Journal of Business; Spokane (Mar 07, 01:57 AM)  Editor's note: The following transcript reflects a conversation between Melissa Ahern, an associate professor in health policy and administration at Washington State University at Spokane, and Ryland "Skip" Davis, Sacred Heart Medical Center's CEO, about the financial squeeze some hospitals are experiencing and related health-care issues.

Ahern: Skip, what are the major issues facing hospitals right now?

Davis: What we know from national data is that about onethird of hospitals are doing well, one-third are breaking even, and one- third are losing money Unfortunately, here in Spokane, we're not in the one-third of the hospitals doing well. Government (Medicare and Medicaid) is our biggest payerrepresenting about 65 percent of our total business. Basically, the cost and demand for government health care is greater than the government's willingness to pay. This forces us to subsidize Medicare and Medicaid patients. We've always done that historically, but our state's deficit results in continued rollbacks in terms of what and how much is covered. This is all compounded by an ever-increasing drug formulary and rising prices for those drugs, technology, labor costs, and liability costs. Medicare faces the same issue.

Ahern: So here we are again in an era of health-care inflation rising costs and prices at a time when more and more people are aging and need additional health care. One of the big drivers of health-care costs has always been the constant growth of medical technology - new drugs, new procedures, and new equipment. Davis: New technologies, such as stents, defibrillators, and ventricular- assist devices (VADs), are examples of technologies that are very expensive. Defibrillators and pacemakers are getting more sophisticated and costly now. VADs, which help augment diseased heart function, are in hot demand, but are very costly. In fact, Sacred Heart surgeons just performed two of the first implantable VAD procedures in the country. Reimbursements for these technologies aren't keeping up with their costs, and yet the demand is growing.

Ahern: What about the issue of technology being costeffective? Do we adopt technologies that are not costeffective?

Davis: The issue with technology is that it always opens up new possibilities and therefore always introduces new costs. MRI is a very effective diagnostic tool that is costly, but enables much more effective treatment. Endoscopes cost money, but they enable excising polyps before they become cancerous. Knee operations used to involve a six-week hospital stay with a cast. Now, total knee replacements involve a fourday stay. My wife had both knees replaced. Before the surgeries, she couldn't walk across the street. Now she can go hiking and is pain-free. So there's no question that many of these technologies are cost-effective from the point of view of the additional quality of life that they confer. The pace of changing technology has quickened.

Ahern: Economists who are studying the health-care economy and the overall economy see that resources over the next decade are probably going to be more scarce, due to scarce energy resources, and due to a rapidly aging population that needs more health care. Do you think that Medicare and Medicaid reimbursements are going to continue to shrink?

Davis: Yes, I foresee continued potential rollbacks in reimbursement. Rollbacks began under the Clinton administration. There is a rollback provision in the new Medicare drug law. On top of that, our state has a $1.8 billion deficit, and there is tremendous demand for funds from higher education, K-12 education, and other social issues that need attention. So health care is in a fairly long line for funding. Federal and state governments are trying to control health care costs, and trying to force efficiencies. Meanwhile, we'll soon need to be able to provide significantly more healthcare services to accommodate the aging baby boomers. The demand continues to exceed our ability to pay for care under our existing system.

Ahern: Unfortunately, the healthcare system is broken in some key ways. Culprits include fragmentation (which results in inefficiency and poor quality), not enough focus on preventive care, payment systems with perverse incentives, and no clear consumer responsibility for costs. Is there a way to fix part of this sooner rather than later? What do we address first?

Davis: Both the government and consumers are unrealistic about health care. Over the last 40 to 50 years, we've developed a mentality that we are entitled to what we want, when we want it, no matter how much it costs. We are not on a sustainable course to be able to offer the same menu of services we've offered in the past. We've got to ask ourselves some difficult questions, such as how much our society wants to spend on the last stages of life.

Ahern: The issue of medical malpractice is currently being raised in the Washington state Legislature and in other states as one that drives up healthcare costs. Conjoined with this issue is the issue of quality in health care and medical errors.

Davis: We have a public expectation that if anything goes wrong, we turn to attorneys. However, these are risks in any given population. For example, there is a statistically documented occurrence of particular types of problems with babies who are born that have nothing to do with errors on the part of doctors or hospitals, but attorneys and patients sue anyway. Sacred Heart has a primary focus on quality and safety, and there is increasingly complementary technology that takes human error out of the equation. We are aggressively pursuing new ways to make care safe.

Ahern: What is a good example of that?

Davis: With technology, bar coding for pharmaceuticals eliminates substantial errors. A number of drugs have very similar names, so taking the writing out of prescribing drugs makes a significant difference. We were early adopters of a computer-assisted pharmacy system that cross-checks drug administration with patient, order, drug, and time, and alerts us to potential errors.

Ahern: It seems like an electronic medical record (EMR) would reduce errors. Having a record that moves with the patient from outpatient to inpatient, from city to city, would eliminate all of the confusion that comes from poor communication about what care the patient has had and needs to have next. Where are we on the EMR?

Davis: We have been moving along on that here in Spokane and are ahead of 99 percent of the rest of the country. We've digitized lab results, and whatever physicians do in the hospital can be electronically. transferred to their offices. Over 600 of our physicians have Palm Pilot devices for use. When they make rounds, they can see patient location, lab, X-ray, and progress notes. Prompting devices for physicians enable them to use time more efficiently in caring for patients. We can send digitized images (X- rays, MRIs, etc.) electronically throughout a network of 35 hospitals.

Ahern: One new initiative that is being touted by the Washington Department of Health is called Bridges to Excellence. That program is designed to help providers move toward increased electronic patient monitoring and also toward pay-for-performance. Providers are paid for quality, and are able to better produce quality because they know exactly how their patients are doing through the electronic-monitoring system.

Davis: That system works if the data is consistent and accurate. Hospitals have differences in patient acuity. Sacred Heart takes more seriously ill heart patients, so we will probably have a somewhat higher mortality rate, compared to an institution that takes less seriously ill heart patients. But good measurement and making those measures available to the public is important for both providers and patients in improving quality. The managerial process must demand accountability. And when we make mistakes, we should admit it, and indicate what steps are being taken to make sure it doesn't happen again. We are making substantial progress.

Ahern: So, if you could redesign the health-care system, what would you do?

Davis: I think the answer lies in publicprivate partnerships. National risk pools can help produce a more actuarially-sound pricing basis. States and employers can work together to come up with innovative approaches to provide some healthinsurance coverage for employees. Tax dollars will continue to have to take care of our low-income vulnerable citizens. Care should be consistent and similar across the country. The Dartmouth Atlas shows that it is currently inconsistent and there is a wide variability in treatments geographically for the same diseases. There needs to be a universal package of care available to everyone. And, consumers need to be responsible for some initial amount of care to be better connected to the economics of health-care decisions.

Copyright Northwest Business Press Inc. Feb 10, 2005

Scripps Howard (Mar 22, 06:35 PM)  Despite extraordinary intervention by Congress and the president in the tragic case of Terri Schiavo, she is a reminder once again of how important it is to make your wishes known for end-of-life care regardless of age.

Schiavo was just 26 years old when a heart stoppage caused severe brain damage 15 years ago, prompting a protracted legal battle between her husband and parents over whether to remove her feeding tube.

Of the 2 million Americans who die each year, 70 percent will do so after the decision is made to forgo life-sustaining treatment, yet the Schiavo case begs the question again: How will you and your family write that final act?

Q: How do I make my wishes known?

A: Start with a living will or other written instructions that describe the treatment you want if you cannot decide yourself. Discuss the instructions with your family, friends and physician, and designate someone you trust to carry out your wishes.

All 50 states and the District of Columbia have laws covering living wills and documents designating a proxy to act for you in a medical crisis. The Supreme Court recognized the right to state your end-of-life wishes in the 1990 case of Nancy Cruzan, who spent seven years on life support when a 1983 car wreck left her comatose at age 25.

Q: What conditions can I specify?

A: You can describe the quality of life you would want, or offer alternatives: How would you want to be treated if illness or accident leaves you in a coma or a persistent vegetative state? Under what conditions would you want to be put on a ventilator? A feeding tube? Antibiotics? Resuscitated if you die?

The case of Karen Ann Quinlan, left comatose by a drug overdose at age 21, brought the issue to national attention in 1976. Her parents gave a New Jersey court permission to take her off a ventilator but allowed nutrition and hydration to continue until her death nine years later.

Q: Will a living will guarantee that my wishes are followed?

A: Maybe, maybe not. The specifics of your condition, the available technology and large and small decisions made along the way typically affect your medical prognosis and appropriate treatment.

However, patients nearing death often draft a detailed written "advance directive" spelling out treatment. Someone with terminal cancer, for instance, may request chemotherapy but reject a respirator.

Health care professionals also may not honor your wishes. A study of 117 doctors published in the Archives of Internal Medicine last July found that physicians didn't follow advance directives 65 percent of the time under hypothetical scenarios for seriously ill patients.

Q: I'm afraid to surrender control of my treatment.

A: As long as you're competent, no one can override you, and you retain the right to change your instructions.

Still, designate someone you trust over 18 to act for you if you can't act for yourself. Generally, your next of kin decide the course of treatment, so a wife typically decides for a husband and a husband for a wife as Florida courts held in the Schiavo case.

Q: Can I trust my spouse or children to do what I want if it's too painful for them?

A: Ask them. A family member may be too emotionally torn to do what you want or understand what's important to you.

But whomever you choose, pick a health-care proxy who will advocate your case. In fact University of Michigan researchers Angela Fagelin and Carl Schneider contend in a recent Hastings Center Report that your proxy choice is far more important than a living will, which works in theory but may fail in practice when end-of-life decisions change radically as a patient's health declines and can't cover all contingencies.

Also, don't wait until disaster strikes to notify your proxy and discuss life-and-death issues.

Should you be the proxy, be prepared to demand the same medical updates the patient would receive and to confer with the medical team, discuss treatment options, and request consultations and second opinions.

Q: Where do I get the forms?

A: The federal Patient Self-Determination Act requires that all health care providers supply patients with the documents required by state law. Advance directives generally must be witnessed by two people (not your proxy) and may require a notary.

On the Net:

www.partnershipforcaring.org has all 50 states' forms.

www.healthdirectives.org will scan in your documents into its database and provide a wallet alert card for $18.

(Reach Mary Deibel at deibelm(at)shns.com)

© 2004 Scripps Howard News Service.

All Rights Reserved.

Daily Mail; London (UK) (Mar 23, 06:49 PM)  IT'S GOT all the telltale signs of a disaster waiting to happen: big tax perks, complicated investments and frenetic marketing by financial advisers.

This time the product is the venture capital trust - but like technology funds, precipice bonds and zero dividend preference shares before them, they are attracting investors who cannot afford to have their fingers burnt.

On the surface, venture capital trusts (VCTs) look like a win- win situation, offering 40pc tax relief on the investment plus tax- free growth and income so long as the shares are held for at least three years. VCTs raise a few million pounds by issuing shares to investors and put the money into fledgling businesses. Shareholders share the profits and the losses.

But there's more than one sting in the tail and the unwary investor could easily be hurt. These are very high-risk schemes, yet some VCTs allow minimum investments of just Pounds 1,000, which is bound to attract some people who cannot afford to lose money.

City watchdog the Financial Services Authority has become concerned that small investors could be tempted by the tax breaks and lock up money they can ill afford to lose.

VCTs have a number of key problems that should persuade small investors to steer clear: YOU must leave your money in them for three years for the tax break to stay intact - but most experts suggest you should really expect to leave your money for ten years.

THEIR shares can be very difficult to trade and most, if they can be sold, go for 15pc to 30pc less than the value of the assets they hold.

THE tax relief only applies on the initial purchase of the shares - so if you want to sell them the buyer won't get tax relief, which undermines their value.

SOME VCTs are being set up by companies with no experience of this style of investment.

WHILE some offer to buy your shares back at a small discount which would give you around 88pc of their true value, this guarantee is only as strong as the company which makes it - and some VCTs are being launched by potentially here-today-gonetomorrow companies.

Ben Yearsley, of independent financial adviser Hargreaves Lansdown, has scrutinised 45 VCTs launched this year. He says: 'There are ten to 15 I would not touch with a bargepole. Only a quarter to a third of them are worthwhile investments.

'I have suggested to these trusts that the minimum investment should be Pounds 5,000, but some are as low as Pounds 1,000.

These are long-term investments of at least seven to ten years and people who cannot afford to tie their money up that long should not buy purely on the back of a tax break.' The FSA is publishing warning guidelines on its internet site at www.fsa.gov.uk. It is also contacting financial advisers to make sure they are following the rules on advised sales and it is checking the activities of those launching VCTs.

Specifically it is looking at direct mail being sent to people, to check it highlights the risks prominently enough, and checking that they are targeting the right type of investor - that is those wealthy enough to consider VCTs.

It will also be looking at material sent to IFAs and press advertising.

"FSA spokesman Rob McIvor says: 'If they are targeting people with Pounds 250,000 of liquid assets that is one thing, but if they are sending material to small investors that is another thing entirely.

'VCTs are supposed to have 70pc of their money in what the Inland Revenue calls qualifying investments - these are usually start-up or fledgling ventures.

'The other 30 pc was generally put into something much less risky such as cash or bonds, but we are now seeing VCTs putting this into areas such as emerging markets or derivatives, which is pushing up the risk levels enormously.' The message is clear. By all means invest in VCTs if you can afford to lose all or most of the money if things go wrong.

But make sure you read all of the material carefully and understand fully what you are getting into. If in any doubt, go to an independent financial adviser and pay them to advise you.

t.hazell@dailymail.co.uk

New Straits Times (Mar 20, 11:09 PM)  THE world has become a global marketplace.

As students explore the world of business and the opportunities and

challenges it presents, it is vital that they do so with an appreciation

of the impact of the global marketplace and international trade.

Through business courses, students will develop a fundamental

understanding of the global economy. They will come to appreciate the

impact that a business can have on their lives and communities today and

on the careers and opportunities they are considering for the future.

As students develop a better understanding of international business,

more options are available to them, allowing them more latitude to apply

their business skills.

Everyone plays a role in the process of marketing. Every product bought

and sold, as well as every service rendered or received, represents the

culmination of the marketing process.

Students will learn about the techniques and strategies used by

businesses to identify and reach potential consumers of their products

and to influence sales.

The dynamic nature of the marketing function ensures that products are

constantly improved to meet customers' expectations and that pricing

policies are responsive and effective.

No product sells itself, therefore, marketing is definitely an area of

business that is highly influenced by new and innovative strategies.

A business studies programme will build a strong foundation for those

who wish to move on to further study and train in specialised areas such

as management, international business, marketing, accounting, information

technology, computer applications, or entrepreneurship.

At Olympia College, students can get a free counselling guide on

courses daily. Call any of its counsellors for more information at

03-20503688 (Kuala Lumpur), 03-7955 8868 (Petaling Jaya), 04- 6584868

(Penang), 07-2233868 (Johor Baru), 09-5177868 (Kuantan) or 05- 2433868

(Ipoh).

You can also email raffles@olympia.edu.my

U.S. Newswire (Mar 02, 11:58 AM)  WASHINGTON, March 2 /U.S. Newswire/ -- Expiring federal tax cuts, nagging state-level tax increases, and looming proposals to boost payroll taxes constitute a triple threat to small businesses: that's the warning the 350,000-member National Taxpayers Union (NTU) gave to policymakers at a forum sponsored by the Small Business & Entrepreneurship Council.

"Small businesses could be locked out of a prosperous future unless the tax cuts of the last four years are locked in," said NTU President John Berthoud, who served as a Speaker at the Council's event. "The income tax rate reductions, phase-out of the death tax, and numerous other recently-enacted provisions have fueled America's economic recovery, for which the small business sector has provided the most horsepower."

Berthoud, who holds a Ph.D. in Political Economy from Yale University, noted that approximately two-thirds of all personal income tax returns in the top bracket report at least some earnings from a small business, making the recent reductions in this and other personal tax brackets a vital component of relief for sole proprietorships and other small firms. He also cited results from NTU's 2004 study of Tax Code complexity, which found that a decade of tinkering with federal tax laws has added a billion extra hours to the annual paperwork burdens on American taxpayers, including small businesses.

"Here today, gone tomorrow tax provisions have contributed greatly to the planning headaches of small businesses," Berthoud said. "A steadily growing economy depends on a solid low-tax structure that businesses can confidently plan around in years to come."

Berthoud also cautioned that ill-advised tax hikes from state governments could prove catastrophic to the small business sector. "In their hunt for new revenue to squander, state lawmakers have disguised tax increases as licensing fees, loophole closures, or temporary surcharges, but the result is the same - businesses and their employees are starved to fatten government's coffers," he said.

Additionally, Berthoud observed that lifting the cap on earnings subject to Social Security taxes "could hit sole proprietors with a one-two punch to their pocketbooks," in the form of a marginal tax rate increase of over 12 percent. High- earning employees of small businesses would likely see a direct tax bite as well as a loss of future wage increases, while other workers might forfeit their jobs entirely as business owners struggle to shoulder the heavier tax load.

"Until the Tax Code is scrapped in favor of a simpler system, the bottom line for businesses may depend on making the recent tax cuts permanent and avoiding punitive increases in other federal and state taxes," Berthoud concluded.

NTU is a non-partisan citizen group working for lower taxes and smaller government. Note: Further tax policy research, including NTU's tax complexity study, is available at http://www.ntu.org.

http://www.usnewswire.com

Journal of Real Estate Literature (Mar 02, 03:28 AM)  Wang, Chen. University of Hong Kong, 2003. The Impact of the Internet on Development Strategies of Real Estate Agencies: A Qualitative Study Based on Beijing's Real Estate Agency Industry.

This study investigates the impact, if any, of the Internet and information technologies on the burgeoning real estate agency industry in Beijing, China. The obvious potential for interaction between the information superhighway and professional real estate services suggests that the design and services of real estate agency could be in a period of structural change. A major concern among real estate companies is the substitution of online services for those traditionally delivered personally. However, in spite of general fears concerning redundancy among real estate professional in Beijing, the results of this study suggest that advancements in information technology actually support the building up of competitive advantages for firms. Further, it appears that the Internet acts as a bridge linking up not only customers to suppliers, but also allows real estate agencies to diversify and spin off additional forms of business.

The dissertation titles and abstracts contained here have been condensed and are published with permission of University Microfilms, Inc., publishers of Dissertation Abstracts International (copyright 1990 by University Microfilms, Inc.), and may not be reproduced without their prior permission. Copies of most of the complete dissertations may be obtained by addressing your request to:

UMI

300 N. Zeeb Road

Ann Arbor, MI 48106

Or by telephone (tool-free) 1-800-521-3042.

* Indicates dissertations in which only a chapter or a significant part of the work is devoted to government policy and planning, real estate business and industry issues, property, contract and transaction types, real estate decision-making processes, market analysis, methodological and theoretical issues, or other real estate related issues.

Copyright American Real Estate Society 2005

International Herald Tribune (Mar 23, 11:53 AM)  Did Greek accountants miss a trick? It is possible that last week, in posting the highest budget deficit recorded so far by any euro-zone country, Greece has simply offered a more honest appraisal of its financial woes than the other 11 countries using the European common currency.

Over the past decade, European governments have refined techniques that mask the extent to which they spend beyond their means. This week, they came up with a new one: giving Germany leeway to take its reunification costs into account even though West and East Germany officially merged 15 years ago. So far, investors have not noticeably penalized governments for such activity. The euro, which the deficit rules are intended to protect, has strengthened against the dollar even as fiscal discipline has weakened. But there seems to be an increasing danger, economists say, that debt traders, the so-called vigilantes of the bond market, will punish European governments for giving unrealistic assessments of their accounts. Already, there are signs of that starting to happen. On Friday, reference rates widened for Greece and for Italy, which also got bad deficit news from the EU statistics office, showing that markets have less faith than before in those countries' ability to manage their finances. Economists warn that this could lead to higher interest rates for everyone in the euro zone if Europe's central bank fears that investors might pull out of Europe, or if it sees higher inflation on the horizon. "The volatility is relatively significant and a strong reminder that deficits can matter," said Herve Clos, an interest rate strategist at BNP Paribas in London. Traders are now focused on whether the rate movement, which means that governments in Rome and Athens must pay more on their debt, will spread to German and French bonds, Clos said.

"Studies show that most euro-zone countries have resorted to a degree of creative accounting at one time or another," said Laurence Boone, a director at Barclays Capital in Paris. Budget overruns in Greece and Italy, as well as pressure from France and Germany to loosen the rules, suggest the need for "independent fiscal commissions that would properly investigate public accounts in the same way as auditors in the private sector," she said.

The driving force behind creation of the euro was that a fixed currency would lower costs and remove exchange-rate uncertainty for businesses within Europe. Political agreement was needed to keep spending among the member states in check and ease fears that a maverick state could trigger inflation.

Lately, countries have been using one-time events to help improve their accounts. The most spectacular example was the sale of next- generation mobile phone licenses. In 2000 alone, euro-zone governments raked in 71 billion, now worth about $94.5 billion, for allowing companies like Deutsche Telekom to carve up the airwaves for high-speed Internet access. That money was "manna from heaven," said Vincent Koen, an economist at the Organization for Economic Cooperation and Development. He calculates that the great telephone sale knocked 1.1 percentage point off euro-zone countries' average deficit, as a percentage of gross domestic product, in 2000. He also notes more serious gimmicks, such as booking cash from sales of state industries but not fully reflecting continued obligations to pay pensions to retiring workers.

That is what France did in 1997, when the government agreed to cover France Telecom's pensions as a way to entice investors to take a stake in the company. The sale allowed France to knock half a percentage point off its deficit rate.

This year, France plans to repeat the process, partly privatizing Electricite de France and Gaz de France, using the proceeds to increase its revenue by around 7 billion and shaving 0.4 percentage point off its deficit rate. Meanwhile, economists say, the full picture of France's long-term obligations to retiring workers probably will not figure in the calculations. Another favored tactic of hard-pressed governments is to book revenue they do not yet have. Koen says Italy counted future revenue from the national lottery in 2001, wiping 0.2 percentage point off its deficit number.

Not all the euro zone's forecasting errors are due to such maneuvers. The economic downturn that started in 2001 contributed to widening government deficits and deepening national debts. But economists are convinced that such sluggishness cannot entirely explain the discrepancies, and many now fear that accounting sleights of hand will only become easier to perform with the currently proposed revisions to the European Union's Stability and Growth Pact.

"Many instances of government accounting have been abnormal," said Olivier Gasnier, an economist at SG Paris. "It now looks like governments will have lots more possibilities to avoid taking painful decisions."

Greece's revised deficit for 2004 came in at 6.1 percent of gross domestic product, or just over twice the 3 percent EU limit. The Italian deficits for 2003 and 2004 could also be revised above 3 percent of GDP, Eurostat, the EU statistics agency, said on Friday.

Journal of Real Estate Literature (Mar 02, 03:28 AM)  Abstract

A house is made up of many characteristics, all of which may affect its value. Hedonic regression analysis is typically used to estimate the marginal contribution of these individual characteristics. This study provides a review of recent studies that have used hedonic modeling to estimate house prices. The findings indicate that slanted versus flat roof, sprinkler system, garden bath, separate shower stall, double oven and gated community positively affect selling price while not having attic space, living in an earthquake zone, proximity to a hog farm, proximity to a landfill, proximity to high voltage lines, corporate-owned properties, percentage of Blacks or Hispanics in an area and properties that require flood insurance negatively affect selling price.

Introduction

Home is defined as the social unit formed by a family residing together. A house, on the other hand, is a bundle of characteristics such as size, quality and location. For a number of reasons, valuing a house is difficult. Being a physical asset, each house has its own specific location. Also, a house is a long-term durable good with a long life, which means that houses with substantially different ages can exist at the same time in the same market. Each house has its own unique set of characteristics that affect value. In addition, certain housing characteristics may be valued differently across different geographical areas. For example, a garage may have a greater value in a colder climate whereas a swimming pool may have a greater value in a warmer climate.

In addition to the problem of the presence of different characteristics across houses, homebuyers possess unique utility functions causing them to value characteristics differently. For example, one homebuyer may place a greater value on hardwood floors than another buyer. Thus a certain house with a given set of characteristics may be valued differently by different buyers.

All these factors suggest that housing is not a homogeneous good. Different bundles of characteristics make valuation difficult. The fact that buyers may value individual characteristics differently further complicates the process. Nonetheless, a substantial body of historical research has attempted to explain the value of housing by valuing its individual components. The typical method used to do this is the hedonic pricing model, because it allows the total housing expenditure to be broken down into the values of the individual components. One caveat in using hedonic pricing models is that the results are location-specific and are difficult to generalize across different geographic locations. Because of this, hedonic pricing models are generally used to gain insight into the workings of a particular market. On the other hand, comparing studies across areas may at least establish those characteristics that are consistently valued (either positively or negatively) by homebuyers.

Comparing studies that use hedonic models is complicated by the fact that studies define and measure variables differently. For example, one study may measure bedrooms as simply the number of bedrooms whereas another study may use binary variables (a dummy variable if the house has one bedroom, a second dummy variable if the house has two bedrooms, etc.) The comparability of previous hedonic pricing studies is also complicated and/or limited because of different empirical specifications. Typically, hedonic pricing equations have been estimated using linear or semi-logarithmic models.

Even with its problems, however, hedonic modeling can be (and has been) useful in addressing a number of issues in housing valuation. It has been used in valuing not only the obvious components such as square footage, bathrooms, etc. but has also been useful in measuring the effect of other issues such as school quality, proximity to a landfill or high voltage lines, and the effect of non- market financing.

Malpezzi, Ozanne and Thibodeau (1980) compare housing to a bundle of groceries in that some bundles are bigger than others and contain different items. Housing is a bundle of bedrooms, bathrooms, and other amenities and the particular bundle of a house distinguishes it from other houses. However, unlike groceries, the price of individual features cannot be directly observed. The usefulness of hedonic modeling is to price these individual features by using multiple regression analysis on a pooled sample of many dwellings. As these authors point out, using this model assumes that consumers derive utility (and therefore value) from various housing characteristics and that the value of this utility can be priced. In housing consumption, consumers will pursue maximization of utility within their budget constraint.

The hedonic model generally takes this form:

Price = f(Physical Characteristics, Other Factors).

This says that the price of the house is a function of its physical characteristics (square footage, bathrooms, age, location, various amenities, etc.) and other factors such as school quality and external factors. The regression estimates give the implicit prices of each variable or characteristic. A complication is that these values are not likely to be the same for all price ranges of houses. For example, the value added of a bedroom might be greater for a $500,000 house than for a $100,000 house. For this reason, the hedonic pricing model is often estimated in semi-log form with the natural log of price used as the dependent variable. Then the coefficient estimates allow one to calculate the percentage change in price for a one-unit change in the given variable. The remainder of the paper reviews recent studies that have estimated hedonic pricing models. After a brief discussion of the early history of hedonic models, the review covers primarily studies that have been published over the last decade. Approximately 125 studies were examined from a number of different journals including the Journal of Real Estate Research, Journal of Real Estate Finance and Economics, Real Estate Economics, Journal of Urban Economics, Land Economics and The Appraisal Journal. The major objectives are to determine variables that are consistently significant in explaining price, compare the coefficients of some variables by geographic location, and examine the relationship between house price and time- on-the-market.

The Theoretical Development of Hedonic Pricing Models

In his 2003 paper, Malpezzi presents an excellent review of the theoretical development behind hedonic pricing models. As he points out, the hedonic model is a way to estimate the value of individual characteristics of the house. Hedonic equations have also been used to measure the effect of various factors of special interest on house prices.

Hedonic models are typically estimated as single-stage equations. That is, the model simply estimates the effect of characteristics on price and does not examine the structural parameters of the individual characteristics. Hedonic models also are estimated various ways regarding the dependent variable, the house price. Price may be specified as an absolute amount (unlogged) or as a logged variable. The most typical model structure historically has been the semi-log form, with the price specified in natural logs and regressed against unlogged independent variables. This allows for variation in characteristic prices across different price ranges within the sample.

Theoretical Underpinnings of the Hedonic Model

As Malpezzi (2003) discusses, the hedonic model arises because of a heterogeneous housing stock and heterogeneous consumers. Not only does each house contain different housing characteristics, but those characteristics may be valued differently by different consumers.

Econometrics has always faced the problem of identification (i.e., distinguishing between supply and demand). In the typical supply and demand model, the price of the good is exogenous and the consumer, being a price-taker, decides how much to consume based on the price. In a nonlinear hedonic model where the price varies with the quantity, the consumer chooses both a quantity and price.

Specification Problems

Due to the difficulty in the practical application of hedonic models, the functional form of the model and the variables included in the model can often seem ad hoc. This can be traced back to the original papers of Lancaster (1966) and Rosen (1974) that present models of housing characteristics but do not specifically identify what those are. In practical application, the dependent variable in the model is usually a recent selling price, standing as a proxy for the value of the house. Using the observed price is generally thought to better minimize bias as compared to other measures such as an owner's self-assessment.

There is almost a limitless number of independent variables that can be included in the model. The high correlation of some of these variables with each other can create estimation problems even if all the variables are not included in the model. For example, a location variable may appear to be highly significant in the model but may actually be reflecting something else, such as school quality. Because of this, interpretation of the individual coefficients can be more difficult.

Studies have wrestled with the problem of correct functional form. Follain and Malpezzi (1980) found that the semi-log specification hassome advantages over the linear form. Some of these are: (1) it allows for variation in the dollar value of each characteristic; (2) the coefficients can be easily interpreted as the percentage change in the price given a one-unit change in the characteristic; and (3) the semi-log model helps minimize the problem of heteroscedasticity.

The Early History of Hedonic Models

Identifying the "father" of hedonic modeling is not easy. In his review, Malpezzi (2003) points out that a study by Court (1939) is often cited as the beginning of hedonic models, although this study actually developed a hedonic price index for automobiles and not for housing. As Goodman (1998) discusses, although popularized by Griliches (1958) in his work on the demand for fertilizer, the term "hedonic" dates back to the 1939 Court article and that Court is generally cited in most articles. Goodman argues that, as a hedonic price analysis, Court's work stands up quite well under contemporary standards. Court, as an economist for the Automobile Manufacturers' Association from 1930 to 1940, recognized that a single variable could not explain automobile demand. His hedonic model to explain price included three variables: dry weight, wheelbase and horsepower. His modeling would be considered modern in that he used a semi-log form, accounted for cars that actually sold and estimated the models over different time periods.

A 1999 study by Colwell and Dillmore, however, points out that it is highly unlikely that Court is the original source of hedonics. Seventeen years prior to the Court study a monograph by Haas (1922a) at the University of Minnesota applied a hedonic model to estimate the value of farmland. Also, a 1926 study by Wallace examined the value of farmland in Iowa. Colwell and Dillmore connect Court to Haas (and Wallace) this way: Court developed his idea for a hedonic model from discussions with the chief of the Bureau of Labor Statistics who probably knew of the work by Wallace and maybe the work by Haas.

Later studies important to hedonic modeling are Lancaster (1966) who provided a microeconomic foundation for estimating the value of utility-generating characteristics (with a natural application to housing) and Rosen (1974) who focused on characteristics with less emphasis on utility and more on price determination. Rosen's work provided the basic foundation for nonlinear hedonic pricing models.

The Relationship between Selling Price and Time-on-the-Market

Typically, a seller's goal is to sell the house at the highest possible price in the shortest possible time. These two objectives are generally reconciled with the setting of the listing price. A listing price that is too high may have the effect of both lengthening the selling time and limiting the pool of potential buyers. Setting the listing price too low may minimize the selling time but may also result in a selling price lower than what otherwise could be attained.

Since selling price and time-on-the-market tend to be interactive variables, some studies have estimated simultaneous or two-stage models to capture the effect. Specifying such models for selling price and time-on-the-market is difficult since they tend to be very similar. This section discusses some recent studies that have followed this procedure.

When time-on-the-market is included and statistically significant in the selling price equation, it is generally negative. This indicates that a longer selling time results in a lower selling price. When selling price is included in a time-on-the-market estimation, the results are much less clear. In some cases, a higher selling price leads to a longer selling time whereas in others, a higher selling price results in a shorter selling time.

The following are some recent studies that have examined the relationship between selling price and time-on-the-market. Jud, Seaks and Winkler (1996) examine the impact of brokers, brokerage firms and marketing strategy on time-on-the-market using a duration model. They find duration dependence to be positive, indicating that the probability of selling the property increases with time-on-the- market. Their results show that higher listing prices result in a longer time-on-the-market whereas reducing the listing price decreases time-on-the-market. The results also show that atypical homes have a longer time-on-the-market.

A 1996 study by Forgey, Rutherford, and Springer estimates a two- stage least squares model of house prices and time-on-the-market. Their results show that housing liquidity depends on market participants' search effort, which is determined by market conditions, physical characteristics of the property, the size of the brokerage firm and listing price. They find that houses with higher liquidity sell for higher prices and that selling prices increase with sellers' search effort.

In testing real estate agents' comments, Haag, Rutherford and Thomson (2000) estimate Ordinary Least Squares (OLS) models for selling price and time-on-the-market. They find that time-on-the- market has a significant negative effect on selling price. Their time-on-the-market equation includes list price, which is shown to be not significant. They find that motivated sellers accept lower selling prices but have a longer selling time and that updated properties produce a higher selling price and a shorter selling time. However, they find that some other improvements such as new paint and roof work decrease price and increase time-on-the-market.

In examining exclusive agency and exclusive right to sale contracts, Rutherford, Springer and Yavas (2001) estimate a simultaneous equations model for selling price and time-on-the- market. The first stage regresses time-on-the-market against various factors and the second stage regresses selling price against a similar set of factors. The results show a positive relationship between selling price and selling time and that exclusive agency listings and builder-owned listings have a shorter selling time than exclusive right to sale listings and owner-held properties. However, exclusive agency listings are associated with lower selling prices while builder-owned properties have higher selling prices. Another 2001 study by Johnson, Salter, Zumpano and Anderson examines the effect of artificial stucco on house prices and selling time. They first use a probit model to relate the presence of artificial siding to explanatory variables. Next, they estimate the selling price using typical explanatory variables with artificial stucco included. Then, they use duration modeling to measure the effect of artificial stucco on selling time. Their results suggest that properties with artificial stucco sell at a premium although the selling time is longer.

Knight (2002) uses a maximum-likelihood probit model and information on price changes during a home's marketing period to examine the selling price and time-on-the-market relationship. He finds that it is expensive to overprice the house initially. Homes that had large percentage adjustments in listing price not only had longer selling times but also ultimately sold at lower average selling prices. A 2003 study by Anglin, Rutherford and Springer also examines the importance of setting the initial listing price and the marketability of the property. The paper measures the degree of overpricing as the percentage difference between the actual listing price and the expected listing price. Their theoretical models shows that there is no direct tradeoff between selling price and selling time but that market conditions affect how the expected selling price and the expected selling time vary jointly based on the initial listing price. They find that increases in the listing price increase time-on-the-market. Their results also show the importance of changing marketing conditions on selling time.

These studies illustrate the difficulty in specifying the relationship between selling price and time-on-the-market. Because of this, most studies involving hedonic pricing models have chosen to ignore these problems by estimating a simpler OLS model, although time-on-the-market is sometimes included as an explanatory variable.

Review of Recent Hedonic Pricing Model Studies

This section discusses some studies published over the last decade that have used hedonic modeling. Approximately 125 were examined.

The Top Twenty Characteristics

Exhibit 1 shows the top twenty characteristics that have been used to specify hedonic pricing equations. The exhibit shows the total number of times a characteristic has been used and the number of times its estimated coefficient has been positive, negative, or not significant. As seen, age shows up most frequently in hedonic models and typically has the expected negative sign although it is seen to be positive and not significant in some studies. Square footage is the next most used characteristic and typically has the expected positive effect on selling price. Other characteristics that appear frequently are garage, fireplace and lot size. Each typically has the expected positive effect. Garage never has a negative sign but it has been not significant in a number of studies. Fireplace shows up negative in only a few studies and lot size never shows up negative.

Other characteristics that show up frequently are bedrooms, bathrooms, swimming pool and basement. Bedrooms show up negative in some studies but bathrooms almost never do. A swimming pool never has a negative effect on selling price although it has been not significant in some studies. Basement is usually positive but it has been shown to be negative or not significant in some studies.

Time-on-the-market shows up in eighteen studies and shows to be not significant most often. When it is significant, it is negative to positive eight to one. This tends to support the argument that the longer a house is on the market, the more willing the seller is to concede o\n the selling price. The opposing theory is that the longer a house in on the market, the more likely the seller is to find the one buyer willing to pay a higher price.

Other characteristics that have been commonly used to specify selling price include distance variables, brick exterior, the number of stories and a time trend. Brick exterior is consistently positive but the other variables have different signs. This could be at least partially a function of the method of specification.

Typical Characteristics by Category

Exhibit 2 shows the top five characteristics by eight categories. The most common structural characteristics are lot size, square feet, age, number of bathrooms and number of bedrooms. All characteristics except age typically have the expected positive sign.

Internal features that appear most frequently are full bathrooms, half bathrooms, fireplace, air-conditioning, hardwood floors and basement. These characteristics rarely have negative coefficients although they sometimes do appear not significant.

External features used most frequently in explaining selling price are garage/garage spaces, deck, pool, porch and carport. None of these characteristics had negative coefficients except carport. One study reported a negative sign on carport.

Exhibit 1

The Twenty Characteristics Appearing Most Often in Hedonic Pricing Model Studies

Characteristics provided by the natural environment consistently have a positive effect on selling price. These include lake front or view, ocean view and a "good view."

Environmental characteristics created by neighborhood or location include location, crime, distance, golf course and trees. Location is generally measured as a neighborhood identifier, zip code, etc. and typically has a positive effect on price. Crime is usually measured as the crime rate for a given area and typically has a negative effect on price. Distance is typically measured as distance from the city center and the estimated coefficient has been both positive and negative. Golf course is usually measured as being on or near a golf course and, as expected, consistently has a positive effect on selling price. Trees usually mean a wooded lot versus an open lot and is also seen to consistently have a positive effect on price.

Environmental characteristics resulting from public services include the school district, percentage minority in school district and access to a public sewer. In general, the consistent significance of the school district variable indicates that perceived school quality has a significant effect on house prices. An increasing minority population in schools has a consistent negative effect on selling price.

Exhibit 2

The Top Five Characteristics by Category from Hedonic Pricing Model Studies

Exhibit 2

The Top Five Characteristics by Category from Hedonic Pricing Model Studies

Marketing, occupancy and selling characteristics include the assessor's judgment of quality, the assessed condition of the house, whether the house is vacant at the time of sale, whether the house is owner-occupied, the time-on-the-market and a time trend. Measures of quality and condition have a positive effect on price. Being owner-occupied also has a positive effect. Being vacant and for sale is not good for the selling price. Generally, time-on-the-market has a negative effect and the time trend variables have been not significant.

The last category, financial issues, includes types of financing (FHA, VA, favorable), whether a house is in foreclosure and property taxes. Studies show that houses with FHA or VA financing sold for less than houses with conventional financing. Being in foreclosure also has a negative effect on price. Studies on property taxes are mixed. One study shows a negative effect while two studies show property taxes are not significant.

All Characteristics by Category

Exhibit 3 presents a comprehensive list of the characteristics that have appeared in hedonic models. As seen, a large of number of diverse variables has been used to define selling price. This section discusses some interesting variables that have not been previously discussed. For example, structural characteristics such as roof type, having a sprinkler system or not having attic space affect selling price. Interior amenities such as having a garden bath, a separate shower stall and a double oven in the kitchen have a consistent positive effect on price. On the other hand, having a fence has not been shown to affect price.

Natural environmental characteristics related to earthquake magnitude or earthquake zones have a negative effect on selling price while living in a gated community has a positive effect. One study, examining the effect of proximity to a hog farm found that selling price decreases as the manure index increases.

Interesting neighborhood characteristics include proximity to a metro station, distance to a landfill and proximity to a religious building. Prices are shown to not be higher for houses closer to a metro station. Likewise, selling prices increase with distance from a landfill. Being located close to a religious building has been shown to both increase and decrease price.

One study shows that being located in proximity to high voltage power lines reduces selling price while the percentage of gifted students in the school increases price.

Studies have shown that houses that are corporate owned have lower selling prices. Studies also show that selling prices decrease as the percentage of Blacks or Hispanics in the area increases.

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category form Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Exhibit 3

Characteristics by Category from Previous Studies

Studies measuring financing characteristics show that owner financed homes sell for less. Also, houses that require flood insurance sell for less.

Comparing Coefficient Estimates by Geographical Area

Exhibit 4 shows coefficient estimates for selected characteristics by geographical area. The coefficients are from studies that used semi-log models and were consistent in their measurement of the characteristics.

As can be seen, estimations are somewhat consistent across areas. For example, the coefficients for square feet do not have a great deal of variation across regions. They are normally in the 0.0004 to 0.0007 range. Square footage seems to have the greatest effect on price in the Southwest where, on average, each additional square foot adds about 0.05% to value. The lowest average effect seems to be in the Midwest. The coefficients for the Southeast and West seem to average in the 0.045% range. Remember that this coefficient is measuring the percentage change in price with each additional square foot. Likewise, the coefficients for lot size are somewhat consistent across geographical regions.

Age consistently has a negative effect on selling price. There is some variation in the coefficient estimates but there does not seem to be a discernable pattern of differences across regions. The average effect of age on value seems to be about 1% or less.

Bathrooms generally have a significant effect on selling price. Studies discussed here that have included the number of bathrooms tend to be limited to Northeast and Southwest data. The bathroom coefficient for the Northeast falls in the 0.13 - 0.18 range indicating that each additional bathroom adds 13% to 18% to the price of the house. The coefficients for the Southwest have a wider variation ranging from 0.015 to 0.18. The average effect on price is in the 10% to 12% range.

As with bathrooms, studies included here that have estimated the effect of bedrooms are limited to the Northeast and Southwest. The effect of an additional bedroom seems to be somewhat greater in the Northeast than in the Southwest.

A number of studies have included fireplace in hedonic models. The presence of a fireplace consistently has a significant positive effect on selling price. Casual observation shows that a fireplace generally affects selling price by a range from 6% to 12% and this effect is consistent across regions, except for the West. The estimated coefficients for the studies from the West seem to be, on average, less than for studies from other areas.

Central air-conditioning generally is significant and has a positive effect on price. Several studies from the Northeast produce models where air-conditioning is significant with an average effect on price in the 7% range with coefficients ranging from 4% to 9%. Several studies from the Midwest also show air-conditioning to be important with the effect in a higher range from 6% to 13%. Although fewer in number, studies from the Southeast and West show air- conditioning to be important with the effect on selling price in the 12% and 3% range, respectively. The effect on price in the Southwest is in the 15% to 19% range.

Exhibit 4

Coeffecient Estimates from Hedonic Pricing Models for Selected Characteristics by Geographical Area

Exhibit 4

Coeffecient Estimates from Hedonic Pricing Models for Selected Characteristics by Geographical Area

Basement is seen to have a significant positive effect on selling price. A \study from the Southeast shows that a basement adds about 12% to value. Several studies from the Midwest show that a basement affects value in the 12% to 16% range. A couple of studies from the West show a basement adds from 6% to 14% to house price.

Swimming pool is an often-included characteristic in hedonic models. It is generally positive and significant. In the Northeast, a pool adds 4% to 6% to value. In the Southeast, the effect is in the 5% to 10% range. The effect in the Midwest is similar to the effect in the Northeast with the average effect on value about 6%. A pool seems to affect price the most in the Southwest, where studies show the effect to be between 8% and 13%. A pool is also important in the West but the effect on value is less consistent than other areas. In the West, the average effect on value ranges from 5% to 13%.

Garage is generally specified in pricing models as the number of garage spaces. This characteristic is included often and has a significant positive effect on selling price. In the Northeast, most studies show that each garage space adds between 6% and 12% to value. Garage spaces are priced similarly in the Southeast with the value added between 6% and 14% of selling price. In the Midwest, the effect on value is between 4% and 12% while the effect in the Southwest is between 6% and 11%. Garage space seems to add the least to value in the West where a number of studies show a 1% to 5% addition to value.

Some studies have attempted to examine the importance of schools by including some school identifier. The typical measure is to identify the home's school district. These measures consistently show perceived school quality to be important. The estimated coefficients are sometimes positive and sometimes negative depending on perceptions. Overall, the effect on price seems to range between 3% and 18%.

The results from the recent study by Sirmans and Macpherson (2003) examining the value of housing characteristics are given at the bottom of Exhibit 4. In general, these results are consistent with the results from previous studies.

Conclusion

This study was made up of several parts: the early history of hedonic modeling was discussed, the relationship between selling price and time-on-the-market was discussed and recent studies using hedonic modeling were reviewed. Although Court (1939) is often viewed as the father of hedonic modeling, earlier hedonic studies that examined the value of farmland date back to Haas (1922a,b) and Wallace (1926). Later studies developed the microeconomic foundation for estimating the value of utility-generating characteristics (Lancaster, 1966) and for nonlinear hedonic pricing (Rosen, 1974).

Selling price and time-on-the-market were seen to be interactive making specification of these variables in a simultaneous framework difficult. Time-on-the-market was seen to be generally negative when estimated in a selling price equation. This implies that a longer selling time results in a lower selling price. When selling price is included in a time-on-the-market equation, the results are less clear. Some models show that houses with higher selling prices sell faster while other studies show that houses with higher selling prices have longer selling times. Studies were discussed that show listing price as a major factor in time-on-the-market.

Using the recent literature, the characteristics that are most frequently included in hedonic pricing models were identified. These include lot size, square feet, age, the number of stories, the number of bathrooms, the number of rooms, the number of bedrooms, fireplace, central air-conditioning, basement, garage, deck, pool, brick exterior, distance to CBD, time-on-the-market and a time trend. These variables generally have the expected signs although in some instances they are not significant. Due to the large number of variables, categories were created and the top five characteristics from each category were identified. The categories and characteristics are: structural features: lot size, square feet, age, number of bathrooms and number of bedrooms; internal features: full baths, half baths, fireplace, air-conditioning, hardwood floors and basement; external features: garage spaces, deck, pool, porch, carport and garage; natural environmental features: lake view, lake front, ocean view and good view; neighborhood and location: location, crime, distance, golf course and trees; public services: school district, percentage of school district minority and public sewer; marketing, occupancy and selling factors: assessor's quality, assessed condition, vacant, owner-occupied, time-on-the-market and time trend; and financing issues: FHA financing, VA financing, foreclosure, favorable financing and property taxes. Most of the characteristics have a positive effect on selling price. Those characteristics that have had a negative effect on price include age, crime, percentage of school district minorities and vacancy.

Some other interesting variables that are seen to affect selling price were discussed. Those that have a positive effect include slanted versus flat roof, sprinkler system, garden bath, separate shower stall, double oven and gated community. Some other characteristics that have a negative effect on selling price include not having attic space, living in an earthquake zone, proximity to a hog farm, proximity to a landfill, proximity to high voltage lines, corporate-owned properties, percentage of Blacks or Hispanics in an area and properties that require flood insurance.

Estimated coefficients for selected characteristics were compared across geographical regions. The results from the recent Sirmans and Macpherson (2003) paper entitled "The Value of Housing Characteristics" were compared to these results and found to be consistent. Some major conclusions were:

* The effect of square footage on selling price does not have a great deal of variation across regions. The greatest effect was in the Southwest and the lowest average effect is in the Midwest;

* The effect of lot size is also somewhat consistent across regions;

* Age is consistently negative and the effect on price seems to be consistent across regions;

* For studies primarily from the Northeast and Southwest, each additional bathroom seems to affect selling price in the 10% to 12% range;

* For studies limited to the Northeast and Southwest, the effect of bedrooms on price seems to greater in the Northeast than in the Southwest;

* Fireplace has a positive effect on selling price in the 6% to 12% range and seems to be consistent across regions, except for the West;

* Central air-conditioning is consistently important in all regions with the greatest price effect in the Southwest;

* Basement adds significant value to selling price in most studies in the 12% to 16% range;

* Swimming pool is a consistently significant characteristic with the effect on price being the greatest in the Southwest and Southeast;

* The value of a garage is consistent across regions in the 6% to 12% range; and

* Perceived school quality consistently has a significant effect on selling price.

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