Tierra Grande - October 2018

OCTOBER 2018 â„¢

JOURNAL OF THE REAL ESTATE CENTER AT TEXAS A&M UNIVERSITY

NON-PROFIT ORG. U.S. POSTAGE PAID HOUSTON, TEXAS PERMIT No. 4126 COLLEGE STATION, TEXAS 77843-2115

In This Issue Center's New Home Price Index Texas Homestead Law Stocks Versus Homes Apartment Market Business Cycles WOTUS Update Houston's Floodplain Regulations Victoria's Economy

Helping Texans make better real estate decisions since 1971

OCTOBER 2018 â„¢

JOURNAL OF THE REAL ESTATE CENTER AT TEXAS A&M UNIVERSITY

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TEXAS

LOUISIANA

ALABAMA

MISSISSIPPI

LAND MARKET TRENDS

•

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•

TRACT SIZES

AVAILABLE ONLY FROM THE REAL ESTATE CENTER GIT YER DATA TODAY AT RECENTER.TAMU.EDU

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Visit us online at

www.recenter.tamu.edu

Director, GARY W. MALER Chief Economist, JAMES P. GAINES Senior Editor, DAVID S. JONES Managing Editor, BRYAN POPE Associate Editor, KAMMY BAUMANN Communications Specialist, HAYLEY RIEDER

OCTOBER 2018

VOLUME 25, NUMBER 4 ™

TIERRA GRANDE JOURNAL OF THE REAL ESTATE CENTER AT TEXAS A&M UNIVERSITY

10 Victoria at a Crossroads

Victoria may have been knocked around by Hurricane Harvey, but with a housing market that looks to be gaining ground and more industrial growth on the way, the South Texas regional hub still has plenty of fight left.

BY JOSHUA G. ROBERSON

Creative Director, ROBERT P. BEALS II Graphic Specialist/Photographer, JP BEATO III Graphic Designer, ALDEN DeMOSS Circulation Manager, MARK BAUMANN Lithography, RR DONNELLEY, HOUSTON

ADVISORY COMMITTEE: Doug Jennings, Fort Worth, chairman; Besa Martin, Boerne, vice chairman; Troy C. Alley, Jr., DeSoto; Russell Cain, Port Lavaca; JJ Clemence, Sugar Land; Alvin Collins, Andrews; Walter F. “Ted” Nelson, Houston; Doug Roberts, Austin; C. Clark Welder, Fredericksburg; and Jan Fite-Miller, Dallas, ex-officio repre­ senting the Texas Real Estate Commission.

TIERRA GRANDE ™ (ISSN 1070-0234) is published quarterly by the Real Estate Center at Texas A&M University, College Station, Texas 77843-2115.

Telephone: 979-845-2031.

VIEWS EXPRESSED are those of the authors and do not imply endorsement by the Real Estate Center, Mays Business School, or Texas A&M University. The Texas A&M University System serves people of all ages, regardless of socioeconomic level, race, color, sex, religion, disability, or national origin. Nothing in this publication should be construed as legal or tax advice. For specific advice, consult an attorney and/or a tax professional.

PHOTOGRAPHY/ILLUSTRATIONS: JP Beato III, pp. 1, 11, 14–15, 26, 27, 28; Getty Images, pp. 5, 8–9; Robert Beals II, pp. 6–7; Alden DeMoss, pp.

23–23. © 2018, Real Estate Center. All rights reserved.

2 Curtain Up

Unveiling a New Tool for Homebuyers and Sellers There’s no one home price index to rule them all. Still, using repeat sales analysis and splitting homes by price tier can certainly give one an edge over another. With that in mind, roll out the red carpet because the Real Estate Center’s new Texas Home Price Index has arrived.

BY JOSHUA G. ROBERSON

Drone photo of Brazos County farmland

PHOTOGRAPHER Alden DeMoss

OCTOBER 2018

Texas Apartment Markets Recovering Good times and bum times—apartment markets have both. They can also reside somewhere in between, riding a period of slow but steady growth. That’s where apartment markets in Texas’ major metros are currently headed. Find out why.

BY ALI ANARI & HAROLD D. HUNT

6 Homestead Advantage

20 Treading Water

8 Nest or Nest Egg?

22 Highs & Lows

When it comes to the state’s homestead law, the tax exemption gets all the attention because it means more money in the bank for homeowners. Equally important are two lesser-known provisions that protect homeowners from creditors and protect occupancy rights. Here’s what you need to know.

BY RUSTY ADAMS

ON THE COVER

14 Steady as She Goes

It hasn’t exactly been smooth sailing for the Waters of the United States rule since its adoption in 2015. WOTUS, which sought to define waters that fall under the Clean Water Act, has been challenged, blocked, and rewritten. Take a deep breath because a resolution could be in sight.

BY CHARLES E. GILLILAND

Hatching Best Investment Plan

of Floodplain Regulations

A home is more than just a place to sleep and store stuff—it’s an investment. Does it yield a bigger return than investing in the stock market?

For people deciding whether to put their money toward a down payment or buy stock, that’s an important question. The answer, though, is complex.

BY HAROLD D. HUNT & CLARE LOSEY

Houston has adopted new building regulations intended to protect homes in the city’s most flood-prone areas. The regulations will increase new-home construction costs, but they could also have human and economic benefits.

Whether those benefits will outweigh the cost increases is the big unknown.

BY ALI ANARI & JAMES P. GAINES

1

Residential

Unveiling a New Tool for Homebuyers and Sellers

By Joshua G. Roberson

E

ven people who don’t work in real estate recognize that Texas’ home prices keep increasing. At the end of 2017, the median residential home price in Texas was $224,000, but there was a large disparity between the four major metro areas and the rest of the state. The average median price in Dallas-Fort Worth, Houston, Austin, and San Antonio was $246,243 while in all other Texas metros the average median price was $164,379.

Roll back just ten years to see how much has changed. At that time, the overall state median price was $146,105, or 65 percent of the 2017 amount. In the major metros, the price was $139,666, and for all other metros the price was just $60,449—significant differences over a ten-year period, even after accounting for inflation (Figure 1).

Figure 1. Changes in Texas’ Home Prices $246,243 $164,379

$139,666 $60,449

2007

2017

Four Major Metro Areas

2007

2017

Other Metro Areas

Source: Real Estate Center at Texas A&M University

To help shed some light on home price changes, the Real Estate Center has rolled out its online, quarterly Texas Home Price Index (HPI) at recenter.tamu.edu.

The index, which is made possible through a research agreement with the Texas Association of Realtors, covers the state’s four big metros and a handful of midsized ones. In addition, it provides indexes by price tier for some of the larger Texas markets. But more on that later.

2

How Prices Got There Part of the reason for the massive price swing is the difference in economic climates. In 2007, the United States’ financial system was feeling the pain brought on by the housing market collapse. Even though Texas wasn’t as directly exposed to the housing bubble as other states were, its economy nonetheless stalled along with the national economy.

The U.S economy is still seeking full recovery, but Texas’ resilient growth has bolstered home values. However, this only explains why overall Texas home prices have grown so rapidly. What is the best way to measure and compare price changes from market to market?

The Trouble with Home Sale Price Statistics Home price statistics, such as average or median price, are familiar and commonly used metrics to follow pricing trends from market to market. They are typically generated by aggregating home sales data within a specific area during a set period. For example, all sales within Dallas County are summed up in one aggregated figure, and an average (or median) is computed. ata for these statistics normally come from either public records, proprietary data collection processes, or through the Multiple Listing Service (MLS). Because Texas is a non-disclosure state, final pricing data more often come through the MLS. The Real Estate Center publishes a variety of pricing metrics on its website under “Housing Activity.”

When using these metrics to analyze a market’s pricing trends, keep in mind only a small percentage of a market’s housing stock is sold at any given time. This is normally not a big deal, but sometimes short-term swings in market trends can lead to exaggerated pricing analytics. These swings can be due to changing consumer demands or sudden scarcity in certain market segments. In either case, these causes can be hard to see on paper when aggregating pricing data.

Because of constant changes in market mix, using general home sales statistics alone may not be the best

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way to follow price growth. Due to these shortcomings, other methods have been developed to measure housing price appreciation more accurately.

Mini-Case Study: The Woodlands In mid-2014, the price of oil per barrel began falling sharply after riding through several boom years. Oil prices bottomed out in early 2016 and have gradually risen since. To no one’s surprise, this fall in oil had an impact on Texas’ economy and housing markets.

Housing statistics for The Woodlands between 2015 and 2016 include what may look like a big fallout in prices following the oil bust. At the end of 2015, the median price of homes sold was $360,000, while at the end of 2016 it was $327,750, a whopping 8 percent year-over-year fall. While it would be easy to generalize this as a decrease in market home prices due to oil, further analysis reveals a little more behind the scenes.

During those two years, The Woodlands’ housing market had a temporary market shift. Overall sales volume dropped between one year and the next. In addition, sales of larger homes (around 4,000 square feet or more) stalled in 2016, which then increased the proportion of smaller homes. While falling oil prices most likely had an overall dampening effect on this housing market as they did on many others, changes in market mix may have also played a hand in exaggerating the price change.

Given how different one house is from another within a market, big changes in market mix make it that much harder to follow overall price trends. This is especially the case if the stock of one type of home is

temporarily disproportional compared with the overall stock. Changes in market mix, like those that occurred in The Woodlands, raise a question: are the same types of houses being compared from one period to another?

Advantages of Repeat Sales Analysis One of the more popular methods of identifying market price appreciation is through the repeat sales analysis.

That is, measuring the change in sales price from multiple sales of the same house.

Repeat sales analysis has a few advantages over other types of analysis. First, home sales are screened to identify properties that have sold at least twice. This helps with the issue of changing market mix from period to period because the analysis focuses on the same property over time instead of different mixes of properties. Second, looking at properties that have sold multiple times shifts the focus to the change in price since the last sale of a specific property. This helps capture appreciation. epeat sales analysis takes another step to isolate true home price appreciation. Ideally, the analysis includes only homes that have had no or minimal physical changes to focus on market-driven price appreciation.

Take, for example, a home purchased ten years ago but that now has an additional bedroom and a pool.

Both of these improvements are likely to add value to the home. Repeat sales analysis is interested only in market-driven price appreciation. This property would be eliminated from analysis because there would be no way to differentiate between price change from the homeowner’s improvements and price change from general market forces.

R

Isolating Home Price Appreciation

65% PRICE APPRECIATION 123

JANUARY 2007 $150,000 OCTOBER 2018

Market forces or home improvements?

123

JANUARY 2017 $247,500 3

Home Price Indexes With data now focused on price change, it’s possible to re-examine market-driven price appreciation by aggregating these records into an HPI. Currently, a handful of repeat sales HPIs are publicly available.

These include the Federal Housing Finance Agency (FHFA) HPI, the Freddie Mac HPI, and the S&P CoreLogic Case-Shiller HPI. Each is based on the same core methodology but differ mainly in their data sources and model tweaks. oth the FHFA and Freddie Mac indexes are constructed using mortgage data through their mortgage pipelines. The FHFA index is actually a joint effort between Fannie Mae and Freddie Mac to maximize geographic coverage of home price index estimates. This data source helps both of these publishers provide Texans with a wide variety of home price metrics at the metropolitan and county levels. These indexes are limited by conventional conforming loans which, by nature, exclude higherpriced homes funded through jumbo loan financing.

The S&P CoreLogic Case-Shiller HPI is published through S&P Dow Jones Indices and is sourced by public housing records and various data partnerships. This index is renowned and commonly quoted through various news outlets. The index is available for the largest U.S. markets and may include additional indexes for condominiums and indexes by low-, middle-, and high-priced tiers.

However, its coverage of Texas is limited to the Dallas-Fort Worth market.

Index January 2000=100

B

Another price slowdown occurred shortly after 2014 when the oil boom ended.

The trends for the two indexes are similar. However, the repeat sales index falls below the median price series. This is partly because repeat sales indexes inherently include only existing homes because those are the homes most likely to have sold more than twice.

This is actually a criticism of the repeat sales model since it excludes newer homes that tend to have higher prices. One way of looking at this, though, is that the repeat sales model follows the existing housing stock instead of the immediate housing market trends. It’s a good example of how there is no one model to rule them all. Home price indexes are best at describing longer-term price growth while home sales statistics are best at describing the price of what has sold at that time.

Figure 3. Houston Home Price Index

by Price Tier

200

175

150

125

100 1999

2003

2007 Low

Figure 2. Houston Home Price Index

Index January 2000=100

250

2015

2019

High

Source: Real Estate Center at Texas A&M University

A

nother way to use repeat sales indexes is by splitting the properties by price tiers (Figure 3). This is done by grouping properties against other home prices when the properties are first purchased. Following these properties across time in Houston revealed that, while each price tier grew year over year, Houston’s lower-priced homes tended to ride the highs and lows with greater magnitude than homes in the higher-priced cohorts. Lower-priced homes began diverging from the pack in 2014, possibly due to the general rising scarcity in lower-priced homes.

200

150

100 2000

2003

2006

2009

Home Price Index

2012

2015

2018

Median Price Index

Source: Real Estate Center at Texas A&M University

A Look at REC’s New Index A sample of the Center’s HPI for Houston (Figure 2) shows the city’s housing market has gone through a number of real estate cycles since the beginning of the series in 2003. A slowdown in price appreciation began in 2007 after a long period of year-over-year growth.

4

2011

Medium

Roberson (jroberson@mays.tamu.edu) is a senior data analyst with the Real Estate Center at Texas A&M University.

THE TAKEAWAY With an improved and expanded database through the Data Relevance Program with the Texas Association of Realtors, the Real Estate Center is now able to generate a repeat sales home price index for Texas’ four major metros as well as for several smaller metros.

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Residential

Homestead Advantage

By Rusty Adams

T

he concept of “homestead” has been part of Texas law since colonial times when Stephen F. Austin persuaded the legislature of Coahuila y Tejas to adopt laws exempting certain property from the claims of creditors. Although the law was briefly repealed, it returned to Texas law in 1839 and has been so enshrined ever since.

The primary purpose originally was to encourage settlement.

Additionally, homestead law protects the home and some means of support, thus keeping families off the public dole, fostering independence, and preserving the integrity of the family as the basic unit of society.

While most Texans have at least some knowledge of the concept of the homestead, the term may have several different implications depending on the context. Texas homestead provisions fall into three general categories: the homestead OCTOBER 2018

exemption from taxation, homestead protection from creditors, and the homestead right of occupancy.

The most common reference to the “homestead exemption” by the general public is to the exemption from ad valorem taxation. A certain portion of the appraised value of a principal residence is excluded from the taxable value. For this purpose, the residence homestead means a structure or a separately secured and occupied portion of a structure, together with up to 20 acres on which the structure sits. Improvements used in the residential occupancy of the structure are also included.

The structure may be a mobile home, and the mobile home will qualify for the exemption even if it is sitting on leased land, as long as the occupant owns the structure. The structure must be designed or adapted for use as a residence and be occupied by the owner or a surviving spouse who has a life estate in the property. It may be owned directly, or it may be owned indirectly through a beneficial interest in a qualifying trust. In this case, a qualifying trustor or beneficiary must occupy the residence.

In the vast majority of Texas school districts, residence homesteads are allowed an exemption of $25,000 of the home’s value for school taxes. In a few cases, only $5,000 of this exemption applies. Homeowners who are 65 or older and disabled cannot receive double that exemption amount.

Any taxing unit has the option to offer an additional “localoption” exemption of at least $3,000 for taxpayers who are 65

5

or older, disabled, or both. If counties collect taxes for farmto-market roads or flood control, the residence homestead is allowed a $3,000 exemption. However, if the county offers the local-option exemption, the homeowner does not receive both $3,000 exemptions—only the local-option exemption.

Additionally, any taxing unit has the option to offer an exemption of up to 20 percent of the homestead’s value, but the exemption must be at least $5,000.

Those who qualify for a residence homestead exemption from property taxes may file an application for the exemption with the appraisal district in the county where the property is located.

T

he homestead of a family or a single adult is protected from forced sale for the purposes of paying debts and judgments. Even an abstracted judgment lien will not attach to a homestead property as long as the property retains its homestead character. There are exceptions.

The homestead may be taken for purchase money liens (i.e., mechanic’s and materialman’s liens; certain home improvement, home equity, and refinance transactions; reverse mortgages; owelty liens; and the refinance of a lien on a mobile home attached to the homestead. To qualify for homestead protection, the homestead must be established before the lien attaches to the property. If the lien is in place before the property becomes a homestead, there is no protection.

Homestead rights also include the right to occupy the property. The right to occupy the homestead extends to all family members who continue to occupy it, including those who

occupy the property after the owner’s death. This protection applies to: • a spouse, • a surviving spouse, • minor children (and in some circumstances their guardian), and • unmarried children.

Children may not claim their homestead rights until the death of the surviving spouse. For the children to claim homestead rights, the surviving spouse must not have abandoned the homestead. This protection applies even when someone else owns the property.

For example, say a homestead is the separate property of the husband. The husband dies and leaves the property to his cousin. As long as the surviving wife does not abandon the homestead, she still has a right to occupy the property even though the cousin is the owner.

Homestead rights commence when the owner: • obtains the right to possess the land, • uses the property as a homestead, and • intends to claim the land as a home.

Typically, a homestead becomes a homestead when the owner occupies and uses the premises as a principal residence.

An affidavit designating the property as a homestead is commonly filed in the real property records of the county where the property is located. This is done to establish the homestead for purposes of the property tax exemption and to protect it from creditors.

An owner who owns multiple properties may wish to establish which of the properties is the homestead. A lender may require a borrower to designate which property is and is not a

By Robert W. Gilmer

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homestead as a condition of the loan. If there is a creditor and the owner owns property larger than the homestead limits, the creditor may require the owner to designate which property is protected. In such a case, the remaining property is subject to forced sale.

The owner does not actually have to reside on the property to claim a homestead. However, the owner must presently intend to occupy and use the property in a reasonable and definite time in the future and must have taken some action to prepare for occupying and using the property as a homestead. omesteads must be based on real property, not personal property. Therefore, a mobile home that is not affixed to the land does not qualify. However, it is possible for a leasehold interest and a life estate to qualify, as well as land held in trust for a beneficiary.

A person may have only one homestead at a time. Nevertheless, it is permissible for homestead protections to “roll over” from one property to another, and the proceeds from the sale of the first homestead may be used to purchase the next. The protection applies to the proceeds as long as they are used to purchase a homestead within six months. If the home is damaged or destroyed, the insurance proceeds are exempt for six months from the date when the owner had a right to demand payment from the insurer. In the event of an involuntary sale, such as a condemnation, the owner may purchase another homestead within “a reasonable time.”

H

An urban homestead for a family or single adult includes up to ten acres used as a home or as both a home and a place to exercise a calling or business. This may be in one or more lots, and it includes any improvements on the land. The lots are usually contiguous, although they need not be as long as they are used together for homestead purposes.

UNDER TEXAS’ HOMESTEAD LAW, qualified homeowners are allowed an exemption of $25,000 of the home’s value for school taxes.

Those who are 65 or older or disabled qualify for an additional $10,000 exemption.

A rural homestead includes up to 100 acres for a single person or 200 acres for a family. The land may be in one or more parcels, and the homestead includes any improvements on the land. The rural homestead may include noncontiguous tracts if they are used in connection with the home tract for the comfort, convenience, or support of the family. An example would be where a separate parcel is farmed to support the family, although the family lives elsewhere. For this rule to apply, the land where the home sits must be rural. The family may not have both urban and rural homesteads.

A homestead is considered urban if it is: • within the limits or extraterritorial jurisdiction of a municipality or • part of a platted subdivision and served by: • police protection, • paid or volunteer fire protection, and • at least three of the following services provided by a municipality or under contract to a municipality: o

electric,

o

natural gas,

o

sewer,

o

storm sewer, and

o

water.

Otherwise it is rural. The urban or rural characterization is determined when the homestead is designated. Once a rural homestead is established, it remains a rural homestead, even if the surrounding area becomes urban.

Property remains a homestead until death, abandonment, or sale. If the owner dies, the homestead terminates unless there are surviving family members who are still entitled to homestead rights. A homestead is considered abandoned when its use is discontinued and there is no intent to use the property again as a home. Even a temporary absence from the home is not abandonment unless there is intent to discontinue use as a home. The burden of proof for abandonment is on the creditor. inally, the homestead may cease when it is sold. If both spouses are living, they are both required to sign the conveyance. Care must be taken when selling a homestead, however. Certain types of transactions, such as “sale and lease back” transactions and “pretended sales,” will result in a loss of homestead protection.

This article discusses the most common homestead exemptions and protections, but it is not exhaustive. Nothing in this publication should be construed as legal advice. For specific advice, consult an attorney.

F

Adams (radams@mays.tamu.edu) is a member of the State Bar of Texas and a research attorney for the Real Estate Center at Texas A&M University.

THE TAKEAWAY Most Texas homeowners are aware of the homestead law that exempts them from certain taxes, but the law provides two other key provisions: homestead protection from creditors and the right of occupancy.

OCTOBER 2018

7

Investment

Nest or Nest Egg? Hatching Best Investment Plan

By Harold D. Hunt & Clare Losey

B

Buying a home is typically the largest investment a household makes. One alternative is to rent a home and invest the down payment in something else. From purely an investment perspective, the anticipated rate of return plays a crucial role in the homebuying decision. This article compares the financial gains from investing in the stock market with the gains from purchasing a home. Households faced with either renting and investing in the stock market or purchasing a home should consider the historic performance of both before making their choice.

The point of initial investment ranges from the beginning of 2000 to the beginning of 2016, a period with significant disruptions in both the stock and housing markets.

Multiple investment opportunities are available to households. However, stocks and real estate have shown to be two of the more popular. According to the Survey of Consumer Finances (conducted by the Federal Reserve Bank), 63.7 percent of all families in the United States held a primary residence in 2016, while 51.9 percent of all families had direct or indirect stock holdings.

8

Although the proportion of families who held a primary residence was somewhat similar to the proportion of families with direct or indirect stock holdings, the values of the assets differed significantly. In 2016, the median value of stocks for families with direct or indirect stock holdings was $40,000, whereas the median home value was almost five times that at $185,000. Home equity depends on whether the homeowner holds a mortgage and the remaining mortgage balance.

By renting and investing in a stock portfolio, the household forgoes the potential to earn appreciation from homeownership but may benefit from selling the stock at a profit. Conversely, by purchasing a home, the household forgoes the future earnings from a stock portfolio as well as the potential to earn dividends. However, renting can cost more than homeownership, in which case a renter household might not have the funds to invest in a stock portfolio.

The question is, if between 2000 and 2016 a household had the option of either renting (and consequently investing in the stock market) or purchasing a home, which provided the greater financial gain? The answer isn’t simple.

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Stocks versus Homes

N

umerous differences complicate a comparison between renting and investing in the stock market and purchasing a home. The Real Estate Center’s analysis attempted to control for the differences through a number of assumptions.

• The household either purchases a home or rents and invests the entire down payment in a stock portfolio at the beginning of the year.

• In the case of a home purchase, the household meets the qualifying requirements for purchasing a home.

• In the case of an investment in stocks, the household does not trade any stocks during the holding period and reinvests all dividends (a buy-and-hold investment strategy).

• The household does not face any constraints in the sale of either the stock portfolio or the home.

• The internal rate of return (IRR) results, based on stock portfolio and home price appreciation or depreciation, are the sole criteria for buying versus renting. The analysis does not account for qualitative differences between OCTOBER 2018

owning and renting, any advantage from leverage in homeownership, or any equity increase from mortgage balance reduction.

• Households seek a longer-term investment in a primary residence. Second-home or investment property purchases are not considered.

Assume a household with $10,000 has two options: rent and open an investment portfolio or spend the money on a down payment on a home. For this analysis, the home price is $100,000.

Investment Portfolio The value of the investment portfolio at the end of each year after a minimum two-year hold, depends on the year the $10,000 was invested (Table 1). Table 2 depicts the IRR on the initial investment based on the year in which the portfolio is liquidated.

The timing of the initial investment, the duration of the holding period, and the volatility in the stock market during the holding period produce dramatically different returns. In general, opening a portfolio in a year with strong stock market

9

returns produces a higher initial IRR due to the positive impact of compounding in the early years.

For example, a portfolio opened in the beginning of 2003 earned an IRR of +12.7 percent after five years (at the end of 2007). The high return stems from the large upswing in the market in the initial year (+19.2 percent) as well as fairly strong growth in the following years, ranging from +12.7 to +14.6 percent (Table 2).

Higher growth in the initial years of a holding period effectively acts as a hedge against future market downturns.

Conversely, a portfolio opened in a year characterized by a stock market decline needs much higher growth in subsequent years to recoup the early losses during the initial years of the holding period. A stock portfolio opened in the beginning of 2002 earned a return of just +6.1 percent after five years (at the end of 2006). Return is significantly lower, as the +0.1 percent increase in the initial year significantly lessened

the impact of subsequent stock market growth on the portfolio’s value (Table 2). ow do the IRRs compare if both portfolios were sold at the end of 2008 during the early stages of the Great Recession (GR)? At +2.4 percent, the return for a portfolio opened in 2003 remains slightly higher than the –1.5 percent return for a portfolio opened in 2002. The poor +0.1 percent annual return in 2002 diminished the ability of the portfolio opened that year to offset the downturn in 2008. By comparison, the initial strong growth in 2003 allowed the portfolio opened that year to better offset the decline in 2008 (Table 2).

H

Home Purchase Home values at the end of each year the home could have been sold, based on the year of purchase and FHFA home price

Table 1. Value of Initial $10,000 S&P 500 Stock Portfolio at Year-End Year of Initial Investment (Beg. of Year) 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

In Dollars 2001

2002

8,019

6,257 6,879

2003

2011

2012

2013

2014

2015

2016

2017

8,032 8,895 9,325 10,780 11,372 7,215 9,086 10,433 10,652 8,829 9,778 10,250 11,851 12,501 7,931 9,988 11,469 11,710 10,016 11,092 11,628 13,444 14,181 8,998 11,331 13,011 13,284 14,214 14,902 17,228 18,173 11,530 14,521 16,673 17,023 11,610 13,422 14,158 8,983 11,313 12,990 13,262 12,120 12,785 8,112 10,216 11,730 11,976 12,195 7,738 9,744 11,189 11,423 6,693 8,429 9,678 9,881 7,990 9,175 9,367 14,460 14,763 11,723

2004

2005

2006

2007

2008

2009

2010

12,345 13,570 15,394 19,728 15,370 13,879 13,239 11,451 10,856 17,109 13,586 11,832

16,313 17,932 20,343 26,069 20,310 18,340 17,494 15,132 14,345 22,609 17,953 15,636 15,314

18,519 20,358 23,094 29,595 23,057 20,820 19,860 17,178 16,285 25,667 20,381 17,750 17,386 15,002

18,774 20,638 23,413 30,003 23,375 21,108 20,134 17,415 16,510 26,021 20,662 17,995 17,625 15,209 11,509

20,985 23,068 26,169 33,536 26,127 23,593 22,505 19,466 18,453 29,084 23,095 20,114 19,700 16,999 12,864 11,331

25,526 28,060 31,832 40,793 31,781 28,698 27,375 23,678 22,447 35,379 28,093 24,467 23,964 20,678 15,648 13,784 13,596

Sources: Real Estate Center at Texas A&M University and Dr. Aswarth Damodaran (New York University)

Table 2. IRR from S&P 500 Stock Portfolio at Year-End Year of Initial Investment (Beg. of Year) 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Percent 2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

–10.5

–14.5 –17.1

–5.3 –4.1 0.1

–2.3 –0.6 3.5 19.2

–1.2 0.5 3.8 14.2 7.7

1.1 2.9 6.1 14.6 10.3 10.1

1.6 3.2 6.0 12.7 9.1 8.5 10.4

–3.6 –2.9 –1.5 2.4 –2.1 –5.1 –8.2 –18.2

–1.0 0.0 1.6 5.5 2.1 0.4 –0.6 –5.5 –10.6

0.4 1.4 3.0 6.6 3.8 2.7 2.3 –0.8 –2.8 20.2

0.5 1.4 2.9 6.1 3.6 2.6 2.2 –0.2 –1.6 13.9 8.3

1.6 2.6 4.0 7.0 4.9 4.2 4.1 2.3 1.7 14.4 10.8 8.8

3.6 4.6 6.1 9.1 7.3 7.0 7.2 6.1 6.2 17.7 15.8 16.1 23.8

4.2 5.2 6.7 9.5 7.9 7.6 7.9 7.0 7.2 17.0 15.3 15.4 20.2 22.5

4.0 4.9 6.3 8.8 7.3 7.0 7.2 6.4 6.5 14.6 12.9 12.5 15.2 15.0 7.3

4.5 5.4 6.6 9.0 7.7 7.4 7.7 6.9 7.0 14.3 12.7 12.4 14.5 14.2 8.8 6.4

5.3 6.3 7.5 9.8 8.6 8.4 8.8 8.2 8.4 15.1 13.8 13.6 15.7 15.6 11.8 11.3 16.6

Sources: Real Estate Center at Texas A&M University and Dr. Aswarth Damodaran (New York University)

10

TIERRA GRANDE

Table 3. Value of $100,000 Home at Year-End Year of Home Purchase (Beg. of Year) 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

In Dollars 2001

2002

2003

2004

113,156 117,164 120,770 124,026 110,433 113,831 116,901 106,729 109,606 105,857

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

129,482 122,043 114,428 110,514 107,214

136,772 128,914 120,870 116,736 113,250 110,277

143,812 135,550 127,092 122,744 119,080 115,953 111,067

146,476 138,061 129,446 125,018 121,286 118,101 113,124 107,095

146,684 138,257 129,630 125,196 121,458 118,269 113,285 107,247 101,997

144,807 136,488 127,971 123,594 119,904 116,755 111,835 105,875 100,692 98,861

142,782 134,579 126,181 121,865 118,226 115,122 110,271 104,394 99,283 97,478 97,340

144,942 136,615 128,091 123,709 120,015 116,864 111,940 105,974 100,786 98,953 98,813 100,093

151,518 142,813 133,902 129,321 125,460 122,166 117,018 110,781 105,358 103,442 103,296 104,634 106,119

162,556 153,217 143,657 138,743 134,600 131,066 125,543 118,852 113,034 110,978 110,821 112,257 113,850 112,152

174,870 164,824 154,539 149,253 144,797 140,995 135,053 127,856 121,597 119,385 119,216 120,761 122,474 120,648 115,412

188,473 177,644 166,560 160,862 156,059 151,962 145,558 137,801 131,055 128,671 128,489 130,154 132,001 130,033 124,390 115,943

203,585 191,889 179,915 173,761 168,573 164,147 157,230 148,850 141,563 138,988 138,792 140,590 142,585 140,459 134,364 125,240 116,420

Sources: Real Estate Center at Texas A&M University and FHFA Home Price Index

appreciation data for Texas, is shown in Table 3. Table 4 shows the IRR based on those values. imilar to renting and investing in the stock market, the return for a home purchase is affected by the timing of the initial investment and the duration of the holding period. While high market volatility significantly impacted the range of stock market investment returns, the low volatility in Texas’ housing market tempered homeowners’ returns.

Overall, lower volatility translated into much less IRR variation from homeownership than from the S&P 500 portfolio.

Annual IRR ranged from –1.3 to +7.9 percent for a home purchase (Table 4) versus –18.2 to +23.8 percent for the stock market portfolio (Table 2). Thus, households had the potential

S

to earn a significantly higher rate of return from the stock market than from owning a home. However, they also risked losing substantially more money. Both results rely heavily on the timing of the initial investment.

In the years immediately preceding the GR’s housing downturn, the return on homeownership remained relatively unchanged. Unlike states such as California and Florida, Texas experienced neither excessively high home price appreciation during the national housing boom of the mid-2000s nor the exceptional price decline immediately after the GR. Since the GR, Texas home prices have increased more rapidly. For homes purchased from 2013 to 2016, the IRR from homeownership ranged from +5.9 to +7.9 percent (Table 4).

RETURN ON INVESTMENT is only one of many factors to look at when deciding whether to purchase a home or rent and invest in the stock market.

Households should also consider the obligations of homeownership, current stock market and housing market conditions, and the social and community aspects of owning versus renting.

OCTOBER 2018

11

More Rewarding Investment?

Based on the IRR, renting and investing in the stock market was generally the more financially rewarding option for a household that invested between 2000 and 2016 (Table 5).

If the initial investment was made in 2000 or 2001, homeownership was, on average, the option that yielded a higher return through 2012. However, for all other years, on average,

investing in the stock market proved the more financially beneficial option.

Alternatively, the higher incidence of negative returns and greater return volatility experienced in the stock market indicates renters assumed much greater risk compared with buying a home. The IRR from a stock portfolio produced negative returns 23 times (Table 2). Meanwhile, IRR from homeownership produced negative returns in only six instances (Table 4).

Table 4. IRR From Homeownership at Year-End Year of Home Purchase (Beg. of Year) 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Percent 2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

6.4

5.4 5.1

4.8 4.4 3.3

4.4 4.0 3.1 2.9

4.4 4.1 3.4 3.4 3.5

4.6 4.3 3.9 3.9 4.2 5.0

4.6 4.4 4.1 4.2 4.5 5.1 5.4

4.3 4.1 3.8 3.8 3.9 4.2 4.2 3.5

3.9 3.7 3.3 3.3 3.3 3.4 3.2 2.4 1.0

3.4 3.2 2.8 2.7 2.6 2.6 2.3 1.4 0.2 –0.6

3.0 2.7 2.4 2.2 2.1 2.0 1.6 0.9 –0.2 –0.8 –1.3

2.9 2.6 2.3 2.2 2.0 2.0 1.6 1.0 0.2 –0.3 –0.4 0.0

3.0 2.8 2.5 2.4 2.3 2.2 2.0 1.5 0.9 0.7 0.8 1.5 3.0

3.3 3.1 2.8 2.8 2.7 2.7 2.6 2.2 1.8 1.8 2.1 2.9 4.4 5.9

3.6 3.4 3.2 3.1 3.1 3.2 3.1 2.8 2.5 2.6 3.0 3.8 5.2 6.5 7.4

3.8 3.7 3.5 3.5 3.5 3.5 3.5 3.3 3.1 3.2 3.6 4.5 5.7 6.8 7.5 7.7

4.0 3.9 3.7 3.8 3.8 3.9 3.8 3.7 3.5 3.7 4.2 5.0 6.1 7.0 7.7 7.8 7.9

Sources: Real Estate Center at Texas A&M University and FHFA Home Price Index

T

Using IRR as a Benchmark

he IRR provides a direct numerical comparison between renting and investing the difference in a stock portfolio and purchasing a home. According to Property Metrics, the IRR “is the percentage rate earned on each dollar invested for each period it is invested.” While the two options share the same initial investment, that value should differ by the end of the chosen holding period, producing different IRRs. A household’s decision to rent and invest the difference in the stock market or purchase a home is displayed in the investment values and IRR at the end of each holding period. Holding periods range from a minimum of two years to a maximum of 18 (for a household that invests as early as the beginning of 2000 and sells as late as the end of 2017). This results in a total of 153 holding periods to be analyzed.

This analysis excludes all expenses accrued from opening and selling a stock portfolio while renting or from buying, holding,

12

and selling a home. Assuming all other factors are fixed, this scenario offers a simple, straightforward comparison between the two options.

Ups and downs in the stock market and Texas housing market have not coincided since 2000 (see table). In fact, dramatic differences in magnitude of change and timing have often resulted in a large variation in the two investments’ rates of return. Consequently, the variation has also affected the winning investment decision for any given holding period.

For this analysis, the S&P 500 represents the performance of the stock market. History shows the stock market is generally more volatile than the housing market. The annual returns for the S&P 500, which include dividends, ranged from –36.6 percent in 2008 to +32.1 percent in 2013. In comparison, the annual return from homeownership for Texas ranged from –1.4 percent in 2011 to +8.2 percent in 2017.

Annual Return from S&P 500 vs Annual Home Price Appreciation for Texas Year

S&P 500 (percent)

Texas (percent)

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

–9.0 –11.8 –22.0 28.4 10.7 4.8 15.6 5.5 –36.6 25.9 14.8 2.1 15.9 32.1 13.5 1.4 11.8 22.0

6.1 6.7 3.5 3.1 2.7 4.4 5.6 5.1 1.9 0.1 –1.3 –1.4 1.5 4.5 7.3 7.6 7.8 8.2

Sources: Dr. Aswath Damodaran (New York University) and the Federal Housing Finance Agency (FHFA) TIERRA GRANDE

Table 5. Investment Matrix to Purchase or Rent and Invest at Year-End Year of Initial Investment or Purchase (Beg. of Year)

2001

2000

p

2001

Percent 2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

p

p

p

p

p

p

p

p

p

p

p

i

i

i

i

i

p

p

p

p

p

p

p

p

p

p

p

i

i

i

i

i

2002

p

2003 2004 2005 2006

i

i

i

i

p

p

i

i

i

i

i

i

i

i

i

i

i

i

p

i

i

i

i

i

i

i

i

i

i

i

i

p

p

i

i

i

i

i

i

i

i

i

i

p

p

i

i

i

i

i

i

i

i i

i

2007 2008

p

p

i

i

i

i

i

i

i

p

p

p

p

i

i

i

i

i

i

p

p

p

i

i

i

i

i

i

2009

i

2010 2011

i

i

i

i

i

i

i

i

i

i

i

i

i

i

i

2012 2013

i

i

i

i

i

i

i

i

i

i

i

2014 2015 2016

i

i

i

p

i

i

p

i i

Note: A “p” indicates that the IRR from homeownership was greater than from an S&P 500 stock portfolio.

An “i” indicates that the IRR from an S&P 500 stock portfolio was greater than from homeownership.

Source: Real Estate Center at Texas A&M University

Furthermore, the severity of the negative returns was much greater for an investment portfolio than for homeownership (–18.2 percent versus –1.3 percent). On average, the potential loss in initial investment proved higher for renters than for homeowners. The IRR from the stock portfolio varied significantly across holding periods, whereas the IRR from homeownership remained in the low single digits.

Note that the analysis for the stock market portfolio reflects before-tax returns. Capital gains tax is not factored into the returns for the stock market or homeownership.

According to the Tax Policy Center, the average effective tax rate for capital gains ranged from a low of 12.5 percent in 2009 to a high of 19 percent in 2000. This represents a significant portion of the overall value of the stock portfolio and would have a large impact on its after-tax return.

If the analysis for the stock market portfolio had accounted for transaction costs and capital gains taxes, the IRR would have decreased. Depending on the severity of the decline in the IRR, this could have reversed the investment decision (i.e., purchase a home rather than rent and invest in a stock portfolio).

purchasing a home versus investing in the stock market. Potential homeowners should typically expect to remain in a home at least two years before the front-end costs are recouped.

Finally, investing in the stock market at the bottom of a recession and selling within a few years is almost always the superior financial investment. The stock market tends to grow at a much faster rate than home prices coming out of a recession. However, when investing for a longer duration, purchasing a home often proves the winning option. ltimately, a household’s decision to rent and invest in the stock market or purchase a home will be determined by a combination of personal and investment preferences, not just the IRR the household would have received from either option. Households are likely to consider factors such as each market’s historic performance and its current conditions, and the ease and ability of qualifying for homeownership. Other factors include the need for flexibility in living arrangements, the obligations of homeownership, available housing stock, nearby amenities, and the social and community aspects of owning versus renting.

Weighing the Options

Dr. Hunt (hhunt@tamu.edu) is a research economist and Losey a research intern with the Real Estate Center at Texas A&M University.

On average, investing in the stock market offered a greater IRR than purchasing a home for Texas households from 2000 to 2016. However, the introduction of capital gains tax can dramatically affect the investment decision. In most cases under current tax law, avoiding capital gains tax on sale of a home gives homeownership a tremendous edge. The impact of capital gains tax and transaction costs, along with other factors such as the impact of leverage from homeownership and equity increases due to mortgage loan reductions, will be discussed in a future article.

Additionally, high rent growth over the past several years has diminished the financial gain from investing in the stock market. Another important factor is the substantial up-front cost of OCTOBER 2018

U

THE TAKEAWAY Between 2000 and 2016, renting and investing in the stock market generally yielded a higher rate of return than investing in a home. However, households faced with both options are likely to consider other factors such as current stock market conditions, their ability to qualify for a mortgage, housing stock, the obligations of homeownership, and the social and community aspects of owning versus renting.

13

Residential

14

TIERRA GRANDE

ew Real Estate Center research finds apartment markets in Austin, Dallas-Fort Worth, and San Antonio are in the final stages of a recovery that began in the aftermath of the Great Recession (GR) of 2007– 09. Houston’s apartment market is in the early stages of a new cycle that began in early 2017.

OCTOBER 2018

15

14

Figure 1. Apartment Vacancy Rate Cycles, Austin

Percent

12 Projections

10

The study uses time series of vacancy rates and rentgrowth rates for apartment markets in the four metros. The data run from third quarter 2005 to first quarter 2018.

8 6 4 2006

2010 2014 2018 2022 2026 Vacancy rate Filtered vacancy rate Average vacancy rate

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

14

Figure 2. Apartment Vacancy Rate Cycles, Dallas-Fort Worth

Percent

12

Projections

10 8 6 2006

2010 2014 2018 2022 2026 Vacancy rate Filtered vacancy rate Average vacancy rate

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

16

Figure 3. Apartment Vacancy Rate Cycles, Houston

14 Percent

In the absence of a major shock to the U.S. and Texas economies, apartment markets in Austin, DFW, and San Antonio are projected to move toward their long-term, steady-state average growth rates. Meanwhile, Houston’s apartment market is expected to complete a cycle recovering from the oil price collapse of 2014 and Hurricane Harvey in 2017.

Projections

12 10 8 6 2006

2010 2014 2018 2022 2026 Vacancy rate Filtered vacancy rate Average vacancy rate

Figures 1 to 4 present time series of vacancy rates, filtered vacancy rates, average vacancy rates, and projections of vacancy rates for the four metropolitan areas. Figures 5 to 8 show time series of rent-growth rates, filtered rent-growth rates, average rent-growth rates, and projections of rent-growth rates for the areas.

In these figures, the blue lines are actual vacancy or rentgrowth rates, the red lines are filtered rates, and the green lines are average rates. The vacancy and rent-growth rates data are filtered to purge short-run fluctuations and reveal longer-term trends.

Apartment Market Vacancy Cycles ustin’s vacancy rate cycles show a peak of more than 12 percent during the GR followed by a post-GR recovery when the area’s vacancy rate trended downward to a trough of 5.4 percent in third quarter 2012. Absorption exceeded new space deliveries from 2010 to 2012. Since then, the vacancy rate moved upward to 9.8 percent in first quarter 2018 (Figure 1). The projected vacancy rate shows a continued upward trend until the end of 2018, then trends downward, reverting toward its long-term average vacancy rate of 7.9 percent.

DFW’s vacancy rate reached a GR peak of more than 13.3 percent in fourth quarter 2009, followed by a downward trend to a trough of 6.8 percent in first quarter 2016. Absorption exceeded unit deliveries in five of the six years between 2010 and 2015. Vacancy rates trended upward to 9.4 percent in first quarter 2018 (Figure 2). The projected vacancy rate shows a continued upward trend until third quarter 2019, then trends downward and reverts toward its long-term average vacancy rate of 8.9 percent.

Houston experienced a GR peak vacancy rate of 15 percent in fourth quarter 2009 (Figure 3). The metro area’s post-GR recovery reduced the area’s apartment vacancy rate to a trough of 7.7 percent in second quarter 2014. The area’s apartment

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

13

Figure 4. Apartment Vacancy Rate Cycles, San Antonio

12 8

Projections

11 10 9

Percent

Percent

12

Projections

4 0

–4

8 7 2006

16

Figure 5. Apartment Rent-Growth Rate Cycles, Austin

2010 2014 2018 2022 2026 Vacancy rate Filtered vacancy rate Average vacancy rate

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

–8 2006

2010 2014 2018 2022 2026 Rent-growth rate Filtered rent-growth rate Average rent-growth rate

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University TIERRA GRANDE

12

12

0 –4 2007

4 0

–4 2007

Percent

Projections

4 2 0

–2 2007

2011 2015 2019 2023 2026 Rent-growth rate Filtered rent-growth rate Average rent-growth rate

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

12

Figure 9. Apartment Vacancy Rate and Rent-Growth Rate Cycles, Austin

Percent

8 4 0 –4 2007

2010 2013 2016 2018 Vacancy rate Rent-growth rate Natural vacancy rate

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

Figure 10. Apartment Vacancy Rate and RentGrowth Rate Cycles, Dallas-Fort Worth

12 8 4 0

2011 2015 2019 2023 2026 Rent-growth rate Filtered rent-growth rate Average rent-growth rate

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University OCTOBER 2018

Figure 8. Apartment Rent-Growth Rate Cycles, San Antonio

6

Percent

Percent

8

16 Projections

2011 2015 2019 2023 2026 Rent-growth rate Filtered rent-growth rate Average rent-growth rate

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

Figure 6. Apartment Rent-Growth Rate Cycles, Dallas-Fort Worth

8

Projections

4

Rent-Growth Rate Cycles Historical time series of actual apartment rents generally display an upward trend, although not monotonically, due to growing costs of apartment construction and general inflation over time. However, rent-growth rates are subject to mean reversion over time, usually display cyclical patterns tied to short-run local economic conditions or events, and are inversely related to vacancy rates.

The apartment rent-growth rate cycles for Austin showed a trough of -5.2 percent in the GR followed by a V-shaped postGR recovery when the area’s rent-growth rate trended upward to more than 7 percent in third quarter 2011 (Figure 5). The rate remained high until third quarter 2015, trending downward since then to less than 1 percent in fourth quarter 2017. Projections show rent growth trending upward until 2021 and moving around its long-term average growth rate of 3.8 percent.

FW’s apartment rent-growth rate experienced a similar V-shaped recovery following the GR and a continuous upward trend until 2016 (Figure 6). The growth rate peaked at 8 percent in second quarter 2016, then reverted to its long-term growth rate of 3.6 percent. Strong employment and population growth led to projected rent-growth rates along its long-term average growth rate.

Houston’s apartment rent-growth rate cycle, like DFW’s, had a V-shaped recovery in the GR that lasted until 2015 (Figure 7). It was boosted by the price of West Texas intermediate crude, which rose from $39.10 per barrel in February 2009 to $105.70 in June 2014. The metro’s apartment rent-growth rate reached a post-GR peak of more than 8 percent in fourth

Figure 7. Apartment Rent-Growth Rate Cycles, Houston

8 Percent

market suffered during the oil price collapse of 2014–15, leading to a post-GR peak of 12.2 percent in first quarter 2017. This was followed by the beginning of a new cycle in the aftermath of Hurricane Harvey. That cycle is projected to continue well into 2022, eventually reverting to a long-term average of 10.1 percent.

San Antonio’s apartment vacancy cycles are similar to Austin’s (Figure 4). After climbing to more than 12 percent in the GR, San Antonio’s apartment vacancy rate trended downward to a trough of 7.4 percent in third quarter 2012. Absorption exceeded deliveries in both 2010 and 2011. Vacancy then shifted upward to 10.9 percent by first quarter 2018. In the absence of a major shock to the market, the area’s apartment vacancy rate is expected to move toward its long-term average rate of 9.8 percent.

–4 2007

2010 2013 2016 2018 Vacancy rate Rent-growth rate Natural vacancy rate

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

17

15

Figure 11. Apartment Vacancy Rate and RentGrowth Rate Cycles, Houston

Percent

10 5 0 –5 2007

2010 2013 2016 2018 Vacancy rate Rent-growth rate Natural vacancy rate

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

12

Figure 12. Apartment Vacancy Rate and RentGrowth Rate Cycles, San Antonio

Percent

8 4 0 –4 2007

2010 2013 2016 2018 Vacancy rate Rent-growth rate Natural vacancy rate

A negative relationship exists between the vacancy rate and the rent-growth rate in apartment markets. That is, higher (lower) rent-growth rates are associated with lower (higher) vacancy rates as shown in Figures 9 to 12 for the four metros’ filtered rates. An important metric in apartment markets is the vacancy rate associated with a zero rent-growth rate signaling the end of positive rent-growth rates.

The scatter diagrams in Figures 13 to 16 bring together pairs of vacancy and rent-growth rates for the four big Texas metros.

Figure 13 shows a zero rent-growth rate in Austin’s apartment market when vacancy rate is equal to 10.2 percent. Positive

Figure 15. Relation Between Apartment RentGrowth and Vacancy Rates, Houston

Figure 13. Relation Between Apartment Rent-Growth and Vacancy Rates, Austin

8

4

0

–4

A Negative Relationship

Rent-Growth Rate, Percent

Rent-Growth Rate, Percent

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

quarter 2014, then trended downward to negative rates in first quarter 2017 due to falling oil prices. Oil price recovery and Hurricane Harvey helped the metro’s apartment market, generating a new cycle that began in second quarter 2017 and is still going on. The rent-growth rate is projected to trend upward until early 2019, then revert to its long-term average rate of 4 percent. ollowing its V-shaped recovery from the GR, San Antonio’s apartment rent-growth rate exhibited two post-GR peaks, the last one with an annual growth rate of more than 5 percent in second quarter 2015 (Figure 8). The double peak may have been the result of a sudden, significant drop in military employment in 2013 and 2014. Since then, the growth rate has trended downward and is currently lower than the long-term average growth rate of 2.8 percent. The rent-growth rate is projected to trend upward, reverting to around 2.8 percent in 2020.

5

6

7 8 9 10 Vacancy Rate, Percent

11

12

10 8 6 4 2 0 –2

7

4 2 0 –2 –4

6

7

8 9 10 Vacancy Rate, Percent

11

12

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

18

10 11 12 13 Vacancy Rate, Percent

14

15

Figure 16. Relation Between Apartment RentGrowth and Vacancy Rates, San Antonio Rent-Growth Rate, Percent

Rent-Growth Rate, Percent

Figure 14. Relation Between Apartment RentGrowth and Vacancy Rates, Dallas-Fort Worth 6

9

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

8

8

8 6 4 2 0

–2

8

9

10 11 Vacancy Rate, Percent

12

13

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University TIERRA GRANDE

T

he Real Estate Center used time series of vacancy rates in percentages and effective rents measured in dollars per square foot from ALN Apartment Data Ltd. for its study of apartment markets in Austin, DFW, Houston, and San Antonio. Like many other economic and financial indicators, time series of vacancy rates and rents are combinations of four components that drive the series: secular trend, seasonal variation, cyclical, and random components.

The Center used the HodrickPrescott filter, a recognized procedure, to purge short-run fluctuations due to

16

seasonal or random components and discover longer-term trends in data.

The filtered vacancy rates revealed cyclical patterns. Filtered rents displayed generally upward or secular trends due to inflation and growing demand for apartments because of growing population and incomes. As in the case of many other economic time series, the growth rates of rents displayed cyclical patterns.

An important feature of cyclical patterns is mean reversion, which is when growth rates deviate in the short run from their long-term averages but eventually return to averages.

Figure 17. Apartment Vacancy Rate Cycles, Major Texas Metros

The mean-reversion property can be exploited for forecasting the directions of changes in time series.

Cyclical movements of vacancy rates and rent-growth rates are due to imbalances and lead-lag relationships between supply and demand sides of goods and services. All market economies proceed in cycles, where several periods of higher growth rates leading to peaks are followed by several periods of lower growth rates ending in troughs. The Center has a research program for detecting and monitoring the most important business cycles in Texas and its major metros.

Figure 18. Apartment Rent-Growth Rate Cycles, Major Texas Metros

12 8

12 Percent

Percent

14 10 8

4 0

6 4 2007

2010 Austin Houston

2013 2016 2018 Dallas-Fort Worth San Antonio

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

(negative) rent-growth rates are associated with vacancy rates smaller (larger) than 10.2 percent. Zero rent-growth rate vacancy rates for DFW, Houston, and San Antonio are 11.1, 13.5, and 11.8 percent, respectively (Figures 14–16).

Lead-Lag Relationships Among Texas Apartment Markets partment rents in all four metropolitan apartment markets declined in the GR and later had sharp post-GR recoveries, but there were lead-lag relationships among their troughs and peaks expected. Figure 17 brings together the filtered vacancy rates for the four apartment markets and shows that Austin’s apartment market was the first to reach a peak vacancy rate in the GR, followed by San Antonio, DFW, and Houston. Austin, DFW, and San Antonio currently exhibit growing vacancy rates while Houston is in an early stage of decreasing vacancy rates.

Figure 18 brings together the filtered rent-growth rates for the four apartment markets and shows that apartment markets in Austin and San Antonio were the first to have rent-growth OCTOBER 2018

–4 2007

2010 Austin Houston

2013 2016 2018 Dallas-Fort Worth San Antonio

Sources: ALN Apartment Data and Real Estate Center at Texas A&M University

rates decline in the GR followed by DFW and Houston. Austin, DFW, and San Antonio markets are currently experiencing decreasing rent-growth rates while Houston is in an early stage of increasing rent-growth rates.

These lead-lag relationships can be used for forecasting purposes using information from one leading metropolitan apartment market for forecasting vacancy rates and rent-growth rates in another lagging metropolitan market.

Dr. Anari (m-anari@tamu.edu) and Dr. Hunt (hhunt@tamu.edu)are research economists with the Real Estate Center at Texas A&M University.

THE TAKEAWAY New Center research shows apartment markets in Austin, Dallas-Fort Worth, and San Antonio are moving toward their long-term, steady-state average growth rates. Meanwhile, Houston’s market is expected to complete a cycle recovering from the oil price collapse of 2014 and Hurricane Harvey in 2017.

19

Water

Treading Water

F

By Charles E. Gilliland

Few issues have ignited as much passion among property owners as the Waters of the United States rule (WOTUS) adopted by the Environmental Protection Agency (EPA) and Army Corps of Engineers (ACOE) in 2015. Considered by many landowners an unprecedented attempt to control land use, WOTUS represents the latest in a series of face-offs between landowners and agencies crafting rules to implement national environmental policies.

None of this is new. Between 1970 and 1973, responding to emerging environmental challenges, a spate of legislation stitched together a foundation for national environmental policies. The results of those efforts continue to shape land use decisions today.

First, the National Environmental Policy Act (NEPA) focused on land use decisions that involved expenditures of federal funds. It posited a policy obligating federal agencies to prepare environmental impact statements. The act also created the Council for Environmental Quality.

Then, in quick succession, came the Clean Air Act (CAA) in 1970, Clean Water Act (CWA) in 1972, and Endangered Species Act (ESA) in 1973. Along with these measures, Senator Henry Jackson of Washington proposed an ambitious National Land Use Policy Act (NLUPA) to support and coordinate land use planning across the country. NLUPA included provisions for an agency charged to work with states to establish land use plans. Presumably, the agency would have worked to coordinate environmental policy by encouraging states to establish plans in line with objectives of the various environmental policy acts. However, seen as “national land use planning,” NLUPA met furious opposition and never passed. Thus, the CAA, CWA, and ESA became the platform for addressing environmental issues without the NLUPA. Many landowners celebrated the demise of NLUPA.

Response to Regulations Through the intervening decades, the broadly supported acts that did pass have sparked confrontations with property owners as their private land management plans ran afoul of rules and regulations designed to implement the legislation.

In Texas, for example, landowners rebelled when word spread that the U.S. Fish and Wildlife Service planned to declare a broad expanse of the Texas Hill Country a critical habitat for the endangered golden-cheeked warbler under ESA. Tempers blazed, politicians scrambled, and a Fish and Wildlife official even relocated out of state amid concerns about his personal

20

safety. Ultimately, Travis County and the City of Austin developed the Balcones Canyonland Conservation Plan to obtain an incidental take permit for activity that might result in habitat destruction. Developers could participate in that permit by paying a fee. With this path to development, the furor ebbed.

The CWA called for state agencies to develop plans to limit harmful discharges by developing Total Maximum Daily Load (TMDL) plans for impaired rivers and streams. Under the provisions of the act, states developed the plans, then the EPA reviewed and approved or disapproved them. To control runoff of pollutants, plans focused on point source polluters like large industrial plants plus the diffused nonpoint source polluters such as individual farmers fertilizing fields and pastures. The shift to scrutiny of nonpoint source pollution pitted dairies against golf courses and lawns as bureaucrats toiled to meet requirements.

Landowners near the Bosque River seethed at the idea that the plan might prohibit currently available land management practices. In addition, landowners in other watersheds worried that TMDLs on nearby streams could eventually affect them as well. Ultimately, the Texas Commission on Environmental Quality devised a plan, and TMDLs faded as an issue.

Defining Which Waters Require Permits

O

ver time, each environmental measure has sparked confrontations between groups affected by enforcement measures only to fade as landowners adjusted to the outcome. Most recently, the CWA sparked a nationwide outcry among landowners as the EPA and ACOE adopted WOTUS, a rule defining which waters require permits under the act, dramatically expanding its jurisdiction.

That rule followed a Supreme Court judgment known as a “plurality decision” in the 2006 case of Rapanos v. United States. Normally, Supreme Court rulings decide the outcome of a case and specify the rationale for reaching that particular determination in a published opinion. When the majority of justices agree with it, that opinion becomes a legal precedent that lower courts must follow in deciding cases. However, when a majority agrees to a particular outcome but disagrees on the rationale for making that ruling in a 4-1-4 vote, the decision becomes a no-clear-majority decision that bears no clearly accepted role in setting precedents for lower courts. The Rapanos case dealing with Clean Water Act issues resulted in a 4-1-4 plurality decision with the definition of what constitutes waters of the United States under the act.

TIERRA GRANDE

As with many issues before the Court, the liberal wing (Bryer, Ginsburg, Souter, and Stevens) voted to affirm lower court rulings based on a broad interpretation of waters subject to the CWA. They would have held Rapanos liable for violating the CWA. However, the conservative wing (Roberts, Alito, Scalia, and Thomas) voted to vacate lower court rulings. Justice Scalia penned an opinion for the four relying on a restrictive definition of jurisdictional waters. ounding out the judgment, Justice Kennedy voted with the conservative justices to vacate the lower court decision but not because he agreed with Justice Scalia’s opinion. Instead, Kennedy argued for a much more expansive definition of jurisdictional waters that would greatly expand the reach of the CWA. Waters adjacent to traditionally navigable waters also should come under jurisdiction, he asserted, if they had a “significant nexus” to the traditional navigable waters such that their condition could adversely affect those waters.

However, he noted that none of the courts had applied a test to see if the wetlands in question met this criterion. While disagreeing with the reasoning in the plurality opinion, he voted to vacate the lower court decision.

For a discussion of the Rapanos case and its subsequent role in defining jurisdictional waters, read “Navigating Watershed Changes” by Judon Fambrough and Dan Hatfield at recenter. tamu.edu. As that article explains, the far-reaching rules envisioned by EPA and ACOE developed in the years following the Rapanos decision, informed by the knowledge that Justice Kennedy appeared to be prepared to vote with the liberal Justices given the right circumstances. The new rule envisioned expansion of jurisdictional waters to cover land previously deemed beyond the control of CWA. That rule implied that many landowners would need a permit before undertaking activities that might affect the newly defined WOTUS. he potential expansion of land use control sparked outrage among landowners across the nation, inciting fierce, vocal opposition. Several lawsuits challenged the rule resulting in the Federal Sixth Circuit Court issuing an injunction against implementation in 2015. Therefore, the EPA adopted the expanded rule in spring 2015, and it took effect

R

August 28, 2015. However, the Sixth Circuit blocked implementation with a nationwide stay in October 2015. The EPA under President Trump began to rewrite the rule in early 2017.

The new rule sought to reinstate the definition of jurisdictional waters used before 2015.

As 2018 began, matters stood in this state of limbo with the approved rule becoming effective but implementation blocked by the injunction prohibiting enforcement. Landowners breathed a sigh of relief while environmentalists chafed at the delay. Then, on January 22, in the National Association of Manufacturers v Department of Defense Et. Al., the Supreme Court unanimously overturned the Sixth Circuit’s injunction, deciding that the matter belonged at the Federal District court level. The Sixth Circuit dissolved the stay and sent the matter back to the district courts.

This meant that the rule, in effect since 2015, could immediately apply across the country.

However, some federal judicial districts ordered stays in the states under their jurisdiction. So the rule remained blocked in those states.

Further, in November 2017, the EPA and the ACOA proposed to delay the effective date of the rule until 2020. That action prompted several states to sue to compel immediate enforcement of the 2015 rule.

Undeterred, the EPA and ACOA presented a draft of the new WOTUS replacement to the White House on June 15, 2018.

Meanwhile, Justice Kennedy has retired.

To keep up with the latest news on WOTUS go to: https:// www.americanbar.org/groups/environment_energy_resources/ resources/wotus/wotus-rule.html.

Waters of the United States (WOTUS) represents the latest in a series of faceoffs between landowners and agencies crafting rules to implement national environmental policies.

T

OCTOBER 2018

Dr. Gilliland (c-gilliland@tamu.edu) is a research economist with the Real Estate Center at Texas A&M University.

THE TAKEAWAY Since taking effect in 2015, the controversial Waters of the United States rule has hit a number of legal snags. The rule is currently blocked in some states, and a replacement rule has been submitted to the White House for review, a process that could take several months.

21

Residential

Highs & Lows of Floodplain

By Luis B. Torres, Clare Losey, & Wesley Miller

H

Houston, the nation’s fourth-largest city and home to a burgeoning oil and gas sector, has weathered three major flooding events over the past three years: the Memorial Day Flood of 2015, the Tax Day Flood of 2016, and Hurricane Harvey in 2017. Concerns over the capacity of the city’s infrastructure to sustain severe flooding have mounted as thousands of households have faced massive rebuilding efforts in the wake of the natural disasters. A total of around 200,000 owner-occupied households in Harris County have registered for Federal Emergency Management Agency (FEMA) assistance because of these events, disrupting both the housing market and the broader economy.

As a result of the flood events, the city and Harris County have revised construction requirements. While revisions to the city’s floodplain ordinance promise to reduce residential damage from flooding events, they may negatively impact housing affordability by lengthening the time and increasing the cost of new-home construction. This will raise the price of new homes within the floodplains. However, the ordinance could mitigate housing damage and loss from flooding, thereby reducing the shock on home prices in the wake of flooding.

Floodplain Ordinance Revisions Houston’s city council approved revisions to its floodplain ordinance in April 2018. The revisions, which were implemented September 1, 2018, will require new homes constructed in the

22

500-year floodplain to meet a minimum elevation at the 500year floodplain plus two feet. Previously, the ordinance applied only to the 100-year floodplain and required a minimum elevation at the 100-year floodplain plus one foot. According to attorney Omar Izfar and professional engineer James Jones, “the revisions [to the floodplain ordinance] add an additional 51,200 acres (13 percent of the overall city limits) to the area regulated by floodplain ordinance.”

The revisions apply primarily to new-home construction, but they also affect the owners of existing homes who build an addition or improve the home’s structure at a cost of more than 50 percent of the value of the existing improvements. Other owners of existing homes are not required to elevate their property, but they may be subject to increased home insurance cost or they may lose access to flood insurance. The revisions apply only to the incorporated areas of the City of Houston, but outlying areas may adopt the revisions in the future.

Natural Disasters and Housing Affordability The impact of natural disasters on housing affordability greatly depends on the health of the region’s economy and housing market. FEMA reported a total of $1.04 billion in residential damage from Hurricane Harvey in Harris County and approved 87,316 owner-occupied households in the county for assistance, representing approximately 10 percent of all owner-occupied households. Homeowners whose TIERRA GRANDE

Regulations

Figure 1. City of Houston Residential Activity 2,500

Number of Sales

Number of Leases

2,000 1,500 1,000 500 0 2011 2012 2013 2014 2015 2016 2017 2018 Note: Seasonally adjusted. The number of sales and leases reflects single-family, townhome, and condo units.

Source: Real Estate Center at Texas A&M University

households as the hurricane disparately damaged lower-income regions in the city (for more on this, read “Imperfect Storm” at recenter.tamu.edu).

In the long run, demand shock for housing units will taper as households with damaged homes relocate to permanent housing.

As the rebuilding process progresses, Houston’s housing stock will return to levels observed prior to Harvey. Housing affordability should improve but may not reach its pre-Harvey status as new construction or remodeling raises the price of a home.

Most Impacted Areas The highest proportion of housing damage occurred northeast of downtown in economically disadvantaged neighborhoods.

These areas consist primarily of older, smaller, and lowerpriced existing homes, suggesting new building regulations may have more impact on the most vulnerable areas (Table 1). Residents in these regions may face increasing difficulty in properties were left uninhabitable faced several options:

Table 1. Most Damaged Houston ZIP Codes, Housing Characteristics

ZIP Code

Proportional Damage (Percent)

Median Year Built

Median Square Footage

Monthly Sales

Median Price (Dollars)

77078 77028 77037 77026 77044 77587 77016 77033 77013 77039 77089 77032 77050 77079 Houston

72 70 50 49 48 46 42 41 40 40 38 38 37 34 18

1968 1950 1962 1945 2011 1961 1964 1954 1964 1971 1976 1981 1972 1971 2000

1,371 1,362 1,404 1,159 2,220 1,701 1,346 1,304 1,459 1,519 1,906 1,506 2,408 2,679 2,168

5 4 4 5 55 3 8 11 3 7 40 3 1 37 6,255

78,200 55,000 136,250 65,000 197,470 111,000 112,500 109,250 100,500 112,500 179,250 84,000 140,000 340,000 225,000

• seek temporary housing and rebuild the home, • sell the home and purchase a different home or rent a housing unit in Houston, or • sell the home and leave Houston.

The first and second option would accelerate the demand for housing units in the region. n the short run, the supply of undamaged housing units declined after Hurricane Harvey. Meanwhile, the demand for units increased as households that sustained property damage sought temporary housing.

New residential leases spiked in Houston in September 2017, more than doubling those of the prior year, indicating strong household demand for temporary housing (Figure 1). The shock pushed the median rent of new residential leases up nearly 10 percent year over year in September 2017. Rising rents contributed to the disproportionate impact of Harvey on lowerincome households.

Following Harvey, two opposing forces—an increase in demand for housing units and a decrease in supply of undamaged housing units—reduced housing affordability in Houston. Harvey particularly limited the supply of homes affordable to lower-income

I

OCTOBER 2018

Note: Proportional damages represent the number of valid disaster assistance applications for housing divided by the number of total housing units. Median year built, median square footage, monthly sales, and median price are estimated with data up to March 2018. The Houston series is aggregated from individual ZIP codes that are listed as part of the City of Houston on the city’s webpage.

Sources: Federal Emergency Management Agency, Real Estate Center at Texas A&M University, and the U.S. Census Bureau

23

financing housing modifications, such as elevating homes to comply with proposed building codes. Additionally, rapid home price appreciation heightens financial burdens for these residents as rising property taxes further strain disposable income levels.

The demographic characteristics of the ZIP codes with the highest proportion of housing damage indicate residents are of lower income and a higher percentage live below the poverty level (Table 2). These neighborhoods contain a higher proportion of minorities than the city; residents are also generally less educated. Exceptions to these demographic trends are in the 77044, 77089, 77050, and 77079 ZIP codes.

Floodplain Ordinance and Housing Affordability

F

loodplain ordinance revisions may reduce Houston’s housing affordability by increasing the cost of new residential construction. However, by mitigating adverse structural damage from natural disasters, the revisions should prevent a negative shock to the supply of undamaged homes following flooding. This will reduce the effects of flooding on housing affordability.

The cost of elevating a new home varies depending on the size of the home and the type of foundation. According to Metrostudy, elevating a slab by one foot adds approximately $35,000 to the construction cost (this includes decking and railing). Each additional foot of elevation increases the cost of the slab by $10,000. Therefore, the cost of elevating a new home by two feet is $45,000; by three feet, $55,000, and so forth. The cost of elevation decreases (increases) as the size of the home decreases (increases).

For existing homes, the cost of elevation is actually higher due to the greater intensity and difficulty of labor involved.

According to the architectural firm Arkitektura Development, elevating an existing home costs an estimated $75 per square foot. The median size of an existing, single-family, for-sale residence in Houston was 2,168 square feet as of March 2018.

The cost of elevating a home this size is $162,600.

The cost of elevating a home will significantly impact housing affordability for lower-income households. Each incremental increase in the cost of elevating a home reduces the already constrained supply of homes that are affordable to lowerincome households. As a result, the price of homes, particularly lower-priced homes, will increase.

Quantifying the Effect of Floodplain Revisions on Housing Affordability The Real Estate Center calculated the effect of the revisions on Houston housing affordability. The analysis computes the percentage of homes that are affordable to each income distribution based on different costs of elevation. It assumes that the purchase price of a new home increases in proportion to the cost of elevating the home (i.e., the homebuilder passes all costs of elevating the home onto the buyer). The analysis calculates the affordability impact on both new and existing homes in $10,000 intervals.

The home price that is affordable to each income distribution figure was calculated from a price-to-income multiplier derived from the Home Mortgage Disclosure Act (HMDA)

For existing homes, the cost of elevation is actually higher due to the greater intensity and difficulty of labor involved.

Table 2. Most Damaged Houston ZIP Codes, Demographic Characteristics

ZIP Code

Population

Median Income

Percent Below Poverty Level

Percent High School Graduate or Higher

Percent Foreign Born

Asian

Black

Hispanic White

Other

(Percent)

Median Age

77078

16,323

32,040

28

71

15

0

62

34

4

0

31

77028

14,457

29,272

27

71

10

0

70

27

1

2

40

77037

19,856

39,513

29

42

44

0

2

91

7

0

32

77026

23,030

25,354

38

63

18

0

55

43

2

0

36

77044

40,389

71,788

13

82

17

2

26

45

26

1

30

77587

16,862

41,840

25

55

39

0

2

89

9

0

29

77016

27,799

31,949

25

75

11

0

71

28

1

0

39

77033

28,190

31,037

31

70

13

0

69

28

1

2

35

77013

20,743

37,987

26

57

34

1

21

71

7

0

30

77039

28,644

36,021

34

49

36

1

7

87

5

0

27

77089

52,207

64,766

11

82

26

13

17

46

23

1

35

77032

13,475

26,061

43

61

23

1

42

45

11

1

25

77050

4,780

52,963

18

66

23

0

42

54

4

0

34

77079

33,229

101,743

8

94

24

9

8

17

63

3

40

Houston

2,240,582

47,010

22

77

29

7

22

44

25

2

33

Note: Proportional damages represent the number of valid disaster assistance applications for housing divided by the number of total housing units. The demographic information is from the 2016 American Community Survey. The Houston series is aggregated from individual ZIP codes that are listed as part of the City of Houston on the city’s webpage.

Sources: Real Estate Center at Texas A&M University and the U.S. Census Bureau

24

TIERRA GRANDE

Figure 2. Houston Housing Affordability by Income Cohort, 2016 New Homes Only

30

60 Percent of Affordable Homes

25

Percent of Affordable Homes

New and Existing Homes

70

50

20

40

15

30

10

20

5 0

10 40

45

50 55 60 65 70 75 80 85 90 95 100 Median Family Income (Thousands of Dollars) No regulations $15,000 in regulations $35,000 in regulations

0

40

45

50 55 60 65 70 75 80 85 90 Median Family Income (Thousands of Dollars)

95 100

$5,000 in regulations $25,000 in regulations $45,000 in regulations

Notes: This graph computes the percent of homes that are affordable to each income distribution based on varying costs of regulations. The home price affordable to each income distribution was calculated from a price-to-income multiplier derived from 2016 data from the Home Mortgage Disclosure Act and U.S. Census Bureau. Based on 2016 Real Estate Center sales price data for both new and existing homes, the percent of homes affordable to each income distribution was computed. While owners of existing homes are not required to elevate their home, using the pool of new and existing homes provides a more representative share of the market. As the cost of regulations increases, the percent of homes affordable to each income distribution decreases. The data reflect only those homes sold through the Multiple Listing Service, which may under-represent lower-priced homes.

Sources: Home Mortgage Disclosure Act, American Community Survey, U.S. Census Bureau, and the Real Estate Center at Texas A&M University

2016 data, U.S. Census Bureau, and the Center (2017 data from HMDA and the Census Bureau have not been released). The analysis calculates affordability for two measures of housing supply: new single-family homes for sale and both new and existing single-family homes for sale. Because the revisions apply primarily to new single-family homes, it is important to isolate the effect of the revisions on new-home affordability.

However, as the supply of new homes represents a small portion of the total stock, using the pool of both new and existing homes provides a more representative share of the market.

Furthermore, the rising price of new homes in response to the cost of elevating a home may induce upward pressure on the price of existing homes. n 2016, a family with a $50,000 income could afford a $170,207 home. Barring any regulations, only 4.5 percent of new single-family homes for sale in Houston were affordable at this income level. As the cost from regulations increases, that percentage drops (Figure 2). If the cost of elevating a new home in Houston averaged $25,000, 1.5 percent of new single-family homes would be affordable to households that earned $50,000.

However, because not every new home lies in a floodplain, this percentage underestimates the stock of new homes affordable to these households. A mere 0.8 percent would be affordable to those households if the cost of elevating a home averaged $45,000.

Housing affordability improves when accounting for existing single-family homes for sale (Figure 2). Without any regulations, 27.0 percent of new and existing single-family homes for sale in Houston would be affordable to households earning $50,000 in 2016. If the cost of elevating the home averaged $25,000 across the city, 20.5 percent would be affordable to these households.

The proportion of affordable homes would decline to 15.4 percent if the cost of elevating a home averaged $45,000.

In some ZIP codes, the cost of elevating a home may actually exceed the median home price. For example, the median

I

OCTOBER 2018

home price for the ZIP code with the highest proportion of home damage (77078) is $78,200 (Table 1). The median square footage of a home in this area is 1,371 square feet, and the cost of elevating a home this size by one foot is $102,825. Thus, the cost of elevating a home outweighs the median price by nearly $25,000. Based on the median household income and age of homes in this ZIP code, elevating the home is economically unfeasible. An additional financial headwind would be the cost of temporary living while the new home is under construction or being elevated. he revisions to the floodplain ordinance will increase the cost of new-home construction, which will likely erode housing affordability. Housing affordability for lower-income households, which experienced more housing damage, will be disproportionally impacted. However, the long-term benefits (e.g., lives and private property saved) of alleviating the physical vulnerability of homes to flooding may outweigh the increased construction costs although most research has found that the costs of regulation outweigh the benefits by a substantial margin. It will take time to see how homebuilders and buyers respond to the new regulations.

T

Dr. Torres (ltorres@mays.tamu.edu) is a research economist, Losey a research intern, and Miller (wamiller@tamu.edu) a research associate with the Real Estate Center at Texas A&M University.

THE TAKEAWAY Houston’s revisions to its floodplain ordinance could diminish housing affordability in the short term by increasing construction costs and, therefore, home prices.

In the long run, the benefits incurred from mitigating flood damage may outweigh the increased construction costs.

25

Market Profile

Despite the setback late last year, Victoria finished 2017 strong with 816 home sales. The market had 802 sales in 2016, and the annual average number of sales since the start of the decade has been 773. Like other Texas coastal metros, Victoria began 2017 with positive first quarter and second quarter year-over-year sales before slumping in the third quarter and rebounding in the fourth. The city had a third quarter yearover-year sales drop of 9.4 percent and a fourth quarter spike of 10.8 percent.

Even before the storm, Victoria was already at the end of a real estate cycle that began toward the beginning of the decade.

Hurricane Harvey added additional short-term distortions that have created conflicting market indicators. Ultimately, before the housing market can substantially improve, the city’s economy needs a kickstart.

Don’t Let Prices Confuse You Sales volume and prices alone suggest the housing market may be gaining ground. Overall prices had been in decline since 2015 when the year-end median price was $174,900. By the end of 2017, median price reached $165,000; the previous year it was $169,900. But the year-to-date median price as of second quarter 2018 reached $171,500. Median price per square foot was $105 in 2015 but fell to $103 and $96 the following two years. Year-to-date median price per square foot as of June 2018 was $101.

26

TIERRA GRANDE

Figure 1. Victoria Active Listings

100

Hurricane Harvey

Hurricane Harvey

Percent Discount

Active Listings

400 350 300 250

97.5 95.0 92.5 90.0

200 2012

2014

2016

2014

2018

Discount rate

Source: Real Estate Center at Texas A&M University

6,000 GDP Millions of Dollars

Months Inventory

Hurricane Harvey

6 4 2

2012

2014

2016

Source: Real Estate Center at Texas A&M University

2016

2018

Close-to-original-list-price ratio

Source: Real Estate Center at Texas A&M University

Figure 2. Victoria Months Inventory

0

Figure 3. Victoria Home Price Discount

2018

The Federal Housing Finance Agency’s home price index, a measure of individual home price appreciation, indicates a similar trend where metro prices rose continually year over year from 2012 through 2015. After that, the index displayed a lot of volatility until Hurricane Harvey. The index finally depressed in the final two quarters of 2017 before climbing back up in 2018.

Because of the storm, it is still too early to tell if home prices have turned around. Major natural disasters often create

Figure 4. Victoria Gross Domestic Product

5,000 4,000 3,000 2,000

2010

2011

2012

2013 2014

2015

2016

Sources: Bureau of Economic Analysis and Haver Analytics

“noise” in a market as homes come on and off the market and get repaired and rebuilt. Conditions gradually return to market levels. This can cause a major shift in the mix of homes available to purchase, which can result in confusing areawide housing metrics. This appears to be happening in Victoria.

One sign of market health is days on market. After bottoming out at a month and a half to sell in 2014, the average market time to sell a home in 2017 was almost three months.

Another sign is active listing count, which had been on the rise since 2014, the year before rig counts in the Eagle Ford Shale dropped dramatically. For the next two years, listing count generally stayed in the mid 200s, lower than the long-term annual average of nearly 300 (Figure 1).

AS OF MAY 2018, 7,428 Victoria County households were approved to receive Federal Emergency Management Agency funds to assist with post-Harvey home repairs (left). Formosa Plastics’ $5 billion expansion of its Jackson County facility (next page) is expected to bring 340 jobs to the region.

OCTOBER 2018

27

Figure 5. Victoria Employment Growth

Percent Employment Growth

6

Post-Harvey Victoria Home Post-Harvey Victoria Home SalesSales

Hurricane Harvey 77

3

87

0

–3 185

–6 2010

2012

2014

2016

59 77

2018

Sales Volume

Sources: Bureau of Labor Statistics, Texas Workforce Commission, and Haver Analytics

Listings peaked the month before Hurricane Harvey at 428 but fell to 259 by June 2018. The sudden swing of listings also occurred in Houston and Beaumont during the same period.

Inventory in Decline

W

≤1 ≤7 ≤ 40 ≤ 86

59

59

77

≤ 139

185

87

ithout as much change in overall sales volSource: Real Estate CenterCenter at Texas at A&M University ume as Houston and Beaumont, Victoria’s Source: Real Estate Texas A&M University housing inventory levels fell. Since September 2017, months inventory has been in double-digit, year-over- as transportation, manufacturing, and construction haven’t year decline and as of June 2018 was 3.6 months (Figure 2). bounced back yet. Other key housing market drivers also Storm effects and volatility in oil markets had a hand in remain down, including household incomes and population reducing housing inventory. According to Federal Emergrowth. gency Management Agency (FEMA) disaster records, almost Alcoa’s Point Comfort plant closure in 2016 was a major 25,000 households—both owners and renters—registered for blow to the region with close to 700 jobs lost, and work still FEMA assistance after Hurricane Harvey. Of those regisneeds to be done to clear storm sediment to restore local ports trants who were homeowners, less than two-thirds claimed to full capacity. to have homeowners insurance, and even fewer had flood There is some good news. Formosa Plastics Corp. recently insurance. Chances are, homes that would have been listed announced a $5 billion expansion of their facility in nearby are still being repaired or waiting to be repaired. Homes that Jackson County that is anticipated to provide about 340 jobs. sold immediately in the two quarters after the storm may At the same time, the Eagle Ford Shale is gradually showing have sold at prices considerably less than what owners were signs of life again, which should help boost port activity. originally asking for. During this period, the close-to-originalSlowly but surely, Victoria and the surrounding region is list-price ratio fell before recovering in second quarter 2018 picking itself back up.

(Figure 3). Until the dust settles, pricing trends may continue Roberson (jroberson@mays.tamu.edu) is a senior data analyst with the Real to be volatile.

Estate Center at Texas A&M University.

Looking Ahead

As more homes are put on the market, prices may drop again since Victoria remains in a down economy. Metrowide gross domestic product (GDP) peaked in 2014 at $5.6 billion at the height of the Eagle Ford oil play, but it has declined every year since (Figure 4). Quarterly employment growth almost returned to positive territory before the storm but stayed negative and fell further after Harvey (Figure 5). Key industries such

28

THE TAKEAWAY Although Victoria is still feeling the effects of Hurricane Harvey, 2017 was a good year for the city in terms of home sales. The local economy is down, but industrial growth and Eagle Ford activity could signal a turnaround.

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