text:
Here Are Your MLB All-Star Game Starters
The MLB announced starters for the All-Star game while you were watching the first half of the Women's World Cup Final. These are the starting lineups as determined by the fan vote: »
The MLB announced starters for the All-Star game while you were watching the first half of the Women's World Cup Final. These are the starting lineups as determined by the fan vote: »
Carli Lloyd is singlehandedly destroying Japan, having earned a hat trick just 15 minutes into today's Women's World Cup final with a long-range bomb that caught the keeper off her line. »
Carli Lloyd has already scored twice in the first five minutes of tonight's Women's World Cup final against Japan, both off set plays. This is the start of which U.S. fans could only dream. »
Here we go. The United States women's national team is taking on Japan in the World Cup final. Follow along as we yell and jingoistically babble our way through the game while the Americans attempt to Do The Whole Shit for the first time since 1999. »
Fox's Women's World Cup coverage has been hit or miss, but this intro featuring Academy Award-winning actress Helen Mirren reading Shel Silverstein's "Where the Sidewalk Ends" is simply outstanding. That's Explosions In The Sky's "Your Hand In Mine" as the music bed. »
Sixth-man extraordinaire Lou Williams is headed to Los Angeles after signing a three-year, $21 million contract with the Lakers, reports Yahoo's Adrian Wojnarowski and RealGM's Shams Charania. »
Jason Pierre-Paul seriously injured his hand in a Saturday night fireworks accident, according to media reports. At least two people reported the Giants defensive end acquired an entire truck full of fireworks: »
Packers tight end Andrew Quarless was arrested by Miami Beach police early Saturday morning on a misdemeanor charge of firing a firearm in public after cops say he fired two shots into the ground after a mild altercation. »
"From the time I was playing Junior hockey for the Sarnia Sting to my first year in the NHL with the Los Angeles Kings, I would start drinking the second I woke up on my days off. I smoked marijuana every single day. By the time I was 19 years old, I was using cocaine weekly," Rich Clune writes in The Players' Tribune… »
If you're former second baseman Chuck Knoblauch and you want to engage in some weird Twitter beef, live your life, man. But if you're former second baseman Chuck Knoblauch, and people are sick of your nonsense after you stopped being able to throw to first base and have had multiple domestic violence incidents since… »
So there's one free agent we haven't heard much from this offseason, and it's none other than LeBron James! James opted out of his contract with the Cleveland Cavaliers, and is technically free to sign with any team in the league at this very second. »
The Los Angeles Lakers are working on a trade to acquire center Roy Hibbert from the Indiana Pacers, reports ESPN's Marc Stein and Ramona Shelburne. The parameters of the trade haven't been finalized, but the Lakers will likely absorb Hibbert into their cap space while sending draft picks in return. »
Here are the best of today's deals. Get every great deal every day on Kinja Deals, follow us onFacebook and Twitter to never miss a deal, join us on Kinja Gear to read about great products, and on Kinja Co-Op to help us find the best. »
Timmy Hansen overtook Mattias Ekström on the final corner to claim the checkered flag at today's WorldRX of Sweden championship, and the finish was almost too much for the FIA announcing team to handle. "You have to excuse my screaming! He's done it! Epic!" »
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The Portland Trail Blazers have fired assistant coach Kim Hughes, a few days after Hughes told an Indiana TV station LaMarcus Aldridge wouldn't be returning to the team, according to The Oregonian. »
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Welcome to Boozinette. This is the Equal Opportunist. »
Today's world-class Peachtree Road Race came down to a photo finish as American Ben Payne lost out to British former Olympian Scott Overall thanks to a brief celebratory hesitation just shy of the finish line. »


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What we're talking about
Updated: December 28, 2012, 12:12 PM ET
Friday, Adnan Virk and Chris Cotter host from the Bristol, CT studios. They'll welcome ESPN NFL analyst Tedy Bruschi (1:30 p.m. ET), ESPN NBA analyst Bruce Bowen (2:30), ESPN.com Heat Index writer Brian Windhorst (2:45) and ESPN 980's Kevin Sheehan (3:30).
Today's main topics:
• NFC East crown on the line Sunday
• Phil Jackson to the Nets?
• NFL coaches on the hot seat
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subset: commoncrawl


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Weekly Wrap: GDP and Greece
Kai Ryssdal
Jul 2, 2015 Catherine Rampell and Felix Salmon join Kai Ryssdal to recap the week in business and finance.
Weekly Wrap: Greece, Federal Reserve and consumerism
Adriene Hill
Jul 2, 2015 Linette Lopez and Sudeep Reddy join Adriene Hill to recap the week in business and finance.
The bond market does what it wants
Kai Ryssdal
Jun 17, 2015 The 10-year Treasury note didn't care much about the Fed's statement.
Three things to know from the Fed's press conference
Nancy Marshall-Genzer
Jun 17, 2015 First up: No interest rate hike, for now.
The last time the Fed raised interest rates
Tony Wagner
Jun 18, 2015 2006 was a very different time... but not too different.
Helping global trade's 'losers'
Ashley Gross
Jun 16, 2015 House's vote puts worker-retraining program in jeopardy.
China helps 'Jurassic World' devour the box office
Adriene Hill
Jun 16, 2015 The action film's opening sets an international record.
Marketing to the Chinese LGBT community
Adriene Hill
Jun 9, 2015 A subsidiary of Alibaba is sponsoring same-sex couples coming to the U.S. to wed.
Weekly Wrap: Jobs report, Federal Reserve and Grexit
Kai Ryssdal
Jun 5, 2015 John Carney and Leigh Gallagher join Kai Ryssdal to recap the week in business and finance.
China may join the TPP...but it'll take a while
Kai Ryssdal
Interview by
Produced by
Jun 8, 2015 President Obama announced that the U.S. is in talks with China about participation in the trade deal.


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Leave MortgageMiser a message to find out more.
Posted 12/07/2009 10:50:10 EST
To suggest Newman is in any worse shape than Mitchell or Hillside is ludicrous and wrong. The reality, as Rick points out, is that the budget for the Newman renovations is excessive and obnoxious. As more »
Posted 10/06/2009 09:41:13 EDT
With all the hype and concern about big banks getting bigger and the demise of the secondary mortgage market, I started to believe it and decided to open a "construction-to-permanent" loan with Needha more »
Posted 10/06/2009 09:00:58 EDT
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MindsetRandom House Publishing Group 2006; US$ 16.00
World-renowned Stanford University psychologist Carol Dweck, in decades of research on achievement and success, has discovered a truly groundbreaking idea?the power of our mindset. � Dweck explains why it?s not just our abilities and talent that bring us success?but whether we approach them with a fixed or growth mindset. She makes clear why praising... more...
Flesh and SpiritPenguin Publishing Group 2007; US$ 7.99
"Chilling...well-written." Publishers Weekly "Terrific." -- Midwest Book Review more...
Breath and BonePenguin Publishing Group 2008; US$ 7.99
The mesmerizing conclusion to the fantasy epic Addicted to an enchantment that turns pain into pleasure?and bound by oaths he refuses to abandon?Valen risks body and soul to rescue one child, seek justice for another, and bring the dying land of Navronne its rightful king. more...
Revolutionary MothersKnopf Doubleday Publishing Group 2007; US$ 16.00
The American Revolution was a home-front war that brought scarcity, bloodshed, and danger into the life of every American. In this groundbreaking history, Carol Berkin shows us how women played a vital role throughout the conflict. The women of the Revolution were most active at home, organizing boycotts of British goods, raising funds for the... more...
Billionaire Doctor, Ordinary NurseHarlequin 2009; US$ 5.04
The overhead lights in the observation ward were off as Annie Jameson swiped her ID card and raced in through the rear entrance of the accident and emergency department with a surprising ten minutes to spare before her late shift started. Eight empty beds lay waiting to be filled�which was good news. The theory was that the obs ward should be cleared... more...
Guardians of The KeepPenguin Publishing Group 2004; US$ 7.99
"A brilliant writer."? BookBrowser "Powerfully entertaining."? Locus "Epic fantasy on a gigantic scale...Carol Berg lights up the sky with a wondrous world."? Midwest Book Review more...
Son of AvonarPenguin Publishing Group 2004; US$ 7.99
"Berg greatly expands her world with surprising insights."- Denver Post "Epic fantasy on a gigantic scale...Carol Berg lights up the sky with a wondrous world."- Midwest Book Review � more...
Daughter of AncientsPenguin Publishing Group 2005; US$ 8.99
In Avonar, Gerick investigates the ancient king D'Arnath's own daughter, held captive by the Lords of Zhev'Na for a thousand years-or so she claims. Entangled in bonds of love, family, and secrecy, Gerick unravels the mysteries of ancient kings, ancient evil-and the dreadful truth of his own destiny. more...
The Soul WeaverPenguin Publishing Group 2005; US$ 7.99
The evil Lords of Zhev'Na kept Gerick captive for months. Although his parents rescued him, he remains tormented by his experience-and mistrusted even by those who love him. Accused of treason, Gerick flees and takes refuge in a magical realm full of outcasts, where he will discover how to use his own magical talent-soul weaving-to save his people... more...
RevelationPenguin Publishing Group 2001; US$ 7.99
Seyonne, the slave-turned-hero from Berg's highly acclaimed Transformation , returns to discover the nature of evil--in a "spellbinding" ( Romantic Times ) epic saga. more...


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The things you might be doing, want to do, and probably should do….based on many true stories, mine and my clients'.
In your 20s:
You have probably just started work and started earning your real income for the first time. Discounting the part-time holiday jobs you might have done, if any at all. All these years, you have been getting allowances from your parents.
What is the very least that we private investors should expect when we invest in the stock market?
Is it enough to simply hand our money over to fund managers and hope that they will try their level best for us?
Some investors do. Some investors believe that letting other people manage their investments could be a good idea. They might do so for a variety of reasons. These could include a lack of investing expertise, a lack of market knowledge or simply because they don't have the time to manage the investments.
A company's annual report is the single most important way for it to convey itself to potential investors. As such, it should come as no surprise that an annual report serves to present the company in best light possible without violating any MAS or SGX regulations. Unfortunately, many investors read annual reports but fail to read them effectively. In other words, while annual reports are clearly prepared without any intent to deceive or reflect dishonesty about the business, investors should always read them with a sense of skepticism. In other words, how can investors learn to interpret the information within the annual report to make more informed investment decisions?
Every week I pop into the BBC Studios in Beach Road for a one-hour live show on the World Service called Business Matters.
To be on the safe side, I always leave my flat shortly after seven in the morning to give myself plenty of time to settle into the studio. Failing to do so could trigger a serious panic-attack in the production team at London's New Broadcasting House.
Securities Investors Association (Singapore) @2015 All rights reserved.This website is a production of SIAS. Reproduction in any form or medium without written permission of SIAS is prohibited.


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Project Ideas for All Occasions From Paper to Fabric
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"Sweet" Cupcake Pot
By: DecoArt
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The project was added to your Craft Projects.
Click here to view your Craft Projects.
Use paint-able texture to create this sweet terra cotta "cupcake" with a cherry on top. This cupcake makes cute kitchen decor.
DecoArt Products Required
Paintable Texture - Thick
- TX05 - Thick
Patio Paint
- DCP07 - Geranium Red
- DCP14 - Cloud White
- DCP21 - Wrought Iron Black
- DCP63 - Blue Bahama --- NEW!!
Glamour Dust
- DAS37 - Glamour Dust Crystal
Palette Knife
- DT02 - Palette Knife
- 3/4" flat brush
- 4 round brush
- 1 1/2" wood bead
- Wood glue
- Foam plate
- 1/3" and 1" round foam pouncers
- Green chenille stem
- Scissors
- 6" standard terra cotta pot
- 7" standard terra cotta saucer
Preparation: Remove all labels and clean surface before painting.
- Use flat brush and Cloud White to paint saucer; let dry.
- Use palette knife to apply Texture Thick to bottom of saucer up to rim, building up thicker and rounding off at sharp edges for "frosting". Make slight indention at top center to glue bead handle into once dried. Set aside and let dry.
- Use flat brush and Blue Bahama to paint pot below rim and let dry.
- Use flat brush and Geranium Red to paint rim and inside of pot; use round brush to paint wood bead Geranium Red. Let dry.
- Use large pouncer and Cloud White to paint scattered dots on Blue Bahama area of pot; let dry.
- Use small pouncer and Wrought Iron Black to paint small dots on Blue Bahama area of pot. Let dry.
- Use round brush and Geranium Red to paint word "Sweet" on side of pot and let dry.
- Use large pouncer and Cloud White to sponge paint over textured area of saucer. While wet, sprinkle with Glamour Dust. Let dry and then shake off excess.
- Glue Geranium Red bead at top center of texture for "cherry" handle of lid. Cut 2 piece of chenille stem and glue inside hole of bead for cherry stem; let glue dry.
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[IMAGE]IMG-7073-2.jpg[/IMAGE]Officials of Tarrant County, the City of Richland Hills and The T (the Fort Worth Transportation Authority) broke ground on a multi-phase enhancement project at the Richland Hills Station of the Trinity Railway Express (TRE). The commuter railroad is jointly-owned and operated by The T and Dallas Area Rapid Transit (DART).
The project has been planned by Richland Hills and The T for several years to improve street and pedestrian access to the TRE Station, expand parking, enhance traffic flow around the station and encourage future development adjacent to the station. The majority of the funding for the enhancements will be from grants through the Federal Transit Administration.
The first phase of the long-term project, to begin this month, will be the addition of 100 parking spaces at the TRE Station Park and Ride lot bringing it to a total of 478 spaces. The Richland Hills Station has the third highest TRE boardings of stations in Tarrant County.
The second phase will be the realignment of area streets and the addition of dedicated turn lanes to expedite traffic flow in and out of the station.
The final phase includes future economic development by private entities on property adjacent to the station.
Officials of Tarrant County, Richland Hills and The T broke ground Sept. 12 for a $2 million enhancement project at the Trinity Railway Express Richland Hills Station that also will encourage adjacent economic development. From left, Richland Hills City Council members Roland Goveas, Bob DeSoto, Edward Lopez, Kenney Davis, Mayor David Ragan; Tarrant County Commissioner Gary Fickes; and Jeff Ritter, board member of The T and former Richland Hills city council member.
Every MI09 can transport up to 2,600 passengers at maximum speeds of approximately 75 miles per hour. Each train is made up of five cars, each equipped with three large doors on either side to facilitate passenger exchange in the stations.
The Brussels based UITP's World Congress is the major global gathering of the world's public transport industry to network, review progress and innovation, understand trends from suppliers as well as focus on the challenges that public transport faces in delivering a viable, sustainable future for the world.
The three additional cars will boost SMART's seating capacity by 35%, officials said. Because of the escalating costs for railcars, the grant also was estimated to have saved taxpayers about $11 million, according to state officials,
Will begin work on a seven-year, $700 million rail delivery partner contract awarded by the California High-Speed Rail Authority earlier this month.
The Coradia Lint 41 is an environmentally-friendly low-consumption Diesel Multiple Unit that can reach a maximum operating speed of up to 87 mph.
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text:
Offer - Large Super Sweet Pineapple Waitrose
4 days guaranteed (avg. 6.5)*
Product Description
Large Supersweet Pineapple
A variety renowned for this intensely sweet flavour.
carefully grown and specially selected to bring you only the juiciest, most delicious fruit
By choosing these products you are improving the nutritional balance of your daily diet. A varied balanced diet together with frequent activity supports a healthy lifestyle.
waitrose.com/lovelife for more information
Product Information
- Brands: Waitrose
- Dietary & Lifestyle: Vegetarian
- Options: Top Offers, On Offer
Essential Waitrose
Keep Refrigerated
Best served at room temperature
Preparation and Usage
Wash before use. Best served at room temperature.
Country of Origin
Country of origin may vary depending upon seasonality
Waitrose Limited,
Package Type
Recycling Information
Tag - Plastic - Not Currently Recycled
Other Information
Full Product Name:
Large supersweet pineapple
Nutritional Data
|Typical Values
|As Sold Per 100g
|Energy kJ
|Energy kcal
|of which saturates
|of which sugars
Customer Reviews
18 June 2015
Little resemblance to a pineapple on the inside
Pale, dry, tasteless; the opposite of golden, juicy, sweet and full of flavour! OCADO you have to do better!
14 June 2015
Good quality pineapple
Left this pineapple to ripen for a few days. Was very sweet and tasty. Would buy again.
14 June 2015
Dry and tasteless. Waste of money.
Dark green, looked underripe, but I pulled a few leaves from centre and they almost fell out, brown and starting to rot, so I thought I'd better use it. Inside was very dry, rotting at centre top. I cut all the brown away and tried a chunk. Tasteless. Disappointed but loath to waste it I stewed with some sugar. I wish I'd checked the latest reviews before purchasing.
03 June 2015
Worst pineapple ever
has the structure of an apple, crunchy, white, and sour. not a decent pineapple by far - pure rip off!
Braised Pork with Pineapple Salad
This recipe makes enough for left overs. Serve in baguettes Vietnamese-style - along with grated carrot, cos lettuce and hoisin sauce.
3 hrs 5 mins
The Ocado Fiery Fruit Salad
The sweet taste of pineapple with a fiery kick makes a stunning dessert for an Asian feast.
15 mins
Pineapple Puree and Orange Semifreddo with Pistachio Brittle
This elegant Italian fruit dessert is simply sublime when fused with the crunchy nut brittle.
4 hrs 20 mins
Pineapple Upside-down Cake with Muscovado Sugar and Lemon Syrup
Fresh pineapple, muscovado sugar and juicy lemons give a new twist to this old-fashioned 'upside-down' cake. Serve warm or cold.
40 mins
Oriental Fruit Salad
Easy-peasy inspiration for after-work meals and simple entertaining.
15 mins
View all recipes containing Large Super Sweet Pineapple Waitrose
- Life guarantee
- * Minimum life based on 'use-by' date of product. Average life based on last week's deliveries. Life guarantee shown based on delivery tomorrow and includes day of delivery. Please book a slot to view Life guarantee for your chosen delivery day. See Terms and Conditions for further details.
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- This data is supplied for personal use only. It may not be reproduced in any way whatsoever without Ocado Limited's prior consent, nor without due acknowledgement.


text:
Towers of London
Towers of London would be the most original rock band to ever come out of England -- if this was 1975. Sadly for Towers, it's not. The London mates, with their ultra-party-coiffed manes, come off as third-generation wannabes so devoid of pure inspiration that even their influences look asinine. The Sex Pistols ought to be shot for the cheap guitar tricks they've spawned, while Mtley Crüe deserves a scalping for hyping ridiculously hairspray-locked 'dos in metal. Towers, biting from both acts, sport pegged black jeans and Chucks in a total poseur-punk rebellion sort of way that is about as threatening as Gary Coleman on security detail. Blood Sweat & Towers is so clearly contrived of Clash and Stooges material that it's downright laughable. And the lyrics don't fare any better: "Parasites of society, now you'll know just who we are!" yells vocalist Donny Tourette on the poorly titled "Kill the Pop Scene." Parasitic annoyances? At least Towers got one thing right.
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text:
Mentor Headlands Vacations
The national capital Washington is located 300 miles (483 kilometers) southeast of Mentor Headlands, while Cleveland lies 25 miles (40 kilometers) to the southwest.
From big-ticket tourist hotspots to secret places that are waiting just for you, Northeast Ohio is brimming with fabulous things to see and do. Approximately 14 miles (23 kilometers) away is Madison. Head here to see the Chalet Debonne Vineyards and Grand River Cellars Winery.
Geneva, is another good spot to discover. It is approximately 19 miles (31 kilometers) from Mentor Headlands and offers a diverse range of points of interest, such as Old Firehouse Winery, Virant Family Winery and Harpersfield Covered Bridge. Be sure not to return to Mentor Headlands until you've investigated Geneva's Harpersfield Vineyard, South River Vineyard and Laurello Vineyards.
This area is renowned for its traditional villages; these are often evocative portals into the region's rich history.
This region features a number of laid-back pursuits. Spend the day cycling or picnicking and leave your worries behind. The Northeast Ohio area has a number of great places to enjoy boating, so be sure you fit that into your itinerary. Swimming is another popular watersport here.
When the time comes to say goodbye to Mentor Headlands, head to the nearest major airport located in Cleveland, 35 miles (56 kilometers) away.


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Women's Saucony
Kinvara TR2
ProGrid Kinvara TR Trail
Men's Saucony
Back to top
Fantastic shoe
By JulieC
from Redwood City, Ca
About Me Casual/ Recreational
Best Uses
Comments about Womens Saucony Kinvara TR2 Trail Running Shoe:
After looking at the last review, I bought these for the 2014 NorCal Tough Mudder. I absolutely loved them. I bought them a half size smaller than my everyday athletic shoes. I'm sort of between sizes 7.5 and 8. I bought these in a 7.5 so they would stay snug in the heavy mud. They worked great. Never had any issues with comfort as heavily loaded as they got with mud. Traction was good on the obstacles and difficult terrain. I tired to save them after the course but I don't think they will survive with all that mud and sediment. Definitely will replace them with another pair for the next race.
Bottom Line Yes, I would recommend this to a friend
Was this review helpful? Yes / No
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By jojogirl
from Asheville, NC
About Me Avid Athlete
Comments about Womens Saucony ProGrid Kinvara TR Trail Running Shoe:
I'm a neutral runner and I normally run in a very cushioned Saucony neutral running shoe with a 12 mm heel-toe drop. These have served me well for years. However, I wanted to venture into experimenting with more minimal running shoes so I decided to try the Saucony Progrid Kinvara Tr. (4 mm heel-toe drop). I live in the mountains and I do a mix of road and trail running. These shoes are simply amazing!! Super lightweight, perfect light cushioning, yet I can feel the ground and respond quickly. They feel like they were made for my feet. Absolutely no blisters and no pressure points anywhere. My calves were a little sore the first couple times due to becoming accustomed to minimal shoes, but they quickly adjusted. My mileage has increased significantly with these shoes. It sometimes feels like I could just run forever in them. Couldn't be more pleased!Like all running shoes, particularly Saucony, it is advisable to size up 1/2 to 1 whole size.
Saucony ProGrid Kinvara
By Ernie D
from Auburn, NY ~ The Finger Lakes
About Me Gym Rat
Comments about Mens Saucony ProGrid Kinvara TR Trail Running Shoe:
At nearly "70" years old my knees lite up with too much road running. For trails and unpaved terrain this shoe was a real find and another great shoe from our friends at Saucony.
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slideshows MORE
Top 10 Stocking-Stuffer Gift Ideas for 2014
4 of 11
3D Drawing Pad
Your eyes will deceive you! Once your drawing is complete, put on the 3D specs, and your creation will appear to float above the paper.
More on: Gifts
4 of 11
Your eyes will deceive you! Once your drawing is complete, put on the 3D specs, and your creation will appear to float above the paper.
More on: Gifts
Bug Off! 6 Tick- and Mosquito-Borne Diseases
Which bug bites are dangerous? Learn about 6 diseases spread by ticks and mosquitoes, the signs and symptoms, and treatment options if someone in your family gets infected.
Find Today's Newest & Best Children's Books!
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VIEWS: 4 PAGES: 38 CATEGORY: Employment POSTED ON: 8/17/2010 Public Domain
Research Division Federal Reserve Bank of St. Louis Working Paper Series Changing Noise Levels and Housing Prices near the Atlanta Airport Jeffrey P. Cohen and Cletus C. Coughlin Working Paper 2005-060D http://research.stlouisfed.org/wp/2005/2005-060.pdf August 2005 Revised July 2008 FEDERAL RESERVE BANK OF ST. LOUIS Research Division P.O. Box 442 St. Louis, MO 63166 ______________________________________________________________________________________ The views expressed are those of the individual authors and do not necessarily reflect official positions of the Federal Reserve Bank of St. Louis, the Federal Reserve System, or the Board of Governors. Federal Reserve Bank of St. Louis Working Papers are preliminary materials circulated to stimulate discussion and critical comment. References in publications to Federal Reserve Bank of St. Louis Working Papers (other than an acknowledgment that the writer has had access to unpublished material) should be cleared with the author or authors. Changing Noise Levels and Housing Prices near the Atlanta Airport Jeffrey P. Cohen Associate Professor of Economics Barney School of Business University of Hartford email@example.com Cletus C. Coughlin Deputy Director of Research and Vice President Research Division Federal Reserve Bank of St. Louis email@example.com July 2008 Abstract Using hedonic models, we analyze the effects of proximity and noise on housing prices in neighborhoods near Hartsfield-Jackson Atlanta International Airport during 1995-2002. Proximity to the airport is related positively to housing prices. We address complications caused by changes over time in the levels and geographic distribution of noise and by the fact that noise contours are measured infrequently. A general decline in noise boosted housing prices during 1995-2002. After accounting for proximity, house characteristics, and demographic variables, houses in noisier areas sold for less than houses subjected to less noise. Also, the noise discount is larger during 2000-2002 than 1995-1999. JEL Codes: Q53, Q51, R31, L93 Keywords: noise, airports, housing prices, hedonic pricing, proximity The authors thank Deborah Roisman and Lesli Ott for excellent research assistance and the City of Atlanta Department of Aviation for noise contour data. Cohen is grateful for the support of the Federal Reserve Bank of St. Louis, and the Faculty Research Network at New York University. The views expressed in this paper are those of the authors and do not necessarily represent those of the Federal Reserve Bank of St. Louis or the Federal Reserve System. 1 Introduction Airports generate both undesirable impacts, such as noise, and desirable impacts, such as employment opportunities and transportation services. In assessing the effects of airports on housing prices, issues related to geography come to the fore. In this paper, we estimate the impact of airport-related noise on housing prices during 1995-2002 in neighborhoods near Hartsfield-Jackson Atlanta International Airport. We address complications that arise because the airport noise contours are produced infrequently and change over time. We also explore how proximity to an airport affects housing prices. Our analysis uses a hedonic pricing model. Hedonic models have been used for many years in housing price studies, with numerous studies producing estimates of the values of amenities as well as disamenities on housing prices. 1 Despite several hedonic airport noise studies, few recent studies have examined noise effects of U.S. airports on housing prices and no known studies have produced estimates of the changing impact over time of given noise levels at a specific airport. 2 Coinciding with our focus on noise and housing prices is the simultaneous consideration of proximity and housing prices. Tomkins et al. (1998) and McMillen (2004a) have found that proximity to airports in Manchester, England, and Chicago, respectively, had a positive effect on housing prices. Access to airport-related jobs and 1 For example, see Greenbaum et al. (2005) – crime, Kiel and Boyle (2001) and Anstine (2003) – environmental disamenities, and Benson et al. (1998) – environmental amenities. 2 The hedonic price method, which uses revealed preference, is the most common approach for assessing the cost of noise. This cost has been examined to a very limited extent via three other methods—artificial neural networks, contingent valuation, and happiness surveys. See Collins and Evans (1994), Feitelson et al. (1996), and van Praag and Baarsma (2005), respectively. The use of artificial neural networks also relies on revealed preference. The other methods rely on subjective, survey-based information. 2 air transportation services can become capitalized into the value of a house. Moreover, ignoring the value of accessibility could bias the estimates of the impact of noise. For comparability purposes, the results of two recent studies are especially relevant. McMillen (2004a) found that residential property values for houses subjected to a noise level of 65 or more decibels near Chicago's O'Hare Airport were about nine percent lower than otherwise similar homes. 3 Similarly, Espey and Lopez (2000) estimated a $2400 difference, slightly more than two percent, in the price of a house in Reno-Sparks, Nevada, in areas with a noise level of at least 65 decibels. Two prior studies have examined the effect of noise at the Atlanta airport on property values. O'Byrne et al. (1985) examined the prices of properties near the Atlanta airport for 1970-72 and 1979-80. Noise negatively affected price in both sets of regressions. Moreover, despite using prices based on individual house sales in one period and owner-appraised Census block aggregates in the other period, their results revealed similar estimates of the noise discount for the two periods. The other study, Lipscomb (2003), examined the sales of 105 single family dwellings in the small city of College Park that occurred from January 1997 to February 2000. In contrast to O'Byrne et al. (1985), Lipscomb (2003) found that airport noise did not have a statistically significant effect on housing prices. Our research updates and extends O'Byrne et al. (1985) and Lipscomb (2003). A noteworthy extension is that it produces results on how the impact of noise on housing prices has changed over time at a specific airport. In a survey of airport-related noise estimates and housing prices, Nelson (1980) concluded that the impact of noise was 3 Nonetheless, because the noise associated with aircraft is diminishing over time, McMillen (2004a) estimated that prices for houses near O'Hare would rise if an additional runway were built. 3 relatively stable across studies; however, a review by Schipper et al. (1998) of 19 studies found much variation among the estimates produced by the studies. Much of this variation could be explained by differences across studies in terms of either the characteristics of the sample population (e.g., mean house price) or the study (e.g., time period, country, and specification). In a recent meta-analysis using 33 estimates for 23 airports in the United States and Canada, Nelson (2004) concluded that variability in estimated noise discounts was related to the country in which the airport was located and to the specification of the hedonic model. In contrast to prior studies, our study uses price data from one source over a moderately long time period, eight years, to explore how the price impact of noise on houses near the Atlanta airport has changed over time. Such an approach is preferable to making inferences based on studies for various airports at different points in time. Our analysis, however, is complicated by the fact that over time a particular house is subjected to different noise levels that are not measured precisely. Noise regulations, quieter aircraft, and soundproofing programs have likely affected the quantity and impact of airport noise on housing prices over time. Data and Model The standard categories of explanatory variables used in studies of housing prices are the structural features of the housing units, location characteristics, and attributes of the social and natural environment. To estimate the impact of specific determinants, we combined data from various sources. The data consist of noise contour maps for the neighborhoods near the airport, demographic data on a block-group basis for median 4 household income and the percent of housing occupied by blacks, as well as data for single family house sales, including sales prices, location, and housing characteristics. Noise contour files for 1995 and 2003, in a format compatible with ArcView Geographic Information Systems (GIS) software, were provided by the City of Atlanta Department of Aviation. 4 The noise contour maps are based on a standard measure of noise used by the Federal Aviation Administration and other federal agencies. This measure, the yearly day-night sound level (DNL), is measured in decibels. Because an increase of 10 decibels is equivalent to a ten-fold increase in sound, a ten-unit increase in the DNL can be viewed similarly. Nelson (2004) notes that normal background noise levels in urban areas are approximately 50-60 decibels during daytime hours and 40 decibels during nighttime. A DNL of 65 decibels is the Federal Aviation Administration's lower limit for defining a significant noise impact on people. 5 At 65 decibels and above, individuals experience the disruption of normal activities, such as speaking, listening, learning, and sleeping. A DNL of 75 decibels or more is viewed as incompatible with single family housing. 6 In contrast to many studies that identify their "noisy" area by one noise contour (i.e., 65 or more decibels), the current analysis uses two noise contours, one for 65 4 ArcView GIS software enables the user to read noise contour maps and match the corresponding noise data with other geo-coded data corresponding to individual properties. Nelson (2004) refers to GIS studies as the "next generation of hedonic studies." For an overview of applying GIS to economic issues, see Bateman et al. (2002). 5 See U.S. Federal Interagency Committee on Noise (1992a,b) for this standard. This standard, however, is somewhat controversial. Sobotta et al. (2007) note that the Environmental Protection Agency and the World Health Organization consider 65 DNL unacceptably high. Research on noise suggests that roughly 12 percent of people subjected to a DNL of 65 decibels report that they are "highly annoyed" by transportation noise. Meanwhile, about 3 percent are highly annoyed when subjected to a DNL of 55 decibels and nearly 40 percent are highly annoyed at a DNL of 75 decibels. See Federal Register (2000). 6 Nelson (2004) notes that since 1979 federal agencies have regarded land subjected to DNLs ranging from 65 to 74 decibels as "normally" incompatible with residential use, while land exposed to a DNL of less than 65 decibels is regarded as "normally" compatible with residential land use. 5 decibels (i.e., 65 to less than 70 decibels) and one for 70 decibels (i.e., 70 to less than 75 decibels). Single family dwelling sale price data for the years 1995 through 2002 have been purchased from First American Real Estate Services for the Atlanta neighborhoods that fall in the 65 DNL and 70 DNL boundaries, as well as within a half mile outside of the 65 DNL boundary, which is termed the "buffer zone." 7 8 Relative to the buffer zone, it is expected that, all else equal, houses subjected to more noise will sell for lower prices. One complication for the current analysis is that the noise levels for a specific house have likely changed over time and precise measurement of these changes is lacking. This issue is addressed in more detail later; at this point, we discuss one reason for changing noise levels and our response to this complication. Prior to 1968, aircraft noise was not regulated on a national basis in the United States. Following Congressional authorization, the Federal Aviation Administration promulgated standards requiring that the best available noise reduction technology be used in new designs of civil subsonic turbojet aircraft. Aircraft satisfying this standard were categorized as Stage 2 aircraft, while those not meeting this standard were classified as Stage 1 aircraft. In 1977, the Federal Aviation Administration adopted more stringent noise standards that applied to all newly manufactured aircraft. Aircraft meeting the new standards, which only apply to commercial subsonic jet aircraft over 75,000 pounds, were classified as Stage 3 aircraft. Following passage of the Airport Noise and Capacity Act in 1990, all commercial jets operating in the United States were required to be Stage 3 7 We eliminated 28 sales in the 75 decibel noise contour from the sample. 8 We chose the 0.5 mile buffer zone rather than the entire metropolitan area for three reasons. First, other airport noise studies have handled analogous problems similarly. Second, we wanted to examine the impact of additional noise relative to some base that exhibits some noise. Third, other parts of Atlanta may face different housing price determinants than the area surrounding the airport. 6 compliant by December 31, 1999. Thus, one implication to be drawn from phasing-in the Stage 3 requirement is that noise levels throughout the sample area should be lower at the end of our time period relative to the beginning. We use a dummy variable to separate the phase-in period that lasts through 1999 from the latter period, 2000-2002. 9 The geographic area that is examined and the relevant noise contours for 1995 are shown in Figures 1 and 2. The airport lies ten miles south of downtown Atlanta. The area under consideration covers parts of Atlanta and five other cities—College Park, Conley, East Point, Forest Park, and Hapeville. This sample consists of 2,370 house sales from 1995 through 2002. Nominal housing sale prices are deflated by the National Association of Realtors median housing price index for Atlanta, with 1995 median sales price for Atlanta as the base year. We refer to these prices as adjusted prices. Between 1995 and 2002 this housing price index increased 50 percent, substantially larger than the 20 percent increase in the consumer price index. In addition to the sales price, housing characteristics such as the numbers of stories, bedrooms, baths, fireplaces, lot size, and the age of the dwelling were contained in the purchased dataset. Table 1 lists the variables used in our analysis and how these variables were measured, while Table 2 contains summary information of these data. 10 Each of the housing characteristics variables, with the exception of the age of the dwelling, is expected to be related positively to housing prices. An increase in the age of a house, holding all other things constant, should tend to reduce its price. 9 The re-drawing of the noise contours causes some houses to switch from one noise area to another one. This issue is addressed later. 10 Following Pennington et al. (1990) and Espey and Lopez (2000), dummy variables are used for measuring selected structural housing characteristics, such as the numbers of bedrooms, bathrooms, and fireplaces. 7 The demographic data are from the Bureau of the Census. Because there are no annual data for neighborhood characteristics, we use 2000 Census data for the sales in all sample years. 11 Specifically, the block group data came from the 2000 Summary Tape File 3 – Sample data. With respect to the neighborhood characteristics, we examine two variables—median household income and the racial composition of the neighborhood. We expect the sign on the income coefficient to be positive due to the neighborhood effects. In other words, houses in neighborhoods where residents have higher incomes should have higher prices. Our expectation concerning the relationship between the percentage of housing occupied by blacks and housing prices is based on O'Byrne et al. (1985), who found a negative relationship. 12 However, possible changes in racial attitudes as well as differences in the composition of the neighborhoods examined here versus those examined by O'Byrne et al. raise some doubts about this expectation. In addition to noise and neighborhood characteristics, the location of a house is likely to affect its price via some other characteristics. Whether the house is located in Atlanta, College Park, Conley, East Point, Forest Park, or Hapeville is potentially important. The benefits and costs of publicly-provided services as well as other features of cities can differ and affect housing prices. We have no expectation as to how housing prices in specific cities are likely to be affected. Finally, ArcView was used to calculate the distance between each property address and the airport. After accounting for airport noise, the authors expect that less distance from the airport should result in higher housing prices, due to more convenient 11 We also ran regressions in which they replaced 2000 Census data with 1990 Census data. These results do not differ materially from their reported results. 12 Greenbaum et al. (2005) found a positive relationship between housing prices and the percentage of white population for neighborhoods in Columbus, Ohio. 8 access to jobs at the airport and air transportation service. 13 14 Ignoring the value of accessibility to the airport could bias the estimated noise effect downward (i.e., to showing a lessened effect). Thus, the model is a hedonic housing price model, with the individual housing characteristics, noise exposure, neighborhood characteristics, the city in which the house is located, and distance to the airport as the explanatory variables. For some regressions, we also included variables to capture the timing of the sale, such as the year or the month (or both) in which the sale occurred. We estimated numerous hedonic housing price models. 15 Three functional forms—a double log form, a semi-log form, and a linear form—were examined. Because of the similarity of the results and to reduce the size of the tables, we have chosen to report only the results of the semi-log and linear functional forms. The change in the geographic distribution of noise that occurred between 1995 and 2003 complicates our attempt to precisely identify the quantitative relationship between noise and housing prices. The first set of results assumes that houses were subjected to noise based on the 1995 noise contours from 1995 through 2002. The second set of results is based on a reduced sample constructed by using information from both the 1995 and 2003 noise contours. Results – Base Model Using 1995 Noise Contours 13 Proximity to an airport may have positive (due to accessibility) as well as negative (due to noise) effects on property values. Tomkins et al. (1998) found that the benefits of easy access to the airport outweighed the costs of living near the airport in Manchester, England. In contrast, Espey and Lopez (2000) found proximity to an airport in Reno, Nevada to be a disamenity. 14 Numerous studies have related property values to the distance from rail stations. Bowes and Ihlanfeldt (2001, p. 3) conclude that "the majority do find that rail stations have a positive (but relatively modest) impact on nearby property values." Bowes and Ihlanfeldt examine four factors related to proximity that might affect property values. The positive factors are the transportation access advantage provided by rail stations and the increased retail activity stemming from rail stations. The negative factors are crime and environmental disamenities, such as noise, pollution, and the unsightliness of rail stations. In their study of Atlanta's rail system, all four factors affected property values. 15 An alternative approach using spatial econometrics would incorporate the impacts of the spatial locations of other houses in determining the price of a specific house. See Cohen and Coughlin (forthcoming). 9 Table 3 contains the results of models using the noise contours for 1995. The estimated models explain 45 percent of the variation in housing prices in the semi-log functional form and 40 percent for the linear form. Nearly every individual variable performed as expected. Variables measuring the structural characteristics of houses exhibited the expected impact on housing prices and, virtually without exception, were statistically significant, often at the 1 percent level. For example, the dummy variables differentiating houses based on the number of bedrooms, Beds3d, Beds4d, and Beds5d, were all related positively to housing prices and, except for Beds3d in the linear form, were statistically significant. Moreover, the size of the estimated coefficients increases as the number of bedrooms increases. The results for the number of bathrooms are similar to the results for the number of bedrooms. Both dummy variables differentiating houses based on the number of bathrooms, Baths2d and Baths3d, were related positively to housing prices, increased in size with the number of bathrooms, and were statistically significant. The dummy variable differentiating houses with two or more fireplaces from other houses, Fire2d, was related positively to housing prices and was statistically significant. The dummy variable differentiating houses with two or more stories from other houses, Storiesd, was also found to be a positive, statistically significant determinant of housing prices. The variable measuring the age of the house, Age, was related negatively to housing prices, but this variable was not statistically significant for the linear specification. This lack of significance of Age indicates that newer houses did not tend to sell for significantly higher prices than older houses. Finally, indicating that larger lots 10 were associated with higher housing prices, the variable measuring lot size, Acres, was related positively to housing prices and was statistically significant. Turning to the neighborhood characteristics, the percentage of houses in a neighborhood occupied by blacks, BlackPerc, was related negatively to housing prices and was statistically significant. Numerous regressions were run that included median household income in the neighborhood in which a house was sold. This variable was not included in the reported results because it was not found to be statistically significant. The dummy variables differentiating the cities in this housing sample provided explanatory power. Relative to Atlanta, ceteris paribus, houses in College Park (City2d) and East Point (City4d) tended to sell for higher prices, while houses in Conley (City3d) and Forest Park (City5d) tended to sell for lower prices. Houses in Hapeville (City6d) tended to sell for prices similar to those in Atlanta. 16 The remaining results concern the variables related to the airport—distance and noise. 17 Some weak evidence is found indicating that the distance from a house to the airport affects the price of the house. The variable measuring that distance, Distance, was related negatively to housing prices; however, a statistically significant relationship was found only for the linear specification. These results are consistent with findings by Lipscomb (2003) that houses closer to the Atlanta airport tended to sell for higher prices. 18 Our results are also consistent with findings by Tomkins et al. (1998) that proximity to the airport in Manchester, England, and by McMillen (2004a) that proximity 16 Given our focus on the impacts of noise and proximity on housing prices, no speculation on the reasons for the results involving specific cities is provided. 17 Regardless of the sample size, the distance and noise measures show little correlation. 18 Based on conventional significance levels, however, Lipscomb (2003) did not find a statistically significant relationship between distance to the airport and housing prices. 11 to Chicago's O'Hare Airport were amenities, but are inconsistent with a finding by Espey and Lopez (2000) that proximity to the airport in Reno, Nevada, was a disamenity. Concerning to airport noise, the results are mixed. Regardless of functional form, airport noise is related negatively to housing prices, but the relationship is statistically significant only for the 65 decibel noise contour, Noise65d_95, and housing prices. The relationship between the variable for the 70 decibel noise contour, Noise70d_95, and housing prices is not statistically significant. Consistent with our expectation, the attempt to differentiate the phase-in period of Stage 3 aircraft from full compliance appears to succeed. NoiseRegd is a positive, statistically significant determinant of AdjPrice. One can view this variable as capturing a broad-based reduction in noise levels between 1995- 1999 and 2000-2002. Our interpretation, which can be questioned, suggests that this regulation affected all housing prices in the sample area, regardless of the initial noise levels. Additional evidence on this issue is provided later. Potential Biases Stemming from Changing Noise Contours One question that deserves scrutiny is whether there are potential biases from the use of the 1995 contours for the entire period. A comparison of the 1995 contours with contours estimated for 2003 suggests that the noise contours have changed between 1995 and 2003. Figure 3 shows how the 65 decibel noise contour has changed between 1995 and 2003. Generally speaking, the 65 decibel noise contour has shifted closer to the ends of the runways. This change and a similar change for the 70 decibel noise contour have 12 resulted from a combination of technological changes, regulatory policy, and airport authority efforts to reduce the effects of noise. 19 The preceding discussion indicates that both the 70 decibel and 65 decibel noise contours have collapsed toward the airport over time so that some houses became subject to less noise. Meanwhile, the buffer zone becomes a relatively larger share of the area under consideration and it too has become subject to less noise. Thus, on average, the houses in each of these areas should tend to increase in value. Our results for NoiseRegd are consistent with this expectation. Two caveats, however, should be highlighted. First, some factor other than declining noise levels might be responsible, at least partially, for this result. In other words, some variable, not included in this model, could have changed between 1995-1999 and 2000-2002 that made houses in the sample relatively more attractive than houses overall in the Atlanta area. Second, the use of NoiseRegd does not preclude the possibility that the inaccurate measurement associated with the changing noise contours could bias our estimates with respect to specific noise contours. Our study uses the 2003 contours to reduce the dataset to address the issue of changing noise levels. We restrict the sample to only those houses that remained in the same contour throughout the sample period. In other words, the resulting sample consists of houses in the 70 decibel contour using both the 1995 and 2003 noise contours, houses in the 65 decibel contour for both noise contours, and houses in the buffer zone for both noise contours. The dummy variables identifying houses in the 65 and 70 decibel noise contours using 1995 and 2003 measures are Noise65d_9503 and Noise70d_9503, 19 Additional information on this topic can be found on the airport's website: www.atlanta-airport.com. After reaching the site, navigate through "Airport Information," "Environmental," and then "Noise and Operations Monitoring System" (NOMS). 13 respectively. Houses classified as switching noise areas between 1995 and 2003 were deleted. 20 As a result, the sample size decreased from 2370 to 1643. In addition, as indicated in Table 4, the distribution of houses across the three noise areas changed. The location of houses in this sample is shown in Figure 4. The percentage of houses in the buffer zone increased by nearly 19 percentage points, while the percentage of houses in the 65 and 70 decibel noise contours declined by roughly 12 and 6 percentage points, respectively. Some minor changes can also be observed in the means of the variables. Not surprisingly, with the relative decline of the houses in the 65 and 70 noise contours, the mean of the adjusted sales price rose as did the distance from the airport. Neighborhood characteristics also changed. The average percentage of houses in the neighborhood occupied by blacks fell. What can be said about potential bias using this sample? Using this reduced sample, it is clear that houses in the 70 decibel and 65 decibel noise contours are subject to roughly the same noise levels throughout the period. (More precisely, the houses in the 70 decibel noise contour are subject to at least 70 decibels of noise throughout the period, with some houses subjected to slightly less noise at the end of the period than at the beginning.) Meanwhile, houses in the buffer zone are likely to be subject to less noise over time. Because the houses in the buffer zone are expected to be affected only minimally by noise, an argument can be made that any reduction in noise for these houses 20 McMillen (2004b) follows another approach to analyze whether homes have risen faster in neighborhoods where noise exposure has changed over time. He assigns dummy variables to properties that switched sides of the 65 decibel noise contour over time, and for the most part finds that on average the houses that switch sides of the noise contour over time do not significantly appreciate. We did run regressions using the entire sample and identified houses that were reclassified into a different noise contour using the 1995 and 2003 noise contours. The results of these regressions, available upon request, indicate no statistical significance for the reclassified houses and do not differ from our reported results. 14 is likely to have a negligible effect on their price, especially given the inclusion of NoiseRegd. This is especially pertinent due to the construction of this sample. Thus, relative to the buffer zone, the noise discount estimates, to the extent that any bias exists, should be biased high. Results – Base Model Using the 1995 and 2003 Noise Contours Table 5 contains the results using the sample restricted to housing sales that occur in the same noise contour using both the 1995 and 2003 noise contours. Given the focus of this paper, we focus our discussion on the results for the variables related to the airport. 21 We begin by discussing the results in Table 5 that are based on the model using the same variables as in Table 3. The results for NoiseRegd are similar regardless of the sample and the measurement of the noise levels. In fact, the parameter estimates for this variable are slightly larger when the smaller sample is used. Thus, there appears to be a consistent positive effect from the general noise reduction in the area near the airport. The results also indicate that the distance from a house to the airport affects the price of a house. The variable measuring distance, Distance, is related negatively to housing prices and is statistically significant. Comparing the parameter estimates, one sees that in Table 5 the marginal value of proximity is much larger than in Table 3. Earlier we noted that the exclusion of the distance variable could bias the noise results. A comparison of the results of Table 5 with a model that excludes distance confirms this possibility. Excluding proximity tends to shrink the estimated impact of noise on housing prices. Based on the model in Table 5, the parameter estimates for the 65 decibel noise contour for the semi-log and linear functional forms when proximity is 21 The results in Tables 3 and 5 for the variables not directly related to the Atlanta airport are very similar. 15 excluded (included) are: -0.024 (-0.030) and -3,451 (-3,962). The parameter estimates for the 70 decibel noise contour are: -0.042 (-0.063) and -7,909 (-9,622). Turning to the noise variables, the parameter estimates for the noise discounts are larger in Table 5 than in Table 3. Contrary to the results in Table 3, the results in Table 5 for the 70 decibel noise contour are statistically significant. Moreover, the relative magnitudes of the parameter estimates for the 65 and 70 decibel noise contours are consistent with expectations (i.e., the noise discount for houses in the 70 decibel noise contour is larger than for houses in the 65 decibel noise contour). Recall that a case can be made that the estimates in Table 5 are biased high. Thus, these estimates provide an upper bound on the noise discount. The coefficient for the 65 decibel noise contour in the semi-log specification has a value of -0.030, which implies that after accounting for other physical and neighborhood characteristics, houses in this noise contour sold for about 3.0 percent less on average than houses in the buffer zone. 22 Meanwhile, the coefficient for the 70 decibel noise contour suggests a noise discount of 6.1 percent. Thus, the noise discount for houses in the 70 decibel noise contour is slightly more than double that of houses in the 65 decibel noise contour. To make these results more directly comparable to existing studies, we calculated the weighted sum of the two noise discounts. In contrast to our finding of 3.3 percent, Espey and Lopez (2000) estimated a noise discount of 2.4 percent for houses subjected to noise levels of 65 or more decibels for the Reno airport, while McMillen (2004a) estimated a 9 percent noise discount for houses subjected to 65 or more decibels for Chicago's O'Hare Airport. In addition to examining different geographic areas, different 22 The estimated coefficient for the noise contours using the semi-log functional form is nearly equal to the noise discount. In percentage terms, the noise discount equals (eβ – 1) x 100, where e is the base of the natural exponential function and β is the parameter relating noise to housing price. 16 time periods of other studies may account for some of these differences between their findings and ours. Finally, for the linear specification, the results in Table 5 indicate noise discounts for the 65 and 70 decibel noise contours of $3,962 and $9,622, respectively. With the average adjusted price of a home in the buffer zone equal to $74,414, the sales prices of homes in the 65 and 70 decibel noise contour bands are roughly 5.3 and 12.9 percent, respectively, lower than in the buffer zone. 23 The weighted sum of these noise discounts is 6.1 percent, which is nearly double our finding for the semi-log specification. Results – Controlling for the Time of Sale One concern about the analysis presented so far is that we might not have controlled adequately for the time of sale. Our analysis has included some factors that control for the time of sale. First, we adjust sales prices in a given year by a yearly median housing price index. This should control for year-to-year changes in housing prices in Atlanta. Second, our dummy variable for noise regulation, NoiseRegd, distinguishes between sales during 1995-1999 versus 2000-2002. A reasonable question is whether our results hold up to other attempts to control for the time of sale. To control for the time of sale, we added year dummies separately, monthly dummies separately, year and monthly dummies together, and dummies for each quarter/year in our sample. In reviewing the results of numerous regressions, the inclusion of year dummies separately yielded results as good as any of our other attempts to control for time of sale. We did not find any seasonal pattern. Results using the year dummies are listed in the right-hand columns in Table 5. We use 1995 as the base year 23 Consistent with a general finding by Schipper et al. (1998), the estimated impact of noise on housing prices tends to be larger for the linear specification relative to semi-log specification. 17 for this set of dummies, so the estimate for the impact on housing prices for a specific year is relative to 1995. Generally speaking, the inclusion of the year dummies had little effect. The overall explanatory power of the models was unchanged and the parameter estimates and their statistical significance changed only minimally. Turning to the year dummies, a number of observations can be made. First, because of multicollinearity, the inclusion of the year dummies precluded the continued inclusion of NoiseRegd. Second, the parameter estimates for the year dummies were always positive and the relationship between the year dummies and the adjusted housing prices was generally statistically significant. Third, the parameter estimates for 2000, 2001, and 2002 are very similar and much larger than the estimates for the prior years. Statistically, this is a major reason why the results for the models using NoiseRegd are so similar to those using the year dummies. These results, which are admittedly suggestive and far from conclusive, support our argument that NoiseRegd is likely capturing the impact of noise reduction. Note that by using adjusted housing price as the dependent variable, we are estimating the change in housing prices in the area near the airport relative to housing prices throughout the metropolitan area. At this point, our argument about noise remains tentative as we cannot rule out that some factor other than noise is driving our result. Results - Using Nominal Prices In addition to concerns about not adequately controlling for the time of sale, a referee asked about the effects of replacing adjusted housing prices with nominal housing 18 prices. Table 6 contains the results of one set of our regressions that is representative of our complete set of regressions. These regressions produced an increase in overall explanatory power. For the semi-log functional form including year dummies, R2 increased from 0.48 to 0.58, while for the linear functional form, R2 increased from 0.42 to 0.49. Not surprisingly, due to the upward trend in Atlanta housing prices over 1995-2002, the parameter estimates for the year dummies increased throughout the period. A similar comment applies to the magnitudes of the estimates for the other variables using the linear functional form. Results – Did the Noise Discount Change Differentially? So far in this analysis, the results suggest that reduced noise levels between 1995- 1999 and 2000-2002 had a positive impact on housing prices for the entire sample area near the Atlanta airport. The next topic explored is the possibility that the noise discount might have changed differentially depending on the noise contour in which a house was located. 24 There are many reasons why the actual noise discount might change differentially across noise contours. Moreover, it is not clear whether this noise discount is more likely to increase or decrease over time. With increasing incomes and with noise being a disamenity, then the noise discount should tend to increase over time. It is possible that houses subjected to more noise would be sold at increasing discounts. Another reason, suggested by a referee, involves the interplay between noise regulations and consumer expectations. We noted earlier that the passage of the Airport Noise and Capacity Act in 1990 led to the expectation that noise levels throughout our 24 The authors also examined time trends for the other independent variables. Their results revealed no linear time trend between these variables and housing sales prices. 19 sample area should be lower at the end of the sample time period relative to the beginning. It is possible that homebuyers and homeowners had an overly optimistic view of the magnitude of the likely noise reduction at the beginning of our sample period. As the uncertainly about noise levels is reduced and actual noise levels turn out to be higher than initially expected, then the estimated noise discount would be larger for the period at the end of our time period relative to the beginning. On the other hand, airport authorities were pursuing policies during the time period under consideration to reduce the effects of noise. 25 For example, houses within the noise contours were soundproofed. Such efforts should make the purchase of these houses more desirable and, consequently, reduce the noise discount. Table 7 contains the results of adding two variables, Noise65dDif and Noise70dDif, which allow the impact of noise in the 65 and 70 decibel noise contours to change between 1995-1999 and 2000-2002. Adding these variables only affected the results concerning noise. The overall explanatory power of the models remained unchanged and the other individual variables were affected only minimally. One finding is that the parameter estimates for NoiseRegd in Table 7 are larger than the comparable estimates in Tables 3 and 5. For example, the comparable parameter estimates for the semi-log functional form are: 0.189 (Table 7), 0.155 (Table 5), and 0.136 (Table 3). The comparable parameter estimates for the linear functional form are; 14,929 (Table 7), 11,624 (Table 5), 10,590 (Table 3). Regardless of the specification, 25 According to the authorities at the Atlanta Airport (http://www.atlanta- airport.com/sublevels/airport_info/noise.htm): "The DOA's Noise Mitigation Program's purpose is to be proactive in addressing eligible noise-impacted properties inside the approved noise contours. This program provides assistance to the communities surrounding HJAIA by continuing to reduce noise- sensitive uses inside the 70 DNL through acquisition/relocation, and complete acoustical treatment for the remaining noise-sensitive uses inside the 65 DNL, thereby enhancing their living conditions." 20 housing prices are affected positively by roughly 20 percent. It is possible that the estimates in Tables 3 and 5 are biased because these models did not allow for differential changes across noise contours. In Table 7 the estimate for NoiseRegd might no longer be capturing some of the increase in the noise discount for the 65 and 70 decibel noise contours. Turning to the noise-related results associated with the possibility of differential changes across noise contours, our evidence suggests that the measured noise discount within the 65 decibel noise contour has tended to become larger. Regardless of the functional form Noise65dDif is a negative, statistically significant determinant of housing prices. The results for the noise discount within the 70 decibel contour have also tended to become larger; however, a statistically significant relationship between Noise70dDif and housing prices was found only for the linear specification. The results in Table 7 indicate no statistically significant noise discount for 1995- 1999. Such a finding is consistent with Lipscomb (2003), whose sample covered January 1997 to February 2000. Nonetheless, for 2000-2002 tests reveal that Noise65d_9503 and Noise65dDif are always jointly significant. A similar comment can be made concerning the 70 decibel noise contour. For 2000-2002 the estimates for the models with NoiseRegd and without the year dummies indicate that the noise discount for the 65 decibel noise contour was 7.5 percent for the semi-log specification and $8,612 or 10.6 percent for the linear specification. The comparable estimates for the 70 decibel noise contour are 12.3 percent and $14,330 or 17.7 percent. 26 26 As can be seen in Table 7, the estimates for the noise discounts are virtually the same for the models with NoiseRegd relative to the models with year dummies. 21 Of course, the preceding numbers are not the end of the story because of the impact of the variable, NoiseRegd, that attempts to differentiate between the phase-in period of noise regulation from 2000-2002. 27 When one includes this variable, then housing prices in both noise contours (as well as the buffer zone) were affected positively. The estimates in Table 7 indicate the overall positive impact of noise changes for the 65 decibel contour was 11.7 percent for the semi-log specification and $6,318 or 7.8 percent for the linear specification. The comparable estimates for the 70 decibel noise contour are 6.0 percent and $600 or 0.7 percent. Conclusion We produce results on two dimensions of housing prices near the Atlanta airport. In the process of generating specific results, we address complications caused by changes over time in the levels and geographic distribution of noise and by the fact that noise levels are measured only at the beginning and after the end of the sample period. Consistent with most studies, including Lipscomb (2003), proximity to the airport is related positively to housing prices. Moreover, when this variable is excluded, the estimated impact of noise on housing prices is much less in absolute value than when this variable is included. Thus, ignoring the value of accessibility likely biases the estimated noise effect to showing a lessened impact. Our second, more extensive set of results involves the relationship between noise and housing prices. This analysis is complicated by changing, generally declining, noise levels that are measured only at the beginning and end of the sample period. Our 27 For those remaining highly skeptical of what NoiseRegd is capturing, the story does end before going any further. 22 preferred sample includes houses that are located in the same noise contour regardless of when the noise contours are constructed. We find evidence indicating that the prices of houses near the Atlanta airport were affected positively by declining noise levels. The magnitude of the resulting impact on housing prices, roughly 20 percent, is substantial. Turning to the issue of whether houses in noisier areas sell for less than those subject to less noise, previous research involving the Atlanta airport is mixed. We find, consistent with O'Byrne et al. (1985), that airport-related noise having a "significant noise impact on people" is associated with lower housing prices. 28 The point estimates of the noise discount are sensitive to both the functional form and the noise contours used to classify houses. Generally speaking, the linear specification yields the largest estimate of the noise discount. Using our preferred sample, we estimate the noise discount for the 65 decibel noise contour for 2000-2002 to be 7.5 percent for the semi-log specification and $8,612 or 10.6 percent for the linear specification. The comparable estimates for the 70 decibel noise contour are 12.3 percent and $14,330 or 17.7 percent. A novel feature of our study was the attempt to identify whether and how this noise discount has changed over time. Comparing 1995-1999 with 2000-2002, we find that the noise discount is relatively larger during the latter period. This result warrants additional scrutiny in other settings. Finally, combining the impact of the general reduction in noise with their noise discount estimates, we find that between the periods 1995-1999 and 2000-2002 housing prices in areas subjected to noise levels of 65 or more decibels have increased. Our 28 Nonetheless, as noted in the body of the paper, these results are consistent with those of Lipscomb (2003). 23 estimates indicate the overall impact of noise changes for the 65 decibel contour was 11.7 percent for the semi-log specification and $6,318 or 7.8 percent for the linear specification. The comparable estimates for the 70 decibel contour are 6.0 percent and $600 or 0.7 percent. REFERENCES Anstine, Jeff (2003) "Property Values in a Low Populated Area when Dual Noxious Facilities are Present," Growth and Change 34(3), 345-358. Bateman, I.J., A.P. Jones, A.A. Lovett, I.R. Lake, and B.H. Day (2002) "Applying Geographical Information Systems (GIS) to Environmental and Resource Economics," Environmental and Resource Economics 22 (1-2), 219-269. Benson, E., J. Hansen, A. Schwartz, Jr., and G. Smersh (1998) "Pricing Residential Amenities: The Value of a View," Journal of Real Estate Finance and Economics 16(1), 55-73. Bowes, David R. and Keith R. Ihlanfeldt (2001) "Identifying the Impacts of Rail Transit Stations on Residential Property Values," Journal of Urban Economics 50(1), 1-25. Cohen, Jeffrey P. and Cletus C. Coughlin (forthcoming) "Spatial Hedonic Models of Airport Noise, Proximity, and Housing Prices," Journal of Regional Science. Collins, Alan and Alec Evans (1994) "Aircraft Noise and Residential Property Values: An Artificial Neural Network Approach," Journal of Transport Economics and Policy 28(2), 175-197. Espey, Molly and Hilary Lopez (2000) "The Impact of Airport Noise and Proximity on Residential Property Values," Growth and Change 31(3), 408-419. Federal Register (July 14, 2000), 65(136), 43802-43824. Feitelson, Eran I., Robert E. Hurd, and Richard R. Mudge (1996) "The Impact of Airport Noise on Willingness to Pay for Residences," Transportation Research: Part D: Transport and Environment 1(1), 1-14. 24 Greenbaum, Robert T., Tricia L. Petras, and George E. Tita (2005) "Do Changes in Crime Rates Affect Housing Prices? A Neighborhood Level Analysis," American Real Estate and Urban Economics Association Annual Meetings, Philadelphia, January 7-9. Kiel, Katherine and Melissa Boyle (2001) "A Survey of House Price Hedonic Studies of the Impact of Environmental Externalities," Journal of Real Estate Literature 9(2), 117- 144. Lipscomb, Cliff (2003) "Small Cities Matter, Too: The Impacts of an Airport and Local Infrastructure on Housing Prices in a Small Urban City," Review of Urban and Regional Development Studies 15(3), 255-273. McMillen, Daniel P. (2004a) "Airport Expansions and Property Values: The Case of Chicago O'Hare Airport," Journal of Urban Economics 55(3), 627-640. ___________ (2004b) "House Prices and the Proposed Expansion of Chicago's O'Hare Airport," Federal Reserve Bank of Chicago Economic Perspectives 28(3), 28-39. Nelson, Jon P. (1980) "Airports and Property Values: A Survey of Recent Evidence," Journal of Transport Economics and Policy 14(1), 37-52. ___________ (2004) "Meta-Analysis of Airport Noise and Hedonic Property Values: Problems and Prospects," Journal of Transport Economics and Policy 38(1), 1-28. O'Byrne, Patricia H., Jon P. Nelson, and Joseph J. Seneca (1985) "Housing Values, Census Estimates, Disequilibrium, and the Environmental Cost of Airport Noise: A Case Study of Atlanta," Journal of Environmental Economics and Management 12(2), 169- 178. Pennington, G., N. Topham, and R. Ward (1990) "Aircraft Noise and Residential Property Values Adjacent to Manchester International Airport," Journal of Transport Economics and Policy 24(1), 49-59. Schipper, Youdi, Peter Nijkamp, and Piet Rietveld (1998) "Why Do Aircraft Noise Value Estimates Differ? A Meta-Analysis," Journal of Air Transport Management 4(2), 117- 124. Sobotta, Robin R., Heather E. Campbell, and Beverly J. Owens. 2007. "Aviation Noise and Environmental Justice," Journal of Regional Science, 47, 125-154. Tomkins, J., N. Topham, J. Twomey and Robert Ward (1998) "Noise versus Access: The Impact of an Airport in an Urban Property Market," Urban Studies 35(2), 243-258. 25 U.S. Federal Interagency Committee on Noise, Federal Agency Review of Selected Noise Analysis Issues, Volume I, Policy Report (Washington DC: FICON, August 1992a). http://www.fican.org. U.S. Federal Interagency Committee on Noise, Federal Agency Review of Selected Noise Analysis Issues, Volume II, Technical Report (Washington DC: FICON, August 1992b). http://www.fican.org. Van Praag, Bernard M.S. and Barbara E. Baarsma (2005) "Using Happiness Surveys to Value Intangibles: The Case of Airport Noise," Economic Journal 115(500), 224-246. 26 Table 1 Variables in Hedonic Regressions Name Definition NomPrice Nominal house sale price. AdjPrice House sale price deflated by median housing price index for Atlanta. Noise65d_95 Dummy variable equal to one for houses within the 65 decibel day-night sound level 1995 noise contour; zero otherwise. Noise70d_95 Dummy variable equal to one for houses within the 70 decibel day-night sound level 1995 noise contour; zero otherwise. Beds3d Dummy variable equal to one for houses with three bedrooms; zero otherwise. Beds4d Dummy variable equal to one for houses with four bedrooms; zero otherwise. Beds5d Dummy variable equal to one for houses with five or more bedrooms; zero otherwise. Baths2d Dummy variable equal to one for houses with two bathrooms; zero otherwise. Baths3d Dummy variable equal to one for houses with three or more bathrooms; zero otherwise. Fire2d Dummy variable equal to one for house with two or more fireplaces; zero otherwise. Storiesd Dummy variable equal to one for houses with more than one story; zero otherwise. Age Age of house in years at the time of its sale. Acres Lot size in acres. Distance Distance in miles from house to airport. Percentage of homes in the neighborhood in which a house was sold occupied by BlackPerc blacks; 2000 Census data is used for sales in all years. Series of dummy variables: City2d for College Park, City3d for Conley, City4d for City#d East Point, City5d for Forest Park, and City6d for Hapeville, using Atlanta as the base city. Noise65d_9503 Dummy variable equal to one for houses with the 65 decibel day-night sound level noise contour for both 1995 and 2003; zero otherwise. Noise70d_9503 Dummy variable equal to one for houses with the 70 decibel day-night sound level noise contour for both 1995 and 2003; zero otherwise. NoiseRegd Dummy variable equal to 1 if houses sold during 2000-2002; zero otherwise. Yeard Series of dummy variables for the year of the sale: 1996, 1997, 1998, 1999, 2000, 2001, and 2002, using 1995 as the base year. Noise65dDif Dummy variable equal to 1 if houses sold during 2000-2002 within the 65 decibel noise contour; zero otherwise. Noise70dDif Dummy variable equal to 1 if houses sold during 2000-2002 within the 70 decibel noise contour; zero otherwise. 27 Table 2: Summary Statistics, Full Sample -- 2370 Observations Count Frequency House Sales in the buffer zone -- 1995 contours 1008 42.53 House Sales in 65 db zone – 1995 contours 1113 46.96 House Sales in 70 db zone – 1995 contours 249 10.51 House Sales in Atlanta 111 4.68 House Sales in College Park 490 20.68 House Sales in Conley 417 17.59 House Sales in East Point 366 15.44 House Sales in Forest Park 833 35.15 House Sales in Hapeville 153 6.46 1 story 2143 90.42 2 or more stories 216 9.11 3 bedrooms 1589 67.05 4 bedrooms 261 11.01 5+ bedrooms 52 2.19 1 bathroom 1055 44.51 2 bathrooms 950 40.08 3+ bathrooms 365 15.40 0 or 1 fireplace 2297 96.92 2+ fireplaces 73 3.08 Mean Std. Dev. Price $ 71,692.37 $ 37,785.67 Distance 3.61 1.00 Age 37.85 16.04 Acres 0.40 0.37 BlackPerc 46.72 30.66 28 Table 3: Base Model -- Full Sample -- 1995 Contours Semi-Log Linear Parameter |t| Parameter |t| Noise65d_95 -0.026** 2.03 -3675.36*** 3.22 Noise70d_95 -0.011 0.45 -1207.04 0.39 NoiseRegd 0.136*** 10.37 10590.63*** 8.70 Distance -0.016 1.04 -2131.67* 1.73 Beds3d 0.080*** 3.93 2650.78 1.35 Beds4d 0.161*** 5.16 12397.86*** 3.63 Beds5d 0.210*** 3.14 23543.69*** 2.60 Baths2d 0.165*** 9.61 9324.92*** 6.58 Baths3d 0.329*** 10.10 25579.41*** 7.05 Fire2d 0.240*** 5.52 25058.19*** 3.60 Storiesd 0.109*** 3.22 15056.98*** 4.78 Age -0.002*** 2.95 -139.97 1.60 Acres 0.104*** 3.25 9285.77*** 2.67 BlackPerc -0.003*** 3.77 -227.74*** 4.14 City2d 0.181*** 4.95 10172.96*** 2.71 City3d -0.078* 1.81 -8400.52** 2.18 City4d 0.266*** 8.13 20095.15*** 5.18 City5d -0.092** 2.09 -10500.33*** 2.67 City6d 0.038 0.62 -3331.17 0.54 Constant 11.032*** 117.31 77245.03*** 9.02 Observations 2370 2370 R-squared 0.45 0.40 Robust t statistics in brackets * significant at 10%; ** significant at 5%; *** significant at 1% 29 Table 4: Summary Statistics, Reduced Sample -- 1643 Observations Count Frequency House Sales in the buffer zone 1008 61.35 House Sales in 65 db zone 568 34.57 House Sales in 70 db zone 67 4.08 House Sales in Atlanta 92 5.60 House Sales in College Park 354 21.55 House Sales in Conley 252 15.34 House Sales in East Point 261 15.89 House Sales in Forest Park 532 32.38 House Sales in Hapeville 152 9.25 1 story 1475 89.77 2 or more stories 158 9.62 3 bedrooms 1057 64.33 4 bedrooms 190 11.56 5+ bedrooms 40 2.43 1 bathroom 1326 80.71 2 bathrooms 667 40.60 3+ bathrooms 270 16.43 0 or 1 fireplace 1579 96.10 2+ fireplaces 64 3.90 Mean Std. Dev. Price $73,624.65 $38,315.04 Distance 3.54 1.10 Age 39.05 17.52 Acres 0.41 0.38 BlackPerc 44.23 30.82 30 Table 5: Base Models – Adjusted Housing Prices Semi-Log Linear Semi-Log Linear Parameter |t| Parameter |t| Parameter |t| Parameter |t| Noise65d_9503 -0.030* 1.76 -3962.4** 2.42 -0.028* 1.66 -3720.5** 2.19 Noise70d_9503 -0.063* 1.79 -9622.2*** 3.49 -0.062* 1.73 -9553.4*** 3.43 NoiseRegd 0.155*** 9.55 11624.38** 7.61 Distance -0.047** 2.43 -3939.3** 2.48 -0.046** 2.41 -3829.7** 2.45 Beds3d 0.093*** 3.73 3137.6 1.28 0.091*** 3.66 3046.6 1.26 Beds4d 0.141*** 3.64 11437.9*** 2.67 0.141*** 3.67 11487.0*** 2.69 Beds5d 0.130* 1.67 13365.2* 1.91 0.129* 1.67 13387.0* 1.91 Baths2d 0.195*** 9.25 11807.7*** 6.89 0.194*** 9.21 11743.3*** 6.88 Baths3d 0.357*** 10.14 27504.8*** 9.36 0.354*** 10.22 27373.6*** 9.50 Fire2d 0.226*** 5.10 20340.3*** 4.54 0.216*** 4.96 19817.4*** 4.45 Storiesd 0.156*** 4.65 16888.5*** 5.11 0.147*** 4.45 16405.1*** 4.96 Age -0.002*** 3.14 -158.8** 2.08 -0.002*** 3.24 -160.5** 2.13 Acres 0.113*** 3.41 10794.6*** 2.76 0.116*** 3.54 10875.7*** 2.80 BlackPerc -0.003*** 3.46 -251.7*** 3.97 -0.003*** 3.47 -250.6*** 4.04 City2d 0.172*** 3.89 10663.8** 2.38 0.177*** 3.92 11196.6** 2.40 City3d -0.068 1.24 -9579.7* 1.93 -0.065 1.19 -9365.3* 1.89 City4d 0.242*** 6.15 17534.1*** 3.73 0.243*** 6.11 17592.0*** 3.73 City5d -0.082 1.58 -11361.3** 2.40 -0.084 1.61 -11438.9** 2.41 City6d -0.033 0.48 -8612.8 1.25 -0.041 0.59 -9033.8 1.32 Constant 11.137*** 100.62 84972.2*** 8.74 11.052*** 94.93 78888.5*** 7.85 1996d 0.086** 2.17 5133.5** 2.13 1997d 0.066 1.53 5898.3* 1.66 1998d 0.063 1.57 3860.0* 1.68 1999d 0.156*** 4.27 10352.8*** 3.97 2000d 0.234*** 5.57 17407.7*** 5.19 2001d 0.243*** 6.60 18343.0*** 6.73 2002d 0.237*** 6.44 16256.6*** 5.95 Observations 1643 1643 1643 1643 R-squared 0.47 0.42 0.48 0.42 Robust t statistics in brackets * significant at 10%; ** significant at 5%; *** significant at 1% 31 Table 6: Base Models – Nominal Housing Prices Semi-Log Linear Parameter |t| Parameter |t| Noise65d_9503 -0.028* 1.66 -5340.1** 2.43 Noise70d_9503 -0.062* 1.73 -13351.2*** 3.74 Distance -0.046** 2.41 -5359.0** 2.55 Beds3d 0.091*** 3.66 3553.7 1.13 Beds4d 0.141*** 3.67 14751.2*** 2.63 Beds5d 0.129* 1.67 14814.7* 1.65 Baths2d 0.194*** 9.21 14953.0*** 6.52 Baths3d 0.354*** 10.22 34326.2*** 8.84 Fire2d 0.216*** 4.96 22669.6*** 3.94 Storiesd 0.147 4.45 23899.0*** 5.29 Age -0.002*** 3.24 -257.5*** 2.58 Acres 0.116*** 3.54 14851.3*** 2.83 BlackPerc -0.003*** 3.47 -334.4*** 3.99 City2d 0.177*** 3.92 14587.7** 2.15 City3d -0.065 1.19 -12981.7* 1.86 City4d 0.243*** 6.11 21205.1*** 3.25 City5d -0.084 1.61 -15900.3** 2.34 City6d -0.041 0.59 -13489.0 1.42 Constant 11.052*** 94.93 89331.9*** 6.52 1996d 0.118*** 2.98 7663.7*** 2.85 1997d 0.172*** 3.98 13837.3*** 3.44 1998d 0.231*** 5.78 15798.2*** 5.97 1999d 0.394*** 10.78 29399.0*** 9.48 2000d 0.531*** 12.63 44704.1*** 10.53 2001d 0.596*** 16.21 52176.9*** 14.89 2002d 0.644*** 17.48 55702.5*** 15.48 Observations 1643 1643 R-squared 0.58 0.49 Robust t statistics in brackets * significant at 10%; ** significant at 5%; *** significant at 1% 32 Table 7: Model With Differential Effects - Adjusted Housing Prices Semi-Log Linear Semi-Log Linear Parameter |t| Parameter |t| Parameter |t| Parameter |t| Noise65d_9503 0.013 0.53 47.05 0.02 0.014 0.61 337.4 0.15 Noise70d_9503 -0.021 0.39 -5657.98 1.53 -0.018 0.32 -5405.3 1.42 NoiseRegd 0.189*** 8.95 14929.14*** 7.48 Noise65dDif -0.091*** 2.62 -8658.68*** 2.81 -0.092*** 2.63 -8716.1*** 2.74 Noise70dDif -0.092 1.51 -8671.62* 1.87 -0.097 1.53 -8988.2* 1.90 Distance -0.045** 2.33 -3749.20** 2.35 -0.044** 2.31 -3641.5** 2.32 Beds3d 0.096*** 3.86 3389.93 1.40 0.093*** 3.80 3299.9 1.38 Beds4d 0.142*** 3.68 11510.04*** 2.69 0.142*** 3.71 11562.4*** 2.71 Beds5d 0.128* 1.66 13261.90* 1.89 0.128* 1.65 13271.2* 1.89 Baths2d 0.195*** 9.31 11849.89*** 6.93 0.195*** 9.30 11836.5*** 6.96 Baths3d 0.358*** 10.18 27532.65*** 9.37 0.355*** 10.27 27427.2*** 9.53 Fire2d 0.228*** 5.07 20536.93*** 4.54 0.217*** 4.92 19945.2*** 4.44 Storiesd 0.162*** 4.85 17503.77*** 5.29 0.154*** 4.65 17072.0*** 5.13 Age -0.002*** 3.08 -152.90** 2.01 -0.003*** 3.17 -154.3** 2.05 Acres 0.110*** 3.32 10475.24*** 2.68 0.112*** 3.45 10571.3*** 2.72 BlackPerc -0.003*** 3.22 -235.74*** 3.76 -0.003*** 3.23 -234.9*** 3.84 City2d 0.183*** 4.11 11691.53*** 2.63 0.187*** 4.14 12208.6*** 2.64 City3d -0.063 1.14 -9109.94* 1.85 -0.061 1.09 -8899.3* 1.82 City4d 0.240*** 6.10 17327.39*** 3.70 0.241*** 6.05 17367.7*** 3.69 City5d -0.075 1.43 -10628.59** 2.28 -0.076 1.46 -10693.3** 2.29 City6d -0.018 0.27 -7202.01 1.06 -0.026 0.37 -7594.1 1.13 Constant 11.095*** 100.69 81023.73*** 8.55 11.008*** 94.84 74757.8*** 7.61 1996d 0.090** 2.29 5560.4** 2.32 1997d 0.071 1.64 6374.9* 1.77 1998d 0.060 1.52 3636.4 1.60 1999d 0.156*** 4.29 10373.2*** 3.99 2000d 0.271*** 6.05 20954.0*** 5.64 2001d 0.277*** 6.87 21612.5*** 7.01 2002d 0.275*** 6.78 19859.8*** 6.45 Observations 1643 1643 1643 1643 R-squared 0.47 0.42 0.48 0.43 Robust t statistics in brackets * significant at 10%; ** significant at 5%; *** significant at 1% 33 34 35 36 37
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Rene Pannevis
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I was born in The Netherlands (1979) in a hippie neighborhood where life was a circus. After graduating High School I worked at a TV-recycle factory where people lost body parts, in garbage and the sanitary sewer system, and at a coffee factory where I developed my taste for coffee. In 2007 I received a bachelor degree in Film Study at Utrecht University. The same year I enrolled in M.F.A. film directing program NYU Tisch School of the Arts. In 2010 I started a fulltime job at Wieden+Kennedy Amsterdam as editor and filmmaker. Directed and edited TVC's including award winning digital content. In November 2012 I finished my thesis film Junkie XL and obtained my M.F.A in directing at NYU Tisch. My shorts Godverdomme!, DJ Tiesto and Junkie XL played at several festivals including Palm Springs, CFC, Brussels Int., Madness Toronto, Singapore Int. Jimff and Hamburg IKKF.
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