bring old as well as new investors into the HTC market.

45 Accuracy of Zillow Home Estimates Charles Corcoran, Ph.D., CFA, and Fei Liu Th is article compares Zillow.com’s home estimate values (Zestimates) with actual sale prices of 2,005 single-family residential properties in two markets in November 2013. A Zillow “four-star” market in suburban St. Paul, Minnesota, and a Zillow “one-star” market in suburban St. Louis, Missouri, are analyzed in terms of Zestimate accuracy between these two markets, as well as within specifi c price ranges. In aggregate, for both markets and within all prices ranges, the mean diff erence between Zestimates and sale prices is 24.8 percent. Comparing the two markets, Zestimate accuracy is signifi cantly better in CONTENTS 2 REAL ESTATE ISSUES ® Published by THE COUNSELORS OF REAL ESTATE ® REAL ESTATE ISSUESVolume 39, Number 1, 2014 the four-star market as compared with the one-star market, with a mean diff erence between Zestimates and sales prices of 17.15 percent and 30.48 percent, respectively. However, with the possible exception of the middle market price range, $203,000– $253,000, diff erences between Zestimates and sale prices are so great as to render doubt about the usefulness of Zestimates, regardless of the market’s star rating. Diff erences usually are overestimates, with subsequent sale prices below Zestimate values.

50 Renewables, Tax Credits and Ad Valorem Taxes: Are Policies Aligned?

P. Barton DeLacy, CRE, FRICS, MAI As the renewable energy industry matures, growing controversy swirls around its funding and, ironically, its sustainability.

Left unchecked, local assessors can undermine the operating effi ciencies of wind and solar farms with assessments based on replacement cost rather than market value.

In this article, the author explores the implications of how wind and solar farms are project fi nanced and poses two questions that bear directly on their ad valorem assessment:

1. Given that, but for production or investment tax credits, most projects would not be built—do these credits accrue to market value, or are they a form of inverse economic obsolescence?

2. Th e relative productivity of a wind or solar farm is a function of its nameplate capacity. A “Net Capacity Factor” measures its effi ciency. Might the latter serve as a measure of functional obsolescence?

Th ese issues now are being raised in Lost Creek Wind LLC v.

DeKalb County Assessor before the State Tax Commission and Circuit Court of Missouri.

VIEWPOINT 26 The Death of Corporate Reputation Bowen H. McCoy, CRE For more than a century law fi rms, investment banks, accounting fi rms, credit rating agencies and companies seeking regular access to U. S. capital markets made large investments in their reputations. Th ey generally treated their customers well and occasionally even endured losses to maintain their reputations as faithful brokers, dealers, issuers and gatekeepers. Many would conclude that this has changed. In this “Viewpoint,” the fi rst of more to come, the author expresses his concern that today’s leading capital market participants no longer treat customers as valued counterparties whose trust must be earned and nurtured, but as distant counterparties to whom no duties are required.

Th e rough and tumble norms of the marketplace have replaced the long standing fi duciary model in U. S. fi nance. Th e result has been unrelenting fi nancial scandal.

RESOURCE REVIEWS 59 The Metropolitan Revolution: How Cities and Metros are Fixing our Broken Politics and Fragile Economy Reviewed by Owen M. Beitsch, Ph.D., CRE In Th e Metropolitan Revolution: How Cities and Metros are Fixing our Broken Politics and Fragile Economy , Bruce Katz and Jennifer Bradley, both of the Brookings Institution, off er a blueprint for action which can rebuild economies and is determinedly self-reliant. Th ey speak of a revolution in thought and actions stemming from “cities and metropolitan areas [as] the engines of economic prosperity and social transformation in the United States.” If they are correct in their outlook, they are capturing the essence of a sustainable movement because cities matter, and the strategic solutions breed largely from locally renewable resources.

Covering a range of community-building activities, Katz and Bradley make the case that local developers and their local governments can achieve an extraordinary range of major improvements by linking with grass root activists, civic institutions, local foundations, and local banks historically bypassed in favor of federal resources. Reviewer Owen Beitsch, CRE, gives the book a “thumbs up” saying “the kernels in this book…shine.” 62 The End of the Suburbs: Where the American Dream Is Moving Reviewed By Roy J. Schneiderman, CRE, FRICS Not oft en does a book reviewed in Real Estate Issues get a “thumbs down,” but reviewer Roy J. Schneiderman, CRE, FRICS, recommends “giving a pass” to this one. “ Th e End of the Suburbs presents a fairly superfi cial treatment of the issues, where all roads lead to “the end of the suburbs”—or at least some of the suburbs,” says Schneiderman. “No doubt this book will be very well-received by people who already agree with the title thesis. But it will do nothing to infl uence those who disagree, and little to inform those who are trying to form an opinion. ” 3 REAL ESTATE ISSUESVolume 39, Number 1, 2014 REAL ESTATE ISSUES ® Published by THE COUNSELORS OF REAL ESTATE ® CONTRIBUTORS Doug Banghart, a partner at Jones Day, Boston, practices in the areas of state and federal tax credit syndication, partnership taxation, and nonprofi t organizations. Banghart represents major institutional investors, developers, local governments, community development entities, and nonprofi t organizations, primarily in real estate redevelopment projects. He has extensive experience in closing new markets tax credit leverage fund transactions, including acting as lead attorney on the largest single qualifi ed equity investment ever closed, and twinned historic and new markets tax credit transactions.

Banghart frequently speaks on issues related to partnership taxation and the legal and tax implications of various incentive programs.

He served as executive editor (1999–2000) and associate editor (1998–1999) of the Capital Defense Journal . He is a member of the Massachusetts Bar Association and the Virginia Bar Association (Young Lawyers Division, Executive Council, 2003–2004).

Banghart received his bachelor of arts degree. from Th e College of Wooster, where he was awarded the Raymond R. Day Prize in Urban Studies and the Pew Research Fellowship. He received his juris doctor degree from Washington and Lee University and his master of laws (LL.M) degree in Taxation from the University of Florida.

Owen M. Beitsch, Ph.D., CRE, FAICP, is a senior principal with Real Estate Research Consultants, an Orlando-based fi rm affi liated with GAI that provides economic advisory services to public and private clients throughout the United States. Beitsch serves on the editorial board of Real Estate Issues and is a research associate and adjunct faculty member at the University of Central Florida.

Nicholas Chatzitsolis, CRE, FRICS, managing director, CBRE, Athens, Greece, began his career with Barclays Bank Property Division in London in the 1980s and has more than 25 years of experience as a real estate professional. He has worked for the Greek Public Estates and for the Lambert Smith Hampton Athens offi ce.

Since 2008, Chatzitsolis has been managing CBRE – Axies, the appraisal company of CBRE Group in Greece. Chatzitsolis’ work experience includes specialised areas such as industrial plants, oil refi neries, major hotel developments, as well as all types of commercial property. He also has been a member of feasibility study teams examining all aspects of town planning and development appraisal. Chatzitsolis has appeared as an expert witness in British, U.S. and Greek courts in property-related cases.

He is a member of the Greek Technical Chamber and a board member of the European Chapter of CRE. He is also a former member of the local (Greek) Board of RICS and a former member of RICS Governing Council. He also served as chairman of RICS Europe during 2001–03. Chatzitsolis has been a visiting lecturer at Panteion University, Athens, since 1999. Chatzitsolis’ earned a bachelor of science degree in Land Admin- istration and a diploma in Estate Management from North East London University U.K., and a master of science degree in Urban Land Appraisal from the University of Reading U.K. Charles P. Corcoran, Ph.D., CFA, is a professor and chair of the Accounting and Finance Department at the University of Wisconsin/River Falls. His recent publications have appeared in Asset International’s CIO, Global Journal of Business Research, Journal of International Business and Economics , Th e Journal of Accounting and Finance Research , the Journal of Instructional Pedagogy , among others. Corcoran teaches Real Estate Finance.

He received his Ph.D. from the University of Minnesota.

P. Barton DeLacy, CRE, FRICS, ASA, MAI, is principal at DeLacy Consulting, LLC, a Chicago-based boutique real estate advisory fi rm specializing in valuation counsel, property tax consulting and Green Energy Valuation. DeLacy’s corporate experience includes practice leadership at Arthur Andersen, Cushman & Wakefi eld and CBRE.

Focusing on the real estate implications of power generation, DeLacy has built valuation models and studied property value impacts for geo-thermal, solar, wind- and coal-fi red power generation. He has also developed adaptive re-use studies for obsolete thermal plants.

Published in Th e Appraisal Journal, Real Estate Issues and Th e Journal of the American Planning Association , he has prepared testimony for federal and state circuit courts and energy siting councils. He has qualifi ed to testify as an expert witness in tax court in several states.

DeLacy holds a master’s degree in Urban Planning from Portland State University and a bachelor of arts degree from Willamette University. He previously served as adjunct professor at the Business School at Portland State University.

Barry A. Diskin, Ph.D., CRE, is professor and Francis J.

Nardozza Scholar in the College of Business at Florida State University. Diskin teaches valuation classes to real estate majors at the undergraduate and graduate levels. His focus and research has been on natural gas pipelines for eminent domain cases, property tax challenges, contamination matters, and contract disputes. Previously, Diskin published in T he Appraisal Journal, the Journal of Real Estate Research, Real Estate Economics, the Journal of the American Bar Association , and other real estate journals. He has been interviewed on national television about home buying issues and testifi ed before the Florida legislature about mobile home park legislation. Diskin is principal in the fi rm Diskin Property Research and has qualifi ed as an expert witness in six states. His doctorate degree is from Georgia State University.

Jack P. Friedman Ph.D., CRE, FRICS, MAI, SREA, ASA, CPA, is principal and CEO of Jack P. Friedman & Associates, Richardson, Texas, a real estate appraisal and economics consulting fi rm. He is nationally recognized as an author, appraiser and consultant in real estate economics and related disciplines.

Friedman’s work in recent years has been in litigation support (principally appraisal review and appraisal) regarding ad valorem tax cases, environmental damages, condemnation, construction defects, contract disputes, and a variety of economic issues.

Formerly, he served as senior research economist and head of research of Texas A&M University’s Texas Real Estate Research Center, and was the Laguarta Professor in the Department of Finance. Friedman has written more than 20 books and 200 articles, and has been published in Th e Appraisal Journal, Real Estate Issues, Real Estate Review, Real Estate Finance , and other journals. 6 R epro duce d w ith p erm is sio n o f th e c o pyrig ht o w ner. F urth er r e pro ductio n p ro hib ite d w ith out p erm is sio n.